Genome-wide association study and high-quality gene mining related to soybean protein and fat

Abstract

Background Soybean is one of the most important oil crops in the world, and its protein and fat are the primary sources of edible oil and vegetable protein. The effective components in soybean protein and fat have positive effects on improving human immunity, anti-tumor, and regulating blood lipids and metabolism. Therefore, increasing the contents of protein and fat in soybeans is essential for improving the quality of soybeans. Results This study selected 292 soybean lines from different regions as experimental materials, based on SLAF-seq sequencing technology, and performed genome-wide association study (GWAS) on the phenotype data from 2019–2021 Planted at the experimental base of Jilin Agricultural University, such as the contents of protein and fat of soybeans. Through the GLM model and MLM model, four SNP sites (Gm09_39012959, Gm12_35492373, Gm16_9297124, and Gm20_24678362) that were significantly related to soybean fat content were associated for three consecutive years, and two SNP sites (Gm09_39012959 and Gm20_24678362) that were significantly related to soybean protein content were associated. By the annotation and enrichment of genes within the 100 Kb region of SNP loci flanking, two genes (Glyma.09G158100 and Glyma.09G158200) related to soybean protein synthesis and one gene (Glyma.12G180200) related to lipid metabolism were selected. By the preliminary verification of expression levels of genes with qPCR, it is found that during the periods of R6 and R7 of the accumulation of soybean protein and fat, Glyma.09G158100 and Glyma.09G158200 are positive regulatory genes that promote protein synthesis and accumulation, while Glyma.12G180200 is the negative regulatory gene that inhibits fat accumulation. Conclusions These results lay the basis for further verifying the gene function and studying the molecular mechanisms regulating the accumulation of protein and fat in soybean seeds.

Genome-Wide Association Analysis-Based Mining of Quality Genes Related to Linoleic and Linolenic Acids in Soybean

“…The candidate genes were scanned within the 100 Kb [34][35][36] region, upstream and downstream of the significant SNP sites obtained by repeated mapping detection for three consecutive years, and the COGs (http://clovr.org/docs/clusters-of-orthologous-groups-cogs/, accessed on 25 August 2023) were compared; GO (http://geneontology.org/, accessed on 25 August 2023); KEGG (https://www.genome.jp/kegg/, accessed on 25 August 2023); Swissprot (http://www.uniprot.org/, accessed on 25 August 2023); Pfam (https: //www.ebi.ac.uk/interpro/, accessed on 25 August 2023); eggNOG (http://eggnog5.embl. de/#/app/home, accessed on 25 August 2023) with six databases to functionally annotate the obtained candidate genes, and g:Profiler (https://biit.cs.ut.ee/gprofiler/gost, accessed on 27 August 2023) was used for enrichment analysis, with the g:SCS threshold statistical test; the significance threshold was set to 0.05; screening and prediction may be related to soybean linoleic acid and linolenic acid content candidate genes.…”