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油菜种子含油量GWAS分析及位点整合系统构建
引用本文:魏大勇,崔艺馨,梅家琴,汤青林,李加纳,钱伟.油菜种子含油量GWAS分析及位点整合系统构建[J].作物学报,2018,44(9):1311-1319.
作者姓名:魏大勇  崔艺馨  梅家琴  汤青林  李加纳  钱伟
作者单位:西南大学园艺园林学院;南方山地园艺学教育部重点实验室;西南大学农学与生物科技学院;西南大学现代农业科学研究院
基金项目:This study was supported by the Doctoral Fund of Southwest University(SWU118010);the National Natural Science Foundation of China(31601333);the National Basic Research Program of China(973 Program 2015CB150201);the Fundamental Research Funds for Central Universities(XDJK2017B036)
摘    要:含油量是油菜最重要的性状之一,目前已有较多的油菜种子含油量定位研究,然而各研究系统相对独立,群体与标记的差别使得难以比较不同研究结果。本研究连续4年种植了一个含308份材料的油菜自然群体,结合60K SNP芯片数据对种子含油量进行了全基因组关联分析(GWAS),并将所鉴定的显著位点与早前2个自然群体及10个分离群体鉴定到的位点进行全基因组比较与整合。结果显示,通过GWAS共检测到8个与种子含油量显著关联的位点,单个位点解释的表型变异度为3.22%~5.13%;结合其他12个群体的定位结果,共获得193个油菜含油量整合位点,分布于油菜的所有19条染色体,A亚基因组平均每条染色体有13个位点,显著高于C亚基因组(7个)。对不同群体鉴定结果的比较发现,7个整合区间能在至少3个群体中被检测到,均位于A亚基因组染色体(A01、A02、A03、A06、A08、A09和A10)上,其中有3个与C亚基因组上的区间存在同源性,在这3个区间中共鉴定到26个已知的油脂代谢相关基因。本研究将193个位点锚定到法国公布的甘蓝型油菜参考基因组,构建了一个可视的油菜种子含油量位点全基因组整合系统,可为油菜种子含油量重要位点的确定提供帮助,并为制定提高油菜种子含油量的育种方案提供参考。

收稿时间:2018-01-30

Genome-wide Association Study on Seed Oil Content in Rapeseed and Construction of Integration System for Oil Content Loci
Da-Yong WEI,Yi-Xin CUI,Jia-Qin MEI,Qing-Lin TANG,Jia-Na LI,Wei QIAN.Genome-wide Association Study on Seed Oil Content in Rapeseed and Construction of Integration System for Oil Content Loci[J].Acta Agronomica Sinica,2018,44(9):1311-1319.
Authors:Da-Yong WEI  Yi-Xin CUI  Jia-Qin MEI  Qing-Lin TANG  Jia-Na LI  Wei QIAN
Institution:1.College of Horticulture and Landscape Architecture, Southwest University, Chongqing 400715, China;2.Key Laboratory of Horticulture Science for Southern Mountainous Regions, Ministry of Education, Chongqing 400715, China;3.College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China;4.Academy of Agricultural Sciences, Southwest University, Chongqing 400715, China
Abstract:Genetic loci for oil content, one of the most important traits of rapeseed (Brassica napus L.), have been widely studied, however, comparisons were difficult to be carried out among studies due to different mapping populations and molecular marker systems. In the present study, a 60K Brassica SNP array was applied in the genome-wide association study (GWAS) using a natural rapeseed population which was comprised of 308 accessions and grown for four consecutive years to identify loci for seed oil content. An integration system was built by anchoring the present loci and previous loci that identified onto the rapeseed genome in other studies using ten segregation populations and two natural populations. A total of eight SNPs significantly associated with seed oil contents of rapeseed were detected in our study, explaining 3.22%-5.13% of the phenotypic variance each SNP. Combining the data from other 12 populations, 193 integrated loci were identified, spreading on all 19 chromosomes of B. napus with more loci distributed on A subgenome (13 loci/chromosome) than C subgenome (seven loci/chromosome). Seven integrated intervals from A subgenome (chromosome A01, A02, A03, A06, A08, A09, and A10) were identified in at least three populations, of which three were homologous to intervals on C subgenome, with 26 known genes associated with seed oil metabolism. The 193 loci were anchored to the reference genome of B. napus var. Darmor-Bzh, resulting in a visualized genome-wide integrated system for seed oil content loci. This study is helpful to determine the important seed oil content loci and to make the optimal breeding strategy to increase oil content in rapeseed.
Keywords:Brassica napus  seed oil content  genome-wide association study  QTL  integrated system  
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