CRISPR-Cas9-based repeat depletion for high-throughput genotyping of complex plant genomes.

High-throughput genotyping enables the large-scale analysis of genetic diversity in population genomics and genome-wide association studies that combine the genotypic and phenotypic characterization of large collections of accessions. Sequencing-based approaches for genotyping are progressively replacing traditional genotyping methods because of the lower ascertainment bias. However, genome-wide genotyping based on sequencing becomes expensive in species with large genomes and a high proportion of repetitive DNA. Here we describe the use of CRISPR-Cas9 technology to deplete repetitive elements in the 3.76-Gb genome of lentil (Lens culinaris), 84% consisting of repeats, thus concentrating the sequencing data on coding and regulatory regions (single-copy regions). We designed a custom set of 566,766 gRNAs targeting 2.9 Gbp of repeats and excluding repetitive regions overlapping annotated genes and putative regulatory elements based on ATAC-seq data. The novel depletion method removed ∼40% of reads mapping to repeats, increasing those mapping to single-copy regions by ∼2.6-fold. When analyzing 25 million fragments, this repeat-to-single-copy shift in the sequencing data increased the number of genotyped bases of ∼10-fold compared to nondepleted libraries. In the same condition, we were also able to identify ∼12-fold more genetic variants in the single-copy regions and increased the genotyping accuracy by rescuing thousands of heterozygous variants that otherwise would be missed because of low coverage. The method performed similarly regardless of the multiplexing level, type of library or genotypes, including different cultivars and a closely related species (L. orientalis). Our results showed that CRISPR-Cas9-driven repeat depletion focuses sequencing data on single-copy regions, thus improving high-density and genome-wide genotyping in large and repetitive genomes.

Genetic and gene expression analysis of flowering time regulation by light quality in lentil.

BACKGROUND AND AIMS: Flowering time is important due to its roles in plant adaptation to different environments and subsequent formation of crop yield. Changes in light quality affect a range of developmental processes including flowering time, but little is known about light quality-induced flowering time control in lentil. This study aims to investigate the genetic basis for differences in flowering response to light quality in lentil. METHODS: We explored variation in flowering time caused by changes in red/far-red-related light quality environments of a lentil interspecific recombinant inbred line (RIL) population developed from a cross between Lens culinaris cv. Lupa and L. orientalis accession BGE 016880. A genetic linkage map was constructed and then used for identifying quantitative trait loci (QTLs) associated with flowering time regulation under different light quality environments. Differential gene expression analysis through transcriptomic study and RT-qPCR were used to identify potential candidate genes. KEY RESULTS: QTL mapping located 13 QTLs controlling flower time under different light quality environments, with phenotypic variance explained ranging from 1.7 to 62.9 %. Transcriptomic profiling and gene expression analysis for both parents of this interspecific RIL population identified flowering-related genes showing environment-specific differential expression (flowering DEGs). One of these, a member of the florigen gene family FTa1 (LcFTa1), was located close to three major QTLs. Furthermore, gene expression results suggested that two other florigen genes (LcFTb1 and LcFTb2), MADS-box transcription factors such as LcAGL6/13d, LcSVPb, LcSOC1b and LcFULb, as well as bHLH transcription factor LcPIF6 and Gibberellin 20 oxidase LcGA20oxC,G may also be involved in the light quality response. CONCLUSIONS: Our results show that a major component of flowering time sensitivity to light quality is tightly linked to LcFTa1 and associated with changes in its expression. This work provides a foundation for crop improvement of lentil with better adaptation to variable light environments.

Gene-based SNP discovery in tepary bean (Phaseolus acutifolius) and common bean (P. vulgaris) for diversity analysis and comparative mapping.

BACKGROUND: Common bean (Phaseolus vulgaris) is an important grain legume and there has been a recent resurgence in interest in its relative, tepary bean (P. acutifolius), owing to this species' ability to better withstand abiotic stresses. Genomic resources are scarce for this minor crop species and a better knowledge of the genome-level relationship between these two species would facilitate improvement in both. High-throughput genotyping has facilitated large-scale single nucleotide polymorphism (SNP) identification leading to the development of molecular markers with associated sequence information that can be used to place them in the context of a full genome assembly. RESULTS: Transcript-based SNPs were identified from six common bean and two tepary bean accessions and a subset were used to generate a 768-SNP Illumina GoldenGate assay for each species. The tepary bean assay was used to assess diversity in wild and cultivated tepary bean and to generate the first gene-based map of the tepary bean genome. Genotypic analyses of the diversity panel showed a clear separation between domesticated and cultivated tepary beans, two distinct groups within the domesticated types, and P. parvifolius was confirmed to be distinct. The genetic map of tepary bean was compared to the common bean genome assembly to demonstrate high levels of collinearity between the two species with differences limited to a few intra-chromosomal rearrangements. CONCLUSIONS: The development of the first set of genomic resources specifically for tepary bean has allowed for greater insight into the structure of this species and its relationship to its agriculturally more prominent relative, common bean. These resources will be helpful in the development of efficient breeding strategies for both species and will facilitate the introgression of agriculturally important traits from one crop into the other.

Genome wide SNP identification in chickpea for use in development of a high density genetic map and improvement of chickpea reference genome assembly.

BACKGROUND: In the whole genome sequencing, genetic map provides an essential framework for accurate and efficient genome assembly and validation. The main objectives of this study were to develop a high-density genetic map using RAD-Seq (Restriction-site Associated DNA Sequencing) genotyping-by-sequencing (RAD-Seq GBS) and Illumina GoldenGate assays, and to examine the alignment of the current map with the kabuli chickpea genome assembly. RESULTS: Genic single nucleotide polymorphisms (SNPs) totaling 51,632 SNPs were identified by 454 transcriptome sequencing of Cicer arietinum and Cicer reticulatum genotypes. Subsequently, an Illumina GoldenGate assay for 1,536 SNPs was developed. A total of 1,519 SNPs were successfully assayed across 92 recombinant inbred lines (RILs), of which 761 SNPs were polymorphic between the two parents. In addition, the next generation sequencing (NGS)-based GBS was applied to the same population generating 29,464 high quality SNPs. These SNPs were clustered into 626 recombination bins based on common segregation patterns. Data from the two approaches were used for the construction of a genetic map using a population derived from an intraspecific cross. The map consisted of 1,336 SNPs including 604 RAD recombination bins and 732 SNPs from Illumina GoldenGate assay. The map covered 653 cM of the chickpea genome with an average distance between adjacent markers of 0.5 cM. To date, this is the most extensive genetic map of chickpea using an intraspecific population. The alignment of the map with the CDC Frontier genome assembly revealed an overall conserved marker order; however, a few local inconsistencies within the Cicer arietinum pseudochromosome 1 (Ca1), Ca5 and Ca8 were detected. The map enabled the alignment of 215 unplaced scaffolds from the CDC Frontier draft genome assembly. The alignment also revealed varying degrees of recombination rates and hotspots across the chickpea genome. CONCLUSIONS: A high-density genetic map using RAD-Seq GBS and Illumina GoldenGate assay was developed and aligned with the existing kabuli chickpea draft genome sequence. The analysis revealed an overall conserved marker order, although some localized inversions between draft genome assembly and the genetic map were detected. The current analysis provides an insight of the recombination rates and hotspots across the chickpea genome.

Gene-based SNP discovery and genetic mapping in pea.

KEY MESSAGE: Gene-based SNPs were identified and mapped in pea using five recombinant inbred line populations segregating for traits of agronomic importance. Pea (Pisum sativum L.) is one of the world's oldest domesticated crops and has been a model system in plant biology and genetics since the work of Gregor Mendel. Pea is the second most widely grown pulse crop in the world following common bean. The importance of pea as a food crop is growing due to its combination of moderate protein concentration, slowly digestible starch, high dietary fiber concentration, and its richness in micronutrients; however, pea has lagged behind other major crops in harnessing recent advances in molecular biology, genomics and bioinformatics, partly due to its large genome size with a large proportion of repetitive sequence, and to the relatively limited investment in research in this crop globally. The objective of this research was the development of a genome-wide transcriptome-based pea single-nucleotide polymorphism (SNP) marker platform using next-generation sequencing technology. A total of 1,536 polymorphic SNP loci selected from over 20,000 non-redundant SNPs identified using deep transcriptome sequencing of eight diverse Pisum accessions were used for genotyping in five RIL populations using an Illumina GoldenGate assay. The first high-density pea SNP map defining all seven linkage groups was generated by integrating with previously published anchor markers. Syntenic relationships of this map with the model legume Medicago truncatula and lentil (Lens culinaris Medik.) maps were established. The genic SNP map establishes a foundation for future molecular breeding efforts by enabling both the identification and tracking of introgression of genomic regions harbouring QTLs related to agronomic and seed quality traits.

Ancient orphan crop joins modern era: gene-based SNP discovery and mapping in lentil.

BACKGROUND: The genus Lens comprises a range of closely related species within the galegoid clade of the Papilionoideae family. The clade includes other important crops (e.g. chickpea and pea) as well as a sequenced model legume (Medicago truncatula). Lentil is a global food crop increasing in importance in the Indian sub-continent and elsewhere due to its nutritional value and quick cooking time. Despite this importance there has been a dearth of genetic and genomic resources for the crop and this has limited the application of marker-assisted selection strategies in breeding. RESULTS: We describe here the development of a deep and diverse transcriptome resource for lentil using next generation sequencing technology. The generation of data in multiple cultivated (L. culinaris) and wild (L. ervoides) genotypes together with the utilization of a bioinformatics workflow enabled the identification of a large collection of SNPs and the subsequent development of a genotyping platform that was used to establish the first comprehensive genetic map of the L. culinaris genome. Extensive collinearity with M. truncatula was evident on the basis of sequence homology between mapped markers and the model genome and large translocations and inversions relative to M. truncatula were identified. An estimate for the time divergence of L. culinaris from L. ervoides and of both from M. truncatula was also calculated. CONCLUSIONS: The availability of the genomic and derived molecular marker resources presented here will help change lentil breeding strategies and lead to increased genetic gain in the future.

Identification of anthracnose race 1 resistance loci in lentil by integrating linkage mapping and genome-wide association study.

Anthracnose, caused byColletotrichum lentis, is a devastating disease of lentil (Lens culinaris Medik.) in western Canada. Growing resistant lentil cultivars is the most cost-effective and environmentally friendly approach to prevent seed yield losses that can exceed 70%. To identify loci conferring resistance to anthracnose race 1 in lentil, biparental quantitative trait loci (QTL) mapping of two recombinant inbred line (RIL) populations was integrated with a genome-wide association study (GWAS) using 200 diverse lentil accessions from a lentil diversity panel. A major-effect QTL (qAnt1.Lc-3) conferring resistance to race 1 was mapped to lentil chromosome 3 and colocated on the lentil physical map for both RIL populations. Clusters of candidate nucleotide-binding leucine-rich repeat (NB-LRR) and other defense-related genes were uncovered within the QTL region. A GWAS detected 14 significant single nucleotide polymorphism (SNP) markers associated with race 1 resistance on chromosomes 3, 4, 5, and 6. The most significant GWAS SNPs on chromosome 3 supported qAnt1.Lc-3 and delineated a region of 1.6 Mb containing candidate resistance genes. The identified SNP markers can be directly applied in marker-assisted selection (MAS) to accelerate the introgression of race 1 resistance in lentil breeding.

The tepary bean genome provides insight into evolution and domestication under heat stress.

Tepary bean (Phaseolus acutifolis A. Gray), native to the Sonoran Desert, is highly adapted to heat and drought. It is a sister species of common bean (Phaseolus vulgaris L.), the most important legume protein source for direct human consumption, and whose production is threatened by climate change. Here, we report on the tepary genome including exploration of possible mechanisms for resilience to moderate heat stress and a reduced disease resistance gene repertoire, consistent with adaptation to arid and hot environments. Extensive collinearity and shared gene content among these Phaseolus species will facilitate engineering climate adaptation in common bean, a key food security crop, and accelerate tepary bean improvement.

Genomic selection for lentil breeding: Empirical evidence.

Genomic selection (GS) is a marker-based selection initially suggested for livestock breeding and is being encouraged for crop breeding. Several statistical models are used to implement GS; however, none have been tested for use in lentil (Lens culinaris Medik.) breeding. This study was conducted to compare the accuracy of different GS models and prediction scenarios based on empirical data and to make recommendations for designing genomic selection strategies for lentil breeding. We evaluated nine single-trait (ST) models, two multiple-trait (MT) models, and a model that incorporates genotype × environment interaction (GEI) using populations from a lentil diversity panel and two recombinant inbred lines (RILs). The lines in all populations were phenotyped for five phenological traits and genotyped using a custom exome capture assay. Within-population, across-population, and across-environment genomic predictions were made. Prediction accuracy varied among the evaluated models, populations, prediction scenarios, and traits. Single-trait models showed similar accuracy in the absence of large effect quantitative trait loci (QTL) but BayesB outperformed all models when there were QTL with relatively large effects. Models that accounted for GEI and MT-GS models increased prediction accuracy for a low heritability trait by up to 66 and 14%, respectively. Moderate to high accuracies were obtained for within-population (range of .36-.85) and across-environment (range of .19-.89) predictions but across-population prediction accuracy was very low. Results suggest that GS can be implemented in lentil breeding to make predictions within populations and across environments, but across-population prediction should not be considered when the population size is small.

Capturing variation in Lens (Fabaceae): Development and utility of an exome capture array for lentil.

PREMISE OF THE STUDY: Lentil is an important legume crop with reduced genetic diversity caused by domestication bottlenecks. Due to its large and complex genome, tools for reduced representation sequencing are needed. We developed an exome capture array for use in various genetic diversity studies. METHODS: Based on the CDC Redberry draft genome, we developed an exome capture array using multiple sources of transcript resources. The probes were designed to target not only the cultivated lentil, but also wild species. We assessed the utility of the developed method by applying the generated data set to population structure and phylogenetic analyses. RESULTS: The data set includes 16 wild lentils and 22 cultivar accessions of lentil. Alignment rates were over 90%, and the genic regions were well represented in the capture array. After stringent filtering, 6.5 million high-quality variants were called, and the data set was used to assess the interspecific relationships within the genus Lens. DISCUSSION: The developed exome capture array provides large amounts of genomic data to be used in many downstream analyses. The method will have useful applications in marker-assisted breeding programs aiming to improve the quality of cultivated lentil.

Defense responses of lentil (Lens culinaris) genotypes carrying non-allelic ascochyta blight resistance genes to Ascochyta lentis infection.

Ascochyta blight of lentil is an important fungal disease in many lentil-producing regions of the world causing major yield and grain quality losses. Quick shifts in aggressiveness of the population of the causal agent Ascochyta lentis mandates developing germplasm with novel and durable resistance. In the absence of complete resistance, lentil genotypes CDC Robin and 964a-46 have frequently been used as sources of partial resistance to ascochyta blight and carry non-allelic ascochyta blight resistance genes. RNA-seq analysis was conducted to identify differences in the transcriptome of CDC Robin, 964a-46 and the susceptible check Eston after inoculation with A. lentis. Candidate defense genes differentially expressed among the genotypes had hypothetical functions in various layers of plant defense, including pathogen recognition, phytohormone signaling pathways and downstream defense responses. CDC Robin and 964a-46 activated cell surface receptors (e.g. receptor like kinases) tentatively associated with pathogen-associated molecular patterns (PAMP) recognition and nucleotide-binding site leucine-rich repeat (NBS-LRR) receptors associated with intracellular effector recognition upon A. lentis infection, and differed in their activation of salicylic acid, abscisic acid and jasmonic acid / ethylene signal transduction pathways. These differences were reflected in the differential expression of downstream defense responses such as pathogenesis-related proteins, and genes associated with the induction of cell death and cell-wall reinforcement. A significant correlation between expression levels of a selection of genes based on quantitative real-time PCR and their expression levels estimated through RNA-seq demonstrated the technical and analytical accuracy of RNA-seq for identification of genes differentially expressed among genotypes. The presence of different resistance mechanisms in 964a-46 and CDC Robin indicates their value for pyramiding gene leading to more durable resistance to ascochyta blight.

QTL mapping reveals genetic determinants of fungal disease resistance in the wild lentil species Lens ervoides.

Lens ervoides, a wild relative of lentil is an important source of allelic diversity for enhancing the genetic resistance of the cultivated species against economically important fungal diseases, such as anthracnose and Stemphylium blight caused by Colletotrichum lentis and Stemphylium botryosum, respectively. To unravel the genetic control underlying resistance to these fungal diseases, a recombinant inbred line (RIL) population (n = 94, F9) originating from a cross between two L. ervoides accessions, L01-827A and IG 72815, was genotyped on the Illumina HiSeq 2500 platform. A total of 289.07 million 100 bp paired-end reads were generated, giving an average 7.53-fold genomic coverage to the RILs and identifying 2,180 high-quality SNPs that assembled in 543 unique haplotypes. Seven linkage groups were resolved among haplotypes, equal to the haploid chromosome number in L. ervoides. The genetic map spanned a cumulative distance of 740.94 cM. Composite interval mapping revealed five QTLs with a significant association with resistance to C. lentis race 0, six QTLs for C. lentis race 1 resistance, and three QTLs for S. botryosum resistance. Taken together, the data obtained in the study reveal that the expression of resistance to fungal diseases in L. ervoides is a result of rearrangement of resistant alleles contributed by both parental accessions.

Classification and characterization of species within the genus lens using genotyping-by-sequencing (GBS).

Lentil (Lens culinaris ssp. culinaris) is a nutritious and affordable pulse with an ancient crop domestication history. The genus Lens consists of seven taxa, however, there are many discrepancies in the taxon and gene pool classification of lentil and its wild relatives. Due to the narrow genetic basis of cultivated lentil, there is a need towards better understanding of the relationships amongst wild germplasm to assist introgression of favourable genes into lentil breeding programs. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows multiplexing of up to 384 samples or more per library to generate genome-wide single nucleotide Polymorphism (SNP) markers. In this study, we aimed to characterize our lentil germplasm collection using a two-enzyme GBS approach. We constructed two 96-plex GBS libraries with a total of 60 accessions where some accessions had several samples and each sample was sequenced in two technical replicates. We developed an automated GBS pipeline and detected a total of 266,356 genome-wide SNPs. After filtering low quality and redundant SNPs based on haplotype information, we constructed a maximum-likelihood tree using 5,389 SNPs. The phylogenetic tree grouped the germplasm collection into their respective taxa with strong support. Based on phylogenetic tree and STRUCTURE analysis, we identified four gene pools, namely L. culinaris/L. orientalis/L. tomentosus, L. lamottei/L. odemensis, L. ervoides and L. nigricans which form primary, secondary, tertiary and quaternary gene pools, respectively. We discovered sequencing bias problems likely due to DNA quality and observed severe run-to-run variation in the wild lentils. We examined the authenticity of the germplasm collection and identified 17% misclassified samples. Our study demonstrated that GBS is a promising and affordable tool for screening by plant breeders interested in crop wild relatives.

Draft genome sequence of chickpea (Cicer arietinum) provides a resource for trait improvement.

Chickpea (Cicer arietinum) is the second most widely grown legume crop after soybean, accounting for a substantial proportion of human dietary nitrogen intake and playing a crucial role in food security in developing countries. We report the ∼738-Mb draft whole genome shotgun sequence of CDC Frontier, a kabuli chickpea variety, which contains an estimated 28,269 genes. Resequencing and analysis of 90 cultivated and wild genotypes from ten countries identifies targets of both breeding-associated genetic sweeps and breeding-associated balancing selection. Candidate genes for disease resistance and agronomic traits are highlighted, including traits that distinguish the two main market classes of cultivated chickpea--desi and kabuli. These data comprise a resource for chickpea improvement through molecular breeding and provide insights into both genome diversity and domestication.

Analysis of gene expression patterns during seed coat development in Arabidopsis.

The seed coat is important for embryo protection, seed hydration, and dispersal. Seed coat composition is also of interest to the agricultural sector, since it impacts the nutritional value for humans and livestock alike. Although some seed coat genes have been identified, the developmental pathways controlling seed coat development are not completely elucidated, and a global genetic program associated with seed coat development has not been reported. This study uses a combination of genetic and genomic approaches in Arabidopsis thaliana to begin to address these knowledge gaps. Seed coat development is a complex process whereby the integuments of the ovule differentiate into specialized cell types. In Arabidopsis, the outermost layer of cells secretes mucilage into the apoplast and develops a secondary cell wall known as a columella. The layer beneath the epidermis, the palisade, synthesizes a secondary cell wall on its inner tangential side. The innermost layer (the pigmented layer or endothelium) produces proanthocyanidins that condense into tannins and oxidize, giving a brown color to mature seeds. Genetic separation of these cell layers was achieved using the ap2-7 and tt16-1 mutants, where the epidermis/palisade and the endothelium do not develop respectively. This genetic ablation was exploited to examine the developmental programs of these cell types by isolating and collecting seed coats at key transitions during development and performing global gene expression analysis. The data indicate that the developmental programs of the epidermis and the pigmented layer proceed relatively independently. Global expression datasets that can be used for identification of new gene candidates for seed coat development were generated. These dataset provide a comprehensive expression profile for developing seed coats in Arabidopsis, and should provide a useful resource and reference for other seed systems.