ArticleFrontiers in plant science2023
Multi-model genome-wide association studies of leaf anatomical traits and vein architecture in rice.
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 7 papers.
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7 citing papers in PubMed.
- Organ-level 3D phenotyping of saffron using a low-cost dual-camera workflow.Plant methods · 2026Article
- Multi-model genome-wide association studies identify stable QTLs and candidate genes for lodging resistance inFrontiers in plant science · 2026Article
- Review
- Rice QTL hotspots related with seed grain size, shape, weight, and color based on genome wide association study and linkage mapping.Scientific reports · 2025Article
- Genetic architecture of ideotype-related traits in middle American beans through single trait, multi-trait and epistatic genome-wide analyses.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Unlocking genetic hotspots: GWAS reveals key nitrogen responsive genomic regions and key genes for root and yield traits in indica rice.Molecular genetics and genomics : MGG · 2025Article
- Exploring Novel Genomic Loci and Candidate Genes Associated with Plant Height in Bulgarian Bread Wheat via Multi-Model GWAS.Plants (Basel, Switzerland) · 2024Article
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4 authors.
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Abstract
Introduction: The anatomy of rice leaves is closely related to photosynthesis and grain yield. Therefore, exploring insight into the quantitative trait loci (QTLs) and alleles related to rice flag leaf anatomical and vein traits is vital for rice improvement. Methods: Here, we aimed to explore the genetic architecture of eight flag leaf traits using one single-locus model; mixed-linear model (MLM), and two multi-locus models; fixed and random model circulating probability unification (FarmCPU) and Bayesian information and linkage disequilibrium iteratively nested keyway (BLINK). We performed multi-model GWAS using 329 rice accessions of RDP1 with 700K single-nucleotide polymorphisms (SNPs) markers. Results: The phenotypic correlation results indicated that rice flag leaf thickness was strongly correlated with leaf mesophyll cells layer (ML) and thickness of both major and minor veins. All three models were able to identify several significant loci associated with the traits. MLM identified three non-synonymous SNPs near Discussion: Several numbers of significant SNPs associated with known gene function in leaf development and yield traits were detected by multi-model GWAS performed in this study. Our findings indicate that flag leaf traits could be improved via molecular breeding and can be one of the targets in high-yield rice development.
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