大豆重组自交系群体NJRSXG百粒重超亲分离的遗传解析
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摘要
【目的】解析大豆重组自交系中百粒重的QTL及其等位变异效应,探究重组自交系中百粒重存在超亲分离的原因,为进一步培育不同类型百粒重大豆提供遗传依据。【方法】利用以先进2号和赶泰2-2为亲本衍生的重组自交系群体NJRSXG为材料,在2009—2011年共5种环境下测定百粒重表型数据,建立具有400个SSR标记的遗传图谱,选用QTLNetwork V2.1软件中混合模型区间作图方法(mixed model based composite interval mapping,MCIM)对表型数据和基因型数据进行大豆百粒重QTL定位研究。在定位结果基础上,分析每个重组自交系群体中每个家系百粒重QTL等位变异类型,建立百粒重QTL-allele矩阵。【结果】5种环境试验的平均结果,亲本先进2号和赶泰2-2的百粒重分别为16.92和14.14g,重组自交系百粒重变幅为12.09—25.01 g,存在超亲分离,多环境下遗传变异系数(genotypic coefficient of variation,GCV)为16.06%,遗传率为96.17%。利用MCIM方法联合5环境原始数据,总共检测到10个加性QTL和9对上位性QTL,10个加性QTL的表型变异解释率变幅为0.69%—14.93%,其中Sw-05-2、Sw-08-1、Sw-12-1和Sw-17-1的表型变异解释率较高,分别为6.91%、14.93%、7.80%和5.01%,Sw-13-3为以往未见报道并兼具加性和上位性效应的位点。上位性QTL的表型变异解释率较小,变幅为0.31%—3.44%,其中Sw-e4的表型变异解释率最高。联合多环境方差分析和QTL定位结果,解析大豆百粒重的遗传结构,发现加性QTL累积贡献了47.91%表型变异,上位性QTL累积贡献13.06%表型变异,未检测出的微效QTL累计解释了35.20%的表型变异。在定位的同时,获得了QTL等位变异的效应,分析重组自交系及其亲本中百粒重QTL等位变异的组成,建立了NJRSXG的百粒重QTL-allele矩阵;两亲本分别具有7对和3对加性增效等位变异,属互补型组合;矩阵中没有一个重组自交家系包含所有减效等位变异或增效等位变异,表明重组自交家系具有进一步改良的潜力;大粒型家系具有较多增效等位变异,小粒型家系具有较多减效等位变异;说明百粒重位点间的重组是产生超亲家系的重要原因。【结论】利用重组自交系群体能够产生超亲分离家系;联合多环境数据检测到10个加性QTL和9对上位性QTL;百粒重QTL位点间的重组是超亲分离的原因;重组自交家系间具有进一步重组的潜力。
【Objective】 The present study aimed at exploring the QTL and their allele effects of the 100-seed weight in a recombinant inbred line(RIL) population for revealing the genetic mechanism of transgressive segregation,and providing guidance for breeding for different seed size types in soybeans. 【Method】 The RIL(recombinant inbred line) population NJRSXG derived from a cross between Xinjin 2 and Gantai 2-2 was tested and measured for their 100-seed weight in five environments from 2009 to 2011. The genetic map with 400 SSR markers was established for QTL mapping using the mixed model based composite interval mapping(MCIM) method in QTL Network V2.1 software. Based on the QTL mapping,the QTL-allele constitutions of each line of the RIL population was obtained,and the corresponding QTL-allele matrix was established. 【Result】 The 100-seed weight of the parents,Xinjin 2 and Gantai 2-2,were 16.92 g and 14.14 g,respectively,with those of the RILs ranging from 12.09 g to 25.01 g,showing an obvious transgressive segregation. The genotypic coefficient of variation(GCV) was 16.06%,and the overall heritability was 96.17% from a joint dataset analysis. Ten additive QTL and nine epistatic QTL pairs were detected in the joint dataset using an MCIM method. The phenotypic variation explained by additive QTL was ranged from 0.69% to 14.93%,and the four major QTLs,i.e.,Sw-05-2,Sw-08-1,Sw-12-1 and Sw-17-1,were 6.91%,14.93%,7.80%,and 5.01%. The Sw-13-3 with both additive effect and epistasis effects had not been reported before. The phenotypic variance of epistatic QTL pairs was small,and ranged from 0.31% to 3.44%. The genetic components of 100-seed weight was estimated from the mapping results,and the analysis of variance for the joint dataset,the genetic contribution due to additive QTL,epistatic QTL pairs,and collective unmapped minor QTL were 47.91%,13.06%,and 35.19% of the phenotypic variation,respectively. From the mapping procedure,the allele effects of all the loci were also obtained,and the genetic constitution of the QTL-alleles for each line of the RIL population and its parents was used to establish the QTL-allele matrix. The two parents have seven and three loci with positive additive effects respectively; therefore,this is a complementary pair of parents. No lines of the RIL population had all positive alleles or all negative alleles,indicating a hidden potential of recombination,and the lines with larger seed weight had more positive alleles,while the lines with smaller seed weight had more negative alleles,which implies that recombination among loci was the major cause for transgressive segregation of the 100-seed weight in the RIL population. In addition,it was also found that there was still a possibility to improve the 100-seed weight through further recombination. 【Conclusion】 The transgressive segregation of 100-seed weight can be found in a RIL population; 10 additive QTL and 9 epistatic QTL were detected using the joint dataset tested under five environments. The transgressive segregation was caused by recombination among loci between parents,and the potential for further improvement through recombination among RILs still exists.
【Objective】 The present study aimed at exploring the QTL and their allele effects of the 100-seed weight in a recombinant inbred line(RIL) population for revealing the genetic mechanism of transgressive segregation,and providing guidance for breeding for different seed size types in soybeans. 【Method】 The RIL(recombinant inbred line) population NJRSXG derived from a cross between Xinjin 2 and Gantai 2-2 was tested and measured for their 100-seed weight in five environments from 2009 to 2011. The genetic map with 400 SSR markers was established for QTL mapping using the mixed model based composite interval mapping(MCIM) method in QTL Network V2.1 software. Based on the QTL mapping,the QTL-allele constitutions of each line of the RIL population was obtained,and the corresponding QTL-allele matrix was established. 【Result】 The 100-seed weight of the parents,Xinjin 2 and Gantai 2-2,were 16.92 g and 14.14 g,respectively,with those of the RILs ranging from 12.09 g to 25.01 g,showing an obvious transgressive segregation. The genotypic coefficient of variation(GCV) was 16.06%,and the overall heritability was 96.17% from a joint dataset analysis. Ten additive QTL and nine epistatic QTL pairs were detected in the joint dataset using an MCIM method. The phenotypic variation explained by additive QTL was ranged from 0.69% to 14.93%,and the four major QTLs,i.e.,Sw-05-2,Sw-08-1,Sw-12-1 and Sw-17-1,were 6.91%,14.93%,7.80%,and 5.01%. The Sw-13-3 with both additive effect and epistasis effects had not been reported before. The phenotypic variance of epistatic QTL pairs was small,and ranged from 0.31% to 3.44%. The genetic components of 100-seed weight was estimated from the mapping results,and the analysis of variance for the joint dataset,the genetic contribution due to additive QTL,epistatic QTL pairs,and collective unmapped minor QTL were 47.91%,13.06%,and 35.19% of the phenotypic variation,respectively. From the mapping procedure,the allele effects of all the loci were also obtained,and the genetic constitution of the QTL-alleles for each line of the RIL population and its parents was used to establish the QTL-allele matrix. The two parents have seven and three loci with positive additive effects respectively; therefore,this is a complementary pair of parents. No lines of the RIL population had all positive alleles or all negative alleles,indicating a hidden potential of recombination,and the lines with larger seed weight had more positive alleles,while the lines with smaller seed weight had more negative alleles,which implies that recombination among loci was the major cause for transgressive segregation of the 100-seed weight in the RIL population. In addition,it was also found that there was still a possibility to improve the 100-seed weight through further recombination. 【Conclusion】 The transgressive segregation of 100-seed weight can be found in a RIL population; 10 additive QTL and 9 epistatic QTL were detected using the joint dataset tested under five environments. The transgressive segregation was caused by recombination among loci between parents,and the potential for further improvement through recombination among RILs still exists.
引文
[1]Hao D R,Cheng H,Yin Z T,Cui S Y,Zhang D,Wang H,Yu D Y.Identification of single nucleotide polymorphisms and haplotypes associated with yield and yield components in soybean(Glycine max)landraces across multiple environments.Theoretical and Applied Genetics,2012,124(3):447-458.
[2]黄中文,赵团结,喻德跃,陈受宜,盖钧镒.大豆产量有关性状QTL的检测.中国农业科学,2009,42(12):4155-4165.Huang Z W,Zhao T J,Yu D Y,Chen S Y,Gai J Y.Detection of QTLs of yield related traits in soybean.Scientia Agricultura Sinica,2009,42(12):4155-4165.(in Chinese)
[3]王凤敏,赵双进,王静华,谷峰,赵青松,杨春燕,张孟臣,秦君.河北省不同时期育成大豆品种产量构成因子分析.大豆科学,2014,33(6):830-836.Wang F M,Zhao S J,Wang J H,Gu F,Zhao Q S,Yang C Y,Zhang M C,Qin J.Analysis on the yield components of soybean cultivars released in defferent stages of Hebei province.Soybean Science,2014,33(6):830-836.(in Chinese)
[4]Maughan P J,Maroof M A S,Buss G R.Molecular-marker analysis of seed weight:Genomic locations,gene action,and evidence for orthologous evolution among three legume species.Theoretical and Applied Genetics,1996,93(4):574-579.
[5]Moose S P,Mumm R H.Molecular plant breeding as the foundation for 21st century crop improvement.Plant Physiology,2008,147(3):969-977.
[6]Zhang Y H,He J B,Wang Y F,Xing G N,Zhao J M,Li Y,Yang S P,Palmer R G,Zhao T J,Gai J Y.Establishment of a 100-seed weight quantitative trait locus-allele matrix of the germplasm population for optimal recombination design in soybean breeding programmes.Journal of Experimental Botany,2015.
[7]Dargahi H,Tanya P,Somta P,Abe J,Srinives P.Mapping quantitative trait loci for yield-related traits in soybean(Glycine max L.).Breeding Science,2014,64(4):282-290.
[8]Kato S,Sayama T,Fujii K,Yumoto S,Kono Y,Hwang T Y,Kikuchi A,Takada Y,Shiraiwa T,Ishimoto M.A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds.Theoretical and Applied Genetics,2014,127(6):1365-1374.
[9]汪霞,徐宇,李广军,李河南,艮文全,章元明.大豆百粒重QTL定位.作物学报,2010,36(10):1674-1682.Wang X,Xu Y,Li G J,Li H N,Gen W Q,Zhang Y M.Mapping quantitative trait loci for 100-seed weight in soybean(Glycine max L.Merr).Acta Agronomica Sinica,2010,36(10):1674-1682.(in Chinese)
[10]孙亚男,仕相林,蒋洪蔚,孙殿军,辛大伟,刘春燕,胡国华,陈庆山.大豆百粒重QTL的上位效应和基因型×环境互作效应.中国油料作物学报,2012,34(6):598-603.Sun Y N,Shi X L,Jiang H W,Sun D J,Xin D W,Liu C Y,Hu G H,Chen Q S.Epistatic effects and q E interaction effects of QTLs for100-seed weight in soybean.Chinese Journal of Oil Crop Sciences,2012,34(6):598-603.(in Chinese)
[11]Gai J Y,Chen L,Zhang Y H,Zhao T J,Xing G N,Xing H.Genome-wide genetic dissection of germplasm resources and implications for breeding by design in soybean.Breeding Science,2012,61(5):495-510.
[12]Hanson C,Robinson H,Comstock R.Biometrical studies of yield in segregating populations of Korean Lespedeza.Agronomy Journal,1956,48(6):268-272.
[13]Schmutz J,Cannon S B,Schlueter J,Ma J,Mitros T,Nelson W,Hyten D L,Song Q,Thelen J J,Cheng J,Xu D,Hellsten U,May G D,Yu Y,Sakurai T,Umezawa T,Bhattacharyya M K,Sandhu D,Valliyodan B,Lindquist E,Peto M,Grant D,Shu S,Goodstein D,Barry K,FutrellGriggs M,Abernathy B,Du J,Tian Z,Zhu L,Gill N,Joshi T,Libault M,Sethuraman A,Zhang X C,Shinozaki K,Nguyen H T,Wing R A,Cregan P,Specht J,Grimwood J,Rokhsar D,Stacey G,Shoemaker R C,Jackson S A.Genome sequence of the palaeopolyploid soybean.Nature,2010,463(7278):178-183.
[14]苏成付,赵团结,盖钧镒.不同统计遗传模型QTL定位方法应用效果的模拟比较.作物学报,2010,36(7):1100-1107.Su C F,Zhao T J,Gai J Y.Simulation comparisons of effectiveness among QTL mapping procedures of different statistical genetic models.Acta Agronomica Sinica,2010,36(7):1100-1107.(in Chinese)
[15]Yang J,Hu C,Hu H,Yu R,Xia Z,Ye X,Zhu J.QTLNetwork:Mapping and visualizing genetic architecture of complex traits in experimental populations.Bioinformatics,2008,24(5):721-723.
[16]Wang S,Basten C,Zeng Z.Windows QTL cartographer 2.5.Department of Statistics,North Carolina State University,Raleigh,NC,2012.
[17]Voorrips R E.Map Chart:Software for the graphical presentation of linkage maps and QTLs.The Journal of Heredity,2002,93(1):77-78.
[18]Han Y P,Li D M,Zhu D,Li H,Li X,Teng W,Li W.QTL analysis of soybean seed weight across multi-genetic backgrounds and environments.Theoretical and Applied Genetics,2012,125(4):671-683.
[19]Zhang W K,Wang Y J,Luo G Z,Zhang J S,He C Y,Wu X L,Gai J Y,Chen S Y.QTL mapping of ten agronomic traits on the soybean(Glycine max L.Merr.)genetic map and their association with EST markers.Theoretical and Applied Genetics,2004,108(6):1131-1139.
[20]Hoeck J A,Fehr W R,Shoemaker R C,Welke G A,Johnson S L,Cianzio S R.Molecular marker analysis of seed size in soybean.Crop Science,2003,43(1):68-74.
[21]Kim H K,Kim Y C,Kim S T,Son B G,Choi Y W,Kang J S,Park Y H,Cho Y S,Cho I S.Analysis of quantitative trait loci(QTLs)for seed size and fatty acid composition using recombinant inbred lines in soybean.Journal of Life Science,2010,20(8):1186-1192.
[22]Panthee D R,Pantalone V R,West D R,Saxton A M,Sams C E.Quantitative trait loci for seed protein and oil concentration,and seed size in soybean.Crop Science,2005,45(5):2015-2022.
[23]Hyten D L,Pantalone V R,Sams C E,Saxton A M,Landau-Ellis D,Stefaniak T R,Schmidt M E.Seed quality QTL in a prominent soybean population.Theoretical and Applied Genetics,2004,109(3):552-561.
[24]Buckler E S,Holland J B,Bradbury P J,Acharya C B,Brown P J,Browne C,Ersoz E,Flint-Garcia S,Garcia A,Glaubitz J C,Goodman M M,Harjes C,Guill K,Kroon D E,Larsson S,Lepak N K,Li H,Mitchell S E,Pressoir G,Peiffer J A,Rosas M O,Rocheford T R,Romay M C,Romero S,Salvo S,Sanchez Villeda H,da Silva H S,Sun Q,Tian F,Upadyayula N,Ware D,Yates H,Yu J,Zhang Z,Kresovich S,Mc Mullen M D.The genetic architecture of maize flowering time.Science,2009,325(5941):714-718.
[25]Flint-garcia S A,Thornsberry J M,Buckler E S T.Structure of linkage disequilibrium in plants.Annu Review of Plant Biology,2003,54(1):357-374.
[26]晁毛妮,郝德荣,印志同,张晋玉,宋海娜,张怀仁,褚珊珊,张国正,喻德跃.大豆生物量与产量组分间的相关及关联分析.作物学报,2014,40(1):7-16.Chao M N,Hao D R,Yin Z T,Zhang J Y,Song H N,Zhang H R,Chu S S,Zhang G Z,Yu D Y.Correlation and association analysis between biomass and yield components in soybean.Acta Agronomica Sinica,2014,40(1):7-16.(in Chinese)
[27]Korir P,Zhang J,Wu K J,Zhao T J,Gai J Y.Association mapping combined with linkage analysis for aluminum tolerance among soybean cultivars released in Yellow and Changjiang River Valleys in China.Theoretical and Applied Genetics,2013,126(6):1659-1675.
[28]Kim H,Xing G N,Wang Y F,Zhao T J,Yu D Y,Yang S P,Li Y,Chen S Y,Palmer R G,Gai J Y.Constitution of resistance to common cutworm in terms of antibiosis and antixenosis in soybean RIL populations.Euphytica,2014,196(1):137-154.
[2]黄中文,赵团结,喻德跃,陈受宜,盖钧镒.大豆产量有关性状QTL的检测.中国农业科学,2009,42(12):4155-4165.Huang Z W,Zhao T J,Yu D Y,Chen S Y,Gai J Y.Detection of QTLs of yield related traits in soybean.Scientia Agricultura Sinica,2009,42(12):4155-4165.(in Chinese)
[3]王凤敏,赵双进,王静华,谷峰,赵青松,杨春燕,张孟臣,秦君.河北省不同时期育成大豆品种产量构成因子分析.大豆科学,2014,33(6):830-836.Wang F M,Zhao S J,Wang J H,Gu F,Zhao Q S,Yang C Y,Zhang M C,Qin J.Analysis on the yield components of soybean cultivars released in defferent stages of Hebei province.Soybean Science,2014,33(6):830-836.(in Chinese)
[4]Maughan P J,Maroof M A S,Buss G R.Molecular-marker analysis of seed weight:Genomic locations,gene action,and evidence for orthologous evolution among three legume species.Theoretical and Applied Genetics,1996,93(4):574-579.
[5]Moose S P,Mumm R H.Molecular plant breeding as the foundation for 21st century crop improvement.Plant Physiology,2008,147(3):969-977.
[6]Zhang Y H,He J B,Wang Y F,Xing G N,Zhao J M,Li Y,Yang S P,Palmer R G,Zhao T J,Gai J Y.Establishment of a 100-seed weight quantitative trait locus-allele matrix of the germplasm population for optimal recombination design in soybean breeding programmes.Journal of Experimental Botany,2015.
[7]Dargahi H,Tanya P,Somta P,Abe J,Srinives P.Mapping quantitative trait loci for yield-related traits in soybean(Glycine max L.).Breeding Science,2014,64(4):282-290.
[8]Kato S,Sayama T,Fujii K,Yumoto S,Kono Y,Hwang T Y,Kikuchi A,Takada Y,Shiraiwa T,Ishimoto M.A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds.Theoretical and Applied Genetics,2014,127(6):1365-1374.
[9]汪霞,徐宇,李广军,李河南,艮文全,章元明.大豆百粒重QTL定位.作物学报,2010,36(10):1674-1682.Wang X,Xu Y,Li G J,Li H N,Gen W Q,Zhang Y M.Mapping quantitative trait loci for 100-seed weight in soybean(Glycine max L.Merr).Acta Agronomica Sinica,2010,36(10):1674-1682.(in Chinese)
[10]孙亚男,仕相林,蒋洪蔚,孙殿军,辛大伟,刘春燕,胡国华,陈庆山.大豆百粒重QTL的上位效应和基因型×环境互作效应.中国油料作物学报,2012,34(6):598-603.Sun Y N,Shi X L,Jiang H W,Sun D J,Xin D W,Liu C Y,Hu G H,Chen Q S.Epistatic effects and q E interaction effects of QTLs for100-seed weight in soybean.Chinese Journal of Oil Crop Sciences,2012,34(6):598-603.(in Chinese)
[11]Gai J Y,Chen L,Zhang Y H,Zhao T J,Xing G N,Xing H.Genome-wide genetic dissection of germplasm resources and implications for breeding by design in soybean.Breeding Science,2012,61(5):495-510.
[12]Hanson C,Robinson H,Comstock R.Biometrical studies of yield in segregating populations of Korean Lespedeza.Agronomy Journal,1956,48(6):268-272.
[13]Schmutz J,Cannon S B,Schlueter J,Ma J,Mitros T,Nelson W,Hyten D L,Song Q,Thelen J J,Cheng J,Xu D,Hellsten U,May G D,Yu Y,Sakurai T,Umezawa T,Bhattacharyya M K,Sandhu D,Valliyodan B,Lindquist E,Peto M,Grant D,Shu S,Goodstein D,Barry K,FutrellGriggs M,Abernathy B,Du J,Tian Z,Zhu L,Gill N,Joshi T,Libault M,Sethuraman A,Zhang X C,Shinozaki K,Nguyen H T,Wing R A,Cregan P,Specht J,Grimwood J,Rokhsar D,Stacey G,Shoemaker R C,Jackson S A.Genome sequence of the palaeopolyploid soybean.Nature,2010,463(7278):178-183.
[14]苏成付,赵团结,盖钧镒.不同统计遗传模型QTL定位方法应用效果的模拟比较.作物学报,2010,36(7):1100-1107.Su C F,Zhao T J,Gai J Y.Simulation comparisons of effectiveness among QTL mapping procedures of different statistical genetic models.Acta Agronomica Sinica,2010,36(7):1100-1107.(in Chinese)
[15]Yang J,Hu C,Hu H,Yu R,Xia Z,Ye X,Zhu J.QTLNetwork:Mapping and visualizing genetic architecture of complex traits in experimental populations.Bioinformatics,2008,24(5):721-723.
[16]Wang S,Basten C,Zeng Z.Windows QTL cartographer 2.5.Department of Statistics,North Carolina State University,Raleigh,NC,2012.
[17]Voorrips R E.Map Chart:Software for the graphical presentation of linkage maps and QTLs.The Journal of Heredity,2002,93(1):77-78.
[18]Han Y P,Li D M,Zhu D,Li H,Li X,Teng W,Li W.QTL analysis of soybean seed weight across multi-genetic backgrounds and environments.Theoretical and Applied Genetics,2012,125(4):671-683.
[19]Zhang W K,Wang Y J,Luo G Z,Zhang J S,He C Y,Wu X L,Gai J Y,Chen S Y.QTL mapping of ten agronomic traits on the soybean(Glycine max L.Merr.)genetic map and their association with EST markers.Theoretical and Applied Genetics,2004,108(6):1131-1139.
[20]Hoeck J A,Fehr W R,Shoemaker R C,Welke G A,Johnson S L,Cianzio S R.Molecular marker analysis of seed size in soybean.Crop Science,2003,43(1):68-74.
[21]Kim H K,Kim Y C,Kim S T,Son B G,Choi Y W,Kang J S,Park Y H,Cho Y S,Cho I S.Analysis of quantitative trait loci(QTLs)for seed size and fatty acid composition using recombinant inbred lines in soybean.Journal of Life Science,2010,20(8):1186-1192.
[22]Panthee D R,Pantalone V R,West D R,Saxton A M,Sams C E.Quantitative trait loci for seed protein and oil concentration,and seed size in soybean.Crop Science,2005,45(5):2015-2022.
[23]Hyten D L,Pantalone V R,Sams C E,Saxton A M,Landau-Ellis D,Stefaniak T R,Schmidt M E.Seed quality QTL in a prominent soybean population.Theoretical and Applied Genetics,2004,109(3):552-561.
[24]Buckler E S,Holland J B,Bradbury P J,Acharya C B,Brown P J,Browne C,Ersoz E,Flint-Garcia S,Garcia A,Glaubitz J C,Goodman M M,Harjes C,Guill K,Kroon D E,Larsson S,Lepak N K,Li H,Mitchell S E,Pressoir G,Peiffer J A,Rosas M O,Rocheford T R,Romay M C,Romero S,Salvo S,Sanchez Villeda H,da Silva H S,Sun Q,Tian F,Upadyayula N,Ware D,Yates H,Yu J,Zhang Z,Kresovich S,Mc Mullen M D.The genetic architecture of maize flowering time.Science,2009,325(5941):714-718.
[25]Flint-garcia S A,Thornsberry J M,Buckler E S T.Structure of linkage disequilibrium in plants.Annu Review of Plant Biology,2003,54(1):357-374.
[26]晁毛妮,郝德荣,印志同,张晋玉,宋海娜,张怀仁,褚珊珊,张国正,喻德跃.大豆生物量与产量组分间的相关及关联分析.作物学报,2014,40(1):7-16.Chao M N,Hao D R,Yin Z T,Zhang J Y,Song H N,Zhang H R,Chu S S,Zhang G Z,Yu D Y.Correlation and association analysis between biomass and yield components in soybean.Acta Agronomica Sinica,2014,40(1):7-16.(in Chinese)
[27]Korir P,Zhang J,Wu K J,Zhao T J,Gai J Y.Association mapping combined with linkage analysis for aluminum tolerance among soybean cultivars released in Yellow and Changjiang River Valleys in China.Theoretical and Applied Genetics,2013,126(6):1659-1675.
[28]Kim H,Xing G N,Wang Y F,Zhao T J,Yu D Y,Yang S P,Li Y,Chen S Y,Palmer R G,Gai J Y.Constitution of resistance to common cutworm in terms of antibiosis and antixenosis in soybean RIL populations.Euphytica,2014,196(1):137-154.