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基于简化基因组测序的亚洲和欧洲普通小麦种质的遗传多样性与群体结构

Genetic Diversity and Population Structure of Asian and European Common Wheat Accessions Based on Genotyping-By-Sequencing.

作者信息

Yang Xiu, Tan Binwen, Liu Haijiao, Zhu Wei, Xu Lili, Wang Yi, Fan Xing, Sha Lina, Zhang Haiqin, Zeng Jian, Wu Dandan, Jiang Yunfeng, Hu Xigui, Chen Guoyue, Zhou Yonghong, Kang Houyang

机构信息

State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China.

Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China.

出版信息

Front Genet. 2020 Sep 25;11:580782. doi: 10.3389/fgene.2020.580782. eCollection 2020.

DOI:10.3389/fgene.2020.580782
PMID:33101397
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7545058/
Abstract

Obtaining information on the genetic diversity and population structure of germplasm facilitates its use in wheat breeding programs. Recently, with the development of next-generation sequencing technology, genotyping-by-sequencing (GBS) has been used as a high-throughput and cost-effective molecular tool for examination of the genetic diversity of wheat breeding lines. In this study, GBS was used to characterize a population of 180 accessions of common wheat originating from Asia and Europe between the latitudes 30° and 45°N. In total, 24,767 high-quality single-nucleotide polymorphism (SNP) markers were used for analysis of genetic diversity and population structure. The B genome contained the highest number of SNPs, followed by the A and D genomes. The polymorphism information content was in the range of 0.1 to 0.4, with a mean of 0.26. The distribution of SNPs markers on the 21 chromosomes ranged from 243 on chromosome 4D to 2,337 on chromosome 3B. Structure and cluster analyses divided the panel of accessions into two subgroups (G1 and G2). G1 principally consisted of European and partial Asian accessions, and G2 comprised mainly accessions from the Middle East and partial Asia. Molecular analysis of variance showed that the genetic variation was greater within groups (99%) than between groups (1%). Comparison of the two subgroups indicated that G1 and G2 contained a high level of genetic diversity. The genetic diversity of G2 was slightly higher as indicated by the observed heterozygosity ( ) = 0.23, and unbiased diversity index () = 0.34. The present results will not only help breeders to understand the genetic diversity of wheat germplasm on the Eurasian continent between the latitudes of 30° and 45°N, but also provide valuable information for wheat genetic improvement through introgression of novel genetic variation in this region.

摘要

获取种质的遗传多样性和群体结构信息有助于其在小麦育种计划中的应用。近年来,随着下一代测序技术的发展,简化基因组测序(GBS)已被用作一种高通量且经济高效的分子工具,用于检测小麦育种品系的遗传多样性。在本研究中,GBS被用于对180份源自亚洲和欧洲、北纬30°至45°之间的普通小麦材料进行特征分析。总共使用了24767个高质量单核苷酸多态性(SNP)标记来分析遗传多样性和群体结构。B基因组包含的SNP数量最多,其次是A和D基因组。多态性信息含量在0.1至0.4之间,平均值为0.26。SNP标记在21条染色体上的分布范围从4D染色体上的243个到3B染色体上的2337个。结构和聚类分析将材料分为两个亚组(G1和G2)。G1主要由欧洲和部分亚洲材料组成,G2主要包括来自中东和部分亚洲的材料。分子方差分析表明,组内遗传变异(99%)大于组间遗传变异(1%)。两个亚组的比较表明,G1和G2都具有高水平的遗传多样性。观察杂合度()= 0.23和无偏多样性指数()= 0.34表明,G2的遗传多样性略高。目前的结果不仅将帮助育种者了解北纬30°至45°之间欧亚大陆上小麦种质的遗传多样性,还将为通过该地区新遗传变异的渐渗进行小麦遗传改良提供有价值的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/b512c07295e1/fgene-11-580782-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/b7aeeeb9cb82/fgene-11-580782-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/778f99741cf0/fgene-11-580782-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/faa35987de90/fgene-11-580782-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/a440be7b37db/fgene-11-580782-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/a51ba3694cea/fgene-11-580782-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/3c55e021fc8a/fgene-11-580782-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/4c076be7aa4c/fgene-11-580782-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/c4f782ca02ba/fgene-11-580782-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/2e630fd833f7/fgene-11-580782-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/b512c07295e1/fgene-11-580782-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/b7aeeeb9cb82/fgene-11-580782-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/778f99741cf0/fgene-11-580782-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/faa35987de90/fgene-11-580782-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/a440be7b37db/fgene-11-580782-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/a51ba3694cea/fgene-11-580782-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/3c55e021fc8a/fgene-11-580782-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/4c076be7aa4c/fgene-11-580782-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/396a/7545058/c4f782ca02ba/fgene-11-580782-g008.jpg
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