Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Mahendar Thudi; Srinivasan Samineni; Wenhao Li; Martin P. Boer; Manish Roorkiwal; Zuoquan Yang; Funmi Ladejobi; Chaozhi Zheng; Annapurna Chitikineni; Sourav Nayak; Zhang He; Vinod Valluri; Prasad Bajaj; Aamir W. Khan; Pooran M. Gaur; Fred van Eeuwijk; Richard Mott; Liu Xin; Rajeev K. Varshney

doi:10.1002/tpg2.20333

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Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

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Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Mahendar Thudi, Srinivasan Samineni, Wenhao Li, Martin P. Boer, Manish Roorkiwal, Zuoquan Yang, Funmi Ladejobi, Chaozhi Zheng, Annapurna Chitikineni, Sourav Nayak, …

The plant genome, Vol.17(1), e20333

2023

DOI: https://doi.org/10.1002/tpg2.20333

PMID: 37122200

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Abstract

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Details

Title: Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea
Authors/Creators: Mahendar Thudi - International Crops Research Institute for the Semi-Arid Tropics
Srinivasan Samineni - SEMI
Wenhao Li - Wageningen University & Research
Martin P. Boer - Wageningen University & Research
Manish Roorkiwal - International Crops Research Institute for the Semi-Arid Tropics
Zuoquan Yang - BGI Group (China)
Funmi Ladejobi - University College London
Chaozhi Zheng - Wageningen University & Research
Annapurna Chitikineni - International Crops Research Institute for the Semi-Arid Tropics
Sourav Nayak - International Crops Research Institute for the Semi-Arid Tropics
Zhang He - BGI (United States)
Vinod Valluri - International Crops Research Institute for the Semi-Arid Tropics
Prasad Bajaj - International Crops Research Institute for the Semi-Arid Tropics
Aamir W. Khan - International Crops Research Institute for the Semi-Arid Tropics
Pooran M. Gaur - Central Agricultural University
Fred van Eeuwijk - Wageningen University & Research
Richard Mott - University College London
Liu Xin - BGI Shenzhen, Shenzhen, Peoples R China
Rajeev K. Varshney - Murdoch University, Food Futures Institute
Publication Details: The plant genome, Vol.17(1), e20333
Publisher: Wiley Periodicals LLC on behalf of Crop Science Society of America.
Number of pages: 16
Grant note: CGIAR Generation Challenge Program; CGIAR Biotechnology and Biological Sciences Research Council (BBSRC), UK; UK Research & Innovation (UKRI); Biotechnology and Biological Sciences Research Council (BBSRC) Food Futures Institute of Murdoch Uni Bill and Melinda Gates Foundation; Bill & Melinda Gates Foundation
Identifiers: 991005602260007891
Copyright: © 2023 The Authors.
Murdoch Affiliation: Centre for Crop and Food Innovation; State Agricultural Biotechnology Centre
Language: English
Resource Type: Journal article

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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