Genetic characterization of semi-arid sheep populations in India using microsatellite markers

Introduction The vast genetic diversity of Indian sheep in semi-arid regions remains largely unexplored, posing difficulties in conservation and sustainable management. Genetic characterization is essential for safeguarding these breeds and designing selective breeding strategies to enhance their resilience and productivity. To bridge this knowledge gap, an investigation was undertaken to genetically characterize different populations of semi-arid sheep (Nellore breed Palla, Brown, and Jodipi phenotypic strains, Macherla and Vizianagaram sheep) from India through microsatellite loci and to explore their genetic divergence. Methods Blood samples and genetic data from five distinct sheep populations were collected from 672 shepherds across 162 flocks. To ensure a thorough genetic characterization, thirty microsatellite markers were utilized. Genetic diversity and population structure were then analyzed using MICROCHECKER, LDNe, STRUCTURE, and Genepop. Results and Discussion Vizianagaram sheep population displayed the highest allele count (276) with a mean allele number of 12.545, while Nellore Palla had the lowest allele count (205) with a mean allele number of 9.318. Private alleles identified in the populations were 22, 33, 48, 57, and 41 for Macherla, Nellore Brown, Nellore Jodipi, Vizianagaram, and Nellore Palla sheep, respectively. The mean observed heterozygosity (Ho) values ranged from 0.587 to 0.732, while the expected heterozygosity (He) values ranged from 0.692 to 0.769 among the populations studied. The microsatellite markers demonstrated a high level of polymorphism, with the Polymorphic Information Content (PIC) value ranging from 0.61 to 0.85. The most notable genetic differentiation among the populations investigated was observed between Vizianagaram and Palla sheep, as evidenced by a high FST value of 0.180. Conversely, the lowest genetic differentiation was recorded between Macherla and Nellore Brown sheep, with an FST value of 0.011. Nei’s unbiased genetic distance varied across populations, with the highest distance observed between Nellore Palla and Vizianagaram sheep (0.926) and the lowest between Macherla and Nellore Brown sheep (0.032), complementing the results of genetic differentiation using FST value. Bottleneck analysis conducted across all populations revealed an abundance of low-frequency alleles, suggesting the absence of recent bottlenecks. Effective population size is optimum in all populations except Nellore Palla and Brown sheep. Structure analysis and factorial correspondence analysis revealed that the five sheep populations under study were distributed into three distinct clusters, with Palla forming a separate cluster. Furthermore, the results of principal component analysis demonstrated that Palla sheep formed a separate sub-cluster within the cluster containing Brown and Macherla sheep. The findings provide valuable insights for conservation and sustainable utilization of the sheep populations for breeding programs.

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Journal
Frontiers in Animal Science
Published
2025-04-08
DOI
https://doi.org/10.3389/fanim.2025.1553610
Citations
3
Primary Topic
Genetic and phenotypic traits in livestock
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article
Field-Weighted Citation Impact
5.45
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article

Genetic characterization of semi-arid sheep populations in India using microsatellite markers

Vinoo Regula, Muralidhar Metta, K. Sudhakar, Panduranga Reddy Punuru et al.
3 citations
Frontiers in Animal Science
Genetic and phenotypic traits in livestock
5.45
article

Genetic characterization of semi-arid sheep populations in India using microsatellite markers

Vinoo Regula, Muralidhar Metta, K. Sudhakar, Panduranga Reddy Punuru, Jaya Madhuri Bhumireddy, Prasanna Baratam, Vani Sunkara, Ravikanth Reddy Poonooru
article en
3 citations

Abstract

Introduction The vast genetic diversity of Indian sheep in semi-arid regions remains largely unexplored, posing difficulties in conservation and sustainable management. Genetic characterization is essential for safeguarding these breeds and designing selective breeding strategies to enhance their resilience and productivity. To bridge this knowledge gap, an investigation was undertaken to genetically characterize different populations of semi-arid sheep (Nellore breed Palla, Brown, and Jodipi phenotypic strains, Macherla and Vizianagaram sheep) from India through microsatellite loci and to explore their genetic divergence. Methods Blood samples and genetic data from five distinct sheep populations were collected from 672 shepherds across 162 flocks. To ensure a thorough genetic characterization, thirty microsatellite markers were utilized. Genetic diversity and population structure were then analyzed using MICROCHECKER, LDNe, STRUCTURE, and Genepop. Results and Discussion Vizianagaram sheep population displayed the highest allele count (276) with a mean allele number of 12.545, while Nellore Palla had the lowest allele count (205) with a mean allele number of 9.318. Private alleles identified in the populations were 22, 33, 48, 57, and 41 for Macherla, Nellore Brown, Nellore Jodipi, Vizianagaram, and Nellore Palla sheep, respectively. The mean observed heterozygosity (Ho) values ranged from 0.587 to 0.732, while the expected heterozygosity (He) values ranged from 0.692 to 0.769 among the populations studied. The microsatellite markers demonstrated a high level of polymorphism, with the Polymorphic Information Content (PIC) value ranging from 0.61 to 0.85. The most notable genetic differentiation among the populations investigated was observed between Vizianagaram and Palla sheep, as evidenced by a high FST value of 0.180. Conversely, the lowest genetic differentiation was recorded between Macherla and Nellore Brown sheep, with an FST value of 0.011. Nei’s unbiased genetic distance varied across populations, with the highest distance observed between Nellore Palla and Vizianagaram sheep (0.926) and the lowest between Macherla and Nellore Brown sheep (0.032), complementing the results of genetic differentiation using FST value. Bottleneck analysis conducted across all populations revealed an abundance of low-frequency alleles, suggesting the absence of recent bottlenecks. Effective population size is optimum in all populations except Nellore Palla and Brown sheep. Structure analysis and factorial correspondence analysis revealed that the five sheep populations under study were distributed into three distinct clusters, with Palla forming a separate cluster. Furthermore, the results of principal component analysis demonstrated that Palla sheep formed a separate sub-cluster within the cluster containing Brown and Macherla sheep. The findings provide valuable insights for conservation and sustainable utilization of the sheep populations for breeding programs.

Frontiers in Animal ScienceVol. 6
Sri Venkateswara Veterinary University (IN), University of Missouri (US)
Openalex Percentile: Top 5%
Genetic and phenotypic traits in livestock
5.45
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