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利用高密度基因分型测序方法评估欧洲小麦品种和优良育成系的遗传结构。

Evaluation of genetic structure in European wheat cultivars and advanced breeding lines using high-density genotyping-by-sequencing approach.

机构信息

Rzeszow University of Technology, Powstańców Warszawy 12, 35-959, Rzeszów, Poland.

Institute of Plant Genetics, Polish Academy of Science, Strzeszyńska 34, 60-479, Poznań, Poland.

出版信息

BMC Genomics. 2021 Jan 28;22(1):81. doi: 10.1186/s12864-020-07351-x.

DOI:10.1186/s12864-020-07351-x
PMID:33509072
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7842024/
Abstract

BACKGROUND

The genetic diversity and gene pool characteristics must be clarified for efficient genome-wide association studies, genomic selection, and hybrid breeding. The aim of this study was to evaluate the genetic structure of 509 wheat accessions representing registered varieties and advanced breeding lines via the high-density genotyping-by-sequencing approach.

RESULTS

More than 30% of 13,499 SNP markers representing 2162 clusters were mapped to genes, whereas 22.50% of 26,369 silicoDArT markers overlapped with coding sequences and were linked in 3527 blocks. Regarding hexaploidy, perfect sequence matches following BLAST searches were not sufficient for the unequivocal mapping to unique loci. Moreover, allelic variations in homeologous loci interfered with heterozygosity calculations for some markers. Analyses of the major genetic changes over the last 27 years revealed the selection pressure on orthologs of the gibberellin biosynthesis-related GA2 gene and the senescence-associated SAG12 gene. A core collection representing the wheat population was generated for preserving germplasm and optimizing breeding programs.

CONCLUSIONS

Our results confirmed considerable differences among wheat subgenomes A, B and D, with D characterized by the lowest diversity but the highest LD. They revealed genomic regions that have been targeted by breeding.

摘要

背景

为了有效地进行全基因组关联研究、基因组选择和杂交育种，必须阐明遗传多样性和基因库特征。本研究旨在通过高通量基因分型测序方法评估 509 个小麦品种代表的注册品种和先进的育种系的遗传结构。

结果

13499 个 SNP 标记中的 30%以上代表 2162 个聚类，被映射到基因上，而 26369 个虚拟 DArT 标记中的 22.50%与编码序列重叠，并在 3527 个块中连接。对于六倍体而言，BLAST 搜索后的完美序列匹配不足以将其明确映射到唯一的基因座。此外，同源基因座中的等位基因变异干扰了一些标记的杂合性计算。对过去 27 年的主要遗传变化的分析表明，赤霉素生物合成相关 GA2 基因和衰老相关 SAG12 基因的同源物受到了选择压力。为了保存种质资源和优化育种计划，生成了一个代表小麦群体的核心收集。

结论

我们的结果证实了小麦亚基因组 A、B 和 D 之间存在相当大的差异，D 亚基因组的多样性最低，但 LD 最高。它们揭示了已经成为育种目标的基因组区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/8327f23fc4aa/12864_2020_7351_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/dae17d608a9c/12864_2020_7351_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/27cd12ed323d/12864_2020_7351_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/2513148947eb/12864_2020_7351_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/4cfb1f05a175/12864_2020_7351_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/e34d0a23163b/12864_2020_7351_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/d1d8ead45a57/12864_2020_7351_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/6c635904f4e5/12864_2020_7351_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/8327f23fc4aa/12864_2020_7351_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/dae17d608a9c/12864_2020_7351_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/27cd12ed323d/12864_2020_7351_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/2513148947eb/12864_2020_7351_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/4cfb1f05a175/12864_2020_7351_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/e34d0a23163b/12864_2020_7351_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/d1d8ead45a57/12864_2020_7351_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/6c635904f4e5/12864_2020_7351_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2106/7842024/8327f23fc4aa/12864_2020_7351_Fig8_HTML.jpg

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