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A chickpea MAGIC population to dissect the genetics of complex traits
Journal article   Open access   Peer reviewed

A chickpea MAGIC population to dissect the genetics of complex traits

Oluwaseun J. Akinlade, Hannah Robinson, Yichen Kang, Mahendar Thudi, Srinivasan Samineni, Pooran Gaur, Millicent R. Smith, Kai P. Voss-Fels, Roy Costilla, Rajeev K. Varshney, …
The plant genome, Vol.18(3), e70096
2025
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CC BY V4.0 Open Access

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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Collaboration types
Domestic collaboration
International collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.4 Crop Science
3.4.96 QTL
Web Of Science research areas
Genetics & Heredity
Plant Sciences
ESI research areas
Plant & Animal Science
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