ArticleFrontiers in plant science2023
Detection of epistasis interaction loci for fiber quality-related trait via 3VmrMLM in upland cotton.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 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
- A genome-wide association study to elucidate the genetic basis of the cottonseed protein content in Upland cotton (Breeding science · 2026Article
- Fine Mapping of QTLs/QTNs and Mining of Genes Associated with Race 7 of the SoybeanPlants (Basel, Switzerland) · 2025Article
- Single- and Multi-Locus GWAS Unravels Novel Genomic Regions Related to Low-Phosphate Stress in Cotton Seedlings.Plants (Basel, Switzerland) · 2025Article
- Genome-wide association study and molecular marker development for susceptibility to Gibberella ear rot in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
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Abstract
Cotton fiber quality-related traits, such as fiber length, fiber strength, and fiber elongation, are affected by complex mechanisms controlled by multiple genes. Determining the QTN-by-QTN interactions (QQIs) associated with fiber quality-related traits is therefore essential for accelerating the genetic enhancement of cotton breeding. In this study, a natural population of 1,245 upland cotton varieties with 1,122,352 SNPs was used for detecting the main-effect QTNs and QQIs using the 3V multi-locus random-SNP-effect mixed linear model (3VmrMLM) method. A total of 171 significant main-effect QTNs and 42 QQIs were detected, of which 22 were both main-effect QTNs and QQIs. Of the detected 42 QQIs, a total of 13 significant loci and 5 candidate genes were reported in previous studies. Among the three interaction types, the AD interaction type has a preference for the trait of FE. Additionally, the QQIs have a substantial impact on the enhancement predictability for fiber quality-related traits. The study of QQIs is crucial for elucidating the genetic mechanism of cotton fiber quality and enhancing breeding efficiency.
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