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, however, surveyed South Asian and Canadian germplasm revealed narrow genetic diversity

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

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

Abstract 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

Phylogenetic relationship within genus <i>Lens</i>.

<p>(A) Dendrogram generated using Neighbour-Joining model based on results from first GBS library. (B) A maximum-likelihood tree based on combined results from two GBS libraries.</p

Detailed steps performed by automated GBS pipeline.

<p>(A) De-multiplex samples: Raw paired-end Illumina reads are assigned to a sample using barcode sequences, which are subsequently trimmed. (B) Trim and filter reads: De-multiplexed paired-end reads are trimmed for base quality and Illumina adaptors. (C) Align reads to a reference genome. (D) Raw SNP calls: Every position in each sample’s alignment is scanned to determine the probability of a variant.</p

Classification and Characterization of Species within the Genus <i>Lens</i> Using Genotyping-by-Sequencing (GBS)

<div><p>Lentil (<i>Lens culinaris</i> ssp. <i>culinaris</i>) is a nutritious and affordable pulse with an ancient crop domestication history. The genus <b>Lens</b> 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 <i>L</i>. <i>culinaris/L</i>. <i>orientalis/L</i>. <i>tomentosus</i>, <i>L</i>. <i>lamottei/L</i>. <i>odemensis</i>, <i>L</i>. <i>ervoides</i> and <i>L</i>. <i>nigricans</i> 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.</p></div

Gene pool classification of lentil based on STRUCTURE results.

<p>(A) Graphical representation of STRUCTURE results indicates two clusters (K = 2) in genus <i>Lens</i> based on the highest delta K score. (B) Additional STRUCTURE analysis revealed substructures (K = 3) within individuals of <i>L</i>. <i>odemensis</i>, <i>L</i>. <i>lamottei</i>, <i>L</i>. <i>ervoides</i> and <i>L</i>. <i>nigricans</i>. (C) The new gene pool classification proposed in this study is shown next to a simplified maximum-likelihood tree of genus <i>Lens</i>. Accession IG 72815 is marked with asterisk.</p

Gene-based SNP discovery and genetic mapping in pea

International audienceGene-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