Employing genome-wide SNP discovery and genotyping strategy to extrapolate the natural allelic diversity and domestication patterns in chickpea

Genome-wide SNP discovery and population structure analysis in pepper (Capsicum annuum) using genotyping by sequencing

Background

Knowledge on population structure and genetic diversity in vegetable crops is essential for association mapping studies and genomic selection. Genotyping by sequencing (GBS) represents an innovative method for large scale SNP detection and genotyping of genetic resources. Herein we used the GBS approach for the genome-wide identification of SNPs in a collection of Capsicum spp. accessions and for the assessment of the level of genetic diversity in a subset of 222 cultivated pepper (Capsicum annum) genotypes.

Results

GBS analysis generated a total of 7,568,894 master tags, of which 43.4% uniquely aligned to the reference genome CM334. A total of 108,591 SNP markers were identified, of which 105,184 were in C. annuum accessions. In order to explore the genetic diversity of C. annuum and to select a minimal core set representing most of the total genetic variation with minimum redundancy, a subset of 222 C. annuum accessions were analysed using 32,950 high quality SNPs. Based on Bayesian and Hierarchical clustering it was possible to divide the collection into three clusters. Cluster I had the majority of varieties and landraces mainly from Southern and Northern Italy, and from Eastern Europe, whereas clusters II and III comprised accessions of different geographical origins. Considering the genome-wide genetic variation among the accessions included in cluster I, a second round of Bayesian (K = 3) and Hierarchical (K = 2) clustering was performed. These analysis showed that genotypes were grouped not only based on geographical origin, but also on fruit-related features.

Conclusions

GBS data has proven useful to assess the genetic diversity in a collection of C. annuum accessions. The high number of SNP markers, uniformly distributed on the 12 chromosomes, allowed the accessions to be distinguished according to geographical origin and fruit-related features. SNP markers and information on population structure developed in this study will undoubtedly support genome-wide association mapping studies and marker-assisted selection programs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3297-7) contains supplementary material, which is available to authorized users.

Genome-wide development and deployment of informative intron-spanning and intron-length polymorphism markers for genomics-assisted breeding applications in chickpea

The discovery and large-scale genotyping of informative gene-based markers is essential for rapid delineation of genes/QTLs governing stress tolerance and yield component traits in order to drive genetic enhancement in chickpea. A genome-wide 119169 and 110491 ISM (intron-spanning markers) from 23129 desi and 20386 kabuli protein-coding genes and 7454 in silico InDel (insertion-deletion) (1-45-bp)-based ILP (intron-length polymorphism) markers from 3283 genes were developed that were structurally and functionally annotated on eight chromosomes and unanchored scaffolds of chickpea. A much higher amplification efficiency (83%) and intra-specific polymorphic potential (86%) detected by these markers than that of other sequence-based genetic markers among desi and kabuli chickpea accessions was apparent even by a cost-effective agarose gel-based assay. The genome-wide physically mapped 1718 ILP markers assayed a wider level of functional genetic diversity (19-81%) and well-defined phylogenetics among domesticated chickpea accessions. The gene-derived 1424 ILP markers were anchored on a high-density (inter-marker distance: 0.65cM) desi intra-specific genetic linkage map/functional transcript map (ICC 4958×ICC 2263) of chickpea. This reference genetic map identified six major genomic regions harbouring six robust QTLs mapped on five chromosomes, which explained 11-23% seed weight trait variation (7.6-10.5 LOD) in chickpea. The integration of high-resolution QTL mapping with differential expression profiling detected six including one potential serine carboxypeptidase gene with ILP markers (linked tightly to the major seed weight QTLs) exhibiting seed-specific expression as well as pronounced up-regulation especially in seeds of high (ICC 4958) as compared to low (ICC 2263) seed weight mapping parental accessions. The marker information generated in the present study was made publicly accessible through a user-friendly web-resource, "Chickpea ISM-ILP Marker Database". The designing of multiple ISM and ILP markers (2-5 markers/gene) from an individual gene (transcription factor) with numerous aforementioned desirable genetic attributes can widen the user-preference to select suitable primer combination for simultaneous large-scale assaying of functional allelic variation, natural allelic diversity, molecular mapping and expression profiling of genes among chickpea accessions. This will essentially accelerate the identification of functionally relevant molecular tags regulating vital agronomic traits for genomics-assisted crop improvement by optimal resource expenses in chickpea.

Transcriptome landscape of perennial wild Cicer microphyllum uncovers functionally relevant molecular tags regulating agronomic traits in chickpea

The RNA-sequencing followed by de-novo transcriptome assembly identified 11621 genes differentially xpressed in roots vs. shoots of a wild perennial Cicer microphyllum. Comparative analysis of transcriptomes between microphyllum and cultivated desi cv. ICC4958 detected 12772 including 3242 root- and 1639 shoot-specific microphyllum genes with 85% expression validation success rate. Transcriptional reprogramming of microphyllum root-specific genes implicates their possible role in regulating differential natural adaptive characteristics between wild and cultivated chickpea. The transcript-derived 5698 including 282 in-silico polymorphic SSR and 127038 SNP markers annotated at a genome-wide scale exhibited high amplification and polymorphic potential among cultivated (desi and kabuli) and wild accessions suggesting their utility in chickpea genomics-assisted breeding applications. The functional significance of markers was assessed based on their localization in non-synonymous coding and regulatory regions of microphyllum root-specific genes differentially expressed predominantly in ICC 4958 roots under drought stress. A high-density 490 genic SSR- and SNP markers-anchored genetic linkage map identified six major QTLs regulating drought tolerance-related traits, yield per plant and harvest-index in chickpea. The integration of high-resolution QTL mapping with comparative transcriptome profiling delineated five microphyllum root-specific genes with non-synonymous and regulatory SNPs governing drought-responsive yield traits. Multiple potential key regulators and functionally relevant molecular tags delineated can drive translational research and drought tolerance-mediated chickpea genetic enhancement.

Exploring Genetic Diversity in Plants Using High-Throughput Sequencing Techniques

Food security has emerged as an urgent concern because of the rising world population. To meet the food demands of the near future, it is required to improve the productivity of various crops, not just of staple food crops. The genetic diversity among plant populations in a given species allows the plants to adapt to various environmental conditions. Such diversity could therefore yield valuable traits that could overcome the food-security challenges. To explore genetic diversity comprehensively and to rapidly identify useful genes and/or allele, advanced high-throughput sequencing techniques, also called next-generation sequencing (NGS) technologies, have been developed. These provide practical solutions to the challenges in crop genomics. Here, we review various sources of genetic diversity in plants, newly developed genetic diversity-mining tools synergized with NGS techniques, and related genetic approaches such as quantitative trait locus analysis and genome-wide association study.

Genotyping by Sequencing (GBS) in Apricots and Genetic Diversity Assessment with GBS-Derived Single-Nucleotide Polymorphisms (SNPs)

Genotyping by sequencing (GBS), which is a highly promising technique for molecular breeding, has been implemented in apricots, including Turkish, European, and Plum Pox Virus-resistant accessions. DNA samples were digested with the ApeKI restriction enzyme to construct a genome-complexity-reduced 90-plex GBS library. After filtering the raw sequences, approximately 28 G of clean data were generated, and 17,842 high-quality single-nucleotide polymorphism (SNP) loci were discovered. A total of 561 SNP loci with 0 or 1 missing reads for the 90 accessions produced 1162 markers that were used for the cluster and population structure analysis of the same collection. The results of the SNP analysis indicated that the relation of the European accessions with the western Turkish apricots was accurately positioned. The resistant accessions from different sources were clustered together, confirming the previous finding that SEO/Harlayne-type resistance probably originated from the same source. The Malatya accessions produce most of the world's dried apricots and are likely to be a genetically distinct group. Simple sequence repeat (SSR) and self-incompatibly (SI) locus characterization of the accessions was also included. SI genotyping supported the SNP findings, demonstrating both the reliability of SNP genotyping and the usefulness of SI genotyping for understanding the history of apricot breeding. The SSR genotyping revealed a characterization similar to that of SNP genotyping with a slightly lower resolution in the dendrogram. In conclusion, the GBS approach was validated in apricots, with the discovery of a large number of SNPs, and was demonstrated to be reliable by fingerprinting the accessions in a more informative manner.

Identification of candidate genes and natural allelic variants for QTLs governing plant height in chickpea

In the present study, molecular mapping of high-resolution plant height QTLs was performed by integrating 3625 desi genome-derived GBS (genotyping-by-sequencing)-SNPs on an ultra-high resolution intra-specific chickpea genetic linkage map (dwarf/semi-dwarf desi cv. ICC12299 x tall kabuli cv. ICC8261). The identified six major genomic regions harboring six robust QTLs (11.5-21.3 PVE), associated with plant height, were mapped within <0.5 cM average marker intervals on six chromosomes. Five SNPs-containing genes tightly linked to the five plant height QTLs, were validated based upon their high potential for target trait association (12.9-20.8 PVE) in 65 desi and kabuli chickpea accessions. The vegetative tissue-specific expression, including higher differential up-regulation (>5-fold) of five genes especially in shoot, young leaf, shoot apical meristem of tall mapping parental accession (ICC8261) as compared to that of dwarf/semi-dwarf parent (ICC12299) was apparent. Overall, combining high-resolution QTL mapping with genetic association analysis and differential expression profiling, delineated natural allelic variants in five candidate genes (encoding cytochrome-c-biosynthesis protein, malic oxidoreductase, NADH dehydrogenase iron-sulfur protein, expressed protein and bZIP transcription factor) regulating plant height in chickpea. These molecular tags have potential to dissect complex plant height trait and accelerate marker-assisted genetic enhancement for developing cultivars with desirable plant height ideotypes in chickpea.

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

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.

Genetic dissection of seed-iron and zinc concentrations in chickpea

The SNP-based high-resolution QTL mapping mapped eight major genomic regions harbouring robust QTLs governing seed-Fe and Zn concentrations (39.4% combined phenotypic variation explained/PVE) on six chromosomes of an intra-specific high-density genetic linkage map (1.56 cM map-density). 24620 SNPs discovered from genome-wide GBS (genotyping-by-sequencing) and 13 known cloned Fe and Zn contents-related chickpea gene-orthologs were genotyped in a structured population of 92 sequenced desi and kabuli accessions. The large-scale 16591 SNP genotyping- and phenotyping-based GWAS (genome-wide association study) identified 16 genomic loci/genes associated (29% combined PVE) with seed-Fe and Zn concentrations. Of these, 11 trait-associated SNPs in the genes linked tightly with eight QTLs were validated by QTL mapping. The seed-specific expression, including pronounced differential-regulation of 16 trait-associated genes particularly in accessions/mapping individuals with contrasting level of seed-Fe and Zn contents was apparent. Collectively, the aforementioned rapid integrated genomic strategy led to delineate novel functional non-synonymous and regulatory SNP allelic-variants from 16 known/candidate genes, including three strong trait-associated genes (encoding late embryogenesis abundant and yellow stripe-like 1 protein, and vacuolar protein sorting-associated protein) and eight major QTLs regulating seed-Fe and Zn concentrations in chickpea. These essential inputs thus have potential to be deployed in marker-assisted genetic enhancement for developing nutritionally-rich iron/zinc-biofortified chickpea cultivars.

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

The 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.

An Integrated Genomic Strategy Delineates Candidate Mediator Genes Regulating Grain Size and Weight in Rice

The present study deployed a Mediator (MED) genes-mediated integrated genomic strategy for understanding the complex genetic architecture of grain size/weight quantitative trait in rice. The targeted multiplex amplicon resequencing of 55 MED genes annotated from whole rice genome in 384 accessions discovered 3971 SNPs, which were structurally and functionally annotated in diverse coding and non-coding sequence-components of genes. Association analysis, using the genotyping information of 3971 SNPs in a structured population of 384 accessions (with 50–100 kb linkage disequilibrium decay), detected 10 MED gene-derived SNPs significantly associated (46% combined phenotypic variation explained) with grain length, width and weight in rice. Of these, one strong grain weight-associated non-synonymous SNP (G/A)-carrying OsMED4_2 gene was validated successfully in low- and high-grain weight parental accessions and homozygous individuals of a rice mapping population. The seed-specific expression, including differential up/down-regulation of three grain size/weight-associated MED genes (including OsMED4_2) in six low and high-grain weight rice accessions was evident. Altogether, combinatorial genomic approach involving haplotype-based association analysis delineated diverse functionally relevant natural SNP-allelic variants in 10 MED genes, including three potential novel SNP haplotypes in an OsMED4_2 gene governing grain size/weight differentiation in rice. These molecular tags have potential to accelerate genomics-assisted crop improvement in rice.

Whole genome re-sequencing reveals genome-wide variations among parental lines of 16 mapping populations in chickpea (Cicer arietinum L.)

BACKGROUND

Chickpea (Cicer arietinum L.) is the second most important grain legume cultivated by resource poor farmers in South Asia and Sub-Saharan Africa. In order to harness the untapped genetic potential available for chickpea improvement, we re-sequenced 35 chickpea genotypes representing parental lines of 16 mapping populations segregating for abiotic (drought, heat, salinity), biotic stresses (Fusarium wilt, Ascochyta blight, Botrytis grey mould, Helicoverpa armigera) and nutritionally important (protein content) traits using whole genome re-sequencing approach.

RESULTS

A total of 192.19 Gb data, generated on 35 genotypes of chickpea, comprising 973.13 million reads, with an average sequencing depth of ~10 X for each line. On an average 92.18 % reads from each genotype were aligned to the chickpea reference genome with 82.17 % coverage. A total of 2,058,566 unique single nucleotide polymorphisms (SNPs) and 292,588 Indels were detected while comparing with the reference chickpea genome. Highest number of SNPs were identified on the Ca4 pseudomolecule. In addition, copy number variations (CNVs) such as gene deletions and duplications were identified across the chickpea parental genotypes, which were minimum in PI 489777 (1 gene deletion) and maximum in JG 74 (1,497). A total of 164,856 line specific variations (144,888 SNPs and 19,968 Indels) with the highest percentage were identified in coding regions in ICC 1496 (21 %) followed by ICCV 97105 (12 %). Of 539 miscellaneous variations, 339, 138 and 62 were inter-chromosomal variations (CTX), intra-chromosomal variations (ITX) and inversions (INV) respectively.

CONCLUSION

Genome-wide SNPs, Indels, CNVs, PAVs, and miscellaneous variations identified in different mapping populations are a valuable resource in genetic research and helpful in locating genes/genomic segments responsible for economically important traits. Further, the genome-wide variations identified in the present study can be used for developing high density SNP arrays for genetics and breeding applications.

Genome-Wide Scans for Delineation of Candidate Genes Regulating Seed-Protein Content in Chickpea

Identification of potential genes/alleles governing complex seed-protein content (SPC) is essential in marker-assisted breeding for quality trait improvement of chickpea. Henceforth, the present study utilized an integrated genomics-assisted breeding strategy encompassing trait association analysis, selective genotyping in traditional bi-parental mapping population and differential expression profiling for the first-time to understand the complex genetic architecture of quantitative SPC trait in chickpea. For GWAS (genome-wide association study), high-throughput genotyping information of 16376 genome-based SNPs (single nucleotide polymorphism) discovered from a structured population of 336 sequenced desi and kabuli accessions [with 150-200 kb LD (linkage disequilibrium) decay] was utilized. This led to identification of seven most effective genomic loci (genes) associated [10-20% with 41% combined PVE (phenotypic variation explained)] with SPC trait in chickpea. Regardless of the diverse desi and kabuli genetic backgrounds, a comparable level of association potential of the identified seven genomic loci with SPC trait was observed. Five SPC-associated genes were validated successfully in parental accessions and homozygous individuals of an intra-specific desi RIL (recombinant inbred line) mapping population (ICC 12299 × ICC 4958) by selective genotyping. The seed-specific expression, including differential up-regulation (>four fold) of six SPC-associated genes particularly in accessions, parents and homozygous individuals of the aforementioned mapping population with a high level of contrasting SPC (21-22%) was evident. Collectively, the integrated genomic approach delineated diverse naturally occurring novel functional SNP allelic variants in six potential candidate genes regulating SPC trait in chickpea. Of these, a non-synonymous SNP allele-carrying zinc finger transcription factor gene exhibiting strong association with SPC trait was found to be the most promising in chickpea. The informative functionally relevant molecular tags scaled-down essentially have potential to accelerate marker-assisted genetic improvement by developing nutritionally rich chickpea cultivars with enhanced SPC.

A High-Resolution InDel (Insertion-Deletion) Markers-Anchored Consensus Genetic Map Identifies Major QTLs Governing Pod Number and Seed Yield in Chickpea

Development and large-scale genotyping of user-friendly informative genome/gene-derived InDel markers in natural and mapping populations is vital for accelerating genomics-assisted breeding applications of chickpea with minimal resource expenses. The present investigation employed a high-throughput whole genome next-generation resequencing strategy in low and high pod number parental accessions and homozygous individuals constituting the bulks from each of two inter-specific mapping populations [(Pusa 1103 × ILWC 46) and (Pusa 256 × ILWC 46)] to develop non-erroneous InDel markers at a genome-wide scale. Comparing these high-quality genomic sequences, 82,360 InDel markers with reference to kabuli genome and 13,891 InDel markers exhibiting differentiation between low and high pod number parental accessions and bulks of aforementioned mapping populations were developed. These informative markers were structurally and functionally annotated in diverse coding and non-coding sequence components of genome/genes of kabuli chickpea. The functional significance of regulatory and coding (frameshift and large-effect mutations) InDel markers for establishing marker-trait linkages through association/genetic mapping was apparent. The markers detected a greater amplification (97%) and intra-specific polymorphic potential (58-87%) among a diverse panel of cultivated desi, kabuli, and wild accessions even by using a simpler cost-efficient agarose gel-based assay implicating their utility in large-scale genetic analysis especially in domesticated chickpea with narrow genetic base. Two high-density inter-specific genetic linkage maps generated using aforesaid mapping populations were integrated to construct a consensus 1479 InDel markers-anchored high-resolution (inter-marker distance: 0.66 cM) genetic map for efficient molecular mapping of major QTLs governing pod number and seed yield per plant in chickpea. Utilizing these high-density genetic maps as anchors, three major genomic regions harboring each of pod number and seed yield robust QTLs (15-28% phenotypic variation explained) were identified on chromosomes 2, 4, and 6. The integration of genetic and physical maps at these QTLs mapped on chromosomes scaled-down the long major QTL intervals into high-resolution short pod number and seed yield robust QTL physical intervals (0.89-2.94 Mb) which were essentially got validated in multiple genetic backgrounds of two chickpea mapping populations. The genome-wide InDel markers including natural allelic variants and genomic loci/genes delineated at major six especially in one colocalized novel congruent robust pod number and seed yield robust QTLs mapped on a high-density consensus genetic map were found most promising in chickpea. These functionally relevant molecular tags can drive marker-assisted genetic enhancement to develop high-yielding cultivars with increased seed/pod number and yield in chickpea.

Three Rice NAC Transcription Factors Heteromerize and Are Associated with Seed Size

NACs are plant-specific transcription factors (TFs) involved in multiple aspects of development and stress. In rice, three NAC TF encoding genes, namely ONAC020, ONAC026, and ONAC023 express specifically during seed development, at extremely high levels. They exhibit significantly strong association with seed size/weight with the sequence variations located in the upstream regulatory region. Concomitantly, their expression pattern/levels during seed development vary amongst different accessions with variation in seed size. The alterations in the promoter sequences of the three genes, amongst the five rice accessions, correlate with the expression levels to a certain extent only. In terms of transcriptional properties, the three NAC TFs can activate and/or suppress downstream genes, though to different extents. Only ONAC026 is localized to the nucleus while ONAC020 and ONAC023 are targeted to the ER and cytoplasm, respectively. Interestingly, these two proteins interact with ONAC026 and the dimers localize in the nucleus. Trans-splicing between ONAC020 and ONAC026 results in three additional forms of ONAC020. The transcriptional properties including activation, repression, subcellular localization and heterodimerization of trans-spliced forms of ONAC020 and ONAC026 are different, indicating toward their role as competitors. The analysis presented in this paper helps to conclude that the three NAC genes, which are associated with seed size, have independent as well as overlapping roles during the process and can be exploited as potential targets for crop improvement.

mQTL-seq delineates functionally relevant candidate gene harbouring a major QTL regulating pod number in chickpea

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 Δ (SNP index)-led QTL-seq analysis and their correlation between two mapping populations based on mQTL-seq, narrowed down two (Caq^aPN4.1: 867.8 kb and Caq^aPN4.2: 1.8 Mb) major genomic regions harbouring robust pod number QTLs into the high-resolution short QTL intervals (Caq^bPN4.1: 637.5 kb and Caq^bPN4.2: 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.

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

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.

Genome-wide insertion-deletion (InDel) marker discovery and genotyping for genomics-assisted breeding applications in chickpea

We developed 21,499 genome-wide insertion-deletion (InDel) markers (2- to 54-bp in silico fragment length polymorphism) by comparing the genomic sequences of four (desi, kabuli and wild C. reticulatum) chickpea [Cicer arietinum (L.)] accessions. InDel markers showing 2- to 6-bp fragment length polymorphism among accessions were abundant (76.8%) in the chickpea genome. The physically mapped 7,643 and 13,856 markers on eight chromosomes and unanchored scaffolds, respectively, were structurally and functionally annotated. The 4,506 coding (23% large-effect frameshift mutations) and regulatory InDel markers were identified from 3,228 genes (representing 11.7% of total 27,571 desi genes), suggesting their functional relevance for trait association/genetic mapping. High amplification (97%) and intra-specific polymorphic (60-83%) potential and wider genetic diversity (15-89%) were detected by genome-wide 6,254 InDel markers among desi, kabuli and wild accessions using even a simpler cost-effective agarose gel-based assay. This signifies added advantages of this user-friendly genetic marker system for manifold large-scale genotyping applications in laboratories with limited infrastructure and resources. Utilizing 6,254 InDel markers-based high-density (inter-marker distance: 0.212 cM) inter-specific genetic linkage map (ICC 4958 × ICC 17160) of chickpea as a reference, three major genomic regions harboring six flowering and maturity time robust QTLs (16.4-27.5% phenotypic variation explained, 8.1-11.5 logarithm of odds) were identified. Integration of genetic and physical maps at these target QTL intervals mapped on three chromosomes delineated five InDel markers-containing candidate genes tightly linked to the QTLs governing flowering and maturity time in chickpea. Taken together, our study demonstrated the practical utility of developing and high-throughput genotyping of such beneficial InDel markers at a genome-wide scale to expedite genomics-assisted breeding applications in chickpea.

An advanced draft genome assembly of a desi type chickpea (Cicer arietinum L.)

Chickpea (Cicer arietinum L.) is an important pulse legume crop. We previously reported a draft genome assembly of the desi chickpea cultivar ICC 4958. Here we report an advanced version of the ICC 4958 genome assembly (version 2.0) generated using additional sequence data and an improved genetic map. This resulted in 2.7-fold increase in the length of the pseudomolecules and substantial reduction of sequence gaps. The genome assembly covered more than 94% of the estimated gene space and predicted the presence of 30,257 protein-coding genes including 2230 and 133 genes encoding potential transcription factors (TF) and resistance gene homologs, respectively. Gene expression analysis identified several TF and chickpea-specific genes with tissue-specific expression and displayed functional diversification of the paralogous genes. Pairwise comparison of pseudomolecules in the desi (ICC 4958) and the earlier reported kabuli (CDC Frontier) chickpea assemblies showed an extensive local collinearity with incongruity in the placement of large sequence blocks along the linkage groups, apparently due to use of different genetic maps. Single nucleotide polymorphism (SNP)-based mining of intra-specific polymorphism identified more than four thousand SNPs differentiating a desi group and a kabuli group of chickpea genotypes.

A genome-wide SNP scan accelerates trait-regulatory genomic loci identification in chickpea

We identified 44844 high-quality SNPs by sequencing 92 diverse chickpea accessions belonging to a seed and pod trait-specific association panel using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays. A GWAS (genome-wide association study) in an association panel of 211, including the 92 sequenced accessions, identified 22 major genomic loci showing significant association (explaining 23-47% phenotypic variation) with pod and seed number/plant and 100-seed weight. Eighteen trait-regulatory major genomic loci underlying 13 robust QTLs were validated and mapped on an intra-specific genetic linkage map by QTL mapping. A combinatorial approach of GWAS, QTL mapping and gene haplotype-specific LD mapping and transcript profiling uncovered one superior haplotype and favourable natural allelic variants in the upstream regulatory region of a CesA-type cellulose synthase (Ca_Kabuli_CesA3) gene regulating high pod and seed number/plant (explaining 47% phenotypic variation) in chickpea. The up-regulation of this superior gene haplotype correlated with increased transcript expression of Ca_Kabuli_CesA3 gene in the pollen and pod of high pod/seed number accession, resulting in higher cellulose accumulation for normal pollen and pollen tube growth. A rapid combinatorial genome-wide SNP genotyping-based approach has potential to dissect complex quantitative agronomic traits and delineate trait-regulatory genomic loci (candidate genes) for genetic enhancement in crop plants, including chickpea.