利用关联分析发掘小麦自然群体旗叶叶绿素含量的优异等位变异

doi:10.3724/SP.J.1006.2012.00962

作物学报 ›› 2012, Vol. 38 ›› Issue (06): 962-970.doi: 10.3724/SP.J.1006.2012.00962

• 作物遗传育种·种质资源·分子遗传学 • 上一篇下一篇

利用关联分析发掘小麦自然群体旗叶叶绿素含量的优异等位变异

李玮瑜^1,2，张斌²，张嘉楠^2,3，昌小平²，李润植^1,*，景蕊莲^2,*

1山西农业大学, 山西太谷 030801; 2中国农业科学院作物科学研究所 / 农作物基因资源与基因改良国家重大科学工程 / 农业部作物种质资源利用重点开放实验室, 北京 100081; 3国家谷子改良中心 / 河北省农林科学院谷子研究所, 河北石家庄 050031

收稿日期:2012-01-19 修回日期:2012-04-18 出版日期:2012-06-12 网络出版日期:2012-04-23
通讯作者: 景蕊莲, E-mail: jingrl@caas.net.cn, Tel: 010-82105829; 李润植, E-mail: rli2001@hotmail.com
基金资助:
本研究由国家高技术研究发展计划(863计划)项目(2011AA100501)和国际农业研究磋商组织(CGIAR)挑战计划项目(G7010.02.01)资助

Exploring Elite Alleles for Chlorophyll Content of Flag Leaf in Natural Population of Wheat by Association Analysis

LI Wei-Yu^1,2,ZHANG Bin²,ZHANG Jia-Nan^2,3,CHANG Xiao-Ping², LI Run-Zhi^1,*,JING Rui-Lian^2,*

1 Agronomy College, Shanxi Agricultural University, Taigu 030801, China; 2 National Key Facility for Crop Gene Resources and Genetic Improvement / Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 3 National Millet Improvement Center of China, Institute of Millet Crops / Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang 050031, China

Received:2012-01-19 Revised:2012-04-18 Published:2012-06-12 Published online:2012-04-23
Contact: 景蕊莲, E-mail: jingrl@caas.net.cn, Tel: 010-82105829; 李润植, E-mail: rli2001@hotmail.com

摘要/Abstract

摘要： 为揭示小麦自然群体干旱胁迫条件下旗叶叶绿素含量的变化, 筛选相关标记的优异等位变异, 以262份小麦种质资源组成的自然群体为材料, 分别种植在北京的2个试验地点, 均设雨养和灌溉处理, 于开花期和灌浆期检测旗叶叶绿素含量。以分布于21条染色体的169个SSR标记检测所有材料的基因型, 利用STRUCTURE 2.3.2软件分析群体结构, 用TASSEL软件的MLM (mixed linear model)方法对小麦自然群体的旗叶叶绿素含量进行关联分析。在此基础上, 将携带某等位变异的所有材料表型均值与携带无效等位基因(null allele)材料表型均值比较, 估计等位变异的表型效应, 鉴别优异等位变异。共检测到2048个等位变异, 每位点2~37个等位变异, 平均12个。每位点的标记多态性信息量(PIC)为0.008~0.936, 平均0.628。在22个标记位点共检测出40个(次)与旗叶叶绿素含量极显著的关联, 其中11个标记位点有2次以上的关联, Xwmc419-1B和Xgwm501-2B分别有3次关联。在Xcfa2123-7A、Xgwm232- 1D和Xgwm429-2B位点分别检测到效应值大于4.0的等位变异。

关键词: 小麦, 叶绿素含量, SSR, 关联分析, 等位变异

Abstract: Elite alleles associated with chlorophyll content of flag leaf in a natural population of winter wheat (Triticum aestivum L.) consisting of 262 accessions were measured at flowering and grain-filling stages under both rainfed and well-watered conditions in two experimental locations in Beijing, China. A total of 169 SSR markers distributed on the 21 chromosomes of wheat were employed to detect the genetic diversity and genetic structure of the population. Association analysis between SSR loci and chlorophyll content trait was performed using TASSEL MLM (mixed linear model) program. The phenotypic allele effect was estimated through comparing the average phenotypic value over accessions with that of “null allele”. A total of 2048 alleles were identified on the 169 SSR loci, and each locus had 2–37 alleles with an average of 12. The polymorphism information contents (PICs) of the SSR loci ranged from 0.008 to 0.936 with an average of 0.628. Forty markers were found to be significantly associated with chlorophyll content (P<0.001) on 22 loci, of which 11 markers showed repeated associations, particularly, loci Xwmc419-1B and Xgwm501-2B had associations for three times. The alleles on loci Xcfa2123-7A, Xgwm232-1D, and Xgwm429-2B exhibited more than 4.0 of phenotypic effect value.

Key words: Wheat (Triticum aestivum L.), Chlorophyll content, SSR, Association analysis, Allelic variation

李玮瑜，张斌，张嘉楠，昌小平，李润植，景蕊莲. 利用关联分析发掘小麦自然群体旗叶叶绿素含量的优异等位变异[J]. 作物学报, 2012, 38(06): 962-970.

LI Wei-Yu,ZHANG Bin,ZHANG Jia-Nan,CHANG Xiao-Ping,LI Run-Zhi,JING Rui-Lian. Exploring Elite Alleles for Chlorophyll Content of Flag Leaf in Natural Population of Wheat by Association Analysis[J]. Acta Agron Sin, 2012, 38(06): 962-970.

导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

链接本文: https://zwxb.chinacrops.org/CN/10.3724/SP.J.1006.2012.00962

https://zwxb.chinacrops.org/CN/Y2012/V38/I06/962

参考文献

[1]Reynolds M, Foulkes M J, Slafer G A, Berry P, Parry M A J, Snape J W, Angus W J. Raising yield potential in wheat. J Exp Bot, 2009, 60: 1899?1918

[2]Borrell A K, Tao Y, Mcintyre C L. Physiological basis, QTL and MAS of the stay-green drought resistance trait in grain sorghum. CIMMYT, Mexico, DF (Mexico), 2000. pp 142?146

[3]Yang D L, Jing R L, Chang X P, Li W. Quantitative trait loci mapping for chlorophyll fluorescence and associated traits in wheat (Triticum aestivum L.). J Integr Plant Biol, 2007, 49: 646?654

[4]Bijanzadeh E, Emam Y. Effect of defoliation and drought stress on yield components and chlorophyll content of wheat. Pak J Biol Sci, 2010, 13: 699?705

[5]Khamssi N N, Najaphy A. Comparison of photosynthetic components of wheat genotypes under rain-fed and irrigate conditions. Photochem Photobiol, 2012, 88: 76?80

[6]Jiang G H, He Y Q, Xu C G, Li X H, Zhang Q. The genetic basis of stay-green in rice analyzed in a population of doubled haploid lines derived from an indica by japonica cross. Theor Appl Genet, 2004, 108: 688?698

[7]Jannink J L, Bink M C A M, Jansen R C. Using complex plant pedigrees to map valuable genes. Trends Plant Sci, 2001, 6: 337?342

[8]Risch N J. Searching for genetic determinants in the new millennium. Nature, 2000, 405: 847?856

[9]Zondervan K T, Cardon L R. The complex interplay among factors that influence allelic association. Nat Rev Genet, 2004, 5: 89?100

[10]de Oliveira Borba T C, Brondani R P V, Breseghello F, Coelho A S G, Mendonca J A, Rangel P H N, Brondani C. Association mapping for yield and grain quality traits in rice (Oryza sativa L). Genet Mol Biol, 2010, 33: 515?524

[11]Huang X H, Zhao Y, Wei X H, Li C, Wang A, Zhao Q, Li W J, Guo Y L, Deng L W, Zhu C R, Fan D L, Lu Y Q, Weng Q J, Liu K Y, Zhou T Y, Jing Y F, Si L Z, Dong G J, Huang T, Lu T T, Feng Q, Qian Q, Li J Y, Han B. Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat Genet, 2011, 44: 32?39

[12]Kump K L, Bradury P J, Wisser R J, Buckler E S, Bclcher A R, Oropeza-Rosas M A, Zwonitzer J C, Kresovich S, McMullen M D, Ware D, Balint-Kurti P J, Holland J. Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nat Genet, 2011, 43: 163?168

[13]Yan J B, Shah T, Warburton M L, Buckler E S, McMullen M D, Crouch J. Genetic characterization and linkage disequilibrium estimation of a global maize collection using SNP markers. PLoS One, 2009, 4: e8451

[14]Breseghello F, Sorrells M E. Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics, 2006, 172: 1165?1177

[15]Wang L F, Ge H M, Hao C Y, Dong Y S, Zhang X Y. Identifying loci influencing 1 000-kernel weight in wheat by microsatellite screening for evidence of selection during breeding. PLoS One, 2012, 7: e29432

[16]Wei T-M(魏添梅), Chang X-P(昌小平), Min D-H(闵东红), Jing R-L(景蕊莲). Analysis of genetic diversity and tapping elite alleles for plant height in drought-tolerant wheat varieties. Acta Agron Sin (作物学报), 2010, 36(6): 895?904 (in Chinese with English abstract)

[17]Zhang J N, Hao C Y, Ren Q, Chang X P, Liu G R, Jing R L. Association mapping of dynamic developmental plant height in common wheat. Planta, 2011, 235: 891?902

[18]Somers D J, Isaac P, Edwards K. A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet, 2004, 109: 1105?1114

[19]Holland J B, Nyquist W E, Cervantes-Martínez C T. Estimating and interpreting heritability for plant breeding: an update. Plant Breed Rev, 2003, 22: 9?112

[20]Liu K, Muse S V. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics, 2005, 21: 2128?2129

[21]Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol, 2005, 14: 2611?2620

[22]Bradbury P J, Zhang Z, Kroon D E, Casstevens T M, Ramdoss Y, Buckler E S. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007, 23: 2633?2635

[23]Hardy O J, Vekemans X. SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Notes, 2002, 2: 618?620

[24]Wen Z-X(文自翔), Zhao T-J(赵团结), Zheng Y-Z(郑永战), Liu S-H(刘顺湖), Wang C-E(王春娥), Wang F(王芳), Gai J-Y(盖钧镒). Association analysis of agronomic and quality traits with SSR markers in Glycine max and Glycine soja in China: I. Population structure and associated markers. Acta Agron Sin (作物学报), 2008, 34(7): 1169?1178 (in Chinese with English abstract)

[25]Wen Z-X(文自翔), Zhao T-J(赵团结), Zheng Y-Z(郑永战), Liu S-H(刘顺湖), Wang C-E(王春娥), Wang F(王芳), Gai J-Y(盖钧镒). Association analysis of agronomic and quality traits with SSR markers in Glycine max and Glycine soja in China: II. Exploration of elite alleles. Acta Agron Sin (作物学报), 2008, 34(8): 1339?1349 (in Chinese with English abstract)

[26]Zhang X-Y(张学勇), Tong Y-P(童依平), You G-X(游光霞), Hao C-Y(郝晨阳), Ge H-M(盖红梅), Wang L-F(王兰芬), Li B(李滨), Dong Y-C(董玉琛), Li Z-S(李振声). Hitchhiking effect mapping: A new approach for discovering agronomic important genes. Sci Agric Sin (中国农业科学), 2006, 39(8): 1526?1535 (in Chinese with English abstract)

[27]Doebley J F, Gaut B S, Smith B D. The molecular genetics of crop domestication. Cell, 2006, 127: 1309?1322

[28]Subudhi P K, Rosenow D T, Nguyen H T. Quantitative trait loci for the stay green trait in sorghum (Sorghum bicolor L.): consistency across genetic backgrounds and environments. Theor Appl Genet, 2000, 101: 733?741

[29]Van Oosteerom E J, Jayachandran R, Bidinger F R. Diallel analysis of the stay-green trait and its components in sorghum. Crop Sci, 1996, 36: 540?555

[30]Walulu R S, Rosenow D T, Wester D B, Nguyen H T. Inheritance of the stay-green trait in sorghum. Crop Sci, 1994, 34: 970?972

[31]Jiang G H, He Y Q, Xu C G, Li X H, Zhang Q. The genetic basis of stay-green in rice analyzed in a population of doubled haploid lines derived from an indica by japonica cross. Theor Appl Genet, 2004, 108: 688?698

[32]Hui Z(惠振). The Photosynthetic Characteristic of TaSG1 Wheat Mutant with Stay-Green Phenotype and the Physiological Mechanism Responsible for Stay-Green. MS Thesis of Shandong Agricultural University, 2009. p 59 (in Chinese with English abstract)

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

[34]Lou X Y, Casella G, Littell R C, Yang M C K, Johnson J A, Wu R L. A haplotype-based algorithm for multilocus linkage disequilibrium mapping of quantitative trait loci with epistasis. Genetics, 2003, 163: 1533?1548

[35]Yang D-L(杨德龙). Genetic Dissection of Quantitive Loci for Important Physiological and Agronomic Traits Associated with Drought Tolerance in Wheat (Triticum aestivum L.). PhD Dissertation of Gansu Agricultural University, 2007. pp 27?31 (in Chinese with English abstract)

[36]Jing R-L(景蕊莲), Chang X-P(昌小平), Jia J-Z(贾继增), Hu R-H(胡荣海). Establishing wheat doubled haploid population for genetic mapping by anther culture. Biotechnology (生物技术), 1999, 9(3): 4?8 (in Chinese)

[37]Zhang K, Zhang Y, Chen G, Tian J. Genetic analysis of grain yield and leaf chlorophyll content in common wheat. Cereal Res Commun, 2009, 37: 499?511

[38]Thornsberry J M, Goodman M M, Doebley J, Kresovich S, Nielsen D, Buckler IV E S. Dwarf8 polymorphisms associate with variation in flowering time. Nat Genet, 2001, 28: 286?289

[39]Yu J, Buckler E S. Genetic association mapping and genome organization of maize. Curr Opin Biotechnol, 2006, 17: 155?160

[40]Flint-Garcia S A, Thuillet A, Yu J, Pressoir G, Romero S M, Mitchell S E, Doebley J, Kresovich S, Goodman M. M, Buckler E S. Maize association population: a high-resolution platform for quantitative trait locus dissection. Plant J, 2005, 44: 1054?1064

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

利用关联分析发掘小麦自然群体旗叶叶绿素含量的优异等位变异

Exploring Elite Alleles for Chlorophyll Content of Flag Leaf in Natural Population of Wheat by Association Analysis

PDF

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0

关于本刊

在线期刊

作者中心

相关单位

联系我们

[1]	翟胜男, 曹新有, 李豪圣, 李吉虎, 李法计, 刘金栋, 夏先春, 吕莹莹, 马瑞峰, 王颖, 耿洪伟, 刘建军. 小麦Pod-A1、Pod-D1和Pod-2D位点等位变异对籽粒过氧化物酶活性的遗传效应分析[J]. 作物学报, 2026, 52(6): 1593-1603.
[2]	习千辉, 徐梓瑗, 刘梦梦, 王宏艺, 郎凯琳, 井震海, 陈锋, 赵磊. 小麦籽粒铜含量的全基因组关联分析及候选基因预测[J]. 作物学报, 2026, 52(6): 1604-1617.
[3]	毛嘉琦, 黄朋雨, 赵佳佳, 郑兴卫, 武棒棒, 郝宇琼, 屈非, 刘成, 马朋涛, 郑军. 山西小麦品种白粉病抗性评价及抗病基因分子检测[J]. 作物学报, 2026, 52(6): 1669-1681.
[4]	胡川, 赵凯男, 黄修利, 吴金芝, 任开明, 王贺正, 付国占, 黄明, 李友军. 一次灌溉下耕作方式和氮肥用量对旱地小麦产量和品质的影响[J]. 作物学报, 2026, 52(6): 1830-1846.
[5]	陈雪燕, 何华川, 李政嘉, 董新盼, 李藕琪, 刘小云, 李丹萍, 陈志伟, 刘国霞, 吕胜源, 吴印莹, 赵振东, 曹新有, 万何平. 水培盐碱复合胁迫下‘济麦60’苗期根系有机酸分泌动态变化及其转录调控机制[J]. 作物学报, 2026, 52(6): 1859-1875.
[6]	高沛阳, 李瑾璇, 董宇奎, 石玉, 张振, 张永丽. 测墒补灌下小麦分蘖发生和成穗对施氮量的响应[J]. 作物学报, 2026, 52(6): 1847-1858.
[7]	唐宽强, 李公允, 宋美毅, 赵雪, 常春玲. 大豆株高性状全基因组关联分析及预测模型构建[J]. 作物学报, 2026, 52(6): 1743-1756.
[8]	张献丰, 郭利建, 李康春, 孔斌雪, 刘玉芳, 车卓, 杨德龙. 小麦ABHD6基因家族鉴定与粒重功能标记开发[J]. 作物学报, 2026, 52(6): 1711-1727.
[9]	张颖星, 宋裕祯, 王跃, 曹越, 曹晓宁, 王瑞云. EMS诱导糜子优异性状突变体的筛选及表型分析[J]. 作物学报, 2026, 52(5): 1388-1400.
[10]	王壮壮, 武紫君, 张永新, 张芯源, 袁丽雪, 陈如雪, 刘世举, 段剑钊, 冯伟, 王同朝, 王永华. 豫东南黏壤潮土区水氮优化协同提高冬小麦产量和氮素利用效率[J]. 作物学报, 2026, 52(5): 1501-1521.
[11]	杨欣雨, 崔文涛, 迪力尼格尔·阿力木, 汪凯翔, 吴鹏昊, 任姣姣. 玉米穗上叶片数全基因组关联分析和全基因组选择[J]. 作物学报, 2026, 52(5): 1573-1590.
[12]	张振, 冯连杰, 石玉, 于振文, 张永丽. 节水补灌下不同穗型小麦产量形成差异研究[J]. 作物学报, 2026, 52(5): 1522-1535.
[13]	闫安, 蒋昆炜, 王蓉圆, 田林, 张璐, 王韵, 徐建龙. 水稻剑叶小维管束数基因SVN7的鉴定与克隆[J]. 作物学报, 2026, 52(5): 1364-1372.
[14]	何万龙, 耿洪伟, 张飞飞, 米克热阿依·阿巴白克热, 罗紫洋, 李鹏程, 周钊宇, 程宇坤. 基于深度学习的小麦重要病害图像识别系统的研究[J]. 作物学报, 2026, 52(5): 1401-1417.
[15]	田春艳, 陆鑫, 吴才文, 徐超华, 刘家勇, 边芯, 桃联安. 基于荧光SSR的甘蔗创新种质遗传多样性分析及育种潜力评估[J]. 作物学报, 2026, 52(4): 1057-1072.