RNA-Seq and Gene Ontology Analysis Reveal Differences Associated With Low R/FR-Induced Shade Responses in Cultivated Lentil and a Wild Relative.

Lentil is an important pulse crop not only because of its high nutrient value but also because of its ecological advantage in a sustainable agricultural system. Our previous work showed that the cultivated lentil and wild lentil germplasm respond differently to light environments, especially to low R/FR-induced shade conditions. Little is known about how cultivated and wild lentils respond to shade at the level of gene expression and function. In this study, transcriptomic profiling of a cultivated lentil (Lupa, L. culinaris) and a wild lentil (BGE 016880, L. orientalis) at several growth stages is presented. De novo transcriptomes were assembled for both genotypes, and differential gene expression analysis and gene ontology enrichment analysis were performed. The transcriptomic resources generated in this study provide fundamental information regarding biological processes and genes associated with shade responses in lentils. BGE 016880 and Lupa shared a high similarity in their transcriptomes; however, differential gene expression profiles were not consistent between these two genotypes. The wild lentil BGE 016880 had more differentially expressed genes than the cultivated lentil Lupa. Upregulation of genes involved in gibberellin, brassinosteroid, and auxin synthesis and signaling pathways, as well as cell wall modification, in both genotypes explains their similarity in stem elongation response under the shade. Genes involved in jasmonic acid and flavonoid biosynthesis pathways were downregulated in BGE 016880 only, and biological processes involved in defense responses were significantly enriched in the wild lentil BGE 016880 only. Downregulation of WRKY and MYB transcription factors could contribute to the reduced defense response in BGE 016880 but not in Lupa under shade conditions. A better understanding of shade responses of pulse crop species and their wild relatives will play an important role in developing genetic strategies for crop improvement in response to changes in light environments.

A PostgreSQL Tripal solution for large-scale genotypic and phenotypic data.

Researchers are seeking cost-effective solutions for management and analysis of large-scale genotypic and phenotypic data. Open-source software is uniquely positioned to fill this need through user-focused, crowd-sourced development. Tripal, an open-source toolkit for developing biological data web portals, uses the GMOD Chado database schema to achieve flexible, ontology-driven storage in PostgreSQL. Tripal also aids research-focused web portals in providing data according to findable, accessible, interoperable, reusable (FAIR) principles. We describe here a fully relational PostgreSQL solution to handle large-scale genotypic and phenotypic data that is implemented as a collection of freely available, open-source modules. These Tripal extension modules provide a holistic approach for importing, storage, display and analysis within a relational database schema. Furthermore, they embody the Tripal approach to FAIR data by providing multiple search tools and ensuring metadata is fully described and interoperable. Our solution focuses on data integrity, as well as optimizing performance to provide a fully functional system that is currently being used in the production of Tripal portals for crop species. We fully describe the implementation of our solution and discuss why a PostgreSQL-powered web portal provides an efficient environment for researcher-driven genotypic and phenotypic data analysis.

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.

KnowPulse: A Web-Resource Focused on Diversity Data for Pulse Crop Improvement.

KnowPulse (https://knowpulse.usask.ca) is a breeder-focused web portal for pulse breeders and geneticists. With a focus on diversity data, KnowPulse provides information on genetic markers, sequence variants, phenotypic traits and germplasm for chickpea, common bean, field pea, faba bean, and lentil. Genotypic data is accessible through the genotype matrix tool, displayed as a marker-by-germplasm table of genotype calls specific to germplasm chosen by the researcher. It is also summarized on genetic marker and sequence variant pages. Phenotypic data is visualized in trait distribution plots: violin plots for quantitative data and histograms for qualitative data. These plots are accessible through trait, germplasm, and experiment pages, as well as through a single page search tool. KnowPulse is built using the open-source Tripal toolkit and utilizes open-source tools including, but not limited to, species-specific JBrowse instances, a BLAST interface, and whole-genome CViTjs visualizations. KnowPulse is constantly evolving with data and tools added as they become available. Full integration of genetic maps and quantitative trait loci is imminent, and development of tools exploring structural variation is being explored.

Construction of high-density linkage maps for mapping quantitative trait loci for multiple traits in field pea (Pisum sativum L.).

BACKGROUND: The objective of this research was to map quantitative trait loci (QTLs) of multiple traits of breeding importance in pea (Pisum sativum L.). Three recombinant inbred line (RIL) populations, PR-02 (Orb x CDC Striker), PR-07 (Carerra x CDC Striker) and PR-15 (1-2347-144 x CDC Meadow) were phenotyped for agronomic and seed quality traits under field conditions over multiple environments in Saskatchewan, Canada. The mapping populations were genotyped using genotyping-by-sequencing (GBS) method for simultaneous single nucleotide polymorphism (SNP) discovery and construction of high-density linkage maps. RESULTS: After filtering for read depth, segregation distortion, and missing values, 2234, 3389 and 3541 single nucleotide polymorphism (SNP) markers identified by GBS in PR-02, PR-07 and PR-15, respectively, were used for construction of genetic linkage maps. Genetic linkage groups were assigned by anchoring to SNP markers previously positioned on these linkage maps. PR-02, PR-07 and PR-15 genetic maps represented 527, 675 and 609 non-redundant loci, and cover map distances of 951.9, 1008.8 and 914.2 cM, respectively. Based on phenotyping of the three mapping populations in multiple environments, 375 QTLs were identified for important traits including days to flowering, days to maturity, lodging resistance, Mycosphaerella blight resistance, seed weight, grain yield, acid and neutral detergent fiber concentration, seed starch concentration, seed shape, seed dimpling, and concentration of seed iron, selenium and zinc. Of all the QTLs identified, the most significant in terms of explained percentage of maximum phenotypic variance (PVmax) and occurrence in multiple environments were the QTLs for days to flowering (PVmax = 47.9%), plant height (PVmax = 65.1%), lodging resistance (PVmax = 35.3%), grain yield (PVmax = 54.2%), seed iron concentration (PVmax = 27.4%), and seed zinc concentration (PVmax = 43.2%). CONCLUSION: We have identified highly significant and reproducible QTLs for several agronomic and seed quality traits of breeding importance in pea. The QTLs identified will be the basis for fine mapping candidate genes, while some of the markers linked to the highly significant QTLs are useful for immediate breeding applications.

Single Nucleotide Polymorphism Markers Associated with Seed Quality Characteristics of Cultivated Lentil.

The dimensions of lentil ( Medik.) seeds are important quality parameters that are major determinants of market preference, cooking time, and post-harvest milling quality. Knowledge of the genetic control of traits related to seed dimensions would be useful for crop improvement. The principal aim of this study was to identify single nucleotide polymorphism (SNP) markers linked to genes that control seed diameter, seed thickness, and seed plumpness. Association mapping analysis with SNP markers was used to study the seed dimensions of 138 diverse cultivated lentil accessions grown at two locations in Saskatchewan, Canada, in 2011 and 2012. Six marker-trait associations were shown to be significant for the studied seed dimension characteristics. Two SNP markers closely associated with seed diameter across locations and years identified in previous work were validated in this study. Three additional marker-seed thickness associations were identified. Using the association mapping strategy, we confirmed the presence of two genomic regions controlling seed diameter and plumpness. This information can be used worldwide as a resource for lentil seed quality improvement programs.

Marker-Trait Association Analysis of Iron and Zinc Concentration in Lentil (Lens culinaris Medik.) Seeds.

Lentil ( Medik.) seeds are relatively rich in iron (Fe) and zinc (Zn), making lentil a potential crop to aid in the global battle against human micronutrient deficiency. Understanding the genetic basis for uptake of seed Fe and Zn is required to increase sustainable concentrations of these minerals in seeds. The objectives of this study were to characterize genetic variation in seed Fe and Zn concentration and to identify molecular markers associated with these traits across diverse lentil accessions. A set of 138 cultivated lentil accessions from 34 countries were evaluated in four environments (2 sites × 2 yr) in Saskatchewan, Canada. The collection was genotyped using 1150 single-nucleotide polymorphism (SNP) markers that are distributed across the lentil genome. The germplasm tested exhibited a wide range of variation for seed Fe and Zn concentration. The marker-trait association analysis detected two SNP markers tightly linked to seed Fe and one linked to seed Zn concentration (-log10 ≥ 4.36). Additional markers were detected at -log10 ≥ 3.06. A number of putative candidate genes underlying detected loci encode Fe- and Zn-related functions. This study provides insight into the genetics of seed Fe and Zn concentration of lentil and opportunities for marker-assisted selection to improve micronutrient concentration as part of micronutrient biofortification programs.

Genetic Diversity of Cultivated Lentil (Lens culinaris Medik.) and Its Relation to the World's Agro-ecological Zones.

Assessment of genetic diversity and population structure of germplasm collections plays a critical role in supporting conservation and crop genetic enhancement strategies. We used a cultivated lentil (Lens culinaris Medik.) collection consisting of 352 accessions originating from 54 diverse countries to estimate genetic diversity and genetic structure using 1194 polymorphic single nucleotide polymorphism (SNP) markers which span the lentil genome. Using principal coordinate analysis, population structure analysis and UPGMA cluster analysis, the accessions were categorized into three major groups that prominently reflected geographical origin (world's agro-ecological zones). The three clusters complemented the origins, pedigrees, and breeding histories of the germplasm. The three groups were (a) South Asia (sub-tropical savannah), (b) Mediterranean, and (c) northern temperate. Based on the results from this study, it is also clear that breeding programs still have considerable genetic diversity to mine within the cultivated lentil, as surveyed South Asian and Canadian germplasm revealed narrow genetic diversity.

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.

Using crude whole-genome assemblies of Neisseria gonorrhoeae as a platform for strain analysis: clonal spread of gonorrhea infection in Saskatchewan, Canada.

Using crude whole-genome assemblies, we analyzed 25 isolates of Neisseria gonorrhoeae by using a high-resolution single nucleotide polymorphism (SNP) approach for nine housekeeping genes, characterizing penA alleles, and antimicrobial susceptibility phenotypes coupled with population structure analysis. Two clonal complexes, characterized by their spatial and geographical persistence, were identified. In addition, the clonal spread of penicillin-resistant/intermediate phenotypes and a novel introduction of the azithromycin resistance phenotype in Saskatchewan, Canada, were ascertained using this method.