Genome-wide association mapping for protein, oil and water-soluble protein contents in soybean

Zhang, Shanshan; Hao, Dejun; Zhang, Shuyu; Zhang, Dan; Wang, Hui; Du, Haiping; Kan, Guizhen; Yu, Deyue

doi:10.1007/s00438-020-01704-7

Cited by 21 publications

(26 citation statements)

References 56 publications

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“…The GWAS panel of soybean used in the current study consists of 211 diverse genotypes; which include 201 genotypes originating from 25 provinces of China that represents all three ecological habitats of China ( Zhang S. et al, 2021 ) and ten genotypes from the United States, Japan, and Brazil ( Zhang et al, 2015 ). This soybean germplasm was evaluated at three different locations in China viz., Nanjing, Nantong, and Yangzhou, for two consecutive years.…”

Section: Methodsmentioning

confidence: 99%

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Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.)

et al. 2022

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Identifying the genetic components underlying yield-related traits in soybean is crucial for improving its production and productivity. Here, 211 soybean genotypes were evaluated across six environments for four yield-related traits, including seed yield per plant (SYP), number of pods per plant number of seeds per plant and 100-seed weight (HSW). Genome-wide association study (GWAS) and genomic prediction (GP) analyses were performed using 12,617 single nucleotide polymorphism markers from NJAU 355K SoySNP Array. A total of 57 SNPs were significantly associated with four traits across six environments and a combined environment using five Genome-wide association study models. Out of these, six significant SNPs were consistently identified in more than three environments using multiple GWAS models. The genomic regions (±670 kb) flanking these six consistent SNPs were considered stable QTL regions. Gene annotation and in silico expression analysis revealed 15 putative genes underlying the stable QTLs that might regulate soybean yield. Haplotype analysis using six significant SNPs revealed various allelic combinations regulating diverse phenotypes for the studied traits. Furthermore, the GP analysis revealed that accurate breeding values for the studied soybean traits is attainable at an earlier generation. Our study paved the way for increasing soybean yield performance within a short breeding cycle.

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Section: Methodsmentioning

confidence: 99%

“…Each genotype was planted in a plot of three rows with row-length and spacing of 200 and 50 cm, respectively. Normal agronomic practices were followed for the cultivation of soybean germplasm at each location, as previously described by Zhang S. et al (2021) .…”

Section: Methodsmentioning

confidence: 99%

Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.)

et al. 2022

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“…Previous studies used a variety of populations and various mapping methods to identify 248 and 327 quantitative trait loci (QTL) for soybean seed protein and seed oil content, respectively (SoyBase, ). Genome-wide association studies (GWAS) were used to find novel loci for soybean oil and protein contents ( Li et al., 2018 ; Lee et al., 2019 ; Zhang et al., 2021 ). However, the mechanisms underlying soybean seed development and the regulation of protein and oil biosynthesis have not been comprehensively investigated.…”

Section: Introductionmentioning

confidence: 99%

Using transcriptomic and metabolomic data to investigate the molecular mechanisms that determine protein and oil contents during seed development in soybean

Wang

Zhang

et al. 2022

Front. Plant Sci.

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Soybean [Glycine max (L.) Merri.] is one of the most valuable global crops. And vegetable soybean, as a special type of soybean, provides rich nutrition in people’s life. In order to investigate the gene expression networks and molecular regulatory mechanisms that regulate soybean seed oil and protein contents during seed development, we performed transcriptomic and metabolomic analyses of soybean seeds during development in two soybean varieties that differ in protein and oil contents. We identified a total of 41,036 genes and 392 metabolites, of which 12,712 DEGs and 315 DAMs were identified. Analysis of KEGG enrichment demonstrated that DEGs were primarily enriched in phenylpropanoid biosynthesis, glycerolipid metabolism, carbon metabolism, plant hormone signal transduction, linoleic acid metabolism, and the biosynthesis of amino acids and secondary metabolites. K-means analysis divided the DEGs into 12 distinct clusters. We identified candidate gene sets that regulate the biosynthesis of protein and oil in soybean seeds, and present potential regulatory patterns that high seed-protein varieties may be more sensitive to desiccation, show earlier photomorphogenesis and delayed leaf senescence, and thus accumulate higher protein contents than high-oil varieties.

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“…Several high-throughput phenotyping approaches have been developed to bridge the genotyping and phenotyping gap for various quality traits, including protein content [ 237 , 238 , 239 ]. Advances in high-throughput non-destructive phenotyping approaches such as hyperspectral technologies, near-infrared reflectance spectroscopy, and nuclear magnetic resonance have enabled the phenotyping of various biochemical attributes in cereal and legume seeds, including protein content, with high accuracy and efficiency [ 237 , 238 , 239 , 240 , 241 ]. For example, Raman spectroscopy has been used to measure SPC in soybean [ 237 ].…”

Section: Non-destructive Phenomics Approach For Quantifying High Prot...mentioning

confidence: 99%

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and ‘Omics’ Tools

Jha

Nayyar

Parida

et al. 2022

IJMS

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Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based ‘dietary protein’ biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.

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Genome-wide association mapping for protein, oil and water-soluble protein contents in soybean

Cited by 21 publications

References 56 publications

Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.)

Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.)

Using transcriptomic and metabolomic data to investigate the molecular mechanisms that determine protein and oil contents during seed development in soybean

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and ‘Omics’ Tools

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