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Identification of Genomic Loci and Candidate Genes Related to Seed Tocopherol Content in Soybean.

ABSTRACT: Soybean seeds are primary sources of natural tocopherols used by the food and pharmaceutical industries, owing to their beneficial impacts on human health. Selection for higher tocopherol contents in seeds along with other desirable traits is an important goal in soybean breeding. In order to identify the genomic loci and candidate genes controlling tocopherol content in soybean seeds, the bulked-segregant analysis technique was performed using a natural population of soybean consisting of 1525 accessions. We constructed the bulked-segregant analysis based on 98 soybean accessions that showed extreme phenotypic variation for the target trait, consisting of 49 accessions with extremely-high and 49 accessions with extremely-low tocopherol content. A total of 144 variant sites and 109 predicted genes related to tocopherol content were identified, in which a total of 83 genes were annotated by the gene ontology functions. Furthermore, 13 enriched terms (p < 0.05) were detected, with four of them found to be highly enriched: response to lipid, response to abscisic acid, transition metal ion transmembrane transporter activity, and double-stranded DNA binding. Especially, six candidate genes were detected at 41.8-41.9 Mb genomic hotspots on chromosome 5 based on ANNOtate VARiation analysis. Among the genes, only Glyma.05G243400 carried a non-synonymous mutation that encodes a "translation elongation factor EF1A or initiation factor IF2gamma family protein" was identified. The haplotype analysis confirmed that Glyma.05G243400 exhibited highly significant variations in terms of tocopherol content across multiple experimental locations, suggesting that it can be the key candidate gene regulating soybean seed tocopherols. The present findings provide novel gene resources related to seed tocopherols for further validation by genome editing, functional characterization, and genetic improvement targeting enhanced tocopherol composition in soybean molecular breeding.

SUBMITTER: Ghosh S

PROVIDER: S-EPMC9269242 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Soybean seeds are rich in secondary metabolites which are beneficial for human health, including tocopherols. Tocopherols play an important role in human and animal nutrition thanks to their antioxidant activity. In this study, the 'Forrest' by 'Williams 82' (F×W82) recombinant inbred line (RIL) population (n = 306) was used to map quantitative trait loci (QTL) for seed α-tocopherol, β-tocopherol, δ -tocopherol, γ-tocopherol, and total tocopherol contents in Carbondale, IL over two years. Also, the identification of the candidate genes involved in soybean tocopherols biosynthetic pathway was performed. A total of 32 QTL controlling various seed tocopherol contents have been identified and mapped on Chrs. 1, 2, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, and 20. One major and novel QTL was identified on Chr. 6 with an R2 of 27.8, 9.9, and 6.9 for δ-tocopherol, α-tocopherol, and total tocopherol content, respectively. Reverse BLAST analysis of the genes that were identified in Arabidopsis allowed the identification of 37 genes involved in soybean tocopherol pathway, among which 11 were located close to the identified QTLs. The tocopherol cyclase gene (TC) Glyma.06G084100 is located close to the QTLs controlling δ-tocopherol (R2 = 27.8), α-tocopherol (R2 = 9.96), and total-tocopherol (R2 = 6.95). The geranylgeranyl diphosphate reductase (GGDR) Glyma.05G026200 gene is located close to a QTL controlling total tocopherol content in soybean (R2 = 4.42). The two methylphytylbenzoquinol methyltransferase (MPBQ-MT) candidate genes Glyma.02G002000 and Glyma.02G143700 are located close to a QTL controlling δ-tocopherol content (R2 = 3.57). The two γ-tocopherol methyltransferase (γ-TMT) genes, Glyma.12G014200 and Glyma.12G014300, are located close to QTLs controlling (γ+ß) tocopherol content (R2 = 8.86) and total tocopherol (R2 = 5.94). The identified tocopherol seed QTLs and candidate genes will be beneficial in breeding programs to develop soybean cultivars with high tocopherol contents.

Project description:Genome-wide association studies (GWAS) is an efficient method to detect quantitative trait locus (QTL), and has dissected many complex traits in soybean [Glycine max (L.) Merr.]. Although these results have undoubtedly played a far-reaching role in the study of soybean biology, environmental interactions for complex traits in traditional GWAS models are frequently overlooked. Recently, a new GWAS model, 3VmrMLM, was established to identify QTLs and QTL-by-environment interactions (QEIs) for complex traits. In this study, the GLM, MLM, CMLM, FarmCPU, BLINK, and 3VmrMLM models were used to identify QTLs and QEIs for tocopherol (Toc) content in soybean seed, including δ‐Tocotrienol (δ‐Toc) content, γ‐Tocotrienol (γ‐Toc) content, α‐Tocopherol (α‐Toc) content, and total Tocopherol (T-Toc) content. As a result, 101 QTLs were detected by the above methods in single-environment analysis, and 57 QTLs and 13 QEIs were detected by 3VmrMLM in multi-environment analysis. Among these QTLs, some QTLs (Group I) were repeatedly detected three times or by at least two models, and some QTLs (Group II) were repeatedly detected only by 3VmrMLM. In the two Groups, 3VmrMLM was able to correctly detect all known QTLs in group I, while good results were achieved in Group II, for example, 8 novel QTLs were detected in Group II. In addition, comparative genomic analysis revealed that the proportion of Glyma_max specific genes near QEIs was higher, in other words, these QEIs nearby genes are more susceptible to environmental influences. Finally, around the 8 novel QTLs, 11 important candidate genes were identified using haplotype, and validated by RNA-Seq data and qRT-PCR analysis. In summary, we used phenotypic data of Toc content in soybean, and tested the accuracy and reliability of 3VmrMLM, and then revealed novel QTLs, QEIs and candidate genes for these traits. Hence, the 3VmrMLM model has broad prospects and potential for analyzing the genetic structure of complex quantitative traits in soybean.

Project description:BackgroundAs a photoperiod-sensitive and self-pollinated species, the growth periods traits play important roles in the adaptability and yield of soybean. To examine the genetic architecture of soybean growth periods, we performed a genome-wide association study (GWAS) using a panel of 278 soybean accessions and 34,710 single nucleotide polymorphisms (SNPs) with minor allele frequencies (MAF) higher than 0.04 detected by the specific-locus amplified fragment sequencing (SLAF-seq) with a 6.14-fold average sequencing depth. GWAS was conducted by a compressed mixed linear model (CMLM) involving in both relative kinship and population structure.ResultsGWAS revealed that 37 significant SNP peaks associated with soybean flowering time or other growth periods related traits including full bloom, beginning pod, full pod, beginning seed, and full seed in two or more environments at -log10(P) > 3.75 or -log10(P) > 4.44 were distributed on 14 chromosomes, including chromosome 1, 2, 3, 5, 6, 9, 11, 12, 13, 14, 15, 17, 18, 19. Fourteen SNPs were novel loci and 23 SNPs were located within known QTLs or 75 kb near the known SNPs. Five candidate genes (Glyma.05G101800, Glyma.11G140100, Glyma.11G142900, Glyma.19G099700, Glyma.19G100900) in a 90 kb genomic region of each side of four significant SNPs (Gm5_27111367, Gm11_10629613, Gm11_10950924, Gm19_34768458) based on the average LD decay were homologs of Arabidopsis flowering time genes of AT5G48385.1, AT3G46510.1, AT5G59780.3, AT1G28050.1, and AT3G26790.1. These genes encoding FRI (FRIGIDA), PUB13 (plant U-box 13), MYB59, CONSTANS, and FUS3 proteins respectively might play important roles in controlling soybean growth periods.ConclusionsThis study identified putative SNP markers associated with soybean growth period traits, which could be used for the marker-assisted selection of soybean growth period traits. Furthermore, the possible candidate genes involved in the control of soybean flowering time were predicted.

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Identification of Genomic Loci and Candidate Genes Related to Seed Tocopherol Content in Soybean.

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