ArticlePloS one2020
Identify QTLs and candidate genes underlying source-, sink-, and grain yield-related traits in rice by integrated analysis of bi-parental and natural populations.
Article in PloS one, 2020. 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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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice (Frontiers in plant science · 2022Review
- A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice.Frontiers in plant science · 2022Article
- Mapping novel QTLs for yield related traits from a popular rice hybrid KRH-2 derived doubled haploid (DH) population.3 Biotech · 2021Article
- A high-resolution genome-wide association study of the grain ionome and agronomic traits in rice Oryza sativa subsp. indica.Scientific reports · 2021Article
- Improving Photosynthetic Metabolism for Crop Yields: What Is Going to Work?Frontiers in plant science · 2021Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
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Abstract
The source-sink relationship determines the ultimate grain yield of rice. In this study, we used a set of reciprocal introgression lines (ILs) derived from Xuishui09 × IR2061 to map quantitative trait loci (QTLs) that were associated with sink-, source-, and grain yield-related traits. A total of 95 QTLs influencing eight measured traits were identified using 6181 high-quality single nucleotide polymorphism markers. Nine background-independent QTLs were consistently detected in seven chromosomal regions in different genetic backgrounds. Seven QTLs clusters simultaneously affected sink-, source-, and grain yield-related traits, probably due to the genetic basis of significant correlations of grain yield with source and sink traits. We selected 15 candidate genes in the four QTLs consistently identified in the two populations by performing gene-based association and haplotype analyses using 2288 accessions from the 3K project. Among these, LOC_Os03g48970 for qTSN3b, LOC_Os06g04710 for qFLL6a, and LOC_Os07g32510 for qTGW7 were considered as the most likely candidate genes based on functional annotations. These results provide a basis for further study of candidate genes and for the development of high-yield rice varieties by balancing source-sink relationships using marker-assisted selection.
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