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A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea

Plant Molecular Biology volume 89, pages 403–420 (2015)Cite this article

Abstract

A combinatorial approach of candidate gene-based association analysis and genome-wide association study (GWAS) integrated with QTL mapping, differential gene expression profiling and molecular haplotyping was deployed in the present study for quantitative dissection of complex flowering time trait in chickpea. Candidate gene-based association mapping in a flowering time association panel (92 diverse desi and kabuli accessions) was performed by employing the genotyping information of 5724 SNPs discovered from 82 known flowering chickpea gene orthologs of Arabidopsis and legumes as well as 832 gene-encoding transcripts that are differentially expressed during flower development in chickpea. GWAS using both genome-wide GBS- and candidate gene-based genotyping data of 30,129 SNPs in a structured population of 92 sequenced accessions (with 200–250 kb LD decay) detected eight maximum effect genomic SNP loci (genes) associated (34 % combined PVE) with flowering time. Six flowering time-associated major genomic loci harbouring five robust QTLs mapped on a high-resolution intra-specific genetic linkage map were validated (11.6–27.3 % PVE at 5.4–11.7 LOD) further by traditional QTL mapping. The flower-specific expression, including differential up- and down-regulation (>three folds) of eight flowering time-associated genes (including six genes validated by QTL mapping) especially in early flowering than late flowering contrasting chickpea accessions/mapping individuals during flower development was evident. The gene haplotype-based LD mapping discovered diverse novel natural allelic variants and haplotypes in eight genes with high trait association potential (41 % combined PVE) for flowering time differentiation in cultivated and wild chickpea. Taken together, eight potential known/candidate flowering time-regulating genes [efl1 (early flowering 1), FLD (Flowering locus D), GI (GIGANTEA), Myb (Myeloblastosis), SFH3 (SEC14-like 3), bZIP (basic-leucine zipper), bHLH (basic helix-loop-helix) and SBP (SQUAMOSA promoter binding protein)], including novel markers, QTLs, alleles and haplotypes delineated by aforesaid genome-wide integrated approach have potential for marker-assisted genetic improvement and unravelling the domestication pattern of flowering time in chickpea.

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Acknowledgments

The authors gratefully acknowledge the financial support by the core grant of National Institute of Plant Genome Research (NIPGR), New Delhi, India. Shouvik Das acknowledges the Department of Biotechnology (DBT), Government of India for Junior Research Fellowship award.

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    Affiliations

    1. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, 502324, India

      Hari D. Upadhyaya, C. L. L. Gowda & Shivali Sharma

    2. National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, 110067, India

      Deepak Bajaj, Shouvik Das, Maneesha S. Saxena, Saurabh Badoni, Akhilesh K. Tyagi & Swarup K. Parida

    3. National Research Centre on Plant Biotechnology (NRCPB), New Delhi, 110012, India

      Vinod Kumar

    4. Division of Genetics, Indian Agricultural Research Institute (IARI), New Delhi, 110012, India

      Shailesh Tripathi

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    1. Hari D. Upadhyaya
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    2. Deepak Bajaj
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    3. Shouvik Das
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    4. Maneesha S. Saxena
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    8. C. L. L. Gowda
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    9. Shivali Sharma
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    10. Akhilesh K. Tyagi
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    11. Swarup K. Parida
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    Correspondence to Swarup K. Parida.

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    Hari D. Upadhyaya, Deepak Bajaj, and Shouvik Das have contributed equally to this work.

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    Upadhyaya, H.D., Bajaj, D., Das, S. et al. A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea. Plant Mol Biol 89, 403–420 (2015). https://doi.org/10.1007/s11103-015-0377-z

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    • DOI: https://doi.org/10.1007/s11103-015-0377-z

    Keywords

    • Chickpea
    • Flowering time
    • GBS
    • GWAS
    • QTL
    • SNP