tokenpocket钱包下载app中文版|myb

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tokenpocket钱包下载app中文版|myb

作者： tokenpocket钱包下载app中文版

2024-03-07 20:05:50

MYB转录因子_百度百科

录因子_百度百科网页新闻贴吧知道网盘图片视频地图文库资讯采购百科百度首页登录注册进入词条全站搜索帮助首页秒懂百科特色百科知识专题加入百科百科团队权威合作下载百科APP个人中心收藏查看我的收藏0有用+10MYB转录因子播报讨论上传视频含有MYB结构域的转录因子MYB类转录因子家族是指含有MYB结构域的一类转录因子。MYB结构域是一段约51-52个氨基酸的肽段，包含一系列高度保守的氨基酸残基和间隔序列。中文名MYB转录因子外文名MYB transcription factors [2]MYB TFs类型含有MYB结构域MYB结构域约51-52个氨基酸的肽段分子结构每隔约18个氨基酸规则间隔目录1分子结构2分类3特点及功能4表达调控5进化分子结构播报编辑MYB转录因子的共同特征是具有保守的MYB-DNA结合域，该结构域由1-4个不完整的重复片段（R）组成，每个重复序列编码3个α-螺旋，包含大约50-53个氨基酸残基。在这3个螺旋中，第二和第三个螺旋形成螺旋-转角-螺旋（helix-turn-helix，HTH）结构。MYB转录因子可以通过HTH结构插入到靶DNA的大沟中进行结合，从而调控靶基因的表达。通常每个MYB重复结构域包含3个保守的色氨酸残基，这些残基被18-19个氨基酸隔开形成二级结构。 [1]首先是每隔约18个氨基酸规则间隔的色氨酸残基，它们参与空间结构中疏水核心的形成。有时色氨酸残基会被某个芳香族氨基酸或疏水氡基酸所取代，尤其是在植物R2R3-MYB转录因子中，R3MYB结构域的第一色氨酸经常被亮氨酸、异亮氨酸或苯丙氨酸所取代。其次，在每个保守的色氨酸前后都存在一些高度保守的氨基酸，例如在第一个色氨酸的C-末端通常是一簇酸性氨基酸正是上述这些保守的氨基酸残基使MYB结构域折叠成螺旋-螺旋-转角-螺旋结构。分类播报编辑植物 MYB 转录因子的分类(3张)根据结合结构域所包含的R结构的数目，MYB家族被分为4个亚类：1R-MYB家族、R2R3-MYB家族、3R-MYB家族和4R-MYB家族。其中，1R-MYB家族包含一个MYB结构域，在调控植物转录和维持染色体结构中起重要作用；R2R3-MYB家族基因在MYB结合结构域中包含两个保守的R2和R3重复序列，同时在C末端可变区内包含一个调控结构域（激活或抑制功能）。其成员众多，功能多样，广泛参与细胞分化、次生代谢、环境胁迫以及病虫害的侵袭；3R-MYB家族基因保守结构域由R1、R2和R3组成，多参与细胞分化及细胞周期的调控；4R-MYB亚家族基因的保守结构域由4个R1/R2重复序列组成，目前在植物中发现的该亚家族基因数目还很少。 [1]特点及功能播报编辑1、激素应答。MYB转录因子通过激素信号传导途径来实现其相应的表达，以维持植物正常的生理活动。例如，拟南芥在干旱和高盐条件下，通过调控脱落酸的含量，可以诱导Atmyb2和Atmyb15的表达提高其耐逆性(Abe et al., 2003 ; Agarwal et al., 2006)；玉米在干旱条件下，ZmybC1基因通过ABA信号传导途径实现其正常表达(Paz-Ares et al.1987)。 [3]2、环境应答。实验表明，MYB转录因子在非生物胁迫（如干旱、低温、高盐以及紫外辐射等）条件下，表达会发生特异性变化。这说明它们在这些过程中具有重要的作用，增强了植物适应复杂多变环境的能力。 [3]3、参与植物苯丙烷类次生代谢途径的调节。苯丙烷类代谢是植物主要的3条次生代谢途径之一，它起始于苯丙氨酸，经过几个共同步骤后，分成两个主要分支途径，其中一条分支称为黄酮类代谢途径，主要与植物色素合成相关。R2R3-MYB转录因子作为调节蛋白广泛参与苯丙烷类代谢途径的调控，主要的证据来自对欧芹、玉米、金鱼草和矮牵牛中黄酮类分支途径的生化和遗传学研究。表达调控播报编辑MYB类转录因子表达的调控类型主要包括：1、蛋白质和蛋白质相互作用的调控2、转录酶的调控3、转录因子磷酸化调控4、氧化还原反应的调控5、蛋白质泛素化作用 [3]进化播报编辑1996年，Lipsick首次提出了MYB类转录因子的进化模式(Lipsick, 1996)。他认为大约在10亿年前产生了原始的MYB基序，然后通过自身的复制产生了含有2或3个重复MYB基序的MYB转录因子，而后又由于全基因组的复制而大大扩增了整个MYB转录因子家族。但是这种全基因组的扩增在动物和细菌中却没有得到发展。同时，他还认为R2R3-MYB类转录因子是由于R1R2R3-MYB类转录因子中R1的缺失而形成的。而Jin等人却提出另外一种进化模式，认为R1R2R3-MYB类转录因子是由R2R3-MYB类转录因子通过全基因组的复制而获得R1形成的(Jin et al., 1999)。这两种进化模式截然相反，所以还有待于对其进行深一步的验证。 [3]新手上路成长任务编辑入门编辑规则本人编辑我有疑问内容质疑在线客服官方贴吧意见反馈投诉建议举报不良信息未通过词条申诉投诉侵权信息封禁查询与解封©2024 Baidu 使用百度前必读 | 百科协议 | 隐私政策 | 百度百科合作平台 | 京ICP证030173号京公网安备110000020000

浅谈MYB转录因子家族的那些事~ - 知乎

浅谈MYB转录因子家族的那些事~ - 知乎首发于植物功能基因研究切换模式写文章登录/注册浅谈MYB转录因子家族的那些事~伯远生物已认证账号在先前的推文中有粉丝留言说想看有关MYB转录因子的介绍，于是小远就赶紧搜集了一些资料来和大家一起分享。在写这篇推文之前，小远还疑惑为啥MYB能被称为明星转录因子？这个疑惑在写文章的过程中很快就被解开了，因为MYB不仅功能强大，而且现有的研究成果也非常的多。MYB转录因子家族作为真核生物中的一类十分保守的转录因子家族，参与了多个发育过程，如根毛发育、花粉形成、种子萌发、花茎强度等方面；在植物遭受干旱、紫外线、冷胁迫、高温胁迫、盐胁迫等非生物胁迫时，MYB转录因子也参与其中并对其进行调节；此外，MYB转录因子还与某些经济作物的品质好坏密切（例如鲜花色泽、果实颜色等）相关。由于MYB的研究成果实在太多，在本次的推文中小远只能和大家分享其中的一小部分（MYB转录因子在非生物胁迫中的研究），希望大家通过阅读本文可以对MYB家族有一定的了解。本次推文的主要内容（绿色部分）如下：1.背景介绍1.1 MYB转录因子的发现植物中第一个MYB转录因子是1987年从玉米中克隆到的ZmMYBC1，研究表明，ZmMYBC1主要参与玉米花青素的合成(Paz-Ares et al., 1987)。此后研究人员利用功能基因组学、转录组学和蛋白质组学等现代分子工具在各种植物中发现和筛选出了大量的MYB转录因子，同时，不断深入地研究也揭示了MYB转录因子在植物生长发育过程中各种途径的调控机制，越来越多的证据支持MYB是植物育种与改良的潜力转录因子。1.2 MYB转录因子的结构及分类MYB转录因子因其N端高度保守的MYB结构域而著称。该结构域一般由1～4段串联且不完全重复序列（R）组成。每个重复序列由50~53个保守的氨基酸残基及中间的间隔序列组成，并形成3个螺旋。第3个螺旋蛋白重复序列组成了一个螺旋-转角-螺旋（HTH）结构，该结构具有3个疏水残基，在HTH三维结构中形成疏水核心。每个重复序列的第3个螺旋是与DNA直接接触的识别螺旋，并插入DNA分子的大沟中。根据MYB基因包含的R结构的个数可以将MYB转录因子分为四类（图1）（郭凯等, 2020）：（1）1R（R1/2，R3-MYB）主要参与植物的形态发生、次生代谢、生物钟控制及花和果实的发育等生理过程。（2）2R（R2R3-MYB）是植物MYB家族中数量最多的一类。根据蛋白质DNA结合区保守氨基酸的基序，2R类成员又可以分为28个亚类。这类MYB成员广泛参与植物初生及次生代谢、细胞分化、激素信号传导、生长发育调控、生物及非生物逆境响应等生命过程。（3）3R（R1R2R3-MYB）存在于大多数真核生物基因组中，它们代表了相对保守的一个基因类别，在细胞周期控制方面起到重要的调控作用。（4）4R（R1R2R2R1/2-MYB）是数量最少的一类MYB转录因子，其成员包含4个R1/R2重复。目前对植物中4R-MYB类蛋白质功能研究较少。图1 植物MYB转录因子分类(Dubos et al., 2010)。2. MYB转录因子在非生物胁迫中的功能2.1 干旱胁迫干旱是影响植物生长和作物产量的重要环境胁迫之一，其严重影响植株生长发育，限制了农作物的产量和质量。在干旱条件下，土壤缺水，植物根部无法吸收足够的水分用于正常的生长发育；同时，叶片气孔关闭，外界二氧化碳不能进入植物体内用于碳同化，在造成光合作用降低的同时，植物的光呼吸增加。另外，干旱还严重影响光合作用和呼吸作用过程中正常的电子传递，造成电子泄露，产生大量活性氧。这些活性氧会影响植物细胞正常的生理代谢，造成植物体生长发育过程受阻，直至死亡(Chen et al., 2006)。在干旱胁迫下，MYB转录因子可以通过调控代谢产物黄酮类化合物、蜡质、角质等生物合成基因的表达，调控植物的抗旱性。此外，MYB转录因子还可以通过ABA信号参与气孔运动（图2）。图2 MYB转录因子在植物抗旱中的作用(Wang et al., 2021)。2.1.1 MYB通过调控类黄酮和角质层合成来影响抗旱黄酮类化合物是植物次生代谢的重要组成部分，可以作为抗氧化剂通过清除活性氧来保护植物免受生物和非生物胁迫。研究表明拟南芥的MYB转录因子（MYB12和MYB75/PAP1）是类黄酮生物合成的关键调控因子（图2）。在转基因植物中，MYB12的过表达显著增加了类黄酮的积累，使植物对干旱和氧化胁迫等非生物胁迫的耐受性增强（图3）(Wang et al., 2016)。图3 转基因拟南芥在干旱胁迫下的表型(Wang et al., 2016)。WT：野生型；KO：ATMYB12敲除突变体；#3/#6：ATMYB12过表达植株。角质层是植物最重要的结构之一，它可以减少地上植物器官水分的散失。角质层的主要成分是角质和蜡，它们的生物合成受到MYB转录因子的广泛调控。研究表明，MYB41、MYB30、MYB94、MYB96、MYB16和MYB106等，可以通过调控角质和蜡的生物合成来影响植物对干旱胁迫的响应（图2）。在拟南芥中，MYB96的过表达可以促进表皮蜡质生物合成上调，从而提高拟南芥的耐旱性（图4）(Lee et al., 2014)。图4 通过电镜观察到MYB96过表达植株的叶片表皮蜡晶体增加(Lee et al., 2014)。2.1.2 MYB通过ABA信号参与气孔运动MYB转录因子还可以通过ABA信号参与调控气孔运动来影响植物的耐旱性(Hetherington, 2003)。拟南芥的MYB60是首个被发现参与气孔运动调控的转录因子(Cominelli et al., 2005)。在光照条件下，MYB60可以促进气孔打开，而在黑暗、干燥和ABA（脱落酸）处理下，MYB60则抑制气孔打开。在myb60突变体中光-诱导的气孔开放被抑制，植物水分流失减少，对干旱的耐受性增强。相反的，MYB60过表达植株则表现出对干旱胁迫的超敏反应（图5）(Oh et al., 2011)。MYB124和MYB88在气孔的形成中起着关键作用，它们限制了保卫母细胞的分裂，防止了气孔簇的形成。MYB44、MYB77、MYB15和MYB37通过ABA信号可以促进气孔关闭，提高植物对干旱的耐受性。而MYB20在ABA介导的气孔关闭中起负调控作用，使得植物对干旱表现出更大的敏感性（图2）。图5 MYB60过表达植株在干旱条件下的生长表型及叶片气孔开放程度(Oh et al., 2011)。2.2 盐胁迫土壤中盐分含量过多时，会降低土壤溶液的渗透势，造成植物吸水困难，不但种子不能萌发或延迟萌发，而且正在生长的植物也不能吸水或者吸水困难，形成生理干旱。另外，高浓度的钠离子可以置换细胞膜中的钙离子，降低生物膜的稳定性，细胞内的钾离子及其它有机溶质外渗，进而引起植物细胞内生理代谢紊乱。MYB转录因子的一些成员也有助于植物的耐盐性，它们可以通过调控角质层形成、抗氧化防御、ABA信号的基因、SOS2表达等来增强植物的耐盐性（图6）。图6 MYB转录因子通过调节下游靶基因参与盐胁迫(Wang et al., 2021)。MYB49可以通过调节角质层形成和抗氧化防御来增加植物对盐胁迫的耐受性。MYB20通过直接与PP2Cs（ABA信号传导的主要负调节剂）启动子结合来负调节其表达，从而调控植物在盐胁迫条件下的耐受性。此外，MYB44也可以通过调节PP2Cs参与盐反应。盐诱导的PP2Cs基因如ABI1，ABI2，ATPP2CA，HAB1和HAB2在MYB44过表达的植物中减少，但在myb44突变体中增强。MYB7通过负调控ABI5在种子发芽期间参与盐胁迫反应，MYB7的突变会导致种子在发芽期间盐胁迫敏感。MYB42则是通过调控SOS2的表达来增强植物的耐盐性（图7）(Sun et al., 2020)。另外一些MYB转录因子，如MYB41和MYB15，其过表达可以增强植物在发芽和根系生长方面的耐盐性。而MYB52则负向调控植物的耐盐性，其过表达会导致种子萌发对盐胁迫超敏。图7 MYB42通过调控SOS2的表达来增强植物的耐盐性(Sun et al., 2020)。2.3 高温胁迫温度是影响植物生长发育、产量和质量以及地理分布的关键环境因子。高温造成的热害可以直接影响作物的生长发育及各种代谢活动，尤其是生殖生长时期生殖器官（如花粉）的代谢和发育（图8）(Vu et al., 2019)。此外，高温还可以直接影响植物细胞内多种组分的稳定性以及多种生理生化反应的正常进行。研究表明，高温下光合作用和呼吸作用均受到抑制，随着温度的升高，光合速率的下降要先于呼吸速率，造成植物饥饿死亡。另外，高温还使植物体内活性氧代谢失调，产生大量的活性氧直接破坏细胞结构和生物大分子(El-Kereamy et al., 2012)。图8 高温可以影响种子萌发到开花结果各个阶段不同器官的生长发育(Vu et al., 2019)。在植物响应高温胁迫的过程中，MYB类转录因子同样起到了非常重要的作用。OsMYB55能直接激活谷氨酸代谢相关基因，使过表达株系体内总氨基酸、谷氨酸、脯氨酸和精氨酸的含量提高，这些代谢产物大都能直接或间接提高植物对逆境的耐受性。MYB68在拟南芥对高温的响应过程中起着非常重要的作用，高温条件下，拟南芥根部MYB68的表达量显著增加，同时MYB68基因的突变体植株生长速率显著低于野生型。MYB30可以通过调节钙信号通路参与氧化和热应激反应，缺乏MYB30蛋白的植物在H2O2和热刺激下表现出[Ca2+]cyt的升高。高温还可以使CmMYB012直接与CmFNS、CmCHS、CmDFR、CmANS和CmUFGT的启动子结合并抑制其表达，导致黄酮类物质和花青素的减少，而黄酮和花青素的减少削弱了植物应对高温胁迫的能力(Zhou et al., 2021)。此外，Hao等人还发现McMYB4可以通过调节苯丙烷代谢和激素信号传导，协调苹果的生长和抗性，从而提高苹果的温度适应性（图9）(Hao et al., 2021)。图9 McMYB4在不同温度条件下调节苯丙烷代谢和激素信号通路的工作模型(Hao et al., 2021)。2.4 低温胁迫低温是植物生长过程中遇到的重要的非生物胁迫因子之一，它对植物的生长、发育、产量以及地理分布均有影响。在长期进化的过程中植物形成了复杂而高效的分子调控机制，从而抵御和适应低温胁迫。当植物受到低温胁迫后，低温信号首先由细胞膜感知，然后通过相应的低温信号传递途径将低温信号向下游传递，与相关转录因子（如，MYB等）结合，激活一系列转录调控过程，调控目的基因的表达，从而提高植物的耐冷与耐寒性。在拟南芥中，MYB15受低温诱导上调表达，MYB15蛋白通过与ICE1互作后结合到关键的冷反应转录因子CBFs启动子元件上来调控植株抗冻性，MYB15过表达导致CBFs表达和植株抗冻性降低，而myb15突变体则表现出CBFs表达和植株抗冻性增加，这表明MYB15负调控CBF的表达。而MYB96受到冷胁迫的诱导后，会通过调节CBF的表达来激活植株的抗冻能力。OsMYB3R-2主要通过上调细胞周期蛋白（Cyclin）基因OsCycB1;1和OsDREB1s的表达赋予植株耐冷性，而OsMYBS3则通过抑制OsDREB1B的表达负调控植株耐冷性。过表达OsMYB4基因可以大大提高水稻对低温，干旱和高盐等非生物胁迫的耐受能力。在白桦中过量表达BpMYB4基因同样能够提高白桦的耐低温能力。此外，在低温胁迫下，MdMYB88和MdMYB124可以作用于MdCCA1的上游，通过结合其启动子的AACCG基序直接调控其表达。激活MdCCA1后，可调节MdCBF基因的表达，诱导COR基因的表达并促进花青素的积累，后者有助于冷胁迫下H2O2的清除。MdMYB88和MdMYB124还可以直接调控MdCSP3的表达，MdCSP3则通过CBF独立的途径增强苹果的耐寒性（图10）(Xie et al., 2018)。图10 苹果MdMYB88和MdMYB124在冷胁迫条件下的工作模型(Xie et al., 2018)。2.5 紫外线胁迫Ultraviolet-B (UV-B)（中波紫外线）对植物来说是一种非生物胁迫，会影响植物的生长和适应。并且，它也可以调节植物光形态建成，例如抑制下胚轴伸长，子叶膨胀以及黄酮积累。持续的高强度辐射会导致DNA的损伤、氧化应激、脂质和蛋白质氧化，从而导致生长发育异常。为了应对紫外线胁迫，植物已进化出通过积累防晒类黄酮，包括黄酮醇、花青素和原花青素等，来限制UV-B造成的损害。研究表明，MYB转录因子在植物对UV-B光的应答中具有重要作用。在苦荞中，MYB4R1可以通过与类黄酮、花青素生物合成通路的基因FtCHS、FtFLS以及FtUFGT启动子中的L-box基序结合，调节植物体内类黄酮和花青素的积累来响应UV-B(Liu et al., 2022)。在拟南芥中，MYB4是紫外线防晒物质合成的负调节因子，它可以抑制C4H基因的转录，该基因是紫外线防晒物质合成的关键酶。类似地，MYB7也参与抑制黄酮醇的生物合成。UV-B照射会抑制植物的下胚轴伸长、根生长，并诱导子叶扩张。在这个过程中，UVR8光感受器起着重要作用。MYB73和MYB77与UVR8以依赖UV-B的方式相互作用，并调节侧根生长。此外，UVR8还在UV-B照射下与MYB13相互作用并诱导MYB13靶基因（CHS/CHI/FLS）表达以刺激类黄酮次级代谢和子叶扩展（图11）(Xu et al., 2020)。图11 UV-B信号促进子叶扩张并抑制侧根生长的模式图(Xu et al., 2020)。小远叨叨文章至此就告一段落了！在本次的推文中小远主要是想和大家一起学习有关MYB转录因子家族在植物响应非生物胁迫中的研究成果！希望大家通过阅读本文可以对MYB转录因子有一定的了解，感兴趣的小伙伴还可以检索相关文献获得更多有关MYB转录因子的研究内容哦。大家还有什么想看的推文也欢迎继续在评论区留言哦！References：Cominelli E, Galbiati M, Vavasseur A, et al. 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Overexpression of Arabidopsis MYB96 confers drought resistance in Camelina sativa via cuticular wax accumulation. Plant Cell Rep. 2014, 33(9): 1535-46.Liu M, Sun W, Ma Z, et al. Integrated network analyses identify MYB4R1 neofunctionalization in the UV-B adaptation of Tartary buckwheat. Plant Commun. 2022, 3(6): 100414.Oh JE, Kwon Y, Kim JH, et al. A dual role for MYB60 in stomatal regulation and root growth of Arabidopsis thaliana under drought stress. Plant Mol Biol. 2011,77(1-2): 91-103.Paz-Ares J, Ghosal D, Wienand U, et al. The regulatory c1 locus of Zea mays encodes a protein with homology to myb proto-oncogene products and with structural similarities to transcriptional activators. EMBO J. 1987, 6(12): 3553-8.Sun Y, Zhao J, Li X, et al. E2 conjugases UBC1 and UBC2 regulate MYB42-mediated SOS pathway in response to salt stress in Arabidopsis. New Phytol. 2020, 227(2): 455-472.Vu LD, Xu X, Gevaert K, et al. Developmental Plasticity at High Temperature. Plant Physiol. 2019, 181(2): 399-411.Wang F, Kong W, Wong G, et al. AtMYB12 regulates flavonoids accumulation and abiotic stress tolerance in transgenic Arabidopsis thaliana. Mol Genet Genomics. 2016, 291(4): 1545-59.Wang X, Niu Y, Zheng Y. Multiple Functions of MYB Transcription Factors in Abiotic Stress Responses. Int J Mol Sci. 2021, 22(11): 6125.Xie Y, Chen P, Yan Y, et al. An atypical R2R3 MYB transcription factor increases cold hardiness by CBF-dependent and CBF-independent pathways in apple. New Phytol. 2018, 218(1):201-218.Xu Y, Zhu Z. UV-B Response: When UVR8 Meets MYBs. Trends Plant Sci. 2020, 25(6): 515-517.Zhou LJ, Geng Z, Wang Y, et al. A novel transcription factor CmMYB012 inhibits flavone and anthocyanin biosynthesis in response to high temperatures in chrysanthemum. Hortic Res. 2021, 8(1): 248.郭凯, 侯留迪, 张莹莹等. 植物MYB基因家族研究进展. 长江大学学报(自然科学版). 2020.NO.1伯远生物近期上新、优惠、招聘活动Recent promotions【限时优惠】IP/Co-IP五折啦！【限时折扣】严选爆款买10赠5！【业务上新】谷子遗传转化【业务升级】玉米遗传转化【业务升级】大豆遗传转化【科研绘图】伯远生物业务介绍【招聘简章】2023，给自己一个不一样的选择！NO.2好文推荐Historical articles转录因子IPA1，次次都能发顶刊是怎么做到的？转录因子研究套路（三）转录因子研究套路（二）转录因子研究套路（一）最强大脑炼成记—如何验证一个基因是转录因子如何预测转录因子？NO.3伯远生物可以提供以下技术服务Commercial services表观组学服务蛋白质组学服务载体构建服务二十二大植物遗传转化服务各物种基因编辑全套服务各种分子检测服务蛋白-蛋白、蛋白-核酸相互作用筛选及验证伯远严选试剂商城-伯远严选，为你而选！伯远工程-让你的植物养的更安心！发布于 2023-06-01 10:43・IP 属地湖北酵母转录激活因子与 DNA 分子识别的研究（书籍）赞同 18添加评论分享喜欢收藏申请转载文章被以下专栏收录植物功能基因研究植物基因功能研

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MYB 癌蛋白：人类癌症的新兴参与者和潜在治疗靶点,Oncogenesis - X-MOL

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MYB 癌蛋白：人类癌症的新兴参与者和潜在治疗靶点

Oncogenesis

(

6.2

)

Pub Date : 2021-02-26

, DOI:

10.1038/s41389-021-00309-y

Ylenia Cicirò

Arturo Sala

Affiliation

Department of Life Sciences, Centre for Inflammation Research and Translational Medicine, Brunel University London, UB8 3PH, Uxbridge, UK.

MYB 转录因子从植物到脊椎动物高度保守，表明它们的功能包含细胞和生物体生物学中的基本机制。在人类中，MYB基因家族由三个成员组成：MYB、MYBL1和MYBL2，分别编码转录因子 MYB、MYBL1 和 MYBL2（也称为 c-MYB、A-MYB 和 B-MYB）。MYB 的截短版本，MYB 家族的原型成员，最初被确定为逆转录病毒致癌基因v-myb的产物, 导致鸟类白血病。这导致了脊椎动物 MYB 的异常激活也可能导致癌症的假设。尽管自分离 v-myb 以来已经过去了三十多年，但直到最近，研究人员才能够检测到MYB基因重排和突变，这是MYB家族成员参与人类癌症的确凿证据。在这篇综述中，我们将重点介绍将MYB家族成员的活动与人类恶性肿瘤联系起来的研究，以及为表达MYB的癌症量身定制的实验性治疗干预措施。

"点击查看英文标题和摘要"

MYB oncoproteins: emerging players and potential therapeutic targets in human cancer

MYB transcription factors are highly conserved from plants to vertebrates, indicating that their functions embrace fundamental mechanisms in the biology of cells and organisms. In humans, the MYB gene family is composed of three members: MYB, MYBL1 and MYBL2, encoding the transcription factors MYB, MYBL1, and MYBL2 (also known as c-MYB, A-MYB, and B-MYB), respectively. A truncated version of MYB, the prototype member of the MYB family, was originally identified as the product of the retroviral oncogene v-myb, which causes leukaemia in birds. This led to the hypothesis that aberrant activation of vertebrate MYB could also cause cancer. Despite more than three decades have elapsed since the isolation of v-myb, only recently investigators were able to detect MYB genes rearrangements and mutations, smoking gun evidence of the involvement of MYB family members in human cancer. In this review, we will highlight studies linking the activity of MYB family members to human malignancies and experimental therapeutic interventions tailored for MYB-expressing cancers.

更新日期：2021-02-26

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MYB orchestrates T cell exhaustion and response to checkpoint inhibition | Nature

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MYB orchestrates T cell exhaustion and response to checkpoint inhibition

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Published: 17 August 2022

MYB orchestrates T cell exhaustion and response to checkpoint inhibition

Carlson Tsui

ORCID: orcid.org/0000-0003-0642-814X1 na1, Lorenz Kretschmer

ORCID: orcid.org/0000-0003-0987-84292 na1, Svenja Rapelius2 na1, Sarah S. Gabriel1, David Chisanga

ORCID: orcid.org/0000-0002-0421-39573,4,5,6, Konrad Knöpper

ORCID: orcid.org/0000-0003-2076-21607, Daniel T. Utzschneider

ORCID: orcid.org/0000-0003-2205-90571, Simone Nüssing8,9, Yang Liao

ORCID: orcid.org/0000-0002-9746-28393,4,5,6, Teisha Mason1, Santiago Valle Torres1, Stephen A. Wilcox4, Krystian Kanev10, Sebastian Jarosch

ORCID: orcid.org/0000-0002-2908-85902, Justin Leube2, Stephen L. Nutt

ORCID: orcid.org/0000-0002-0020-66374, Dietmar Zehn

ORCID: orcid.org/0000-0003-1393-852710, Ian A. Parish

ORCID: orcid.org/0000-0003-3528-478X8,9, Wolfgang Kastenmüller

ORCID: orcid.org/0000-0002-3835-14857, Wei Shi3,4,5,11, Veit R. Buchholz

ORCID: orcid.org/0000-0003-0441-39132 na2 & …Axel Kallies

ORCID: orcid.org/0000-0002-6312-69681 na2 Show authors

Nature

volume 609, pages 354–360 (2022)Cite this article

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Gene regulation in immune cellsImmunotherapy

AbstractCD8+ T cells that respond to chronic viral infections or cancer are characterized by the expression of inhibitory receptors such as programmed cell death protein 1 (PD-1) and by the impaired production of cytokines. This state of restrained functionality—which is referred to as T cell exhaustion1,2—is maintained by precursors of exhausted T (TPEX) cells that express the transcription factor T cell factor 1 (TCF1), self-renew and give rise to TCF1− exhausted effector T cells3,4,5,6. Here we show that the long-term proliferative potential, multipotency and repopulation capacity of exhausted T cells during chronic infection are selectively preserved in a small population of transcriptionally distinct CD62L+ TPEX cells. The transcription factor MYB is not only essential for the development of CD62L+ TPEX cells and maintenance of the antiviral CD8+ T cell response, but also induces functional exhaustion and thereby prevents lethal immunopathology. Furthermore, the proliferative burst in response to PD-1 checkpoint inhibition originates exclusively from CD62L+ TPEX cells and depends on MYB. Our findings identify CD62L+ TPEX cells as a stem-like population that is central to the maintenance of long-term antiviral immunity and responsiveness to immunotherapy. Moreover, they show that MYB is a transcriptional orchestrator of two fundamental aspects of exhausted T cell responses: the downregulation of effector function and the long-term preservation of self-renewal capacity.

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Defining ‘T cell exhaustion’

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30 September 2019

Christian U. Blank, W. Nicholas Haining, … Dietmar Zehn

MainT cell exhaustion is an important physiological adaptation to continuous antigen stimulation in chronic infection and cancer, and although it protects against excessive immune-mediated tissue damage, it also contributes to viral or tumour persistence1,2,4,7. TPEX cells have the ability to continuously self-renew and give rise to functionally restrained effector cells, and therefore have an essential role in maintaining chronically antigen-stimulated T cells and their exhausted phenotype3,4,5,8,9. TPEX cells also mediate the response to therapeutic checkpoint inhibition3,5,10,11, which can reinvigorate exhausted CD8+ T cell responses and has revolutionized cancer therapy12. In mice, TPEX cells are defined by the co-expression of PD-1, the transcriptional regulators TCF1 and ID3 and the surface molecules CXCR5 and Ly108. By contrast, exhausted effector T (TEX) cells co-express PD-1 and TIM-3 but lack the expression of TCF1, ID3, CXCR5 and Ly108 (refs. 3,4,5,6,8,9,13). Thus, exhausted CD8+ T cells constitute a dynamic network of phenotypically and functionally distinct populations that ultimately depend on the functionality of TPEX cells. We and others have shown that TPEX and TEX cells are controlled by specific transcriptional and metabolic networks that support their differentiation and maintenance13,14,15,16,17,18. It remains, however, unclear how precisely longevity, self-renewal and responsiveness to checkpoint inhibition are orchestrated within the TPEX cell compartment.CD62L+ TPEX cells have stem-like potentialTo identify factors that promote the self-renewal and multipotency of TPEX cells, we performed single-cell RNA sequencing (scRNA-seq) of TPEX-cell-enriched (PD-1+TIM-3−) CD8+ T cells sorted at 30 days post-infection (dpi) from mice chronically infected with lymphocytic choriomeningitis virus (LCMV) clone-13 (Cl13). Combined analysis of our data and publicly available scRNA-seq datasets11,19 (Fig. 1a and Extended Data Fig. 1a,b) identified two distinct TPEX cell clusters, both marked by high expression of Tcf7 and Id3 (Fig. 1a–c). The smaller of these clusters was characterized by high expression of transcripts that are typically associated with naive or central memory T cells, including Sell (encoding CD62L), Ccr7, S1pr1, Lef1, Satb1 and Bach2 (referred to as CD62L+ TPEX cells; Fig. 1a–c and Supplementary Table 1). By contrast, the larger TPEX cell cluster showed low expression of Sell but was enriched for other TPEX-cell-associated transcripts, including Icos, Xcl1, Cxcl10, Cd28 and Eomes (CD62L− TPEX cells; Fig. 1a–c and Supplementary Table 1). In line with previous findings20,21, we identified two TEX cell clusters, both marked by the expression of Gzmb and lack of Tcf7, but distinguished by the differential expression of Cx3cr1 (Fig. 1a–c and Supplementary Table 1). The two remaining clusters expressed intermediate levels of both TPEX and TEX cell marker genes (cluster 3) or cell-cycle-related genes such as Mki67, Ccnb2 and E2f1 (cluster 4) (Fig. 1a–c and Supplementary Table 1). To examine the heterogeneity of TPEX cells experimentally, we used CD8+ Id3GFP P14 T cells, which express a transgenic T cell receptor (TCR) specific for the LCMV epitope gp33, and GFP under the control of Id3, specific to TPEX cells13. Id3GFP P14 cells were adoptively transferred into naive mice, which were subsequently inoculated with LCMV-Docile, which causes chronic infection (Fig. 1d and Extended Data Fig. 1c–j). Both early TPEX and TEX cells were readily detectable during the acute phase (5–9 dpi) of the immune response (Extended Data Fig. 1d), and about 30% of TPEX cells expressed CD62L, which gradually declined and stabilized at around 10% by three weeks after infection (Fig. 1d and Extended Data Fig. 1d,e). CD62L+ TPEX cells were enriched in the spleen and lymph nodes, but largely absent from the blood, bone marrow and liver (Extended Data Fig. 1f). CD62L+ and CD62L− TPEX cells expressed high levels of PD-1, the activation marker CD44, the exhaustion-associated transcription factor TOX and the co-stimulatory molecule ICOS (Extended Data Fig. 1g,i), indicating that both populations were chronically stimulated, and both expressed low amounts of CD160, 2B4 and TIGIT (Extended Data Fig. 1h,j). Consistent with the notion that TPEX cells are particularly dependent on strong TCR signals13,15, both CD62L+ and CD62L− TPEX cells expressed higher levels of the TCR-induced transcriptional regulator NUR77 than TEX cells (Extended Data Fig. 1k–p). There were no major differences in cytokine production between the two TPEX subsets, but IFNγ+ cells were enriched among CD62L+ TPEX cells (Extended Data Fig. 2a,b). CD62L+ TPEX cells were also found among endogenous gp33-specific and among polyclonal antigen-responsive PD-1+CD8+ T cells in LCMV-Docile-infected mice (Extended Data Fig. 2c–e). Notably, CD62L+ TPEX cells were transcriptionally distinct from both naive and memory T cells derived from acute LCMV infection (Extended Data Fig. 2f,g).Fig. 1: CD62L marks transcriptionally distinct and functionally superior TPEX cells during chronic infection.a–c, Naive wild-type mice were infected with LCMV-Cl13 and TPEX-cell-enriched (PD-1+TIM-3lo) CD8+ T cells were sorted and subjected to scRNA-seq at 30 dpi. The resulting data were combined with publicly available scRNA-seq datasets from mouse exhausted CD8+ T cells11,19 and analysed. a, Uniform manifold approximation and projection (UMAP) plot of 15,743 single exhausted T cells coloured according to cluster classification. b, Normalized gene expression of Tcf7, Sell, Gzmb and Cx3cr1 projected onto the UMAP. c, Heat map showing the expression of all identified cluster signature transcripts. d, Congenically marked naive P14 cells were transferred into recipient mice, which were subsequently infected with LCMV-Docile and analysed at 21 dpi. Flow cytometry plots show the expression of PD-1, Ly108 and CD62L in splenic P14 T cells. e, UMAP plot showing two predicted developmental trajectories generated using Slingshot analysis. Cells are colour-coded on the basis of pseudotime prediction. f–k, Congenically marked naive P14 T cells were transferred into primary recipient (R1) mice, which were then infected with LCMV-Cl13. The indicated subsets of P14 T cells were sorted at 28 dpi and 3 × 103–15 × 103 cells were re-transferred to infection-matched secondary recipient (R2) mice. Splenic P14 T cells of R2 mice were analysed at day 21 after re-transfer. f, Schematic of the experimental set-up. g,h, Flow cytometry plots (g) and cell numbers (h) of recovered progenies at day 21 after re-transfer (gated on CD4−CD19− cells). i–k, Flow cytometry plots (i), numbers (j) and average percentages (k) of recovered CD62L+ TPEX, CD62L− TPEX and TEX cells per spleen in R2 mice. Cells were gated on P14 cells (day 21 after re-transfer). Dots in graphs represent individual mice (h,j); horizontal lines and error bars of bar graphs indicate mean and s.e.m., respectively. Data are representative of at least two independent experiments. P values are from Mann–Whitney tests (h,j); P > 0.05, not significant (NS).Source dataFull size imageSlingshot analysis of our scRNA-seq data revealed a developmental trajectory that began with CD62L+ TPEX cells and progressed into CD62L− TPEX cells, from which it bifurcated into either CX3CR1+ or CX3CR1− TEX cells (Fig. 1e). Similar results were obtained when we sorted P14 TPEX cells based on a Tcf7GFP reporter from LCMV-Cl13-infected mice and performed scRNA-seq followed by RNA velocity analysis (Extended Data Fig. 2h–j). Overall, these data suggest a one-way developmental trajectory that originates from CD62L+ TPEX cells. To test this model experimentally, we sorted CD62L+ TPEX, CD62L− TPEX and TEX P14 cells on day 28 after infection with LCMV-Cl13, separately re-transferred them into congenically marked infection-matched hosts and analysed three weeks later (Fig. 1f–k). Compared with CD62L− TPEX and TEX cells, CD62L+ TPEX cells showed a superior repopulation capacity (Fig. 1g,h) and were able to efficiently self-renew and give rise to both CD62L− TPEX and TEXcells (Fig. 1i–k). These characteristics were maintained even after repetitive adoptive transfers (Extended Data Fig. 3a–f). By contrast, the few CD62L+ TEX cells that were detected in the P14 compartment (around 1–2%) did not expand or generate progeny efficiently (Extended Data Fig. 3g–l). We confirmed the superior developmental properties of CD62L+ TPEX cells using single T cell transfer and fate-mapping via retrogenic colour barcoding22,23,24,25 (Extended Data Fig. 4). Notably, single CD62L+ TPEX cells exhibited self-renewal and multipotent repopulation capacity, akin to single naive T cells (Extended Data Fig. 4a–h). In line with the epigenetic imprint of exhaustion26,27,28, progeny derived from single CD62L+ TPEX cells maintained high levels of PD-1 expression compared to their naive-derived counterparts (Extended Data Fig. 4d,g,i). The CD62L-linked developmental hierarchy uncovered here is unrelated to previously proposed TPEX cell subsets based on differential CD69 expression29 (Extended Data Fig. 5a–j). Together, these results show that CD62L+ TPEX cells represent a transcriptionally distinct population with stem-like developmental capacity that maintains the responses of exhausted CD8+ T cells during chronic infection.MYB governs exhausted T cell function and longevityFunctional annotation of our scRNA-seq data identified Myb, encoding the transcription factor MYB (also called c-Myb), as specifically enriched among CD62L+ TPEX cells (Fig. 2a,b and Supplementary Table 1). MYB has important roles in the self-renewal of haematopoietic stem cells and cancer cells30, T cell leukaemia31 and CD8+ memory T cells32,33. To characterize the dynamics of Myb expression in chronic infection, we infected MybGFP reporter mice34 with LCMV-Docile (Fig. 2c and Extended Data Fig. 5k), and found that the expression of Myb was highest in CD62L+ TPEX cells (Fig. 2c and Extended Data Fig. 5k). Myb expression in CD8+ T cells responding to LCMV-Docile infection was significantly higher than in those responding to LCMV-Armstrong infection (Extended Data Fig. 5l), and was further enhanced by the inhibition of PD-1 signalling in vivo (Extended Data Fig. 5m–o). Moreover, in vitro TCR stimulation induced the expression of Myb in a dose-dependent manner (Extended Data Fig. 5p). Finally, the proportions of CD62L+ antigen-specific CD8+ T cells were 10-fold higher in LCMV-Docile versus LCMV-Armstrong infection (Extended Data Fig. 5q,r). Together, these data indicate that strong and persistent TCR stimulation favours the sustained expression of MYB and retention of CD62L+ TPEX cells during chronic infection.Fig. 2: The transcription factor MYB is required for the generation of CD62L+ TPEX cells and the functional exhaustion of T cells during chronic infection.a, Normalized gene expression of Myb projected onto the UMAP plot. b, Violin plots showing normalized expression of Sell and Myb. c, MybGFP reporter mice were infected with LCMV-Docile and splenic CD8+ T cells were analysed at the indicated time points after infection. Left, representative flow cytometry plots showing the expression of CD62L and Myb–GFP among naive (CD44lo) and gp33+ CD8+ T cells. Right, quantification showing the geometric mean fluorescence intensity (GMFI) of Myb–GFP among CD62L+ TPEX, CD62L− TPEX and TEX cells as fold change over naive CD8+ T cells. d–j, Mybfl/flCd4Cre (Myb-cKO) and littermate Mybfl/fl control (Ctrl) mice were infected with either LCMV-Armstrong (LCMV-Arm) or LCMV-Docile (LCMV-Doc). d, Schematic of the experimental set-up. e–h, Survival curves of Myb-cKO and control mice and box plots showing the frequencies of gp33+CD8+ T cells at the indicated time points after infection with LCMV-Armstrong (e,f) or LCMV-Docile (g,h). i,j, Flow cytometry plots and quantification showing the expression of IFNγ and TNF after gp33 peptide restimulation (i) and the frequencies of CD62L+ TPEX cells (j). Cells were gated on gp33+ cells; 8 dpi. k–n, Mixed bone marrow chimeric mice containing Myb-cKO and Cd4Cre control T cells were infected with LCMV-Docile and analysed at the indicated time points. k, Schematic of the experimental set-up. l–n, Quantifications show the frequencies of gp33+ TPEX cells (l), Ki67+ cells (m) and gp33+ cells (n). Dots represent individual mice; symbols and error bars represent mean and s.e.m., respectively; box plots indicate minimum and maximum values (whiskers), interquartile range (box limits) and median (centre line). Data are representative of all analysed mice (e,g), two (c,f,i,j,l–n) or three independent experiments (h). P values are from two-tailed unpaired t-tests (c,f,h–j) and Mann–Whitney tests (l–n).Source dataFull size imageTo study the role of MYB in CD8+ T cells during viral infection, we infected Mybfl/flCd4Cre mice35 (which lack MYB specifically in T cells) and Mybfl/fl (control) littermates with LCMV-Docile or LCMV-Armstrong (Fig. 2d). Before infection, Mybfl/flCd4Cre mice showed no major abnormalities in the thymic and mature CD8+ T cell compartments (Extended Data Fig. 6). LCMV-Armstrong-infected Mybfl/flCd4Cre mice mounted CD8+ T cell responses that were similar to those of controls, and showed no overt signs of disease (Fig. 2e,f and Extended Data Fig. 7a–d). By contrast, LCMV-Docile-infected Mybfl/flCd4Cre but not control mice exhibited signs of severe immunopathology and most became moribund within 10 dpi (Fig. 2g and Extended Data Fig. 7e–i). Depletion of CD8+ T cells averted these symptoms and protected LCMV-Docile-infected Mybfl/flCd4Cre mice (Extended Data Fig. 7j,k), indicating that MYB-deficient CD8+ T cells mediated the fatal immunopathology in chronic LCMV infection. In line with these findings, splenic gp33+CD8+ T cells accumulated at increased frequencies in Mybfl/flCd4Cre mice at 8 dpi (Fig. 2h). MYB-deficient TPEX and TEX cells expressed significantly higher levels of IFNγ and TNF, whereas TEX cells also expressed more granzyme B and underwent increased proliferation (measured by the expression of Ki67) compared to controls (Fig. 2i and Extended Data Fig. 7l–o), despite the viral titres being similar in both groups of mice (Extended Data Fig. 7p). MYB-deficient gp33+CD8+ T cells showed increased expression of the inhibitory receptors PD-1 and TIM-3 compared to control cells (Extended Data Fig. 7q), which suggests that the increased function and proliferation of effector cells was not due to impaired expression of inhibitory receptors. Notably, CD62L+ TPEX cells were specifically lost in the absence of MYB (Fig. 2j and Extended Data Fig. 7r,s).To longitudinally examine the cell-intrinsic role of MYB in the absence of potentially confounding immune pathology, we generated mixed bone marrow chimeric mice that contained small numbers of Mybfl/flCd4Cre (10–20%) and congenically marked Cd4Cre control CD8+ T cells and infected them with LCMV-Docile (Fig. 2k–n and Extended Data Fig. 8). Consistent with our observations in non-chimeric mice, MYB-deficient antigen-specific CD8+ T cells proliferated more and exhibited increased expression of effector molecules compared to controls (Extended Data Fig. 8a–e). Similarly, the MYB-deficient CD8+ T cell compartment was devoid of CD62L+ TPEX cells (Extended Data Fig. 8f,g). Although MYB-deficient TCF1+ TPEX cells initially developed, they were poorly maintained (Fig. 2l and Extended Data Fig. 8h–j). This observation concurred with a premature termination of cell-cycle activity in MYB-deficient TPEX and TEX cells and a marked contraction of the entire antigen-specific compartment (Fig. 2m,n and Extended Data Fig. 8k–n). Similar results were obtained from adoptively transferred MYB-deficient and control P14 T cells (Extended Data Fig. 9a–g). Thus, MYB mediates the development of CD62L+ TPEX cells and functional exhaustion of CD8+ T cells during the acute phase, sustains long-term proliferative capacity and prevents the attrition of antigen-specific T cells during the chronic phase of infection.MYB orchestrates exhausted T cell transcriptionWe next sorted MYB-deficient and control P14 TPEX cells from LCMV-Docile-infected mice and performed transcriptional profiling by RNA-seq (Extended Data Fig. 10a). The analysis showed that there was a loss of the CD62L+ TPEX cell signature in MYB-deficient compared with control TPEX cells (Extended Data Fig. 10b), confirming that MYB deficiency resulted in the loss of CD62L+ TPEX cells and not merely CD62L expression. We next performed RNA-seq of control and MYB-deficient P14 TEX cells and TPEX cells sorted for differential expression of CD62L (Fig. 3a). The analysis revealed transcriptional divergence between all subsets and identified 584 differentially expressed genes (P < 0.05) between control CD62L+ and CD62L− TPEX cells (Fig. 3b, Extended Data Fig. 10c and Supplementary Table 2). CD62L+ TPEX cells expressed higher levels of transcripts that encode molecules related to lymph node homing (for example, Sell, Ccr7 and S1pr1), and higher levels of the cell-cycle inhibitors Cdkn1b and Cdkn2d and the quiescence factors Klf2 and Klf3, compared with CD62L− TPEX cells. Genes that were upregulated in CD62L− TPEX cells included those that encode positive cell-cycle regulators (E2f1, Cdc6, Skp2, Cdc25a and Kif14), metabolic enzymes (P2rx7, Hk2, Pfkm, Pkm and Gpd2) and nutrient transporters (Slc7a5, Slc19a2 and Slc25a10) (Extended Data Fig. 10c and Supplementary Table 2). A comparison of MYB-deficient and control CD62L− TPEX cells identified 580 differentially expressed genes (Supplementary Table 2), including genes that encode molecules related to T cell exhaustion and TPEX cell identity (Lef1, Eomes, Ctla2a, Irf4, Ikzf2, Nt5e and Cd160), cell-cycle regulation and stem cell renewal (E2f1, Rbl2, Kif14, Cdc25b, Bmp7 and Wnt3) (Fig. 3c). Consistent with the impaired expression of transcripts related to cell migration and lymph node homing (Ccr7, Cxcr5, S1pr1, Itgb1 and Itgb3), MYB-deficient antigen-specific CD8+ T cells were largely excluded from the lymph nodes (Extended Data Fig. 10d,e). We also observed increased expression of Kit—encoding KIT, which is involved in haematopoiesis and T cell activation36,37—in MYB-deficient versus wild-type TPEX cells (Fig. 3c). Indeed, KIT was exclusively expressed in CD62L− TPEX cells and was highly upregulated in MYB-deficient TPEX cells (Fig. 3d and Extended Data Fig. 10f,g). A comparison of MYB-deficient and control TEX cells revealed further significant transcriptional changes (1,532 differentially expressed genes), including the upregulation of transcripts that encode cytotoxic molecules (Gzma, Gzmc and Gzme) or that are related to terminally exhausted TEX cells (Cd7, Cd244a, Cd160, Entpd1, Id2 and Cd101), and the downregulation of transcripts related to CX3CR1+ TEX cells, which have been shown to be more effective in controlling viral burden compared to their CX3CR1− counterparts20,21 (Cx3cr1, Zeb2, Klf2 and S1pr1) (Extended Data Fig. 10h–j and Supplementary Table 2). Flow cytometric analysis revealed a lack of CX3CR1+ cells and an increase in terminally exhausted CD101+ cells among MYB-deficient TEX cells compared to controls (Extended Data Fig. 10k–l). Consistent with accelerated differentiation into terminally differentiated cells, TPEX-cell-related transcripts, including Tcf7, Slamf6, Lef1 and Xcl1, were more strongly downregulated in MYB-deficient than in control TEX cells (Extended Data Fig. 10h,j). Many of the genes that were dysregulated in the absence of MYB, including Tcf7, Kit, Slamf6, Lef1, Klf2, S1pr1, Icos, E2f1, Gzma, Gzmc and Myb itself, contained MYB-binding regions in human T cells38 (Supplementary Table 3), which were conserved and aligned with open chromatin regions in mouse exhausted T cells13 (Fig. 3e,f, Extended Data Fig. 11a–d and Supplementary Table 3). Together, our results show that MYB is a central transcriptional orchestrator of T cell exhaustion that mediates the development of CD62L+ TPEX cells and restrains the terminal differentiation of exhausted T cells.Fig. 3: MYB regulates the expression of genes that are critical for the function and maintenance of exhausted T cells.a–c, Congenically marked Mybfl/flCd4Cre (Myb-cKO) and Cd4Cre (control) P14 T cells were adoptively transferred into naive recipient mice, which were then infected with LCMV-Docile. Splenic P14 subsets were sorted at 7 dpi and processed for bulk RNA-seq. a, Schematic of the experimental set-up. b, Sample dendrogram and three-dimensional scaling plot of all the samples. logFC, log-transformed fold change. c, Volcano plot highlighting genes that are differentially expressed (false discovery rate (FDR) < 0.15) between Myb-cKO TPEX and control CD62L− TPEX cells, with genes of interest annotated. d, Flow cytometry plots and quantification show the frequencies of KIT+ cells among control and Myb-cKO TPEX P14 T cells at day 8 after infection with LCMV-Docile (gated on TPEX cells). e,f, Tracks show MYB chromatin immunoprecipitation followed by sequencing (ChIP–seq) peaks in the TCF7 (e) and KIT (f) gene loci of human Jurkat T cells and assay for transposase-accessible chromatin using sequencing (ATAC-seq) peaks of TPEX and TEX cells in the corresponding mouse gene loci aligned according to sequence conservation. Dots in graph represent individual mice; box plots indicate minimum and maximum values (whiskers), interquartile range (box limits) and median (centre line). Data are representative of two independent experiments (d). P values are from two-tailed unpaired t-tests (d).Source dataFull size imageCD62L+ TPEX cells fuel therapeutic reinvigorationTo test the functional potential of MYB-dependent CD62L+ TPEX cells, we separately transferred CD62L+ and CD62L− TPEX cells as well as TEX cells into either wild-type (Extended Data Fig. 11e–g) or T-cell-deficient Tcra−/− mice (Fig. 4a,b), which were then infected with LCMV-Armstrong. Although all subsets maintained high expression of PD-1 (Extended Data Fig. 11g), progeny that were derived from CD62L+ TPEX cells expanded more efficiently (Fig. 4b and Extended Data Fig. 11f,g), contained more KLRG1+ effector cells and provided significantly enhanced viral control compared to the other exhausted T cell subsets (Fig. 4b). CD62L+ TPEX cells also gave rise to more CX3CR1+ TEX cells (Extended Data Fig. 11h,i), altogether indicating that they have a superior potential to generate functional effector cells as compared to their CD62L− counterparts. We next tested the role of PD-1 and therapeutic PD-1 checkpoint blockade in the generation and function of CD62L+ TPEX cells. To this end, we generated P14 T cells that lack functional Pdcd1 (encoding PD-1) using CRISPR–Cas9 (Extended Data Fig. 12a–f). Similar to previous studies39,40,41, PD-1-deficient P14 T cells exhibited increased clonal expansion in response to LCMV-Docile, as compared with control cells (Extended Data Fig. 12b). Although the frequencies of TPEX and TEX cells were unaffected by the loss of PD-1 (Extended Data Fig. 12c), the frequencies—but not the numbers—of CD62L+ TPEX cells were markedly decreased compared to control P14 T cells (Extended Data Fig. 12d). This was due to a concurrent increase in the proportions and the absolute numbers of KIT+ TPEX cells and TEX cells (Extended Data Fig. 12e,f). These results indicate that PD-1 signalling does not affect the development or maintenance of CD62L+ TPEX cells but limits their differentiation into CD62L− TPEX and TEX cells. In line with this conclusion, the numbers of CD62L+ TPEX cells remained stable during PD-1 checkpoint inhibition, whereas the overall population of antigen-responsive PD-1+CD8+ T cells expanded robustly (Extended Data Fig. 12g–p). To directly test the role of CD62L+ TPEX cells in checkpoint blockade, we performed adoptive transfer experiments in the context of therapeutic PD-1 inhibition (Fig. 4c–e). Re-transferred CD62L+ TPEX cells proliferated strongly in response to PD-1 checkpoint inhibition and generated larger progenies compared with untreated controls, while undergoing concurrent self-renewal (Fig. 4d,e). In stark contrast, both CD62L− TPEX and TEX cells showed no apparent proliferative response (Fig. 4d,e), which indicates that CD62L+ but not CD62L− TPEX cells fuel the generation of effector cells in response to checkpoint blockade. Consistent with this conclusion, MYB-deficient antigen-responsive PD-1+CD8+ T cells, which lack CD62L+ TPEX cells, did not expand in response to PD-1 checkpoint inhibition (Fig. 4f–h). Together, our results reveal that MYB-dependent CD62L+ TPEX cells exclusively fuel the proliferative burst in response to PD-1 checkpoint inhibition and therefore dictate the success of therapeutic checkpoint blockade.Fig. 4: CD62L+ TPEX cells show enhanced potential for effector cell generation and selectively mediate responsiveness to PD-1 checkpoint blocking therapy.a,b, Congenically marked naive P14 T cells were transferred into primary recipient (R1) mice, which were subsequently infected with LCMV-Cl13. Exhausted T cell subsets were sorted at 28 dpi and 1.0 × 104–2.5 × 104 cells or no cells (Nil) were re-transferred into secondary Tcra−/− recipient (R2) mice. Splenic P14 T cells of R2 mice were analysed 8 days after infection with LCMV-Armstrong. a, Schematic of the experimental set-up. b, Numbers of recovered P14 T cells (left), percentages of KLRG1+ (middle) and splenic viral loads (right). PFU, plaque-forming units. c–e, Congenically marked naive P14 T cells were transferred into CD4-depleted R1 mice, which were subsequently infected with LCMV-Cl13. Exhausted T cell subsets were sorted at 28 dpi and re-transferred to infection-matched CD4-depleted (CD4 Δ) R2 mice, treated with anti-PD-L1 antibodies or phosphate-buffered saline (PBS) on days 1, 4, 7, 10 and 13 and analysed at day 14 after re-transfer. c, Schematic of the experimental set-up. d, Representative flow cytometry plots of splenic progeny derived from transferred T cell subsets after treatment with anti-PD-L1, at day 14 after re-transfer (cells were gated on CD4−CD19−PD-1+ cells). Box plots show the relative progeny expansion in anti-PD-L1-treated versus PBS-treated mice (left) and the numbers of CD62L+ TPEX cells among progeny after anti-PD-L1 treatment (right). e, Average subset distribution. f–h, Mixed bone marrow chimeric mice containing congenically marked Myb-cKO and Cd4Cre (control) T cells, infected with LCMV-Docile, were treated with anti-PD-L1 on days 33, 36, 39, 42 and 45 and analysed at 49 dpi. f, Schematic of the experimental set-up. g,h, Representative flow cytometry plots (g) and box plot (h) showing the fold change of frequencies of splenic polyclonal PD1+CD8+ T cells in anti-PD-L1-treated versus PBS-treated mice. Cells were gated on CD8+ cells; 49 dpi. Dots in graphs represent individual mice; box plots indicate minimum and maximum values (whiskers), interquartile range (box limits) and median (centre line); horizontal lines and error bars of bar graphs indicate mean and s.e.m., respectively. Data are representative of at least two independent experiments (b,d–e,g–h). P values are from two-tailed unpaired t-tests (b (middle), h) and Mann–Whitney tests (b (left, right, d).Source dataFull size imageOverall, our data show that the CD8+ T cell response in chronic infection is maintained by a small population of distinct TPEX cells that co-express TCF1, CD62L and the transcription factor MYB. These cells, which we term stem-like exhausted T (TSLEX) cells here, possess superior self-renewal, multipotency and long-term proliferative capacity compared to their TCF1+ but CD62L− descendants. Loss of MYB abrogated the differentiation of TSLEX cells and severely impaired the the persistence of the entire TCF1+ TPEX cell compartment, ultimately resulting in the collapse of the complete CD8+ T cell response. MYB also mediates functional exhaustion during chronic infection by restricting the initial expansion and effector function of antigen-responsive CD8+ effector T cells. As a result, mice that lacked MYB in their T cells succumbed to chronic but not acute viral infection, highlighting that T cell exhaustion is an essential adaptation to chronic infection. Thus, MYB represents a transcriptional checkpoint that instructs the differentiation and function of CD8+ T cells in response to severe or chronic infection. Our data also show that TSLEX cells are exclusively required to mediate the response to PD-1 checkpoint inhibition. These findings not only advance our understanding of the mechanisms of T cell re-invigoration in the context of checkpoint inhibition, but also emphasize the need for new therapeutic strategies that target TSLEX cells to harness the full potential of T cell-mediated immunotherapy. Furthermore, the superior proliferative and developmental potential of TSLEX cells makes them prime targets of adoptive T cell transfer and chimeric antigen receptor (CAR) T cell therapies. Finally, our results show that two central but seemingly unrelated properties of exhausted T cells—limited function and longevity—are intimately linked by a single transcription factor MYB; this is a notable example of evolutionary parsimony, which ensures ongoing T cell immunity during chronic infection while preventing collateral damage to the host.MethodsMice and generation of mixed bone marrow chimeric miceAll mice used in this study were on a C57BL/6J background. Age- and sex-matched mice were used for experiments and allocated to experimental groups without further randomization or blinding. CD45.1 or CD45.2 mice were obtained from the Australian Resources Centre or were purchased from Envigo at 6–8 weeks of age. Id3GFP mice42 expressing the P14 TCR transgene (JAX: Tg(TcrLCMV)327Sdz) were used in some experiments as described13. MybGFP mice and Mybfl/flCd4Cre mice were described previously34. Mybfl/flCd4Cre mice were crossed to include the P14 TCR transgene for some experiments. Littermate Mybfl/fl mice were used as controls. Mixed bone marrow chimeric mice were generated by irradiating CD45.1 host mice (2× 5.5 Gy), before reconstitution with a mix of CD45.1/CD45.2 Cd4Cre bone marrow and CD45.2 Mybfl/flCd4Cre bone marrow. Mice were left to recover for six to eight weeks before further experiments. P14 transgenic Tcf7GFP mice on a CD45.1 background were generated in the laboratory of D.Z. by inserting a GFP expression construct into the Tcf7 gene locus and will be described in detail elsewhere. P14 mice expressing diverse combinations of the congenic markers CD45.1/.2 and Thy1.1/1.2, as well as Tcra−/− mice were bred under specific-pathogen-free conditions at the mouse facility of the Institute for Medical Microbiology, Immunology and Hygiene at the Technical University of Munich. All mice were maintained and used in accordance with the guidelines of the University of Melbourne Animal Ethics Committee or the district government of upper Bavaria (Department 5—Environment, Health and Consumer Protection).Generation of colour-barcoded P14 cellsRetrogenic colour-barcoding was used to heritably label individual P14 cells and their progeny for in vivo single-cell fate-mapping experiments, as previously described24,25. In brief, bone marrow was collected from congenically marked (CD45.1+ or CD90.1+) P14 donor mice and stained with Ly6A/E (Sca-1), anti-mouse CD3 and CD19 antibodies, together with propidium iodide for live or dead discrimination. Haematopoietic stem cells (HSCs) were then sorted as live CD3−CD19−Sca-1+ cells and cultured at 37 °C in cDMEM (DMEM (Life Technologies), supplemented with 10% FCS, 0.025% l-glutamine, 0.1% HEPES, 0.1% gentamycin and 1% penicillin/streptomycin), supplemented with 20 ng ml−1 mouse IL-3, 50 ng ml−1 mouse IL-6 and 50 ng ml−1 mouse SCF, for three to four days in tissue-culture-treated 48-well-plates. Expanded stem cells were then retrovirally transduced with constructs encoding the fluorescent proteins GFP, YFP, BFP, CFP and T-Sapphire by spinoculation. After two days in culture, the transduced HSCs were suspended in fetal calf serum (FCS) and injected intravenously into irradiated C57BL/6 recipient mice (2 × 4.5 Gy, with a resting period of 4 h). After several weeks, colour-barcoded naive (CD8+CD44low) P14 cells were sorted from the peripheral blood of retrogenic mice and transferred into C57BL/6 recipients.Organ preparation and adoptive T cell transferSingle-cell suspensions were obtained by mashing total spleens, lymph nodes or bone marrow through a 70-μm nylon cell strainer (BD). For liver samples, lymphocytes were obtained by density gradient centrifugation. Red blood cells were lysed with a hypotonic ammonium chloride-potassium bicarbonate (ACK) or ammonium chloride-Tris (ACT) buffer. For isolating naive CD8+ or transgenic P14 T cells, the mouse CD8+ T cell enrichment kit (Miltenyi Biotech) was used, or cells were sorted as live CD8+CD44low cells.For primary population transfer experiments, 2,000–10,000 naive P14 T cells were injected into naive congenically marked primary recipients. For adoptive re-transfer experiments, P14 cells were first enriched from the spleens and lymph nodes of primary or secondary recipients by sorting CD45.1+Thy1.1+ cells, followed by staining with anti-mouse CD62L, anti-mouse Ly108 and the eBioscience Fixable Viability Dye eFluor 780 or propidium iodide for live or dead discrimination. The indicated subsets were then sorted according to their expression profile of CD62L and Ly108 (note: the anti-mouse CD62L antibody was titrated to a dilution that precludes functional blocking of the molecule). Unless specified otherwise, equal numbers of cells of each subset were injected, ranging between 3,000 and 40,000 for secondary transfers and between 1,000 and 3,000 for tertiary transfers. In cases in which the numbers of transferred cells differed between experimental groups (Extended Data Fig. 3), a fold expansion factor was calculated by dividing the number of recovered P14 cells by the number of transferred cells. A 10% take rate was assumed for these calculations, based on our measurements in Extended Data Fig. 4f.For primary single-cell transfer experiments, naive P14 cells were isolated from the peripheral blood or spleens of naive retrogenic P14 donor mice by staining with anti-mouse CD8, anti-mouse CD44, anti-mouse CD45.1 and anti-mouse Thy1.1. For secondary single-cell re-transfers, anti-mouse CD45.1, anti-mouse CD62L and anti-mouse Ly108 were used, together with the eBioscience Fixable Viability Dye eFluor 780 or propidium iodide for live or dead discrimination. Single P14 cells were then isolated by successively sorting individual cells according to their unique congenic or retrogenic colour barcode and their CD62L/Ly108 phenotype into a 96-well V-bottom plate containing a pellet of 4 × 105 C57BL/6 splenocytes. The unique congenic and retrogenic colour barcodes of sorted cells enabled the simultaneous transfers of multiple individual cells for fate-mapping. After sorting, the whole content of each well was injected into separate C57BL/6 recipients.Gene deletion by CRISPR –Cas9–sgRNA complex electroporationPdcd1 gene deletion was conducted as reported previously41. In brief, P14 cells were purified using an EasySep mouse CD8+ T cell isolation kit (STEMCELL Technologies) according to the manufacturer’s instructions, after which cells were electroporated (Pulse DN100) with a complex of Alt-R S.p. Cas9 Nuclease (Integrated DNA Technologies) and a previously described Pdcd1-targeting sgRNA (Synthego)41 using the P3 primary cell 4D-Nucleofector X kit S electroporation kit (Lonza) and Lonza 4D-Nucleofector Core Unit (Lonza). Cells were rested in fully supplemented RPMI medium (see above) at 37 °C for 10 min, after which P14 cells were counted, and 5,000 P14 cells were injected intravenously into recipient mice before infection with LCMV.LCMV infections and checkpoint blockadeLCMV-Docile, LCMV-Cl13 and LCMV-Armstrong were propagated and quantified as previously described26. For LCMV-Docile and LCMV-Cl13 infection, frozen stocks were diluted in PBS and 2 × 106 PFU were injected intravenously. For LCMV-Armstrong infection, frozen stocks were diluted in PBS and 2 × 105 PFU were injected intraperitoneally. For infection of Tcra−/− mice, a dosage of 2 × 103 PFU was used. For CD4+ T cell depletion, mice were injected twice intraperitoneally with 200 μg per mouse of anti-CD4 monoclonal antibody (GK1.5, BioXCell) one day before and one day after infection with LCMV-Cl13. For CD8+ T cell depletion, mice were injected intraperitoneally with 100 μg per mouse of anti-CD8 monoclonal antibody (YTS-169, BioXCell) on days 1, 3 and 5 of infection. For PD-1 blockade, monoclonal anti-PD-L1 antibodies (B7-H1, BioXCell) were injected intraperitoneally at 200 μg per mouse at the specified days after infection.In vitro culture of naive CD8+ T cellsCell-culture 48-well or 96-well plates were prepared by coating with anti-CD3 at various concentrations for at least 2 h at 4 °C. Control wells were coated with PBS for the same duration. The wells were washed twice using PBS. Enriched naive CD8+ T cells were seeded in the wells and were cultured in RPMI medium supplemented with 10% FCS, 55 μM β-mercaptoethanol, 2 mM Glutamax, 25 mM HEPES buffer and 100 U ml−1 penicillin and 10 μg ml−1 streptomycin for three days in a humidified incubator at 37 °C with 5% CO2.Surface and intracellular antibody staining of mouse cellsSurface staining was performed for 30 min at 4 °C in PBS supplemented with 2% FCS (FACS buffer) with the following antibodies: CD8a (53-6.7, BD), CD44 (IM7, BD), CD45.1 (A20, BD or Biolegend), CD45.2 (104, BD), CD90.1 (HIS52, Thermo Fisher Scientific) CX3CR1 (SA011F11, Biolegend), PD-1 (RMP1-30 or 29F.1A12, Biolegend), CD62L (MEL-14, Biolegend), TIM-3 (RMT3-23, Biolegend), CD101 (Moushi101, Thermo Fisher Scientific), Ly108 (eBio13G3-18D, BD), CD117 (KIT) (ACK2, Thermo Fisher Scientific), CD244 (2B4) (eBio244F4, Thermo Fisher Scientific), CD160 (eBioCNX46-3, eBioscience), TIGIT (GIGD7, Thermo Fisher Scientific) and KLRG1 (2F1, Biolegend). LCMV-derived Db/gp33-41 tetramers were obtained from the NIH Tetramer Facility; tetramer staining was performed for 30–60 min at 4 °C in FACS buffer. Each cell staining reaction was preceded by a 10-min incubation with purified anti-mouse CD16/32 Ab (FcgRII/III block; 2.4G2) and (fixable) viability dye (Thermo Fisher Scientific). For intracellular cytokine staining, splenocytes were ex vivo restimulated with gp33-41 (gp33) peptide (5 mM) for 5 h in the presence of brefeldin A (Sigma) for the last 4.5 h, fixed and permeabilized using the Cytofix/Cytoperm (BD) or transcription factor staining kit (eBioscience) and stained with anti-IFNγ (XMG1.2, Thermo Fisher Scientific), TNF (MP6-XT22, Thermo Fisher Scientific). Other intracellular staining was performed with the Foxp3 transcription factor staining kit (eBioscience) and the following antibodies: TCF1 (C63D9, Cell Signaling), GZMB (MHGB04, Thermo Fisher Scientific) and Ki67 (FM264G, BD).In vitro activation of T cellsCD8+ T cells were isolated using the CD8+ T cell enrichment kit (Miltenyi Biotech) and, in some instances, CTV labelled. Wild-type cells were stimulated with plate-bound anti-CD3 at the indicated concentration and in fully supplemented tissue-culture medium (RPMI plus 10% FCS, 2 mM Glutamax, 1 mM pyruvate, 55 μM mercaptoethanol, 100 U ml−1 penicillin, 10 μg ml−1 streptomycin) and 100 U ml−1 IL-2.HistologyFor immunofluorescence, spleens were embedded and frozen in OCT, sectioned at 15 μm and mounted on SuperFrostPlus Adhesion glass (Thermo Fisher Scientific). Sections were dehydrated using silica beads, fixed with 4% paraformaldehyde for 10 min and washed with PBS. Samples were blocked using 5% normal goat serum for 2 h before staining. Samples were incubated with antibodies against B220 (RA3-6B2, eBioscience), CD3 (17A2, eBioscience) and F4/80 (BM8, Biolegend) diluted in 5% NGS for 2 h at room temperature in the dark. After staining, samples were washed with PBS at least three times. Samples were then mounted using ProLong Gold Antifade Mountant (Invitrogen) and imaged using an inverted LSM780 microscope (Carl Zeiss) and a plan apochromat 63× NA 1.40 oil-immersion objective (Carl Zeiss). For haematoxylin and eosin (H&E) staining, organs were collected and fixed in 10% formalin. Fixed samples were embedded in paraffin and sectioned at 10 μm, mounted on SuperFrostPlus Adhesion glass and stained using H&E. Mounted samples were imaged using a Nikon SMZ1270 Stereo Microscope. Imaging data were analysed using Fiji (ImageJ) software (NIH).scRNA-seq and analysisRelating to the dataset introduced in Fig. 1: TPEX-cell-enriched CD8+ T cells were sorted as CD8+PD-1+TIM-3low from the spleens of chronically infected mice (LCMV-Cl13) using a FACSAria III (BD Biosciences). Afterwards, the single cells were encapsulated into droplets with the ChromiumTM Controller (10X Genomics) and processed following the manufacturer’s specifications. Bead captured transcripts in all encapsulated cells were uniquely barcoded using a combination of a 16-bp 10X barcode and a 10-bp unique molecular identifier (UMI). The Chromium Single Cell 3’ Library & Gel Bead Kit v2 for the wild-type untreated sample or v3 for wild type treated with 200 µg of anti-PD-L1 antibody (10F.9G2, BioXCell) for 24 h were used to generate cDNA libraries (10X Genomics) following the protocol provided by the manufacturer. Libraries were quantified by QubitTM 3.0 Fluometer (Thermo Fisher Scientific) and quality was checked using 2100 Bioanalyzer with High Sensitivity DNA kit (Agilent). For library sequencing the NovaSeq 6000 platform (S1 Cartridge, Illumina) in 50-bp paired-end mode was used. The sequencing data were demultiplexed using CellRanger software (v.2.0.2) and the reads were aligned to the mouse mm10 reference genome using STAR aligner. Aligned reads were used to quantify the expression level of mouse genes and generate the gene-barcode matrix. Subsequent data analysis was performed using Seurat R package (v.3.2)43. The sequencing data are available at the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo) under the accession number GSE168282 (ref. 19). For further analysis in this study, datasets GSM5135522 and GSM5135523 (ref. 19) were combined with another publicly available scRNA-seq dataset of mouse exhausted CD8+ T cells, accessed from GSE122712 (ref. 11) and analysed using Seurat R package (v.3.2)43. The 2,000 most variable genes were included for the anchoring process and used for downstream analysis to calculate principal components of log-normalized and scaled expression data. On the basis of the principal component analysis (PCA), a UMAP of the identified clusters was visualized. Cluster-specific genes were identified with the FindAllMarker function in Seurat with parameters min.pct = 0.25, logfc.threshold = 0.25. Trajectories were predicted using the Slingshot 1.4.0 package44, using the function slingshot with default settings and starting with the CD62L+ TPEX cell cluster. The functional annotation tool DAVID (LHRI) was used to interrogate gene sets to identify transcription factors of interest. Selected lists of genes were then further explored using enrichment analyses against existing RNA-seq datasets13,20.For the dataset used in Extended Data Fig. 2h–j, TPEX cells were sorted as live CD8+PD1+CD45.1+Tcf7–GFP+ cells from the spleens of chronically infected mice (LCMV-Cl13, 28 dpi) using a MoFlo Astrios cell sorter (Beckman Coulter) and processed using the 10X Genomics technology, according to the manufacturer’s protocol (Chromium Single Cell 3’ GEM v3 kit). Quality control was performed with a High Sensitivity DNA Kit (Agilent 5067-4626) on a Bioanalyzer 2100, as recommended in the protocol. Libraries were quantified with the Qubit dsDNA HS Assay Kit (Life Technologies Q32851). All steps were performed using RPT filter tips (Starlab) and LoBind tubes (Sigma). The library was sequenced with 20,000 reads per cell. Illumina paired-end sequencing was performed with 150 cycles on a Novaseq 6000. Annotation of the sequencing data was performed using CellRanger software (v.5.0.0) against the mouse reference genome GRCm38 (mm10-2020-A). All subsequent analysis was performed using SCANPY (v.1.6)45. After general pre-processing (less than 15% mitochondrial genes, regressing out cell cycle, filtering mitochondrial genes and total counts), the data were count-normalized per cell and logarithmized. RNA velocities were calculated using Velocyto46 and analysed with scVelo47. The sequencing data are available at the NCBI GEO (http://www.ncbi.nlm.nih.gov/geo) under the accession number GSE205608.Bulk RNA extraction, sequencing and analysisRelating to the dataset in Extended Data Fig. 2f,g, the indicated subsets of exhausted P14 cells (CD62L+ TPEX, CD62L− TPEX, TEX) were sorted from the spleen of chronically infected mice (LCMV-Cl13) at 28 dpi. As a comparison, memory P14 cells were sorted from the spleen of LCMV-Armstrong-infected mice at 28 dpi according to the following phenotypes: CD62L+Ly108+ (CD62L+ memory), CD62L−Ly108+ (CD62L− memory) and CD62L−Ly108− (effector). In addition, naive P14 cells were included for the analysis. RNA extraction from sorted P14 T cells was performed using the RNeasy Plus Mini Kit (Qiagen) according to the manufacturer’s instructions. Each sample group consisted of two to three biological replicates. Sequencing was performed on an Illumina Novaseq by Novogene, generating 150-bp paired-end reads. RNA-seq reads were aligned to the mouse reference genome GRCm38/mm10 using STAR (v.2.5.4)48. Read counts per gene locus were obtained with htseq-count (v.0.11.4)49. Statistical analysis was performed in R (v.3.6.3). Genes with total reads lower than 200 across all samples were excluded. Normalization and differential gene expression analysis was performed using DESeq2 (v.1.26.0). Batch effects were identified using sva (v.3.34.0) and subsequently modelled in the DESeq2 design formula. Genes were considered differentially expressed when they achieved anFDR of less than 0.05 and a log2-transformed fold change of greater than 1. The sequencing data are available at the NCBI GEO (http://www.ncbi.nlm.nih.gov/geo) under the accession number GSE205608.Relating to the data in Fig. 3 and Extended Data Fig. 10, RNA extraction from sorted P14 T cells was performed using the RNeasy Plus Mini Kit (Qiagen) according to the manufacturer’s instructions. Each sample group consisted of two experimental replicates. All samples were sequenced on an Illumina NextSeq500 generating 80-bp paired-end reads. RNA-seq reads were aligned to the mouse reference genome GRCm38/mm10 using the Subread aligner (Rsubread v.2.2.6)50. Gene-level read counts were obtained by running featureCounts51, a read count summarization program within the Rsubread package52 and the inbuilt Rsubread annotation that is a modified version of the NCBI RefSeq mouse (mm10) genome annotation build 38.1. Pseudogenes, or genes that did not meet a counts per million reads (CPM) cut-off of 0.5 in at least two libraries were excluded from further analysis. Read counts were converted to log2-CPM, quantile normalized and precision weighted with the voom function of the limma package53,54 after accounting for batch effects. A linear model was fitted to each gene, and the empirical Bayes moderated t-statistic was used to assess differences in expression55,56. Raw P values were adjusted to control the global FDR across all comparisons using the ‘global’ option in the decideTests function in the limma package. Genes were called differentially expressed if they achieved an FDR of 15% or less. Enrichment analysis of Gene Ontology (GO) terms on the differentially expressed genes was performed using the goana function within the limma package57. Pathway enrichment against the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways on the differentially expressed genes was performed using the kegga function also implemented in the limma package. Gene set enrichment analysis was performed using Gene Set Enrichment Analysis (GSEA) software (v.4.0.3)58.ChIP–seq analysisPreviously published raw ChIP–seq data for the MYB transcription factor38 were downloaded from the NCBI GEO with accession number GSE59657. Reads were mapped to the human genome (GRCh38) using the align function in Rsubread (refs. 50,52). Peak calling was performed using Homer (v.4.11)59 with an FDR set to 1 × 10−8. In brief, tags for the aligned libraries were first created using the makeTagsDirectory function within Homer then followed by peak calling using the ‘style’ factor parameter with called peaks annotated to the nearest genes. Overlap between differentially expressed genes from the RNA-seq data (mouse) and ChIP–seq data (human) was performed by first transforming the human genes associated with each annotated peak to their corresponding mouse homologues using information available in the Ensembl database through the biomaRt Bioconductor package60. The two sets of genes were then compared for common genes.Analysis of evolutionary conservationGenomic conservation data for the human and mouse genomes were obtained from UCSC Genome Browser (https://genome.ucsc.edu). Annotated tracks of human ChIP data were manually aligned to annotated tracks of mouse ATAC data using conserved loci of 100 vertebrates against the human genome and conserved loci of 30 mammals against the mouse genome as reference points.Flow cytometryFlow cytometry was performed using a Fortessa or Cytoflex LX (Beckman Coulter) and sort purification was performed on a BD FACSAria Fusion or MoFlo Astrios (Beckman Coulter). All data were analysed using FlowJo 10 (Tree Star). Graphs and statistical analyses were done with Prism 7 (GraphPad Software).StatisticsA paired or unpaired Student’s t-test (two-tailed), Welch’s t-test, Mann–Whitney U test or one-way ANOVA was used to assess significance. Statistical methods to predetermine sample size were not used.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

Most of the sequencing data generated for this study have been deposited in the NCBI GEO database with accession number GSE188526. The sequencing data shown in Extended Data Fig. 2f–j have been deposited with accession number GSE205608. Source data are provided with this paper.

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Download referencesAcknowledgementsWe acknowledge I. Andrä and M. Schiemann for cell sorting, and R. Gloury and I. Hensel for technical help. This work was supported by the National Health and Medical Research Council of Australia (NHMRC) Research Fellowship (to A.K.) and Ideas Grants (APP2004333 to A.K. and C.T.; APP2001719 to I.A.P.); the European Research Council (starting grant 949719 SCIMAP to V.R.B.); the Else Kröner-Fresenius-Stiftung (EKFS 2019_A91 to V.R.B.); the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation; SFB-TRR 338/1 2021–452881907, SFB 1054–210592381 to V.R.B.); and the Deutsche Krebshilfe (DKH 70113918 to V.R.B). A.K. is a Senior Research Fellow of the NHMRC; D.T.U. is a Special Fellow of The Leukemia & Lymphoma Society and is supported by an NHMRC fellowship (1194779). We acknowledge the Melbourne Cytometry Platform for provision of flow cytometry services and the NIH Tetramer Facility for providing tetramers.Author informationAuthor notesThese authors contributed equally: Carlson Tsui, Lorenz Kretschmer, Svenja RapeliusThese authors jointly supervised this work: Veit R. Buchholz, Axel KalliesAuthors and AffiliationsDepartment of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, AustraliaCarlson Tsui, Sarah S. Gabriel, Daniel T. Utzschneider, Teisha Mason, Santiago Valle Torres & Axel KalliesInstitute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich (TUM), Munich, GermanyLorenz Kretschmer, Svenja Rapelius, Sebastian Jarosch, Justin Leube & Veit R. BuchholzOlivia Newton-John Cancer Research Institute, Melbourne, Victoria, AustraliaDavid Chisanga, Yang Liao & Wei ShiThe Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, AustraliaDavid Chisanga, Yang Liao, Stephen A. Wilcox, Stephen L. Nutt & Wei ShiDepartment of Medical Biology, University of Melbourne, Melbourne, Victoria, AustraliaDavid Chisanga, Yang Liao & Wei ShiSchool of Cancer Medicine, La Trobe University, Melbourne, Victoria, AustraliaDavid Chisanga & Yang LiaoWürzburg Institute of Systems Immunology, Max Planck Research Group, Julius-Maximilians-Universität Würzburg, Würzburg, GermanyKonrad Knöpper & Wolfgang KastenmüllerPeter MacCallum Cancer Centre, Melbourne, Victoria, AustraliaSimone Nüssing & Ian A. ParishSir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, AustraliaSimone Nüssing & Ian A. ParishDivision of Animal Physiology and Immunology, School of Life Sciences Weihenstephan, Technical University of Munich (TUM), Freising, GermanyKrystian Kanev & Dietmar ZehnSchool of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, AustraliaWei ShiAuthorsCarlson TsuiView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsC.T., L.K., V.R.B. and A.K. designed the study and wrote the manuscript. C.T., L.K. and S.R. performed core experimental work and data analysis. S.S.G. performed initial key experiments. D.C., K. Knöpper, Y.L., W.S., L.K. and S.J. performed computational analyses. K. Kanev, W.K., D.T.U., S.N., T.M., S.V.T., S.A.W., I.A.P., S.J. and J.L. performed supporting experimental work and data analysis. S.L.N., K. Kanev and D.Z. contributed new reagents or analytic tools.Corresponding authorsCorrespondence to

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Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Extended data figures and tablesExtended Data Fig. 1 Isolation of polyclonal exhausted T cells for scRNA-seq and phenotypic characterization of CD62L+ TPEX cells in chronic infection.(a, b) CD4+ T cell-depleted naive mice were infected with LCMV-Cl13, treated with or without anti-PD-L1, and exhausted PD-1+TIM-3lo T cells were sorted at >day 30 post-infection as described19. (a) Schematic of the experimental set-up. (b) Flow cytometry plots showing the sorting strategy. (c–j) Naive congenically marked (CD45.1+) Id3-GFP P14 cells were transferred to naive recipients (Ly.5.2), which were then infected with LCMV-Docile. Splenic P14 T cells were analysed at the indicated time points after infection. (c) Schematic of the experimental set-up. (d) Flow cytometry plots showing the expression of Id3-GFP, TCF1 and CD62L among splenic P14 T cells at 7 and 21 dpi. (e) Quantification showing absolute numbers of splenic CD62L+ TPEX, CD62L− TPEX and total P14 cells (left) and frequencies of CD62L+ cells among TPEX cells (right) at the indicated time points after infection (f) Flow cytometry plots showing the expression of Ly108 and CD62L and quantification of CD62L+ TPEX cells among P14 T cells in the spleen, lymph nodes, blood, bone marrow and liver at day 31 post LCMV-Docile infection. (g–j) Histograms (g, h) and quantification (i, j) of expression of molecules as indicated in P14 T cell subsets and naive CD8+ T cells. (k–p) Congenically marked naive Nur77-GFP reporter P14 T cells were transferred into naive (k–m) or CD4-T-cell-depleted (n–p) recipient mice, which were subsequently infected with LCMV-Cl13. Nur77-GFP expression was analysed at indicated time points post-infection. (k, n) Schematics of the experimental set-up. Histograms (l, o) and quantifications (m, p) showing Nur77-GFP expression in the indicated P14 T cell subsets at 8 and 21 dpi. GMFI, geometric mean fluorescence intensity. Dots in graphs represent individual mice; box plots indicate range, interquartile and median; horizontal lines and error bars of bar graphs indicate mean and s.e.m. Data are representative of two independent experiments (e, f, i, j) and all analysed mice (m, p). P values are from two-tailed unpaired t-tests (e, i, j), two-way ANOVA (f), and one-way ANOVA (m, p); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 2 Functional and transcriptional profiling of exhausted T cell subsets and RNA velocity analysis showing that differentiation streams originate from CD62L+ TPEX cells.(a, b) Congenically marked naive P14 T cells were adoptively transferred into naive recipient mice, which were then infected with LCMV-Cl13. Splenic P14 T cells from each group were sorted at day 28 post-infection and restimulated independently using gp33-pulsed splenocytes in vitro. (a) Schematic of the experimental set-up. (b) Quantifications showing cytokine production of each subset after restimulation. (c–e) Wild-type mice were infected with LCMV-Docile and splenic CD8+ T cells were analysed at the indicated time points after infection. (c) Schematic of the experimental set-up. (d) Flow cytometry plots showing the expression of CD62L in TPEX (Ly108hi) and TEX (Ly108lo) cells among endogenous gp33-specific CD8+ T cells. (e) Quantification showing the proportions of CD62L-expressing cells among gp33+ TPEX cells (left) and polyclonal PD-1+ TPEX cells (right) at the indicated time points after infection (f, g) Congenically marked naive P14 T cells were adoptively transferred into naive recipient mice, which were then infected with LCMV-Cl13 or LCMV-Armstrong. Splenic P14 compartments from each group were sorted at 28 dpi and processed for bulk RNA-seq. (f) Schematic of the experimental set-up. (g) Principal component plot showing the transcriptional landscapes of sorted populations as indicated. (h–j) Congenically marked naive Tcf7-GFP P14 T cells were adoptively transferred into naive mice, which were then infected with LCMV-Cl13. P14 TPEX cells were sorted at day 28 post-infection based on the expression of Tcf7-GFP. (h) Schematic of the experimental set-up. (i) Flow cytometry plots showing the sorting strategy and post-sort purity. (j) RNA velocity analysis showing developmental trajectories of TPEX cells, together with the expression of Tcf7 (left) and Sell (right). Horizontal lines and error bars of bar graphs indicate mean and s.e.m., respectively. Data are representative of two independent experiments (b) and all analysed mice (e). P values are from Mann–Whitney tests (b) and two-tailed unpaired t-tests (e); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 3 Capacity for self-renewal and multipotent differentiation is restricted to the CD62L+ TPEX cell compartment.(a–f) Congenically marked naive P14 T cells were transferred into primary recipient mice (R1), which were then infected with LCMV-Cl13. The indicated subsets of P14 T cells were sorted at 21 dpi and 4×104 cells were re-transferred to infection-matched secondary recipient mice (R2). The indicated subsets of P14 T cells were sorted from R2 mice at 35 dpi and 1~3×103 cells were re-transferred to infection-matched tertiary recipient mice (R3). Splenic P14 T cells of R3 mice were analysed at day 14 post re-transfer. (a) Schematic of the experimental set-up. (b) Representative flow cytometry plots showing the sorting strategy and post-sort purities. Flow cytometry plots (c) and calculated fold expansion (d) of recovered P14 progenies at day 14 after secondary and tertiary re-transfers. Flow cytometry plots and quantifications showing expression of Ly108 and CD62L of splenic P14 cells in R2 and R3 mice (e) and average percentages of recovered CD62L+ TPEX, CD62L− TPEX and TEX cells per spleen in R2 and R3 mice (f) at day 14 post re-transfer, respectively. (g–l) Congenically marked naive P14 T cells were transferred into primary recipient mice (R1), which were then infected with LCMV-Cl13. The indicated subsets of P14 T cells were sorted at 28 dpi and 3–30 x 103 cells were re-transferred to infection-matched secondary recipient mice (R2). Splenic P14 T cells of R2 mice were analysed at day 14 post re-transfer. Of note, maximum cell numbers attainable for each subset were transferred to allow for reliable evaluation of phenotypic diversification in expanded progenies. Fold expansion of recovered progenies was then normalized to distinct input numbers. (g) Schematic of the experimental set-up. (h) Representative flow cytometry plots showing the sorting strategy and post-sort purities. Flow cytometry plots (i) and fold expansion (j) of recovered progenies at day 14 post re-transfer. Flow cytometry plots and quantifications showing expression of Ly108 and CD62L of splenic P14 cells of R2 mice (k) and average percentages of recovered CD62L+ TPEX, CD62L− TPEX, CD62L+ TEX and CD62L− TEX cells per spleen (l) in R2 mice at day 14 post re-transfer. Dots in graphs represent individual mice; horizontal lines and error bars of bar graphs indicate mean and s.e.m., respectively. Data are representative of two independent experiments (b, c, e, h, i, k) and all analysed mice (d, f, j, l). P values are from Mann–Whitney tests (d, j); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 4 Single CD62L+ TPEX cells show a stem-like capacity for self-renewal and multipotent differentiation.(a–d) Single naive colour-barcoded P14 T cells were transferred to primary recipient mice, which were then infected with LCMV-Armstrong. Splenic P14 T cells were analysed at day 8 post LCMV-Armstrong infection. (a) Schematic of the experimental set-up for the naive P14 single-cell transfer. (b) Flow cytometry plots showing expression of GFP and YFP (left) or BFP/CFP and CFP/T-Sap (right) in peripheral blood of retrogenic P14 donor mice (pre-gated on CD8+CD44loCD45.1+). (c) Tracking of colour-barcoded single-cell-derived progenies at 8 dpi in the spleens of three representative recipient mice. Recovered progenies were distinguished according to their combinatorial expression of GFP and YFP into populations I, II, III, IV and V, which were further subdivided by their expression of T-Sapphire, CFP, and BFP into progenies characterized by their unique combinatorial colour barcode. Note: in the display used, CFP emission appears on the diagonal between the BFP (x-axis) and T-Sapphire signal (y-axis) and is therefore indicated on both axes. (d) Flow cytometry plots depicting combined staining of CD45.1 and Thy1.1 with KLRG1 (upper row), or CD62L with PD-1 (lower row) for three progenies derived from adoptively transferred single naive P14 cells (grey: endogenous CD4−CD19− cells). (e–i) Colour-barcoded naive P14 T cells were transferred into primary recipient mice (R1), which were subsequently infected with LCMV-Cl13. P14 T cells were sorted at 28 dpi and single CD62L+ or CD62L− TPEX cells were re-transferred into naive secondary recipient mice (R2), which were subsequently infected with LCMV-Armstrong. Splenic P14 T cells were analysed at day 8 post LCMV-Armstrong infection. (e) Schematic of the experimental set-up. (f) Percentages of transferred single cells of CD62L+ TPEX, CD62L− TPEX cell or naive phenotype from which progenies were recovered at 8 dpi. (g) As in (d), but for adoptively re-transferred single CD62L+ TPEX cells. (h) Size of single-T-cell-derived progenies and frequencies of CD62L+, KLRG1+ and (i) PD-1+ cells therein. Dots in graphs represent individual clones derived from a single transferred cell. Horizontal lines and error bars of bar graphs indicate mean and s.e.m., respectively. Data show all analysed mice (h, i). P values are from Mann–Whitney tests (h–i); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 5 CD69 expression in TPEX cells does not correlate with CD62L expression and does not predict developmental and repopulation potential; chronic LCMV infection and strong TCR stimuli favour MYB expression and the formation of stem-like CD62L+ TPEX cells.(a) Normalized expression of Cd69 projected on the UMAP of scRNA-seq data as in Fig. 1. (b) Enrichment of Ly108+CD69+ (“TEX prog1”) and Ly108+CD69− (“TEX prog2”) signatures29 at single-cell and cluster levels. (c) Flow cytometry plots and quantification showing CD69 expression in CD62L+ and CD62L− P14 TPEX cells on day 28 post LCMV-Cl13 infection. (d–j) Congenically marked naive P14 T cells were transferred into primary recipient mice (R1), which were then infected with LCMV-Cl13. The indicated subsets of P14 T cells were sorted at 28 dpi and re-transferred to infection-matched secondary recipient mice (R2). Splenic P14 T cells of R2 mice were analysed at day 14 post re-transfer. (d) Schematic of the experimental set-up. (e) Representative flow cytometry plots showing the sorting strategy and post-sort purities. (f) Quantification of recovered P14 cells at day 14 post re-transfer. (g) Flow cytometry plots and quantifications showing expression of Ly108 and CD69 of splenic P14 cells of R2 mice and (h) average percentages of recovered CD69+ TPEX, CD69− TPEX, CD69+ TEX and CD69− TEX cells per spleen in R2 mice at day 14 post re-transfer. (i) Flow cytometry plots and quantifications showing expression of Ly108 and CD62L of splenic P14 cells of R2 mice and (j) average percentages of recovered CD62L+ TPEX, CD62L− TPEX and TEX cells per spleen in R2 mice at day 14 post re-transfer. (k-l) Naive MybGFP reporter mice were infected with either LCMV-Docile or LCMV-Armstrong and CD8+ T cells were analysed at the indicated time points after infection. (k) Representative flow cytometry plots depict Ly108 and Myb-GFP expression among antigen-specific (gp33+) CD8+ T cells. (l) Histograms (filled) show Myb-GFP expression of gp33+ CD8+ T cells in mice infected with LCMV-Docile (top) and LCMV-Armstrong (bottom). Empty histograms depict Myb-GFP expression in naive CD8+ T cells in the same samples. Corresponding quantification show the fold change of geometric mean fluorescence intensity (GMFI) of Myb-GFP in the indicated populations. (m–o) LCMV-Docile-infected MybGFP reporter mice were treated with or without anti-PD-L1. Splenic CD8+ T cells were analysed at 6 dpi. (m) Schematic of the experimental set-up. (n) Flow cytometry plots and quantification showing frequencies of splenic gp33+ CD8+ T cells in anti-PD-L1-treated and untreated control mice at 6 dpi. (o) Histograms showing Myb-GFP expression of gp33+ and naive (gated on CD62L+CD44−) CD8+ T cells in the same mice. (p) Naive MybGFP and wild-type (non-reporter, control) CD8+ T cells were stimulated and cultured in vitro using plate-bound anti-CD3. Representative histogram and normalized quantification show GMFI of Myb-GFP expression in CD8+ T cells stimulated with plate-bound anti-CD3 at the indicated concentrations. (q) Flow cytometry plots and quantification show the frequencies of Ly108+ and CD62L+ cells among splenic antigen-specific (gp33+) T cells in wild-type mice at day 8 post LCMV-Docile or LCMV-Armstrong infection. (r) Congenically marked P14 T cells were adoptively transferred into naive recipient mice, which were then infected with either LCMV-Docile or LCMV-Armstrong. Splenic P14 T cells were analysed at 8 dpi. Flow cytometry plots and quantification show the frequencies of Ly108+ and CD62L+ cells among splenic P14 T cells. Dots in graphs represent individual mice (c, f, l, o, q, r) and individual wells (p); box plots indicate range, interquartile and median; horizontal lines and error bars in indicate mean and s.e.m., respectively. Data are representative of two independent experiments (c, l, o, p) and all analysed mice (f, q, r). P values are from two-tailed unpaired t-tests (c, l, o–r) and Mann–Whitney tests (f); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 6 Development of mature CD8+ T cells is largely normal in Mybfl/flCd4Cre mice.Adult 8-12 weeks Mybfl/flCd4Cre (Myb-cKO) and littermate Mybfl/fl control (Ctrl) mice were euthanized, and T cell populations were analysed in the thymus, spleen and lymph nodes. Flow cytometry and quantifications showing (a–c) frequencies of thymocyte subsets, (d–f) frequencies and abundance of mature splenic CD8+ T cells, (g) surface expression of CD127 (IL-7R), CCR7 and CD25 (IL-2R) of splenic CD8+ T cells and (h, i) frequencies of mature CD8+ T cells residing in lymph nodes. (h). Dots in graphs represent individual mice; box plots indicate range, interquartile and median. All data are representative of two independent experiments. P values are from two-tailed unpaired t-tests (d, f–h) and Mann–Whitney tests (a, c, e, i); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 7 MYB is required to limit CD8+ T cell expansion and cytotoxicity in response to chronic infection.(a–s) Mybfl/flCd4Cre (Myb-cKO) mice and littermate Mybfl/fl control mice (Ctrl) were infected with either LCMV-Armstrong (a–d) or LCMV-Docile (e–s). (a–b) Flow cytometry plots showing (a) splenic antigen-specific (gp33+) CD8+ cells and (b) expression of CD62L and KLRG1 among antigen-specific cells in Myb-cKO and control mice at indicated time points post LCMV-Armstrong infection. (c) Quantification of central memory (TCM), effector memory (TEM), CX3CR1+ and KLRG1+ cells among gp33+ CD8+ cells in Myb-cKO and control mice at indicated time points post LCMV-Armstrong infection. (d) Numbers of splenic gp33+CD8+ T cells in Myb-cKO and control mice at indicated time points post LCMV-Armstrong infection. (e) Box plots showing the weights of spleens (left) and the total numbers of splenocytes (right) in Myb-cKO and control mice at day 8 post LCMV-Docile infection. (f) Spleen size (left) and haematoxylin and eosin staining of sections showing infiltration of immune cells (arrows) in livers (middle) and lungs (right) in Myb-cKO and control mice at 8 dpi. (g) Confocal images of F4/80 and B220 expression in frozen spleen sections and (h) quantification showing the cellular organization and area of lymphoid regions in Myb-cKO and control mice at day 8 post LCMV-Docile infection. (i) Confocal images of CD3 and B220 expression in frozen spleen sections showing the distribution of B and T cells in the spleens of Myb-cKO and control mice at day 8 post LCMV-Docile infection. (j) Image and box plot showing the size and weights of spleens in untreated and CD8+ T-cell-depleted Myb-cKO mice at day 8 post LCMV-Docile infection. (k) Survival curve of CD8-depleted Myb-cKO mice post LCMV-Docile infection. (l) Proportion of cytokine-producing antigen-specific TPEX and TEX cell subsets after gp33 peptide restimulation of Myb-cKO and control mice at day 8 post LCMV-Docile infection. (m, n) Quantification of IFNγ expression (m), and granzyme B (GZMB) expression in TPEX and TEX cells (n) in Myb-cKO and control mice at day 8 post LCMV-Docile infection. (o) Flow cytometry plots and quantification showing the proportions of Ki67+ within the gp33+ compartment in Myb-cKO and control mice at day 8 post LCMV-Docile infection. (p) Box plots showing viral titres in the kidneys of Myb-cKO and control mice at day 8 post LCMV-Docile infection. (q) Box plots showing the expression of PD-1 (left) and TIM-3 (right) among gp33+ CD8+ T cells of control and Myb-cKO mice at day 8 post LCMV-Docile infection. (r) Flow cytometry plots and quantification show the frequencies of TPEX cells (TCF1+TIM-3−) and TEX cells (TCF1-TIM-3+) among splenic gp33+ CD8+ T cells of Myb-cKO and control mice. (s) Quantification showing the absolute numbers of splenic CD8+, gp33+, CD62L+ TPEX, CD62L− TPEX and TEX cells in Myb-cKO and control mice at day 8 post LCMV-Docile infection. GMFI, geometric mean fluorescence intensity. Dots in graphs represent individual mice; box plots indicate range, interquartile and median; horizontal lines in (h) indicate median. Data are representative of two independent experiments (c–e, k–r) or all mice (j, s) and images (h) analysed; P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 8 MYB limits CD8+ T cell expansion and cytotoxicity during chronic infection in a cell-intrinsic manner.(a–n) Naive CD45.1 mice were lethally irradiated and reconstituted using a mixture of Mybfl/flCd4Cre (Myb-cKO) and Cd4Cre or littermate Mybfl/fl control (Ctrl) bone marrow. Chimeric mice were subsequently infected with LCMV-Docile and analysed at the indicated time points after infection. Quantification showing the frequencies of (a) polyclonal antigen-specific gp33+ cells among Myb-cKO and control CD8+ T cells at 8 dpi. (b) Flow cytometry plots and quantification of IFNγ+ cells among Myb-cKO and control CD8+ T cells after peptide restimulation in vitro at 8 dpi. (c) Quantification of GZMB expression among gp33+ cells of the indicated genotypes. (d, e) Flow cytometry plots and quantification showing the frequencies of (d) Ki67+ cells and (e) annexin-V+ cells among Myb-cKO and control antigen-responsive CD8+ T cells. (f, g) Flow cytometry plots and quantification showing the frequencies of TCF1+ TPEX cells among antigen-specific T cells (f) and CD62L+ cells among TPEX cells (g) in Myb-cKO and control compartments at 8 dpi. (h) Flow cytometry plots showing the frequencies of TPEX cells among gp33+ cells at 49 dpi. (i–j) Flow cytometry plots (i) and quantification (j) showing kinetics of splenic polyclonal PD-1+ TPEX cells among Myb-cKO and control CD8+ T cells after infection. (k–l) Flow cytometry plots (k) and quantification (l) showing the frequencies of the entire antigen-responsive PD-1+ cell compartment among Myb-cKO and control CD8+ T cells at indicated time points after infection. (m, n) Flow cytometry plots and quantifications showing the frequencies of Ki67+ cells among Myb-cKO and control polyclonal TPEX (m) and TEX (n) cells at indicated time points after infection. GMFI, geometric mean fluorescence intensity. Dots in graphs represent individual mice; box plots indicate range, interquartile and median. Symbols and error bars represent mean and s.e.m., respectively. All data are representative of two independent experiments. P values are from two-tailed unpaired t-tests (a–g) and Mann–Whitney tests (j–n); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 9 MYB limits proliferation and cytotoxicity and sustains the long-term self-renewal of exhausted CD8+ T cells.(a–g) Congenically marked naive control (Cd4Cre) and Mybfl/flCd4Cre (Myb-cKO) P14 T cells were adoptively transferred into naive recipient mice, which were subsequently infected with LCMV-Docile. Splenic P14 T cells were analysed at indicated time points post-infection (p.i). (a) Schematic of the experimental set-up. (b) Box plot showing PD-1 expression of transferred P14 cells at 8 dpi. (c) Flow cytometry plots and quantification showing frequencies of CD62L+ cells among Myb-cKO and control P14 TPEX cells. (d) Flow cytometry plots and quantification showing the expression of granzyme B (GZMB) in Myb-cKO and control TEX P14 cells at 8 dpi. (e) Flow cytometry plots and quantifications showing the production of cytokines as indicated from Myb-cKO and control P14 T cells after gp33 peptide restimulation at 8 dpi. (f) Flow cytometry plots and quantification showing the frequencies of TPEX cells among Myb-cKO and control P14 T cells at the indicated time points after infection. (g) Flow cytometry plots and quantification showing the frequencies of Ki67+ cells among Myb-cKO and control P14 T cells at indicated time points after infection. GMFI, geometric mean fluorescence intensity. Dots in graphs represent individual mice; box plots indicate range, interquartile and median; Data are representative of two independent experiments (b–g). P values are from two-tailed unpaired t-tests; P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 10 MYB regulates the expression of multiple genes that are critical to exhausted T cell function and maintenance.(a, b) Congenically marked Mybfl/flCd4Cre (Myb-cKO, CD45.2+) and Cd4Cre (Ctrl, CD45.2+ or CD45.2+CD45.1+) P14 T cells were adoptively transferred into separate naive recipient (CD45.1) mice, which were then infected with LCMV-Docile. Splenic P14 TPEX cells were sorted at day 7 post-infection and processed for bulk RNA-seq. (a) Schematic of the experimental set-up. (b) Gene set enrichment analysis showing loss of CD62L+ TPEX transcriptional signature in Myb-cKO TPEX cells compared to control TPEX cells. (c) Volcano plots highlighting genes differentially expressed (FDR < 0.15) between control CD62L+ TPEX and CD62L− TPEX cells. (d–e) Mixed bone marrow chimeric mice containing congenically marked Myb-cKO and control CD8+ T cells were infected with LCMV-Docile. Flow cytometry plots (d) and quantification (e) showing the frequencies of the entire antigen-responsive PD-1+ cell compartment among Myb-cKO and control CD8+ T cells in the spleen and lymph nodes at day 70 post-infection. (f, g) Congenically marked Myb-cKO and Ctrl P14 T cells were adoptively transferred into separate naive recipient mice, which were then infected with LCMV-Docile. Splenic P14 TPEX cells were analysed at day 8 post-infection. (f) Schematic of the experimental set-up. (g) Quantification showing the abundances of the indicated P14 subsets per spleen. (h) Heat map depicting genes differentially expressed (FDR < 0.15, FC > 1) between control CD62L+ TPEX and CD62L− TPEX cell or Myb-cKO and control TPEX and TEX cells, with genes of interest annotated. (i) Gene set enrichment analysis showing loss of CX3CR1+ TEX transcriptional signature in P14 Myb-cKO TEX cells compared to control TEX cells. (j) Volcano plot highlighting genes differentially expressed (FDR < 0.15) between control and Myb-cKO TEX cells with genes of interested annotated. (k) Flow cytometry plots and quantification show the frequencies of CX3CR1+ cells among control and Myb-cKO TEX P14 T cells at day 8 post LCMV-Docile infection. (l) Flow cytometry plots and quantifications showing CX3CR1 and CD101 expression in Myb-cKO and control TEX cells at the indicated time points after infection. Dots in graph represent individual mice; box plots indicate range, interquartile and median. Symbols and error bars in (l) represent mean and s.e.m., respectively Data are representative of two independent experiments (e, g, k, l). P values are from two-tailed unpaired t-tests; P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 11 MYB directly regulates target gene expression, and CD62L+ TPEX cells have a superior potential to give rise to CX3CR1+ TEX cells.(a–d) Representative tracks showing MYB ChIP–seq peaks in the LEF1 (a), E2F1 (b), GZMA (c), and MYB (d) gene loci of human Jurkat T cells and ATAC-seq peaks of TPEX and TEX cells in the corresponding mouse gene loci aligned according to the sequence conservation. (e–g) Congenically marked naive P14 cells were transferred to primary recipient mice (R1), which were subsequently infected with LCMV-Cl13. The indicated subsets of P14 cells were sorted at 28 dpi and re-transferred to naive secondary recipient mice (R2), which were then infected with LCMV-Armstrong. Splenic P14 T cells in R2 mice were analysed at 8 dpi. (e) Schematic of the experimental set-up. (f) Flow cytometry plots of progenies recovered at 8 dpi. (g) Cell numbers (left) and quantification of PD-1 expression (right) in P14 T cell populations derived from the indicated transferred subsets at 8 dpi. (h, i) Congenically marked naive P14 T cells were transferred into primary recipient mice (R1), which were then infected with LCMV-Docile. The indicated subsets of P14 T cells were sorted at 7 dpi and 7.5×104 cells were re-transferred to infection-matched (LCMV-Docile) secondary recipient mice (R2). Splenic P14 T cells of R2 mice were analysed at day 28 post re-transfer. (h) Schematic of the experimental set-up. (i) Flow cytometry plots and box plots showing the frequencies of CX3CR1+ and CD101+ cells among recovered TEX cells derived from the indicated re-transferred TPEX subsets at day 28 post re-transfer. Data are representative of two independent experiments. P values are from Mann–Whitney tests (g) and two-tailed unpaired t-test (i); P > 0.05, not significant (n.s.).Source dataExtended Data Fig. 12 Effect of PD-1 signalling on CD62L+ TPEX cells.(a–f) Congenically marked PD-1-deficient (Pdcd1−/−) and control P14 T cells were transferred to naive mice, which were subsequently infected with LCMV-Docile. Splenic P14 T cells were analysed at 7 dpi. (a) Schematic of the experimental set-up. (b) P14 T cell frequencies and numbers of indicated genotypes. (c) Flow cytometry plots and frequencies of TPEX (Ly108hiTIM-3lo) and TEX (Ly108loTIM-3hi) cells. (d) Box plots show frequencies and numbers of CD62L+ TPEX cells among control and PD-1-deficient P14 cells. Flow cytometry plots and box plots show (e) frequencies of KIT+ TPEX cells and (f) numbers of KIT+ TPEX and TEX cells per spleen. (g–k) Wild-type mice were infected with LCMV-Docile and treated with anti-PD-L1 at 200 μg/mouse at 1, 3 and 5 dpi. Splenic CD8+ T cells were analysed at 6 dpi. (g) Schematic of the experimental set-up. (h) Flow cytometry plots and quantification showing the frequencies of PD-1+ cells among splenic CD8+ T cells. (i–j) Flow cytometry plots (i) and quantification (j) showing expression of CD62L among polyclonal TPEX cells (Ly108hiTIM-3lo). (k) Quantification showing the population sizes of CD62L+ TPEX, CD62L− TPEX and TEX cells among total CD8+ T cells in untreated and anti-PD-L1-treated mice. (l–p) Wild-type mice were infected with LCMV-Docile and treated with anti-PD-L1 at 200 μg/mouse at 21, 23, 25, 27 and 29 dpi. Splenic CD8+ T cells were analysed at 31 dpi. (l) Schematic of the experimental set-up. (m–n) Flow cytometry plots (m) and quantification (n) showing the frequencies of the PD-1+ cells among splenic CD8+ T cells. (o) Flow cytometry plots and quantification showing the expression of CD62L among polyclonal TPEX cells (Ly108hiTIM-3lo). (p) Quantification showing the population sizes of CD62L+ TPEX, CD62L− TPEX and TEX cells among total CD8+ T cells in untreated and anti-PD-L1-treated mice. Dots in graphs represent individual mice; box plots indicate range, interquartile and median. Data are representative of at least two independent experiments. P values are from two-tailed unpaired t-tests; P > 0.05, not significant (n.s.).Source dataSupplementary informationReporting SummaryPeer Review FileSupplementary Table 1List of cluster signature genes identified by scRNA-seq.Supplementary Table 2List of genes differentially expressed between control and Myb-cKO P14 subsets.Supplementary Table 3List of genes differentially expressed between control and Myb-cKO P14 subsets and bound by MYB in human T cells.Source dataSource Data Fig. 1Source Data Fig. 2Source Data Fig. 3Source Data Fig. 4Source Data Extended Data Fig. 1Source Data Extended Data Fig. 2Source Data Extended Data Fig. 3Source Data Extended Data Fig. 4Source Data Extended Data Fig. 5Source Data Extended Data Fig. 6Source Data Extended Data Fig. 7Source Data Extended Data Fig. 8Source Data Extended Data Fig. 9Source Data Extended Data Fig. 10Source Data Extended Data Fig. 11Source Data Extended Data Fig. 12Rights and permissions

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Reprints and permissionsAbout this articleCite this articleTsui, C., Kretschmer, L., Rapelius, S. et al. MYB orchestrates T cell exhaustion and response to checkpoint inhibition.

Nature 609, 354–360 (2022). https://doi.org/10.1038/s41586-022-05105-1Download citationReceived: 15 November 2021Accepted: 13 July 2022Published: 17 August 2022Issue Date: 08 September 2022DOI: https://doi.org/10.1038/s41586-022-05105-1Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard

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MYB function in normal and cancer cells | Nature Reviews Cancer

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nature

nature reviews cancer

review articles

article

Review Article

Published: July 2008

MYB function in normal and cancer cells

Robert G. Ramsay1 & Thomas J. Gonda2

Nature Reviews Cancer

volume 8, pages 523–534 (2008)Cite this article

8806 Accesses

454 Citations

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Key Points

The MYB oncogene is associated with leukaemogenesis in several species including humans. MYB can be activated by overexpression or inappropriate expression, structural alteration and/or genomic rearrangements.

MYB is clearly required in the bone marrow, colonic crypt and neurogenic niches as demonstrated when global or tissue-specific knockout mice were generated. Multiple cell types are affected and these contribute to the stem cell niches in these tissues.

MYB transcription is tightly regulated by attenuation sequences that reside in the first intron and mutations in this region in colorectal cancer correlate with elevated MYB expression, a characteristic of most colorectal cancers. In breast cancer oestrogen receptor-α (ERα) relieves the attenuation allowing elevated MYB expression, a characteristic of most ERα+ breast cancers.

Sub-optimal MYB function, either through protein changes or through heterozygous loss, compromises the ability to maintain tissue homeostasis when these tissues are subjected to stress. This might have clinical implications for treating patients with abnormal MYB function who would otherwise appear normal.

Over 80 cellular targets of the MYB transcription factor have been identified that partly, but incompletely, explain the importance of MYB in development, cell survival, proliferation and homeostasis. When MYB is overexpressed or inappropriately activated, some of these, and perhaps additional target genes, contribute to the transforming capacity of MYB.

Therapeutic interventions that target MYB in malignancy have been limited, but the observation that ERα+ breast cancer cells have elevated MYB indicates that targeting ERα-regulated gene expression might be efficacious. In addition, immunotherapy against MYB is now under investigation.

AbstractThe transcription factor MYB has a key role as a regulator of stem and progenitor cells in the bone marrow, colonic crypts and a neurogenic region of the adult brain. It is in these compartments that a deficit in MYB activity leads to severe or lethal phenotypes. As was predicted from its leukaemogenicity in several animal species, MYB has now been identified as an oncogene that is involved in some human leukaemias. Moreover, recent evidence has strengthened the case that MYB is activated in colon and breast cancer: a block to MYB expression is overcome by mutation of the regulatory machinery in the former disease and by oestrogen receptor-α (ERα) in the latter.

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Figure 1: MYB genomic and protein structure.Figure 2: A model of MYB transcriptional elongation control.Figure 3: MYB is required for normal adult haematopoiesis.Figure 4: MYB is intrinsic to stem and progenitor cell niches in at least three tissue compartments.Figure 5: MYB overexpression.

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Download referencesAcknowledgementsThis work has been supported by research grants to R.G.R. and T.G. from the National Health and Medical Research Council of Australia, the Cancer Council of Victoria and the Queensland Cancer Fund. R.G.R. is also a National Research Fellow of the NHMRC. We wish to thank members of our respective laboratories for their ongoing commitment to hard work and dedication to unravelling the mysteries of MYB in cancer. Finally, sincere thanks to the members of the MYB research community with whom we have travelled in our growing understanding of what was once 'only a retroviral oncogene' in chickens but is now a key player in both normal and cancer biology in humans.Author informationAuthors and AffiliationsPeter MacCallum Cancer Centre, St Andrew's Place, Melbourne, 3002, Victoria, AustraliaRobert G. RamsayUniversity of Queensland Diamantina Institute for Cancer, Immunology and Metabolic Medicine, Princess Alexandra Hospital, Ipswich Road, Buranda, 4102, Queensland, AustraliaThomas J. GondaAuthorsRobert G. RamsayView author publicationsYou can also search for this author in

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Robert G. Ramsay.Supplementary informationSupplementary information S1 (table) (PDF 284 kb)Related linksRelated linksDATABASESNational Cancer Institute

breast cancer

colorectal cancer

leukaemia

melanoma

oesophageal cancer

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FURTHER INFORMATION

Oncomine

Stanford Microarray Database

GlossaryHypomorphic mutants

Mostly partial loss of function mutants. These mutations are extraordinarily valuable as they allow sufficient gene function to generate viable animals but are defective enough to produce a phenotype.

Haematopoiesis

Responsible for generating all the cell lineages of the blood system. In adult mammals it has two principal arms that build the myeloid and lymphoid compartments. The former is responsible for macrophages, platelets, red blood cells, neutrophils, eosinophils and basophils. B- and T-cell production falls into the domain of the lymphoid compartment.

Transcriptional elongation

An essential component of gene transcription that involves the extended polymerization of ribonucleotides as a gene is transcribed. This occurs after transcription initiation and seems to be subject to regulation both at short distances from the transcription initiation sites and during elongation itself.

Mismatch repair

A process that identifies nucleotide changes that differ from the parental DNA strand, and which restores the daughter sequence to the wild-type or parental sequence. Regions that contain stretches of mono- or dinucleotide repeats are particularly prone to mutation if cells are defective in a group of proteins that collectively govern the mismatch repair process.

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MYB oncoproteins: emerging players and potential therapeutic targets in human cancer | Oncogenesis

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MYB oncoproteins: emerging players and potential therapeutic targets in human cancer

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Published: 26 February 2021

MYB oncoproteins: emerging players and potential therapeutic targets in human cancer

Ylenia Cicirò1 & Arturo Sala

ORCID: orcid.org/0000-0002-2841-78661

Oncogenesis

volume 10, Article number: 19 (2021)

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AbstractMYB transcription factors are highly conserved from plants to vertebrates, indicating that their functions embrace fundamental mechanisms in the biology of cells and organisms. In humans, the MYB gene family is composed of three members: MYB, MYBL1 and MYBL2, encoding the transcription factors MYB, MYBL1, and MYBL2 (also known as c-MYB, A-MYB, and B-MYB), respectively. A truncated version of MYB, the prototype member of the MYB family, was originally identified as the product of the retroviral oncogene v-myb, which causes leukaemia in birds. This led to the hypothesis that aberrant activation of vertebrate MYB could also cause cancer. Despite more than three decades have elapsed since the isolation of v-myb, only recently investigators were able to detect MYB genes rearrangements and mutations, smoking gun evidence of the involvement of MYB family members in human cancer. In this review, we will highlight studies linking the activity of MYB family members to human malignancies and experimental therapeutic interventions tailored for MYB-expressing cancers.

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IntroductionVertebrate MYB genes encode transcription factors related to the v-myb oncogene, the transforming gene of avian retroviruses causing myelomas and lymphomas in birds1,2. AMV was originally identified as a virus that induces a disease in chickens similar to acute myelogenous leukaemia in humans3. The v-mybAMV oncogene product, a 45 kDa protein, was proved to be a truncated version of vertebrate MYB, the 75 kDa product of the proto-oncogene MYB, mainly expressed in haematopoietic tissues4,5. The v-myb oncogene was also found fused to a second oncogene, v-ets, in the E26 retrovirus that cause avian erythroblastosis6. Invertebrates carry only one MYB gene which, from a phylogenetical and functional point of view, is equivalent to vertebrate MYBL2, suggesting that this is the most ancient member of the family7,8. There is no homologue of the MYB gene in nematodes, although distantly related genes, such as Cdc5 and SNAPc, have been identified in Caenorhabditis elegans9,10.In humans and other mammals, the transcription factor MYB (encoded by MYB) is the prototype member of the family, which includes MYBL1 (encoded by MYBL1) and MYBL2 (encoded by MYBL2)11. Although similar in structure, the different MYB proteins interact with unique co-factors and their expression is often nonoverlapping, suggesting that they might have distinct biological roles (Fig. 1)12,13,14,15.Fig. 1: MYB family members’ protein structures.The v-myb DNA-binding domain is equivalent to amino acids 72–192 of MYB, except the introduction of four point mutations (I91N, L106H, V117D, and I181V) and the addition of six amino acids in N-terminal region derived from the retroviral Gag polyprotein187. The white dots on AMV v-myb structure indicate point mutations important for the ability of v-myb to transform cells188. MYB co-activators are listed in green and the co-repressors are listed in red. The DNA-binding domain (DBD) is comprised of three repeats (R1, R2, and R3). It is the binding site for a number of proteins including p100, PARP, c-Ski, N-CoR, RAR, Cyp40, C/EMPbeta, SMRT, and mSin3A, as depicted; the central transactivation domain (TAD) is the interaction site for CBP/p300; the negative regulatory domain (NRD) extends from the FAETL motif to the EVES peptide sequence (involved in intramolecular and intermolecular protein–protein interactions) and includes the binding sites for p160/p67, Pin1, and TIF1beta150,189,190,191,192,193. The post-translational modifications include phosphorylation (P), acetylation (AC), and sumoylation (SUMO)194,195,196,197.Full size imageMYB proteins structure and identification of target genesMYB proteins contain a highly conserved helix-turn-helix (HTH) DNA-binding domain (DBD) at the N-terminus, encompassing three tandem repeated domains of ~50 amino acids containing tryptophan named R1, R2, and R316; a conserved C-terminal negative regulatory domain (NRD); a trans-activating domain (TAD) in the central portion of the protein. The latter includes an acidic region and a heptad leucine-zipper repeat only present in MYB and MYBL1 (Fig. 1)9.All MYB family members recognise and bind the same DNA consensus sequence [PyAAC(G/T)G] to transactivate gene expression. This motif, firstly identified by the Klempnauer group using DNA footprinting assays, is known as the canonical MYB-binding site (MBS)17. The sequence was later confirmed to be present, and bound by v-myb, in the promoter region of the first MYB-target gene identified in vertebrates, mim-118. With the development of more advanced genomic technologies, different groups attempted the identification of MYB target genes at the global level. The Ness team found the c-MYB protein bound to over 10,000 promoters in the cancer breast cell line MCF-7, and validated known MYB target genes involved in the cell cycle, such as MYC and CCNB1, or identified new MYB target genes involved in stemness and transcription control such as JUN, KLF4, NANOG and SND119. Another study by the Gonda lab identified genes regulated by MYB in mouse myeloid progenitor cells. This study not only confirmed that MYB positively regulates promoters of key cell proliferation genes, such as Myc, but it can also work as a transcriptional repressor. Indeed, several key regulators of myeloid differentiation such as Runx1, Pu.1, Junb and Cebp were strongly suppressed by exogenous expression of MYB, suggesting a mechanism used by the transcription factor to suppress differentiation and promote self-renewal20. A selection of MYB target genes that have been shown to mediate physiological functions in normal or disease contexts is shown in Table 1.Table 1 Selected MYB target genes.Full size tableThe transcriptional activity of MYB proteins is regulated either positively or negatively by co-factors; cellular proteins physically interacting with the different MYB family members are indicated under their protein structures in Fig. 1. Structure–function relationships have been largely inferred by studying the prototype member of the family, MYB (c-MYB). For example, the TAD domain confers transactivating activity to MYB by recruiting CREB-binding domain protein (CBP) and p30021,22. The CAAT enhancer-binding protein (C/EBP) family member NF‐M cooperates with MYB in transcriptionally activating the mim‐1 promoter through an adjacent DNA-binding site and it is also co‐activated by CBP in a Ras‐dependent manner, suggesting that CBP might work by functionally linking MYB and NF-M22. Indeed, NF-M has been shown to affect the MYB-C/EBP interaction by disrupting the N-terminal region within the repeat domain R1 (amino acids 47–71), enhancing MYB oncogenic activity23.MYB can cooperate, cross-regulate and compete with other transcription factors, such as members of the C/EBP family, the ETS family, and GATA124,25,26. Recently, it has been shown that in ALL patients aberrant recruitment of the histone acetyl transferase CBP/p300 by MYB in the enhancer region of the protooncogene TAL1 occurs via the formation of de novo MYB-binding elements27.Alterations of MYB family genes in human cancer and experimental therapeutic approachesMYB family members are often aberrantly expressed in human cancers, suggesting that they could be important for tumour initiation and/or maintenance. Since MYB proteins are essential for key cellular processes such as growth, differentiation and survival, it is likely that genomic mutations or alterations of gene expression might contribute to oncogenesis. Broadly expressed transcription factors are considered unsuitable therapeutic targets since their inactivation or downregulation could be detrimental to organism homoeostasis. Furthermore, it is inherently difficult to block the interaction of transcription factors with DNA using small molecules. Despite these caveats, therapeutic approaches aiming at inhibiting MYB oncoproteins, or their target genes, in cancer are under investigation in preclinical and clinical studies.In the following paragraphs, we discuss studies in which MYB family members have been implicated in forms of human cancer. We also highlight laboratory experiments, or clinical trials, in which MYB, or MYB-regulated genes, have been targeted for therapeutic purposes.

MYB

Disruption of MYB causes embryonic lethality due to the failure of foetal hepatic haematopoiesis28. The key role of the MYB gene product in mammalian haematopoiesis is also indicated by its ability to regulate the expression of foetal haemoglobin and requirement for the maturation of T and B lymphocytes29,30,31,32. Although prevalently expressed in haematopoietic cells, MYB expression is detected also in neural tissues, as well as in colonic crypts and breast cells33,34,35,36,37.MYB, similarly to the ubiquitous member of the family MYBL2, regulates cyclin-dependent kinases (Cdks) expression and activity, essential for cell duplication38,39. MYB autoregulates its own expression and is engaged in positive and negative regulatory loops with cyclins and Cdks, in both the G1 and G2 phases of the cell cycle38,40,41,42.

MYB alterations in cancerGenetic mutations and augmented expression of MYB have been firstly noted in leukaemic cells, and only relatively recently in solid cancers. Overexpression of wild type MYB is insufficient for full transformation of human epithelial cells, supporting the hypothesis that it promotes tumourigenesis only in combination with additional genetic alterations43.The first recurrent genomic rearrangements of the MYB locus were evidenced in acute T cell leukaemia, in which MYB overexpression is caused by gene duplication or translocation, juxtaposing strong enhancers from other genomic locations44. Summarising the information present in literature, it is possible to group MYB oncogenic alterations into three classes: overexpression, fusion with partner genes, and ectopic binding of the MYB oncoprotein to enhancer sequences caused by somatic mutations (i.e. TAL1 enhancer27). MYB gene amplification and overexpression have been observed in acute myeloid leukaemia (AML), non-Hodgkin lymphoma, colorectal cancer, and breast cancer5,45,46,47,48. Fusion with partner genes is mainly observed in solid tumours, as discussed in detail in the following sections.MYB genomic alterations have been detected in multiple forms of human cancer, suggesting a causative role. Therefore, numerous studies have been conducted in which inhibition of MYB, or of its downstream genes, has been used as a potential therapeutic strategy. Preclinical studies and actionable MYB target genes are summarised in Table 2.Table 2 Preclinical and clinical therapeutic strategies based on inhibition of MYB or actionable MYB-target genes.Full size table

MYB and leukaemia

In a cluster of acute lymphoblastic leukaemia (ALL) patients, mutations of the TAL1 enhancer create ex-novo MYB-binding sites. The leukaemias arising in these patients show MYB-dependency consequential to the aberrant activation of the TAL1 oncogene by MYB27. Through genomic screening of an independent set of 107 individuals with T cell ALL (T-ALL) and 12 T-ALL cell lines, Lahortiga et al. detected duplication of MYB in 9 of 107 (8.4%) cases and in five different cell lines49. The flanking genes HBS1L and AHI1 were duplicated in some patients, but the commonly duplicated region covered only the MYB gene. The duplication is associated with a threefold increase in MYB expression, and its knockdown initiates T cell differentiation. Thus, MYB duplications may be leukaemogenic in a subset of T-ALL patients49.

In acute basophilic leukaemia (ABL) the MYB locus is fused to another gene encoding the transcription factor GATA1. This rare subtype of acute myeloblastic leukaemia is characterised by the t(X;6)(p11;q23) translocation, leading to decrease or loss of GATA1 (located on chromosome X) expression50. Mice transgenically expressing the MYB–GATA1 fusion develop myelodysplasia and leukaemia when endogenous, wild-type GATA1 expression is concurrently downregulated51. Ducassou and co-workers showed that the fusion promotes not only haematopoietic progenitor cell self‐renewal, but also induces a bias toward granulocytic differentiation, consequently to sensitisation towards NGF- and IL-33-induced differentiation52. The skewing towards basophilic differentiation was confirmed in primary human CD34‐positive stem/progenitor cells, where the basophilic markers CD203c and FcϵRI were activated after MYB–GATA1 expression. In vivo experiments using NSG mice led to conclusive evidence that basophilic differentiation is a direct consequence of MYB-GATA1 expression, rather than loss of endogenous GATA152. The increased responsiveness to IL-33 could contribute to the leukaemic phenotype, as previously observed in other myeloproliferative malignancies53. Thus, MYB-GATA1 might promote cell growth, self-renewal and leukaemic transformation of basophilic progenitor cells52.

A case report described a Philadelphia-negative myeloproliferative neoplasm (Ph-MPN) with an uncommonly rapid leukaemic progression, linked to JAK2V617F mutation. This primary myelofibrosis (PMF)-patient developed a peculiar chromosomal rearrangement resulting in a fusion involving EWSR1 and MYB. There are only a few cases reporting fusion of EWSR1 in leukaemia, whereas it is common in soft tissue sarcoma54,55,56. EWSR1 is a FET (FUS, EWS, TAF15) family member whose function is to regulate transcription and mRNA splicing57. Therefore, it seems reasonable to speculate that the EWSR1-MYB fusion could lead to dysregulated MYB transcriptional activity. Indeed, expression of the MYB target gene BCL2 was deregulated in EWSR1-MYB positive PMF, suggesting that molecular alterations involving MYB could increase disease risk in PMF patients58.

AML is the most common form of acute leukaemia in adults59. Although recent advances in genomic characterisations have shed some light on the molecular patterns involved in this cancer, the 5-year survival rate is <70% in children and 35% in adults60,61.

AML is a heterogeneous disease, often characterised by the presence of gene fusions or recurrent mutations in a set of driver genes62. Genomic rearrangements involving the MLL gene, such as MLL–AF4 t(4;11)(q21;q23); MLL–AF9; t(9;11)(p22;q23); MLL–ENL; t(11;19)(q23;p13.3); MLL–AF10 t(10;11)(p12;q23) or MLL–AF6 t(6;11)(q27;q23) are associated with a very aggressive form of leukaemia63,64. MYB has been shown to be a key downstream effector of MLL fusion oncoproteins, suggesting that it could be a target for therapeutic interventions65. Since, as mentioned before, targeting transcription factors with small molecule inhibitors is difficult, the focus has been directed towards proteins that work as co-activators in the MYB network. p300 is a MYB transcriptional co-activator, required for leukaemogenesis66. The small molecule inhibitor Celastrol, a triterpenoid, was used to disrupt the MYB/p300 interaction, therefore interrupting MYB signalling in leukaemic cells. Celastrol did not change MYB expression but inhibited the interaction of the transactivation domain of MYB with the KIX domain of p300. Accordingly, Celastrol strongly inhibited MYB-dependent transcriptional activation of target genes. Celastrol enhanced survival of mice transplanted with patient-derived HoxA9/Meis1-driven AML, confirming that targeting MYB transcription function could be an effective strategy in this leukaemia67. Another compound used to disrupt the interaction between MYB and p300, Naphthol AS-E phosphate, inhibited the expression of the MYB gene itself, as well as that of several MYB-target genes, inducing myeloid differentiation and apoptosis68. The negative effect of Naphthol AS-E phosphate on MYB gene expression could be a consequence of the block of MYB gene autoregulation. Nicolaides et al. showed that human MYB maintains high levels of its expression through an autoregulatory mechanism involving MYB-binding sites in the 5′ flanking region of the MYB gene itself41.

The anti-helminth agent mebendazole exhibited anticancer activity in AML human cell lines by interfering with MYB activity. Short-term exposure to the drug induced changes in the expression level of MYB-regulated genes in cells expressing the MLL-AF9 fusion oncoprotein69. Expression of the MYB oncoprotein was drastically reduced in the presence of low concentrations of the drug in all cell lines analysed, whereas MYB mRNA levels were only reduced after exposure to very high mebendazole concentrations, and only in a few of the cell lines. This suggested that the drug acts mainly at the protein level. Indeed, inhibition of the proteasome reversed MYB protein loss, demonstrating that mebendazole causes proteasomal degradation of MYB by interfering with the heat shock protein 70 (HSP70) chaperone system. Importantly, mebendazole impaired AML cancer progression in vivo69.

5-hydroxy-2-methyl-1,4-naphthoquinone (also known as plumbagin) has been shown to target the transcriptional-activating domain (TAD) of MYB. By using the MYB TAD fused to the Gal4 DBD, the Klempnauer group observed that plumbagin inhibits transcription of a reporter gene containing GAL4-binding sites. Increasing the dosage of ectopically expressed p300, progressively antagonised the effect of plumbagin, demonstrating that the drug interfered with the p300–MYB interaction in AML cells70.

Recently, a peptidomimetic approach to block the activity of MYB was developed by designing an inhibitory peptide called MYBMIM. The MYBMIM inhibitory effect is caused by its ability to disrupt the MYB:CBP/p300 complex. MYBMIM directly binds to the KIX domain of CBP with an affinity similar to the naïve complex, causing its disassembly and reduced MYB-dependent expression of genes whose enhancers are occupied by it. NOD-scid mice engrafted with leukaemia cells treated with the peptide showed significant reduction of cancer burden, which was caused by mitochondrial apoptosis. Furthermore, ChIP analysis revealed a marked loss of the epigenetic mark H3K27ac on super-enhancers regulated by acetylation driven by p300:CBP, and consequent reduced expression of key MYB-regulated genes such as MYC and BCL271.

MYB and paediatric low-grade gliomas (PLGGs)

PLGGs typically present gene fusions, especially related to component of the MAPK pathway, such as BRAF72. MYB rearrangements have been recently discovered in the context of whole-genome sequencing (WGS) and/or RNA-sequencing (RNA-seq) of 249 samples of PLGGs, leading to the identification of recurrent MYB-QKI fusions in angiocentric gliomas73. MYB fused to the RNA-binding protein QKI confers oncogenic properties using three distinct mechanisms. Firstly, the alteration results in the translocation of a super enhancer located in the 3′ untranslated region of QKI upstream the MYB promoter, resulting in its activation. Secondly, the MYB-QKI fusion protein acts as transcription factor, binding and activating the MYB promoter through a positive feedback loop. Thirdly, hemizygous loss of QKI expression caused by the rearrangement of its locus contributes to oncogenesis since it functions as a tumour-suppressor gene74,75,76. Gene-set enrichment analysis (GSEA) revealed that the expression of MYB-QKI fusion was associated with MYB signature genes73. MYB protein structure and its modifications found in tumours are fundamental for its transforming ability. In fact, as already mentioned above, full-length MYB is not endowed with a strong oncogenic activity in vitro, whereas C-terminal truncations are required for its activation77. MYB-QKI breakpoints in MYB intron 9–15 result in C-terminal truncation and oncogenic activation of MYB73.

MYB and cancers of the gastrointestinal tract

80% of colorectal cancers are characterised by MYB overexpression, which is associated with tumour aggressiveness and poor prognosis78,79. MYB overexpression in colon cancer is a consequence of mutations in intron 1 regulatory sequence80. Given the broad presence of the oncoprotein in this cancer, investigators in the Australian Peter MacCallum Cancer Centre engineered a vaccine against the MYB antigen called TetMYB. It is composed of an inactivated MYB protein flanked by the tetanus toxin T cell epitopes cloned into the pVAX1 plasmid vector. The immunotherapeutic role of the pVAX1-Tet-human MYB DNA vaccine was investigated in colon and adenoid cystic carcinoma (ACC) patients, also in combination with the anti-PD-1 antibody BGB-A317 to assess safety and maximum tolerated dose (MTD) in a first-in-human clinical trial81. This approach should overcome limitations caused by epitope/MHC restriction when targeting an endogenous antigen, as its application will not depend upon a need to match the patient’s MHC subtype. The trial, if successful, could pave the way for vaccine treatment not only of colorectal cancers or ACC, but also other MYB-expressing cancers. This clinical trial is based upon preclinical studies of the same Australian group in mice transplanted with MC38 colon adenocarcinoma cells expressing high levels of MYB. Breaking peripheral tolerance with the vaccine strategy enhanced anti-tumour immunity mediated by both CD4+ and CD8+ T cells, without insurgence of autoimmunity, causing a significant suppression of MC38 cancer growth78. MYB alterations have been also observed in pancreatic cancer, where it has been shown to interact with genes required for proliferation, survival and metastasis82.

MYB and breast cancer

MYB has been found bound to more than 10,000 promoters in MCF-7 breast cancer cells and recognised as a key activator of downstream targets, including genes involved in cancer progression and metastasis, such as cyclooxygenase-2 (COX-2), BCL2, BCLXL, JUN, KLF4, NANOG, MYC, and CXCR419. Breast cancer is a heterogeneous disease with a clinical outcome strictly determined by molecular profiles83,84. Over 70% of human breast cancers are oestrogen receptor-positive (ER+) and express MYB85. Gonda and colleagues reported for the first time that inhibition of MYB expression severely impairs the proliferation of ER+, but not ER−, breast cancer cell lines37. The relationship between MYB and ER is also indicated by the expression of MYB in normal, ER+ murine mammary epithelial cells, suggesting a salient role of the MYB transcription factor in mammary cell proliferation and tumour development in the human and mouse systems37,86.

ER+ breast cancer benefits from endocrine therapy (ET), which can reduce local and distant cancer recurrence and mortality rate87,88. ET can be administrated as neoadjuvant, adjuvant or palliative treatment and includes aromatase inhibitors, selective ER modulators (SERMs) such as tamoxifen, and antagonists such as fulvestrant89.

In ER+ve breast cancer patients, MYB expression is oestrogen-dependent, since it was observed that MYB mRNA levels were 5-fold higher 24 h after stimulating breast cancer cells with beta-estradiol, suggesting a strong correlation between the proto-oncogene expression and ER status in cancer19. MYB expression in ER+ve breast cancer cells is regulated at the level of transcriptional elongation, leading to the hypothesis that CDK9 inhibitors could be used to indirectly target MYB in this cancer. Indeed, CDK9 inhibition resulted in apoptotic death of breast cancer cell lines, accompanied by dose-dependent inhibition of the MCL-1 gene and protein expression90. CDK9 inhibitors also impaired cell proliferation and cell cycle progression, inducing arrest at both the G1/S and G2/M phases of the cell cycle. Moreover, this led to the downregulation of MYB target genes involved in cell cycle progression such as CCNB1 and CCNE1, which was reversed by ectopic expression of MYB90.

Breast cancer patients often develop resistance to treatment. Activation of epithelial–mesenchymal transition (EMT) is a mechanism by which breast cancer cells acquire resistance to targeted therapies91. Micro-RNAs have been implicated in the EMT process, particularly the miR-200 family92,93. Following ectopic over expression of miR-200b/c in drug-resistant cells, MYB expression levels decreased, indicating that it is a target of miR-200s. After silencing MYB in an ER+ve breast cancer cell line refractory to tamoxifen therapy, the authors of the study observed that the EMT markers vimentin, ZEB1, and ZEB2 were downregulated, further supporting the hypothesis that MYB is involved in EMT and drug resistance in breast cancer. Indeed, as expected, breast cell line sensitivity to tamoxifen therapy was increased after inhibiting MYB expression94.

MYB and ACC

Stenman and colleagues discovered the translocation t(6;9)(q23;p23) as a genomic hallmark of ACC95. The translocation results in the fusion of the carboxyl-terminus of the MYB oncoprotein to five amino acids (SWYLG) encoded by the last exon of NFIB (Fig. 2)95,96. ACC is characterised by the presence of the MYB-NFIB fusion gene in 30–86% of cases, depending on the study97,98. An important consequence of chromosomal rearrangements in ACC is the translocation of strong enhancers near the MYB, or MYBL1, locus, which activates their transcription99. Rearrangements of the MYB locus have been observed in ACCs of the breast, lungs or glands in different body locations and in cylindromas, suggesting that MYB activation is frequent in exocrine gland tumours98,100,101,102. Another consequence of the chromosomal translocations detected in ACC and other gland tumours is, in some cases, loss of genetic material. In this regard, Mitani and colleagues theorised that two genetic events drive ACC pathogenesis: one involves the generation of fusion genes resulting from reciprocal translocation between chromosome 6q and 9p or other partners, and the other event constitutes a loss of genetic material, denoting the presence of one or more tumour suppressor genes103. Most ACCs do not acquire a large number of genetic changes, typical of other carcinomas104. Over half of ACC cases present chromosome 6 deletions, suggesting an important selection for these alterations in the molecular aetiology of these neoplasms. However, efforts to identify a tumour suppressor gene at these loci in ACC have been unsuccessful to date103,105.Fig. 2: Schematic illustration of the MYB-NFIB fusion gene.The t(6;9) translocation results in a MYB-NFIB gene fusion. Arrows indicate the breaking points.Full size image

MYB-NFIB is a putative oncoprotein, which has been shown to control ACC tumour cell proliferation and spherogenesis106. Intriguingly, the fusion gene is regulated by AKT-dependent signalling downstream of the IGF1 receptor and its expression can be downregulated by IGF1R-inhibition with linsitinib. Furthermore, EGFR and MET signalling also promote growth of ACC cells106. In line with these findings, evidence in patients or xenograft models indicate that monoclonal antibodies targeting IGF1 or EGF receptors could be effective drugs in ACCs expressing the fusion oncoprotein107,108,109. To investigate the implication of the MYB-NFIB fusion gene in ACC, Mitani and co-workers analysed a cohort of 123 salivary carcinomas, including primary ACCs of the salivary gland, metastatic ACCs, non-ACC salivary carcinomas, and normal salivary gland tissues103. Using RT-PCR, validated by fluorescence in situ hybridisation (FISH) analysis, they found that among 89 ACC cases (72 primary ACCs and 17 metastatic), 26 were positive for expression of the MYB-NFIB fusion transcript. Interestingly, none of the 34 non-ACC carcinomas were positive. In addition, 14 different fusion transcripts involving multiple exons of MYB and NFIB were identified. To provide further insights on the role of MYB in this cancer, expression of the wild type or fusion MYB transcripts was quantified. Unsurprisingly, MYB expression was elevated in MYB-NFIB fusion positive ACCs, probably caused by loss of the negative regulatory sequence at the 3′ untranslated region of MYB. Interestingly, the expression of wild type MYB was elevated >40-fold in fusion-negative ACCs compared to non-ACC carcinomas, and only 2-fold lower than fusion-positive ACCs. The authors concluded that whereas genomic rearrangement must be causative of MYB overexpression in fusion positive ACCs, alternative mechanisms may be responsible for MYB overexpression in fusion negative ACCs103. Thus, MYB overexpression is a frequent consequence of the MYB-NFIB fusion in glandular tumours, but can also occur via other mechanisms.

The polyether ionophore monensin was recently identified as a MYB inhibitor using a luciferase-based screen and tested on ACC cell lines derived from ACC patients. These cells were more sensitive to the anti-cancer agent than MYB-expression negative, control cell lines. Monensin suppressed both MYB-NFIB mRNA and protein levels. Moreover, the compound, and related polyether ionophores, also induced differentiation and promoted apoptosis of leukaemic cell lines, suggesting that MYB inhibitors can be effective against solid and liquid malignancies110. Using a chemical screen in Zebrafish, the group of Leonard Zon have demonstrated that retinoic acid is a suppressor of MYB in ACC. All trans retinoic acid (ATRA) treatment of mice bearing patient-derived ACC tumours showed reduced expression of MYB and binding of MYB at translocated enhancers. Importantly, ATRA inhibited the expression of cell cycle related, MYB-target genes. ATRA is used in the clinic for the treatment of promyelocytic leukaemia and has a known safety profile, suggesting that it will be soon used in the context of a clinical trial in ACC patients111.

Identification of actionable target genes downstream of MYB can be a reasonable alternative to avoid negative consequences caused by inactivation of the wild-type MYB transcription factor. Indeed, the potential haematologic toxicity of anti-MYB therapies could be further exacerbated in patients under regimens of chemotherapy and radiotherapy. An important gene axis regulated by MYB is the insulin growth factor and its receptor. Interestingly, insulin growth factor receptor (IGFR) signalling positively regulates MYB-NFIB in ACC, suggesting that MYB and IGFR are engaged in a feed forward loop in cancer112,113. Accordingly, it has been shown that the small molecule inhibitor Linsitinib or the therapeutic antibody Figitumumab reduce the growth of ACC tumours in mouse models and in patients, suggesting that targeting IGFR signalling could be an effective strategy in MYB overexpressing cancers109,112. In an effort to identify new MYB target genes in ACC, our group has generated retroviral vectors expressing wild-type MYB or two MYB-NFIB variants derived from ACC patients. The different MYB isoforms were ectopically expressed in immortalised breast MCF10A cells, and genes up or downregulated were identified by microarrays. GSEA revealed that ATR/BRCA was the top activated downstream pathway, with a significant upregulation of ATR gene expression43. ATR mRNA levels were increased in primary ACCs compared to normal salivary glands. Accordingly, the clinical ATR kinase inhibitor VX-970 caused apoptosis of primary ACC cells in vitro and significant shrinkage of ACC patient-derived xenografts. These results support the theory that acting on downstream target genes/proteins might be a worthy—and even safer—alternative to directly targeting the MYB gene itself43.

Surgery is the first line treatment for ACC, followed by cytotoxic chemotherapy and/or radiotherapy as adjuvant treatments to avoid recurrence. Unfortunately, standard treatments only provide limited benefit in advanced disease, which is usually lethal, with a high rate of recurrence and metastasis. Therefore, new and more effective treatments are urgently needed for these high-risk patients. Previous clinical trials have led to the approval of tyrosine kinase inhibitors (TKI) for the treatment of aggressive forms of solid malignancies, such as thyroid cancer refractory to radio therapy and unresectable hepatocellular carcinoma114,115. Most of the targeted tyrosine kinases are also MYB regulated, such as vascular endothelial growth factor receptors (VEGFRs), fibroblast growth factor receptors (FGFRs), the stem cell factor receptor KIT (c-KIT), FMS-like tyrosine kinase 3 (FLT3), platelet-derived growth factor receptors (PDGFRs), and the proto-oncogene RET95,115,116,117,118,119. Persson and co-workers have recently shown that VEGFA, FGF2, KIT and other genes encoding receptor tyrosine kinases are commonly overexpressed in ACC samples, leading to consider TKIs as credible candidates for the treatment of relapsed/metastatic ACC patients95. However, it has been observed an overall poor response in therapies against these targets in ACC, suggesting that other, more relevant MYB downstream genes should be clinically exploited in this tumour.

MYBL1

MYBL1 is predominantly expressed in the central nervous system (CNS), germinal B-lymphocytes, mammary gland ductal epithelium, and in the testis120,121. It has a key role in spermatogenesis, particularly in cell cycle progression of germ cells through pachynema121,122. MYBL1-null mice are viable, but exhibit growth abnormalities as well as defects in spermatogenesis and female breast development120.

MYBL1 alterations in cancerMYBL1 rearrangements are a hallmark of low-grade gliomas (LGGs), the commonest paediatric CNS neoplasm, arising in children and adolescents114,123. Recent molecular characterisations through WGS have led to the identification of new genetic alterations in LGGs. These studies have identified activation of the MAPK/ERK pathway caused by the duplication of the tyrosine kinase domain (TKD) of the FGFR1 gene and frequent rearrangements of the MYB family members MYB and MYBL1 in diffuse cerebral LGGs124. 8q13.1 gain was observed as a significant recurrent event in diffuse astrocytoma grade IIs. This leads to a duplication of MYBL1 and truncation of its C-terminal NRD, resulting in anchorage-independent growth of NIH-3T3 cells and tumour formation in nude mice125. MYBL1 gene amplification is a distinct alteration of the subtype IDH-wt/H3-wt of diffuse gliomas, together with TERT and BRAF mutations, EGFR and FGFR1 alterations, and other chromosomal aberrations126. Although these alterations are rare, sequencing analysis of uncommon low-grade neuro-epithelial tumours revealed that these pathogenic mutations occur at a high frequency (78%) in this cohort114.Patients with isomorphic diffuse glioma or astrocytoma can harbour copy number alterations of MYBL1 or MYB (13 out of 25 samples, 52%), as assessed with RNA sequencing. Gene fusions accounted for 50% of cases127.ACC is characterised by the chromosomal translocation t(6;9), leading to the expression of the MYB-NFIB fusion gene95. Although MYB is the MYB family member most often involved in this cancer, it was recently demonstrated that a subset of ACCs contains the t(8;9) chromosomal translocation128. This results in the creation of a MYBL1-NFIB gene fusion, which probably functions in a manner similar to MYB-NFIB, given the structural analogies between MYBL1 and MYB. Indeed, tumours with MYB and MYBL1 translocations display overlapping gene expression profiles and clinical outcome, suggesting that the related MYB proteins are interchangeable oncogenic drivers in ACC. The research group that identified the translocation t(8;9), also highlighted a t(8;14) translocation, leading to the fusion of MYBL1 to the RAD51B gene128.In MYB or MYB-NFIB negative subsets of breast ACC tumours, alternative genetic mechanisms of MYB activation have been demonstrated. RNA and WGS unveiled that these cancers could harbour MYBL1 rearrangements, including those between MYBL1-ACTN1 and MYBL1-NFIB102. In these rare triple negative breast cancers (TNBC), the histological pattern was identical to the MYB-NFIB-positive, salivary gland ACCs. The MYBL1 rearrangements were confirmed at genomic level by the FISH technique. The translocation results in an in-frame chimeric transcript containing the DNA-binding and transactivating domains, encoded by exons 1–14, of MYBL1 fused to the exon 9 of NFIB. In addition, another in-frame fusion between MYBL1-ACTN1 was also detected for the first time in ACC samples. The fusion leads to loss of the C-terminus region of MYBL1 due to the fusion of exons 1–8 of MYBL1 with exons 10–21 of ACTN1102.Another organ in which ACC neoplasms can originate is the lung. Primary tracheobronchial ACC is one of the rarest types of lung cancer, accounting for <1% of cases. Pei et al. analysed 7 lung ACCs, documenting that 7 out of 7 cases presented MYB or MYBL1 genes fused with NFIB or, less frequently, with RAD51B101. Primary cutaneous ACCs display a genetic landscape similar to those of salivary glands, showing fusions of either MYB or MYBL1 with the common partner NFIB129.

MYBL2

MYBL2, encoding the transcription factor MYBL2, is ubiquitous and often co-expressed with other MYB members. It has been shown to regulate cell cycle progression, cell survival and differentiation being an essential component of the DREAM complex130,131,132,133. It is also a promoter of cell survival by activating antiapoptotic genes such as BIRC5 (survivin), CLU (ApoJ/clusterin) and BCL2134,135,136,137. MYBL2 has been shown to aid repair of DNA double-strand breaks, supporting genome stability in haematopoietic and pluripotent stem cells138,139. Expression of MYBL2 is important for both normal and transformed cell homoeostasis. This concept is supported by the early embryonic lethal phenotype of MYBL2 knockout mice, due to impaired inner cell mass formation, or suppression of cell cycle progression and cell survival in oesophageal, hepatic, colorectal, and sympathetic nervous system cancer cells in which the expression of MYBL2 has been downregulated140,141,142,143,144,145. The activity of MYBL2 is highly regulated at transcriptional and post-transcriptional levels. Cyclins and their catalytic partners, the cyclin-dependent kinases (Cdks), function as key regulators of the cell cycle146. Cyclin D1 with Cdk4 or Cdk6 has been shown to play an important role at the ‘restriction point’ in the G1 phase of the cell cycle before cells enter into the mitotic cycle, whereas, for the transition from G1 to S phase, cyclin E–Cdk2 complexes are the most critical, and cyclin A–Cdk2 complexes are required during S phase146. MYBL2 is regulated by the transcription factor E2F and required for the expression of cyclin B and cdc2 in G2/M147,148,149. When overexpressed, the tumour suppressor protein p53 induces Waf1/Cip1/p21 protein-dependent cell-cycle arrest and activation of MYBL2 allows cells to escape this block, suggesting that MYBL2 acts at a later stage than Waf1/Cip1/p21 during cell-cycle progression150,151. MYBL2 is a substrate for cyclin A/E–Cdk2 kinase activity and its transcriptional activity is regulated by phosphorylation148,150.Genes involved in the G2/M phase of the cell cycle are activated by MYBL2 switching from the repressive DREAM to the MuvB (MMB) complex136,152,153. MYBL2 is transcriptionally repressed in G1, activated by cyclin A/Cdk2-mediated phosphorylation during S-phase, and subsequently degraded in late G2 in a ubiquitin-dependent manner147,148,154,155. Phosphorylation of MYBL2 occurs at Serine or Threonine residues followed by Proline156. Pin1 isomerase recognises the pSer/pThr-Pro residues altering functions of the MYBL2 protein by inducing conformation changes. Cdk-dependent phosphorylation and Pin1 isomerization induce Plk1 kinase binding to MYBL2. Plk1 phosphorylates the region of MYBL2 containing the transcriptional activation domain (TAD), suggesting that PLK1-induced modification of MYBL2 is crucially required for transcriptional activation of pro-mitotic genes157. Consistent with an important role in cell cycle progression, down-regulation of MYBL2 leads to spindle and centrosome defects, arrest in the G2/M phase of the cell cycle, failure in cytokinesis, polyploidy and apoptosis132,158.

MYBL2 alterations in cancerThe DREAM complex [DP, RB-like, E2F4 and MuvB (synMuv genes, class B)] is a master coordinator of cell cycle-dependent gene expression and the balance between repressive DREAM and activating MYB-MuvB (MMB) complexes is frequently perturbed in cancer159,160,161,162. Increased expression of several components of the MMB complex, including MYBL2 and FOXM1, correlates with aggressive tumour features and poor prognosis144,163. To investigate the clinical relevance of the MYBL2/FOXM1/CDK/PLK1 axis, Werwein et al. used a pan-cancer resource of expression signatures that correlate cancer gene expression and clinical prognosis data, called PRECOG157. Interestingly, among the 50 genes (and their products) analysed, 44 (including MYBL2, FOXM1, CCNA2, and PLK1) were found to be targets of DREAM-mediated repression, while 29 of them were also targets of MMB activation157. Overexpression of MYBL2 disturbs myeloid differentiation and promotes the progression of solid cancers where it is also an indicator of poor prognosis133,142,164,165,166. MYBL2 is frequently overexpressed in malignancies including breast cancer, non-small-cell lung cancer (NSCLC), AML, colorectal cancer, pancreatic ductal adenocarcinoma, and neuroblastoma167,168,169,170,171,172,173,174,175.The molecular mechanisms causing increased expression of MYBL2 in multiple human cancers are still not fully elucidated.

MYBL2 and breast cancer

Alterations of gene expression might be caused by amplification of the MYBL2 locus located in chromosome 20q13176,177,178. 20q13 amplification or copy gains are common in breast cancer and are usually associated with poor prognosis176. Notably, a MYBL2 germline polymorphism causing the Serine-to-Glycine amino acid change S427G is correlated to a high risk of basal-like breast cancer133. Moreover, MYBL2 overexpression was noted in HER2+/ER− and luminal B breast cancer samples, but not in luminal A or normal breast tissue, strongly suggesting a correlation between MYBL2 expression and aggressiveness of breast cancer177. A recent review explains the molecular mechanisms of MYBL2 amplification and new therapeutic opportunities in breast cancers179.

MYBL2, clear cell renal cell carcinoma (ccRCC) and NSCLC

ccRCC is the most frequent renal malignancy180. MYBL2 expression could be used as a biomarker to predict patients’ prognosis in this cancer. MYBL2 was found upregulated in a cohort of 530 ccRCC patients compared to healthy tissues. Of note, upregulated MYBL2 was significantly associated with age and sex of cancer patients, advanced T stage, lymph node and distant metastases, clinical stage and histological grade181. Moreover, a significant correlation between high MYBL2 expression and worse prognosis was established by Kaplan–Meier analysis, indicating that MYBL2 expression is an independent biomarker of progression in ccRCC181.

Another neoplasia characterised by deregulation of MYBL2 is non-small-cell lung cancer (NSCLC). Analysis of MCODE clusters highlighted genes involved in “driver networks” for NSCLC, which include the transcription factors FOXM1, TFDP1, E2F4, SIN3, and MYBL2182. A further study confirmed the potential oncogenic role of MYBL2 in NSCLC. Through chromatin immunoprecipitation (ChIP) assay, researchers identified a direct binding between MYBL2 and the gene Non-SMC CondensinIComplex Subunit H (NCAPH), well-known to have oncogenic properties in lung cancer. A significant correlation between high NCAPH expression and poor prognosis was confirmed, suggesting that targeting the MYBL2-regulated gene could be of potential therapeutic value in this setting169.

MYBL2 and leukaemia

MYBL2 overexpression is a prognostic factor in AML, defining a subset of patients with poor prognosis170,183. This could be linked to the reduced expression of miR-30a, miR-30b and miR-30c, involved in the regulation of haematopoiesis and cell differentiation, which were shown to be expressed at lower levels in MYBL2high AML samples170,184,185. The strong correlation between overexpression of MYBL2 and downregulation of the miR-30 cluster suggests that the micro-RNAs antagonise the expression of MYBL2, or that the latter suppresses miRNAs expression in AML170.

A recent study published in Cell revealed a link between MYBL2 and the protein phosphatase 2A (PP2A) in leukaemia. Morita and co-workers identified a class of small molecule that they called iHAPs—improved heterocyclic activators of PP2A—able to activate a PP2A complex, which suppresses tumour progression. PP2A is an enzyme formed by different subunits; among them, PPP2R1A, PPP2CA, and PPP2R5E are strictly required for antitumor activity186. Using isotope-labelled amino acids (SILAC) and mass spectrometry analysis, substrates dephosphorylated by PP2A in the presence or absence of iHAPs were identified, among which MYBL2. The researchers were able to activate the PP2A complex, usually present in an inactive form in cancers due to the overexpression of inhibitory proteins, and observe dephosphorylation of MYBL2 on Ser241, required for transactivation of cell cycle-related genes, resulting in an irreversible growth arrest of multiple cancer cells. Thus, MYBL2 is centrally involved in cancer cell proliferation and can be indirectly targeted by small molecule-mediated reactivation of the PP2A tumour suppressor protein186.

ConclusionsThe MYB transcription factors are a point of convergence of numerous signalling pathways essential for multiple cellular functions, and their deregulation has been associated with aggressive behaviour of cancer cells. Reflecting the high similarity of protein structures, MYBL1, MYBL2, and MYB are all involved in the control of cell survival, proliferation and differentiation. One could hypothesise that spatio-temporal differences in gene expression during organogenesis and in pathological conditions may determine specific MYB requirements in cells. The ever-expanding number of studies reporting deregulation of MYB family members in the pathogenesis of human cancers is instigating researchers to find new and more efficient methods to target these transcription factors. Direct pharmacological inhibition of MYB or its product MYB, is emerging as a potential therapeutic strategy for both liquid and solid malignancies. Nevertheless, inhibiting MYB could potentially lead to haematopoietic toxicity, indicating that targeting downstream target genes and coactivator molecules might make more clinical sense. Further studies will be required to develop effective therapeutic interventions aiming at suppressing MYB signalling in tumours while minimising risks to patients.

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Download referencesAcknowledgementsY.C. and A.S. are supported by a grant from the Oracle Cancer Trust.Author informationAuthors and AffiliationsDepartment of Life Sciences, Centre for Inflammation Research and Translational Medicine, Brunel University London, UB8 3PH, Uxbridge, UKYlenia Cicirò & Arturo SalaAuthorsYlenia CiciròView author publicationsYou can also search for this author in

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Reprints and permissionsAbout this articleCite this articleCicirò, Y., Sala, A. MYB oncoproteins: emerging players and potential therapeutic targets in human cancer.

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Genome-wide analysis of MYB transcription factors and their responses to salt stress in Casuarina equisetifolia

Yujiao Wang1, Yong Zhang1, Chunjie Fan1, Yongcheng Wei1, Jingxiang Meng1, Zhen Li1 & …Chonglu Zhong1 Show authors

BMC Plant Biology

volume 21, Article number: 328 (2021)

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AbstractBackgroundMYB transcription factors are a kind of DNA binding protein that can specifically interact with the promoter region. Members of MYB TFs are widely involved in plant growth and development, secondary metabolism, stress response, and hormone signal transduction. However, there is no report of comprehensive bioinformatics analysis on the MYB family of Casuarina equisetifolia.ResultsIn this study, bioinformatics methods were used to screen out 182 MYB transcription factors from the Casuarina equisetifolia genome database, including 69 1R-MYB, 107 R2R3-MYB, 4 R1R2R3-MYB, and 2 4R-MYB. The C. equisetifolia R2R3-MYB genes were divided into 29 groups based on the phylogenetic topology and the classification of the MYB superfamily in Arabidopsis thaliana, while the remaining MYB genes (1R-MYB, R1R2R3-MYB, and 4R-MYB) was divided into 19 groups. Moreover, the conserved motif and gene structure analysis shown that the members of the CeqMYBs were divided into the same subgroups with mostly similar gene structures. In addition, many conserved amino acids in the R2 and R3 domains of CeqMYBs by WebLogo analysis, especially tryptophan residues (W), with 3 conserved W in R2 repeat and 2 conserved W in R3 repeat. Combining promoter and GO annotation analysis, speculated on the various biological functions of CeqMYBs, thus 32 MYB genes were selected to further explore its response to salt stress by using qPCR analysis technique. Most CeqMYB genes were differentially regulated following multiple salt treatments.ConclusionsSeven genes (CeqMYB164, CeqMYB4, CeqMYB53, CeqMYB32, CeqMYB114, CeqMYB71 and CeqMYB177) were assigned to the “response to salt stress” by GO annotation. Among them, the expression level of CeqMYB4 was up-regulated under various salt treatments, indicating CeqMYB4 might participated in the response to salt stress. Our results provide important information for the biological function of C. equisetifolia, as well as offer candidate genes for further study of salt stress mechanism.

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BackgroundMYB (v-myb avian myeloblastosis viral oncogene homolog) transcription factor (TF) family is one of the largest transcription factors in plants and gets its name because its structure has a conserved DNA binding region, known as MYB domain. The N-terminal regions of the MYB transcription factor domain are highly conserved, and the domain consists of 1–4 serial and nonredundant imperfect sequence repeats (R1, R2, R3 and R4). Each repeat includes about 50 amino acids, containing a series of highly conserved amino acid residues and interval sequences, wherein the amino acid residues participate in the binding process with DNA in the form of helix-turn-helix (HTH) [1, 2]. MYB proteins can be divided into different classes according to the number of repeats: 1R-MYB (one repeats), R2R3-MYB (two repeats), R1R2R3-MYB (three repeats), and 4R-MYB (four repeats) [3, 4].As regulatory protein, MYB TFs play an important role in plant growth and development. In 1987, Paz-Ares et al. identified the first plant MYB gene in maize, and the research showed that it was related to anthocyanin synthesis, and named it ZmMYBC1 [5]. Since then, the MYB gene had been identified and isolated in many species. Among them, R2R3-MYB TFs had been certified to be widely involved in the regulation of plant secondary metabolism, and acted a key role in the regulation of plant cell differentiation and organ formation [4, 6, 7]. Overexpression of MYB6 in transgenic poplar resulted in significantly increased anthocyanin and procyanidins accumulation, but inhibited the development of secondary cell walls [8]. And Mu et al. found that R2R3 TF AtMYB59 could regulate the cell cycle and root growth of Arabidopsis thaliana [9] and JcMYB1 (R2R3-MYB) played an important role in the abiotic stress response [10]. In addition, MYB30 in defense reaction was important for the regulation of root growth, and LcMYB2 promoted seed germination and root growth under drought stress [11]. It was found that 3R type MYB MYBL2 not only inhibited trichome development, but also inhibited flavonoid biosynthetic [12, 13], and 3R type MYB PhMYBx down-regulated anthocyanin synthesis [14, 15]. Previous study had found that the expression of AtMYB2 was up-regulated in late plant development and participated in the regulation of whole plant senescence [16].MYB family genes are also widely involved in plant responses to hormones and environmental factors, and play an important regulatory role in plant responses to stress. For example, the R2R2-MYB TF AtMYB41 could not only affect cell wall development, but also respond to ABA, drought, and salt stress [17]. Previous studies showed that AtMYB96 enhanced the resistance of A. thaliana to low temperature by promoting the expression of CBFs [18], while AtMYB14 and AtMYB15 participated in low-temperature response by negatively regulating the expression of CBFs [19, 20]. What’s more, AtMYB60 in A. thaliana had been shown to be involved in drought tolerance stress in plants [21]. Recently, ZmMYB3R and GmMYB118 were found that could improve tolerance to drought and salt stress in transgenic plants [22, 23]. Additionally, AtMYB2, AtMYB44 and AtMYB74 enhanced the tolerance of A. thaliana to salt stress [24,25,26], while AtMYB73 played a negative role in plant salt stress resistance [27]. Furthermore, TaMYB73, StMYB30 and GhMYB73 were reported to enhance salt stress tolerance in transgenic plants [28,29,30]. In transgenic tomato plants, SlMYB102 increased the salt tolerance by regulating Na+-K+ homeostasis and ROS balance [31]. Although most MYB genes in response to salt stress belonged to R2R3 type, a few 3R-MYB genes (including OsMYB3R-2 and TaMYB3R1) were involved in the regulation of plant salt stress [32, 33].The Casuarinaceae is a relatively special family of angiosperms, and is relatively distantly related to other plants [34]. C. equisetifolia is widely cultivated in tropical and subtropical regions and have many uses. It is suitable for coastal windbreak and sand fixation, saline-alkali land improvement and afforestation in arid areas. It can also fix nitrogen and provide wood and fuelwood, and is applied in agroforestry [35]. In addition, Casuarina is one of the few plants that thrive on coastal beaches because of its salt resistance and the flexibility of its branches that can withstand typhoons. The availability of the complete Casuarina sequence [36] combined with bioinformatics methods provides an opportunity to conduct a comprehensive, genome-wide analysis of C. equisetifolia MYB genes.The MYB gene family has been extensively studied in monocot and dicot plant. However, current basic knowledge of MYB proteins in C. equisetifolia is still limited. In present study, a total of 182 MYB genes were identified using the known MYB gene sequences from A. thaliana genome. Furthermore, the physical position, phylogenetic relationships, conserved motifs and exon-intron structure were performed. We further analyzed selective pressure, cis-acting element and gene ontology of these genes. Finally, the expression levels of selected CeqMYB genes in roots and shoots under different salt concentrations and treatment times were investigated by using RNA-seq data and qRT-PCR. Based on current data, this is the first report on genome-wide gene family identification in C. equisetifolia. Therefore, the present study provides a starting point to explore the functions of MYB genes in C. equisetifolia, and it also helps to select candidate genes for genetic engineering in C. equisetifolia breeding.ResultsIdentification of MYB genes in C. equisetifolia

The candidate genes with typical MYB or MYB-like domains were preliminarily screened from Casuarina genomic database according to the Hidden Markov Model (HMM) profile of the MYB domain. A total of 182 MYB genes were identified in C. equisetifolia after removing redundant repetitive sequences. Based on the order of gene identifier, CeqMYB genes were named CeqMYB1 to CeqMYB182. The lengths of the protein sequences of CeqMYB range from 104 to 1072 amino acids, and molecular weight vary from 11.08 kDa (CeqMYB153) to 117.93 kDa (CeqMYB158). Moreover, the theoretical isoelectric point (pI) ranged from 4.06 to 10.65. Some other parameters, such as scaffold position, open reading frame (ORF) length and number of domains, were detailed in the Table S1. The predicted subcellular localization data (Table S2) showed that most CeqMYB proteins were predicted to be expressed in the nucleus, while some were localized to chloroplasts (CeqMYB41, CeqMYB114 and CeqMYB148), mitochondria (CeqMYB37), and cytoplasm (CeqMYB5 and CeqMYB23).Phylogenetic trees and group classification of CeqMYB genesA total of 69 1R-MYB proteins, 107 R2R3-MYB proteins, four R1R2R3-MYB proteins, and two 4R-MYB proteins were identified in C. equisetifolia (Table S1). Based on the alignment, two phylogenetic trees were constructed using MYB proteins in A. thaliana and C. equisetifolia (Figs. 1A and Fig. 2). The number distribution of MYB gene in C. equisetifolia was consistent with that in A. thaliana (Fig. 1B). R2R3-MYB protein was the largest subfamily, while the number of 4R-MYB subfamily was the smallest.

Fig. 1Phylogenetic relationships among R2R3-MYB genes in Casuarina equisetifolia and Arabidopsis thaliana. A Putative functions of the MYB proteins in C. equisetifolia based on the phylogenetic tree along with MYBs from A. thaliana. For details of the functions see Table S3. The circular unrooted tree was generated by NJ method with 1000 bootstrap replicates. B The number distribution of MYB gene in C. equisetifolia and A. thalianaFull size imageFig. 2Phylogenetic tree of 1R-MYB, 3R-MYB and 4R-MYB genes in Casuarina equisetifolia and Arabidopsis thaliana. The circular unrooted tree was generated by NJ method with 1000 bootstrap replicatesFull size imageThe first phylogenetic tree (Fig. 1A) contained 125 R2R3-MYB genes of A. thaliana and 107 R2R3-MYB genes of C. equisetifolia. Then, these 107 R2R3-MYB genes in C. equisetifolia were divided into 29 groups (C1 ~ C29) according to the topology of the tree and the classification of the MYB superfamily in A. thaliana (Table S3). C13, C18 and C21 had only 1 member, which was the smallest group, while C15 had 10 members, which was the largest group. In addition, the members of C4, C10, C14, and C22 did not cluster into any group of A. thaliana, indicating that some changes occurred among MYB genes of different species during the evolutionary process. Most groups in our study (C1, C3, C5, C6, etc.) were supported by the previous studies with high bootstrap. For example, AtMYB93, AtMYB92, and AtMYB53 in group C1 regulated root development, and AtMYB49, AtMYB41, AtMYB74, and AtMYB102 in group C3 responded to adversity stress.In the second phylogenetic tree (Fig. 2), a total of 131 MYB proteins (119 1R-MYB, nine 3R-MYB and three 4R-MYB) from C. equisetifolia and A. thaliana were extracted to construct the phylogenetic tree. According to the topology of the tree and classifications in A. thaliana, these 131 MYB proteins were divided into 19 groups (A1 ~ A19). As shown in Fig. 2, one 4R-MYB protein (CeqMYB43) was clustered into the 4R-MYB protein of A. thaliana, three R1R2R3-MYB proteins (CeqMYB104, CeqMYB135 and CeqMYB158) were clustered into five R1R2R3-MYB proteins of A. thaliana.

CeqMYB genes structure and protein motif analysisIn order to have a more comprehensive understanding of the conserved domains of the CeqMYB genes, The Motif Elicitation (MEME) analysis was performed. Twenty conserved motifs were found in the R2R3-MYB and other CeqMYBs (1R-MYB, 3R-MYB and 4R-MYB) proteins of C. equisetifolia (Figs. 3A; Fig. 4A). As shown in Fig. 3A and Table S4, motif 1, motif 2, motif 3, motif 4, motif 9 and motif 10 were found to encode the MYB DNA-binding domain, while the other motifs didn’t have function annotation in R2R3-MYB of C. equisetifolia. A total of 100 of the 107 R2R3-MYB proteins included motif 3, motif 4, motif 2, motif 6 and motif 1. CeqMYB28 was composed of motif 3 and motif 2, motif 10 and motif 17. CeqMYB96, CeqMYB41, CeqMYB180, CeqMYB146, CeqMYB177 and CeqMYB164 clustered in the C29 group had unique motifs, including 9, 19, 10, 4 and 8 in R2R3-MYB proteins of C. equisetifolia. This characteristic was similar to a previous study in Chinese jujube (Ziziphus jujuba Mill.) R2R3-MYB proteins [3]. In addition, the conserved motif of other CeqMYB genes (1R-MYB, 3R-MYB and 4R-MYB) were predicted, different groups had different motifs, and motif 1 was common to all MYB genes in Fig. 4A. Specifically, motif 1 repeated four times in CeqMYB137, but repeated twice in members of A16 group. And motif 5 repeated three times in CeqMYB43. The motifs 17,1,5, and 4 were each repeated twice in CeqMYB87. The similar result was also found in Helianthus annuus L [37]. Furthermore, the result of PFAM and SMART annotation were shown in Table S5, Motif 1, motif 2, motif 5, motif 6, and motif 8 were found to encode the MYB DNA-binding domain and motif 4 encode the MYB-CC type domain, while the other motifs didn’t have function annotation.

Fig. 3Conserved motif and gene structure analysis of the R2R3-MYB proteins in Casuarina equisetifolia. A Groups of R2R3-MYB genes are highlighted with different colored backgrounds, and all motifs were identified by MEME. The different colored boxes represent different motifs and their position in each MYB sequence. For details of the motifs see Table S4. B The exons and introns are indicated by yellow rectangles and black lines, respectivelyFull size imageFig. 4Distributions of conserved motifs gene structure and in CeqMYB genes (1R-MYB, 3R-MYB and 4R-MYB). A The motifs of numbers 1–20 is indicated in different colored boxes. The sequence information of the motifs is provided in Table S5. B The yellow boxes and black lines indicate exons and introns, respectivelyFull size imageTo demonstrate conservation at particular positions, WebLogo was used to investigate further. The results (Fig. 5) showed that there were many conserved amino acids in the R2 and R3 domains of CeqMYBs, especially tryptophan residues (W), with 3 conserved W in R2 repeat. In the R3 repeat, there were only two conserved W residues, and the first W is usually replaced by either leucine (L) or phenylalanine (F) [38], which was replaced by L in this study.

Fig. 5R1, R2 and R3 MYB repeats of the proteins in CeqMYB gene family. A R2 and R3 MYB repeats of R2R3-MYB proteins in C. equisetifolia. B R1, R2 and R3 MYB repeats of 1R-MYB, 3R-MYB and 4R-MYB proteins in C. equisetifolia. The overall height of each stack showed the conservation of the MYB protein sequence at that position. English letters indicate the different type of amino acid residueFull size imageIn order to gain more insights into the structural diversity of MYB TFs, the exon/intron organization of R2R3-MYB and other MYB (1R-MYB, 3R-MYB and 4R-MYB) of C. equisetifolia were demonstrated separately. As shown in Fig. 3B, the 107 R2R3-MYB genes contained different numbers of exons, varying from 1 to 12. We found that most of the R2R3-MYB genes had two (20/107) or three (71/107) exons, while those with 9 and 12 exons existed just one each. In addition, combined with phylogenetic tree classification, it was found that there were 5 genes containing one exon and these 5 genes were clustered in the same group C27. Furthermore, the details of the exon/intron structural analysis of other CeqMYB genes (1R-MYB, 3R-MYB and 4R-MYB) were shown in Fig. 4B. The number of exons in 1R-MYBs ranged from 1 to 11, and the number of exons in 3R-MYBs ranged from 8 to 11. What’s more, the two 4R-MYBs had 9 (CeqMYB87) and 10 (CeqMYB43) exons, respectively. Based on the above observations, it was found that CeqMYB genes clustered in the same group had the same or similar number of exons. For example, CeqMYB genes belonging to the C28 (3 exons) and A14 (6 exons) group had the identical number of exons, while the A7 group had 4 to 6 exons. In brief, the number of exons of MYB genes from C. equisetifolia was quite different, but the closer the phylogenetic trees were, the greater the similarity of gene structure was.

MYB paralogs and orthologsA total of 53 orthologues and 54 paralogues were identified based on the topology of phylogenetic tree and BLASTN methods. The ratio of non-synonymous substitution (Ka) and synonymous substitution (Ks) can reflect the selection pressure in the process of organism evolution. Thus, to explore the role of selection pressure in MYB gene family evolution, Ks values, Ka values, and Ka/Ks ratios of paralogues and orthologues were obtained (Table S6 and Fig. 6). Generally, a ratio of Ka/Ks less than 1 represent purification selection; a ratio of Ka/Ks greater than 1 mean positive selection; a ratio of Ka/Ks equal to 1 indicate neutral selection. The Ka/Ks ratio of all CeqMYB gene pairs was less than 1, of which the Ka/Ks ratio of most orthologues was 0.1–0.3, and that of paralogues was 0.1–0.5 (Fig. 6). The result suggested that purifying selection might have played an important role in the evolution of the MYB genes in C. equisetifolia.

Fig. 6Ka/Ks ratios of paralogs and orthologs. The black lines indicated Ka/Ks equal to 0.1, 0.3 and 0.5. The red dots represented 1R-MYB, 3R-MYB and 4R-MYB genes in C. equisetifolia and A. thaliana. The green dots represented R2R3-MYB genes in C. equisetifolia and A. thalianaFull size imageProfiling of expressed CeqMYB genes and GO annotation analysisBased on transcriptome data, heat maps of CeqMYB genes treated with 200 mM NaCl at different time periods were analyzed (Fig. 7A). Next, the heat map data of 182 MYB genes were clustered into 25 expression patterns for trend analysis (Fig. 7B; Table S7). The CeqMYB genes responded to different time periods after 200 mM NaCl treatment, such as CeqMYB122 and CeqMYB14 were strongly up-regulated at 24 and 168 h after salt treatment, while the expression levels of CeqMYB10 and CeqMYB112 were up-regulated at 1 h after salt treatment and then down-regulated at later time points. Some of paralogues had similar expression patterns; for example, CeqMYB163/− 113 was initially up-regulated and reached a maximum at 6 h, but then decreased gradually. Nevertheless, some of the paralogues showed different expression patterns; for instance, the expression of CeqMYB16 was continuously up-regulated after salt treatment and reached the highest level after 168 h, while its paralogue, CeqMYB140, was highly expressed in 1 h during salt stress.

Fig. 7Expression pattern of 182 CeqMYB genes following NaCl treatment at different time points as determined by RNA-Seq. A The heatmap shows the hierarchical clustering of 182 CeqMYB genes at different time points. The color scale represents log10 expression values, blue represents low expression and red indicates a high expression level (transcript abundance). B Trend analysis of 182 CeqMYB genes expression (25 trends)Full size imageIn order to predict the function of the MYB protein in C. equisetifolia, the GO annotation using a cut-off value of P ≤ 0.05 showed that a total of 131 GO items were enriched during the salt treatment (Table S8). As shown in Fig. 8A, 80% of term were categorized into biological process. Among these terms, nucleus, organelle, binding, biological regulation, cellular process and metabolic process were predominant (Fig. 8B). The analysis of cell component annotation showed that these proteins were mainly located in the nucleus, and the results were consistent with the prediction of subcellular localization. Furthermore, it was found that some CeqMYB genes assigned to the categories associated with development, hormone, and stress response. Seven genes were assigned to the “response to salt stress” category, of which CeqMYB164, CeqMYB4, CeqMYB53, CeqMYB32, CeqMYB114 and CeqMYB71 were also assigned to the categories associated with hormone response. Specially, CeqMYB177 was in the categories associated with development, hormone, and stress response (Fig. 8C; D).

Fig. 8GO enrichment analysis of 182 CeqMYB genes under salt stress. A the GO annotation using a cut-off value of P ≤ 0.05 showed that a total of 131 GO items, including molecular function, biological process, and cellular component. B The numbers of predominant GO items. C Some CeqMYB genes assigned to the categories associated with development, hormone, and stress response. The color gradient represents the size of the P value and the size of circular represents number of CeqMYB genes. The “rich factor” shows the ratio of the number of the CeqMYB genes to the total gene number in certain categories D Seven genes were assigned to the “response to salt stress” category. The grey circular indicated the gene was not involved in the category. The black circular indicated the gene was assigned to relevant categoryFull size imageIn summary, combined with the expression pattern after salt treatment and GO annotation analysis, 32 CeqMYB genes were selected for further analysis.Promoter analysisThe cis-element analysis of 32 selected CeqMYB genes were shown in Fig. 9, O2-site involved in zein metabolism regulation was found in the promoters of 4 CeqMYB genes. The differentiation of the palisade mesophyll cells (HD-Zip 1) and cell cycle regulation (MSA-like) element were found in the CeqMYB13 and CeqMYB117 promoter, respectively. Additionally, the meristem expression (CAT-box), seed-specific regulation (RY-element) and endosperm expression (GCN4_motif) were also identified in the promoters of the CeqMYB genes. Many hormone-responsive elements were identified, the auxin-responsive element (TGA element and AuxRR-core), the SA-responsive element (TCA element), the MeJA-responsive element (CGTCA motif and TGACG motif), the gibberellin-responsive element (TATC-box, GARE-motif and P-box) and the ABA-responsive element (ABRE) were found in the promoters of 12, 14, 25, 20 and 23 CeqMYB genes, respectively. In addition, stress related cis- elements including MBS (drought induced response element), LTR (low temperature response element), ARE (anaerobic induced response element), GC-motif (anoxic specific inducibility element) and TC-rich (defense and stress response element) were also identified in promoter regions of 32 selected CeqMYB genes. Therefore, the CeqMYB genes might be transcriptionally regulated under different abiotic stresses.

Fig. 9Cis-acting elements analysis of 32 selected CeqMYB genes in promoter region. Number of each cis-acting element in the promoter regionFull size imageValidation of CeqMYB genes expression following salt treatmentAccording with the expression pattern after salt treatment and GO annotation analysis, the expression of 32 selected CeqMYB genes in root and shoot were detected by qRT-PCR after different concentrations of NaCl were used to treat the clone A8 seedlings for different time points. In addition, the specific primers of qRT-PCR were listed in Table S9.Fig. S1 showed that the expression of 90.6% (29/32) MYB genes was induced/repressed under different concentrations of NaCl treatment in C. equisetifolia roots. For example, expression of CeqMYB18, CeqMYB113, CeqMYB163, CeqMYB177 were up-regulated and peaked at 400 mM. Furthermore, expression of 16 genes peaked at different concentrations (Fig. 10). For example, CeqMYB31 and CeqMYB90 were up-regulated under low salt treatment and reached the maximum at 200 mM, but then dropped subsequently. Moreover, CeqMYB90 were significantly up-regulated more than 4-fold. In addition, the root response in salt stress at 200 mM NaCl shown in Fig. S2, all members of selected CeqMYBs can make relevant stress. Nine genes (CeqMYB14, CeqMYB16, CeqMYB31, CeqMYB32, CeqMYB37, CeqMYB71, CeqMYB97, CeqMYB122 and CeqMYB165) were up-regulated at 24 h and 168 h, whereas only CeqMYB164 was repressed with increasing time. Similar results were obtained in the paralogous (CeqMYB113/− 163), the expression levels were significantly up-regulated by high salinity treatment (400 mM) and at the time of 1 h in roots (Fig. 10 and Fig. S2).

Fig. 10Relative expression of 22 CeqMYB genes following NaCl treatment at different concentrations in roots as determined by qRT-PCR. The Y-axis and X-axis indicated relative expression levels and salt concentration of stress treatment, respectively. Mean values and standard deviations (SDs) were obtained from three biological and three technical replicates. The error bars indicate standard deviation. **P < 0.01 and *P < 0.05Full size imageNext, we analyzed the CeqMYB genes expression profile in shoots after treating at different concentrations of NaCl and at the same concentration for different time. Of the 32 CeqMYB genes, 15 were up-regulated at different concentrations, while 16 genes were down-regulated, compared with untreated seedlings (Fig. S3). The 16 genes were intensely up-regulated and peaked at low salinity (100 mM), and were then distinctly down-regulated (Fig. 11A). CeqMYB113 (more than 60-fold), CeqMYB138 (more than 15-fold), CeqMYB108 (more than 4-fold), CeqMYB112 (more than 4-fold) and CeqMYB63 (more than 6-fold) were strongly up-regulated in response to NaCl treatment at 100 mM. To further investigate the response of CeqMYB genes in shoots to salt stress, different time periods of salt treatment were used. From these, the expression level of CeqMYB97 did not change significantly, 8 genes were induced and peaked at 24 h, and 3 genes were suppressed at different time points (Fig. S4). Furthermore, Fig. 11B shown that 15 of 32 CeqMYB genes were expressed and peaked at 1 h, indicating a possible role for these genes in immediate/early responses of seedlings to osmotic stress. CeqMYB113 and CeqMYB163 were typical of this trend, the expression of which remained relatively unchanged at later time points but was strongly up-regulated by about 15-fold at 1 h. In short, most CeqMYB genes were up-regulated in root and shoot by multiple NaCl treatment, suggesting these genes may play important roles in salt stress response.

Fig. 11Relative expression of some CeqMYB genes following multiple NaCl treatment in roots as determined by qRT-PCR. A The expression level of 12 CeqMYB genes were up-regulated and peaked at 100 mM under different salt concentrations treatment. The Y-axis and X-axis indicated relative expression levels and salt concentration of stress treatment, respectively. B The expression level of 15 CeqMYB genes were up-regulated and peaked at 1 h following 200 mM NaCl treatment. The Y-axis and X-axis indicates relative expression levels and the time courses of stress treatments, respectively. Mean values and standard deviations (SDs) were obtained from three biological and three technical replicates. The error bars indicate standard deviation. **P < 0.01 and *P < 0.05Full size imageDiscussionMYB genes family is one of the largest transcription factors in plants. And MYB genes play important roles in many physiological processes of plants, such as cell cycle, primary metabolism, secondary metabolism, environmental response and stress response [4, 7, 38, 39]. So far, this is the first systematic study of the gene families in C. equisetifolia using bioinformatics tools and expression profiles based on the sequenced C. equisetifolia genome.In this present study, a total of 182 CeqMYB genes were identified in the C. equisetifolia genome, and the distribution trend of CeqMYB members was similar to that reported in A. thaliana (Fig. 1B). The phylogenetic relationship of MYB gene family in C. equisetifolia and A. thaliana was studied (Figs. 1 and 2). Phylogenetic trees showed that some MYB genes in C. equisetifolia and A. thaliana formed their own independent clusters, which indicated that two species had a conserved evolutionary process. Moreover, not all groups of CeqMYB genes contain AtMYB genes. For example, the C4 group does not contain any AtMYB, reflecting the requirements of species to adapt to their specific environment [40].. The most closely related MYB genes may share a similar function. Previous studies have reported that AtMYB44 enhanced transgenic soybean tolerance to drought/salt stress by positively regulating abscisic acid (ABA) signaling to induce stomatal closure [41], and AtMYB73 played a negative role in plant tolerance to salt stress [27]. AtMYB44 and AtMYB73 were clustered in the same group, suggesting that CeqMYB130/− 7/− 10/− 129/− 103 in C27 group responded to salt stress.Furthermore, the conserved motif and gene structure of 182 CeqMYB genes were analyzed (Figs. 3 and 4). The number and distribution of conserved motifs and exon/intron structures were different in CeqMYB genes. Among them, 4 CeqMYB genes had only one motif, and the maximum had 10 motif elements. The motif distribution of the same group of MYB was relatively consistent, most motif elements were concentrated and regularly distributed at the N-terminal, and a few (such as motif 18 and motif 17 in R2R3-MYB) were irregularly distributed at the C-terminal, indicating that CeqMYB genes with a close evolutionary relationship had similar functions. Some motifs appeared more frequently, such as motif 4 and motif 2, reflecting their importance to the function of CeqMYB protein. In addition, the members of the CeqMYB genes were divided into the same groups with mostly similar gene structures. Combined with previous studies [42, 43], it was also found that the number of exons in most MYB genes did not exceed two introns. On the whole, the differences in the number, type and distribution of the conserved motifs and exon/intron structures in the sequences might reveal the different functions of each gene. Ka/Ks can reflect the selection pressure in the process of biological evolution. Ka/Ks analysis was performed on all the identified homologous pairs, and the results showed that all the Ka/Ks ratios were less than 1 (Fig. 6), indicating that the MYB gene was mainly affected by purifying selection during evolution (Table S6).Many MYB proteins are involved in the response of plants to adverse growth environment, some of which were closely related to the regulation of plant salt stress. Recent research reported that GhMYB108-like would play important regulatory role in response to drought and salt stresses based on quantitative expression analysis [44] and overexpression of TaMYB344 in tobacco enhanced the tolerance of plant to drought, high temperature and salt stress [45], while overexpression of VcMYB4a in blueberry callus enhanced sensitivity to salt, drought, cold, freezing, and heat stress [46]. Based on transcriptome data, we analyzed the expression patterns of 182 CeqMYB genes in response to 200 mM NaCl treatment at different time periods, and divided them into 25 groups according to different expression patterns (Fig. 7). Moreover, analysis of the molecular function annotations revealed that seven CeqMYB genes responded to salt stress (Fig. 8). From these, we selected 32 MYB genes to further explore their response to salt stress. Promoter analysis (Fig. 9) showed that 24 of the 32 selected CeqMYB genes harbored ABRE cis-regulatory elements involved in ABA responsiveness in their promoters. The auxin-responsive element (TGA-element and AuxRR-core) were also identified in the promoters of the 11 selected CeqMYB genes. Studies had shown that ABA signaling pathway played an important role in MYB-mediated salt tolerance. Overexpression of TaMYB33 could enhance drought and salt tolerance in Arabidopsis thaliana through ABA-mediated regulation of stress response signals [47]. In addition, the R2R3-type MYB TF encoded by MULTIPASS (OSMPs) were involved in plant hormone and cell wall synthesis while responding to high salinity signals [48]. These results suggested that MYB TFs can enhance salt tolerance of plants by mediating the signaling of plant hormones.And the elucidation of gene expression patterns can provide important clues about gene function. The expression levels of 32 MYB genes were examined in the root and shoot of C. equisetifolia under various NaCl concentrations and time points under salt stress. The expression of 22 genes in roots and 15 genes in shoots were up-regulated after different concentration of NaCl treatment (Fig. S1; Fig. S3). Specially, expression level of CeqMYB16, CeqMYB37 and CeqMYB56 did not change significantly in root, but down-regulate in shoots. And CeqMYB71 were down-regulated at different concentration in root and shoot. Moreover, the expression level of some CeqMYB genes were up-regulated in root under salt stress, but down-regulated in shoots. The similar result was observed in Helianthus annuus [37], suggesting that some MYB genes were specifically expressed in roots. Some paralogous pairs exhibited similar expression patterns in the same tissue. For example, CeqMYB7/− 10 peaked at 300 mM NaCl in roots, but dropped to less than half that of CK at different concentration of NaCl treatment in shoots. Most genes with the same number of exons had similar expression patterns, such as CeqMYB7/− 10 contained one exon and CeqMYB4/− 16/− 32 contained 3 three exons (Fig. S3). Furthermore, qRT-PCR experiments and RNA-Seq data analysis showed that most CeqMYB genes were up-regulated at different time points following salt treatment in roots and shoots (Fig. S2; Fig. S4), consistent with previous studies such as that reported by Zhou et al. who found that some MYB genes in oil palm were induced at 24 h or/and 48 h by 300 mM NaCl treatment [49]. At least 8 genes were expressed in peanut roots under salt stress by qRT-PCR analysis [50]. In addition, rapid induction of AtMYB41 expression in response to osmotic and salt stress [51], and transgenic plants overexpressing AtMYB74 displayed hypersensitivity to NaCl during seed germination [26]. CeqMYB4, CeqMYB98, CeqMYB72, AtMYB41 and AtMYB74 were clustered in the same group, which suggested that these three CeqMYB genes responded to salt stress. In this study, CeqMYB4, which was a homologous pair of AtMYB74, was strongly up-regulated by about 10-fold at 1 and 24 h. It once again showed that CeqMYB4 played an important role in salt stress. Similarly, most CeqMYB genes were up-regulated to some extent following NaCl treatment, indicating a possible crucial role in response to salt stress.ConclusionsIn this study, 182 MYB genes were identified in the genome of C. equisetifolia. A comprehensive bioinformatics analysis was performed to investigate phylogenetic relationships, conserved motifs, gene structure, and promoter analysis. GO annotation analysis of CeqMYB genes in C. equisetifolia revealed that seven CeqMYB genes were assigned to the “response to salt stress” category. Combined with expression profile analysis by RNA-Seq data, 32 MYB genes were selected to further explore their response to salt stress. Expression profiling of selected 32 genes in root and shoot were detected by qRT-PCR after different concentrations of NaCl were used to treat seedlings for different time point. The expression levels of most selected MYB genes were up-regulated in shoots and roots at different treatment. Moreover, the expression level of CeqMYB4 was up-regulated under various salt treatments, indicating CeqMYB4 might participated in the response to salt stress. The information provided by these results may be helpful for further functional analysis of CeqMYB gene to elucidate its salt stress mechanism in C. equisetifolia.Materials and methodsSequence retrieval and gene identificationThe Casuarina genome data was downloaded from online website (http://forestry.fafu.edu.cn/db/Casuarinaceae/). MYB genes were identified according to previous research methods [3, 52]. The HMM profile of MYB TFs (PF00249) was downloaded from Pfam protein family database (http://pfam.xfam.org/), then used it as query (P < 0.001) for the identification of all putative CeqMYB genes. Finally, all candidate MYB genes were manually screened by the Pfam database (http://pfam.janelia.org/), the NCBI Conserved Domain database (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) and the SMART database (http://smart.embl-heidelberg.de/). A. thaliana genome sequences were obtained from the Phytozome database (http://www.phytozome.net/). To analysis the number of amino acids, open reading frame (ORF) length, molecular weight (MW) and isoelectric point (pI) for each MYB gene by using ExPASy (http://www.expasy.ch/tools/pi_tool.html). In addition, through online website WoLP PSORT (https://wolfpsort.hgc.jp/), predict the subcellular localization of CeqMYB deduced proteins.Multiple sequence alignment and phylogenetic tree constructionMYB deduced proteins in C. equisetifolia were aligned with AtMYBs using ClustalX 2.11 [53, 54] software with default parameters. A neighbor-joining (NJ) phylogenetic analysis was conducted by MEGA7 based on the alignment. Bootstrap analysis with 1000 replicates was performed to calculate the reliability of the NJ tree [55].Exon–intron structural and conserved motif analysisIn order to map the gene structure of exon-intron distribution of MYB gene, the online Gene Structure Display Server (http://gsds.cbi.pku.edu.ch) was used. For this purpose, CDS of each MYB gene and its corresponding genomic DNA sequence need to be uploaded. The MEME online program (http://meme-suite.org/tools/meme) was employed to analysis conserved motifs of MYB superfamily members in C. equisetifolia. The parameters for performing this analysis were as follows: number of repetition = any; maximum number of motifs = 20; optimum motif length = 6–200 residues. And the each of the putative motifs was annotated by searching Pfam and SMART.Ka and Ks analysis of homologous pairBased on the method from the study [56], defined paralogs. And the method was conducted by working a BLASTN [57] for all nucleotide sequences for each species. A pair of matching sequences that aligned exceed 300 bp and the identity ran over 80% were defined as pairs of paralogs in C. equisetifolia. The synonymous (Ks) and non-synonymous (Ka) substitutions per site between gene pairs were calculated by DnaSP v5.0 software [58].Gene ontology (GO) annotation analysisGene ontology (GO) analysis was carried out for the CeqMYB genes from agriGO database (http://systemsbiology.cau.edu.cn/agriGOv2/index.php). All the 23,397 genes of C. equisetifolia were taken as the reference set and CeqMYB genes for both samples were taken as the test set. The results were divided into three categories, namely molecular function, biological process, and cellular component.Expression profiling of CeqMYB genesThe expression profile data were downloaded from the Short Read Archive of the NCBI database (project accession number SRP064226) for expression analysis of C. equisetifolia root in different periods of salt treatment. The raw read counts for each transcript were calculated using Htseq-count and then normalized to transcripts per million (TPM). A heatmap was generated and visualized using the TBTOOLS software [59], the color scale shown represents TPM counts, and the ratios were log2 transformed. R software (https:// www.r-project.org) was used for the clustering analysis.Putative promoter Cis-acting element analysisTo further study the regulatory mechanism of the CeqMYB genes in the abiotic stress response, many cis-acting elements related to plant growth and development, phytohormonal response, and abiotic and biotic stress responses were identified through PlantCARE program. The upstream 1500 bp region of the translation start site of the CeqMYB genes were download from the Casuarinaceae Database. The PlantCARE program was used to screen cis-elements in putative. The elements involved in plant growth and development, hormone response, abiotic and biological stress response were summarized.Plant materials and salt treatmentsThe C. equisetifolia clone A8 (bred by the Zhanjiang Forestry Research Institute, selected from a commercial plantation in 1980s, which has been commercialized now, no any required permission for its sample collection and use) was preserved and cultivated by the Research Institute of Tropical Forestry, Chinese Academy of Forestry. Rooted cuttings of the clone A8 cultured in a growth chamber for 3 months were prepared for the experiment. For salt treatments, roots and shoots were harvested at 0, 1, 6, 24 and 168 h after 200 mM NaCl treatment, respectively. Furthermore, various concentrations (0, 100, 200, 300 and 400 mM NaCl) solution was poured over the culture medium vermiculite and black soil. The roots and shoots were harvested following 24 h of salt treatment and immediately frozen in liquid nitrogen, and transferred to an ultra-low temperature freezer for storage at-80 °C prior to needed for RNA extraction.RNA extraction and qRT-PCR analysisTotal RNA was extracted from roots using the Aidlab plant RNA kit (Aidlab Biotech, Beijing, China) based on specifications. The integrity and concentration of the RNA was verified by 1% agarose gel electrophoresis and NanoDrop™ One/OneC (ThermoFisher Scientific, USA). The first strand cDNA was synthesized by PrimerScript RT MasterMix (Takara, Tokyo, Japan) according to the manufacturer’s instructions. qRT-PCR was performed on an LightCycler480 II Real-Time PCR system (Made in Switzerland) using TB Green Premix Ex Taq II (TaKaRa Biotechnology Co. Ltd., Dalian, China) with a 20 μL sample volume. And each reaction mixture contained 2.0 μl of diluted cDNA, 0.8 μl of each primer, 10.0 μl of TB Green Premix Ex Taq II, and 6.4 μl of RNase-free water. qPCR reaction cycling conditions were set as per the manufacturer’s instructions for TB Green Premix Ex Taq II. Each sample was conducted three times biologically using replicate. The relative expression level of each gene was calculated as 2-ΔΔCT [60] compared with untreated control plants that were set as 1. Specific primers for CeqMYB genes were designed by Primer Premier 5.0 software and the EF1α was used as housekeeping gene [61]. Statistical analysis and drawing by GraphPad 8 software [62].Statistical analysisStatistical significance was performed using a paired Student’s t test by JMP 8 software. The mean values and standard deviations (SDs) were calculated from three biological and three technical replicates, and significant differences relative to controls are indicated at **P < 0.01 and *P < 0.05.

Availability of data and materials

Raw Illumina sequence data were deposited in the Short Read Archive of the NCBI database (project accession number SRP064226). The datasets supporting the results of this article are included in the article and Additional files.

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Download referencesAcknowledgementsNot applicable.FundingThis work was supported by a grant from the Specific Program for National Non-profit Scientific Institutions (CAFYBB2018ZB003), a project funded by the National Natural Science Foundation of China (Grant No. 31770716). The fundings body was not involved in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.Author informationAuthors and AffiliationsResearch Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, 510520, ChinaYujiao Wang, Yong Zhang, Chunjie Fan, Yongcheng Wei, Jingxiang Meng, Zhen Li & Chonglu ZhongAuthorsYujiao WangView author publicationsYou can also search for this author in

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PubMed Google ScholarZhen LiView author publicationsYou can also search for this author in

PubMed Google ScholarChonglu ZhongView author publicationsYou can also search for this author in

PubMed Google ScholarContributionsConceived and designed the experiments: YJW, CLZ and YZ. Performed the experiments: YJW and YCW Analyzed the data: YJW, JXM and ZL. Wrote the paper: YJW. Participated in the design of this study and revised manuscript: YJW, CJF and YZ. The authors read and approved the final manuscript.Corresponding authorCorrespondence to

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Additional informationPublisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary InformationAdditional file 1: Figure S1. Relative expression of 32 selected CeqMYB genes following NaCl treatment at different concentrations in roots by qRT-PCR. The Y-axis and X-axis indicated relative expression levels and salt concentration of stress treatment, respectively. Mean values and standard deviations (SDs) were obtained from three biological and three technical replicates. The error bars indicate standard deviation. **P < 0.01 and *P < 0.05.Additional file 2: Figure S2. Relative expression of 32 selected CeqMYB genes following NaCl treatment at different time periods in roots by RNA-Seq. The heatmap shows the hierarchical clustering of 32 CeqMYB genes at different time points. The color scale represents log10 expression values, blue represents low expression and red indicates a high expression level (transcript abundance).Additional file 3: Figure S3. Relative expression of 32 selected CeqMYB genes following NaCl treatment at different concentrations in shoots by qRT-PCR. The Y-axis and X-axis indicated relative expression levels and salt concentration of stress treatment, respectively. Mean values and standard deviations (SDs) were obtained from three biological and three technical replicates. The error bars indicate standard deviation. **P < 0.01 and *P < 0.05.Additional file 4: Figure S4. Relative expression of 32 selected CeqMYB genes following NaCl treatment at different time periods in shoots by qRT-PCR. The Y-axis and X-axis indicates relative expression levels and the time courses of stress treatments, respectively. Mean values and standard deviations (SDs) were obtained from three biological and three technical replicates. The error bars indicate standard deviation.Additional file 5: Table S1. Details of the identified CeqMYB genes. Table S2 The prediction of subcellular localization in CeqMYB genes. Table S3 Putative functions of the MYB proteins in Casuarina equisetifolia. Table S4 Detailed information for the 20 motifs in the R2R3-MYB proteins of Casuarina equisetifolia. Table S5 Detailed information for the 20 motifs in the 1R-MYB, 3R-MYB and 4R-MYB proteins of Casuarina equisetifolia. Table S6 Ka/Ks ratios of gene pairs in Casuarina equisetifolia. Table S7 Heat map data of 182 MYB gene family in Casuarina equisetifolia. Table S8 Gene ontology of the of MYB gene family in Casuarina equisetifolia. Table S9 List of primer sequences used for qRT-PCR analysis of 32 selected CeqMYB genes.Rights and permissions

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Reprints and permissionsAbout this articleCite this articleWang, Y., Zhang, Y., Fan, C. et al. Genome-wide analysis of MYB transcription factors and their responses to salt stress in Casuarina equisetifolia.

BMC Plant Biol 21, 328 (2021). https://doi.org/10.1186/s12870-021-03083-6Download citationReceived: 05 April 2021Accepted: 01 June 2021Published: 08 July 2021DOI: https://doi.org/10.1186/s12870-021-03083-6Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard

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Keywords

Casuarina equisetifolia

MYB transcription factorGO annotation analysisSalt stress

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BMC Plant Biology

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【学术前沿】Plant Cell | 邓兴旺团队揭示转录因子MYB112连通光和生物钟信号调控幼苗…_澎湃号·政务_澎湃新闻-The Paper

沿】Plant Cell | 邓兴旺团队揭示转录因子MYB112连通光和生物钟信号调控幼苗…_澎湃号·政务_澎湃新闻-The Paper下载客户端登录无障碍+1【学术前沿】Plant Cell | 邓兴旺团队揭示转录因子MYB112连通光和生物钟信号调控幼苗…2023-06-20 17:01来源：澎湃新闻·澎湃号·政务字号光和生物钟分别作为重要的环境信号和植物内源信号，协作调控植物的生长发育。在自然界中，处于黑暗环境的幼苗进行暗形态建成，下胚轴快速伸长，子叶闭合黄化，产生顶端弯钩，有利于幼苗穿破土壤而进入光照环境。光照环境下幼苗转而进行光形态建成，下胚轴伸长受到抑制，子叶张开转绿，开始进行光合作用。生物钟作为植物内源计时机制，可以使植物感知并预测环境光信号的昼夜节律变化，进而调控基因的节律表达，使植物得以调整自身形态建成的节律性以适应周期变化的光信号，从而增强植物的环境适应性。MYB转录因子家族是植物最大的转录因子家族之一，其中R2R3型MYB转录因子（DNA结合域含2个MYB重复序列）广泛参与调控植物特异的生物学进程，如光形态建成、植物次生代谢、生物和非生物胁迫响应等。虽然拟南芥R2R3-MYB转录因子家族包含多达126个基因，但这些基因是否参与连通光和生物钟信号目前仍不清楚。2023年6月19日，南方科技大学生科院生物系长期杰出访问教授邓兴旺院士团队在The Plant Cell发表了题为“MYB112 Connects Light and Circadian Clock Signals to Promote Hypocotyl Elongation in Arabidopsis”的研究论文，鉴定到一个连通光信号和生物钟信号的关键转录因子MYB112，揭示了光信号和生物钟信号产生联系并调控拟南芥光形态建成的新机制。该研究发现，R2R3-MYB转录因子MYB112是拟南芥光形态建成的负向调节因子（图1A），其mRNA及蛋白在光照条件下积累。MYB112能够与光形态建成的核心抑制子PIF4（PHYTOCHROME-INTERACTING FACTOR 4）蛋白直接互作，增强PIF4对下游靶基因YUCCA8、IAA19和IAA29的转录激活能力。研究人员进一步鉴定了MYB112的关键靶基因，MYB112能够直接结合在LUX（LUX ARRHYTHMO，编码生物钟中央振荡器的核心组分）的启动子上并抑制LUX的转录，减弱LUX对PIF4转录的抑制作用，从而促进PIF4的转录。最后，该研究发现在昼夜循环的条件下，MYB112主要是在下午促进PIF4转录本的积累并增强PIF4蛋白的转录激活能力，最终促进幼苗的下胚轴伸长。综上，该项研究揭示了MYB112连通光和生物钟信号从而调控拟南芥光形态建成的分子机制（图1B）。图1 昼夜循环下MYB112调控拟南芥下胚轴伸长的分子机制南科大生科院已出站博士后蔡宇鹏（现在中国农业科学院作物科学研究所工作）和博士研究生刘永庭为本文共同第一作者；生物系邓兴旺教授和李健研究助理教授为本文共同通讯作者；南科大为论文第一单位。华南农业大学王海洋教授和南京农业大学许冬清教授参与指导本工作，北京市农林科学院范阳阳博士完成了本工作中的生信分析。本项研究得到了国家自然科学基金委、南方科技大学、广东省普通高校植物细胞工厂分子设计重点实验室等的资助。论文链接：https://doi.org/10.1093/plcell/koad170原标题：《【学术前沿】Plant Cell | 邓兴旺团队揭示转录因子MYB112连通光和生物钟信号调控幼苗光形态建成的分子机制》阅读原文特别声明本文为澎湃号作者或机构在澎湃新闻上传并发布，仅代表该作者或机构观点，不代表澎湃新闻的观点或立场，澎湃新闻仅提供信息发布平台。申请澎湃号请用电脑访问http://renzheng.thepaper.cn。+1收藏我要举报查看更多查看更多开始答题扫码下载澎湃新闻客户端Android版iPhone版iPad版关于澎湃加入澎湃联系我们广告合作法律声明隐私政策澎湃矩阵澎湃新闻微博澎湃新闻公众号澎湃新闻抖音号IP SHANGHAISIXTH TONE新闻报料报料热线: 021-962866报料邮箱: news@thepaper.cn沪ICP备14003370号沪公网安备31010602000299号互联网新闻信息服务许可证：31120170006增值电信业务经营许可证：沪B2-2017116© 2014-2024 上海东方报业有限公

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【学术前沿】Plant Cell | 邓兴旺团队揭示转录因子MYB112连通光和生物钟信号调控幼苗…_澎湃号·政务_澎湃新闻-The Paper

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