小麦F型雄性不育系和恢复系SSR指纹图谱构建及遗传差异分析
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摘要
基于荧光毛细管电泳检测系统和SSR指纹数据库管理系统,采用21对SSR核心引物对小麦F型不育系和恢复系进行SSR指纹图谱构建和遗传差异分析,以保护其品种权,同时为杂交组合的选配提供参考。结果显示21对核心SSR引物在F型不育系和442个恢复系中共检测到214个等位变异,不同位点等位变异数的变幅为6~16,平均等位变异数为10.76个;平均多态性信息含量(PIC)与基因多样性分别为0.70和0.73,21对核心SSR引物的分辨率达100%;获得了每份材料独特的DNA指纹图谱报告,为品种权保护提供了技术支撑;恢复系间的遗传距离为0.014~0.952,平均遗传距离为0.723,遗传距离大于0.500的占95%,说明恢复系间遗传多样性比较丰富;不育系与恢复系材料间的遗传距离为0.300~0.952,平均遗传距离为0.681,遗传距离大于0.500的占93%,说明不育系材料与恢复系材料间遗传差异较大,可以从中选择遗传距离大的配制组合。
In order to protect wheat variety and provide theoretical reference for the selection of hybrid wheat combinations, twenty-one core SSRs covering the entire wheat genome were used to construct fingerprinting database and analyze genetic difference for F-type wheat male sterile line and 442 restorer lines, based on fluorescence capillary electrophoresis detection platforms and SSR fingerprint database management system. Two hundred and fourteen allelic variations were detected with an average allele number of 10.76. The average of polymorphism information content(PIC) and gene diversity values were determined to be 0.70 and 0.73, respectively. The resolution of twentyone core SSR primers was 100%. The unique DNA fingerprinting of each material was obtained, which provided technical support for the protection of variety rights. The genetic distance between the restorer lines was 0.014-0.952 with an average allele number of 0.723, and the genetic distance greater than 0.500 reached 95%, which indicated that the genetic diversity among the restorer lines was more abundant. The genetic distance between sterile line and restorer lines was 0.300-0.952, with an average allele number of 0.681, and the restorer lines accounted for 93% with genetic distance greater than 0.500, which showed that there was a great genetic difference between sterile line and restorer lines and it was beneficial to select the restorer line and sterile line configuration with large genetic distance.
In order to protect wheat variety and provide theoretical reference for the selection of hybrid wheat combinations, twenty-one core SSRs covering the entire wheat genome were used to construct fingerprinting database and analyze genetic difference for F-type wheat male sterile line and 442 restorer lines, based on fluorescence capillary electrophoresis detection platforms and SSR fingerprint database management system. Two hundred and fourteen allelic variations were detected with an average allele number of 10.76. The average of polymorphism information content(PIC) and gene diversity values were determined to be 0.70 and 0.73, respectively. The resolution of twentyone core SSR primers was 100%. The unique DNA fingerprinting of each material was obtained, which provided technical support for the protection of variety rights. The genetic distance between the restorer lines was 0.014-0.952 with an average allele number of 0.723, and the genetic distance greater than 0.500 reached 95%, which indicated that the genetic diversity among the restorer lines was more abundant. The genetic distance between sterile line and restorer lines was 0.300-0.952, with an average allele number of 0.681, and the restorer lines accounted for 93% with genetic distance greater than 0.500, which showed that there was a great genetic difference between sterile line and restorer lines and it was beneficial to select the restorer line and sterile line configuration with large genetic distance.
引文
[1]赵昌平.中国杂交小麦研究现状与趋势.中国农业科技导报,2010,12(2):5-8.
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[3]刘丽华,庞斌双,刘阳娜,等.2009-2014年国家冬小麦区域试验品系的遗传多样性及群体结构分析.麦类作物学报,2016,26(2):165-171.
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[7]王凤格,杨扬,易红梅,等.中国玉米审定品种标准SSR指纹库的构建.中国农业科学,2017,50(1):1-14.
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[9]中华人民共和国农业部.NY/T 1433-2014.水稻品种鉴定DNA指纹方法.北京:中国农业科学技术出版社,2014.
[10]庄杰云,施勇烽,应杰政,等.中国主栽水稻品种微卫星标记数据库的初步构建.中国水稻科学,2006,20(5):460-468.
[11]Courtois B,Frouin J,Greco R,et al.Genetic diversity and population structure in a European collection of rice.Crop Science,2012,52:1663-1675.
[12]中华人民共和国农业部.NY/T 2634-2014.棉花品种真实性鉴定SSR分子标记法.北京:中国农业科学技术出版社,2014.
[13]匡猛,杨伟华,许红霞,等.中国棉花主栽品种DNA指纹图谱构建及SSR标记遗传多样性分析.中国农业科学,2011,44(1):20-27.
[14]关荣霞,刘燕,刘章雄,等.利用SSR方法鉴定大豆品种纯度.分子植物育种,2003,1(3):357-360.
[15]张军,赵团结,盖钧镒.中国东北大豆育成品种遗传多样性和群体遗传结构分析.作物学报,2008,34(9):1529-1536.
[16]陆光远,伍晓明,张冬晓,等.SSR标记分析国家油菜区试品种的特异性和一致性.中国农业科学,2008,41(1):32-42.
[17]段艳凤,刘杰,卞春松,等.中国88个马铃薯审定品种SSR指纹图谱构建与遗传多样性分析.作物学报,2009,35(8):1451-1457.
[18]刘红艳,左阳,吴坤,等.国家芝麻区域试验新品种(系)的DNA指纹分析.作物学报,2012,38(4):596-605.
[19]季伟,王立新,孙辉,等.小麦SSR分析体系的简化.农业生物技术学报,2007,15(5):907-908.
[20]Liu K,Muse S V.Power Marker:an integrated analysis environment for genetic marker data.Bioinformatics,2005,21(9):2128-2129.
[21]Brandle J E,Mc Vetty P B E.Geographical diversity parental selection and heterosis in oilseed rape.Canadian Journal of Plant Science,1990,70:935-940.
[2]中华人民共和国农业部.NY/T2859-2015.主要农作物品种真实性SSR分子标记检测普通小麦.北京:中国农业科学技术出版社,2015.
[3]刘丽华,庞斌双,刘阳娜,等.2009-2014年国家冬小麦区域试验品系的遗传多样性及群体结构分析.麦类作物学报,2016,26(2):165-171.
[4]刘丽华,庞斌双,李宏博,等.2009-2015年北京市冬小麦区域试验品系的DNA指纹分析.作物杂志,2016(5):13-18.
[5]Wang L X,Qiu J,Chang L F,et al.Assessment of wheat variety distinctness using SSR markers.Journal of Integrative Agriculture,2015,14(10):1923-1935.
[6]中华人民共和国农业部.NY/T 1432-2014.玉米品种鉴定DNA指纹方法.北京:中国农业科学技术出版社,2014.
[7]王凤格,杨扬,易红梅,等.中国玉米审定品种标准SSR指纹库的构建.中国农业科学,2017,50(1):1-14.
[8]王凤格,田红丽,赵久然,等.中国328个玉米品种(组合)SSR标记遗传多样性分析.中国农业科学,2014,47(5):856-864.
[9]中华人民共和国农业部.NY/T 1433-2014.水稻品种鉴定DNA指纹方法.北京:中国农业科学技术出版社,2014.
[10]庄杰云,施勇烽,应杰政,等.中国主栽水稻品种微卫星标记数据库的初步构建.中国水稻科学,2006,20(5):460-468.
[11]Courtois B,Frouin J,Greco R,et al.Genetic diversity and population structure in a European collection of rice.Crop Science,2012,52:1663-1675.
[12]中华人民共和国农业部.NY/T 2634-2014.棉花品种真实性鉴定SSR分子标记法.北京:中国农业科学技术出版社,2014.
[13]匡猛,杨伟华,许红霞,等.中国棉花主栽品种DNA指纹图谱构建及SSR标记遗传多样性分析.中国农业科学,2011,44(1):20-27.
[14]关荣霞,刘燕,刘章雄,等.利用SSR方法鉴定大豆品种纯度.分子植物育种,2003,1(3):357-360.
[15]张军,赵团结,盖钧镒.中国东北大豆育成品种遗传多样性和群体遗传结构分析.作物学报,2008,34(9):1529-1536.
[16]陆光远,伍晓明,张冬晓,等.SSR标记分析国家油菜区试品种的特异性和一致性.中国农业科学,2008,41(1):32-42.
[17]段艳凤,刘杰,卞春松,等.中国88个马铃薯审定品种SSR指纹图谱构建与遗传多样性分析.作物学报,2009,35(8):1451-1457.
[18]刘红艳,左阳,吴坤,等.国家芝麻区域试验新品种(系)的DNA指纹分析.作物学报,2012,38(4):596-605.
[19]季伟,王立新,孙辉,等.小麦SSR分析体系的简化.农业生物技术学报,2007,15(5):907-908.
[20]Liu K,Muse S V.Power Marker:an integrated analysis environment for genetic marker data.Bioinformatics,2005,21(9):2128-2129.
[21]Brandle J E,Mc Vetty P B E.Geographical diversity parental selection and heterosis in oilseed rape.Canadian Journal of Plant Science,1990,70:935-940.