ArticleFrontiers in plant science2022
Genome-wide association study reveals novel QTLs and candidate genes for seed vigor in rice.
Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Genome-wide association study identifies key loci and candidate genes for seed vigor in upland cotton (Frontiers in plant science · 2026Article
- Dynamic monitoring of rice plant height during the early growth stage using UAV-LiDAR and GWAS analysis of growth rate.Frontiers in plant science · 2026Article
- Genome-wide association study uncovers a novel gene responsible for rice seedling submergence tolerance.Plant biotechnology journal · 2025Article
- Transcriptome and metabolome analysis of senescent rice (Oryza sativa L.) seeds: insights into the mechanism of germination vigor and seedling morphogenesis.BMC plant biology · 2025Article
- Article
- Mapping of quantitative trait loci for early seed germination using whole-genome resequencing chromosome segment substitution lines of aus Kasalath in the background of japonica Nipponbare.Frontiers in plant science · 2025Article
- Combining Hyperspectral Techniques and Genome-Wide Association Studies to Predict Peanut Seed Vigor and Explore Associated Genetic Loci.International journal of molecular sciences · 2024Article
- Identification of novel candidate loci and genes for seed vigor-related traits in upland cotton (Frontiers in plant science · 2023Article
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14 authors.
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Abstract
Highly seed vigor (SV) is essential for rice direct seeding (DS). Understanding the genetic mechanism of SV-related traits could contribute to increasing the efficiency of DS. However, only a few genes responsible for SV have been determined in rice, and the regulatory network of SV remains obscure. In this study, the seed germination rate (GR), seedling shoot length (SL), and shoot fresh weight (FW) related to SV traits were measured, and a genome-wide association study (GWAS) was conducted to detect high-quality loci responsible for SV using a panel of 346 diverse accessions. A total of 51 significant SNPs were identified and arranged into six quantitative trait locus (QTL) regions, including one (
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