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水稻抽穗期单核苷酸多态性基因分型检测方法的开发

Development of SNP genotyping assays for heading date in rice.

作者信息

Kitazawa Noriyuki, Shomura Ayahiko, Mizubayashi Tatsumi, Ando Tsuyu, Hayashi Nagao, Yabe Shiori, Matsubara Kazuki, Ebana Kaworu, Yamanouchi Utako, Fukuoka Shuichi

机构信息

Institute of Crop Science, National Agriculture and Food Research Organization (NARO), 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan.

Institute of Agrobiological Sciences, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan.

出版信息

Breed Sci. 2024 Jun;74(3):274-284. doi: 10.1270/jsbbs.23093. Epub 2024 Jun 25.

Abstract

Heading date (HD) is a crucial agronomic trait, controlled by multiple loci, that conditions a range of geographical and seasonal adaptations in rice ( L.). Therefore, information on the HD genotypes of cross parents is essential in marker-assisted breeding programs. Here, we used the Fluidigm 96-plex SNP genotyping platform to develop genotyping assays to determine alleles at 41 HD loci (29 previously characterized genes and 12 quantitative trait loci [QTLs], including a newly detected QTL). The genotyping assays discriminated a total of 144 alleles (defined on the basis of the literature and publicly available databases) and QTLs. Genotyping of 377 cultivars revealed 3.5 alleles per locus on average, a higher diversity of , , , and than that of the other loci, and the predominance of the reference ('Nipponbare') genotype at 30 of the 41 loci. HD prediction models using the data from 200 cultivars showed good correlation ( > 0.69,  < 0.001) when tested with 22 cultivars not included in the prediction models. Thus, the developed assays provide genotype information on HD and will enable cost-effective breeding.

摘要

抽穗期(HD)是一个关键的农艺性状,受多个基因座控制,它决定了水稻(Oryza sativa L.)在一系列地理和季节条件下的适应性。因此,杂交亲本的HD基因型信息在标记辅助育种计划中至关重要。在这里,我们使用Fluidigm 96重SNP基因分型平台开发基因分型检测方法,以确定41个HD基因座(29个先前已鉴定的基因和12个数量性状基因座[QTL],包括一个新检测到的QTL)的等位基因。该基因分型检测方法共区分出144个等位基因(根据文献和公开数据库定义)和QTL。对377个品种的基因分型显示,每个基因座平均有3.5个等位基因,其中HD1、HD2、HD3和HD4的多样性高于其他基因座,并且在41个基因座中的30个基因座上,参考基因型(“日本晴”)占主导地位。使用200个品种的数据建立的HD预测模型,在对预测模型中未包含的22个品种进行测试时显示出良好的相关性(r>0.69,P<0.001)。因此,所开发的检测方法提供了关于HD的基因型信息,并将实现经济高效的育种。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1a/11561416/95920f369db4/74_274-g001.jpg

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