Dataset Information

Characterising root trait variability in chickpea (Cicer arietinum L.) germplasm.

ABSTRACT: Chickpea (Cicer arietinum L.) is an important grain legume crop but its sustainable production is challenged by predicted climate changes, which are likely to increase production limitations and uncertainty in yields. Characterising the variability in root architectural traits in a core collection of chickpea germplasm will provide the basis for breeding new germplasm with suitable root traits for the efficient acquisition of soil resources and adaptation to drought and other abiotic stresses. This study used a semi-hydroponic phenotyping system for assessing root trait variability across 270 chickpea genotypes. The genotypes exhibited large variation in rooting patterns and branching manner. Thirty root-related traits were characterised, 17 of which had coefficients of variation ?0.3 among genotypes and were selected for further examination. The Pearson correlation matrix showed a strong correlation among most of the selected traits (P?0.05). Principal component analysis revealed three principal components with eigenvalues >1 capturing 81.5% of the total variation. An agglomerative hierarchical clustering analysis, based on root trait variation, identified three genotype homogeneous groups (rescaled distance of 15) and 16 sub-groups (rescaled distance of 5). The chickpea genotypes characterised in this study with vastly different root properties could be used for further studies in glasshouses and field trials, and for molecular marker studies, gene mapping, and modelling simulations, ultimately aimed at breeding germplasm with root traits for improved adaptation to drought and other specific environments.

SUBMITTER: Chen Y

PROVIDER: S-EPMC5429021 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Characterising root trait variability in chickpea (Cicer arietinum L.) germplasm.

Chen Yinglong Y Ghanem Michel Edmond ME Siddique Kadambot Hm KH

Journal of experimental botany 20170401 8

Chickpea (Cicer arietinum L.) is an important grain legume crop but its sustainable production is challenged by predicted climate changes, which are likely to increase production limitations and uncertainty in yields. Characterising the variability in root architectural traits in a core collection of chickpea germplasm will provide the basis for breeding new germplasm with suitable root traits for the efficient acquisition of soil resources and adaptation to drought and other abiotic stresses. T ...[more]

PMID: 28338728

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Project description:Elucidation of the genetic basis of drought tolerance is vital for genomics-assisted breeding of drought tolerant crop varieties. Here, we used genotyping-by-sequencing (GBS) to identify single nucleotide polymorphisms (SNPs) in recombinant inbred lines (RILs) derived from a cross between a drought tolerant chickpea variety, Pusa 362 and a drought sensitive variety, SBD 377. The GBS identified a total of 35,502 SNPs and subsequent filtering of these resulted in 3237 high-quality SNPs included in the eight linkage groups. Fifty-one percent of these SNPs were located in the genic regions distributed throughout the genome. The high density linkage map has total map length of 1069 cm with an average marker interval of 0.33 cm. The linkage map was used to identify 9 robust and consistent QTLs for four drought related traits viz. membrane stability index, relative water content, seed weight and yield under drought, with percent variance explained within the range of 6.29%-90.68% and LOD scores of 2.64 to 6.38, which were located on five of the eight linkage groups. A genomic region on LG 7 harbors quantitative trait loci (QTLs) explaining > 90% phenotypic variance for membrane stability index, and > 10% PVE for yield. This study also provides the first report of major QTLs for physiological traits such as membrane stability index and relative water content for drought stress in chickpea. A total of 369 putative candidate genes were identified in the 6.6 Mb genomic region spanning these QTLs. In-silico expression profiling based on the available transcriptome data revealed that 326 of these genes were differentially expressed under drought stress. KEGG analysis resulted in reduction of candidate genes from 369 to 99, revealing enrichment in various signaling pathways. Haplotype analysis confirmed 5 QTLs among the initially identified 9 QTLs. Two QTLs, qRWC1.1 and qYLD7.1, were chosen based on high SNP density. Candidate gene-based analysis revealed distinct haplotypes in qYLD7.1 associated with significant phenotypic differences, potentially linked to pathways for secondary metabolite biosynthesis. These identified candidate genes bolster defenses through flavonoids and phenylalanine-derived compounds, aiding UV protection, pathogen resistance, and plant structure.The study provides novel genomic regions and candidate genes which can be utilized in genomics-assisted breeding of superior drought tolerant chickpea cultivars.

Dataset Information

Characterising root trait variability in chickpea (Cicer arietinum L.) germplasm.

Publications

Characterising root trait variability in chickpea (Cicer arietinum L.) germplasm.

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