Genetic Diversity in Chickpea (Cicer arietinum L.) Using Microsatellite Markers
Malagouda D. Patil *
Department of Genetics and Plant Breeding, College of Agriculture, Vijayapur, UAS, Dharwad, India and AICRP on MULLaRP, MARS, UAS, Dharwad, India.
L. M. B. Ashwini
Department of Genetics and Plant Breeding, College of Agriculture, Vijayapur, UAS, Dharwad, India.
Amruta P. Barigal
AICRP on MULLaRP, MARS, UAS, Dharwad, India.
Babu N. Motagi
AICRP on Safflower, Agricultural Research Station, Annigeri, India.
Chandrakant D. Soregaon
Department of Genetics and Plant Breeding, College of Agriculture, Vijayapur, UAS, Dharwad, India.
Rajkumar B. Jolli
Regional Agricultural Research Station, Vijayapur, India.
*Author to whom correspondence should be addressed.
Abstract
Aim: This study assessed SSR-based genetic diversity among 75 chickpea (Cicer arietinum L.) genotypes to identify genetically diverse parental resources for chickpea improvement.
Study Design: Laboratory-based molecular characterisation and genetic diversity analysis using SSR markers followed by similarity and cluster analyses.
Place and Duration of Study: Molecular Biology Laboratory, Department of Biotechnology, College of Agriculture, Vijayapur, University of Agricultural Sciences, Dharwad in 2021.
Methodology: Seventy-five chickpea genotypes were characterised using 20 polymorphic SSR markers distributed across the genome. Genomic DNA was extracted from young leaf samples using the CTAB method, followed by PCR amplification and separation of SSR products on 3% agarose gels. The amplification profiles were scored as binary data and used to estimate genetic similarity based on the Nei and Li coefficient. Genetic relationships were assessed through UPGMA cluster analysis using NTSYSpc and marker informativeness was evaluated using polymorphic information content (PIC).
Results: The 20 SSR markers generated a total of 73 alleles across the 75 chickpea genotypes, with an average of 3.65 alleles per marker. The number of alleles per marker ranged from 1 to 6, with TA22, TA28 and TA29 exhibiting the highest allelic variation (6 alleles each). PIC values ranged from 0.419 (TA194) to 0.797 (TA28), with 17 markers recording PIC values above 0.50, indicating their high discriminatory potential. UPGMA cluster analysis grouped the genotypes into 23 distinct clusters, with Cluster II being the largest (29 genotypes), followed by Cluster I (10 genotypes), while the remaining clusters comprised fewer or single genotypes, reflecting substantial genetic differentiation among the genotypes.
Conclusion: The SSR markers effectively revealed substantial genetic diversity and distinct molecular relationships among the chickpea genotypes. The identified genetically diverse genotypes can be utilised as promising parents to broaden the breeding base and develop diverse populations for improving chickpea productivity and adaptability.
Keywords: Chickpea, genetic similarity, SSR markers, UPGMA clustering, molecular characterization