上海地区水稻已知品种SSR指纹图谱库构建
|
摘要
用24对引物构建上海地区53份水稻品种的DNA指纹图谱,为当地水稻新品种保护、遗传资源评价及亲缘关系分析提供理论依据和技术支持。结果显示,试验中共检测出109条多态性片段,变幅2~9条,平均每对引物4.5417条多态性片段,有效等位基因数为70.8187,平均每个标记2.9508个;Shannon多样性指数(Ⅰ)平均值为1.1296,变幅0.4949~1.8402;多态性信息含量(PIC)平均值为0.5415,变幅0.2656~0.8001。用24个标记建立53份材料的DNA指纹图谱,这些字符串就构成了这53份材料的"身份证号码",本试验中,各材料的分子身份证号码是唯一的;聚类分析表明,在遗传相似系数0.21处可以将53份材料分为2个类群,分别为粳稻组和籼稻组,但是组内遗传距离较近。由此可见,上海地区水稻品种的遗传多样性相对狭窄。
The DNA fingerprints can provide a theoretical foundation and technical support for the variety'sprotection, evaluation of genetic diversity and relationships analysis. In this study, the DNA fingerprints of 53 rice varieties in Shanghai were established by 24 pairs of SSR primers. A total of 109 alleles were detectedfrom tested rice varieties, ranged from 2 to 9. The average number of alleles per locus was 4.5471. The effectivealleles was 70.8187, 2.9508 for each primer pair on average. Shannon's information index(Ⅰ) ranged from0.4949 to 1.8402 with average 1.1296. And its average PIC index was 0.5415, with a range of 0.2656-0.8001.24 pairs of SSR were used to establish the DNA fingerprints, and the strings constituted the‘ID number'. Inthis experiment, the ID number was unique for every cultivar. The cluster analysis showed that the testedcultivars could be classified into 2 groups at the level of genetic similarities coefficient 0.21, which wereJaponica group and Indica group. The results indicated that narrow genetic base existed among the detectedcultivars in Shanghai.
The DNA fingerprints can provide a theoretical foundation and technical support for the variety'sprotection, evaluation of genetic diversity and relationships analysis. In this study, the DNA fingerprints of 53 rice varieties in Shanghai were established by 24 pairs of SSR primers. A total of 109 alleles were detectedfrom tested rice varieties, ranged from 2 to 9. The average number of alleles per locus was 4.5471. The effectivealleles was 70.8187, 2.9508 for each primer pair on average. Shannon's information index(Ⅰ) ranged from0.4949 to 1.8402 with average 1.1296. And its average PIC index was 0.5415, with a range of 0.2656-0.8001.24 pairs of SSR were used to establish the DNA fingerprints, and the strings constituted the‘ID number'. Inthis experiment, the ID number was unique for every cultivar. The cluster analysis showed that the testedcultivars could be classified into 2 groups at the level of genetic similarities coefficient 0.21, which wereJaponica group and Indica group. The results indicated that narrow genetic base existed among the detectedcultivars in Shanghai.
引文
[1]Bredemeijer G M M,Cook R J,Ganal M W,et al.Construction and testing of microsatellite database containing more than 500 tomato varieties[J].Theoretical and Applied Genetics,2002(105):1019-1026.
[2]Rder M S,Wendehake K,Korzun V,et al.Construction and analysis of a microsatellite-based database of European wheat varieties[J].Theoretical and Applied Genetics,2002(106):67-73.
[3]王凤格,赵久然,郭景伦,等.中国玉米新品种DNA指纹库建立系列研究I.玉米品种纯度及真伪鉴定中SSR技术标准实验体系的建立[J].玉米科学,2003,11(1):3-6.
[4]赵久然,王凤格,郭景伦,等.中国玉米新品种DNA指纹库建立系列研究Ⅱ.适于玉米自交系和杂交种指纹图谱绘制的SSR核心引物的确定[J].玉米科学,2003,11(2):3-5.
[5]王凤格,赵久然,佘花娣,等.中国玉米新品种DNA指纹库建立系列研究Ⅲ.多重PCR技术在玉米SSR引物扩增中的应用[J].玉米科学,2003,11(4):3-6.
[6]张安宁,王加红,余新桥,等.SSR标记在杂交稻纯度鉴定中的应用[J].上海农业学报,2013,6(29):53-55.
[7]赵虹,徐国华,廖芳丽.SSR分子标记技术在杂交水稻种子纯度鉴定中的作用[J].湖北农业科学,2011,50(17):3490-3491.
[8]詹庆才.利用微卫星DNA标记进行杂交水稻种子纯度鉴定的研究[J].杂交水稻,2002,17(5):46-50.
[9]肖小余,王玉平,张建勇,等.四川省主要杂交稻亲本的SSR多态性分析和指纹图谱的构建与应用硼[J].中国水稻科学,2006,20(1):1-7.
[10]庄杰云,施勇峰,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[J].中国水稻科学,2006,19(50):460-468.
[11]程本义,施勇烽,沈伟峰,等.南方稻区国家水稻区域试验品种的微卫星标记分析[J].中国水稻科学,2007,21(1):7-12.
[12]程本义,吴伟,夏俊辉,等.浙江省水稻品种DNA指纹数据库的初步构建及其应用[J].浙江农业学报,2009,21(6):555-560.
[13]程本义,夏俊辉,龚俊义,等.SSR荧光标记毛细管电泳检测法在水稻DNA指纹鉴定中的应用[J].中国水稻科学,2011,25(6):672-676.
[14]吴毅歆,刘春明,毛自朝,等.云南省134个水稻新品种DNA指纹图谱构建和遗传多样性分析[J].分子植物育种:网络版,2012(10):1287-1296.
[15]王如琼,余显权,姜敬伟,等.贵州省2011年水稻区试品种DNA指纹图谱的构建及遗传多样性分析[J].种子,2012,31(4):35-39.
[16]陈英华,侯昱铭,李宏宇,等.东北地区水稻区试新品种的DNA指纹图谱构建及遗传多样性分析[J].种子,2009,28(3):28-35.
[17]肖子发,朱克永,刘之熙,等.利用SSR标记构建湖南省审杂交水稻品种DNA指纹图谱[J].杂交水稻,2011,26(3):51-56.
[18]朱珊,黄仁良,孙娜,等.江西省2009年水稻区试品种的DNA指纹图谱构建及遗传多样性分析[J].江西农业学报,2010,22(9):20-23,26.
[19]马红勃,许旭明,韦新宇,等.基于SSR标记的福建省若干水稻品种DNA指纹图谱构建及遗传多样性分析[J].福建农业学报,2010,25(1):33-38.
[20]中华人民共和国农业部.水稻品种鉴定DNA指纹方法[S].
[21]端木银熙,孙菊英,钟卫国,等.优质高产多抗水稻新品种——常农粳3号[J].农业科技通讯,2003(1):36-37.
[22]罗治靖,沈卫平,陈明姣,等.淡黄叶优质粳稻不育系金汇A的选育[J].杂交水稻,2013,3(28):12-14.
[23]张金渝,张建华,杨晓洪,等.玉米DUS测试标准品种的SSR分子指纹图谱的构建[J].玉米科学,2006,14(4):47-52.
[24]赖运平,张浙峰,王丽容,等.利用SSR标记筛选DUS测试中甘蓝型油菜近似品种[J].分子植物育种,2013,11(2):174-184.
[25]马琳,余显权,赵福胜.贵州地方水稻品种“禾”的SSR指纹图谱构建[J].西南农业学报,2010,23(1):5-10.
[26]International Rice Genome Sequencing Project.The map-based sequence of the rice genome[J].Nature,2005,7052(436):793-800.
[27]Zeng Y,Yang S,Cui H,et al.QTLs of Cold Tolerance-Related Traits at the Booting Stage for NIL-RILs in Rice Revealed by SSR[J].Genes&Genomics,2009,2(31):143-154.
[28]Marathi B,Guleria S,Mohapatra T,et al.QTL analysis of novel genomic regions associated with yield and yield related traits in new plant type based recombinant inbred lines of rice(Oryza sativa L.)[J].BMC Plant Biology,2012,doi:10.1186/1471-2229-12-137.
[29]Hesham A,Agrama,Mcclung,et al.Using minimum DNA marker loci for accurate population classification in rice(Oryza sativa L.)[J].Mol Breeding,2012,2(29):413-425.
[2]Rder M S,Wendehake K,Korzun V,et al.Construction and analysis of a microsatellite-based database of European wheat varieties[J].Theoretical and Applied Genetics,2002(106):67-73.
[3]王凤格,赵久然,郭景伦,等.中国玉米新品种DNA指纹库建立系列研究I.玉米品种纯度及真伪鉴定中SSR技术标准实验体系的建立[J].玉米科学,2003,11(1):3-6.
[4]赵久然,王凤格,郭景伦,等.中国玉米新品种DNA指纹库建立系列研究Ⅱ.适于玉米自交系和杂交种指纹图谱绘制的SSR核心引物的确定[J].玉米科学,2003,11(2):3-5.
[5]王凤格,赵久然,佘花娣,等.中国玉米新品种DNA指纹库建立系列研究Ⅲ.多重PCR技术在玉米SSR引物扩增中的应用[J].玉米科学,2003,11(4):3-6.
[6]张安宁,王加红,余新桥,等.SSR标记在杂交稻纯度鉴定中的应用[J].上海农业学报,2013,6(29):53-55.
[7]赵虹,徐国华,廖芳丽.SSR分子标记技术在杂交水稻种子纯度鉴定中的作用[J].湖北农业科学,2011,50(17):3490-3491.
[8]詹庆才.利用微卫星DNA标记进行杂交水稻种子纯度鉴定的研究[J].杂交水稻,2002,17(5):46-50.
[9]肖小余,王玉平,张建勇,等.四川省主要杂交稻亲本的SSR多态性分析和指纹图谱的构建与应用硼[J].中国水稻科学,2006,20(1):1-7.
[10]庄杰云,施勇峰,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[J].中国水稻科学,2006,19(50):460-468.
[11]程本义,施勇烽,沈伟峰,等.南方稻区国家水稻区域试验品种的微卫星标记分析[J].中国水稻科学,2007,21(1):7-12.
[12]程本义,吴伟,夏俊辉,等.浙江省水稻品种DNA指纹数据库的初步构建及其应用[J].浙江农业学报,2009,21(6):555-560.
[13]程本义,夏俊辉,龚俊义,等.SSR荧光标记毛细管电泳检测法在水稻DNA指纹鉴定中的应用[J].中国水稻科学,2011,25(6):672-676.
[14]吴毅歆,刘春明,毛自朝,等.云南省134个水稻新品种DNA指纹图谱构建和遗传多样性分析[J].分子植物育种:网络版,2012(10):1287-1296.
[15]王如琼,余显权,姜敬伟,等.贵州省2011年水稻区试品种DNA指纹图谱的构建及遗传多样性分析[J].种子,2012,31(4):35-39.
[16]陈英华,侯昱铭,李宏宇,等.东北地区水稻区试新品种的DNA指纹图谱构建及遗传多样性分析[J].种子,2009,28(3):28-35.
[17]肖子发,朱克永,刘之熙,等.利用SSR标记构建湖南省审杂交水稻品种DNA指纹图谱[J].杂交水稻,2011,26(3):51-56.
[18]朱珊,黄仁良,孙娜,等.江西省2009年水稻区试品种的DNA指纹图谱构建及遗传多样性分析[J].江西农业学报,2010,22(9):20-23,26.
[19]马红勃,许旭明,韦新宇,等.基于SSR标记的福建省若干水稻品种DNA指纹图谱构建及遗传多样性分析[J].福建农业学报,2010,25(1):33-38.
[20]中华人民共和国农业部.水稻品种鉴定DNA指纹方法[S].
[21]端木银熙,孙菊英,钟卫国,等.优质高产多抗水稻新品种——常农粳3号[J].农业科技通讯,2003(1):36-37.
[22]罗治靖,沈卫平,陈明姣,等.淡黄叶优质粳稻不育系金汇A的选育[J].杂交水稻,2013,3(28):12-14.
[23]张金渝,张建华,杨晓洪,等.玉米DUS测试标准品种的SSR分子指纹图谱的构建[J].玉米科学,2006,14(4):47-52.
[24]赖运平,张浙峰,王丽容,等.利用SSR标记筛选DUS测试中甘蓝型油菜近似品种[J].分子植物育种,2013,11(2):174-184.
[25]马琳,余显权,赵福胜.贵州地方水稻品种“禾”的SSR指纹图谱构建[J].西南农业学报,2010,23(1):5-10.
[26]International Rice Genome Sequencing Project.The map-based sequence of the rice genome[J].Nature,2005,7052(436):793-800.
[27]Zeng Y,Yang S,Cui H,et al.QTLs of Cold Tolerance-Related Traits at the Booting Stage for NIL-RILs in Rice Revealed by SSR[J].Genes&Genomics,2009,2(31):143-154.
[28]Marathi B,Guleria S,Mohapatra T,et al.QTL analysis of novel genomic regions associated with yield and yield related traits in new plant type based recombinant inbred lines of rice(Oryza sativa L.)[J].BMC Plant Biology,2012,doi:10.1186/1471-2229-12-137.
[29]Hesham A,Agrama,Mcclung,et al.Using minimum DNA marker loci for accurate population classification in rice(Oryza sativa L.)[J].Mol Breeding,2012,2(29):413-425.
目录