河南省近年审定小麦品种基于系谱和SNP标记的遗传多样性分析

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曹廷杰, 谢菁忠, 吴秋红, 陈永兴, 王振忠, 赵虹, 王西成, 詹克慧, 徐如强, 王际睿, 罗明成, 刘志勇. 河南省近年审定小麦品种基于系谱和SNP标记的遗传多样性分析. 41(2): 197-206
CAO Ting-Jie, XIE Jing-Zhong, WU Qiu-Hong, CHEN Yong-Xing, WANG Zhen-Zhong, ZHAO Hong, WANG Xi-Cheng, ZHAN Ke-Hui, XU Ru-Qiang, WANG Ji-Rui, LUO Ming-Cheng, LIU Zhi-Yong. Genetic Diversity of Registered Wheat Varieties in Henan Province Based on Pedigree and Single-Nucleotide Polymorphism. Acta Agronomica Sinica, 41(2): 197-206 复制到剪切板

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作物学报编辑部

河南省近年审定小麦品种基于系谱和SNP标记的遗传多样性分析

曹廷杰^1,², 谢菁忠¹, 吴秋红¹, 陈永兴¹, 王振忠¹, 赵虹², 王西成², 詹克慧³, 徐如强⁴, 王际睿⁵, 罗明成⁶, 刘志勇¹^*

¹中国农业大学植物遗传育种系, 北京 100193

²河南省农业科学院小麦研究所, 河南郑州 450002

³河南农业大学, 河南郑州 450002

⁴郑州大学生命科学院, 河南郑州 450001

⁵四川农业大学小麦研究所, 四川成都 611130

⁶University of California at Davis, Davis, CA 95616, USA

^*通讯作者(Corresponding author): 刘志勇, E-mail: zhiyongliu@cau.edu.cn

第一作者联系方式: E-mail: caotingjie893@163.com

收稿日期:2014-12-19

基金:本研究由国家重点基础研究发展计划(973计划)项目(2011CB100104)资助;

摘要

为了解河南省近年小麦品种的遗传基础, 利用Illumina 90k iSelect SNP标记技术对豫麦34及该省2000—2013年审定的小麦品种共96个进行全基因组扫描, 分析了其遗传多样性和遗传基础。结果表明, 在所有SNP位点中, 多态性比率为47.39% (38 661/81 587), 多态性标记在基因组间分布呈现B>A>D。96个品种亲缘关系较近, 两两遗传相似系数的平均值为0.719, 变幅为0.552~0.998, 且94.3%的品种间遗传相似系数在0.652~0.812之间; 按UPGMA法将96个品种划分为7个类群。综合SNP和系谱分析, 近10年河南省审定的96个小麦品种遗传多样性不够丰富, 多数品种亲缘关系较近, 在育种中迫切需要引入新的种质资源, 拓宽遗传背景。

关键词: 河南省; 小麦品种; 遗传多样性; SNP

Genetic Diversity of Registered Wheat Varieties in Henan Province Based on Pedigree and Single-Nucleotide Polymorphism

CAO Ting-Jie^1,², XIE Jing-Zhong¹, WU Qiu-Hong¹, CHEN Yong-Xing¹, WANG Zhen-Zhong¹, ZHAO Hong², WANG Xi-Cheng², ZHAN Ke-Hui³, XU Ru-Qiang⁴, WANG Ji-Rui⁵, LUO Ming-Cheng⁶, LIU Zhi-Yong^1,^*

¹ Department of Plant Genetics & Breeding, China Agricultural University, Beijing 100193, China

² Wheat Research Institute, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China

³Henan Agricultural University, Zhengzhou 450002, China

⁴ School of Life Science, Zhengzhou University, Zhengzhou 450001, China

⁵ Wheat Research Institute, Sichuan Agricultural University, Chengdu 611130, China

⁶University of California at Davis, Davis, CA 95616, USA

Abstract

To understand the genetic diversity of wheat varieties in Henan Province at whole genome level, we selected 96 registered wheat varieties in the past decade for SNP genotyping using the Illumina 90k iSelect SNP chip. The results showed that 47.39% of the SNPs (38 661 out of 81 587) were polymorphism between varieties. The genome distribution of polymorphic SNPs showed a tendency of B > A > D. The genetic similarity of the 96 varieties ranged from 0.552 to 0.998 with an average value of 0.719. However, genetic similarity of 0.652 to 0.812 was found for 94.3% of the tested varieties, indicating highly similarity for most of the varieties in Henan province. The 96 wheat varieties could be classified as seven groups by UPGMA analyses. Based on pedigree and SNP analyses, very narrow genetic background was observed for the registered varieties in the past decade in Henan province. It is an urgent task for wheat breeders to explore and introduce diversified germplasm resources into wheat breeding program to increase the yield potential and stress tolerance in the future.

Keyword: Henan Province; Wheat varieties; Genetic Diversity; SNPs

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小麦(Tritium aestivum L.)是世界上主要粮食作物之一。在我国, 小麦是仅次于水稻和玉米的第三大粮食作物, 在农业生产中占有十分重要的地位。河南省是我国小麦主产区和商品粮产区, 也是小麦育种工作起步较早、发展较快的省份。自20世纪40年代以来, 河南小麦育种取得了很大成就, 促成生产用种9次大规模的更换。然而, 近十几年来, 由于在小麦育种中大量使用相同和相近的亲本, 导致新育成品种遗传基础日益狭窄、遗传变异率低^{[1, 2]}, 极大限制了小麦产量和品质的进一步改良, 而且还使小麦生产应对不良环境的能力大大降低, 增加潜在的用种风险。因此, 对河南省近年来审定小麦品种进行遗传多样性分析, 全面了解这些品种的遗传基础和亲缘关系, 对发掘利用优异的育种材料, 拓宽遗传基础, 加快小麦育种改良进程具有重要意义。

根据系谱分析小麦育成品种的遗传多样性及其与骨干亲本的亲缘关系, 虽然可以大致判断品种间遗传差异, 但难以量化, 存在一定局限性。一个新品种的选育过程往往是育种家对某一亲本经过连续多年的遗传改良, 最终选择出优良品系, 其遗传构成可能源于多个亲本, 加之部分品种系谱来源复杂或存在不确定性, 通过系谱追踪难以准确判断其遗传物质来源。近年来随着DNA分子标记技术的出现, 为在DNA水平上评估不同品种间的亲缘关系及计算品种间的遗传距离提供了新的方法和手段。Sun等^[3]利用RAPD标记技术分析了西藏小麦、普通小麦和欧洲斯卑尔托小麦遗传多样性, 发现欧洲斯卑尔托小麦和西藏小麦遗传多样性远高于普通小麦; Wang等^[4]利用SSR标记技术分析发现我国云南和西藏小麦品种的遗传多样性高于新疆小麦品种; Talebi等^[5]利用AFLP标记分析表明伊朗小麦品种遗传多样性丰富。虽然RAPD、SSR和AFLP等分子标记均已应用于小麦品种的遗传多样性研究, 但受方法和位点数量的限制, 无法从全基因组水平上进行高通量遗传研究。

单核苷酸多态性(single nucleotide polymorphism, SNP)是普遍存在于生物基因组中的一种新型分子标记, 是指在基因组水平上由单个核苷酸的变异而引起的DNA序列单个碱基多态性变化。SNP是二等位基因, 具有在基因组中数量最多、分布密度高、无需电泳、可高通量自动化检测等特点^{[6, 7]}。大规模、高通量SNP芯片检测首先广泛应用于人类群体结构的遗传学研究和关联性分析^[8], 商业化的SNP芯片也已被应用于一些家畜全基因组关联分析、QTL定位和候选基因筛选^{[9, 10]}。在植物中, Clark等^[11]利用高通量SNP芯片技术对模式植物拟南芥不同品系进行了多态性研究。近年来, 随着小麦EST测序和高通量测序研究工作的开展, SNP开发和利用进展迅速^[12]。Cavanagh等^[13]和Wang等^[14]开发了小麦基于Illumina技术平台的9k和90k高通量SNP分析芯片, 已开始应用于小麦遗传连锁图谱的构建、DNA指纹分析、群体结构和连锁不平衡分析, 以及基因定位等诸多领域。SNP标记能真实反映小麦品种间的亲缘关系^{[15, 16, 17]}, 可以用于小麦品种遗传多样性研究。

近十几年来, 河南省审定的小麦品种有近百个, 但尚未见到从全基因组水平上对其遗传多样性和亲缘关系进行研究的报道。本研究采用Illumina 90k iSelect SNP标记技术对近年来河南省审定的96个小麦品种的遗传基础进行分析, 旨在了解这些品种在全基因组水平上的遗传多样性和亲缘关系, 以期为小麦新品种选育的亲本选配提供理论依据。

1 材料与方法

1.1 小麦品种及其DNA提取

除豫麦34外, 其他供试品种均为2000— 2013年河南省审定的品种或生产上种植面积较大的国家审定品种, 共计96个(见附表), 分别由品种育成单位提供, 各品种的系谱资料源自品种参试时育种单位提供的信息。

2012年10月在中国农业大学小麦遗传育种温室种植, 植株长至二叶一心时, 取小麦叶片, 按Saghai-Maroof等^[18]的CTAB法提取基因组DNA。

1.2 SNP芯片分析

利用Illumina 90k iSelect SNP标记对96个小麦品种进行全基因组扫描, 采用Genome Studio Polyploid Clustering Module v1.0进行样本的原始SNP分型, 由美国加州大学戴维斯分校基因组中心完成。

将SNP分型数据分别记为1 (纯合AA)、2 (杂合AB)、3 (纯合BB)和0 (缺失), 建立原始矩阵。用NTSYS-PC ver. 2.1 统计软件计算品种间遗传相似系数, 采用非加权配对算术平均法(UPGMA)构建遗传关系树状图。

2 结果与分析

2.1 多态性SNP位点的分布

在分布于21条染色体的81 587个SNP位点中, 38 661个被检测到多态性, 多态性比率为47.39%, 其中28 761个定位于染色体上。每条染色体分布106~2685个多态性位点, 差异较大, 且在A、B、D基因组上分布不均。以B基因组最多(14 049个, 占48.85%), 尤其是1B上最多, 2B和5B上次之; A基因组上多态性位点为11 548个, 占40.15%, 以5A、6A和7A上较多; D基因组上多态性位点最少, 仅有3164个, 占11.00%, 尤以4D上最少(图1-A)。整体来看, 1B、5B和2B染色体上多态性位点最多, 4D染色体上多态性位点最少。

多态性SNP位点在7个部分同源群中分布也不均匀, 在第1和第2部分同源群上分布最多, 其次是在第5和第6部分同源群上, 而在第4部分同源群最少(图1-B)。

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	图1 多态性位点在染色体(A)和部分同源群(B)上的分布Fig. 1 Distributions of polymorphic SNPs on individual chromosome (A) and each homoeologous group (B)

2.2 小麦品种间的遗传相似系数

基于SNP标记数据的品种两两间遗传相似系数, 其变异范围为0.552~0.998, 平均值为0.719, 其中中育9号与矮抗58间的遗传相似性最低(0.552), 而周麦22与周麦23间的遗传相似性最高(0.998)。

96个供试品种两两计算, 共获得4560个遗传相似系数, 以0.02为组距进行次数分布分析, 可见, 96个品种间的遗传相似系数在0.7处分布密度最大, 两侧不对称(图2)。经卡平方测验, 不符合正态分布(P < 0.01), 呈左偏态分布; 大于0.7的遗传相似系数有2812个(61.67%), 小于0.7的有1748个(38.33%); 主要分布在0.63~0.83之间, 占95.94% (4375/4560)。

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	图2 品种间遗传相似系数的次数分布Fig. 2 Distribution of genetic similarity between varieties

为了探讨近十几年来河南省审定小麦品种遗传多样性的演变趋势, 将96个品种按审定年份分为3组, 每组的品种数接近, 可见组内品种的遗传相似性均较高, 且自2005年以后平均遗传相似系数有升高趋势(表1)。

表1 不同阶段审定品种的遗传相似系数 Table 1 Genetic similarity coefficient of Henan wheat cultivars at different period

2.3 聚类分析

根据小麦SNP遗传相似系数矩阵进行聚类分析, 96个品种被划分为7大类群, 其中矮抗58单独组成第I类, 第II和第III类各有7个品种, 第IV类有17个品种, 第V类41个品种, 第VI和第VII类分别包括10个和13个品种(图3)。

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	图3 河南省96个审定小麦品种的SNP数据聚类图Fig. 3 Phylogenetic tree of 96 registered wheat varieties in Henan Province revealed by SNP

第II类品种间的遗传相似系数变幅在0.658~ 0.988之间, 平均0.735, 有4个为优质强筋品种, 其中豫麦34是郑农16 (豫麦34/小偃6号)的亲本之一, 二者相似系数为0.988; 郑麦9023、西农979和平麦998均是以小偃6号作为间接亲本而育成的品种, 在遗传基础上具有很高的亲缘性。

第III类品种间遗传相似系数为0.702~0.976, 平均0.784。这些品种均具有早熟特性, 除泛麦8号和洛麦24外, 其他均为直接或间接利用豫麦18育成的品种。丰舞981是漯麦4号的系选品种, 而漯麦4号的母本是豫麦18; 睢科2号的母本是漯麦4号, 所以丰舞981与睢科2号的亲缘关系较近, 其遗传相似系数为0.976; 洛麦24并非由豫麦18直接选育而成, 但其亲本之一的洛太911在田间表现与豫麦18极为相似, 且均为偃师4号的后代。

第IV类的17个品种间遗传相似系数变幅在0.681~0.906, 平均0.761。这些品种是以新乡市农业科学院选育的品种及其衍生品种为主, 它们大多是以百泉3047-3、百泉3199、内乡82C6为亲本选育出的品种。如新麦18和新麦19都是以(C5/新乡3577)F₃ d1s作为母本, 以新麦9号作为父本选育而成的小麦品种, 其遗传相似系数为0.906; 周麦20的亲本之一也是新麦9号。

第V类品种数最多, 有41个, 占42.7%, 品种间遗传相似系数为0.647~0.998, 平均0.769。这些品种的亲本大多含有豫麦21、周麦11及8425B中的1个或2个, 有的则源自这3个品种的衍生系, 如以周麦16、周麦13等为亲本选育出的品种, 均聚在这一类群中。

第VI类的10个品种间遗传相似系数变幅最小(0.719~0.933)之间, 平均值最高(0.801)。它们主要是以豫麦2号或者其衍生系豫麦49及豫麦41为亲本之一育成的品种。如太空6号是豫麦49通过航天诱变选育而成; 豫麦49-198为豫麦49的系选品种, 两者的相似系数为0.933。

第VII类包含13个品种, 其遗传相似系数变幅在0.664~0.966之间, 平均值为0.721, 均是以偃师4号衍生系, 如豫麦18、周麦8826、豫麦10号、豫麦21为亲本之一育成的品种, 并且都继承了偃师4号的优良性状。

聚类分析结果表明, 河南省近十几年来审定的品种在DNA水平上的差异不大, 大部分品种的亲缘关系较近, 遗传基础较窄。

3 讨论

近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]}。但由于受环境等自然因素的影响和标记数量的限制, 无法从全基因组水平上进行研究。本研究选用分布于小麦21条染色体上的81 587个SNP位点对河南省近年来审定的96个小麦品种进行了全基因组扫描, 发现SNP位点多态性比率为47.39%, 其中, 以B基因组上的多态性位点最多, A基因组次之, D基因组最少, 与贾继增等^[19]运用RFLP标记对来自11个国家的15个小麦品种(系)进行遗传多样性分析研究结果一致。究其原因, 主要是普通小麦进化过程中D基因组与AABB基因组形成六倍体小麦时间较短, 且来源比较单一, 品系间多态性较低。另外D基因组可能携带较多的与普通小麦广适应性、抗逆性和加工品质等重要性状的关键基因, 在长期的选择和育种过程中, 所承受的选择压力大于A和B基因组, 从而造成更多、更强的选择牵连效应发生, 导致其遗传多样性低。本研究中尤其以4D染色体上的多态性位点最少, 这与郝晨阳等^[1]和倪中福等^[20]研究结果一致。推测与4D染色体上可能携带较多控制重要性状的基因(如育性基因、矮秆基因等), 在育种过程中施加了较强的定向选择所产生的选择牵连作用, 导致其遗传多样性显著偏低。贾继增等^[19]报道过与此不同的结果, 他们研究发现, 1D和5D遗传多样性最小, 通过分析多态性RFLP位点在7个部分同源群的分布发现, 第1和第2部分同源群最多, 第4部分同源群最少。这可能是由于不同试验所选取的材料来源不同造成的。

许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21, 22, 23, 24, 25, 26, 27, 28, 29]}。本研究进一步证实河南省近期选育的小麦品种存在亲缘关系近、遗传相似性高的问题, 并且有进一步加重的趋势, 这将导致很难获得突破性育种进展, 降低品种抵御各种自然灾害的能力, 增加潜在的用种风险。造成河南省小麦品种遗传多样性水平低、遗传基础狭窄的原因可能一是核心骨干亲本的反复利用, 二是定向人工选择。本研究通过聚类和系谱分析, 发现河南省小麦骨干亲本品种主要由6大血缘系统组成, 分别是周麦、新麦、偃师4号、豫麦2号、豫麦18和陕西小麦系统。周麦系统主要是以周麦品种和周8425B为亲本材料, 利用该血缘系统育成的品种数量最多, 占整个参试品种总数的42.7%, 高产、稳产性特点突出; 新麦系统主要以百泉3047-3、百泉3199、内乡82C6为亲本; 偃师4号系统包括以偃师4号为间接亲本选育的品种; 豫麦2号系统是以豫麦2号及其后代豫麦49作为育种亲本; 豫麦18系统均包括豫麦18血统, 突出特点是早熟; 陕西小麦血统为亲本选育的品种的主要特点是优质强筋。定向人工选择可能是河南省小麦遗传多样性降低的另一个主要原因。河南省地处黄淮麦区, 生态条件适宜小麦的生长发育和产量潜力的发挥, 育种家根据对产量有利的目标性状进行选择的趋势, 导致部分多样化基因位点丢失, 使品种的优良性状趋于类似。由于周麦系列具有较好的综合农艺性状和丰产性, 得到大部分育种家的认可和偏爱, 成为选配高产组合的首选亲本材料, 因此导致近十几年来河南省审定小麦品种中有将近一半直接或间接含有周麦品种血缘。

虽然聚类结果与品种特性和系谱信息有较好的一致性, 但也有例外。如矮抗58是以周麦11为母本, 以豫麦49和郑州8960杂交后代为父本选育而成的品种, 但它并没有与周麦11和豫麦49的后代品种聚在一类; 浚2016和众麦998之间的相似系数为0.996, 田间长相也十分接近, 但系谱记载表明两者没有直接的亲缘关系。其可能原因一是供试种子来源, 由于亲本材料的搜集渠道很多, 可能会存在材料本身与名称不符的现象; 二是育种家定向选择的结果, 多年的选择往往都集中在某些或某个位点, 从而导致其他某些或某个位点的丢失, 尤其在同一生态区; 三是系谱记载不完善。另外, 遗传变异(含重组)也可能是产生上述现象的重要原因。

值得注意的是, 尽管近年来河南省小麦育种中因大量使用相同或类似的骨干亲本或骨干亲本衍生材料做亲本, 致使育成的小麦品种遗传差异不明显、遗传基础狭窄、多样性水平较低, 但可以看出, 河南省的小麦品种间仍然存在一定的类群分化和遗传多样性, 可分为周麦类型、新麦类型、陕西优质类型、豫麦2号类型和早熟豫麦18类型。纵观河南省生产上得以大面积推广利用的代表性小麦品种, 它们都具有独特的遗传构成, 其中以矮抗58最为典型, 该品种表现高产、稳产、广适、抗性强, 在聚类图中自成一类, 众多优异性状的组合是否来自有利基因的聚合和重组, 有待深入研究。

针对河南省小麦育种策略, 建议一方面要继续广泛收集种质资源, 加强与国内外育种单位资源材料间的交流与合作, 不断拓宽小麦亲本的遗传基础; 另一方面要大力加强种质资源的创新研究和利用, 利用当地的高产小麦品种与从国内外引进的优异基因资源进行聚合杂交和回交转育, 创造新的优异中间育种材料, 突破主产区小麦育种的瓶颈, 使河南省小麦育种水平跨上新台阶。

4 结论

多态性SNP位点在不同染色体和7个部分同源群间分布不均匀, 其中以4D染色体上的多态性位点最少。品种间的遗传相似度较高, 遗传相似系数平均值为0.719, 并且有增加的趋势。河南省小麦品种间存在一定的类群分化和遗传多样性, 代表性小麦品种都具有其独特的遗传构成。

附表用于SNP分析的小麦品种名称及系谱 Supplementary table The wheat varieties for SNP genotyping and their pedigrees

序号 Order	品种 Variety	系谱 Pedigree	育种单位 Breeding institute	审定年份 Year registered
1	豫麦34	矮丰3号//孟201/牛朱特/3/豫麦2号	河南郑州市农林科学研究所	1994
2	中育6号	烟1604/中育3号	中国农业科学院棉花研究所	2000
3	新麦9号	百泉3047-3/内乡82C6	河南新乡市农业科学院	2000
4	郑麦9023	西农881/陕213	河南省农业科学院小麦研究所	2001
5	中育5号	冀麦5418/豫麦10号	中国农业科学院棉花研究所	2001
6	安麦1号	百农3217/9612-2//周8826	河南安阳市农业科学研究所	2001
7	新麦11	百泉30473/内乡82C6	河南新乡市农业科学院	2001
8	济麦1号	731429A/郑7025/2/郑821/3/豫麦21	河南济源市农业科学研究所	2001
9	偃高1号	(西农806/比16)F₃//洛阳7602	河南偃师市高龙镇农技站	2002
10	洛麦1号	Tal不育株/周8832(早)//南阳756	河南洛阳市农林科学院	2002
11	周麦16	豫麦21/周8425B	河南周口市农业科学院	2002
12	周麦20	周麦13/新麦9号//豫麦49	河南周口市农业科学院	2002
13	新麦12	豫麦24/豫麦21	河南新乡市农业科学院	2002
14	新麦13	宛原长白/(C5/3577)F₃ d1	河南新乡市农业科学院	2002
15	太空6号	豫麦49航天诱变	河南省农业科学院小麦研究所	2003
16	郑农17	豫麦51/优繁5号	河南郑州市农林科学研究所	2003
17	郑农16	豫麦34/小偃6号	河南郑州市农林科学研究所	2003
18	中育8号	鲁麦15/93中6	中国农业科学院棉花研究所	2003
19	新麦16	郑州891/内乡82C6/豫麦2号	河南新乡市农业科学院	2003
20	偃展4110	89(35)-14/矮早781-4	河南省豫西农作物品种展览中心	2003
21	郑麦004	豫麦13/90m434//石89-6021	河南省农业科学院小麦研究所	2004
22	睢科2号	漯麦4号/西北矮秆选系(97-26)	河南省睢县农业科学研究所	2004
23	周麦17	矮早781/周8425B//豫麦21	河南周口市农业科学院	2004
24	安麦7号	豫麦13/周8826	河南安阳市农业科学研究所	2004
25	中育9号	豫麦21/92R139	中国农业科学院棉花研究所	2004
26	豫农9901	咸阳超大穗/豫农8923	河南农业大学	2004
27	濮麦9号	(徐州174/内乡183)/豫麦24	河南濮阳市农业科学院	2004
28	温9519	兰考4号/温2540	河南温县农业科学研究所	2004
29	泛麦5号	京泛309/82C6	河南黄泛区农场农业科学研究所	2004
30	泛麦3号	豫同843/苏麦3号	河南黄泛区农场农业科学研究所	2004
31	温9629	豫麦21/豫麦41	河南温县农业科学研究所	2004
32	丰舞981	豫麦18/80(6)-3-3-10	河南舞阳县种子公司	2004
34	新麦18	(C5/新乡3577)F₃ d1//新麦9号	河南新乡市农业科学院	2004
35	周麦18	内乡185/豫麦21	河南周口市农业科学院	2004
36	开麦18	开64/89中170//开1003/温2540	河南开封市农林科学研究院	2004
37	矮抗58	周麦11//豫麦4号9/郑州8960	河南科技学院	2005
38	豫麦49-198	394A/豫麦2号	河南平安种业有限公司	2005
39	新原958	豫麦34/新麦9号	河南省新乡县原种场	2005
40	西农979	西农2611/(918/95选1) F₁	西北农林科技大学	2005
41	许农5号	周麦8846/豫麦21	河南许昌市农业科学研究所	2005
42	郑麦366	豫麦47/PH82-2-2	河南省农业科学院小麦研究所	2005
43	花培5号	(豫麦18/花4-3) F₁花药培养	河南省农业科学院小麦研究所	2006
44	花培3号	花953350-1-2/花965437-1-1	河南省农业科学院小麦研究所	2006
45	花培1号	百农64/豫麦21	河南省农业科学院小麦研究所	2006
46	富麦2008	豫麦18/80(6)-3-3-10	河南省科学院同位素研究所	2006
47	项麦969	豫麦21/豫麦18//豫麦18	河南项城市农业科学研究所	2006
48	豫农201	内乡182/818036//太910889/石6021	河南农业大学	2006
49	04中36	百农64/周麦11	中国农业科学院棉花研究所	2006
50	洛麦21	周麦13/洛麦1号	河南洛阳市农林科学院	2006
51	平安6号	莱州953/温2540	河南平安种业有限公司	2006
52	豫展4号	百农64/周麦13	河南省农作物品种展览中心	2006
53	郑麦9694	豫麦21/豫麦18//豫麦21	河南省农业科学院小麦研究所	2006
54	新麦19	(C5/新乡3577) F₃ d1/新麦9号	河南新乡市农业科学院	2006
55	漯麦8号	烟中1604/豫麦41	河南漯河市农业科学院	2007
56	郑育麦9987	豫麦2号/豫麦21//豫麦55	河南郑州友邦农作物新品种研究所	2007
57	中育10号	豫麦41/宝丰94-24//豫麦49	中国农业科学院棉花研究所	2007
58	豫农202	豫麦21/豫农127	河南农业大学	2007
59	许科1号	97-042/漯麦4号	河南许科种业有限公司	2007
60	周麦22	周麦12/豫麦49//周麦13	河南周口市农业科学院	2007
61	漯麦9号	周麦13/百农64	河南漯河市农业科学院	2008
62	花培6号	豫麦21/豫麦2号//漯麦4号	河南省农业科学院小麦研究所	2008
63	众麦998	百农71-22/矮早781//温2540/苏芙林10	河南省新安县科协	2008
64	周麦23	周麦13/新麦9号	河南周口市农业科学院	2008
65	平麦998	豫麦21/陕优225	河南省平顶山市农业科学研究所	2008
66	洛麦22	周麦13/豫麦49	河南洛阳市农林科学院	2008
67	中育12	矮败小麦轮选群体	中国农业科学院棉花研究所	2008
68	泛麦8号	泛矮2/原泛3号	河南黄泛区农场农业科学研究所	2008
69	豫保1号	豫麦2号/周8826	河南省农业科学院植物保护研究所	2008
70	花培8号	9824H-1-2/91138//91138	河南省农业科学院小麦研究所	2009
71	豫农416	豫麦49//豫麦21/豫麦35	河南农业大学	2009
72	豫农982	HY9153/百农3217//豫麦49	河南农业大学	2009
74	汝州0319	太谷核不育系轮回	河南汝州市农业科学研究所	2009
75	新麦21	偃展1号/新麦9号	河南新乡市农业科学院	2009
76	郑麦9962	豫麦18/Ta971832	河南省农业科学院小麦研究所	2010
77	浚2016	豫麦52/郑麦9023//周麦13	河南浚县农业科学研究所	2011
78	郑麦7698	郑麦9405/4B269//周麦16	河南省农业科学院小麦研究所	2011
79	丰德存麦1号	周9811/矮抗58	河南天存小麦改良技术研究所	2011
80	豫教5号	郑91138/豫麦49	河南教育学院	2011
81	太学7号	豫麦57/周麦16	河南洛阳太学农作物研究所	2011
82	许科316	周麦16/百农64	河南许科种业有限公司	2011
83	洛麦24	洛太911/淮阴9628	河南洛阳市农林科学院	2011
84	周麦25	周麦13/新麦9号//豫麦49	河南周口市农业科学院	2011
85	平安8号	豫麦2号/周麦13	河南平安种业有限公司	2011
86	兰考198	r81/百农64//偃展4110	河南天民种业有限公司	2011
87	开麦20	矮开79/开麦14	河南开封市农林科学研究院	2011
88	开麦21	鲁D9401/开麦16	河南开封市农林科学研究院	2011
89	郑麦379	周麦13/D9054-6-1(41)	河南省农业科学院小麦研究所	2012
90	郑麦583	矮抗58系选	河南省农业科学院小麦研究所	2012
91	许科718	周麦13/漯麦4号(61)	河南许科种业有限公司	2012
92	中育9398	矮败小麦/新麦18 (42)	中国农业科学院棉花研究所	2012
93	郑麦0856	郑麦9405/4B269//周麦16	河南省农业科学院小麦研究所	2012
94	天禾3号	矮败小麦/天禾077(45)	河南安阳市天禾农作物研究所	2012
95	周麦32	矮抗58/周麦24	河南周口市农业科学院	2013
96	许科415	周麦16/轮选01-1	河南许科种业有限公司	2013

附表用于SNP分析的小麦品种名称及系谱 Supplementary table The wheat varieties for SNP genotyping and their pedigrees

The authors have declared that no competing interests exist.

作者已声明无竞争性利益关系。

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[6]	Nasu S, Suzuki J, Ohta R, Hasegawa K, Yui R, Kitazawa N, Monna L, Minobe Y. Search for and analysis of single nucleotide polymorphisms (SNPs) in rice (Oryza sativa, Oryza rufipogon) and establishment of SNP markers. DNA Res, 2002, 9: 163-171 [本文引用:]
[7]	邹喻苹, 葛颂. 新一代分子标记-SNPs及其应用, 生物多样性, 2003, 11: 370-382 Zou Y P, Ge S. A novel molecular marker: SNPs and its application. Biodiversity Sci, 2003, 11: 370-382 (in Chinese with English abstract) [本文引用:1] [CJCR: 1.854]
[8]	Nishida N, Koike A, Tajima A, Ogasawara Y, Ishibashi Y, Uehara Y, Inoue I, Tokunaga K. Evaluating the performance of Afrymetrix SNP array 6. 0 platform with 400 Japanese individuals. BMC Genomics, 2008, 9: 431 [本文引用:1] [JCR: 4.397]
[9]	Karlsson E K, Baranowska I, Wade C M, Salmon Hillbertz N H, Zody M C, Anderson N, Biagi T M, Patterson N, Pielberg G R, Kulbokas , Comstock K E, Keller E T, Mesirov J P, von Euler H, Kämpe O, Hedhammar A, Land er E S, Andersson G, Andersson L, Lindblad-Toh K. Efficient mapping of Mendelian traits in dogs through genome-wide association. Nat Genet, 2007, 39: 1321-1328 [本文引用:1] [JCR: 35.209]
[10]	Anderson L. Genome-wide association analysis in domestic animals: a powerful approach for genetic dissection of trait loci. Genetica, 2009, 136: 341-349 [本文引用:1] [JCR: 1.681]
[11]	Clark R M, Schweikert G, Toomajian C, Ossowski S, Zeller G, Shinn P, Warthmann N, Hu T T, Fu G, Hinds D A, Chen H, Frazer K A, Huson D H, Schölkopf B, Nordborg M, Rätsch G, Ecker J R, Weigel D. Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science, 2007, 317: 338-342 [本文引用:]
[12]	Rafalski A: Applications of single nucleotide polymorphisms in crop genetics. Curr Opin Plant Biol, 2002, 5: 94-100 [本文引用:1] [JCR: 8.455]
[13]	Cavanagh C R, Chao S, Wang S, Huang B E, Stephen S, Kiani S, Forrest K, Saintenac C, Brown-Guedira G L, Akhunova A, See D, Bai G, Pumphrey M, Tomar L, Wong D, Kong S, Reynolds M, da Silva M L, Bockelman H, Talbert L, Anderson J A, Dreisigacker S, Baenziger S, Carter A, Korzun V, Morrell P L, Dubcovsky J, Morell M K, Sorrells M E, Hayden M J, Akhunov E. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat land races and cultivars. Proc Natl Acad Sci USA, 2013, 110: 8057-8062 [本文引用:1] [JCR: 9.737]
[14]	Wang S, Wong D, Forrest K, Allen A, Chao S, Huang B E, Maccaferri M, Salvi S, Milner S G, Cattivelli L, Mastrangelo A M, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, International Wheat Genome Sequencing Consortium, Plieske J, Mather D, Lillemo M, Dolferus R, Brown-Guedira G, Korol A, Akhunova A R, Feuillet C, Salse J, Morgante , Pozniak C, Luo M C, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards K J, Hayden M, Akhunov E. Characterization of polyploid wheat genomic diversity using a high-density 90, 000 single nucleotide polymorphism array. Plant Biotechnol J, 2014, 12: 787-796 [本文引用:1] [JCR: 6.279]
[15]	Ren J, Chen L, Sun D, You F M, Wang J, Peng Y, Nevo E, Beiles A, Sun D, Luo M C, Peng J. SNP-revealed genetic diversity in wild emmer wheat correlates with ecological factors. BMC Evol Biol, 2013, 13: 169 [本文引用:1] [JCR: 3.285]
[16]	Chao S, Dubcovsky J, Dvorak J, Luo M C, Baenziger S P, Matnyazov R, Clark D R, Talbert L E, Anderson J A, Dreisigacker S, Glover K, Chen J, Campbell K, Bruckner P L, Rudd J C, Haley S, Carver B F, Perry S, Sorrells M E, Akhunov E D. Population- and genome-specific patterns of linkage disequilibrium and SNP variation in spring and winter wheat (Triticum aestivum L. ). BMC Genomics, 2010, 11: 727 [本文引用:1] [JCR: 4.397]
[17]	Wurschum T, Langer S M, Longin C F, Korzun V, Akhunov E, Ebmeyer E, Schachschneider R, Schacht J, Kazman E, Reif J C. Population structure, genetic diversity and linkage disequilibrium in elite winter wheat assessed with SNP and SSR markers. Theor Appl Genet, 2013, 126: 1477-1486 [本文引用:1] [JCR: 3.658]
[18]	Saghai-Maroof M A, Soliman K M, Jorgensen R A, Allard R W. Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci USA, 1984, 81: 8014-8018 [本文引用:1] [JCR: 9.737]
[19]	贾继增, 张正斌, Devos K, Gale M D. 小麦21条染色体RFLP作图位点遗传多样性分析. 中国科学: C 辑, 2001, 31: 13-21 Jia J Z, Zhang Z B, Devos K, Gale M D. Genetic diversity of 21 chromosomes in wheat revealed by RFLP mapping. Sci China (Ser C), 2001, 31: 13-21 (in Chinese) [本文引用:3] [CJCR: 0.833]
[20]	倪中福, 张义荣, 梁荣奇, 刘广田, 孙其信. 普通小麦D染色体组微卫星分子标记遗传差异研究. 作物学报, 2003, 29: 145-151 Ni Z F, Zhang Y R, Liang R Q, Liu G T, Sun Q X. Genetic diversity of D-genome revealed by SSR markers in wheat (Triticum aestivum L. ). Acta Agron Sin, 2003, 29: 145-151 (in Chinese with English abstract) [本文引用:2] [CJCR: 1.667]
[21]	蒲艳艳, 程凯, 李斯深. 山东省近期育成小麦品种遗传多样性的SSR分析. 分子植物育种, 2011, 9: 443-449 Pu Y Y, Cheng K, Li S S. Genetic diversity of recent wheat cultivars in Shand ong Province using SSR markers. Mol Plant Breed, 2011, 9: 443-449 (in Chinese with English abstract) [本文引用:2] [CJCR: 1.23]
[22]	李志波, 王睿辉, 张茶, 梁虹, 马峙英, 赵玉欣, 王静华. 河北省小麦品种基于农艺性状的遗传多样性分析. 植物遗传资源学报, 2009, 10: 436-442 Li Z B, Wang R H, Zhang C, Liang H, Ma Z Y, Zhao Y X, Wang J H. Genetic diversity analysis of bread wheat (Triticum aestivum L. ) cultivars in Hebei Province based on agronomic traits. J Plant Genet Resour, 2009, 10: 436-442 (in Chinese with English abstract) [本文引用:2] [CJCR: 1.1628]
[23]	傅体华, 王春梅, 任正隆. 四川育成小麦品种的SSR遗传多态性及系谱关系. 四川农业大学学报, 2007, 25: 1-7 Fu T H, Wang C M, Ren Z L. SSR genetic diversity among modern advanced wheat cultivars (Triticum aestivum L. ) in Sichuan and its relationships with their pedigree. J Sichuan Agric Univ, 2007, 25: 1-7 (in Chinese with English abstract) [本文引用:2] [CJCR: 0.5]
[24]	李学军, 潘玉朋, 王小利, 李立群, 王培, 冯毅, 王辉. 陕西育成小麦品种的遗传多样性演变. 西北农林科技大学学报(自然科学版), 2011, 39: 48-54 Li X J, Pan Y P, Wang X L, Li L Q, Wang P, Feng Y, Wang H. Evolution of genetic diversity of the winter varieties grown at Shaanxi. J Northwest A&F Univ (Nat Sci Edn), 2011, 39: 48-54 (in Chinese with English abstract) [本文引用:2]
[25]	潘玉朋, 李立群, 郑锦娟, 王培, 冯毅, 李学军. 黄淮麦区近年大面积推广小麦品种的遗传多样性分析. 西北农业学报, 2011, 20: 47-52 Pang Y P, Li L Q, Zheng J J, Wang P, Feng Y, Li X J. Analysis of genetic diversity of the large-scale promoted wheat varieties grown at Huang-Huai area in recent years. Acta Agric Boreali- Occid Sin, 2011, 20: 47-52 (in Chinese with English abstract) [本文引用:2]
[26]	耿惠敏, 刘红彦, 宋玉立, 王俊美, 李锁平. 40个河南省审定小麦品种遗传多样性的SSR标记分析. 西北农业学报, 2005, 14: 27-32 Geng H M, Liu H Y, Song Y L, Wang J M, Li S P. SSR analysis of genetic diversity among forty released wheat cultivars in Henan Province. Acta Agric Boreali-Occident Sin, 2005, 14: 27-32 (in Chinese with English abstract) [本文引用:2]
[27]	徐晓丹, 冯晶, 蔺瑞明, 赵蕾, 林风, 徐世昌. 河南小麦主栽品种亲缘系数的分析. 麦类作物学报, 2011, 31: 653-659 Xu X D, Feng J, Lin R M, Zhao L, Lin F, Xu S C. Coefficient of parentage analysis for leading wheat cultivars in Henan Province. J Triticeae Crops, 2011, 31: 653-659 (in Chinese with English abstract) [本文引用:2] [CJCR: 1.007]
[28]	王冬梅, 冯晶, 王凤涛, 蔺瑞明, 徐世昌. 2010-2011年度四省小麦区试品种遗传多样性和抗条锈性分析. 植物保护, 2013, 39: 21-28 Wang D M, Feng J, Wang F T, Lin R M, Xu S C. Genetic diversity and stripe rust resistance of regional trial wheat cultivars in four provinces in 2010-2011. Plant Prot, 2013, 39: 21-28 (in Chinese with English abstract) [本文引用:2]
[29]	张清海, 王志和, 刘华山, 李铁庄, 周新宝, 李汉中, 韩秀云, 张智伟, 闵保锋, 张宏涛. 河南主要推广小麦品种系谱追溯及其亲本组配技术分析. 中国农学通报, 2000, 16: 3-6 Zhang Q H, Wang Z H, Liu H S, Li T Z, Zhou X B, Li H Z, Han X Y, Zhang Z W, Min B F, Zhang H T. The pedigree analysis and techniques for parent combination of the major wheat extension varieties in Henan Province. Chin Agric Sci Bull, 2000, 16: 3-6 (in Chinese with English abstract) [本文引用:2]

2005

0.0

0.833

郝晨阳, 王兰芬, 张学勇, 游光霞, 董玉琛, 贾继增, 刘旭, 尚勋武, 刘三才, 曹永生. 我国五十年来育成小麦品种的遗传多样性演变. 中国科学: C辑, 2005, 35: 408-415

Hao C

, Wang L

, Zhang X

, You G

, Dong Y

, Jia J

, Liu

, Shang X

, Liu S

, Cao Y

Genetic diversity changes of Chinese cultivars in the past 50 years.

Sci China (Ser C), 2005, 35: 408-415 (in Chinese)

对我国小麦育成品种初选核心种质(1680份)的78个微卫星标记(SSR)位点进行了扫描, 并就此对50年来育成品种的遗传多样性进行了评价和分析, 得到以下结果和结论: (ⅰ) 74对SSR荧光引物共检测到1336个等位变异, 其中1253个等位变异可以定位在71个位点上. 这71个位点上检测到的每个位点等位变异数为4~44个, 平均17.6个; 多态性信息指数(PIC)为0.19~0.89, 平均为0.69. (ⅱ) 三个基因组的平均等位变异丰富度为 B ＞ A ＞ D , 遗传多样性指数为 B ＞ D ＞ A . (ⅲ) 7个部分同源群的平均等位变异丰富度为2=7＞3＞4＞6＞5＞1, 遗传多样性指数为7＞3＞2＞4＞6＞5＞1. 结合两个指标分析, 第7部分同源群具有最高的多样性, 而1, 5群多样性最低. (ⅳ) 21条染色体中, 7 A , 3 B 和2 D 三条染色体遗传多样性较高, 而2 A , 1 B , 4 D , 5 D 和1 D 的遗传多样性偏低. (ⅴ) 育成品种遗传多样性指数以50年代的最高, 以后越来越低, 但年代间变化较平缓; 品种间平均遗传距离以50年代最高(0.731), 以后逐渐减小, 各年代依次为0.711, 0.706, 0.696和0.695. 品种遗传基础狭窄化问题日趋突出, 应引起有关部门和育种家的关注.

... 然而, 近十几年来, 由于在小麦育种中大量使用相同和相近的亲本, 导致新育成品种遗传基础日益狭窄、遗传变异率低^[1,2], 极大限制了小麦产量和品质的进一步改良, 而且还使小麦生产应对不良环境的能力大大降低, 增加潜在的用种风险 ...

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 本研究中尤其以4D染色体上的多态性位点最少, 这与郝晨阳等^[1]和倪中福等^[20]研究结果一致 ...

1997

0.0

Tanksley S

, Mccouch S

Seed banks and molecular maps: unlocking genetic potential from the wild.

Science, 1997, 277: 1063-1066

The authors are in the Department of Plant Breeding, 252 Emerson Hall, Cornell University, Ithaca, NY 14853, USA.

1998

1.643

0.0

Sun Q

, Ni Z

, Liu Z

, Gao J

, Huang T

Genetic relationships and diversity among Tibetan wheat, common wheat and European spelt wheat revealed by RAPD markers.

Euphytica, 1998, 99: 205-211

1. Department of Plant Genetics & Breeding, China Agricultural University, Beijing, 100094, P.R. China

An endemic hexaploid wheat found in Tibet, China was taxonomically classified as a subspecies in common wheat, i.e. Triticum aestivum ssp. tibetanum. Seven accessions of the Tibetan wheat, 22 cultivars of common wheat and 17 lines of spelt wheat were used for RAPD analysis to study the genetic relationships of the Tibetan wheat with common wheat and spelt wheat, and to assess the genetic diversity (GD) among and within the taxa. RAPD polymorphism was found to be much higher within spelt wheat and the Tibetan wheat than within common wheat. The GD value between the Tibetan wheat and common wheat is lower than that between the Tibetan wheat and spelt wheat. The result of cluster analysis showed that the 46 genotypes were distinctly classified into two groups. Group 1 included all European spelt wheat lines, while group 2 includes all Chinese common wheat and the Tibetan wheat accessions. However, the Tibetan wheat was substantially differentiated from Chinese common wheat at a lower hierarchy. Our results support an earlier classification of the Tibetan wheat as a subspecies in common wheat. European spelt wheat and the Tibetan wheat showed much higher genetic diversity than Chinese common wheat, which could be used to diversify the genetic basis for common wheat breeding.

... Sun等^[3]利用RAPD标记技术分析了西藏小麦、普通小麦和欧洲斯卑尔托小麦遗传多样性, 发现欧洲斯卑尔托小麦和西藏小麦遗传多样性远高于普通小麦 ...

2007

2.076

1.323

Wang H

, Wang

, Chen P

, Liu D

Assessment of genetic diversity of Yunnan, Tibetan, and Xinjiang wheat using SSR markers.

J Genet Genomics, 2007, 34: 623-633

Abstract A total of 206 SSR (Simple Sequence Repeats) primer pairs were used to detect genetic diversity in 52 accessions of three unique wheat varieties of western China. A total of 488, 472, and 308 allelic variants were detected in 31 Yunnan, 15 Tibetan and 6 Xinjiang wheat accessions with an average of PIC values 0.2764, 0.3082, and 0.1944, respectively. Substantial differences in allelic polymorphisms were detected by SSR markers in all the 21 chromosomes, the 7 homoeologous groups, and the three genomes (A, B, and D) in Yunnan, Tibetan, and Xinjiang wheat. The highest and lowest allelic polymorphisms in all the 21 chromosomes were observed in 3B and 1D chromosomes, respectively. The lowest and highest allelic polymorphisms among the seven homoeologous groups was observed in 6 and 3 homoeologous groups, respectively. Among the three genomes, B genome showed the highest, A the intermediate, and D the lowest allelic polymorphism. The genetic distance ( GD ) indexes within Yunnan, Tibetan, and Xinjiang wheat, and between different wheat types were calculated. The GD value was found to be much higher within Yunnan and Tibetan wheat than within Xinjiang wheat, but the GD value between Yunnan and Tibetan wheat was lower than those between Yunnan and Xinjiang wheat, and between Tibetan and Xinjiang wheat. The cluster analysis indicated a closer relationship between Yunnan and Tibetan wheat than that between Yunnan and Xinjiang wheat or between Tibetan and Xinjiang wheat.

... Wang等^[4]利用SSR标记技术分析发现我国云南和西藏小麦品种的遗传多样性高于新疆小麦品种 ...

2012

0.0

... Talebi等^[5]利用AFLP标记分析表明伊朗小麦品种遗传多样性丰富 ...

2002

2003

0.0

1.854

邹喻苹, 葛颂. 新一代分子标记-SNPs及其应用, 生物多样性, 2003, 11: 370-382

Zou Y

, Ge

A novel molecular marker: SNPs and its application.

Biodiversity Sci, 2003, 11: 370-382 (in Chinese with English abstract)

Single nucleotide polymorphisms (SNPs) are an abundant form of DNA variation which have a frequency of 1% or more throughout the genomes. SNPs consist of a single nucleotide base alteration including transition and transversion. They are stable and reliable mutation and are frequently referred to as bi-allelic makers. SNPs can be used conveniently for large-scale and high throughput genome analysis, in particular combining DNA chips and microarrays techniques. Therefore, SNPs provide a novel molecular marker system potentially useful for a wide range of biological disciplines. Here we briefly introduce the history and developments of SNP techniques, including its basic concept, its discovery and screening. We also discuss its applications in different research areas such as genetic mapping in mode animals and plants, DNA fingerprinting and its application in variety identification, species origin and relationship, linkage disequilibrium and associate analysis, and its application in population genetics. We anticipate that SNP markers will contribute greatly to the studies on population genetics, molecular breeding as well as evolutionary biology.

Laboratory of Systematic and Evolutionary Botany,Institute of Botany,Chinese Academy of Sciences,Beijing 100093

单核苷酸多态性(SNPs)是广泛存在于基因组中的一类DNA序列变异，其频率为1%或更高。它是由单个碱基的转换或颠换引起的点突变，稳定而可靠，并通常以二等位基因的形式出现。采用生物芯片和DNA微阵列技术来检测SNP，便于对基因组进行大幅度和高通量分析。因此，作为新一代分子标记，SNP在生物学诸多领域具有广阔应用前景。本文简要叙述SNPs技术的发展历史、研究动态以及相关的理论，介绍了与SNPs相关的基本术语、概念及其特点，列举了发现与检测SNPs主要技术的原理和方法，同时还根据一些具体实例介绍了SNPs在模式动、植物遗传图谱构建、品种鉴定、物种起源与亲缘关系、连锁不平衡与关联分析及其在群体遗传结构及其变化机制研究中的应用。最后展望了SNPs在群体遗传、分子育种和生物进化等研究领域中的应用前景。

... SNP是二等位基因, 具有在基因组中数量最多、分布密度高、无需电泳、可高通量自动化检测等特点^[6,7] ...

2008

4.397

0.0

... 大规模、高通量SNP芯片检测首先广泛应用于人类群体结构的遗传学研究和关联性分析^[8], 商业化的SNP芯片也已被应用于一些家畜全基因组关联分析、QTL定位和候选基因筛选^[9,10] ...

2007

35.209

0.0

Karlsson E

, Baranowska

, Wade C

, Salmon Hillbertz

N H

, Zody

M C

, Anderson

, Biagi

T M

, Patterson

, Pielberg

G R

, Kulbokas

, Comstock

K E

, Keller

E T

, Mesirov

J P

, von Euler

, Kämpe

, Hedhammar

, Land er

E S

, Andersson

, Lindblad-Toh

. Efficient mapping of Mendelian traits in dogs through genome-wide association. Nat Genet, 2007, 39: 1321-1328

With several hundred genetic diseases and an advantageous genome structure, dogs are ideal for mapping genes that cause disease. Here we report the development of a genotyping array with ~27,000 SNPs and show that genome-wide association mapping of mendelian traits in dog breeds can be achieved with only ~20 dogs. Specifically, we map two traits with mendelian inheritance: the major white spotting ( S ) locus and the hair ridge in Rhodesian ridgebacks. For both traits, we map the loci to discrete regions of <1 Mb. Fine-mapping of the S locus in two breeds refines the localization to a region of ~100 kb contained within the pigmentation-related gene MITF . Complete sequencing of the white and solid haplotypes identifies candidate regulatory mutations in the melanocyte-specific promoter of MITF . Our results show that genome-wide association mapping within dog breeds, followed by fine-mapping across multiple breeds, will be highly efficient and generally applicable to trait mapping, providing insights into canine and human health.

2009

1.681

0.0

Anderson

Genome-wide association analysis in domestic animals: a powerful approach for genetic dissection of trait loci.

Genetica, 2009, 136: 341-349

Domestic animals have a sufficiently old history (thousands of generations) to allow evolution of phenotypes, but also a sufficiently young history (~10,000 years) to allow powerful genetic dissection of phenotypic diversity. Domestic animals are therefore a unique resource for exploring genotype–phenotype relationships. Quantitative Trait Locus (QTL) mapping has been very successful in domestic animals but the identification of Quantitative Trait Mutations (QTMs) has been hard although a few prominent success histories have been reported. Genome-wide association analysis is now emerging as a powerful method for high-resolution mapping of loci controlling phenotypic traits in domestic animals. In two recent proof-of-principle studies we have used this approach to identify the mutations underlying two monogenic trait loci in dogs, white spotting and the hair ridge in Ridgeback dogs. In each case, we used only about 10 cases and 10 controls and mapped the locus to a region of about one mega base pair. In both cases the underlying mutations were non-coding underscoring the significance of regulatory mutations as a source for phenotypic diversity. Furthermore, we were able to shed light on the evolution of the allelic series at the white spotting ( S ) locus in dogs which encodes the microphthalmia-associated transcription factor (MITF). Our data showed that the three variant alleles described at this locus ( Irish spotting , piebald and extreme white ) do not represent three independent mutations but rather different combinations of a set of regulatory mutations affecting MITF expression. This is an excellent illustration of how the characterization of alleles selected during animal domestication contributes to an improved understanding of genotype–phenotype relationships.

1.Uppsala University Department of Medical Biochemistry and Microbiology Uppsala Sweden 2.Swedish University of Agricultural Sciences Department of Animal Breeding and Genetics Box 597 751 24 Uppsala Sweden

2007

2002

8.455

0.0

Rafalski A: Applications of single nucleotide polymorphisms in crop genetics. Curr Opin Plant Biol, 2002, 5: 94-100

Abstract The discovery of single nucleotide polymorphisms (SNPs) and insertions/deletions, which are the basis of most differences between alleles, has been simplified by recent developments in sequencing technology. SNP discovery in many crop species, such as corn and soybean, is relatively straightforward because of their high level of intraspecific nucleotide diversity, and the availability of many gene and expressed sequence tag (EST) sequences. For these species, direct readout of SNP haplotypes is possible. Haplotype-based analysis is more informative than analysis based on individual SNPs, and has more power in analyzing association with phenotypes. The elite germplasm of some crops may have been subjected to bottlenecks relatively recently, increasing the amount of linkage disequilibrium (LD) present and facilitating the association of SNP haplotypes at candidate gene loci with phenotypes. Whole-genome scans may help identify genome regions that are associated with interesting phenotypes if sufficient LD is present. Technological improvements make the use of SNP and indel markers attractive for high-throughput use in marker-assisted breeding, EST mapping and the integration of genetic and physical maps.

... 近年来, 随着小麦EST测序和高通量测序研究工作的开展, SNP开发和利用进展迅速^[12] ...

2013

9.737

0.0

Cavanagh C

, Chao

, Wang

, Huang B

, Stephen

, Kiani

, Forrest

, Saintenac

, Brown-Guedira

G L

, Akhunova

, See

, Bai

, Pumphrey

, Tomar

, Wong

, Kong

, Reynolds

, da Silva

M L

, Bockelman

, Talbert

, Anderson

J A

, Dreisigacker

, Baenziger

, Carter

, Korzun

, Morrell

P L

, Dubcovsky

, Morell

M K

, Sorrells

M E

, Hayden

M J

, Akhunov

. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat land races and cultivars. Proc Natl Acad Sci USA, 2013, 110: 8057-8062

a Commonwealth Scientific and Industrial Research Organization, Plant Industry and Food Futures National Research Flagship,Canberra, ACT 2601, Australia; b US Department of Agriculture–Agricultural Research Service Biosciences Research Laboratory, Fargo, ND 58102; c Department of Plant Pathology, Kansas State University, Manhattan, KS 66506; d Food Futures National Research Flagship and Mathematics, Informatics and Statistics Division, Commonwealth Scientific andIndustrial Research Organization, Dutton Park, QLD 4102, Australia; e Department of Primary Industries Victoria, Victorian AgriBiosciences Center, Bundoora, VIC 3083, Australia; f US Department of Agriculture–Agricultural Research Service Eastern Regional Small Grains Genotyping Laboratory, Raleigh, NC 27695; g US Department of Agriculture Western Regional Small Grains Genotyping Laboratory, Pullman, WA 99164; h US Department of Agriculture–Agricultural Research Service, Manhattan, KS 66506; i Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99164; j Department of Molecular Biology and Biotechnology, Chaudhary Charan Singh Haryana Agricultural University, Hisar 125004, India; k Genetic Resources and Enhancement Unit, Centro Internacional de Mejoramiento de Maíz y Trigo, Mexico City, 06600, Mexico; l US Department of Agriculture–Agricultural Research Service, Aberdeen, ID 83210; m Department of Plant Sciences, Montana State University, Bozeman, MT 59717; n Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108; o Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68588; p KWS Lochow GmbH, 37555 Einbeck, Germany; q Department of Plant Sciences, University of California, Davis, CA 95616; r Howard Hughes Medical Institute, Chevy Chase, MD 20815; and s Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to localconditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughputarray to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessionsof hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact ofcrop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneckand extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzinggenetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected toselection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology.An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-basedanalysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targetsor multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selectedalleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variationin the targets of directional selection during breeding probably associated with changing agricultural practices or environmentalconditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supportingfuture population genomic and genome-wide association studies in wheat.

... Cavanagh等^[13]和Wang等^[14]开发了小麦基于Illumina技术平台的9k和90k高通量SNP分析芯片, 已开始应用于小麦遗传连锁图谱的构建、DNA指纹分析、群体结构和连锁不平衡分析, 以及基因定位等诸多领域 ...

2014

6.279

0.0

Wang

, Wong

, Forrest

, Allen

, Chao

, Huang B

, Maccaferri

, Salvi

, Milner S

, Cattivelli

, Mastrangelo A

, Whan

, Stephen

, Barker

, Wieseke

, Plieske

, International Wheat Genome Sequencing Consortium, Plieske

, Mather

, Lillemo

, Dolferus

, Brown-Guedira

, Korol

, Akhunova

A R

, Feuillet

, Salse

, Morgante

, Pozniak

, Luo

M C

, Dvorak

, Morell

, Dubcovsky

, Ganal

, Tuberosa

, Lawley

, Mikoulitch

, Cavanagh

, Edwards

K J

, Hayden

, Akhunov

. Characterization of polyploid wheat genomic diversity using a high-density 90, 000 single nucleotide polymorphism array. Plant Biotechnol J, 2014, 12: 787-796

1 Department of Plant Pathology, Kansas State University, Manhattan, KS, USA 2 Department of Environment and Primary Industry, AgriBioSciences, La Trobe R&D Park, Bundoora, Vic., Australia 3 School of Biological Sciences, University of Bristol, Bristol, UK 4 US Department of Agriculture–Agricultural Research Service Biosciences Research Laboratory, Fargo, ND, USA 5 Commonwealth Scientific and Industrial Research Organization, Computational Informatics and Food Futures National Research Flagship, Dutton Park, Qld, Australia 6 Department of Agricultural Sciences, University of Bologna, Bologna, Italy 7 Consiglio per la Ricerca e la sperimentazione in Agricoltura, Genomics Research Centre, Fiorenzuola d'arda, Italy 8 Consiglio per la Ricerca e la sperimentazione in Agricoltura, Cereal Research Centre, Foggia, Italy 9 Commonwealth Scientific and Industrial Research Organization, Plant Industry and Food Futures National Research Flagship, Canberra, ACT, Australia 10 TraitGenetics GmbH, Gatersleben, Germany 11 IWGSC, Bethesda, MD, USA 12 Department of Plant Sciences, Norwegian University of Life Sciences, Ås, Norway 13 Waite Research Institute, School of Agriculture, Food and Wine, University of Adelaide, Urrbrae, SA, Australia 14 Murdoch University, Murdoch, WA, Australia 15 US Department of Agriculture–Agricultural Research Service Eastern Regional Small Grains Genotyping Laboratory, Raleigh, NC, USA 16 Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, Mount Carmel, Haifa, Israel 17 K-State Integrated Genomics Facility, Kansas State University, Manhattan, KS, USA 18 INRA – Université Blaise Pascal, UMR 1095, Genetics Diversity and Ecophysiology of Cereals, Clermont-Ferrand, France 19 Department of Crop and Environmental Sciences, University of Udine, Via delle Scienze, Udine, Italy 20 Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada 21 Department of Plant Sciences, University of California, Davis, CA, USA 22 Howard Hughes Medical Institute, Chevy Chase, MD, USA 23 Illumina Inc., Hayward, CA, USA † Bayer, Research & Development, Morrisville, NC, USA * Correspondence (Tel +61 3 9032 7084; fax +61 3 9032 7000; email matthew.hayden@dpi.vic.gov.au ) and (Tel 785 532 1342; fax 785 532 5692; email eakhunov@ksu.edu )

> High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

2013

3.285

0.0

... SNP标记能真实反映小麦品种间的亲缘关系^[15,16,17], 可以用于小麦品种遗传多样性研究 ...

2010

4.397

0.0

... SNP标记能真实反映小麦品种间的亲缘关系^[15,16,17], 可以用于小麦品种遗传多样性研究 ...

2013

3.658

0.0

Wurschum

, Langer S

, Longin C

, Korzun

, Akhunov

, Ebmeyer

, Schachschneider

, Schacht

, Kazman

, Reif J

Population structure, genetic diversity and linkage disequilibrium in elite winter wheat assessed with SNP and SSR markers.

Theor Appl Genet, 2013, 126: 1477-1486

Abstract Modern genomics approaches rely on the availability of high-throughput and high-density genotyping platforms. A major breakthrough in wheat genotyping was the development of an SNP array. In this study, we used a diverse panel of 172 elite European winter wheat lines to evaluate the utility of the SNP array for genomic analyses in wheat germplasm derived from breeding programs. We investigated population structure and genetic relatedness and found that the results obtained with SNP and SSR markers differ. This suggests that additional research is required to determine the optimum approach for the investigation of population structure and kinship. Our analysis of linkage disequilibrium (LD) showed that LD decays within approximately 5–10 cM. Moreover, we found that LD is variable along chromosomes. Our results suggest that the number of SNPs needs to be increased further to obtain a higher coverage of the chromosomes. Taken together, SNPs can be a valuable tool for genomics approaches and for a knowledge-based improvement of wheat.

1. State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany 3. KWS LOCHOW GMBH, 29303, Bergen, Germany 4. Department of Plant Pathology, 4024 Throckmorton Plant, Sciences Center, Kansas State University, Manhattan, KS, 66506, USA 5. Nordsaat Saatzuchtgesellschaft mbH, 38895, Langenstein, Germany 6. Limagrain GmbH, 31226, Peine-Rosenthal, Germany 7. Lantmännen SW Seed Hadmersleben GmbH, 39398, Hadmersleben, Germany 2. Leibniz Institute of Plant Genetics and Crop Plant Research, 06466, Gatersleben, Germany

... SNP标记能真实反映小麦品种间的亲缘关系^[15,16,17], 可以用于小麦品种遗传多样性研究 ...

1984

9.737

0.0

Saghai-Maroof M

, Soliman K

, Jorgensen R

, Allard R

. Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci USA, 1984, 81: 8014-8018

Spacer-length (sl) variation in ribosomal RNA gene clusters (rDNA) was surveyed in 502 individual barley plants, includingsamples from 50 accessions of cultivated barley, 25 accessions of its wild ancestor, and five generations of composite crossII (CCII), an experimental population of barley. In total, 17 rDNA sl phenotypes, made up of 15 different rDNA sl variants,were observed. The 15 rDNA sl variants comprise a complete ladder in which each variant differs in length from adjacent variantsby approximately equal to 115 nucleotide pairs. Studies of four rDNA sl variants in an F2 population showed that these variantsare located at two unlinked loci, Rrn1 and Rrn2, each with two codominant alleles. Using wheat-barley addition lines, we determinedthat Rrn1 and Rrn2 are located on chromosomes 6 and 7, respectively. The nonrandom distribution of sl variants between locisuggests that genetic exchange occurs much less frequently between than within the two loci, which demonstrates that Rrn1and Rrn2 are useful as new genetic markers. Frequencies of rDNA sl phenotypes and variants were monitored over 54 generationsin CCII. A phenotype that was originally infrequent in CCII ultimately became predominant, whereas the originally most frequentphenotype decreased drastically in frequency, and all other phenotypes originally present disappeared from the population.We conclude that the sl variants and/or associated loci are under selection in CCII.

... 2012年10月在中国农业大学小麦遗传育种温室种植, 植株长至二叶一心时, 取小麦叶片, 按Saghai-Maroof等^[18]的CTAB法提取基因组DNA ...

2001

0.0

0.833

贾继增, 张正斌, Devos

, Gale M

小麦21条染色体RFLP作图位点遗传多样性分析. 中国科学: C 辑, 2001, 31: 13-21

Jia J

, Zhang Z

, Devos

, Gale M

Genetic diversity of 21 chromosomes in wheat revealed by RFLP mapping.

Sci China (Ser C), 2001, 31: 13-21 (in Chinese)

对来自世界11个国家的15个小麦品种(系)( Triticum aestivum L.AABBDD,2 n = 42)472个RFLP位点的遗传多样性进行了检测,并进行了逐条染色体分析,结果发现:(ⅰ) 15个品种在各条染色体上的聚类各不相同.根据472个遗传位点遗传多样性数据,15个品种可聚类为4类,Synthetic,Hope, Timgalen各为一类,其余品种为一类,遗传距离远近恰与其所携带的小麦亲缘种染色体数目有关.(ⅱ)普通小麦遗传多样性非常贫乏,不同国家来源的品种相似系数高达0.8以上,多数品种间的大多数位点无遗传多样性,有53%的位点在供试的栽培品种中完全无多样性.(ⅲ)以四倍体小麦(AABB)和粗山羊草(DD)为亲本的品种(系)中,其对应的染色体上有较高的遗传多样性,其中有49.4%的等位变异在供试栽培种中没有发现,说明小麦的原始供体种是丰富现代栽培小麦遗传多样性的重要资源.(ⅳ) 根据遗传多样性位点及其作图位置, 可以检测到小麦栽培品种与其亲缘种杂交后代中亲缘种的染色体(片段).(ⅴ)在小麦的A,B,D3个基因组中, B基因组的遗传多样性最高,D基因组最差(尤以1D最甚),A基因组居中.(ⅵ)中国古老栽培品种中国春(CS)与国外栽培品种主要差异表现在染色体1B,3B和5A上,并发现了12个中国春的特异等位变异.认为现代栽培小麦遗传多样性狭窄是目前小麦育种难以取得突破的关键问题之一,并对如何丰富小麦的遗传多样性提出了建议.

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 39%, 其中, 以B基因组上的多态性位点最多, A基因组次之, D基因组最少, 与贾继增等^[19]运用RFLP标记对来自11个国家的15个小麦品种(系)进行遗传多样性分析研究结果一致 ...

... 贾继增等^[19]报道过与此不同的结果, 他们研究发现, 1D和5D遗传多样性最小, 通过分析多态性RFLP位点在7个部分同源群的分布发现, 第1和第2部分同源群最多, 第4部分同源群最少 ...

2003

0.0

1.667

倪中福, 张义荣, 梁荣奇, 刘广田, 孙其信. 普通小麦D染色体组微卫星分子标记遗传差异研究. 作物学报, 2003, 29: 145-151

Ni Z

, Zhang Y

, Liang R

, Liu G

, Sun Q

Genetic diversity of D-genome revealed by SSR markers in wheat (Triticum aestivum L. ).

Acta Agron Sin, 2003, 29: 145-151 (in Chinese with English abstract)

本研究采用微卫星(SSR)分子标记技术, 对我国不同生态区的6个春小麦品种(系)及北方冬麦区的17个冬小麦品种(系)D染色体组的遗传多样性进行了分析. 结果显示, 23个微卫星引物在23份材料间共扩增出65个等位基因, 平均每个引物为2.9个. 分析发现, 冬小麦群体内检测到的等位基因数(60个)及平均遗传距离(0.4504)明显高于春小麦(48

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 本研究中尤其以4D染色体上的多态性位点最少, 这与郝晨阳等^[1]和倪中福等^[20]研究结果一致 ...

2011

0.0

1.23

蒲艳艳, 程凯, 李斯深. 山东省近期育成小麦品种遗传多样性的SSR分析. 分子植物育种, 2011, 9: 443-449

Pu Y

, Cheng

, Li S

Genetic diversity of recent wheat cultivars in Shand ong Province using SSR markers.

Mol Plant Breed, 2011, 9: 443-449 (in Chinese with English abstract)

为了揭示山东省近年来小麦品种的遗传多样性.选用分布于小麦21条染色体上的68个SSR引物,对44个山东省小麦品种进行了遗传多样性分析.共检测到248个等位基因,每对引物的等位基因数变幅为2～9个,平均为3.65个.每个SSR位点的多态性信息量(PIC)变化范围为0.087～0.837,平均为0.562.44个品种间的遗传相似系数变幅为0.593～0.918之间,平均值为0.694.平均等位位点为B基因组((3.667)>A基因组(3.606)>D基因组(3.417),平均PIC值各基因组间差异不大.聚类分析结果表明,山东省小麦品种遗传多样性较低,品种间的亲缘关系较近.应拓宽亲本选择范围,扩大遗传背景,以利于山东省小麦育种水平的进一步提高.

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2009

0.0

1.1628

李志波, 王睿辉, 张茶, 梁虹, 马峙英, 赵玉欣, 王静华. 河北省小麦品种基于农艺性状的遗传多样性分析. 植物遗传资源学报, 2009, 10: 436-442

Li Z

, Wang R

, Zhang

, Liang

, Ma Z

, Zhao Y

, Wang J

Genetic diversity analysis of bread wheat (Triticum aestivum L. ) cultivars in Hebei Province based on agronomic traits.

J Plant Genet Resour, 2009, 10: 436-442 (in Chinese with English abstract)

为明确河北省小麦品种遗传多样性的基础和历史演变,本研究以所收集的该省近60年来审(认)定的125个小麦品种为研究材料,以8个农艺性状为基础进行了遗传多样性分析.结果表明:河北省小麦品种农艺性状变异比较丰富,以每穗不孕小穗数的变异系数最高(52.63%),其次为单株粒重和有效分蘖数,每穗小穗数的变异最小;多样性指数从20世纪70年代的1.62增加到目前的1.89,平均值为1.76,但略低于其他省份.在上述分析基础上,用最长距离法可将125份材料聚为3大类,其中80.8%(101个)的品种归入第3大类,主要为20世纪90年代以后的品种.这说明该省小麦品种遗传多样性在逐步提高的同时,其遗传基础仍需进一步拓宽.

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2007

0.0

0.5

傅体华, 王春梅, 任正隆. 四川育成小麦品种的SSR遗传多态性及系谱关系. 四川农业大学学报, 2007, 25: 1-7

Fu T

, Wang C

, Ren Z

SSR genetic diversity among modern advanced wheat cultivars (Triticum aestivum L. ) in Sichuan and its relationships with their pedigree.

J Sichuan Agric Univ, 2007, 25: 1-7 (in Chinese with English abstract)

选用小麦染色体上的60 SSR标记,对来自四川3个不同单位近30年育成的47个普通小麦品种的遗传多样性进行了分析.60个SSR位点中共检测到118个等位变异,每个位点的等位变异范围为1～5个,平均为1.08个.品种的遗传相似系数从1980年以来有逐渐升高的趋势.育成小麦品种的3个染色体组以B染色体组遗传多样性最高,D染色体组最低.通过UPGMA聚类,可以把47个品种分为3个松散的群,在每一个群内,很多品种都来自于同一个育种单位,与系谱来源一致.这些结果表明由于不同育种单位采用相似遗传特性的育种亲本,四川育成小麦品种的遗传基础越来越狭窄,种质资源的创新和遗传多样性拓宽是今后小麦育种和小麦生产成效的前提.比较而言,推广面积大的品种相互之间遗传多样性较大,归于不同的类群,具有更广泛的适应性. Abstract： Simple sequence repeats (SSRs) or microsatellites, with high polymorphism and abundant information, were used to detect the genetic diversity of wheat (Triticum aestivum L.) germplasm. In this study, 47 wheat advanced cultivars (lines) released by three different breeding stations in Sichuan province, were analyzed with 60 SSRs. A total of 108 allelic variants were detected at 60 SSR loci, ranging from one to five per locus with an average of 1.08. Genetic similarities (GS) ranged from 0.42 to 0.97 with average of 0.68. The average GS value of cultivars bred in different periods showed that the genetic diversity had the decreasing tendency since 1980s. The comparison of A, B, D chromosomes based on SSR markers indicated that the polymorphism of genome B was the highest and that of genome D was the lowest. UPGMA analysis in total genome based on GS value produced three loose groups. Most of the cultivars developed from the same breeding stations clustered in one group. Moreover, the parentage of advanced cultivars also contributed significantly to the clustering pattern. It was clearly shown that most current advanced cultivars in Sichuan China possessed narrow genetic background due to sharing breeding materials of other breeding stations or using certain elite breeding parents by different breeding stations. Thus it is an urgent need to diversify the genetic base by using new sources from the germplasm in wheat improvement programs in Sichuan province.

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2011

0.0

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2011

0.0

潘玉朋, 李立群, 郑锦娟, 王培, 冯毅, 李学军. 黄淮麦区近年大面积推广小麦品种的遗传多样性分析. 西北农业学报, 2011, 20: 47-52

Pang Y

, Li L

, Zheng J

, Wang

, Feng

, Li X

Analysis of genetic diversity of the large-scale promoted wheat varieties grown at Huang-Huai area in recent years.

Acta Agric Boreali- Occid Sin, 2011, 20: 47-52 (in Chinese with English abstract)

In order to investigate genetic relationships of the large scale promoted wheat varieties which grown at Huang huai area in recent years. Thirty one SSR makers were used to detect genetic diversity among 25 elite wheat lines. Totally 148 alleles were revealed among 25 cultivars with 31 SSR markers, 2-15 alleles could be detected at different SSR locus, with the average of 4.77 alleles per SSR marker; the range of PIC was 0.253-0.889, with the average of 0.552. In the three genomes of wheat, the average genetic richness was D＞B＞A, and the genetic diversity indexes was D＞A＞B. Comparing of genetic diversity among 7 homoeologous, the average genetic richness was 1＞7＞2＞5＞3=4＞6, and the genetic diversity indexes was 5＞3＞6＞4＞2＞1＞7. Cluster analysis showed the genetic similarity coefficient ( GS ) changed convergence of 0.34-0.85, with an average of 0.61. In the genetic similarity coefficient ( GS ) 0.59 area, all the cultivars could be cluster into five categories, of which 80% of the species were gathered in the first class. Cultivars of the same region or species breeding units approximately were gathered in one class. These results suggested that the genetic basis of the majority of the 56 wheat varieties was very narrow.

采用31对SSR引物对黄淮麦区近年大面积推广的25份小麦品种进行微卫星标记位点扫描及遗传多样性分析，共检测到148个等位基因变异，变化范围为2～15个，平均每个位点检测到的等位基因数为4.77个。位点多态性信息指数（ PIC ）变幅为0.253～0.889，平均0.552。3个基因组的平均等位变异丰富度为D>B>A，遗传多样性指数为D>A>B。7个部分同源群的平均等位变异丰富度为1＞7＞2＞5＞3=4＞6，平均遗传多样性指数为5＞3＞6＞4＞2＞1＞7。聚类分析表明，品种间的遗传相似系数（ GS ）变幅0.34～0.85，平均为0.61,SSR标记能将25份小麦品种相互区分开,在遗传相似系数( GS )0.59处，可将供试品种聚为5大类，其中80%的品种被聚在第Ⅰ类，同一地区或育种单位的品种大致聚在一个类群里。表明黄淮麦区近年大面积推广的小麦品种间遗传差异较小，遗传基础狭窄。

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2005

0.0

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2011

0.0

1.007

徐晓丹, 冯晶, 蔺瑞明, 赵蕾, 林风, 徐世昌. 河南小麦主栽品种亲缘系数的分析. 麦类作物学报, 2011, 31: 653-659

Xu X

, Feng

, Lin R

, Zhao

, Lin

, Xu S

Coefficient of parentage analysis for leading wheat cultivars in Henan Province.

J Triticeae Crops, 2011, 31: 653-659 (in Chinese with English abstract)

In order to investigate the genetic diversity of leading wheat cultivars in Henan province and provide theoretical guidance for wheat breeding, the pedigree information of 57 major wheat cultivars was investigated and the coefficient of parentage (COP) between the parents and cross combinations was calculated. The results showed that only seven of the 57 cultivars had relationship in their parents; It showed that the relationship among 757 of the 1596 combinations, the range of COP value of all cultivars was 0.0000~0.7500 with the average value of 0.0413; Cluster analysis suggested that the 57 cultivars could be divided into 7 groups. The co ancestry coefficient of core parents, Yumai2, Yumai18, Yumai21, Yumai25 with 57 leading varieties indicated that they were with high breeding value. The genetic background of the tested materials was rich and there still had great potential for breeding varieties using those materials. The majority of the core parents were cultivars bred earlier , so it is important to enhance the utilization of novel wheat germplasm.

为探讨河南省小麦遗传背景丰富度，追溯了河南省57份小麦主栽品种的系谱信息，计算并分析了品种亲本间及品种组合间的亲缘系数（coefficient of parentage，COP）。结果表明，供试品种中只有7个品种的父母本之间有亲缘关系。1 596对组合中，757对存在亲缘关系，所有组合的COP值变异范围为0.0000~0.7500，亲缘系数总和为65.8393，平均值为0.0413。聚类分析将57份品种分为7个类群。骨干亲本豫麦2号、豫麦18号、豫麦21号、豫麦25号与57份主栽品种的共祖先度分析表明，这几个品种的利用价值很高。由此判断，供试材料的遗传背景丰富，品种组合选育优良品种还有很大潜力。骨干亲本大都是早期培育品种，今后需加强对小麦种质资源的挖掘和利用。

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2013

0.0

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...

2000

0.0

... 3 讨论近年来, 有多项研究利用分子标记、系谱和农艺性状分析评价小麦品种的遗传多样性^{[1,19,20,21,22,23,24,25,26,27,28,29]} ...

... 许多研究表明, 我国不同地区都存在小麦主栽品种亲缘关系较近和遗传基础不够广泛的现象^{[21,22,23,24,25,26,27,28,29]} ...