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Genome-Wide Association Studies Prioritize Genes Controlling Seed Size and Reproductive Period Length in Soybean

文献类型： 外文期刊

作者： Wang, Le 1 ; Niu, Fu'an 4 ; Wang, Jinshe 5 ; Zhang, Hengyou 1 ; Zhang, Dan 3 ; Hu, Zhenbin 2 ;

作者机构： 1.Chinese Acad Sci, Northeast Inst Geog & Agroecol, State Key Lab Black Soils Conservat & Utilizat, Key Lab Soybean Mol Design Breeding, Harbin 150081, Peoples R China

2.US Dept Agr, Agr Res Serv, Anim Genom & Improvement Lab, Beltsville, MD 20705 USA

3.Henan Agr Univ, Coll Agron, Collaborat Innovat Ctr Henan Grain Crops, Zhengzhou 450002, Peoples R China

4.Shanghai Acad Agr Sci, Inst Crop Breeding & Cultivat, Shanghai 201403, Peoples R China

5.Henan Acad Agr Sci, Inst Crop Mol Breeding, Natl Innovat Ctr Biobreeding Ind, Zhengzhou 450002, Peoples R China

关键词： GWAS; soybean; Glycine max; 100-seed weight; reproductive period length; Arabidopsis

期刊名称：PLANTS-BASEL （ 影响因子：4.5； 五年影响因子：4.8 ）

ISSN： 2223-7747

年卷期： 2024 年 13 卷 5 期

页码：

收录情况： SCI

摘要： Hundred-seed weight (HSW) and reproductive period length (RPL) are two major agronomic traits critical for soybean production and adaptation. However, both traits are quantitatively controlled by multiple genes that have yet to be comprehensively elucidated due to the lack of major genes; thereby, the genetic basis is largely unknown. In the present study, we conducted comprehensive genome-wide association analyses (GWAS) of HSW and RPL with multiple sets of accessions that were phenotyped across different environments. The large-scale analysis led to the identification of sixty-one and seventy-four significant QTLs for HSW and RPL, respectively. An ortholog-based search analysis prioritized the most promising candidate genes for the QTLs, including nine genes (TTG2, BZR1, BRI1, ANT, KLU, EOD1/BB, GPA1, ABA2, and ABI5) for HSW QTLs and nine genes (such as AGL8, AGL9, TOC1, and COL4) and six known soybean flowering time genes (E2, E3, E4, Tof11, Tof12, and FT2b) for RPL QTLs. We also demonstrated that some QTLs were targeted during domestication to drive the artificial selection of both traits towards human-favored traits. Local adaptation likely contributes to the increased genomic diversity of the QTLs underlying RPL. The results provide additional insight into the genetic basis of HSW and RPL and prioritize a valuable resource of candidate genes that merits further investigation to reveal the complex molecular mechanism and facilitate soybean improvement.

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