The genetic architecture of water-soluble protein content and its genetic relationship to total protein content in soybean

Abstract

Water-soluble protein content (WSPC) is a critical factor in both soybean protein quality and functionality. However, the underlying genetic determinants are unclear. Here, we used 219 soybean accessions and 152 recombinant inbred lines genotyped with high-density markers and phenotyped in multi-environments to dissect the genetic architectures of WSPC and protein content (PC) using single- and multi-locus genome-wide association studies. In the result, a total of 32 significant loci, including 10 novel loci, significantly associated with WSPC and PC across multi-environments were identified, which were subsequently validated by linkage mapping. Among these loci, only four exhibited pleiotropic effects for PC and WSPC, explaining the low correlation coefficient between the two traits. The largest-effect WSPC-specific loci, GqWSPC8, was stably identified across all six environments and tagged to a linkage disequilibrium block comprising two promising candidate genes AAP8 and 2 S albumin, which might contribute to the high level of WSPC in some soybean varieties. In addition, two genes, Glyma.13G123500 and Glyma.13G194400 with relatively high expression levels at seed development stage compared with other tissues were regarded as promising candidates associated with the PC and WSPC, respectively. Our results provide new insights into the genetic basis of WSPC affecting soybean protein quality and yield.

Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea

“…Orthologous genes for the ones harbouring the peak markers of the metaQTL were identified and QTL within 50 kb around these genes were searched. This further reinforced the interest of the SW QTL mQTL2.1 and mQTL4.1, of the TSW QTL mQTL6.2 and mQTL2.2 and the SPC QTL mQTL4.3 and mQTL4.5 which corresponded to QTL of the same traits in soybean 34 , 36 – 40 (Supplementary Table S5 ).…”

Genome-Wide Detection of Major and Epistatic Effect QTLs for Seed Protein and Oil Content in Soybean Under Multiple Environments Using High-Density Bin Map

“…qPro-9-2 is reported as being associated with nearest markers ofSat_293 and BARC-010523-00698 covering large physical interval of 2,967,367–46,053,138 [ 14 ]. qPro-10-1 has been detected as linked to the nearest marker Satt173 in the similar physical distance [ 14 , 65 ]. qPro-13-2 and qPro-18-1 were mapped in the same region as previous studies [ 39 , 40 , 65 ].…”

Artificial selection on GmOLEO1 contributes to the increase in seed oil during soybean domestication

“…The association panel for GWAS consisted of a diverse collection of 219 soybean accessions (including 195 landraces and 24 elite varieties) originating from 26 provinces across six different agroecological regions in China, ranging from latitudes 53 to 24°N and longitudes 134 to 97°E [49]. Field experiments were performed in the 2009, 2011, 2012, 2013 and 2014 growing seasons at four different geographic locations as previously described [50]. Briefly, soybean plants were examined under field conditions at the following experimental stations: Jiangpu Experimental Station of Nanjing Agricultural University (32.1°N 118.4°E), Nanjing, in 2009 (designated as Environment 1, E1); Maozhuang Experimental Station (34.8°N 113.6°E) of Henan Agricultural University Zhengzhou, in 2009 (E2) and 2011 (E3); the Fangcheng Experimental Farm (33.2°N 112.9°E) of Henan Agricultural University in 2012 (E4), and Yuanyang Experimental Station of Henan Academy of Agricultural Sciences, Zhengzhou, in 2013 (E5) and in 2014 (E6).…”