小麦抽穗期和开花期性状的全基因组关联分析
|
摘要
为揭示控制小麦抽穗期和开花期性状的遗传位点,利用均匀分布在21条染色体上的106对SSR标记,对205份小麦品种构成的自然群体进行关联分析。结果表明,在106对SSR标记中共检测到879个等位变异,主要等位变异频率的变化范围为0.175～0.986,平均为0.548;多态性信息指数的变化范围为0.028～0.900,平均为0.557。采用混合线性模型共检测到7个与抽穗期和开花期显著关联(P<0.01)的位点,其中1个存在极显著关联(P<0.001)。另外,Xgwm182(5D)在灌溉条件下与抽穗期显著关联,Xbarc42(3D)在雨养条件下分别与抽穗期和开花期显著关联,这两个位点与前人的研究结果一致。Xgwm102(2D)在灌溉条件下与开花期显著关联,而Xgwm124(1B)在雨养条件下与抽穗期显著关联。Xgwm130(7A)在雨养和灌溉条件下均与抽穗期相关联。研究结果为小麦抽穗期和开花期性状的分子标记辅助选择育种提供了信息。
In order to reveal the genetic loci controlling the heading and flowering date of wheat, 106 pairs of SSRmarkers, evenly distributed on 21 chromosomes, and a natural population consisted of 205 accessions, were used toperform genome-wide association analysis. The results showed that 879 allelic variations were detected in 106 pairsof SSR markers. The main allelic variation frequency ranged from 0.175 to 0.986 with an average of 0.548. Thepolymorphism information index ranged from 0.028-0.900 with an average of 0.557. A mixed linear model was usedto detect seven loci associated with significant heading and flowering date(P <0.01), one of which were extremelysignificant(P < 0.001). In addition, Xgwm182(5 D) was significantly associated with heading date under irrigationconditions. Xbarc42(3 D) was significantly associated with heading and flowering date under rainfed conditions,respectively. These two sites were consistent with previous studies. Xgwm102(2 D) was significantly associated withflowering date under irrigation conditions, while Xgwm124(1 B) was significantly associated with heading date underrainfed conditions. Xgwm130(7 A) was associated with heading date under rainfed and irrigation conditions. The aboveresults provide information for molecular marker-assisted selection breeding of heading and flowering date in wheat.
In order to reveal the genetic loci controlling the heading and flowering date of wheat, 106 pairs of SSRmarkers, evenly distributed on 21 chromosomes, and a natural population consisted of 205 accessions, were used toperform genome-wide association analysis. The results showed that 879 allelic variations were detected in 106 pairsof SSR markers. The main allelic variation frequency ranged from 0.175 to 0.986 with an average of 0.548. Thepolymorphism information index ranged from 0.028-0.900 with an average of 0.557. A mixed linear model was usedto detect seven loci associated with significant heading and flowering date(P <0.01), one of which were extremelysignificant(P < 0.001). In addition, Xgwm182(5 D) was significantly associated with heading date under irrigationconditions. Xbarc42(3 D) was significantly associated with heading and flowering date under rainfed conditions,respectively. These two sites were consistent with previous studies. Xgwm102(2 D) was significantly associated withflowering date under irrigation conditions, while Xgwm124(1 B) was significantly associated with heading date underrainfed conditions. Xgwm130(7 A) was associated with heading date under rainfed and irrigation conditions. The aboveresults provide information for molecular marker-assisted selection breeding of heading and flowering date in wheat.
引文
[1]宋彦霞,景蕊莲,霍纳新,等.普通小麦(T. aestivum L.)不同作图群体抽穗期QTL分析.中国农业科学,2006(11):2186-2193.
[2]宋彦霞.小麦抽穗期及其它农艺性状的QTL分析.雅安:四川农业大学,2005.
[3]闫雪,史雨刚,李晓宇,等.小麦开花期QTL分析.山西农业科学,2015,43(8):919-921,950.
[4]谷俊涛,刘桂茹,栗雨勤,等.不同抗旱类型小麦品种开花期光合速率与抗旱性的比较研究.河北农业大学学报,2001(3):1-4.
[5]何龙海.水稻抽穗期基因位点的连锁与关联分析.南昌:江西农业大学,2014.
[6]Mackay I,Powell W. Methods for linkage disequllibrium mapping incrops. Trends in Plant Science,2007,12(2):57-63.
[7]Qaseem M F,Qureshi R,Muqaddasi Q H,et al. Genome-wideassociation mapping in bread wheat subjected to independent andcombined high temperature and drought stress. PLoS ONE,2018,13(6):e0199121.
[8]刘坤,张雪海,孙高阳,等.玉米株型相关性状的全基因组关联分析.中国农业科学,2018,51(5):821-834.
[9]李婉琳,宋洁,郭文,等.马铃薯主要农艺性状的SSR标记关联分析.分子植物育种,2016,14(11):3102-3112.
[10]赵波,叶剑,金文林,等.不同类型小豆种质SSR标记遗传多样性及性状关联分析.中国农业科学,2011,44(4):673-682.
[11]赖勇,吕仲昱,贾建磊,等.外引大麦农艺性状SSR关联位点及等位变异表型效应分析.麦类作物学报,2018,38(4):424-429.
[12]邹德堂,赵广欣,孙健.水稻淀粉合成候选基因OsAGPL3与淀粉相关性状的关联分析.东北农业大学学报,2017,48(9):1-10.
[13]郭杰.小麦育成品种穗顶部、基部结实性及其它产量相关性状的遗传解析.南京:南京农业大学,2015.
[14]Somers D J,Isaac P,Edwards K. A high-density microsatelliteconsensus map for bread wheat(Triticum aestivum L.). Theoreticaland Applied Genetics,2004(10):1105-1114.
[15]Liu K,Muse S V. PowerMarker:an integrated analysis environmentfor genetic marker analysis. Bioinformatics,2005,21(9):2128-2129.
[16]Pritchard J K,Stephens M,Rosenberg N A,et al. Associationmapping in structured populations. American Journal of HumanGenetics,2000,67(1):170-180.
[17]Evanno G,Regnaut S,Goudet J. Detecting the number of clustersof individuals using the software STRUCTURE:a simulation study.Molecular Ecology,2005,14(8):2611-2620.
[18]Hardy O J,Vekemans X. SPAGeDi:a versatile computer programto analyze spatial genetic structure at the individual or populationlevels. Molecular Ecology,2002,2(4):618-620.
[19]Bernardo R. Best linear unbiased prediction of maize single-crossperformance. Crop Science,1996,36(1):50-56.
[20]胡建帮. 262份小麦自然群体抽穗期的关联分析.合肥:安徽农业大学,2015.
[21]Zanke C,Ling J,Plieske J,et al. Genetic architecture of main effectQTL for heading date in European winter wheat. Frontiers in PlantScience,2014,5:217.
[22]张嘉楠.小麦资源材料抗旱相关性状关联分析及优异等位基因挖掘.保定:河北农业大学,2010.
[23]王曙光,史雨刚,史华伟,等.春小麦光合特性与抗旱性的关系研究.作物杂志,2017(6):23-29.
[24]赵京岚.粗山羊草和普通小麦主要农艺性状与SSR标记的关联分析.泰安:山东农业大学,2014.
[25]刘国祥.小麦抽穗期基因遗传作图.雅安:四川农业大学,2012.
[26]朱玉磊,王升星,赵良侠,等.以关联分析发掘小麦整穗发芽抗性基因分子标记.作物学报,2014,40(10):1725-1732.
[27]闫鹏娇.小麦K-CMS恢复系的遗传多样性研究及关联分析.杨凌:西北农林科技大学,2017.
[2]宋彦霞.小麦抽穗期及其它农艺性状的QTL分析.雅安:四川农业大学,2005.
[3]闫雪,史雨刚,李晓宇,等.小麦开花期QTL分析.山西农业科学,2015,43(8):919-921,950.
[4]谷俊涛,刘桂茹,栗雨勤,等.不同抗旱类型小麦品种开花期光合速率与抗旱性的比较研究.河北农业大学学报,2001(3):1-4.
[5]何龙海.水稻抽穗期基因位点的连锁与关联分析.南昌:江西农业大学,2014.
[6]Mackay I,Powell W. Methods for linkage disequllibrium mapping incrops. Trends in Plant Science,2007,12(2):57-63.
[7]Qaseem M F,Qureshi R,Muqaddasi Q H,et al. Genome-wideassociation mapping in bread wheat subjected to independent andcombined high temperature and drought stress. PLoS ONE,2018,13(6):e0199121.
[8]刘坤,张雪海,孙高阳,等.玉米株型相关性状的全基因组关联分析.中国农业科学,2018,51(5):821-834.
[9]李婉琳,宋洁,郭文,等.马铃薯主要农艺性状的SSR标记关联分析.分子植物育种,2016,14(11):3102-3112.
[10]赵波,叶剑,金文林,等.不同类型小豆种质SSR标记遗传多样性及性状关联分析.中国农业科学,2011,44(4):673-682.
[11]赖勇,吕仲昱,贾建磊,等.外引大麦农艺性状SSR关联位点及等位变异表型效应分析.麦类作物学报,2018,38(4):424-429.
[12]邹德堂,赵广欣,孙健.水稻淀粉合成候选基因OsAGPL3与淀粉相关性状的关联分析.东北农业大学学报,2017,48(9):1-10.
[13]郭杰.小麦育成品种穗顶部、基部结实性及其它产量相关性状的遗传解析.南京:南京农业大学,2015.
[14]Somers D J,Isaac P,Edwards K. A high-density microsatelliteconsensus map for bread wheat(Triticum aestivum L.). Theoreticaland Applied Genetics,2004(10):1105-1114.
[15]Liu K,Muse S V. PowerMarker:an integrated analysis environmentfor genetic marker analysis. Bioinformatics,2005,21(9):2128-2129.
[16]Pritchard J K,Stephens M,Rosenberg N A,et al. Associationmapping in structured populations. American Journal of HumanGenetics,2000,67(1):170-180.
[17]Evanno G,Regnaut S,Goudet J. Detecting the number of clustersof individuals using the software STRUCTURE:a simulation study.Molecular Ecology,2005,14(8):2611-2620.
[18]Hardy O J,Vekemans X. SPAGeDi:a versatile computer programto analyze spatial genetic structure at the individual or populationlevels. Molecular Ecology,2002,2(4):618-620.
[19]Bernardo R. Best linear unbiased prediction of maize single-crossperformance. Crop Science,1996,36(1):50-56.
[20]胡建帮. 262份小麦自然群体抽穗期的关联分析.合肥:安徽农业大学,2015.
[21]Zanke C,Ling J,Plieske J,et al. Genetic architecture of main effectQTL for heading date in European winter wheat. Frontiers in PlantScience,2014,5:217.
[22]张嘉楠.小麦资源材料抗旱相关性状关联分析及优异等位基因挖掘.保定:河北农业大学,2010.
[23]王曙光,史雨刚,史华伟,等.春小麦光合特性与抗旱性的关系研究.作物杂志,2017(6):23-29.
[24]赵京岚.粗山羊草和普通小麦主要农艺性状与SSR标记的关联分析.泰安:山东农业大学,2014.
[25]刘国祥.小麦抽穗期基因遗传作图.雅安:四川农业大学,2012.
[26]朱玉磊,王升星,赵良侠,等.以关联分析发掘小麦整穗发芽抗性基因分子标记.作物学报,2014,40(10):1725-1732.
[27]闫鹏娇.小麦K-CMS恢复系的遗传多样性研究及关联分析.杨凌:西北农林科技大学,2017.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |