Genetic Diversity and Population Structure of Mexican Gir Cattle Using Genome-Wide SNP Data
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ID: 321373
2026
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Abstract
Abstract This study characterizes the genomic diversity and population structure of Mexican Gir cattle. We sampled 226 animals from three tropical herds and isolated DNA from hair samples was genotyped using the GGP Indicus 50K array. After quality control, 212 animals and 28,394 autosomal SNPs remained for a within-breed analysis. We merged the Mexican Gir dataset with an available online database involving 134 worldwide breeds. The combined dataset was used for across-breed comparisons, with 9,091 shared SNPs. Within-breed diversity was high (Heterozygosity Observed = 0.40; Heterozygosity Expected = 0.38), and genomic inbreeding by Hardy-Weinberg Equilibrium (FIS=-0.04), by Genomic Relationship Matrix (FGRM=-0.02) and by Runs of Homozygosity (FROH=0.07) was low. Runs of Homozygosity were dominated by short segments (1–2 Mb), which accounted for 75% of the total detected segments, consistent with historical rather than recent inbreeding. Multidimensional scaling grouped Mexican Gir with Asian zebu, particularly Gir from India and Pakistan; pairwise Fixation Index values were lowest versus Gir, Red Sindhi, Lohani, Rojhan, and Tharparkar, and IBS heatmaps showed greater similarity to Asian indicine than to unrelated zebu. ADMIXTURE-supported ancestry components were concordant with the breed’s introduction history. Overall, Mexican Gir exhibit ample genetic variability and low recent inbreeding, providing a robust foundation to intensify selection for productivity and tropical adaptation while safeguarding diversity. These results support genomic monitoring (FIS, FGRM, FROH), balanced sire usage, and targeted germplasm introduction as management priorities.
| Reference Key |
openalex_W7169533923
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| Authors | Ricardo Martínez-Rocha, Jonathan Emanuel Valerio-Hernández, Rafael Núñez-Domínguez, Rodolfo Ramírez-Valverde, Joel Domínguez-Viveros, Juan Fernando Saiz, Julius Mugambe, Jorge Hidalgo |
| Journal | Translational animal science |
| Year | 2026 |
| DOI |
10.1093/tas/txag094
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| URL | |
| Keywords | Keywords not found |
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