ArticleBMC genetics2019
Genome-wide association study of four yield-related traits at the R6 stage in soybean.
Article in BMC genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Genome-Wide Association Study Identifies QTNs and Candidate Genes Conferring Resistance to Soybean Frogeye Leaf Spot Race 7.Plants (Basel, Switzerland) · 2026Article
- Integrative haplotype and SNP-based GWAS supports the identification of stable genomic loci controlling yield-related traits in soybean.Frontiers in plant science · 2026Article
- Natural variation of theFrontiers in plant science · 2026Article
- Genome-Wide Characterization of a Carbon Ion Beam-Induced Soybean Mutant Population Reveals Extensive Genetic Variation for Trait Improvement.International journal of molecular sciences · 2025Article
- GWAS analysis revealed genomic loci and candidate genes associated with the 100-seed weight in high-latitude-adapted soybean germplasm.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genome-wide association study of sucrose content in vegetable soybean.BMC plant biology · 2024Article
- Genome-Wide Association Analysis of Yield-Related Traits and Candidate Genes in Vegetable Soybean.Plants (Basel, Switzerland) · 2024Article
- Identification of the domestication gene GmCYP82C4 underlying the major quantitative trait locus for the seed weight in soybean.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Global Status of Vegetable Soybean.Plants (Basel, Switzerland) · 2023Review
- Identification of major quantitative trait loci and candidate genes for seed weight in soybean.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean.Frontiers in plant science · 2023Review
- Genome-Wide Association Study Revealed SNP Alleles Associated with Seed Size Traits in African Yam Bean (Genes · 2022Article
- Genome wide association analysis for yield related traits in maize.BMC plant biology · 2022Article
- Identification of major genomic regions for soybean seed weight by genome-wide association study.Molecular breeding : new strategies in plant improvement · 2022Article
- Genome-wide association analysis for yield-related traits at the R6 stage in a Chinese soybean mini core collection.Genes & genomics · 2021Article
- Genome-wide association analysis reveals quantitative trait loci and candidate genes involved in yield components under multiple field environments in cotton (Gossypium hirsutum).BMC plant biology · 2021Article
- Genome-wide association studies of plant architecture-related traits and 100-seed weight in soybean landraces.BMC genomic data · 2021Article
- Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean.Frontiers in genetics · 2021Article
- Identification of quantitative trait nucleotides and candidate genes for soybean seed weight by multiple models of genome-wide association study.BMC plant biology · 2020Article
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12 authors.
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Abstract
backgroundThe 100-pod fresh weight (PFW), 100-seed fresh weight (SFW), 100-seed dry weight (SDW) and moisture content of fresh seeds (MCFS) at the R6 stage are crucial factors for vegetable soybean yield. However, the genetic basis of yield at the R6 stage remains largely ambiguous in soybean.
resultsTo better understand the molecular mechanism underlying yield, we investigated four yield-related traits of 133 soybean landraces in two consecutive years and conducted a genome-wide association study (GWAS) using 82,187 single nucleotide polymorphisms (SNPs). The GWAS results revealed a total of 14, 15, 63 and 48 SNPs for PFW, SFW, SDW and MCFS, respectively. Among these markers, 35 SNPs were repeatedly identified in all evaluated environments (2015, 2016, and the average across the two years), and most co-localized with yield-related QTLs identified in previous studies. AX-90496773 and AX-90460290 were large-effect markers for PFW and MCFS, respectively. The two markers were stably identified in all environments and tagged to linkage disequilibrium (LD) blocks. Six potential candidate genes were predicted in LD blocks; five of them showed significantly different expression levels between the extreme materials with large PFW or MCFS variation at the seed development stage. Therefore, the five genes Glyma.16g018200, Glyma.16g018300, Glyma.05g243400, Glyma.05g244100 and Glyma.05g245300 were regarded as candidate genes associated with PFW and MCFS.
conclusionThese results provide useful information for the development of functional markers and exploration of candidate genes in vegetable soybean high-yield breeding programs.
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