Genome-wide association and transcriptional studies reveal novel genes for unsaturated fatty acid synthesis in a panel of soybean accessions

Multi-omics analysis reveals novel loci and a candidate regulatory gene of unsaturated fatty acids in soybean (Glycine max (L.) Merr)

BACKGROUND

Soybean is a major oil crop; the nutritional components of soybean oil are mainly controlled by unsaturated fatty acids (FA). Unsaturated FAs mainly include oleic acid (OA, 18:1), linoleic acid (LLA, 18:2), and linolenic acid (LNA, 18:3). The genetic architecture of unsaturated FAs in soybean seeds has not been fully elucidated, although many independent studies have been conducted. A 3 V multi-locus random single nucleotide polymorphism (SNP)-effect mixed linear model (3VmrMLM) was established to identify quantitative trait loci (QTLs) and QTL-by-environment interactions (QEIs) for complex traits.

RESULTS

In this study, 194 soybean accessions with 36,981 SNPs were calculated using the 3VmrMLM model. As a result, 94 quantitative trait nucleotides (QTNs) and 19 QEIs were detected using single-environment (QTN) and multi-environment (QEI) methods. Three significant QEIs, namely rs4633292, rs39216169, and rs14264702, overlapped with a significant single-environment QTN.

CONCLUSIONS

For QTNs and QEIs, further haplotype analysis of candidate genes revealed that the Glyma.03G040400 and Glyma.17G236700 genes were beneficial haplotypes that may be associated with unsaturated FAs. This result provides ideas for the identification of soybean lipid-related genes and provides insights for breeding high oil soybean varieties in the future.

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Genome-wide association and RNA-seq analyses reveal a potential gene related to linolenic acid in soybean seeds

Linolenic acid (LA) has poor oxidative stability since it is a polyunsaturated fatty acid. Soybean oil has a high LA content and thus has poor oxidative stability. To identify candidate genes that affect the linolenic acid (LA) content in soybean seeds, a genome-wide association study (GWAS) was performed with 1,060 soybean cultivars collected in China between 2019-2021 and which LA content was measured using matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS). A candidate gene, GmWRI14, encoding an APETALA2 (AP2)-type transcription factor, was detected by GWAS in cultivars from all three study years. Multiple sequence alignments showed that GmWRI14 belongs to the plant WRI1 family. The fatty acid contents of different soybean lines were evaluated in transgenic lines with a copy of GmWRI14, control lines without GmWRI14, and the gmwri14 mutant. MALDI-TOF IMS revealed that GmWRI14 transgenic soybeans had a lower LA content with a significant effect on seed size and shape, whereas gmwri14 mutants had a higher LA content. compared to control. The RNA-seq results showed that GmWRI14 suppresses GmFAD3s (GmFAD3B and GmFAD3C) and GmbZIP54 expression in soybean seeds, leading to decreased LA content. Based on the RNA-seq data, yeast one-hybrid (Y1H) and qRT-PCR were performed to confirm the transcriptional regulation of FAD3s by GmWRI14. Our results suggest that FAD3 is indirectly regulated by GmWRI14, representing a new molecular mechanism of fatty acid biosynthesis, in which GmWRI14 regulates LA content in soybean seeds.

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

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 study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Genome-wide association analysis of sucrose and alanine contents in edamame beans

The sucrose and Alanine (Ala) content in edamame beans significantly impacts the sweetness flavor of edamame-derived products as an important attribute to consumers' acceptance. Unlike grain-type soybeans, edamame beans are harvested as fresh beans at the R6 to R7 growth stages when beans are filled 80-90% of the pod capacity. The genetic basis of sucrose and Ala contents in fresh edamame beans may differ from those in dry seeds. To date, there is no report on the genetic basis of sucrose and Ala contents in the edamame beans. In this study, a genome-wide association study was conducted to identify single nucleotide polymorphisms (SNPs) related to sucrose and Ala levels in edamame beans using an association mapping panel of 189 edamame accessions genotyped with a SoySNP50K BeadChip. A total of 43 and 25 SNPs was associated with sucrose content and Ala content in the edamame beans, respectively. Four genes (Glyma.10g270800, Glyma.08g137500, Glyma.10g268500, and Glyma.18g193600) with known effects on the process of sucrose biosynthesis and 37 novel sucrose-related genes were characterized. Three genes (Gm17g070500, Glyma.14g201100 and Glyma.18g269600) with likely relevant effects in regulating Ala content and 22 novel Ala-related genes were identified. In addition, by summarizing the phenotypic data of edamame beans from three locations in two years, three PI accessions (PI 532469, PI 243551, and PI 407748) were selected as the high sucrose and high Ala parental lines for the perspective breeding of sweet edamame varieties. Thus, the beneficial alleles, candidate genes, and selected PI accessions identified in this study will be fundamental to develop edamame varieties with improved consumers' acceptance, and eventually promote edamame production as a specialty crop in the United States.

Identification of quantitative trait loci associated with seed quality traits between Canadian and Ukrainian mega-environments using genome-wide association study

KEY MESSAGE

Identifying QTL associated with soybean seed quality traits from a diverse GWAS panel cultivated in Canadian and Ukrainian mega-environments may facilitate future cultivar development for foreign markets. Understanding the complex genetic basis of seed quality traits for soybean in the mega-environments (MEs) is critical for developing a marker-assisted selection program that will lead to breeding superior cultivars adapted to specific regions. This study aimed to analyze the accumulation of 14 soybean seed quality traits in Canadian ME and two seed quality traits in Ukrainian ME and identify associated ME specific quantitative trait loci (QTLSP) and ME universal QTL (QTLU) for protein and oil using a genome-wide association study (GWAS) panel consisting of 184 soybean genotypes. The panel was planted in three locations in Canada and two locations in Ukraine in 2018 and 2019. Genotype plus genotype-by-environment biplot analysis was conducted to assess the accumulation of individual seed compounds across different locations. The protein accumulation was high in the Canadian ME and low in the Ukrainian ME, whereas the oil concentration showed the opposite trends between the two MEs. No QTLU were identified across the MEs for protein and oil concentrations. In contrast, nine Canadian QTLSP for protein were identified on various chromosomes, which were co-located with QTL controlling other traits identified in the Canadian ME. The lack of common QTLU for protein and oil suggests that it may be necessary to use QTLSP associated with these traits separately for the Canadian and Ukrainian ME. Additional Ukrainian data for seed compounds other than oil and protein are required to identify novel QTLSP and QTLU for such traits for the individual or combined Canadian and Ukrainian MEs.

Integrating omics approaches to discover and prioritize candidate genes involved in oil biosynthesis in soybean

Soybean is a major source of edible protein and oil. Oil content is a quantitative trait that is significantly determined by genetic and environmental factors. Over the past 30 years, a large volume of soybean genetic, genomic, and transcriptomic data have been accumulated. Nevertheless, integrative analyses of such data remain scarce, in spite of their importance for crop improvement. We hypothesized that the co-occurrence of genomic regions for oil-related traits in different studies may reveal more stable regions encompassing important genetic determinants of oil content and quality in soybean. We integrated publicly available data, obtained with distinct techniques, to discover and prioritize candidate genes involved in oil biosynthesis and regulation in soybean. We detected key fatty acid biosynthesis genes (e.g., BCCP2 and ACCase, FADs, KAS family proteins) and several transcription factors, which are likely regulators of oil biosynthesis. In addition, we identified new candidates for seed oil accumulation and quality, such as Glyma.03G213300 and Glyma.19G160700, which encode a translocator protein homolog and a histone acetyltransferase, respectively. Further, oil and protein genomic hotspots are strongly associated with breeding and not with domestication, suggesting that soybean domestication prioritized other traits. The genes identified here are promising targets for breeding programs and for the development of soybean lines with increased oil content and quality.

Genome-Wide Association Study Identifies Candidate Genes Related to the Linoleic Acid Content in Soybean Seeds

Soybean (Glycine max (L.) Merrill) oil is a complex mixture of five fatty acids (palmitic, stearic, oleic, linoleic, and linolenic). The high content of linoleic acid (LA) contributes to the oil having poor oxidative stability. Therefore, soybean seed with a lower LA content is desirable. To investigate the genetic architecture of LA, we performed a genome-wide association study (GWAS) using 510 soybean cultivars collected from China. The phenotypic identification results showed that the content of LA varied from 36.22% to 72.18%. The GWAS analysis showed that there were 37 genes related to oleic acid content, with a contribution rate of 7%. The candidate gene Glyma.04G116500.1 (GmWRI14) on chromosome 4 was detected in three consecutive years. The GmWRI14 showed a negative correlation with the LA content and the correlation coefficient was -0.912. To test whether GmWRI14 can lead to a lower LA content in soybean, we introduced GmWRI14 into the soybean genome. Matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS) showed that the overexpression of GmWRI14 leads to a lower LA content in soybean seeds. Meanwhile, RNA-seq verified that GmWRI14-overexpressed soybean lines showed a lower accumulation of GmFAD2-1A and GmFAD2-1B than control lines. Our results indicate that the down-regulation of the FAD2 gene triggered by the transcription factor GmWRI14 is the underlying mechanism reducing the LA level of seed. Our results provide novel insights into the genetic architecture of LA and pinpoint potential candidate genes for further in-depth studies.

Identification of potential QTLs and genes associated with seed composition traits in peanut (Arachis hypogaea L.) using GWAS and RNA-Seq analysis

Cultivated peanut (Arachis hypogaea L.) is a major oilseed crop providing edible oil and protein. Oil quality is determined by fatty acid composition including the ratio of oleic acid (C18:1) and linoleic acid (C18:2). A genome-wide association study with 13,382 single nucleotide polymorphisms (SNPs) was conducted to investigate the genetics basis of oil, protein, eight fatty acid concentrations, and O/L ratio (ratio of oleic and linoleic acid) using a diverse panel of 120 genotypes mainly selected from the U.S. peanut mini core collection grown in two years. A total of 178 significant quantitative trait loci (QTLs) associated with those seed composition traits were identified with phenotypic variation explained (PVE) from 18.35% to 27.56%. RNA-Seq analysis identified 282 DEGs (differentially expressed genes) within the 1 Mb of the significant QTLs for seed composition traits. Among those 282 genes, sixteen candidate genes for seed fatty acid metabolism and protein synthesis were screened according to the gene functions.

Identification of Loci and Candidate Genes Analyses for Tocopherol Concentration of Soybean Seed

Tocopherol (Toc) occurs in soybean seeds and is extracted together with the soybean oil. Toc is utilized as an antioxidant in food and an additive in animal feed. A total of 180 representative accessions and 144 recombinant inbred lines (RILs) from the cross of 'Hefeng 25' and 'OAC Bayfield' were selected to evaluate individuals and total Toc concentrations in soybean seeds. The 180 soybean samples were sequenced by the approach of Specific Locus Amplified Fragment Sequencing (SLAF-seq). A total of 22,611 single nucleotide polymorphisms (SNPs) were developed. Nineteen quantitative trait nucleotides (QTNs) were identified associated with individual or total-Toc based on genome-wide association analysis (GWAS). Among them, three QTNs located near known QTLs, and 16 were novel. Eighteen QTLs and nine eQTLs were also detected by linkage mapping. The QTN rs9337368 on Chr.02 was colocalized according to the linkage mapping of the RILs and genome-wide association analysis and regarded as a stable locus for mining the candidate genes in association with Toc. A total of 42 candidate genes near the 200 kbp flanking region of this identified locus were found. Upon a gene-based association, 11 SNPs from five genes out of the 42 candidates were detected. Expression level analysis of five candidate genes revealed that two genes were significantly related to Toc content. The identified loci, along with the candidate genes, might be valuable for increasing the Toc concentration in soybean seeds and improving the nutritional value of soybean oil.

Interspecific Variation in the Unsaturation Level of Seed Oils Were Associated With the Expression Pattern Shifts of Duplicated Desaturase Genes and the Potential Role of Other Regulatory Genes

Seed oils are of great economic importance both for human consumption and industrial applications. The nutritional quality and industrial value of seed oils are mostly determined by their fatty acid profiles, especially the relative proportions of unsaturated fatty acids. Tree peony seed oils have recently been recognized as novel edible oils enriched in α-linolenic acid (ALA). However, congeneric species, such as Paeonia ostii and P. ludlowii, showed marked variation in the relative proportions of different unsaturated fatty acids. By comparing the dynamics of fatty acid accumulation and the time-course gene expression patterns between P. ostii and P. ludlowii, we identified genes that were differentially expressed between two species in developing seeds, and showed congruent patterns of variation between expression levels and phenotypes. In addition to the well-known desaturase and acyltransferase genes associated with fatty acid desaturation, among them were some genes that were conservatively co-expressed with the desaturation pathway genes across phylogenetically distant ALA-rich species, including Camelina sativa and Perilla frutescens. Go enrichment analysis revealed that these genes were mainly involved in transcriptional regulation, protein post-translational modification and hormone biosynthesis and response, suggesting that the fatty acid synthesis and desaturation pathway might be subject to multiple levels of regulation.

Natural Variation in Fatty Acid Composition of Diverse World Soybean Germplasms Grown in China

Soybean (Glycine max L. Merr.) is one of the most important crops in the world. Its major content of vegetable oil made it widely used for human consumption and several food industries. To investigate the variation in seed fatty acid composition of soybeans from different origins, a set of 633 soybean accessions originated from four diverse germplasm collections—including China, United States of America (USA), Japan, and Russia—were grown in three locations, Beijing, Anhui, and Hainan for two years. The results showed significant differences (P < 0.001) among the four germplasm origins for all fatty acid contents investigated. Higher levels, on average, of palmitic acid (PA) and linolenic acid (LNA) were observed in Russian germplasm (12.31% and 8.15%, respectively), whereas higher levels of stearic acid (SA) and oleic acid (OA) were observed in Chinese germplasm (3.95% and 21.95%, respectively). The highest level of linoleic acid (LA) was noticed in the USA germplasm accessions (56.34%). The largest variation in fatty acid composition was found in LNA, while a large variation was observed between Chinese and USA germplasms for LA level. Maturity group (MG) significantly (P < 0.0001) affected all fatty acids and higher levels of PA, SA, and OA were observed in early maturing accessions, while higher levels of LA and LNA were observed in late maturing accessions. The trends of fatty acids concentrations with different MG in this study further provide an evidence of the importance of MG in breeding for such soybean seed components. Collectively, the unique accessions identified in this study can be used to strengthen the soybean breeding programs for meeting various human nutrition patterns around the globe.

A Combined Linkage and GWAS Analysis Identifies QTLs Linked to Soybean Seed Protein and Oil Content

Soybean is an excellent source of vegetable protein and edible oil. Understanding the genetic basis of protein and oil content will improve the breeding programs for soybean. Linkage analysis and genome-wide association study (GWAS) tools were combined to detect quantitative trait loci (QTL) that are associated with protein and oil content in soybean. Three hundred and eight recombinant inbred lines (RILs) containing 3454 single nucleotide polymorphism (SNP) markers and 200 soybean accessions, including 94,462 SNPs and indels, were applied to identify QTL intervals and significant SNP loci. Intervals on chromosomes 1, 15, and 20 were correlated with both traits, and QTL qPro15-1, qPro20-1, and qOil5-1 reproducibly correlated with large phenotypic variations. SNP loci on chromosome 20 that overlapped with qPro20-1 were reproducibly connected to both traits by GWAS (p < 10-4). Twenty-five candidate genes with putative roles in protein and/or oil metabolisms within two regions (qPro15-1, qPro20-1) were identified, and eight of these genes showed differential expressions in parent lines during late reproductive growth stages, consistent with a role in controlling protein and oil content. The new well-defined QTL should significantly improve molecular breeding programs, and the identified candidate genes may help elucidate the mechanisms of protein and oil biosynthesis.