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在干旱环境下,国际干旱地区农业研究中心小麦的单性状和多性状基因组预测及与籽粒产量和微量营养素相关性状的全基因组关联分析。

Single- and multi-trait genomic prediction and genome-wide association analysis of grain yield and micronutrient-related traits in ICARDA wheat under drought environment.

机构信息

The International Center for Agricultural Research in the Dry Areas (ICARDA), Rabat, Morocco.

AgroBioSciences, Mohammed VI Polytechnic University (UM6P), Ben Guerir, Morocco.

出版信息

Mol Genet Genomics. 2023 Nov;298(6):1515-1526. doi: 10.1007/s00438-023-02074-6. Epub 2023 Oct 18.

DOI:10.1007/s00438-023-02074-6
PMID:37851098
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10657311/
Abstract

Globally, over 2 billion people suffer from malnutrition due to inadequate intake of micronutrients. Genomic-assisted breeding is identified as a valuable method to facilitate developing new improved plant varieties targeting grain yield and micronutrient-related traits. In this study, a genome-wide association study (GWAS) and single- and multi-trait-based genomic prediction (GP) analysis was conducted using a set of 252 elite wheat genotypes from the International Center for Agricultural Research in Dry Areas (ICARDA). The objective was to identify linked SNP markers, putative candidate genes and to evaluate the genomic estimated breeding values (GEBVs) of grain yield and micronutrient-related traits.. For this purpose, a field trial was conducted at a drought-prone station, Merchouch, Morocco for 2 consecutive years (2018 and 2019) followed by GWAS and genomic prediction analysis with 10,173 quality SNP markers. The studied genotypes exhibited a significant genotypic variation in grain yield and micronutrient-related traits. The GWAS analysis identified highly significantly associated markers and linked putative genes on chromosomes 1B and 2B for zinc (Zn) and iron (Fe) contents, respectively. The genomic predictive ability of selenium (Se) and Fe traits with the multi-trait-based GP GBLUP model was 0.161 and 0.259 improving by 6.62 and 4.44%, respectively, compared to the corresponding single-trait-based models. The identified significantly linked SNP markers, associated putative genes, and developed GP models could potentially facilitate breeding programs targeting to improve the overall genetic gain of wheat breeding for grain yield and biofortification of micronutrients via marker-assisted (MAS) and genomic selection (GS) methods.

摘要

全球范围内,超过 20 亿人因微量营养素摄入不足而遭受营养不良。基因组辅助育种被认为是一种有价值的方法,可以帮助开发针对粮食产量和与微量营养素相关的性状的新型改良植物品种。在这项研究中,利用来自国际干旱地区农业研究中心(ICARDA)的 252 个精英小麦基因型进行了全基因组关联研究(GWAS)以及基于单个性状和多个性状的基因组预测(GP)分析。目的是鉴定连锁 SNP 标记、假定候选基因,并评估粮食产量和与微量营养素相关的性状的基因组估计育种值(GEBVs)。为此,在摩洛哥的 Merchouch 干旱易发站进行了为期两年(2018 年和 2019 年)的田间试验,随后进行了 GWAS 和基因组预测分析,使用了 10,173 个质量 SNP 标记。研究的基因型在粮食产量和与微量营养素相关的性状方面表现出显著的基因型变异。GWAS 分析鉴定了与锌(Zn)和铁(Fe)含量分别位于 1B 和 2B 染色体上的高度显著关联的标记和连锁假定基因。与相应的单个性状基于模型的 GP GBLUP 相比,多性状基于模型的 GP GBLUP 对硒(Se)和 Fe 性状的基因组预测能力分别提高了 0.161 和 0.259,分别提高了 6.62%和 4.44%。鉴定的显著连锁 SNP 标记、关联的假定基因和开发的 GP 模型可能有助于通过标记辅助(MAS)和基因组选择(GS)方法进行的旨在提高小麦产量和微量营养素生物强化整体遗传增益的育种计划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/5c4bb54260ed/438_2023_2074_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/d2205ab15b60/438_2023_2074_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/e2ef00f7df18/438_2023_2074_Fig2a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/668606e96832/438_2023_2074_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/32345d55bd26/438_2023_2074_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/1fb7dfeb056b/438_2023_2074_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/5c4bb54260ed/438_2023_2074_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/d2205ab15b60/438_2023_2074_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/e2ef00f7df18/438_2023_2074_Fig2a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/668606e96832/438_2023_2074_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/32345d55bd26/438_2023_2074_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/1fb7dfeb056b/438_2023_2074_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ae/10657311/5c4bb54260ed/438_2023_2074_Fig6_HTML.jpg

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