Genetic diversity and genome-scale population structure of wild Indian major carp, Labeo catla (Hamilton, 1822), revealed by genotyping-by-sequencing

Labeo catla (catla) is the second most commercially important and widely cultured Indian major carp (IMC). It is indigenous to the Indo-Gangetic riverine system of India and the rivers of Bangladesh, Nepal, Myanmar, and Pakistan. Despite the availability of substantial genomic resources in this important species, detailed information on the genome-scale population structure using SNP markers is yet to be reported. In the present study, the identification of genome-wide single nucleotide polymorphisms (SNPs) and population genomics of catla was undertaken by re-sequencing six catla populations of riverine origin from distinct geographical regions. DNA isolated from 100 samples was used to perform genotyping-by-sequencing (GBS). A published catla genome with 95% genome coverage was used as the reference for mapping reads using BWA software. From a total of 472 million paired-end (150 × 2 bp) raw reads generated in this study, we identified 10,485 high-quality polymorphic SNPs using the STACKS pipeline. Expected heterozygosity (He) across the populations ranged from 0.162 to 0.20, whereas observed heterozygosity (Ho) ranged between 0.053 and 0.06. The nucleotide diversity (π) was the lowest (0.168) in the Ganga population. The within-population variation was found to be higher (95.32%) than the among-population (4.68%) variation. However, genetic differentiation was observed to be low to moderate, with F(st) values ranging from 0.020 to 0.084, and the highest between Brahmani and Krishna populations. Bayesian and multivariate techniques were used to further evaluate the population structure and supposed ancestry in the studied populations using the structure and discriminant analysis of principal components (DAPC), respectively. Both analyses revealed the existence of two separate genomic clusters. The maximum number of private alleles was observed in the Ganga population. The findings of this study will contribute to a deeper understanding of the population structure and genetic diversity of wild populations of catla for future research in fish population genomics.