Nature Genetics发表文章解析现代小麦的起源 5月1号Nature Genetics发表了两篇小麦的文章。前几天我们还念叨着一篇文章即将在NG发表( 厉害了|小麦大规模外显子测序 )，没成想在五一假期的第一天就上线了，而且还是双黄蛋，其中一篇“ Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome ”，我们已邀请一作贺飞给我们介绍这篇文章。今天我们要说的的是另外一篇文章“ Tracing the ancestry of modern bread wheats ”。 简介 利用外显子组测序技术从全世界范围内选出的大约500个小麦品种进行基因分型，来探索10000年的杂交、选择、适应和植物育种如何塑造了现代面包小麦的基因组成。 在基因、染色体和亚基因组水平上观察到大量的遗传变异，并利用这些信息来破译现代小麦的可能起源、迁移以及自驯化以来选择的等位基因变异。 我们的数据支持先前的小麦进化模型（reconciled model of wheat evolution），并为未来的育种改良提供了新的途径。 背景 面包小麦具有三个密切相关的亚基因组(AABBDD)组成的异源六倍体基因组。 它被认为起源于两次多倍化事件: 第一次是野生四倍体小麦(Triticum urartu Tumanian ex Gandilyan，AA)与未发现的节节麦(Aegilops speltoides Tausch)谱系(BB)杂交形成的四倍体，距今约50万年; 第二次是原始四倍体杂种(AABB)与野生二倍体节节麦(DD)杂交形成的六倍体，约10,000 年。 考古植物学的证据表明，由此产生的六倍体小麦是在从以色列、约旦、黎巴嫩、叙利亚到土耳其东南部、伊拉克伊朗的西部一个地区新月沃土被驯化的。 因此，现代栽培的面包小麦是至少一万年来人类在驯化和栽培(改良和繁殖)过程中选择的产物。 今天，它们包括适应各种环境的高产品种，从尼日利亚、澳大利亚、印度和埃及的低湿度地区到南美洲等高湿度地区。 结果 为了探索目前可获得的小麦基因库中存在的遗传多样性的起源和模式，我们构建了一个由分布在全世界范围内的487个小麦材料组成的群体，包括野生二倍体和四倍体近亲、驯化的四倍体和六倍体地方品种、古老品种和现代优良品种。 将这些品系的外显子组捕获序列数据映射到中国春参考基因组序列，发现了620,158个高可信度遗传变异，分布在41,032个小麦基因上。 该变异数据集提供了小麦基因组多样性在不同尺度(基因、区域、染色体和基因组)的全面综述，并代表了丰富的遗传信息来源，可供学术界和农业研究界利用。 系统发育和主成分分析(PCAs)揭示了三个主要因素驱动文中所使用小麦品系的多样性分区(图2) : 春化要求(冬季 vs 春季) ，历史群体(i 至 IV，最古老到最新: 从古老的地方品种到现代精英品系)和地理起源(欧洲，亚洲，大洋洲，非洲和美洲)(图2a )。 在基于大小、代表性和统计支持度选择的11个主要树支中，单系保护的排列检验证实了这三个因子的强大作用( P 1 × 10^˗6^)。 然而，系统发育的深层结构主要围绕大陆差异，随后由于现代小麦育种实践中对产量的强烈选择导致生长习性性状(如春化要求)的近期变化。 国家和大陆同时叠加在系统发育群上表明，所观察到的遗传多样性主要是沿着东西轴构成的，与人类迁出新月沃土的既定路线相一致。 两条通往西欧的道路沿着一条内陆路线(经过安纳托利亚和巴尔干到中欧)和一条沿海路线(经过埃及到马格里布和伊比利亚半岛) ，辅之以东北和内亚山走廊的另外两条路线，随后在美国、大洋洲和非洲领土上又发生了殖民活动(图2b )。 接下来探讨了驯化(比较野生小麦和驯化小麦)和育种(比较历史面包小麦类群 i 和 IV)所产生的选择足迹。 为了检测驯化信号，我们计算了来自亚洲的野生二倍体(T.urartu，A.speltoides，A.tauschii)、野生四倍体(T.diccoides)和驯化的六倍体(T.aestivum)小麦的每个位点的核苷酸多样性。 野生小麦祖先和六倍体地方品种之间的对比表明，在小麦的驯化过程中，基因组多样性(ROD)的减少具有很大的异质性(补充图6)。 受到强烈影响的基因组区域(1221) ，显示至少丧失了五分之四的多样性 ，覆盖了9% 的小麦基因组(1.2 Gb)。 已知的驯化基因如脆性穗轴(Brt)、韧性颖片(Tg)、同源配对(Ph)和非自由脱粒性状(Q)位于受到选择的区域内(小于 5Mb)。 有趣的是，已知的驯化基因只占受选择基因组区域的一小部分，这表明进一步的驯化基因仍有待发现。 为了揭示在过去两个世纪中(自1830年以来)小麦改良育种者所选择的基因组区域，我们比较了欧洲研究小组在历史群体 II、 III 和 IV (即那些受到育种影响的群体)与群体 I (地方品种)的多样性减少统计数据(图3a)。 我们的结果与两轮主要的多样性减少是一致的，第一波在第 I和第 II 组之间(11.7% 的多样性减少) ，反映了早期的育种改良。第二波在第 III 和第 IV 组之间(13.3% 的多样性减少) ，反映了绿色革命期间的育种实践(即从1950年到1960年代后期开始的农业实践的更新)。 现代小麦品种与I类相比，核苷酸多样性平均损失21.8% ，染色体内和染色体之间变异很大(图3 b)。 与 D 亚基因组(中位数 多样性减少 为5.8%)相比，A亚基因组(中位数多样性减少为33.2%)和B亚基因组(中位数多样性减少为28.0%)似乎更强烈，这可能反映了它们对小麦改良的不同贡献(图3a)。 为了确定小麦育种者选择的遗传标记和区域，我们对所有样本进行了全基因组扫描，以考虑群体内部和群体之间的渐进群体结构，并在欧洲和亚洲样本中分别以较高的粒度(granularity)进行扫描。 我们确定了5,089个多态位点显示改善信号( P 0.0001)。 已知基因包括光周期敏感基因(Ppd)和春化基因(VRN)、矮化基因(Rht)、谷蛋白(Glu)和醇溶蛋白(Gli)基因、卷曲圆锥花序基因(FZP)、粒数基因(GNS)、蜡质基因(Wx)以及驱动植物构型的 都与这些改良信号密切相关(在5 Mb之内)。 大的基因组区域(10 Mb) ，在过去的两个世纪中(在历史的第I和第IV之间)选择似乎已经发生，并最终变得固定，特别是在染色体1A 和两个结构重新排列的染色体4A 和7B 上观察到(图3b)。 将欧洲和亚洲基因型的8,308和9,948个与改良足迹相关的多态位点扩展到超过2 Mb 的重叠窗口，定义了一个950 Mb (基因组的7%)和1.3 Gb (基因组的9%)的基因组空间，这两个地理区域分别具有选择标记。 有趣的是，在欧洲和亚洲种质之间，只有168 Mb的基因组区域的选择特征是相同的。 通过多环境全基因组关联研究(GWAS) ，检验了观察到的等位变异是否与抽穗期和株高这两个关键的生活史性状相关。 我们的调查了四个环境（法国、匈牙利、土耳其和英国）中的435个六倍体小麦基因型的开花期和株高。 我们分别鉴定了48个和40个与开花期和 株高变异显著相关的基因组位点，其中包括已知控制开花期的基因(Ppd，VRN，FDL，WPCL）和影响株高的Rht基因等。 目前的数据可以为从目前未知的位点中识别相关候选基因以进行功能验证提供了基础，例如在2A染色体上检测到的主要开花期关联的位点，其中 Cry (隐花色素)基因是一个推定的驱动因子。 值得注意的是，多样性、选择足迹和 GWAS 分析清楚地表明，只有一小部分同源基因座含有重合信号，这支持了现代六倍体面包小麦具有二倍体遗传行为的观点，正如前面从平行优势选择中得出的结论，选择同时发生在同源基因区域之间很罕见。 最后，利用一个基于网络的系统发育方法重建现代六倍体小麦的网状进化历史。 聚集共识网络(图4a)包括垂直(物种关系)和水平(网状)事件的信号在小麦-山羊草物种复合体。 小麦进化的综合模型(图4b)是深入分析网络的边缘和边缘权重(图4a)之后得出的综合结论得出的，并通过评价替代共识树拓扑等得到支持。 图4b中的模型通过野生二倍体AA和SS(接近BB)杂交产生野生四倍体AABB杂交后代，并与野生二倍体DD基因型杂交产生六倍体AADDBB)，大大改进了现代面包小麦的进化路径。 我们的分析证实，小麦B基因组来源于山羊草属(Aegilops)系，该系产生了小麦 s. speltoides (SS) ，而 tauschii 和 T.urartu 的祖先分别代表了D和A基因组系的起源。 T. araraticum (也被称作 T. araraticum Jakubz) 代表了 AAGG 四倍体祖先最接近的野生后代。 它似乎随后被驯化形成 T. timopheevii (Zhuk.) 同时也与 T. boeoticum 杂交，形成 T. zhukovskyi (Menabde Ericzjan)谱系(AAAAGG)。 该模型证实了野生二粒小麦是所有现代四倍体AABB和六倍体AABBDD基因型的现代A和B小麦亚基因组祖先的最近的后代。 我们的数据表明，在驯化和栽培的早期阶段，野生二粒小麦池 T. dicoccoides (Körn. ex Asch. and Graebner) Schweinf 产生了至少两个不同的栽培四倍体谱系， T. dicoccum Schrank ex Schübl. (domesticated emmer, also known as T. dicoccon Schrank) and T. durum Desf. (domesticated durum or hard or pasta wheat)。 最后，该模型支持了这样的假设，即普通小麦最有可能来源于 T. durum 和接近 A. tauschii 的 D 基因组之间的一个祖先杂交事件(图4b)。 随后，在六倍体小麦与四倍体小麦杂交中发现了 T. spelta ，至今仍有 T. dicoccum 渐渗的证据。 其他推定的网状事件 ，少于3个证据支持，需要进一步研究，并没有纳入我们的进化模型(图4b)。 网状进化场景在驯化期间和之后首先建立了一个基本的六倍体面包小麦基因库α(图4a, α community)。 这可能包括起源于新月沃土的原始小麦地方品种，并衍生了两个六倍体群落β和γ(图4a)，γ集群主要包括来自西欧的现代基因型，即1986年或更晚的品系主要由小麦品种和当前品种组成，β集群主要包括在东欧国家的一些材料，即冷战期间属于华沙条约组织的国家。 这两个现代群体（β和γ）在进化史上的明显分离可能反映了人类历史和由此产生的社会经济后果如何影响了现代小麦种质的遗传构成，β基因型今天仍在匈牙利和乌克兰种植，而γ基因型在欧洲联盟的许多地区仍占主导地位。 讨论 面包小麦的进化来源于其二倍体和四倍体的祖先，包括大规模和反复的杂交和基因流动事件， T. durum 是当今面包小麦种质资源最可能的祖先。 这种复杂的杂交和基因流动解释了在基因组尺度上观察到的多样性分配(D亚基因组贫乏) ，并支持这样的观点，即现代六倍体小麦在遗传上和表型上表现为类似二倍体的特征，只有一小部分同源基因位点同时具有驯化、选择等信号。 现代面包小麦起源于约10,000年前的新月沃土，今天在小麦基因库中观察到的变异是在人类迁徙、人为选择和后来的育种驯化过程中形成的。 重要的是，在气候变化加速期间，适应新环境的标志仍然是备受关注的研究课题，我们的选择性扫描分析和 GWAS 都强调了未来基因和 / 或等位基因发现的目标。 我们在这里报告的数据和种质收集，以及我们提供给更广泛的研究团体的数据和种质收集，代表了遗传多样性的丰富来源，可以应用于理解和改善多样性，从环境适应到抗病性和营养物质利用效率。
中国春甲基化数据 表观遗传学中，甲基化的研究是重要的一块研究内容。最近小麦品种中国春的参考基因组在science杂志上发表。文章中有甲基化的数据，为了让大家在实际研究过程中方便的使用这个数据，我们特别邀请了中国农大的郭伟龙团队进行了数据的分析和处理，并最终呈现在我们小麦多组学网站上。下面我们具体介绍下这块内容。 1 数据来源： NCBI登录号 SRP133674 ， 文章：Shifting the limits in wheat research and breeding using a fully annotated reference genome 取材时期 Cytosine methylation was profiled in DNA extracted from two-week old CS leaf tissue in three different contexts: CpG dinucleotides, CHG and CHH (where H corresponds to A, T or C). The frozen leaves from the five samples at 3-leaf stage (Zadok stage 13) were ground and divided as input for the preparation of both RNA-seq libraries (detailed in Chinese Spring tissues study) and whole genome bisulfite sequencing (WGBS) libraries. 2 结果描述 前面我们提到了这些数据来自science杂志上的中国春参考基因组。下面我们就总结下这篇文章中甲基化方面的结果。 Wheat DNA methylation frequency of cytosines in the sequence contexts of CpG (average 92.7%), CHG (average 51.3%) and CHH (average 2.7%). The observed levels of cytosine methylations are among the highest observed in angiosperms (161), likely reflecting the abundance of repetitive elements throughout the wheat genome. Methylation patterns in wheat largely follow those observed in other species, showing enrichment in CpG and CHG sequence contexts at pericentromeric regions (gene poor) and depletion toward the chromosome ends (gene rich). 首先看一看high confidence genes的甲基化pattern。如下图所示，在基因编码区相对较低，CpG和CHG而在上有启动子和下游则相对较高。而CHH则相对较平稳。大家分析自己的基因时可以看看是否属于这个pattern。 high confidence genes (TSS = transcription start site; TTS = transcription termination site) High rates of DNA methylation likely serve to prevent transposition by restricting the expression of transposable elements. However, where repetitive elements are proximal to gene sequences, the enriched methylation can perform a regulatory function, predominantly silencing expression. The distinct and highly conserved methylation patterns observed in regions of HC genes and their regulatory regions showed higher levels of DNA methylation associated with the 5’ regulatory regions in all contexts that diminished rapidly at the transcriptional start site (TSS). 而low confidence (LC) genes的甲基化pattern又是如何呢？如下图，3种类型都相对平稳。 (TSS = transcription start site; TTS = transcription termination site) DNA methylation increased in the gene body where the CpG methylation formed a peak, whereas gene body methylation levels remained at extremely low levels at CHG and CHH sites. In the 3’ regulatory region after the transcriptional termination site (TTS) methylation rapidly reverted to the levels in 5’ sequences. This contrasted with the pattern observed for LC genes, where a near uniform level of methylation was observed in all sequence contexts. As a conclusion, many of the features included in the LC annotation are either no genes, are truncated or have lost their function through mutation (i.e. pseudogenes). 有一点很重要，甲基化也是一个动态变化的过程，不同发育时期，不同环境下都会发生变化。有些结论要辩证的看待。 Copia repeat elements TE序列相对来说甲基化程度要高很多 3 甲基化分析 农大的郭伟龙老师开发了甲基化mapping软件BS-Seeker2(BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data)以及后续甲基化分析软件CGmapTools(CGmapTools improves the precision of heterozygous SNV calls and supports allele-specific methylation detection and visualization in bisulfite-sequencing data)。 具体的分析流程见 这里 。 需要注意的地方： 1、单条染色体需要拆分成两部分，即使用官方提供的161010_Chinese_Spring_v1.0_pseudomolecules_parts.fasta进行基因组index 2、使用bs_seeker2-call_methylation.py时不要整个基因组一起call methylation，一来速度太慢，二来整个基因组一起会出现bug(其他人有没有还不清楚)。我简单的说下我的测试过程，整个基因组进行call methylation，根据程序提示如果1A部分已经运行完毕，直接停止；分离出1A的bam文件单独对1A进行call methylation；将1A和2A合并到一起call methylation。最后发现，整个基因组call methylation的结果与其它两个均不同；而无论是1A单独还是1A和2A一起call methylation，结果都是相同的。 4 Jbrowse呈现 目前可以在我们网站(http://202.194.139.32)上查询感兴趣基因的甲基化水平。 绿色箭头处可输入转录本名字，如*TraesCS7A02G208100.1* 下面我们看一个例子。GS5基因在水稻中控制水稻的粒形和粒重，在小麦里中GS5（TraesCS3A02G212900LC, TraesCS3B02G277100LC和TraesCS3D02G172900）也已经被多个课题组同源克隆，其中3B基因有两处大插入，破坏了基因结构。从甲基化水平上来看，两处插入序列的甲基化水平较高（如下图）。 TaGS5 最后再强调一点，这里的甲基化是苗期叶片中的，不代表其他组织中的甲基化水平一定也是这样。
支持python3，可用来统计基因组上的gap位置，gap大小。输出格式是gff3。当然根据需要修改print那一行可以输出bed等格式 使用格式如下： python3 getgaps.py genome.fasta gaps.gff3 #!/usr/bin/envpython3 #thiscodewaschangedbasedonbiostarhttps://www.biostars.org/p/152592/ #Importnecessarypackages import argparse import re from Bio import SeqIO #Parsecommand-linearguments parser=argparse.ArgumentParser() parser.add_argument( fasta ) args=parser.parse_args() #OpenFASTA,searchformaskedregions,printinGFF3format with open(args.fasta) as handle: i= 0 for record in SeqIO.parse(handle, fasta ): for match in re.finditer( 'N+' ,str(record.seq)): i=i+ 1 print (record.id, . , gap ,match.start()+ 1 ,match.end(), . , . , . , Name=gap +str(i)+ ;size= +str(match.end()-match.start()),sep= '\\t' ) #usethefollowingatCMD:FILENAME.pyFILENAME.fastaFILENAME.gff3here
小麦族多组学数据网站——序列获取 5/2 本期作者 Neal 眨眼五一假期已过，其实很大一部分做小麦的往往没有五一假期。今天我们想要说一说与microRNA的话题。前面我们谈过一些microRNA的话题，我整理了一下列在下面，感兴趣的可以去看看，也欢迎大家就small RNA方面的内容与我们交流。 今天要谈的这篇文章前几天刚刚在plant journal在线。文章的题目是“ Identification and characterisation of a previously unknown drought tolerance—associated microRNA in barley ”。作者系澳大利亚常春藤名校联盟“八大名校”之一的阿德莱德大学（The University of Adelaide ）。通讯作者是 Shi Bujun , 第一作者是 Zhou Hui 。文章的DOI是 10.1111/tpj.13938 ，输入DOI可在网站sci-hub.tw上下载。 本文是一个反向遗传的例子，不像图位克隆这样正向遗传的文章，一换扣一环，逻辑方面较简单，文章阅读起来也相对容易，貌似小麦里图位克隆也比较简单，文章所呈现出来的内容也是行云流水。实际上在小麦做图位克隆并不简单，图位克隆过程中很多的曲折实际上很少会在文章中有所呈现。而反向遗传学方面，也即基因功能和机制的方面研究，很大程度上需要转基因技术和基因编辑技术，这才是反向遗传学的硬通货。除此之外，一些必要的点缀也是需要的，毕竟红花还得绿叶配。从一个简单的idea到最终论文里呈现的完美故事，统领整个研究的是逻辑思维能力，这才是一篇论文研究的灵魂所在。反向遗传学对逻辑方面的能力要求要比正向遗传学高。今天我们就以这一篇文章为例谈一谈。 首先先从文章的干货开始谈起。过表达hvu-miRX的大麦植株耐旱性与对照相比得到提高，表型见下图，文中也对一些耐旱性的指标进行了评价，结果也是阳性的。可能只是先在线的原因，图片里的文字看不清楚。 现在我们知道miRNA是通过剪切靶基因的转录本而行使生物学功能的，在表达水平上往往成相反的趋势，也即当miRNA的表达量升高时，靶基因的表达量就降低，反之亦然。这里为了行文的方便，miRNA和靶基因之间的关系做了简单化处理。在这里hvu-miRX的靶基因之一是编码NAD(P)-binding domain的基因，该基因的表达水平在过表达hvu-miRX的大麦里与对照相比降低了，这符合我们的预期。但是该基因不受干旱诱导。文中没有对此作出解释，其实我们可以做这样一个假设，含有NAD(P)-binding domain的基因负调控大麦的抗旱性。大家认为这个假设对不对呢？同时文中回避了过表达hvu-miRX的大麦在干旱处理过后，该靶基因的表达水平。所以hvu-miRX是否真的通过这个靶基因来提高大麦对干旱的耐受性还没有一锤定音，也即不能排除其他未知的途径。大家可以进一步思考下，如果要验证这个假设需要安排哪些实验呢？其实我认为这才是文章的亮点所在，然而本文并没有更进一步。 说完了转基因，我们再谈一谈这个研究的来龙去脉。这就不得不提2011年的两篇研究，一篇是在组学水平上鉴定大麦的miRNA（ Discovery of barley miRNAs through deep sequencing of short reads ），另外一篇发现在过表达TaDREB3的大麦里有一个miRNA与对照相比上调表达（ Improvement of stress tolerance of wheat and barley by modulation of expression of DREB/CBF factors ），同时过表达TaDREB3的大麦对干旱的耐受性增加。这是为啥本篇为啥要研究miRX。我们前面提到也有过表达miRX的大麦，但文中作者没有提到是否DREB3的表达是否受miRX调控，也许因为DREB3并不是miRX的靶基因吧。这其实也是一种常见的研究思路，先广撒网，再从捞到的鱼里挑挑拣拣，选择一条上好的鱼苗子养大。我们以前常说生信就是指路的也是这样一个道理，数据越多，方向也就更坚定，脚下的路也就越平坦。 接下来是对miRX的研究，希望说明miRX确实是一个miRNA，并且也确实收到干旱的诱导。除了这些，本文还发现pri-miRX的正向上有8个ORF，其中最长的一个编码65个氨基酸。前面已经有研究表明pri-miRNA是可以编码一些小肽的，本文没有再进一步去验证。获得的15个cDNA（pri-miRX）克隆中，有2个存在单碱基变异，作者认为很可能是反转录过程中引起的错误。是不是反转录引起的错误，多重复几次反转录是不是就可以验证了？另外有没有可能是RNA编辑？ 这一部分在讨论里还提到pri-miRX的5'末端多了四个碱基GAAA。我们知道mRNA会在5'末端加帽，即加1个G，而这里却加了4个碱基？作者表示还需要更多的时间来研究GAAA可能的生物学作用。看到此处，我首先想到的有没有可能是接头序列？我查了下材料方法，本文使用的反转录试剂盒是GeneRacer，在附件一里看到其接头引物的3'末端就是GAAA，如下图。所以我不太清楚作者是否排除了加上的这四个碱基？有兴趣的小伙伴可以仔细研究下，看看这个GAAA是不是真的？ 接下来作者继续分析了这个miRX的启动子序列。这里先卖个关子，大家想一下为啥要花很多精力分析和研究启动子呢？ 作者在分析了一些启动子的基本元件后将启动子截成4段启动GUS，用来寻找核心启动子。通过数GUS的细胞数目的来衡量启动子效率的高低。由于我没做过这种实验和文中材料方法部分介绍也比较少，不了解这个实验的可靠性。有懂的小伙伴可以评价下。下图是结果的柱状图，因为文中没有交代该实验重复了几次，这个实验误差有点大，所以对文中所下的结论还是有点疑问的？ 这里要交代为啥要研究miRX的启动子。因为在转TaDREB3的材料里，miRX上调表达，考虑到DREB3是一个转录因子，所以就假设DREB3通过结合其启动子区基序来调控miRX的表达。但是仅从启动子序列上来来看，没有迹象表明受DREB3调控,后续的共表达实验也没有证明DREB3直接调控miRX。 下面说一说miRNA的靶基因。预测得到15个靶基因，降解组支持的有3个。然而文中并没有交代支持靶基因的降解组read是多少，也没有具体交代使用了哪个组织的降解组文库，以及原始的降解组数据是否已提交至公共数据库。 有降解组支持的3个靶基因，选择了那个编码NAD(P)-binding domain的基因进行了验证（The target gene encoding the NAD(P)-binding domain-containing protein was further verified using gene specific 5′ RACE）。这里列出了文中的原话。按照我的理解如果要验证miRNA的靶基因，一般使用的是3' PPM-RACE和5' RLM-RACE。而这里作者所讲的5′ RACE是不是5' RLM-RACE我就不太确定了。在材料方法和附件里也没有对这一实验的描述。下图中3个黑色箭头上方的数字表示一共验证了8个克隆，其中有6个克隆支持在经典的10-11位之间剪切靶基因，当然这是按照我的理解，至于是降解组的read还是克隆，得向作者确认。这个地方最好再放上测序的峰图。 然而，定量PCR结果表明NAD(P)-binding domain-containing 的基因的表达没有发生变化。 除了以上内容，本文还分析了miRX在大麦基因组的拷贝数和位置，以及miRX在植物里的保守性。 以上就是本文的全部内容。建议大家有时间的话读读原文，结合本次的解读，希望能够有自己的思考。本文的亮点有两条，第一证明miRX受DREB3调控，第二证明过表达miRX的大麦对干旱的耐受性是通过哪个靶基因起作用。然而，本文在这两方面得到的都是阴性结果。本文对大部分实验结果的描述和分析很到位，这点是我要学习地方，写文章的时候几句话就把结果交代完了，在往下就没东西写了。而对实验方法部分的描述却很不到位，一些关键信息缺失。
2018年第13周小麦文献推荐（4.1） 今天是4.1号，大家要小心呢。还有别忘了我们的线上摄影展（ 第一届“小麦研究联盟”线上摄影展 ），现在就可以发给我们了。 听说最近天气变化剧烈，特地查了下天气预报。下面播报下天气预报 。下周一，北方大部气温将抬升近期最高点，河北南部、山东西北部、河南北部、陕西关中等地，将再次向30℃以上发起冲击，局地或将有高温现身。省会级城市中，郑州、济南、银川、兰州有望创下今年气温新高，其中郑州、济南将超30℃。南方大部最高气温也多在25-30℃左右。不过，北方温暖的春意还不能完全站稳脚跟。下周前期，较强冷空气来袭，各地气温将迅速下降。明天，冷空气的先头部队就率先在新疆发动攻势，乌鲁木齐最高气温将从今天的26℃降到明天的8℃，随后还将逐步跌落至仅有6℃，寒冷如冬。4月3-6日，冷空气东移南下，逐渐影响全国大部，北方大部地区的气温将转为偏低，华北地区最高气温纷纷降到15℃左右，而东北则降至个位数，最低气温将再度跌破冰点。其中，降温最猛烈的河南、山东一带，累积降幅可达到20℃上下，例如济南、郑州最高气温将由2日的30℃出头降至10℃左右。我们的麦S特别提醒大家注意倒春寒（ 低温、高温对起身拔节期小麦的影响 ）。 说完了天气，我们开始说一说我们这一周的文献更新。 1 Genome-wide identification of wheat (Triticum aestivum) expansins and expansin expression analysis in cold-tolerant and cold-sensitive wheat cultivars. PMID:29596529 DOI:10.1371/journal.pone.0195138 2 Coupled ultradian growth and curvature oscillations during gravitropic movement in disturbed wheat coleoptiles PMID: 29596500 DOI: 10.1371/journal.pone.0194893 3 Quantitative trait loci associated with soft wheat quality in a cross of good by moderate quality parents. PMID: 29593939 PMCID: PMC5868479 DOI: 10.7717/peerj.4498 4 Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing PMID: 29593779 PMCID: PMC5857551 DOI: 10.3389/fgene.2018.00076 5 The Role of Hydrogen Peroxide in Mediating the Mechanical Wounding-Induced Freezing Tolerance in Wheat PMID: 29593774 PMCID: PMC5861560 DOI: 10.3389/fpls.2018.00327 6 Zinc and Iron Concentration as Affected by Nitrogen Fertilization and Their Localization in WheatGrain. PMID: 29593765 PMCID: PMC5855893 DOI: 10.3389/fpls.2018.00307 7 Genetic Dissection of End-Use Quality Traits in Adapted Soft White Winter Wheat PMID: 29593752 PMCID: PMC5861628 DOI: 10.3389/fpls.2018.00271 8 Identification and Characterization of Wheat Yellow Striate Virus, a Novel Leafhopper-Transmitted Nucleorhabdovirus Infecting Wheat PMID: 29593700 PMCID: PMC5861215 DOI: 10.3389/fmicb.2018.00468 9 Genome-wide association mapping for resistance to leaf rust, stripe rust and tan spot in wheatreveals potential candidate genes PMID: 29589041 DOI: 10.1007/s00122-018-3086-6 10 Efficient anchoring of alien chromosome segments introgressed into bread wheat by new Leymus racemosus genome-based markers PMID: 29587653 DOI: 10.1186/s12863-018-0603-1 11 Expression of Pinellia pedatisecta Lectin Gene in Transgenic Wheat Enhances Resistance to Wheat Aphids PMID: 29587341 DOI: 10.3390/molecules23040748 12 Wheat starch with low retrogradation properties produced by modification of the GtfB enzyme 4,6-α-glucanotransferase from Streptococcus thermophilus PMID: 29582651 DOI: 10.1021/acs.jafc.8b00550 13 TaEDS1 genes positively regulate resistance to powdery mildew in wheat PMID: 29582247 DOI: 10.1007/s11103-018-0718-9 14 Identification of Wheat Inflorescence Development-Related Genes Using a Comparative Transcriptomics Approach PMID: 29581960 PMCID: PMC5822904 DOI: 10.1155/2018/6897032 15 Dynamic Evolution of α-Gliadin Prolamin Gene Family in Homeologous Genomes of Hexaploid Wheat PMID: 29581476 DOI: 10.1038/s41598-018-23570-5 16 Contrasting plant height can improve the control of rain-borne diseases in wheat cultivar mixture: modelling splash dispersal in 3-D canopies PMID: 29579151 DOI: 10.1093/aob/mcy024 17 Transgenic expression of plastidic glutamine synthetase increases nitrogen uptake and yield in wheat PMID: 29577547 DOI: 10.1111/pbi.12921 18 Wheat expansin gene TaEXPA2 is involved in conferring plant tolerance to Cd toxicity PMID: 29576078 DOI: 10.1016/j.plantsci.2018.02.022 19 Molecular Diversity and Landscape Genomics of the Crop Wild Relative Triticum urartu Across the Fertile Crescent PMID: 29573496 DOI: 10.1111/tpj.13888 20 Responses of seminal wheat seedling roots to soil water deficits PMID: 29567416 DOI: 10.1016/j.jplph.2018.03.002 最后，告诉大家一个小技巧，在PubMed数据库里按照如下格式搜索，可以搜索关键词wheat在2018年3月24日至2018年3月30日的文献更新。 ( (wheat ) AND 2018/03/24 15.00 :2018/03/30 15.00 ) 欢迎关注 “ 小麦研究联盟 ”， 了解小麦新进展
2018年第二周小麦文献推荐（1.14） 大家好！不知不觉今天是18年的第二周周末了。 昨天的推送收到很多反馈，胖丫让我感谢你们，她受益良多。有小伙伴问起Sentieon，昨天也没多说，今天多说两句，这个软件的功能和GATK功能类似，准确性上不输GATK，但是速度上要比它快N多倍。特别是当有大量样本需要做的时候，建议还是试一试Sentieon，毕竟时间就是金钱呢。这是一款商业软件，有兴趣的小伙伴可以邮件联系 support@sentieon.com ，可以获取试用版。也欢迎大家进群交流小麦方面的内容，可以加“wheatgenome”,老师或者博后也可以加“xiaoxuan8765”。 小麦组学研究在接来下2-3年一定是热点，除了中国春参考基因组，其它材料的基因组也会陆续发表。现在有各种组装技术加持，这些小麦族基因组不比参考基因组差，数据增多势必会促进我们的研究，但同时竞争也会更加激烈。作为传统的小麦研究者来讲，我们有材料，但是技术方面不成熟，而对于早期研究拟南芥、水稻等模式作物的研究者来讲，带着新技术新方法进入小麦也是顺其自然的过程。一个有技术，一个有材料或者数据，两者结合一定会有火花擦出来。回头看看最近2年的研究，这种合作方式越来越常见，最近黄三文小组和罗杰小组最近就联手在Cell上发表了一篇利用多组学数据研番茄果实的营养和风味的文章，这就是一个极好的合作共赢的例子。世界的发展也是这样的趋势，国家与国家之间联系越来越紧密，在这样一个信息和数据爆炸的时代，科研节奏会越来越快，专业的东西交给专业的人做，所以敞开胸怀合作一定不是坏选择。 又有点扯远了，下面让我们看看最近一周小麦方面又有哪些东西更新。 1 High throughput SNP discovery and genotyping in hexaploid wheat Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research 2 Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs Stable quantitative trait loci (QTL) are important for deployment in marker assisted selection in wheat (Triticum aestivum L.) and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE) by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading) and yield related traits (test weight, thousand kernel weight, harvest index). The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive) at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1, and UDP-glucose 6-dehydrogenase 1-like isoform X1. The stable QTL could be important for further validation, high throughput SNP development, and marker-assisted selection (MAS) in wheat. 3 Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat Winter wheat parents ‘Harry’ (drought tolerant) and ‘Wesley’ (drought susceptible) were used to develop a recombinant inbred population with future goals of identifying genomic regions associated with drought tolerance. To precisely map genomic regions, high-density linkage maps are a prerequisite. In this study genotyping-by- sequencing (GBS) was used to construct the high-density linkage map. The map contained 3,641 markers distributed on 21 chromosomes and spanned 1,959 cM with an average distance of 1.8 cM between markers. The constructed linkage map revealed strong collinearity in marker order across 21 chromosomes with POPSEQ-v2.0, which was based on a high-density linkage map. The reliability of the linkage map for QTL mapping was demonstrated by co-localizing the genes to previously mapped genomic regions for two highly heritable traits, chaff color, and leaf cuticular wax. Applicability of linkage map for QTL mapping of three quantitative traits, flag leaf length, width, and area, identified 21 QTLs in four environments, and QTL expression varied across the environments. Two major stable QTLs, one each for flag leaf length ( Qfll . hww-7A ) and flag leaf width ( Qflw . hww-5A ) were identified. The map constructed will facilitate QTL and fine mapping of quantitative traits, map-based cloning, comparative mapping, and in marker-assisted wheat breeding endeavors. 4 A genome-wide association study of wheat yield and quality-related traits in southwest China Wheat ( Triticum aestivum L.) is one of the most productive and important crops and its yield potential and quality characteristics are tightly linked with the global food security. In this study, genome-wide association study (GWAS) was conducted for yield and quality-related traits. Based on the high-density wheat 90K Illumina iSelect SNP Array, 192 bread wheat lines from southwest China, including 25 synthetic hexaploid wheat lines, 80 landraces, and 87 cultivars were analyzed. Association analysis results indicated that there were 57, 27, 30, and 34 SNPs associated with plant height (PH), grain protein content (GPC), thousand kernel weight (TKW), and SDS sedimentation volume (SSV) have been detected, respectively. Then, integrating RNA-Seq with bioinformatics analysis, 246 candidate genes (102 for GPC, 52 for TKW, and 92 for SSV) were found. Further analysis indicated that one up-regulated and two down-regulated expression genes affect GPC. Additionally, two haplotypes significantly affecting PH were detected in a 2.2-Mb genome region encompassing a gene which encoded an ubiquitin-specific protease, TaUBP24. The functional markers of TaUBP24 have been developed, which could be used for marker-assisted selection to improve wheat quality and yield. 5 Characterization of Novel Gene Yr79 and Four Additional QTL for All-stage and High-temperature Adult-plant Resistance to Stripe Rust in Spring Wheat PI 182103 Stripe rust, caused by Puccinia striiformis f. sp. tritici , is an important disease of wheat worldwide. Exploring new resistance genes is essential for breeding resistant wheat cultivars. PI 182103, a spring wheat landrace originally from Pakistan, has shown a high level of resistance to stripe rust in fields for many years, but genes for resistance to stripe rust in the variety have not been studied. To map the resistance gene(s) in PI 182103, 185 recombinant inbred lines (RILs) were developed from a cross with Avocet Susceptible (AvS). The RIL population was genotyped with SSR and SNP markers and tested with races PST-100 and PST-114 at the seedling stage under controlled greenhouse conditions and at the adult-plant stage in fields at Pullman and Mt. Vernon, Washington under natural infection by the stripe rust pathogen in 2011, 2012, and 2013. A total of five quantitative trait loci (QTL) were detected. QyrPI182103.wgp-2AS and QyrPI182103.wgp-3AL were detected at the seedling stage, QyrPI182103.wgp-4DL was detected only in Mt. Vernon field tests, and QyrPI182103.wgp-5BS was detected in both seedling and field tests. QyrPI182103.wgp-7BL was identified as a high-temperature adult-plant (HTAP) resistance gene and detected in all field tests. Interactions among the QTL were mostly additive, but some negative interactions were detected. The 7BL QTL was mapped in chromosomal bin 7BL 0.40-0.45 and identified as a new gene, permanently designated as Yr79 . SSR markers Xbarc72 and Xwmc335 flanking the Yr79 locus were highly polymorphic in various wheat genotypes, indicating that the molecular markers are useful for incorporating the new gene for potentially durable stripe rust resistance into new wheat cultivars. 6 Succession of Fungal and Oomycete Communities in Glyphosate-Killed Wheat Roots. The successional dynamics of root-colonizing microbes are hypothesized to be critical to displacing fungal pathogens that can proliferate after the use of some herbicides. Applications of glyphosate in particular, which compromises the plant defense system by interfering with the production of aromatic amino acids, is thought to promote a buildup of root pathogens and can result in a ‘greenbridge’ between weeds or volunteers and crop hosts. By planting two to three weeks after spraying, growers can avoid most negative impacts of the greenbridge by allowing pathogen populations to decline, but with the added cost of delayed planting dates. However, the specific changes in microbial communities during this period of root death and the microbial taxa likely to be involved in displacing pathogens are poorly characterized. Using high-throughput sequencing, we characterized fungal and oomycete communities in roots after applications of herbicides with different modes of action (glyphosate or clethodim) and tracked their dynamics over three weeks in both naturally infested soil and soil inoculated with Rhizoctonia solani *AG-8. We found that many unexpected taxa were present at high relative abundance (eg. *Pythium volutum and Myrmecridium species) in live and dying wheat roots and may play an under-recognized role in greenbridge dynamics. Moreover, communities were highly dynamic over time and had herbicide-specific successional patterns, but became relatively stable by two weeks after herbicide application. Network analysis of communities over time revealed patterns of interactions among taxa that were both common and unique to each herbicide treatment and identified two primary groups of taxa with many positive associations within-groups but negative associations between-groups, suggesting that these groups are antagonistic to one another in dying roots and may play a role in displacing pathogen populations during greenbridge dynamics. 7 Characterization of Adult Plant Resistance to Leaf Rust and Stripe Rust in Indian Wheat Cultivar ‘New Pusa 876’ Growing resistant varieties is the most effective and economical method for controlling rust of wheat ( Triticum aestivum L.). Resistance to leaf rust and stripe rust, caused by Puccinia triticina Erikss. and P. striiformis Westend. f. sp. tritici , respectively, was investigated in 148 F5recombinant inbred lines derived from a cross between ‘Avocet’ and ‘New Pusa 876’ (NP876). The parents and population were phenotyped for resistance in field trials for 3 and 2 yr for leaf rust and stripe rust, respectively, and genotyped with gene-linked molecular markers. The segregation analyses indicated that the adult plant resistance to leaf rust and stripe rust was conferred by five and four additive effect genes, respectively. Among them, the slow-rusting adult plant resistance gene Lr46/Yr29 reduced 14 and 16% of mean leaf rust and stripe rust severities, respectively, whereas a severity reduction of 26% occurred due to Lr67/Yr46 for both rusts. Both resistance genes were contributed by NP876. An additive effect between leaf rust resistance genes Lr46 and Lr67 was detected, with a reduction up to 11% when they were present together. The effect of combining Yr29 and Yr46 was additive but not significant, with a mean reduction of 5% in severity. New Pusa 876 can be used as a multiple rust resistance source to breed wheat varieties that may contribute towards durable resistance. 8 Temperature and Alternative Hosts Influence Aceria tosichella Infestation and Wheat Streak Mosaic Virus Infection Wheat streak mosaic, caused by Wheat streak mosaic virus (WSMV; family Potyviridae), is the most important and common viral disease of wheat (Triticum aestivum L.) in the Great Plains of North America. WSMV is transmitted by the wheat curl mite (WCM; Aceria tosichella). We evaluated how mean daily temperatures, cumulative growing degree-days, day of the year, and surrounding alternative host identity affected WCM infestation and WSMV infection of wheat from late summer through early autumn in Montana, United States. Cumulative growing degree-days, warm mean daily temperatures (i.e., 10°C), and surrounding alternative hosts interacted to alter risk of WCM infestation and WSMV infection. Wheat surrounded by Bromus tectorum L. and preharvest volunteer wheat had WCM infestation and WSMV infection rates of 88% in years when the mean daily temperature was 15°C in October, compared with 23% when surrounded by bare ground, and 1% when the temperature was 0°C regardless of surrounding alternative host. Mean daily temperatures in the cereal-growing regions of Montana during autumn are marginally conducive to WCM population growth and movement. As the region continues to warm, the period of WCM movement will become longer, potentially increasing the frequency of WSMV outbreaks. 9 Wheat resistances to Fusarium root rot and head blight are both associated with deoxynivalenol and jasmonate related gene expression Fusarium graminearum is a major pathogen of wheat causing Fusarium head blight (FHB). Its ability to colonize wheat via seedling root infection has been reported recently. Our previous study on Fusarium root rot (FRR) has disclosed histological characteristics of pathogenesis and pathogen defense that mirror processes of spike infection. Therefore, it would be interesting to understand whether genes relevant for FHB resistance are induced in roots. The concept of similar-acting defense mechanisms provides a basis for research at broad Fusarium resistance in crop plants. However, molecular defense responses involved in FRR as well as their relation to spike resistance are unknown. To test the hypothesis of a conserved defense response, a candidate gene expression study was conducted to test the activity of selected prominent FHB defense-related genes in seedling roots, adult plant roots, spikes and shoots. FRR was examined at seedling and adult plant stages to assess age-related pattern of disease and pathogen resistance. This study offers first evidence for a significant genetic overlap in root and spike defense responses, both in local and distant tissues. The results point to plant development-specific rather than organ-specific determinants of resistance, and suggest roots as an interesting model for studies on wheat-Fusarium interactions. 10 Three-Dimensional Analysis of Chloroplast Structures Associated with Virus Infection Chloroplasts are multifunctional organelles whose morphology is affected by environmental stresses. Although the three-dimensional (3D) architecture of thylakoid membranes has been reported previously, a 3D visualization of chloroplast under stress has not been explored. In this work, we used a positive-strand RNA ((+)RNA) virus, barley stripe mosaic virus (BSMV) to observe chloroplast structural changes during infection by electron tomography. The analyses revealed remodeling of the chloroplast membranes, characterized by the clustering of outer membrane-invaginated spherules in inner membrane-derived packets. Diverse morphologies of cytoplasmic invaginations ( CI s) were evident with spherules at the periphery and different sized openings connecting the CI s to the cytoplasm. Immunoelectron microscopy of these viral components verified that the aberrant membrane structures were sites for BSMV replication. The BSMV αa replication protein localized at the surface of the chloroplasts and played a prominent role in eliciting chloroplast membrane rearrangements. In sum, our results have revealed the 3D structure of the chloroplasts induced by BSMV infection. These findings contribute to our understanding of chloroplast morphological changes under stress conditions and during assembly of plant (+)RNA virus replication complexes. 11 No Time to Waste: Transcriptome Study Reveals that Drought Tolerance in Barley May Be Attributed to Stressed-Like Expression Patterns that Exist before the Occurrence of Stress Plant survival in adverse environmental conditions requires a substantial change in the metabolism, which is reflected by the extensive transcriptome rebuilding upon the occurrence of the stress. Therefore, transcriptomic studies offer an insight into the mechanisms of plant stress responses. Here, we present the results of global gene expression profiling of roots and leaves of two barley genotypes with contrasting ability to cope with drought stress. Our analysis suggests that drought tolerance results from a certain level of transcription of stress-influenced genes that is present even before the onset of drought. Genes that predispose the plant to better drought survival play a role in the regulatory network of gene expression, including several transcription factors, translation regulators and structural components of ribosomes. An important group of genes is involved in signaling mechanisms, with significant contribution of hormone signaling pathways and an interplay between ABA, auxin, ethylene and brassinosteroid homeostasis. Signal transduction in a drought tolerant genotype may be more efficient through the expression of genes required for environmental sensing that are active already during normal water availability and are related to actin filaments and LIM domain proteins, which may function as osmotic biosensors. Better survival of drought may also be attributed to more effective processes of energy generation and more efficient chloroplasts biogenesis. Interestingly, our data suggest that several genes involved in a photosynthesis process are required for the establishment of effective drought response not only in leaves, but also in roots of barley. Thus, we propose a hypothesis that root plastids may turn into the anti-oxidative centers protecting root macromolecules from oxidative damage during drought stress. Specific genes and their potential role in building up a drought-tolerant barley phenotype is extensively discussed with special emphasis on processes that take place in barley roots. When possible, the interconnections between particular factors are emphasized to draw a broader picture of the molecular mechanisms of drought tolerance in barley. 12 How exogenous nitric oxide regulates nitrogen assimilation in wheat seedlings under different nitrogen sources and levels Nitrogen (N) is one of the most important nutrients for plants and nitric oxide (NO) as a signaling plant growth regulator involved in nitrogen assimilation. Understanding the influence of exogenous NO on nitrogen metabolism at the gene expression and enzyme activity levels under different sources of nitrogen is vitally important for increasing nitrogen use efficiency (NUE). This study investigated the expression of key genes and enzymes in relation to nitrogen assimilation in two Australian wheat cultivars, a popular high NUE cv. Spitfire and a normal NUE cv. Westonia, under different combinations of nitrogen and sodium nitroprusside (SNP) as the NO donor. Application of NO increased the gene expressions and activities of nitrogen assimilation pathway enzymes in both cultivars at low levels of nitrogen. At high nitrogen supplies, the expressions and activities of N assimilation genes increased in response to exogenous NO only in cv. Spitfire but not in cv. Westonia. Exogenous NO caused an increase in leaf NO content at low N supplies in both cultivars, while under high nitrogen treatments, cv. Spitfire showed an increase under ammonium nitrate (NH4NO3) treatment but cv. Westonia was not affected. N assimilation gene expression and enzyme activity showed a clear relationship between exogenous NO, N concentration and N forms in primary plant nitrogen assimilation. Results reveal the possible role of NO and different nitrogen sources on nitrogen assimilation in Triticum aestivum plants. 13 Reference Quality Genome Assemblies of Three Parastagonospora nodorum Isolates Differing in Virulence on Wheat Parastagonospora nodorum , the causal agent of Septoria nodorum blotch of wheat, has emerged as a model necrotrophic fungal organism for the study of host-microbe interactions. To date, three necrotrophic effectors have been identified and characterized from this pathogen, including SnToxA, SnTox1, and SnTox3. Necrotrophic effector identification was greatly aided by the development of a draft genome of Australian isolate SN15 via Sanger sequencing, yet remained largely fragmented. This research presents the development of near-finished genomes of *P. nodorum *isolates Sn4, Sn2000, and Sn79-1087 using long-read sequencing technology. RNAseq analysis of isolate Sn4 consisting of eight time-points covering various developmental and infection stages mediated the annotation of 13,379 genes. Analysis of these genomes revealed large-scale polymorphism between the three isolates, including the complete absence of contig 23 from isolate Sn79-1087 and a region of genome expansion on contig 10 in isolates Sn4 and Sn2000. Additionally, these genomes exhibit the hallmark characteristics of a 'two-speed' genome, being partitioned into two distinct GC-equilibrated and AT-rich compartments. Interestingly, isolate Sn79-1087 contains a lower proportion of AT-rich segments, indicating a potential lack of evolutionary hot spots. These newly sequenced genomes, consisting of telomere to telomere assemblies of nearly all 23 *P. nodorum *chromosomes provides a robust foundation for the further examination of effector biology and genome evolution. 14 Exploration of Mechanisms for Internal Deterioration of Wheat Seeds in Postharvest Storage and Nitrogen Atmosphere Control for Properties Protection Wheat ( Triticum aestivum L.) seeds were stored in simulated conditions of four regions for 300 d. Changes of biochemical properties and electron microscope pictures demonstrated that unfavorable storage conditions caused serious internal deterioration and promoted the accumulation of unhealthy products in wheat seeds. Two hypotheses were proposed to explain the internal deterioration during storage. This work confirmed that the unfavorable storage conditions damaged enzymatic scavenging systems. As a result, without an effective scavenging system, serious internal deterioration occurred in wheat seeds. Atmospheric composition was adjusted to evaluate the potential of applying nitrogen atmosphere control in wheat storage. The results showed that 98% nitrogen gas in atmosphere effectively protected scavenging systems in wheat seeds and alleviate the internal deterioration. 15 Winter Wheat Yield Gaps and Patterns in China Wheat ( Triticum aestivum L.) yield stagnation has been reported in some regions of the world. China is the largest producer of wheat across the globe, but the pattern of its wheat yield stagnation remains poorly addressed. Here, our goal is to examine the temporal trends and spatial patterns of wheat yields along with possible causes based on a comprehensive assessment of winter wheat yield throughout China over the 31-yr period from 1980 to 2010. Combined with the Agricultural Production Systems Simulator (APSIM) wheat model, we assessed the winter wheat yield gaps and patterns in 1414 counties and at five physiogeographic regional scales across China to ascertain the driving factors of yield variations. Wheat yields increased in 53% of the 1414 counties, but the remaining counties experienced yields that never improved, stagnated, or collapsed from 1980 to 2010. The yield gap analysis showed that actual yields represented only 59% of the national average yield potential, indicating a substantial opportunity to improve winter wheat yields. Relatively larger yield gaps were observed in the northern China Plain (NC, 47%) and in southwestern China (SW, 45%). Although the yield gaps in these regions were accompanied by significantly progressive uptrends of actual yields, our results suggest that agronomic management could be further improved. Moreover, underperforming regions could potentially benefit from new investments and strategies to reliably increase actual yields and reverse trends in stagnation in winter wheat performance. 16 Pangenome analyses of the wheat pathogen Zymoseptoria tritici reveal the structural basis of a highly plastic eukaryotic genome We constructed and analyzed the pangenome of Zymoseptoria tritici , a major pathogen of wheat that evolved host specialization by chromosomal rearrangements and gene deletions. We used single-molecule real-time sequencing and high-density genetic maps to assemble multiple genomes. We annotated the gene space based on transcriptomics data that covered the infection life cycle of each strain. Based on a total of five telomere-to-telomere genomes, we constructed a pangenome for the species and identified a core set of 9149 genes. However, an additional 6600 genes were exclusive to a subset of the isolates. The substantial accessory genome encoded on average fewer expressed genes but a larger fraction of the candidate effector genes that may interact with the host during infection. We expanded our analyses of the pangenome to a worldwide collection of 123 isolates of the same species. We confirmed that accessory genes were indeed more likely to show deletion polymorphisms and loss-of-function mutations compared to core genes. 17 Expressed Ay HMW glutenin subunit in Australian wheat cultivars indicates a positive effect on wheat quality Out of the six HMW-GS genes, 1Ay is usually not expressed in bread wheat cultivars . In the current study, an active 1Ay gene has been integrated into two Australian wheat cultivars, Livingston and Bonnie Rock, through conventional backcross approach. Three sister lines at BC4F4 generation for each cross were obtained and underwent a series of quality testing. Results show that the active 1Ay subunit increased the amount total protein, Glutenin/Gliadin ratio and unextractable polymeric protein. The expressed 1 Ay also resulted in up to 10% increase of gluten content, 5% increase of glutenin, and hence increased the HMW- to LMW-GS ratio without affecting the relative amount of other subunits. Milling yield and Flour swelling were decreased in the Livingston lines and remained mostly unchanged for Bonnie Rock. Alveograph result showed that Ay improved dough strength in Livingston and dough extensibility in Bonnie Rock. Zeleny sedimentation value was found to be higher in all three lines of Bonnie Rock but only in one of Livingston derivatives. The dough development time and peak resistance, determined on the micro Z-arm mixer were increased in most cases. Overall, the integration of Ay subunit showed significant positive effects in bread making quality.
12 29 本期作者：大汉武 胖丫 前几天关于锈病无毒基因解读的年末大餐（ 年末的惊喜一：小麦锈病史上具有里程碑意义的进展！ ， 再析小麦锈病里程碑进展-植物病害流行学角度 ），不知大家感受如何？小编悄悄看了下阅读量，创了历史新高，这倒不是解读的好，主要是结果太震撼了！同时也看出大家的关注程度，抗病这块在小麦育种中还是举足轻重。 就在文章刚刚出来那会，小编第一时间联系到了文章的作者陈嘉鹏博士和 Zhang Peng 老师（这里首先感谢同门晓果同学和河北农大李在峰老师积极的联系）,了解到文章背后的一些小故事。多说一句，通讯作者Robert F. Park和Peter N. Dodds可谓是植物病理界冉冉升起的新秀。 在介绍本篇文章之前，首先要回顾两个常识，锈菌有两个核；锈菌是活体寄生，通过自身发育的吸器进入寄主细胞壁与细胞膜形成类似三明治结构。 本文用到两个小种，即野生型 Pgt279 和发生自然变异的 Pgt632 ，前者不可以侵染含有抗病基因 Sr50 的小麦材料，后者可以。作者对这两个小种的基因组进行了全基因组重测序，经过多步生信分析和筛选，两个小种与锈菌参考基因组PGTAus-pan相比分别约有110万个杂合变异（包括单碱基/多碱基的变异, single/multiple nucleotide variants, SNVs/MNVs ; 和小片段插入及缺失）。（为什么作者费力的要挖掘杂合差异？在这里先卖个关子，后面会详细说明。）根据现有的认知，亚麻锈的无毒基因在吸器中表达，因此，作者优先鉴定了编码吸器分泌蛋白haustorial secreted protein (以下简称HSP)的基因592个。尽管没有新的非同义突变nonsynonymous（这次搞对了，哈哈） ，但是有18个HSP基因在 Pgt632 内发生了杂合性丢失（loss-of-heterozygosity，以下简称LOH，可以理解为在染色体发生重组时，其中一条染色体上的一小段发生了丢失）。通过比较这18个HSP基因的物理位置发现，LOH横跨了大约2.5Mb的物理区间，该区间包含4个完整的scaffolds以及1个scaffolds的部分，如下图 Pgt632 的杂合性丢失可能是突变体发生了片段缺失，这会使该区域的DNA拷贝数减半；或者是两个单倍核发生体细胞重组，此时DNA拷贝数不会变化。所以只要检测DNA拷贝数是否变化就可以验证 Pgt632 的杂合性丢失是如何发生的。这个问题就简单了，统计该区域标准化之后的reads覆盖度发现，野生型 Pgt279 和突变型 Pgt632 之间DNA拷贝数相同。进一步对该区域内的一些基因位点进行覆盖度统计和分析，发现两个小种之间也没有差异。如下图A-C 进一步的定量PCR实验验证拷贝数未发生变化。 我想作者此刻的心情是无比兴奋的，他坚定地得出以下结论：该区域的杂合性丢失是由锈菌中的两个单倍核型发生了交换引起的。于是给出了以下几句话（我个人觉得这是本文最重要的发现之一）：Although it is not clear how genetic exchange occurs between the two separate haploid nuclei, which are thought to replicate independently , genetic evidence suggests that nuclear exchange and recombination between coinoculated rust isolates can result in previously unknown virulence combinations . There is also evidence for nuclear fusion in Pgt , and somatic hybridization has been postulated as a mechanism underlying the emergence of new lineages in asexual rust populations . 大意是虽然目前还不清楚两个单独的单倍体细胞核之间是如何发生遗传交换的，但遗传证据却表明以前被认为独立复制的两个核的确发生了遗传物质的交换，这种遗传交换会引起小种毒力的变化，以往已经有很多证据，比如核融合，体细胞杂交等都是除了有性重组之外引起遗传物质变化的重要原因。 既然推出了突变型突变的可能原因，那么接下来如何拿到候选基因呢？此刻一个不容忽视的问题摆在了面前，该区间约有2.5Mb。作者率先将该区域所有可能的HSP基因注释了一遍，共有24个，然后比较他们在突变菌Pgt632上丢失但是在野生菌Pgt279杂合率接近0.5的，再进行实验验证。最后只有一个AvrSr50 candidate, 当HSP#8 (HSGS210 |asmbl_13131|m.9539) 与Sr50共表达后能够成功引起细胞坏死实验，并通过酵母双杂等一系列实验验证了结果。这个无毒基因编码132氨基酸，且与已知的鉴定出来的无毒蛋白没有同源性，AvrSr35编码的是578氨基酸，目前同样也是独一的，看来小麦锈菌的无毒蛋白多样 性还很丰富。 还有一张图，见下。作者主要对秆锈菌编码外泌蛋白的基因表达进行了聚类分析，分别从吸器，牙管，及侵染小麦叶片2-7天的这几个层面。 到了这里，本篇解析基本完毕。但是标题说了，还有背后的故事，哈哈。确实有点小故事，彩蛋来了。话说当年Park教授在温室中像往常一样对秆锈菌进行扩繁或者鉴定工作，当他用 Pgt279 （野生型，不侵染 Sr50 基因材料）对含有 Sr50 的小麦材料接种时，突然发现后代出现了致病反应，Park很兴奋，小心的把它保存起来，在排除了锈菌污染和小麦材料可能是假杂种后，他们于2015年便开展了上述研究。另外，同年Lagudgh（偶像之一）率领的团队成功克隆到 Sr50 基因，为Park后期的工作奠定了坚实的基础。小编不由感慨，如果Park当时认为是由污染引起的而忽略它，可能就没有今天这个故事了，所以，科研实验还是要善于观察，留心记录的，另外还要有丰富的基础知识，大胆提出假设。这两篇文章的一作貌似都是做生物信息出身的（再次对生信人顶礼膜拜！），他们通过科学的算法使得科研思路能够实现。当然，也非一帆风顺，本篇一作嘉鹏博士邮件里跟我说，他们后面总共在候选区域预测了25个候选基因，实际上是一个一个进行了验证，当验证到第15个的时候，结果出来了.....看来科研还需要一颗恒心，一次两次失败不要紧，三次四次不要紧，起码像人家弄到15次，哈哈。每一个成功的背后都是辛苦的付出，探究永远在路上！ 欢迎关注 “ 小麦研究联盟 ”， 了解小麦新进展 请点击此处输入图片描述 投稿、转载、合作以及信息分布等请联系： wheatgenome
Dissect the bread wheat genome using next-generation sequencing. The sequence data do cover nearly all wheat genes. The size of wheat genome is about 17 gigabase pairs. About 80% of the genome sequences are repetitive sequences. 94,000-96,000 genes were identified, and this number is consistent with the number of genes identified from A, B and D genome ( T. monococcum and Ae. speltoides and Ae. tauschii ). Based on the sequence data from T. monococcum and Ae. speltoides and Ae. tauschii , 2/3 of these identified genes were assigned to A, B and D genome. Using the full-length cDNA sequences from rice, sorghum, brachypodium and barley, the 454 reads of bread wheat were assembled and 949,279 sequences were identified. By comparing these sequences with the Brachypodium genome, the sequence conservation was investigated. Brachypodium sequence on 1 and 4 chromosomes showed less conservative with sequences from bread wheat. Generally, genes lost during the polyploidy process. But several class of gene families with the role of defence, nutrition content, energy metabolism and growth have increased size (due to domestication). I think, the major contribution of this work is that it produced nearly all the wheat genome sequence and assembled nearly all gene sequences. But no physical map, no location of these genes. It is much easier to get the copy number of certain gene in bread wheat. Here is the report from Scientific American _" New Slice of Wheat Genome Could Help Feed Growing Global Population " http://blogs.scientificamerican.com/observations/2012/11/28/new-slice-of-wheat-genome-could-help-feed-growing-global-population/ Decoding our daily bread_Peter Langridge.pdf wheat genome_nature_2012.pdf
标签: wheat
