Literature DB >> 35588015

Identification of closely associated SNPs and candidate genes with seed size and shape via deep re-sequencing GWAS in soybean.

Zhenqi Shao1, Jiabiao Shao1, Xiaobo Huo1, Wenlong Li1, Youbin Kong1, Hui Du1, Xihuan Li2, Caiying Zhang3.   

Abstract

KEY MESSAGE: A soybean natural population was genotyped by deep re-sequencing and phenotyped for six seed size- and shape-related traits under six environments to identify closely associated SNPs and candidate genes. Seed size and shape are important determining factors for soybean yield formation, while their genetic basis and molecular mechanism are still largely unknown, which seriously constrains the increasing of soybean yield at present. In view of this, a natural population was genotyped via the deep re-sequencing technique (~ 20 ×) and phenotyped for six related traits under six environments. In total, 154 SNPs were closely associated with seed length across diverse environments, and 323, 483, 565, 394 and 2038 SNPs were closely associated with seed width, seed diameter, seed circumference, seed area and ratio of length to width under multiple environments. Moreover, 98.70%, 96.28%, 48.24%, 85.13%, 97.21% and 98.58% of them were further demonstrated by the BLUP and mean values of the related traits. Furthermore, 218 genes flanking the associated SNPs on chromosomes 6 and 10 were analyzed for DNA mutations and RNA expressions through SNP alleles and transcriptome data, simultaneously. The candidate genes, Glyma.10G035200 (Sn1-specific diacylglycerol lipase), Glyma.10G035400 (transcription factor) and Glyma.10G058200 (phenylalanine ammonia-lyase), were discovered to relate with the seed size and shape for their different DNA sequences or differential RNA expressions among soybean varieties at five seed developmental stages. Thus, these closely associated SNPs and related genes provide novel insights and useful information for the seed size and shape genetic basis dissection and breeding improvement in soybean.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Year:  2022        PMID: 35588015     DOI: 10.1007/s00122-022-04116-w

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.574


  3 in total

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