Dataset Information

EcoTILLING-Based Association Mapping Efficiently Delineates Functionally Relevant Natural Allelic Variants of Candidate Genes Governing Agronomic Traits in Chickpea.

ABSTRACT: The large-scale mining and high-throughput genotyping of novel gene-based allelic variants in natural mapping population are essential for association mapping to identify functionally relevant molecular tags governing useful agronomic traits in chickpea. The present study employs an alternative time-saving, non-laborious and economical pool-based EcoTILLING approach coupled with agarose gel detection assay to discover 1133 novel SNP allelic variants from diverse coding and regulatory sequence components of 1133 transcription factor (TF) genes by genotyping in 192 diverse desi and kabuli chickpea accessions constituting a seed weight association panel. Integrating these SNP genotyping data with seed weight field phenotypic information of 192 structured association panel identified eight SNP alleles in the eight TF genes regulating seed weight of chickpea. The associated individual and combination of all SNPs explained 10-15 and 31% phenotypic variation for seed weight, respectively. The EcoTILLING-based large-scale allele mining and genotyping strategy implemented for association mapping is found much effective for a diploid genome crop species like chickpea with narrow genetic base and low genetic polymorphism. This optimized approach thus can be deployed for various genomics-assisted breeding applications with optimal expense of resources in domesticated chickpea. The seed weight-associated natural allelic variants and candidate TF genes delineated have potential to accelerate marker-assisted genetic improvement of chickpea.

SUBMITTER: Bajaj D

PROVIDER: S-EPMC4835497 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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EcoTILLING-Based Association Mapping Efficiently Delineates Functionally Relevant Natural Allelic Variants of Candidate Genes Governing Agronomic Traits in Chickpea.

Bajaj Deepak D Srivastava Rishi R Nath Manoj M Tripathi Shailesh S Bharadwaj Chellapilla C Upadhyaya Hari D HD Tyagi Akhilesh K AK Parida Swarup K SK

Frontiers in plant science 20160419

The large-scale mining and high-throughput genotyping of novel gene-based allelic variants in natural mapping population are essential for association mapping to identify functionally relevant molecular tags governing useful agronomic traits in chickpea. The present study employs an alternative time-saving, non-laborious and economical pool-based EcoTILLING approach coupled with agarose gel detection assay to discover 1133 novel SNP allelic variants from diverse coding and regulatory sequence co ...[more]

PMID: 27148286

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Project description:The present study used a whole-genome, NGS resequencing-based mQTL-seq (multiple QTL-seq) strategy in two inter-specific mapping populations (Pusa 1103 × ILWC 46 and Pusa 256 × ILWC 46) to scan the major genomic region(s) underlying QTL(s) governing pod number trait in chickpea. Essentially, the whole-genome resequencing of low and high pod number-containing parental accessions and homozygous individuals (constituting bulks) from each of these two mapping populations discovered >8 million high-quality homozygous SNPs with respect to the reference kabuli chickpea. The functional significance of the physically mapped SNPs was apparent from the identified 2,264 non-synonymous and 23,550 regulatory SNPs, with 8-10% of these SNPs-carrying genes corresponding to transcription factors and disease resistance-related proteins. The utilization of these mined SNPs in ? (SNP index)-led QTL-seq analysis and their correlation between two mapping populations based on mQTL-seq, narrowed down two (Caq(a)PN4.1: 867.8 kb and Caq(a)PN4.2: 1.8 Mb) major genomic regions harbouring robust pod number QTLs into the high-resolution short QTL intervals (Caq(b)PN4.1: 637.5 kb and Caq(b)PN4.2: 1.28 Mb) on chickpea chromosome 4. The integration of mQTL-seq-derived one novel robust QTL with QTL region-specific association analysis delineated the regulatory (C/T) and coding (C/A) SNPs-containing one pentatricopeptide repeat (PPR) gene at a major QTL region regulating pod number in chickpea. This target gene exhibited anther, mature pollen and pod-specific expression, including pronounced higher up-regulated (?3.5-folds) transcript expression in high pod number-containing parental accessions and homozygous individuals of two mapping populations especially during pollen and pod development. The proposed mQTL-seq-driven combinatorial strategy has profound efficacy in rapid genome-wide scanning of potential candidate gene(s) underlying trait-associated high-resolution robust QTL(s), thereby expediting genomics-assisted breeding and genetic enhancement of crop plants, including chickpea.

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Dataset Information

EcoTILLING-Based Association Mapping Efficiently Delineates Functionally Relevant Natural Allelic Variants of Candidate Genes Governing Agronomic Traits in Chickpea.

Publications

EcoTILLING-Based Association Mapping Efficiently Delineates Functionally Relevant Natural Allelic Variants of Candidate Genes Governing Agronomic Traits in Chickpea.

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