Genome-wide high-throughput SNP discovery and genotyping for understanding natural (functional) allelic diversity and domestication patterns in wild chickpea

Advancing Chickpea Breeding: Omics Insights for Targeted Abiotic Stress Mitigation and Genetic Enhancement

Chickpea is a major source of proteins and is considered the most economically vital food legume. Chickpea production is threatened by several abiotic and biotic factors worldwide. The main constraints limiting worldwide chickpea production are abiotic conditions such as drought, heat, salinity, and cold. It is clear that chickpea is treasured for its nutritive value, in particular its high protein content, and hence study of problems like drought, cold and salinity stresses are very important concerning chickpeas. In this regard, several physiological, biochemical, and molecular mechanisms are reviewed to confer tolerance to abiotic stress. The most crippling economic losses in agriculture occur due to these abiotic stressors, which affect plants in many ways. All these abiotic stresses affect the water relations of the plant, both at the cellular level as well as the whole-plant level, causing both specific and non-specific reactions, damage and adaptation reactions. These stresses share common features. Breeding programs use a huge collection of over 100,000 chickpea accessions as their foundation. Significant advancements in conventional breeding, including mutagenesis, gene/allele introgression, and germplasm introduction, have been made through this method. Abiotic tolerance and yield component selection are made easier by creating unique DNA markers for the genus Cicer, which has been made possible by developments in high-throughput sequencing and molecular biology. Transcriptomics, proteomics, and metabolomics have also made it possible to identify particular genes, proteins, and metabolites linked to chickpea tolerance to abiotic stress. Chickpea abiotic stress tolerance has been directly and potentially improved by biotechnological applications, which are covered by all 'Omics' approaches. It requires information on the abiotic stress response at the different molecular levels, which comprises gene expression analysis for metabolites or proteins and its impact on phenotype. Studies on chickpea genome-wide expression profiling have been conducted to determine important candidate genes and their regulatory networks for abiotic stress response. This study aimed to offer a detailed overview of the diverse 'Omics' approaches for resilience's to abiotic stresses on chickpea plants.

Genome-wide association study of salt tolerance at the seed germination stage in lettuce

Developing lettuce varieties with salt tolerance at the seed germination stage is essential since lettuce seeds are planted half an inch deep in soil where salt levels are often highest in the salinity-affected growing regions. Greater knowledge of genetics and genomics of salt tolerance in lettuce will facilitate breeding of improved lettuce varieties with salt tolerance. Accordingly, we conducted a genome-wide association study (GWAS) in lettuce to identify marker-trait association for salt tolerance at the seed germination stage. The study involved 445 diverse lettuce accessions and 56,820 single nucleotide polymorphism (SNP) markers obtained through genotype-by-sequencing technology using lettuce reference genome version v8. GWAS using two single-locus and three multi-locus models for germination rate (GR) under salinity stress, 5 days post seeding (GR5d_S) and a salinity susceptibility index (SSI) based on GR under salinity stress and control conditions, 5 days post seeding (SSI_GR5d) revealed 10 significant SNPs on lettuce chromosomes 2, 4, and 7. The 10 SNPs were associated with five novel QTLs for salt tolerance in lettuce, explaining phenotyping variations of 5.85%, 4.38%, 4.26%, 3.77%, and 1.80%, indicating the quantitative nature of these two salt tolerance-related traits. Using the basic local alignment search tool (BLAST) within 100 Kb upstream and downstream of each of the 10 SNPs, we identified 25 salt tolerance-related putative candidate genes including four genes encoding for major transcription factors. The 10 significant salt tolerance-related SNPs and the 25 candidate genes identified in the current study will be a valuable resource for molecular marker development and marker-assisted selection for breeding lettuce varieties with improved salt tolerance at the seed germination stage.

Genome-wide association study reveals SNP markers controlling drought tolerance and related agronomic traits in chickpea across multiple environments

Chickpea, renowned for its exceptional nutritional value, stands as a crucial crop, serving as a dietary staple in various parts of the world. However, its productivity faces a significant challenge in the form of drought stress. This challenge highlights the urgent need to find genetic markers linked to drought tolerance for effective breeding programs. The primary objective of this study is to identify genetic markers associated with drought tolerance to facilitate effective breeding programs. To address this, we cultivated 185 chickpea accessions in two distinct locations in Lebanon over a two-year period, subjecting them to both irrigated and rain-fed environments. We assessed 11 drought-linked traits, including morphology, growth, yield, and tolerance score. SNP genotyping revealed 1344 variable SNP markers distributed across the chickpea genome. Genetic diversity across populations originating from diverse geographic locations was unveiled by the PCA, clustering, and structure analysis indicating that these genotypes have descend from five or four distinct ancestors. A genome-wide association study (GWAS) revealed several marker trait associations (MTAs) associated with the traits evaluated. Within the rainfed conditions, 11 significant markers were identified, each associated with distinct chickpea traits. Another set of 11 markers exhibited associations in both rainfed and irrigated environments, reflecting shared genetic determinants across these conditions for the same trait. The analysis of linkage disequilibrium (LD) highlighted two genomic regions with notably strong LD, suggesting significant interconnections among several investigated traits. This was further investigated by the correlation between major markers associated with these traits. Gene annotation of the identified markers has unveiled insights into 28 potential genes that play a role in influencing various chickpea drought-linked traits. These traits encompass crucial aspects such as blooming organ development, plant growth, seed weight, starch metabolism, drought regulation, and height index. Among the identified genes are CPN60-2, hsp70, GDSL(GELP), AHL16, NAT3, FAB1B, bZIP, and GL21. These genes collectively contribute to the multifaceted response of chickpea plants to drought stress. Our identified genetic factors exert their influence in both irrigated and rainfed environments, emphasizing their importance in shaping chickpea characteristics.

Novel Alleles from Cicer reticulatum L. for Genetic Improvement of Cultivated Chickpeas Identified through Genome Wide Association Analysis

The availability of wild chickpea (Cicer reticulatum L.) accessions has the potential to be used for the improvement of important traits in cultivated chickpeas. The main objectives of this study were to evaluate the phenotypic and genetic variations of chickpea progeny derived from interspecific crosses between C. arietinum and C. reticulatum, and to establish the association between single nucleotide polymorphism (SNP) markers and a series of important agronomic traits in chickpea. A total of 486 lines derived from interspecific crosses between C. arietinum (CDC Leader) and 20 accessions of C. reticulatum were evaluated at different locations in Saskatchewan, Canada in 2017 and 2018. Significant variations were observed for seed weight per plant, number of seeds per plant, thousand seed weight, and plant biomass. Path coefficient analysis showed significant positive direct effects of the number of seeds per plant, thousand seed weight, and biomass on the total seed weight. Cluster analysis based on the agronomic traits generated six groups that allowed the identification of potential heterotic groups within the interspecific lines for yield improvement and resistance to ascochyta blight disease. Genotyping of the 381 interspecific lines using a modified genotyping by sequencing (tGBS) generated a total of 14,591 SNPs. Neighbour-joining cluster analysis using the SNP data grouped the lines into 20 clusters. The genome wide association analysis identified 51 SNPs that had significant associations with different traits. Several candidate genes associated with early flowering and yield components were identified. The candidate genes and the significant SNP markers associated with different traits have a potential to aid the trait introgression in the breeding program.

Association mapping in bambara groundnut [Vigna subterranea (L.) Verdc.] reveals loci associated with agro-morphological traits

BACKGROUND

Genome-wide association studies (GWAS) are important for the acceleration of crop improvement through knowledge of marker-trait association (MTA). This report used DArT SNP markers to successfully perform GWAS on agro-morphological traits using 270 bambara groundnut [Vigna subterranea (L.) Verdc.] landraces sourced from diverse origins. The study aimed to identify marker traits association for nine agronomic traits using GWAS and their candidate genes. The experiment was conducted at two different locations laid out in alpha lattice design. The cowpea [Vigna unguiculata (L.) Walp.] reference genome (i.e. legume genome most closely related to bambara groundnut) assisted in the identification of candidate genes.

RESULTS

The analyses showed that linkage disequilibrium was found to decay rapidly with an average genetic distance of 148 kb. The broadsense heritability was relatively high and ranged from 48.39% (terminal leaf length) to 79.39% (number of pods per plant). The GWAS identified a total of 27 significant marker-trait associations (MTAs) for the nine studied traits explaining 5.27% to 24.86% of phenotypic variations. Among studied traits, the highest number of MTAs was obtained from seed coat colour (6) followed by days to flowering (5), while the least is days to maturity (1), explaining 5.76% to 11.03%, 14.5% to 19.49%, and 11.66% phenotypic variations, respectively. Also, a total of 17 candidate genes were identified, varying in number for different traits; seed coat colour (6), days to flowering (3), terminal leaf length (2), terminal leaf width (2), number of seed per pod (2), pod width (1) and days to maturity (1).

CONCLUSION

These results revealed the prospect of GWAS in identification of SNP variations associated with agronomic traits in bambara groundnut. Also, its present new opportunity to explore GWAS and marker assisted strategies in breeding of bambara groundnut for acceleration of the crop improvement.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Genome-wide analysis suggests the potential role of lncRNAs during seed development and seed size/weight determination in chickpea

The integrated transcriptome data analyses suggested the plausible roles of lncRNAs during seed development in chickpea. The candidate lncRNAs associated with QTLs and those involved in miRNA-mediated seed size/weight determination in chickpea have been identified. Long non-coding RNAs (lncRNAs) are important regulators of various biological processes. Here, we identified lncRNAs at seven successive stages of seed development in small-seeded and large-seeded chickpea cultivars. In total, 4751 lncRNAs implicated in diverse biological processes were identified. Most of lncRNAs were conserved between the two cultivars, whereas only a few of them were conserved in other plants, suggesting their species-specificity. A large number of lncRNAs differentially expressed between the two chickpea cultivars associated with seed development-related processes were identified. The lncRNAs acting as precursors of miRNAs and those mimicking target protein-coding genes of miRNAs involved in seed size/weight determination, including HAIKU1, BIG SEEDS1, and SHB1, were also revealed. Further, lncRNAs located within seed size/weight associated quantitative trait loci were also detected. Overall, we present a comprehensive resource and identified candidate lncRNAs that may play important roles during seed development and seed size/weight determination in chickpea.

Exploring Chickpea Germplasm Diversity for Broadening the Genetic Base Utilizing Genomic Resourses

Legume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%–24% protein, 41%–51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in “Omics” sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas.

A Comprehensive Review on Chickpea (Cicer arietinum L.) Breeding for Abiotic Stress Tolerance and Climate Change Resilience

Chickpea is one of the most important pulse crops worldwide, being an excellent source of protein. It is grown under rain-fed conditions averaging yields of 1 t/ha, far from its potential of 6 t/ha under optimum conditions. The combined effects of heat, cold, drought, and salinity affect species productivity. In this regard, several physiological, biochemical, and molecular mechanisms are reviewed to confer tolerance to abiotic stress. A large collection of nearly 100,000 chickpea accessions is the basis of breeding programs, and important advances have been achieved through conventional breeding, such as germplasm introduction, gene/allele introgression, and mutagenesis. In parallel, advances in molecular biology and high-throughput sequencing have allowed the development of specific molecular markers for the genus Cicer, facilitating marker-assisted selection for yield components and abiotic tolerance. Further, transcriptomics, proteomics, and metabolomics have permitted the identification of specific genes, proteins, and metabolites associated with tolerance to abiotic stress of chickpea. Furthermore, some promising results have been obtained in studies with transgenic plants and with the use of gene editing to obtain drought-tolerant chickpea. Finally, we propose some future lines of research that may be useful to obtain chickpea genotypes tolerant to abiotic stress in a scenario of climate change.

Genome-Wide Association Analysis for Phosphorus Use Efficiency Traits in Mungbean (Vigna radiata L. Wilczek) Using Genotyping by Sequencing Approach

Mungbean (Vigna radiata L. Wilczek) is an annual grain legume crop affected by low availability of phosphorus. Phosphorus deficiency mainly affects the growth and development of plants along with changes in root morphology and increase in root-to-shoot ratio. Deciphering the genetic basis of phosphorus use efficiency (PUE) traits can benefit our understanding of mungbean tolerance to low-phosphorus condition. To address this issue, 144 diverse mungbean genotypes were evaluated for 12 PUE traits under hydroponics with optimum- and low-phosphorus levels. The broad sense heritability of traits ranged from 0.63 to 0.92 and 0.58 to 0.92 under optimum- and low-phosphorus conditions, respectively. This study, reports for the first time such a large number of genome wide Single nucleotide polymorphisms (SNPs) (76,160) in mungbean. Further, genome wide association study was conducted using 55,634 SNPs obtained by genotyping-by-sequencing method. The results indicated that total 136 SNPs shared by both GLM and MLM models were associated with tested PUE traits under different phosphorus regimes. We have identified SNPs with highest p value (-log10(p)) for some traits like, TLA and RDW with p value (-log10(p)) of more than 6.0 at LP/OP and OP condition. We have identified nine SNPs (three for TLA and six for RDW trait) which was found to be present in chromosomes 8, 4, and 7. One SNP present in Vradi07g06230 gene contains zinc finger CCCH domain. In total, 71 protein coding genes were identified, of which 13 genes were found to be putative candidate genes controlling PUE by regulating nutrient uptake and root architectural development pathways in mungbean. Moreover, we identified three potential candidate genes VRADI11G08340, VRADI01G05520, and VRADI04G10750 with missense SNPs in coding sequence region, which results in significant variation in protein structure at tertiary level. The identified SNPs and candidate genes provide the essential information for genetic studies and marker-assisted breeding program for improving low-phosphorus tolerance in mungbean.

Genome-Wide SNP Discovery and Mapping QTLs for Seed Iron and Zinc Concentrations in Chickpea (Cicer arietinum L.)

Biofortification through plant breeding is a cost-effective and sustainable approach towards addressing micronutrient malnutrition prevailing across the globe. Screening cultivars for micronutrient content and identification of quantitative trait loci (QTLs)/genes and markers help in the development of biofortified varieties in chickpea (Cicer arietinum L.). With the aim of identifying the genomic regions controlling seed Fe and Zn concentrations, the F2:3 population derived from a cross between MNK-1 and Annigeri 1 was genotyped using genotyping by sequencing approach and evaluated for Fe and Zn concentration. An intraspecific genetic linkage map comprising 839 single nucleotide polymorphisms (SNPs) spanning a total distance of 1,088.04 cM with an average marker density of 1.30 cM was constructed. By integrating the linkage map data with the phenotypic data of the F2:3 population, a total of 11 QTLs were detected for seed Fe concentration on CaLG03, CaLG04, and CaLG05, with phenotypic variation explained ranging from 7.2% (CaqFe3.4) to 13.4% (CaqFe4.2). For seed Zn concentration, eight QTLs were identified on CaLG04, CaLG05, and CaLG08. The QTLs individually explained phenotypic variations ranging between 5.7% (CaqZn8.1) and 13.7% (CaqZn4.3). Three QTLs for seed Fe and Zn concentrations (CaqFe4.4, CaqFe4.5, and CaqZn4.1) were colocated in the "QTL-hotspot" region on CaLG04 that harbors several drought tolerance-related QTLs. We identified genes in the QTL regions that encode iron-sulfur metabolism and zinc-dependent alcohol dehydrogenase activity on CaLG03, iron ion binding oxidoreductase on CaLG04, and zinc-induced facilitator-like protein and ZIP zinc/iron transport family protein on CaLG05. These genomic regions and the associated markers can be used in marker-assisted selection to increase seed Fe and Zn concentrations in agronomically superior chickpea varieties.

Integrating genomics for chickpea improvement: achievements and opportunities

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.

Genome-wide SNP identification in Prunus rootstocks germplasm collections using Genotyping-by-Sequencing: phylogenetic analysis, distribution of SNPs and prediction of their effect on gene function

Genotyping-by-Sequencing (GBS) was applied in a set of 53 diploid Prunus rootstocks and five scion cultivars from three subgenera (Amygdalus, Prunus and Cerasus) for genome-wide SNP identification and to assess genetic diversity of both Chilean and Spanish germplasm collections. A group of 45,382 high quality SNPs (MAF >0.05; missing data <5%) were selected for analysis of this group of 58 accessions. These SNPs were distributed in genic and intergenic regions in the eight pseudomolecules of the peach genome (Peach v2.0), with an average of 53% located in exonic regions. The genetic diversity detected among the studied accessions divided them in three groups, which are in agreement with their current taxonomic classification. SNPs were classified based on their putative effect on annotated genes and KOG analysis was carried out to provide a deeper understanding of the function of 119 genes affected by high-impact SNPs. Results demonstrate the high utility for Prunus rootstocks identification and studies of diversity in Prunus species. Also, given the high number of SNPs identified in exonic regions, this strategy represents an important tool for finding candidate genes underlying traits of interest and potential functional markers for use in marker-assisted selection.

Genotyping-by-Sequencing Derived Single Nucleotide Polymorphisms Provide the First Well-Resolved Phylogeny for the Genus Triticum (Poaceae)

Wheat (Triticum spp.) has been an important staple food crop for mankind since the beginning of agriculture. The genus Triticum L. is composed of diploid, tetraploid, and hexaploid species, majority of which have not yet been discriminated clearly, and hence their phylogeny and classification remain unresolved. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows us to generate genome-wide single nucleotide polymorphism (SNP) markers. In this study, we used GBS to obtain SNPs covering all seven chromosomes from 283 accessions of Triticum-related genera. After filtering low-quality and redundant SNPs based on haplotype information, the GBS assay provided 14,188 high-quality SNPs that were distributed across the A (71%), B (26%), and D (2.4%) genomes. Cluster analysis and discriminant analysis of principal components (DAPC) allowed us to distinguish six distinct groups that matched well with Triticum species complexity. We constructed a Bayesian phylogenetic tree using 14,188 SNPs, in which 17 Triticum species and subspecies were discriminated. Dendrogram analysis revealed that the polyploid wheat species could be divided into groups according to the presence of A, B, D, and G genomes with strong nodal support and provided new insight into the evolution of spelt wheat. A total of 2,692 species-specific SNPs were identified to discriminate the common (T. aestivum) and durum (T. turgidum) wheat cultivar and landraces. In principal component analysis grouping, the two wheat species formed individual clusters and the SNPs were able to distinguish up to nine groups of 10 subspecies. This study demonstrated that GBS-derived SNPs could be used efficiently in genebank management to classify Triticum species and subspecies that are very difficult to distinguish by their morphological characters.

Whole Genome Diversity, Population Structure, and Linkage Disequilibrium Analysis of Chickpea (Cicer arietinum L.) Genotypes Using Genome-Wide DArTseq-Based SNP Markers

Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced "Kabuli" breeding lines and Iranian landrace "Desi" chickpea genotypes, were genotyped using DArTseq-Based single nucleotide polymorphism (SNP) markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that was covered by SNPs varied from 16,236.36 kbp (LG8) to 67,923.99 kbp (LG5), while LG4 showed a higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6, and LG8 showed higher mean PIC value than average. Unweighted neighbor joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and discriminant analysis of principal component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2 ≥ 0.8, while 2961 pairs of markers showed complete LD (r2 = 1), and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggest the presence of a high genetic diversity among the studied chickpea genotypes. This study also demonstrates the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits, such as seed yield, abiotic, and biotic stresses, and therefore can be efficiently used in breeding programs to improve chickpea.

Multi-trait analysis of domestication genes in Cicer arietinum - Cicer reticulatum hybrids with a multidimensional approach: Modeling wide crosses for crop improvement

Domestication and subsequent breeding have eroded genetic diversity in the modern chickpea crop by ˜100-fold. Corresponding reductions to trait variation create the need, and an opportunity, to identify and harness the genetic capacity of wild species for crop improvement. Here we analyze trait segregation in a series of wild x cultivated hybrid populations to delineate the genetic underpinnings of domestication traits. Two species of wild chickpea, C. reticulatum and C. echinospermum, were crossed with the elite, early flowering C. arietinum cultivar ICCV96029. KASP genotyping of F2 parents with an FT-linked molecular marker enabled selection of 284 F3 families with reduced phenological variation: 255 F3 families of C. arietinum x reticulatum (AR) derived from 17 diverse wild parents and 29 F3 families of C. arietinum x echinospermum (AE) from 3 wild parents. The combined 284 lineages were genotyped using a genotyping-by-sequencing strategy and phenotyped for agronomic traits. 50 QTLs in 11 traits were detected from AR and 35 QTLs in 10 traits from the combined data. Using hierarchical clustering to assign traits to six correlated groups and mixed model based multi-trait mapping, four pleiotropic loci were identified. Bayesian analysis further identified four inter-trait relationships controlling the duration of vegetative growth and seed maturation, for which the underlying pleiotropic genes were mapped. A random forest approach was used to explore the most extreme trait differences between AR and AE progenies, identifying traits most characteristic of wild species origin. Knowledge of the genomic basis of traits that segregate in wild-cultivated hybrid populations will facilitate chickpea improvement by linking genetic and phenotypic variation in a quantitative genetic framework.

Genome-wide cis-regulatory signatures for modulation of agronomic traits as exemplified by drought yield index (DYI) in chickpea

Developing functional molecular tags from the cis-regulatory sequence components of genes is vital for their deployment in efficient genetic dissection of complex quantitative traits in crop plants including chickpea. The current study identified 431,194 conserved non-coding SNP (CNSNP) from the cis-regulatory element regions of genes which were annotated on a chickpea genome. These genome-wide CNSNP marker resources are made publicly accessible through a user-friendly web-database ( http://www.cnsnpcicarbase.com ). The CNSNP-based quantitative trait loci (QTL) and expression QTL (eQTL) mapping and genome-wide association study (GWAS) were further integrated with global gene expression landscapes, molecular haplotyping, and DNA-protein interaction study in the association panel and recombinant inbred lines (RIL) mapping population to decode complex genetic architecture of one of the vital seed yield trait under drought stress, drought yield index (DYI), in chickpea. This delineated two constituted natural haplotypes and alleles from a histone H3 protein-coding gene and its transcriptional regulator NAC transcription factor (TF) harboring the major QTLs and trans-acting eQTL governing DYI in chickpea. The effect of CNSNPs in TF-binding cis-element of a histone H3 gene in altering the binding affinity and transcriptional activity of NAC TF based on chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) assay was evident. The CNSNP-led promising molecular tags scanned will essentially have functional significance to decode transcriptional gene regulatory function and thus can drive translational genomic analysis in chickpea.

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.

Genome-wide signatures of local adaptation among seven stoneflies species along a nationwide latitudinal gradient in Japan

Background

Environmental heterogeneity continuously produces a selective pressure that results in genomic variation among organisms; understanding this relationship remains a challenge in evolutionary biology. Here, we evaluated the degree of genome-environmental association of seven stonefly species across a wide geographic area in Japan and additionally identified putative environmental drivers and their effect on co-existing multiple stonefly species. Double-digest restriction-associated DNA (ddRAD) libraries were independently sequenced for 219 individuals from 23 sites across four geographical regions along a nationwide latitudinal gradient in Japan.

Results

A total of 4251 candidate single nucleotide polymorphisms (SNPs) strongly associated with local adaptation were discovered using Latent mixed models; of these, 294 SNPs showed strong correlation with environmental variables, specifically precipitation and altitude, using distance-based redundancy analysis. Genome–genome comparison among the seven species revealed a high sequence similarity of candidate SNPs within a geographical region, suggesting the occurrence of a parallel evolution process.

Conclusions

Our results revealed genomic signatures of local adaptation and their influence on multiple, co-occurring species. These results can be potentially applied for future studies on river management and climatic stressor impacts.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5453-3) contains supplementary material, which is available to authorized users.

Comparative genome-wide survey of single nucleotide variation uncovers the genetic diversity and potential biomedical applications among six Macaca species

Macaca is of great importance in evolutionary and biomedical research. Aiming at elucidating genetic diversity patterns and potential biomedical applications of macaques, we characterized single nucleotide variations (SNVs) of six Macaca species based on the reference genome of Macaca mulatta. Using eight whole-genome sequences, representing the most comprehensive genomic SNV study in Macaca to date, we focused on discovery and comparison of nonsynonymous SNVs (nsSNVs) with bioinformatic tools. We observed that SNV distribution patterns were generally congruent among the eight individuals. Outlier tests of nsSNV distribution patterns detected 319 bins with significantly distinct genetic divergence among macaques, including differences in genes associated with taste transduction, homologous recombination, and fat and protein digestion. Genes with specific nsSNVs in various macaques were differentially enriched for metabolism pathways, such as glycolysis, protein digestion and absorption. On average, 24.95% and 11.67% specific nsSNVs were putatively deleterious according to PolyPhen2 and SIFT4G, respectively, among which the shared deleterious SNVs were located in 564–1981 genes. These genes displayed enrichment signals in the ‘obesity-related traits’ disease category for all surveyed macaques, confirming that they were suitable models for obesity related studies. Additional enriched disease categories were observed in some macaques, exhibiting promising potential for biomedical application. Positively selected genes identified by PAML in most tested Macaca species played roles in immune and nervous system, growth and development, and fat metabolism. We propose that metabolism and body size play important roles in the evolutionary adaptation of macaques.

Genomic approaches for studying crop evolution

Understanding how crop plants evolved from their wild relatives and spread around the world can inform about the origins of agriculture. Here, we review how the rapid development of genomic resources and tools has made it possible to conduct genetic mapping and population genetic studies to unravel the molecular underpinnings of domestication and crop evolution in diverse crop species. We propose three future avenues for the study of crop evolution: establishment of high-quality reference genomes for crops and their wild relatives; genomic characterization of germplasm collections; and the adoption of novel methodologies such as archaeogenetics, epigenomics, and genome editing.

Genome-wide generation and genotyping of informative SNPs to scan molecular signatures for seed yield in chickpea

We discovered 2150 desi and 2199 kabuli accessions-derived SNPs by cultivar-wise individual assembling of sequence-reads generated through genotyping-by-sequencing of 92 chickpea accessions. Subsequent large-scale validation and genotyping of these SNPs discovered 619 desi accessions-derived (DAD) SNPs, 531 kabuli accessions-derived (KAD) SNPs, 884 multiple accessions-derived (MAD) SNPs and 1083 two accessions (desi ICC 4958 and kabuli CDC Frontier)-derived (TAD) SNPs that were mapped on eight chromosomes. These informative SNPs were annotated in coding/non-coding regulatory sequence components of genes. The MAD-SNPs were efficient to detect high intra-specific polymorphic potential and wide natural allelic diversity level including high-resolution admixed-population genetic structure and precise phylogenetic relationship among 291 desi and kabuli accessions. This signifies their effectiveness in introgression breeding and varietal improvement studies targeting useful agronomic traits of chickpea. Six trait-associated genes with SNPs including quantitative trait nucleotides (QTNs) in combination explained 27.5% phenotypic variation for seed yield per plant (SYP). A pentatricopeptide repeat (PPR) gene with a synonymous-coding SNP/QTN significantly associated with SYP trait was found most-promising in chickpea. The essential information delineated can be of immense utility in genomics-assisted breeding applications to develop high-yielding chickpea cultivars.

Genetic and Genomic Tools to Asssist Sugar Beet Improvement: The Value of the Crop Wild Relatives

Sugar beet (Beta vulgaris L. ssp. vulgaris) is one of the most important European crops for both food and sugar production. Crop improvement has been developed to enhance productivity, sugar content or other breeder's desirable traits. The introgression of traits from Crop Wild Relatives (CWR) has been done essentially for lessening biotic stresses constraints, namely using Beta and Patellifolia species which exhibit disease resistance characteristics. Several studies have addressed crop-to-wild gene flow, yet, for breeding programs genetic variability associated with agronomically important traits remains unexplored regarding abiotic factors. To accomplish such association from phenotype-to-genotype, screening for wild relatives occurring in habitats where selective pressures are in play (i.e., populations in salt marshes for salinity tolerance; populations subjected to pathogen attacks and likely evolved resistance to pathogens) are the most appropriate streamline to identify causal genetic information. By selecting sugar beet CWR species based on genomic tools, rather than random variations, is a promising but still seldom explored route toward the development of improved crops. In this perspective, a viable streamline for sugar beet improvement is proposed through the use of different genomic tools by recurring to sugar beet CWRs and focusing on agronomic traits associated with abiotic stress tolerance. Overall, identification of genomic and epigenomic landscapes associated to adaptive ecotypes, along with the cytogenetic and habitat characterization of sugar beet CWR, will enable to identify potential hotspots for agrobiodiversity of sugar beet crop improvement toward abiotic stress tolerance.

Characterization of Linkage Disequilibrium and Population Structure in a Mungbean Diversity Panel

Mungbean [Vigna radiata (L.) R. Wilczek var. radiata] is an important grain legume globally, providing a high-quality plant protein source largely produced and consumed in South and East Asia. This study aimed to characterize a mungbean diversity panel consisting of 466 cultivated accessions and demonstrate its utility by conducting a pilot genome-wide association study of seed coat color. In addition 16 wild accessions were genotyped for comparison and in total over 22,000 polymorphic genome-wide SNPs were identified and used to analyze the genetic diversity, population structure, linkage disequilibrium (LD) of mungbean. Polymorphism was lower in the cultivated accessions in comparison to the wild accessions, with average polymorphism information content values 0.174, versus 0.305 in wild mungbean. LD decayed in ∼100 kb in cultivated lines, a distance higher than the linkage decay of ∼60 kb estimated in wild mungbean. Four distinct subgroups were identified within the cultivated lines, which broadly corresponded to geographic origin and seed characteristics. In a pilot genome-wide association mapping study of seed coat color, five genomic regions associated were identified, two of which were close to seed coat color genes in other species. This mungbean diversity panel constitutes a valuable resource for genetic dissection of important agronomical traits to accelerate mungbean breeding.

Population structure and association analysis of heat stress relevant traits in chickpea (Cicer arietinum L.)

Understanding genetic diversity and population structure is prerequisite to broaden the cultivated base of any crop. In the current investigation, we report discovery of a total of 319 alleles by assaying 81 SSRs on 71 chickpea genotypes. The cluster analysis based on Jaccard coefficient and unweighted neighbor joining algorithm categorized all genotypes into two major clusters. Cultivars grown within the same agro-climatic zones were clustered together, whereas the remaining genotypes particularly advanced breeding lines and accessions assigned to another cluster. Population structure analysis separated the entire collection into two subpopulations (K = 2) and the clustering pattern remained in close agreement with those of distance-based methods. Importantly, we also discovered marker trait association for membrane stability index (MSI) and leaf chlorophyll content measured as SPAD chlorophyll meter reading (SCMR), the two important physiological parameters indicative of heat stress (HS) tolerance in chickpea. Association analysis using both general linear and mixed linear models of the mean phenotypic data of traits recorded in 2016 and 2017 uncovered significant association of NCPGR206 and H2L102 with the MSI trait. Likewise, SSR markers GA9, TR31 and TA113 exhibited significant association with SCMR trait. The genomic regions putatively linked with two traits may be investigated in greater detail to further improve knowledge about the genetic architecture of HS tolerance in chickpea.

Population structure and association analysis of heat stress relevant traits in chickpea (Cicer arietinum L.)

Understanding genetic diversity and population structure is prerequisite to broaden the cultivated base of any crop. In the current investigation, we report discovery of a total of 319 alleles by assaying 81 SSRs on 71 chickpea genotypes. The cluster analysis based on Jaccard coefficient and unweighted neighbor joining algorithm categorized all genotypes into two major clusters. Cultivars grown within the same agro-climatic zones were clustered together, whereas the remaining genotypes particularly advanced breeding lines and accessions assigned to another cluster. Population structure analysis separated the entire collection into two subpopulations (K = 2) and the clustering pattern remained in close agreement with those of distance-based methods. Importantly, we also discovered marker trait association for membrane stability index (MSI) and leaf chlorophyll content measured as SPAD chlorophyll meter reading (SCMR), the two important physiological parameters indicative of heat stress (HS) tolerance in chickpea. Association analysis using both general linear and mixed linear models of the mean phenotypic data of traits recorded in 2016 and 2017 uncovered significant association of NCPGR206 and H2L102 with the MSI trait. Likewise, SSR markers GA9, TR31 and TA113 exhibited significant association with SCMR trait. The genomic regions putatively linked with two traits may be investigated in greater detail to further improve knowledge about the genetic architecture of HS tolerance in chickpea.

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.

Coding SNPs analysis highlights genetic relationships and evolution pattern in eggplant complexes

Brinjal (Solanum melongena), scarlet (S. aethiopicum) and gboma (S. macrocarpon) eggplants are three Old World domesticates. The genomic DNA of a collection of accessions belonging to the three cultivated species, along with a representation of various wild relatives, was characterized for the presence of single nucleotide polymorphisms (SNPs) using a genotype-by-sequencing approach. A total of 210 million useful reads were produced and were successfully aligned to the reference eggplant genome sequence. Out of the 75,399 polymorphic sites identified among the 76 entries in study, 12,859 were associated with coding sequence. A genetic relationships analysis, supported by the output of the FastSTRUCTURE software, identified four major sub-groups as present in the germplasm panel. The first of these clustered S. aethiopicum with its wild ancestor S. anguivi; the second, S. melongena, its wild progenitor S. insanum, and its relatives S. incanum, S. lichtensteinii and S. linneanum; the third, S. macrocarpon and its wild ancestor S. dasyphyllum; and the fourth, the New World species S. sisymbriifolium, S. torvum and S. elaeagnifolium. By applying a hierarchical FastSTRUCTURE analysis on partitioned data, it was also possible to resolve the ambiguous membership of the accessions of S. campylacanthum, S. violaceum, S. lidii, S. vespertilio and S. tomentsum, as well as to genetically differentiate the three species of New World Origin. A principal coordinates analysis performed both on the entire germplasm panel and also separately on the entries belonging to sub-groups revealed a clear separation among species, although not between each of the domesticates and their respective wild ancestors. There was no clear differentiation between either distinct cultivar groups or different geographical provenance. Adopting various approaches to analyze SNP variation provided support for interpretation of results. The genotyping-by-sequencing approach showed to be highly efficient for both quantifying genetic diversity and establishing genetic relationships among and within cultivated eggplants and their wild relatives. The relevance of these results to the evolution of eggplants, as well as to their genetic improvement, is discussed.

Potential Uses of Wild Germplasms of Grain Legumes for Crop Improvement

Challenged by population increase, climatic change, and soil deterioration, crop improvement is always a priority in securing food supplies. Although the production of grain legumes is in general lower than that of cereals, the nutritional value of grain legumes make them important components of food security. Nevertheless, limited by severe genetic bottlenecks during domestication and human selection, grain legumes, like other crops, have suffered from a loss of genetic diversity which is essential for providing genetic materials for crop improvement programs. Illustrated by whole-genome-sequencing, wild relatives of crops adapted to various environments were shown to maintain high genetic diversity. In this review, we focused on nine important grain legumes (soybean, peanut, pea, chickpea, common bean, lentil, cowpea, lupin, and pigeonpea) to discuss the potential uses of their wild relatives as genetic resources for crop breeding and improvement, and summarized the various genetic/genomic approaches adopted for these purposes.

SNP-Discovery by RAD-Sequencing in a Germplasm Collection of Wild and Cultivated Grapevines (V. vinifera L.)

Whole-genome comparisons of Vitis vinifera subsp. sativa and V. vinifera subsp. sylvestris are expected to provide a better estimate of the valuable genetic diversity still present in grapevine, and help to reconstruct the evolutionary history of a major crop worldwide. To this aim, the increase of molecular marker density across the grapevine genome is fundamental. Here we describe the SNP discovery in a grapevine germplasm collection of 51 cultivars and 44 wild accessions through a novel protocol of restriction-site associated DNA (RAD) sequencing. By resequencing 1.1% of the grapevine genome at a high coverage, we recovered 34K BamHI unique restriction sites, of which 6.8% were absent in the ‘PN40024’ reference genome. Moreover, we identified 37,748 single nucleotide polymorphisms (SNPs), 93% of which belonged to the 19 assembled chromosomes with an average of 1.8K SNPs per chromosome. Nearly half of the SNPs fell in genic regions mostly assigned to the functional categories of metabolism and regulation, whereas some nonsynonymous variants were identified in genes related with the detection and response to environmental stimuli. SNP validation was carried-out, showing the ability of RAD-seq to accurately determine genotypes in a highly heterozygous species. To test the usefulness of our SNP panel, the main diversity statistics were evaluated, highlighting how the wild grapevine retained less genetic variability than the cultivated form. Furthermore, the analysis of Linkage Disequilibrium (LD) in the two subspecies separately revealed how the LD decays faster within the domesticated grapevine compared to its wild relative. Being the first application of RAD-seq in a diverse grapevine germplasm collection, our approach holds great promise for exploiting the genetic resources available in one of the most economically important fruit crops.

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.

Genotyping-by-sequencing provides the discriminating power to investigate the subspecies of Daucus carota (Apiaceae)

BACKGROUND

The majority of the subspecies of Daucus carota have not yet been discriminated clearly by various molecular or morphological methods and hence their phylogeny and classification remains unresolved. Recent studies using 94 nuclear orthologs and morphological characters, and studies employing other molecular approaches were unable to distinguish clearly many of the subspecies. Fertile intercrosses among traditionally recognized subspecies are well documented. We here explore the utility of single nucleotide polymorphisms (SNPs) generated by genotyping-by-sequencing (GBS) to serve as an effective molecular method to discriminate the subspecies of the D. carota complex.

RESULTS

We used GBS to obtain SNPs covering all nine Daucus carota chromosomes from 162 accessions of Daucus and two related genera. To study Daucus phylogeny, we scored a total of 10,814 or 38,920 SNPs with a maximum of 10 or 30 % missing data, respectively. To investigate the subspecies of D. carota, we employed two data sets including 150 accessions: (i) rate of missing data 10 % with a total of 18,565 SNPs, and (ii) rate of missing data 30 %, totaling 43,713 SNPs. Consistent with prior results, the topology of both data sets separated species with 2n = 18 chromosome from all other species. Our results place all cultivated carrots (D. carota subsp. sativus) in a single clade. The wild members of D. carota from central Asia were on a clade with eastern members of subsp. sativus. The other subspecies of D. carota were in four clades associated with geographic groups: (1) the Balkan Peninsula and the Middle East, (2) North America and Europe, (3) North Africa exclusive of Morocco, and (4) the Iberian Peninsula and Morocco. Daucus carota subsp. maximus was discriminated, but neither it, nor subsp. gummifer (defined in a broad sense) are monophyletic.

CONCLUSIONS

Our study suggests that (1) the morphotypes identified as D. carota subspecies gummifer (as currently broadly circumscribed), all confined to areas near the Atlantic Ocean and the western Mediterranean Sea, have separate origins from sympatric members of other subspecies of D. carota, (2) D. carota subsp. maximus, on two clades with some accessions of subsp. carota, can be distinguished from each other but only with poor morphological support, (3) D. carota subsp. capillifolius, well distinguished morphologically, is an apospecies relative to North African populations of D. carota subsp. carota, (4) the eastern cultivated carrots have origins closer to wild carrots from central Asia than to western cultivated carrots, and (5) large SNP data sets are suitable for species-level phylogenetic studies in Daucus.

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.

First-generation HapMap in Cajanus spp. reveals untapped variations in parental lines of mapping populations

Whole genome re-sequencing (WGRS) was conducted on a panel of 20 Cajanus spp. accessions (crossing parentals of recombinant inbred lines, introgression lines, multiparent advanced generation intercross and nested association mapping population) comprising of two wild species and 18 cultivated species accessions. A total of 791.77 million paired-end reads were generated with an effective mapping depth of ~12X per accession. Analysis of WGRS data provided 5 465 676 genome-wide variations including 4 686 422 SNPs and 779 254 InDels across the accessions. Large structural variations in the form of copy number variations (2598) and presence and absence variations (970) were also identified. Additionally, 2 630 904 accession-specific variations comprising of 2 278 571 SNPs (86.6%), 166 243 deletions (6.3%) and 186 090 insertions (7.1%) were also reported. Identified polymorphic sites in this study provide the first-generation HapMap in Cajanus spp. which will be useful in mapping the genomic regions responsible for important traits.

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.

Developing maps of fitness consequences for plant genomes

Predicting the fitness consequences of mutations, and their concomitant impacts on molecular and cellular function as well as organismal phenotypes, is an important challenge in biology that has new relevance in an era when genomic data is readily available. The ability to construct genomewide maps of fitness consequences in plant genomes is a recent development that has profound implications for our ability to predict the fitness effects of mutations and discover functional elements. Here we highlight approaches to building fitness consequence maps to infer regions under selection. We emphasize computational methods applied primarily to the study of human disease that translate physical maps of within-species genome variation into maps of fitness effects of individual natural mutations. Maps of fitness consequences in plants, combined with traditional genetic approaches, could accelerate discovery of functional elements such as regulatory sequences in non-coding DNA and genetic polymorphisms associated with key traits, including agronomically-important traits such as yield and environmental stress responses.

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.

Genetic Relationship in Cicer Sp. Expose Evidence for Geneflow between the Cultigen and Its Wild Progenitor

There is a debate concerning mono- or poly-phyletic origins of the Near Eastern crops. In parallel, some authors claim that domestication was not possible within the natural range of the wild progenitors due to wild alleles flow into the nascent crops. Here we address both, the mono- or poly-phyletic origins and the domestications within or without the natural range of the progenitor, debates in order to understand the relationship between domesticated chickpea (Cicer arietinum L.) and its wild progenitor (C. reticulatum Ladizinsky) with special emphasis on its domestication centre in southeastern Turkey. A set of 103 chickpea cultivars and landraces from the major growing regions alongside wild accessions (C. reticulatum, C. echinospermum P.H Davis and C. bijugum K.H. Rech) sampled across the natural distribution range in eastern Turkey were genotyped with 194 SNPs markers. The genetic affinities between and within the studied taxa were assessed. The analysis suggests a mono-phyletic origin of the cultigen, with several wild accession as likely members of the wild stock of the cultigen. Clear separation between the wild and domesticated germplasm was apparent, with negligible level of admixture. A single C. reticulatum accession shows morphological and allelic signatures of admixture, a likely result of introgression. No evidence of geneflow from the wild into domesticated germplasm was found. The traditional farming systems of southeaster Turkey are characterized by occurrence of sympatric wild progenitor-domesticated forms of chickpea (and likewise cereals and other grain legumes). Therefore, both the authentic crop landraces and the wild populations native to the area are a unique genetic resource. Our results grant support to the notion of domestication within the natural distribution range of the wild progenitor, suggesting that the Neolithic domesticators were fully capable of selecting the desired phenotypes even when facing rare wild-domesticated introgression events.