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Updated: May 2, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Genomic dissection of phenological and yield-associated traits in lentil (Lens culinaris Medik.) using genome-wide
Yogesh Dashrath Naik1, Vinay Kumar Sharma1, Muraleedhar S Aski2
1Department of Agricultural Biotechnology and Molecular Biology, Dr. Rajendra Prasad Central Agricultural University (RPCAU), Pusa, Bihar India.
Abstract:
Lentil (Lens culinaris Medik.), a nutrient-rich legume cultivated worldwide, plays a vital role in combating malnutrition and hidden hunger. Understanding the genetic architecture underlying key phenological and agronomic traits in lentil is crucial for accelerating molecular breeding. In this study, genome-wide association mapping was conducted using 142 genetically diverse lentil accessions, evaluated across two field environments over two years. High-throughput sequencing generated 34,995 high-quality single-nucleotide polymorphisms, which were used for genetic characterization and for the identification of marker-trait associations for phenological and yield-associated traits. Population structure analysis identified three subpopulations (K = 3), with UPGMA clustering showing a similar pattern. Association mapping was performed using multi-locus models and further confirmed through a single-locus generalized linear model. A total of 64 significant associations were identified, of which Chr5_342836807 and Chr6_200603138 were consistently detected across all environments for days to 50% flowering. Putative candidate genes located near these phenology-associated loci such as abscisate β-glucosyltransferase, pentatricopeptide repeat proteins, and transcription factors from the MYB, MADS-box, and GRAS families are likely involved in flowering-time regulation in lentil. These findings reveal novel associations between genetic variants and complex traits and identify putative genes that may be exploited in marker-assisted selection and genomic prediction strategies.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s12298-026-01739-x.
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