ArticleFrontiers in plant science2022
Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis.
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 24 papers, 4 of them syntheses that pooled it.
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Who cites it
24 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Transcriptome-based meta-analysis of drought stress regulatory genes in tomato.BMC plant biology · 2025Pooled it
- Unravelling consensus genomic regions conferring stem-related traits in wheat via meta-QTL analysis.BMC plant biology · 2025Pooled it
- Meta-QTL analysis and in-silico transcriptome assessment for controlling chlorophyll traits in common wheat.The plant genome · 2023Pooled it
- Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment.BMC genomics · 2023Pooled it
- Genetic dissection of cold stress tolerance and yield potential under cold stress in nested synthetic wheat (Triticum aestivum L.) introgression libraries using multi-locus genome-wide association and haplotype analysis.Functional & integrative genomics · 2026Article
- Uncover the genetic basis of processing quality related traits in common wheat (Frontiers in plant science · 2026Article
- Dissecting the genetics of forage quality traits in soft red winter wheat in the U.S. southeast region.Frontiers in plant science · 2026Article
- Article
- Identification of quantitative trait loci and candidate genes underlying kernel traits of wheat (Triticum aestivum L.) in response to drought stress.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Candidate Gene for Kernel-Related Traits in Maize Revealed by a Combination of GWAS and Meta-QTL Analyses.Plants (Basel, Switzerland) · 2025Article
- Integrated meta-QTL and in silico transcriptome assessment pinpoint major genomic regions responsible for spike length in wheat (Triticum aestivum L.).The plant genome · 2024Article
- Genomic-wide analysis reveals seven in absentia genes regulating grain development in wheat (Triticum aestivum L.).The plant genome · 2024Article
- Alleles on locus chromosome 4B from different parents confer tiller number and the yield-associated traits in wheat.BMC plant biology · 2024Article
- Genome-wide association studies reveal stable loci for wheat grain size under different sowing dates.PeerJ · 2024Article
- Meta-QTL mapping for wheat thousand kernel weight.Frontiers in plant science · 2024Article
- Performing whole-genome association analysis of winter wheat plant height using the 55K chip.Frontiers in plant science · 2024Article
- Meta-QTL analysis and candidate genes for quality traits, mineral content, and abiotic-related traits in wild emmer.Frontiers in plant science · 2024Article
- Meta-QTL analysis in wheat: progress, challenges and opportunities.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Review
- QTL mapping for kernel-related traits in a durum wheat xFrontiers in plant science · 2023Article
- Responses of wheat kernel weight to diverse allelic combinations under projected climate change conditions.Frontiers in plant science · 2023Article
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8 authors.
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Abstract
Grain weight is a key determinant for grain yield potential in wheat, which is highly governed by a type of quantitative genetic basis. The identification of major quantitative trait locus (QTL) and functional genes are urgently required for molecular improvements in wheat grain yield. In this study, major genomic regions and putative candidate genes for thousand grain weight (TGW) were revealed by integrative approaches with QTL linkage mapping, meta-analysis and transcriptome evaluation. Forty-five TGW QTLs were detected using a set of recombinant inbred lines, explaining 1.76-12.87% of the phenotypic variation. Of these, ten stable QTLs were identified across more than four environments. Meta-QTL (MQTL) analysis were performed on 394 initial TGW QTLs available from previous studies and the present study, where 274 loci were finally refined into 67 MQTLs. The average confidence interval of these MQTLs was 3.73-fold less than that of initial QTLs. A total of 134 putative candidate genes were mined within MQTL regions by combined analysis of transcriptomic and omics data. Some key putative candidate genes similar to those reported early for grain development and grain weight formation were further discussed. This finding will provide a better understanding of the genetic determinants of TGW and will be useful for marker-assisted selection of high yield in wheat breeding.
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