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Genomic dissection of phenological and yield-associated traits in lentil (Lens culinaris Medik.) using genome-wide association mapping
Journal article   Open access   Peer reviewed

Genomic dissection of phenological and yield-associated traits in lentil (Lens culinaris Medik.) using genome-wide association mapping

Yogesh Dashrath Naik, Vinay Kumar Sharma, Muraleedhar S. Aski, K. M. Shivaprasad, Mangesh Pralhad Jadhav, Manda Sriswathi, Damaris A. Odeny, Kumari Anjani, Somashekhar Punnuri, Rajeev K. Varshney, …
Physiology and molecular biology of plants
2026
DOI: https://doi.org/10.1007/s12298-026-01739-x
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Abstract

Life Sciences & Biomedicine Plant Sciences Science & Technology
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 beta-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.

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