Genetic Diversity and Population Structure of Madhuca longifolia in Tamil Nadu, India Revealed by SSR Markers

Madhuca longifolia a multipurpose tree species of significant ecological and socioeconomic importance, remains underexplored at the molecular level despite its wide distribution and utility. The present study aimed to assess the genetic diversity and population structure of M. longifolia accessions collected from Tamil Nadu, India and to evaluate the effectiveness of simple sequence repeat (SSR) markers for molecular characterization and precision breeding applications. A total of 56 accessions representing three geographic populations (South, Central and North) were genotyped using 15 polymorphic SSR markers developed through transcriptome analysis. The markers exhibited high polymorphism, with polymorphic information content (PIC) values ranging from 0.608 to 0.666, indicating strong discriminatory power. Genetic diversity parameters revealed substantial allelic richness across populations, with mean expected heterozygosity (He = 0.657) and Shannon’s information index (I = 1.080). Population-level analysis indicated moderate genetic differentiation, with Nei’s genetic distance ranging from 0.553 to 1.319 and the highest divergence observed between Central and North populations. Analysis of molecular variance (AMOVA) demonstrated that 75% of the total genetic variation resided within individuals, while only 18% was attributed to differences among populations, suggesting extensive gene flow and outcrossing behavior. Cluster analysis and dendrogram construction grouped the accessions into distinct genetic clusters corresponding to geographic origin, with certain clusters exhibiting high genetic divergence, highlighting their potential for heterosis breeding. The identification of highly informative loci such as MLO24 and MLO33 further strengthens their applicability in molecular fingerprinting and germplasm management. Overall, the study confirms that M. longifolia populations in Tamil Nadu possess high genetic diversity and a structured yet interconnected genetic architecture. These findings provide a robust foundation for conservation strategies, marker-assisted selection and the development of precision breeding programs aimed at improving economically important traits.