ArticleThe plant genome2025
A chickpea MAGIC population to dissect the genetics of complex traits.
Article in The plant genome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Multi-parent mapping reveals epistatic architecture and elite haplotypes for multi-trait improvement in cotton.Genome biology · 2026Article
- Multi-model genome-wide association analysis of agronomic traits in a Kabuli chickpea MAGIC-subset population (Frontiers in plant science · 2026Article
- MAGIC populations: a next-generation framework for dissecting complex quantitative traits and accelerating molecular breeding in crops.Frontiers in plant science · 2026Review
- A chickpea MAGIC population to dissect the genetics of complex traits.The plant genome · 2025Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiparent populations are now widespread in crop genetic studies as they capture more genetic diversity and offer high statistical power for detecting quantitative trait loci (QTLs). To confirm the suitability of using a recently developed chickpea (Cicer arietinum L.) multi-parent advanced generation intercross (MAGIC) population for genetic studies, we characterized the diversity of the eight founder lines and explored the linkage disequilibrium decay, marker coverage, segregation distortion, allelic variation, and structure of the population. The MAGIC population was genotyped using whole-genome sequencing; following marker curation, a total of 4255 high-quality polymorphic single nucleotide polymorphism markers were used for genomic analyses. To demonstrate the effectiveness of the MAGIC population to dissect the genetics of key agronomic traits (days to 50% flowering and plant height), we employed both a genome-wide mapping approach using fixed and random model circulating probability unification and a haplotype-based mapping using the local genomic estimated breeding value approach. Our analyses confirmed the role of genomic regions previously reported in the literature and identified several new QTLs for days to 50% flowering and plant height. We also showed the potential for trait improvement through stacking the top 10 haploblocks to develop early flowering chickpea and selection of desirable haplotypes on chromosome 4 to improve plant height. Our results demonstrate the chickpea MAGIC population is a valuable resource for researchers and pre-breeders to study the genetic architecture of complex traits and allelic variation to accelerate crop improvement in chickpea.
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