ArticlePloS one2015
Construction of a Genetic Linkage Map and Identification of QTLs for Seed Weight and Seed Size Traits in Lentil (Lens culinaris Medik.).
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed, 66 citations in OpenAlex.
- Identification of a robust QTL hotspot across environments governing drought tolerance in lentil (Lens culinaris Medikus).BMC genomics · 2026Article
- Genomic Regions Associated with Drought Tolerance and Other Traits in Lentils (Plants (Basel, Switzerland) · 2026Article
- Identification of novel genes associated with herbicide tolerance in Lentil (Lens culinaris ssp. culinaris Medik.).Scientific reports · 2024Article
- Omics technologies towards sesame improvement: a review.Molecular biology reports · 2023Review
- Next-Generation-Sequencing-Based Simple Sequence Repeat (SSR) Marker Development and Linkage Mapping in Lentil (Life (Basel, Switzerland) · 2023Article
- Genomic selection for target traits in the Australian lentil breeding program.Frontiers in plant science · 2023Article
- Morpho-biochemical characterization of a RIL population for seed parameters and identification of candidate genes regulating seed size trait in lentil (Frontiers in plant science · 2023Article
- The Prospects of gene introgression from crop wild relatives into cultivated lentil for climate change mitigation.Frontiers in plant science · 2023Review
- Construction of a high-density genetic map for faba bean (Frontiers in plant science · 2023Article
- Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate-Lentil a Case Study.Frontiers in plant science · 2022Review
- Article
- Genomics Associated Interventions for Heat Stress Tolerance in Cool Season Adapted Grain Legumes.International journal of molecular sciences · 2021Review
- Mapping QTL for important seed traits in an interspecific F2 population of pigeonpea.3 Biotech · 2020Article
- Article
- Identification of genomic regions associated with early plant vigour in lentil (Journal of genetics · 2020Article
- A high-density genetic map constructed using specific length amplified fragment (SLAF) sequencing and QTL mapping of seed-related traits in sesame (Sesamum indicum L.).BMC plant biology · 2019Article
- Article
- Genotyping by Sequencing of Cultivated Lentil (Frontiers in genetics · 2019Article
- Identification of a SiCL1 gene controlling leaf curling and capsule indehiscence in sesame via cross-population association mapping and genomic variants screening.BMC plant biology · 2018Article
- Genetic Mapping of Milling Quality Traits in Lentil (The plant genome · 2018Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Seed weight and seed size both are quantitative traits and have been considered as important components of grain yield, thus identification of quantitative trait loci (QTL) for seed traits in lentil (Lens culinaris) would be beneficial for the improvement of grain yield. Hence the main objective of this study was to identify QTLs for seed traits using an intraspecific mapping population derived from a cross between L. culinaris cv. Precoz (seed weight-5.1g, seed size-5.7mm) and L. culinaris cv. L830 (seed weight-2.2g, seed size-4mm) comprising 126 F8-RILs. For this, two microsatellite genomic libraries enriched for (GA/CT) and (GAA/CTT) motif were constructed which resulted in the development of 501 new genomic SSR markers. Six hundred forty seven SSR markers (including 146 previously published) were screened for parental polymorphism and 219 (33.8%) were found to be polymorphic among the parents. Of these 216 were mapped on seven linkage groups at LOD4.0 spanning 1183.7cM with an average marker density of 5.48cM. Phenotypic data from the RILs was used to identify QTLs for the seed weight and seed size traits by single marker analysis (SMA) followed by composite interval mapping (CIM) which resulted in one QTL each for the 2 traits (qSW and qSS) that were co-localized on LG4 and explained 48.4% and 27.5% of phenotypic variance respectively. The current study would serve as a strong foundation for further validation and fine mapping for utilization in lentil breeding programs.
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