A chickpea genetic variation map based on the sequencing of 3,366 genomes.

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.

Celebrating Professor Rajeev K. Varshney's transformative research odyssey from genomics to the field on his induction as Fellow of the Royal Society.

Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground-breaking work, especially his effort to list orphan tropical crops to genomic resource-rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape.

Delineating Marker-Trait Associations for Fusarium Wilt in Chickpea Using the Axiom® CicerSNP Array.

Fusarium wilt (FW) caused by Fusarium oxysporum f. sp. ciceri is a devastating disease of chickpea (Cicer arietinum). To identify promising resistant genotypes and genomic loci for FW resistance, a core set of 179 genotypes of chickpea was tested for FW reactions at the seedling and reproductive stages under field conditions and controlled conditions in the greenhouse. Our results revealed that at the seedling stage, most of the genotypes were resistant, whereas at the reproductive stage, most of the genotypes were susceptible. Genotyping using a 50K Axiom® CicerSNP Array and trait data of FW together led to the identification of 26 significant (P ≤ E-05) marker-trait associations (MTAs) for FW resistance. Among the 26 MTAs, 12 were identified using trait data recorded in the field (three at the seedling and nine at the reproductive stage), and 14 were identified using trait data recorded under controlled conditions in the greenhouse (six at the seedling and eight at the reproductive stage). The phenotypic variation explained by these MTAs varied from 11.75 to 15.86%, with an average of 13.77%. Five MTAs were classified as major, explaining more than 15% of the phenotypic variation for FW, and two were declared stable, being identified in two environments. One of the promising stable and major MTAs (Affx_123280060) detected in field conditions at the reproductive stage was also detected in greenhouse conditions at the seedling and reproductive stages. The stable and major (>15% PVE) MTAs can be used in chickpea breeding programs.

BSA­seq and genetic mapping reveals AhRt2 as a candidate gene responsible for red testa of peanut.

KEY MESSAGE: The candidate recessive gene AhRt2 responsible for red testa of peanut was identified through combined BSA-seq and linkage mapping approaches. The testa color of peanuts (Arachis hypogaea L.) is an important trait, and those with red testa are particularly popular owing to the high-anthocyanin content. However, the identification of genes underlying the regulation of the red testa trait in peanut are rarely reported. In order to fine map red testa gene, two F2:4 populations were constructed through the cross of YZ9102 (pink testa) with ZH12 (red testa) and ZH2 (red testa). Genetic analysis indicated that red testa was controlled by a single recessive gene named as AhRt2 (Red testa gene 2). Using BSA-seq approach, AhRt2 was preliminary identified on chromosome 12, which was further mapped to a 530-kb interval using 220 recombinant lines through linkage mapping. Furthermore, functional annotation, expression profiling, and the analyses of sequence variation confirmed that the anthocyanin reductase namely (Arahy.IK60LM) was the most likely candidate gene for AhRt2. It was found that a SNP in the third exon of AhRt2 altered the encoding amino acids, and was associated with red testa in peanut. In addition, a closely linked molecular marker linked with red testa trait in peanut was also developed for future studies. Our results provide valuable insight into the molecular mechanism underlying peanut testa color and present significant diagnostic marker resources for marker-assisted selected breeding in peanut.

SSR markers in revealing extent of genetic diversity and phylogenetic relationships among chickpea core collection accessions for Western Himalayas.

BACKGROUND: The exploration of genetic diversity is the key source of germplasm conservation and potential to broaden its genetic base. The globally growing demand for chickpea suggests superior/climate-resilient varieties, which in turn necessitates the germplasm characterization to unravel underlying genetic variation. METHODOLOGY AND RESULTS: A chickpea core collection comprising of diverse 192 accessions which include cultivated Cicer arietinum, and wild C. reticulatum, C. echinospermum, and C. microphyllum species were investigated to analyze their genetic diversity and relationship, by assaying 33 unlinked simple sequence repeat (SSR) markers. The results amplified a total of 323 alleles (Na), ranging from 2 to 8 with an average of 4.25 alleles per locus. Expected heterozygosity (He) differed from 0.46 to 0.86 with an average of 0.68. Polymorphic information content (PIC) ranged from 0.73 to 0.98 with an average of 0.89. Analysis of molecular variance (AMOVA) showed that most of the variation was among individuals (87%). Cluster analysis resulted in the formation of four distinct clusters. Cluster I represented all cultivated and clusters II, III, and IV comprised a heterogeneous group of cultivated and wild chickpea accessions. CONCLUSION: We report considerable diversity and greater resolving power of SSR markers for assessing variability and interrelationship among the chickpea accessions. The chickpea core is expected to be an efficient resource for breeders for broadening the chickpea genetic base and could be useful for selective breeding of desirable traits and in the identification of target genes for genomics-assisted breeding.

Fine mapping and gene cloning in the post-NGS era: advances and prospects.

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Integrating genomics for chickpea improvement: achievements and opportunities.

KEY MESSAGE: Integration of genomic technologies with breeding efforts have been used in recent years for chickpea improvement. Modern breeding along with low cost genotyping platforms have potential to further accelerate chickpea improvement efforts. The implementation of novel breeding technologies is expected to contribute substantial improvements in crop productivity. While conventional breeding methods have led to development of more than 200 improved chickpea varieties in the past, still there is ample scope to increase productivity. It is predicted that integration of modern genomic resources with conventional breeding efforts will help in the delivery of climate-resilient chickpea varieties in comparatively less time. Recent advances in genomics tools and technologies have facilitated the generation of large-scale sequencing and genotyping data sets in chickpea. Combined analysis of high-resolution phenotypic and genetic data is paving the way for identifying genes and biological pathways associated with breeding-related traits. Genomics technologies have been used to develop diagnostic markers for use in marker-assisted backcrossing programmes, which have yielded several molecular breeding products in chickpea. We anticipate that a sequence-based holistic breeding approach, including the integration of functional omics, parental selection, forward breeding and genome-wide selection, will bring a paradigm shift in development of superior chickpea varieties. There is a need to integrate the knowledge generated by modern genomics technologies with molecular breeding efforts to bridge the genome-to-phenome gap. Here, we review recent advances that have led to new possibilities for developing and screening breeding populations, and provide strategies for enhancing the selection efficiency and accelerating the rate of genetic gain in chickpea.

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding.

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

Toward the sequence-based breeding in legumes in the post-genome sequencing era.

Efficiency of breeding programs of legume crops such as chickpea, pigeonpea and groundnut has been considerably improved over the past decade through deployment of modern genomic tools and technologies. For instance, next-generation sequencing technologies have facilitated availability of genome sequence assemblies, re-sequencing of several hundred lines, development of HapMaps, high-density genetic maps, a range of marker genotyping platforms and identification of markers associated with a number of agronomic traits in these legume crops. Although marker-assisted backcrossing and marker-assisted selection approaches have been used to develop superior lines in several cases, it is the need of the hour for continuous population improvement after every breeding cycle to accelerate genetic gain in the breeding programs. In this context, we propose a sequence-based breeding approach which includes use of independent or combination of parental selection, enhancing genetic diversity of breeding programs, forward breeding for early generation selection, and genomic selection using sequencing/genotyping technologies. Also, adoption of speed breeding technology by generating 4-6 generations per year will be contributing to accelerate genetic gain. While we see a huge potential of the sequence-based breeding to revolutionize crop improvement programs in these legumes, we anticipate several challenges especially associated with high-quality and precise phenotyping at affordable costs, data analysis and management related to improving breeding operation efficiency. Finally, integration of improved seed systems and better agronomic packages with the development of improved varieties by using sequence-based breeding will ensure higher genetic gains in farmers' fields.

Plant vigour QTLs co-map with an earlier reported QTL hotspot for drought tolerance while water saving QTLs map in other regions of the chickpea genome.

BACKGROUND: Terminal drought stress leads to substantial annual yield losses in chickpea (Cicer arietinum L.). Adaptation to water limitation is a matter of matching water supply to water demand by the crop. Therefore, harnessing the genetics of traits contributing to plant water use, i.e. transpiration rate and canopy development dynamics, is important to design crop ideotypes suited to a varying range of water limited environments. With an aim of identifying genomic regions for plant vigour (growth and canopy size) and canopy conductance traits, 232 recombinant inbred lines derived from a cross between ICC 4958 and ICC 1882, were phenotyped at vegetative stage under well-watered conditions using a high throughput phenotyping platform (LeasyScan). RESULTS: Twenty one major quantitative trait loci (M-QTLs) were identified for plant vigour and canopy conductance traits using an ultra-high density bin map. Plant vigour traits had 13 M-QTLs on CaLG04, with favourable alleles from high vigour parent ICC 4958. Most of them co-mapped with a previously fine mapped major drought tolerance "QTL-hotspot" region on CaLG04. One M-QTL was found for canopy conductance on CaLG03 with the ultra-high density bin map. Comparative analysis of the QTLs found across different density genetic maps revealed that QTL size reduced considerably and % of phenotypic variation increased as marker density increased. CONCLUSION: Earlier reported drought tolerance hotspot is a vigour locus. The fact that canopy conductance traits, i.e. the other important determinant of plant water use, mapped on CaLG03 provides an opportunity to manipulate these loci to tailor recombinants having low/high transpiration rate and plant vigour, fitted to specific drought stress scenarios in chickpea.

Development and evaluation of high-density Axiom® CicerSNP Array for high-resolution genetic mapping and breeding applications in chickpea.

To accelerate genomics research and molecular breeding applications in chickpea, a high-throughput SNP genotyping platform 'Axiom® CicerSNP Array' has been designed, developed and validated. Screening of whole-genome resequencing data from 429 chickpea lines identified 4.9 million SNPs, from which a subset of 70 463 high-quality nonredundant SNPs was selected using different stringent filter criteria. This was further narrowed down to 61 174 SNPs based on p-convert score ≥0.3, of which 50 590 SNPs could be tiled on array. Among these tiled SNPs, a total of 11 245 SNPs (22.23%) were from the coding regions of 3673 different genes. The developed Axiom® CicerSNP Array was used for genotyping two recombinant inbred line populations, namely ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261). Genotyping data reflected high success and polymorphic rate, with 15 140 (29.93%; ICCRIL03) and 20 018 (39.57%; ICCRIL04) polymorphic SNPs. High-density genetic maps comprising 13 679 SNPs spanning 1033.67 cM and 7769 SNPs spanning 1076.35 cM were developed for ICCRIL03 and ICCRIL04 populations, respectively. QTL analysis using multilocation, multiseason phenotyping data on these RILs identified 70 (ICCRIL03) and 120 (ICCRIL04) main-effect QTLs on genetic map. Higher precision and potential of this array is expected to advance chickpea genetics and breeding applications.

Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy.

Grain legumes form an important component of the human diet, provide feed for livestock, and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress, posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the past half century. To achieve faster genetic gains in legumes in rainfed conditions, this review proposes the integration of modern genomics approaches, high throughput phenomics, and simulation modelling in support of crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval, and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experimental plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers' fields, will deliver higher genetic gains. Enhanced genetic gains, including not only productivity but also nutritional and market traits, will increase the profitability of farming and the availability of affordable nutritious food especially in developing countries.

Molecular Mapping of QTLs for Heat Tolerance in Chickpea.

Chickpea (Cicer arietinum L.), a cool-season legume, is increasingly affected by heat-stress at reproductive stage due to changes in global climatic conditions and cropping systems. Identifying quantitative trait loci (QTLs) for heat tolerance may facilitate breeding for heat tolerant varieties. The present study was aimed at identifying QTLs associated with heat tolerance in chickpea using 292 F8-9 recombinant inbred lines (RILs) developed from the cross ICC 4567 (heat sensitive) × ICC 15614 (heat tolerant). Phenotyping of RILs was undertaken for two heat-stress (late sown) and one non-stress (normal sown) environments. A genetic map spanning 529.11 cM and comprising 271 genotyping by sequencing (GBS) based single nucleotide polymorphism (SNP) markers was constructed. Composite interval mapping (CIM) analysis revealed two consistent genomic regions harbouring four QTLs each on CaLG05 and CaLG06. Four major QTLs for number of filled pods per plot (FPod), total number of seeds per plot (TS), grain yield per plot (GY) and % pod setting (%PodSet), located in the CaLG05 genomic region, were found to have cumulative phenotypic variation of above 50%. Nineteen pairs of epistatic QTLs showed significant epistatic effect, and non-significant QTL × environment interaction effect, except for harvest index (HI) and biomass (BM). A total of 25 putative candidate genes for heat-stress were identified in the two major genomic regions. This is the first report on QTLs for heat-stress response in chickpea. The markers linked to the above mentioned four major QTLs can facilitate marker-assisted breeding for heat tolerance in chickpea.

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 dissection of AP2/ERF and HSP90 gene families in five legumes and expression profiles in chickpea and pigeonpea.

APETALA2/ethylene response factor (AP2/ERF) and heat-shock protein 90 (HSP90) are two significant classes of transcription factor and molecular chaperone proteins which are known to be implicated under abiotic and biotic stresses. Comprehensive survey identified a total of 147 AP2/ERF genes in chickpea, 176 in pigeonpea, 131 in Medicago, 179 in common bean and 140 in Lotus, whereas the number of HSP90 genes ranged from 5 to 7 in five legumes. Sequence alignment and phylogenetic analyses distinguished AP2, ERF, DREB, RAV and soloist proteins, while HSP90 proteins segregated on the basis of their cellular localization. Deeper insights into the gene structure allowed ERF proteins to be classified into AP2s based on DNA-binding domains, intron arrangements and phylogenetic grouping. RNA-seq and quantitative real-time PCR (qRT-PCR) analyses in heat-stressed chickpea as well as Fusarium wilt (FW)- and sterility mosaic disease (SMD)-stressed pigeonpea provided insights into the modus operandi of AP2/ERF and HSP90 genes. This study identified potential candidate genes in response to heat stress in chickpea while for FW and SMD stresses in pigeonpea. For instance, two DREB genes (Ca_02170 and Ca_16631) and three HSP90 genes (Ca_23016, Ca_09743 and Ca_25602) in chickpea can be targeted as potential candidate genes. Similarly, in pigeonpea, a HSP90 gene, C.cajan_27949, was highly responsive to SMD in the resistant genotype ICPL 20096, can be recommended for further functional validation. Also, two DREB genes, C.cajan_41905 and C.cajan_41951, were identified as leads for further investigation in response to FW stress in pigeonpea.

QTL-seq for rapid identification of candidate genes for 100-seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea.

Terminal drought is a major constraint to chickpea productivity. Two component traits responsible for reduction in yield under drought stress include reduction in seeds size and root length/root density. QTL-seq approach, therefore, was used to identify candidate genomic regions for 100-seed weight (100SDW) and total dry root weight to total plant dry weight ratio (RTR) under rainfed conditions. Genomewide SNP profiling of extreme phenotypic bulks from the ICC 4958 × ICC 1882 population identified two significant genomic regions, one on CaLG01 (1.08 Mb) and another on CaLG04 (2.7 Mb) linkage groups for 100SDW. Similarly, one significant genomic region on CaLG04 (1.10 Mb) was identified for RTR. Comprehensive analysis revealed four and five putative candidate genes associated with 100SDW and RTR, respectively. Subsequently, two genes (Ca_04364 and Ca_04607) for 100SDW and one gene (Ca_04586) for RTR were validated using CAPS/dCAPS markers. Identified candidate genomic regions and genes may be useful for molecular breeding for chickpea improvement.

Two key genomic regions harbour QTLs for salinity tolerance in ICCV 2 × JG 11 derived chickpea (Cicer arietinum L.) recombinant inbred lines.

BACKGROUND: Although chickpea (Cicer arietinum L.), an important food legume crop, is sensitive to salinity, considerable variation for salinity tolerance exists in the germplasm. To improve any existing cultivar, it is important to understand the genetic and physiological mechanisms underlying this tolerance. RESULTS: In the present study, 188 recombinant inbred lines (RILs) derived from the cross ICCV 2 × JG 11 were used to assess yield and related traits in a soil with 0 mM NaCl (control) and 80 mM NaCl (salinity) over two consecutive years. Salinity significantly (P < 0.05) affected almost all traits across years and yield reduction was in large part related to a reduction in seed number but also a reduction in above ground biomass. A genetic map was constructed using 56 polymorphic markers (28 simple sequence repeats; SSRs and 28 single nucleotide polymorphisms; SNPs). The QTL analysis revealed two key genomic regions on CaLG05 (28.6 cM) and on CaLG07 (19.4 cM), that harboured QTLs for six and five different salinity tolerance associated traits, respectively, and imparting either higher plant vigour (on CaLG05) or higher reproductive success (on CaLG07). Two major QTLs for yield in the salinity treatment (explaining 12 and 17% of the phenotypic variation) were identified within the two key genomic regions. Comparison with already published chickpea genetic maps showed that these regions conferred salinity tolerance across two other populations and the markers can be deployed for enhancing salinity tolerance in chickpea. Based on the gene ontology annotation, forty eight putative candidate genes responsive to salinity stress were found on CaLG05 (31 genes) and CaLG07 (17 genes) in a distance of 11.1 Mb and 8.2 Mb on chickpea reference genome. Most of the genes were known to be involved in achieving osmoregulation under stress conditions. CONCLUSION: Identification of putative candidate genes further strengthens the idea of using CaLG05 and CaLG07 genomic regions for marker assisted breeding (MAB). Further fine mapping of these key genomic regions may lead to novel gene identification for salinity stress tolerance in chickpea.

Genotyping-by-sequencing based intra-specific genetic map refines a ''QTL-hotspot" region for drought tolerance in chickpea.

To enhance the marker density in the "QTL-hotspot" region, harboring several QTLs for drought tolerance-related traits identified on linkage group 04 (CaLG04) in chickpea recombinant inbred line (RIL) mapping population ICC 4958 × ICC 1882, a genotyping-by-sequencing approach was adopted. In total, 6.24 Gb data from ICC 4958, 5.65 Gb data from ICC 1882 and 59.03 Gb data from RILs were generated, which identified 828 novel single-nucleotide polymorphisms (SNPs) for genetic mapping. Together with these new markers, a high-density intra-specific genetic map was developed that comprised 1,007 marker loci spanning a distance of 727.29 cM. QTL analysis using the extended genetic map along with precise phenotyping data for 20 traits collected over one to seven seasons identified 49 SNP markers in the "QTL-hotspot" region. These efforts have refined the "QTL-hotspot" region to 14 cM. In total, 164 main-effect QTLs including 24 novel QTLs were identified. In addition, 49 SNPs integrated in the "QTL-hotspot" region were converted into cleaved amplified polymorphic sequence (CAPS) and derived CAPS (dCAPS) markers which can be used in marker-assisted breeding.

Development of DArT markers and assessment of diversity in Fusarium oxysporum f. sp. ciceris, wilt pathogen of chickpea (Cicer arietinum L.).

BACKGROUND: Fusarium oxysporum f. sp. ciceris (Foc), the causal agent of Fusarium wilt of chickpea is highly variable and frequent recurrence of virulent forms have affected chickpea production and exhausted valuable genetic resources. The severity and yield losses of Fusarium wilt differ from place to place owing to existence of physiological races among isolates. Diversity study of fungal population associated with a disease plays a major role in understanding and devising better disease control strategies. The advantages of using molecular markers to understand the distribution of genetic diversity in Foc populations is well understood. The recent development of Diversity Arrays Technology (DArT) offers new possibilities to study the diversity in pathogen population. In this study, we developed DArT markers for Foc population, analysed the genetic diversity existing within and among Foc isolates, compared the genotypic and phenotypic diversity and infer the race scenario of Foc in India. RESULTS: We report the successful development of DArT markers for Foc and their utility in genotyping of Foc collections representing five chickpea growing agro-ecological zones of India. The DArT arrays revealed a total 1,813 polymorphic markers with an average genotyping call rate of 91.16% and a scoring reproducibility of 100%. Cluster analysis, principal coordinate analysis and population structure indicated that the different isolates of Foc were partially classified based on geographical source. Diversity in Foc population was compared with the phenotypic variability and it was found that DArT markers were able to group the isolates consistent with its virulence group. A number of race-specific unique and rare alleles were also detected. CONCLUSION: The present study generated significant information in terms of pathogenic and genetic diversity of Foc which could be used further for development and deployment of region-specific resistant cultivars of chickpea. The DArT markers were proved to be a powerful diagnostic tool to study the genotypic diversity in Foc. The high number of DArT markers allowed a greater resolution of genetic differences among isolates and enabled us to examine the extent of diversity in the Foc population present in India, as well as provided support to know the changing race scenario in Foc population.