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

Abstract

BackgroundThe 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.ResultsWe 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.ConclusionsThe 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.

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

“…To select the regions of interest in the genome for the array, we used several sources: (1) the coding DNA sequence from the Medicago truncatula Gaertn. genome version Mt4.0 (Tang et al., 2014); (2) Illumina RNA‐Seq reads from L. culinaris 2 × 250 MiSeq data (BioProject PRJNA434239); and (3) a collection of previously generated L. culinaris Sanger expressed sequence tags, 454 reads, and contigs (Sharpe et al., 2013 [BioProject PRJNA192531]; Kaur et al., 2011). RNA‐Seq reads were aligned to the reference genome Lc1.2 using TopHat 2.1.1 (Trapnell et al., 2009), and Cufflinks 2.2.1 (Trapnell et al., 2010) was used to determine the transcript coordinates.…”

QTLs for iron concentration in seeds of the cultivated lentil (Lens culinaris Medic.) via genotyping by sequencing

“…Most linkage maps of lentil have been constructed using RAPD, SSR, ISSR, and AFLP markers. The linkage maps of lentil constructed by Sharpe et al (2013) and Ates et al (2016) had 537 and 1780 SNP markers, respectively, which is less than the 4177 SNPs in the current study. The number of mapping markers in this study, 4177, is higher than the results from other linkage maps [e.g., 114 (Rubeena et al, 2003) to 283 (Hamwieh et al, 2005)].…”

“…The total length of the linkage map was 497.1 cM in the current study. In previous lentil mapping studies, lengths of the linkage maps varied from 751 cM to 4060.6 cM (Eujayl et al, 1998;Rubeena et al, 2003;Duran et al, 2004;Hamwieh et al, 2005;Tanyolac et al, 2010;Gupta et al, 2012;De la Puente et al, 2013;Sharpe et al, 2013;Gujaria-Verma, 2014;Ates et al, 2016). The length of the map reported here was shorter than in these previous studies, but the value was close to the findings (751 cM) published by Hamwieh et al (2005).…”

“…Due to cost efficiencies, GBS is a preferred approach when constructing linkage maps of mapping populations with high-density SNP markers . Many such SNP-based maps and/or QTL maps have been constructed in plant species such as lentil (Sharpe et al, 2013;GujariaVerma et al, 2014;Ates et al, 2016), maize Li et al, 2015), maize and barley (Elshire et al, 2011), wheat and barley (Poland et al, 2012), chickpea (Jaganathan et al, 2015), cotton (Gossypium hirsutum L.) (Gore et al, 2014), potato (Solanum tuberosum L.) (Uitdewilligen et al, 2013), raspberry (Rubus idaeus L.) (Ward et al, 2013), wheat (Saintenac et al, 2013), apple (Malus spp.) (Gardner et al, 2014), barley (Mascher et al, 2013;Liu et al, 2014), canola (Raman et al, 2014), cassava (Manihot esculenta Crantz) (Rabbi et al, 2014), oat (Avena sativa L.) (Huang et al, 2014), and soybean (Sonah et al, 2013;Bastien et al, 2014).…”

A SNP-Based Genetic Linkage Map of Soybean Using the SoyS - NP6K Illumina Infinium BeadChip Genotyping Array

“…Among these molecular markers, single nucleotide polymorphisms (SNPs) represent the most suitable because they occurred at high density within genomes (Gaur et al, 2012). Millions of SNPs were generated in Soybean (Lam et al, 2010), Arabidopsis , Rice (Subbaiyan et al, 2012;Xu et al, 2012), and other crops (Sim et al, 2012a,b;Sharpe et al, 2013;Delourme et al, 2013). High-throughput SNP genotyping is widely used in plant genomics studies such as genome-wide association (Atwell et al, 2010;Huang et al, 2010;Tian et al, 2011;Branca et al, 2010), comparative genomics (Muchero et al, 2009;Luo et al, 2009), and genetic linkage maps construction (Shirasawa et al, 2010;Huo et al, 2011).…”