ArticleScientific reports2020
Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Meta QTL analysis for dissecting abiotic stress tolerance in chickpea.BMC genomics · 2024Pooled it
- Meta-analysis of the quantitative trait loci associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits in pigeonpea (Cajanus cajan L.).The plant genome · 2023Pooled it
- Combination of meta-analysis of QTL and GWAS to uncover the genetic architecture of seed yield and seed yield components in common bean.The plant genome · 2023Pooled it
- Meta-QTLs and candidate genes for kernel protein content in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Characterization of Genetic Diversity and Genomic Prediction of Secondary Metabolites in Pea Genetic Resources.Plants (Basel, Switzerland) · 2026Article
- Decoding the genetic architecture of seed quality traits in mungbean through quantitative trait loci mapping.Frontiers in plant science · 2026Article
- QTL mapping for hundred-seed weight in soybean using high-density SLAF-seq technology.BMC plant biology · 2025Article
- Genome-wide association studies of nutritional traits in peas (Pisum sativum L.) for biofortification.The plant genome · 2025Article
- Harnessing historical genebank data to accelerate pea breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genomic Selection for Pea Grain Yield and Protein Content in Italian Environments for Target and Non-Target Genetic Bases.International journal of molecular sciences · 2025Article
- Innovations in functional genomics and molecular breeding of pea: exploring advances and opportunities.aBIOTECH · 2024Review
- Identification of QTLs associated with seed protein concentration in two diverse recombinant inbred line populations of pea.Frontiers in plant science · 2024Article
- Genomic prediction and allele mining of agronomic and morphological traits in pea (Frontiers in plant science · 2023Article
- High confidence QTLs and key genes identified using Meta-QTL analysis for enhancing heat tolerance in chickpea (Frontiers in plant science · 2023Article
- Quantitative trait loci associated with amino acid concentration andFrontiers in plant science · 2023Article
- Article
- Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and 'Omics' Tools.International journal of molecular sciences · 2022Review
- Phenotypic and Genotypic Characterization and Correlation Analysis of Pea (Plants (Basel, Switzerland) · 2022Article
- Genetic and Genomic Resources for Soybean Breeding Research.Plants (Basel, Switzerland) · 2022Review
- Unraveling the Genetic Basis of Key Agronomic Traits of Wrinkled Vining Pea (Frontiers in plant science · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms.
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