Genetic Dissection of Drought and Heat Tolerance in Chickpea through Genome-Wide and Candidate Gene-Based Association Mapping Approaches

Thudi, Mahendar; Upadhyaya, Hari D.; Rathore, Abhishek; Gaur, Pooran M.; Krishnamurthy, L.; Roorkiwal, Manish; Nayak, Spurthi N.; Chaturvedi, Sushil K.; Basu, Partha; Gangarao, N. V. P. R.; Fikre, Asnake; Kimurto, Paul; Sharma, Prakash C.; Sheshashayee, M. S.; Tobita, Satoshi; Kashiwagi, Junichi; Ito, Osamu; Killian, Andrzej; Varshney, Rajeev K.

doi:10.1371/journal.pone.0096758

Cited by 201 publications

(178 citation statements)

References 44 publications

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“…In recent years, molecular mechanisms for tolerance to drought stress in plants have become an active area of investigation and many genes regulated by drought stress have been reported in a variety of plants (Sehgal et al, 2012;Thudi et al, 2014;Xu et al, 2014). Very little is known about the physiological and molecular mechanisms by which the model legume M. truncatula responds to drought stress.…”

Section: Introductionmentioning

confidence: 99%

Morph-physiological responses to water deficit in parental genotypes of Medicago truncatula recombinant inbred lines

Mahfoudh¹,

Abdelly²

2016

Afr. J. Biotechnol.

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Medicago truncatula is an omni-Mediterranean species grown as an annual forage legume. In addition to its small genome size and simple genetics, M. truncatula harbors several attributes which make it an attractive model legume. In this study, we investigated morphological and photosynthetic responses to water deficit in parental genotypes of M. truncatula recombinant inbred lines. Ten parental lines were cultivated under three water regimes (100% of field capacity (FC), 50% FC and 30% FC) and were harvested at flowering time and at the end of their lifecycle. Results from ANOVA showed that variability of measured parameters was explained by the effects of line, treatment and their interaction with treatment factor recorded the highest values. Out of the 27 traits, 14 were influenced by the line x treatment interaction. High to moderate broad-sense heritability (H²) were observed for most of the traits under control treatment and drought stress. Most of the correlations between measured traits were positive under the three water regimes. The flowering time was positively correlated with aerial and root growth rate. The tolerance of lines to water deficit seems to depend, in particular, on their ability to maintain higher photosynthetic activity. In 30% FC, principal component analysis clustered lines into two groups. The Jemalong A17 line was the least affected for most phenotypic parameters. Hence, all populations of recombinant inbred lines derived from crosses between Jemalong A17 and the remaining lines were useful for the identification of the genetic determinants for tolerance to water deficit in M. truncatula.

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Section: Introductionmentioning

confidence: 99%

Morph-physiological responses to water deficit in parental genotypes of Medicago truncatula recombinant inbred lines

Mahfoudh¹,

Abdelly²

2016

Afr. J. Biotechnol.

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“…In order to ascertain the accuracy and novelty of seven genomic loci-carrying genes for branch number regulation in chickpea (identified by their validation in natural and mapping populations), the outcomes of the present study was compared/correlated with that of previous reports [18][19][20][21][22][23]. For this, markers linked/flanking the branch number known QTLs/genes (documented in previous QTL mapping studies), were selected for their further validation in the branch number-specific natural (60 diverse desi and kabuli Cicer accessions) and mapping populations [(ICC 4958 × ICC 17160) and (ICC 12299 × ICC 8261)] constituted in the present study.…”

Section: Validation Of Bn-associated Genes In Bi-parental Mapping Popmentioning

confidence: 99%

“…The effect of branching on seed and pod yield as well as water-use efficiency is extensively studied and well documented in chickpea [17]. Only limited number of QTLs/genes regulating branch number have been identified utilizing QTL mapping and trait association analysis [18][19][20][21][22][23]. However, these identified QTLs/genes are yet to be deployed in marker-assisted selection for developing cultivars with high branch number in chickpea.…”

Section: Introductionmentioning

confidence: 99%

Identification of candidate genes for dissecting complex branch number trait in chickpea

et al. 2016

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a b s t r a c tThe present study exploited integrated genomics-assisted breeding strategy for genetic dissection of complex branch number quantitative trait in chickpea. Candidate gene-based association analysis in a branch number association panel was performed by utilizing the genotyping data of 401 SNP allelic variants mined from 27 known cloned branch number gene orthologs of chickpea. The genome-wide association study (GWAS) integrating both genome-wide GBS-(4556 SNPs) and candidate gene-based genotyping information of 4957 SNPs in a structured population of 60 sequenced desi and kabuli accessions (with 350-400 kb LD decay), detected 11 significant genomic loci (genes) associated (41% combined PVE) with branch number in chickpea. Of these, seven branch number-associated genes were further validated successfully in two inter (ICC 4958 × ICC 17160)-and intra (ICC 12299 × ICC 8261)-specific mapping populations. The axillary meristem and shoot apical meristem-specific expression, including differential up-and down-regulation (4-5 fold) of the validated seven branch number-associated genes especially in high branch number as compared to the low branch number-containing parental accessions and homozygous individuals of two aforesaid mapping populations was apparent. Collectively, this combinatorial genomic approach delineated diverse naturally occurring novel functional SNP allelic variants in seven potential known/candidate genes [PIN1 (PIN-FORMED protein 1), TB1 (teosinte branched 1), BA1/LAX1 (BARREN STALK1/LIKE AUXIN1), GRAS8 (gibberellic acid insensitive/GAI, Repressor of ga13/RGA and Scarecrow8/SCR8), ERF (ethylene-responsive element-binding factor), MAX2 (more axillary growth 2) and lipase] governing chickpea branch number. The useful information generated from this study have potential to expedite marker-assisted genetic enhancement by developing high-yielding cultivars with more number of productive (pods and seeds) branches in chickpea.

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“…However, the knowledge generated by the gene action and genetic variation for crop improvement efforts has enabled to transfer useful alleles from the desi to kabuli varieties such as ICCV2 and KAK 2. There are numerous known molecular markers linked to stress tolerance (Dita et al, 2006;Millan et al, 2006), salt tolerance (Samineni, 2010), drought tolerance (Azam et al, 2014;Kale et al, 2015), heat tolerance (Thudi et al, 2014), yield (Rehman et al, 2011) and biotic stress tolerance (Flandez-Galvez et al, 2003) in chickpea. With availability of a reference genome, the potential to map different QTL and identify the linked molecular markers facilitates the transfer of several QTL in one improved cultivar simultaneously.…”

Section: Gene Discovery and Qtl Analysismentioning

confidence: 99%

Analysis of the Chickpea genome using next generation sequencing data

Ruperao¹

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Chickpea is an annual, self-pollinating, diploid (2n=2x=16) and the second most important food legume crop with major production areas in the Indian sub-continent, West Asia and North Africa. Australia is the largest exporter of chickpea and yield for 2015 has been forecasted at 990,000 tonnes (http://www.agriculture.gov.au/abares/media-releases/2015). The main constraint for increasing yield is the susceptibility of the plant to foliar disease, ascochyta blight, fusarium wilt. Chickpea breeding aims at high yielding cultivars that combine longlasting resistance against both biotic and abiotic stress. Emerging sequencing technologies have enhanced the availability of crop genomic resources. Analysis of huge amounts of genomic data comes with major computational challenges.This thesis describes a new method for assessing the quality of reference genome assembly by flow sorting and isolating chromosomes based on size. This chromosomal DNA was sequenced and mapped to the reference genome assembly.This approach will reduce the genome DNA complexity to a chromosome level and is expect to correspond to only one chromosome assembly. Appling this approach on both released desi and kabuli reference genomes has shown miss-assembly. The desi genome was of poor quality compared to the kabuli genome. To fix these misassemblies, we developed a novel method called skimGBS for rearranging the fragmented sequences. In this approach, genotypes were called from population individuals to construct haplotype blocks. Based on the haplotype block signature, contigs/fragmented sequences were reordered as new assemblies. Using this approach, both desi and kabuli genomes were improved by placing unplaced contig sequences into chromosomes. Furthermore, these improved reference assemblieswere assessed and annotated.This thesis also reports identification of more than 800,000 high quality SNPs by sequencing 69 diverse Australian chickpea accessions. Gene loss, genetic relatedness, population structure and diversity analysis was also performed. The public accessibility of the data and above results provides a valuable resource to support chickpea research.iiThe developed methodology can also apply to other genomics studies, and will therefore be a valuable approach to assist crop improvement and further breeding approaches.iii

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Genetic Dissection of Drought and Heat Tolerance in Chickpea through Genome-Wide and Candidate Gene-Based Association Mapping Approaches

Cited by 201 publications

References 44 publications

Morph-physiological responses to water deficit in parental genotypes of Medicago truncatula recombinant inbred lines

Morph-physiological responses to water deficit in parental genotypes of Medicago truncatula recombinant inbred lines

Identification of candidate genes for dissecting complex branch number trait in chickpea

Analysis of the Chickpea genome using next generation sequencing data

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