SynthesisScientific reports2022
Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification.
Synthesis in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 30 citations in OpenAlex.
- Integrative genomics resolves rice loci associated with acidic soil-related aluminum, cadmium, and manganese stress responses.Plant cell reports · 2026Article
- Genomic dissection of iron toxicity tolerance in rice identifies key loci, candidate genes, and associated haplotypes.Scientific reports · 2026Article
- Meta-QTLs and candidate genes for kernel protein content in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Candidate Gene for Kernel-Related Traits in Maize Revealed by a Combination of GWAS and Meta-QTL Analyses.Plants (Basel, Switzerland) · 2025Article
- Genetic dissection of yield and yield-related traits in mungbean based on QTL meta-analysis.Frontiers in genetics · 2025Article
- Identification of a novel locus qGW12/OsPUB23 regulating grain shape and weight in rice (Oryza sativa L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Review
- Refinement of rice blast disease resistance QTLs and gene networks through meta-QTL analysis.Scientific reports · 2024Article
- Fine mapping of interspecific secondary CSSL populations revealed key regulators for grain weight atPhysiology and molecular biology of plants : an international journal of functional plant biology · 2024Article
- Genome-wide screening of meta-QTL and candidate genes controlling yield and yield-related traits in barley (Hordeum vulgare L.).PloS one · 2024Article
- Unraveling genomic regions and candidate genes for multiple disease resistance in upland cotton using meta-QTL analysis.Heliyon · 2023Article
- Gene based markers improve precision of genome-wide association studies and accuracy of genomic predictions in rice breeding.Heredity · 2023Article
- A meta-QTL analysis highlights genomic hotspots associated with phosphorus use efficiency in rice (Frontiers in plant science · 2023Article
- Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Frontiers in genetics · 2023Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative trait loci (QTL) for rice grain weight identified using bi-parental populations in various environments were found inconsistent and have a modest role in marker assisted breeding and map-based cloning programs. Thus, the identification of a consistent consensus QTL region across populations is critical to deploy in marker aided breeding programs. Using the QTL meta-analysis technique, we collated rice grain weight QTL information from numerous studies done across populations and in diverse environments to find constitutive QTL for grain weight. Using information from 114 original QTL in meta-analysis, we discovered three significant Meta-QTL (MQTL) for grain weight on chromosome 3. According to gene ontology, these three MQTL have 179 genes, 25 of which have roles in developmental functions. Amino acid sequence BLAST of these genes indicated their orthologue conservation among core cereals with similar functions. MQTL3.1 includes the OsAPX1, PDIL, SAUR, and OsASN1 genes, which are involved in grain development and have been discovered to play a key role in asparagine biosynthesis and metabolism, which is crucial for source-sink regulation. Five potential candidate genes were identified and their expression analysis indicated a significant role in early grain development. The gene sequence information retrieved from the 3 K rice genome project revealed the deletion of six bases coding for serine and alanine in the last exon of OsASN1 led to an interruption in the synthesis of α-helix of the protein, which negatively affected the asparagine biosynthesis pathway in the low grain weight genotypes. Further, the MQTL3.1 was validated using linked marker RM7197 on a set of genotypes with extreme phenotypes. MQTL that have been identified and validated in our study have significant scope in MAS breeding and map-based cloning programs for improving rice grain weight.
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