ArticleFrontiers in genetics2021
Identification and Validation of Major QTLs, Epistatic Interactions, and Candidate Genes for Soybean Seed Shape and Weight Using Two Related RIL Populations.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Mining genes, genomic selection and simulation breeding on hundred-seed weight using a four-way RIL population.Frontiers in plant science · 2026Article
- Genetic loci underlying seed size and yield-related traits in cowpea.Frontiers in plant science · 2026Article
- Article
- Genome-wide association study of drought tolerance in wheat (Triticum aestivum L.) identifies SNP markers and candidate genes.Molecular genetics and genomics : MGG · 2024Article
- Molecular and genetic insights into secondary metabolic regulation underlying insect-pest resistance in legumes.Functional & integrative genomics · 2023Review
- Major genetic locus with pleiotropism determined seed-related traits in cultivated and wild soybeans.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Construction of a genetic map and QTL mapping of seed size traits in soybean.Frontiers in genetics · 2023Article
- Genetic Diversity and Association Analysis for Carotenoid Content among Sprouts of Cowpea (International journal of molecular sciences · 2022Article
- Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments.Frontiers in plant science · 2022Article
- A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice.Frontiers in plant science · 2022Article
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9 authors.
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Abstract
Understanding the genetic mechanism underlying seed size, shape, and weight is essential for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line (RIL) populations, LM6 and ZM6, were evaluated across multiple environments to identify and validate M-QTLs as well as identify candidate genes behind major and stable quantitative trait loci (QTLs). A total of 239 and 43 M-QTLs were mapped by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM) approaches, from which 180 and 18, respectively, are novel QTLs. Twenty-two QTLs including four novel major QTLs were validated in the two RIL populations across multiple environments. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Thirty-four QTLs associated with seed flatness index (FI) were identified and reported here for the first time. Seven QTL clusters comprising several QTLs for seed size, shape, and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17, and 19 were identified. Gene annotations, gene ontology (GO) enrichment, and RNA-seq analyses of the genomic regions of those seven QTL clusters identified 47 candidate genes for seed-related traits. These genes are highly expressed in seed-related tissues and nodules, which might be deemed as potential candidate genes regulating the seed size, weight, and shape traits in soybean. This study provides detailed information on the genetic basis of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning, and for marker-assisted selection (MAS) targeted at improving these traits individually or concurrently.
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