New-generation sequencing technologies, among them SNP chips for massive genotyping, have proven to be useful for the effective management of genetic resources. Also, developing nucleus herds is an effective method for genetic improvement work. To date, molecular studies in Peruvian cattle are still in their infancy. To close this gap, we here employed two SNP panels (BovineHD and Bovine100K) to determine for the first time the Peruvian nucleus herd’s genetic diversity and population structure that belong to INIA. This nucleus comprises Brahman (N=16), Braunvieh (N=14), Gyr (N=11), and Fleckvieh (N=22) breeds. Additionally, samples from a locally adapted creole cattle, the Arequipa Fighting Bull (AFB, N=12), were incorporated into the study. The genetic diversity indices in all breeds showed a high proportion of polymorphic SNPs, varying from 69.37% in Gyr to 80.81% in Braunvieh. Also, Braunvieh possessed the highest observed heterozygosity (0.53±0.17), while Brahman possessed the lowest (0.44±0.10), indicating that the former is more diverse compared to the other cattle breed groups. According to the molecular variance analysis, 83.92% of the variance occurs within individuals, whereas 16.0% occurs between populations. The pairwise FST estimates between breeds showed values that ranged from 0.054 (Braunvieh vs AFB) to 0.266 (Brahman vs AFB). Pairwise Reynold’s distance showed a pattern similar to the one obtained with the FST statistics, with values ranging from 0.058 to 0.309. A dendrogram was constructed using the Neighbor-Joining clustering algorithm, and similar to the principal coordinate analysis, three groups were identified. Results showed a clear separation between Bos indicus (Brahman and Gyr) and B. taurus breeds (Braunvieh and Fleckvieh). For Fleckvieh and Braunvieh, there were two subgroups each one of them grouping with the AFB group. Similar results were obtained with ADMIXTURE analysis with K= 3 as the most optimal number for the inferred genetic structure of the populations. The results from the current study would contribute to the appropriate management avoiding loss of genetic variability in these breeds and to future improvements for this nucleus. Additional work is needed to speed up the breeding process in the Peruvian cattle system.

A total of 63 blood samples were collected from four commercial breeds of taurus and indicus cattle (Brahman, Braunvieh, Gyr, and Fleckvieh). According to their pedigree, up to grandfathers, genetic origins for Brahman and Gyr were predominantly from Brasil; for Braunvieh, Switzerland and Colombia; while for Fleckvieh was Germany (Supplementary material 1). Blood sampling was performed from a government herd (EEA Donoso) located in Huaral, Lima (128 masl; 11º31’18’’ S and 77º14’06’’ W). Precautions were taken to avoid sampling from related individuals. Blood samples were collected from the epidural vein using a vacutainer containing EDTA as an anticoagulant and were immediately transferred to the laboratory for DNA extraction. Additionally, hair samples were collected from the tail of Arequipa fighting bull (AFB) bovines from the Andagua district, Castilla province, in Arequipa (3574 masl; −15.499548◦, −72.359927◦). These individuals were selected as they possessed most of the morphological characteristics of a PCC. In addition, the owners indicated its parents were also creole. Genomic DNA was extracted from whole blood and hair samples using protocols elaborated in-house. The concentration and purity of isolated DNA were measured by the Nanodrop spectrophotometer (Model ND2000, Thermo Fisher Scientific, Wilmington, DE, USA) prior to genotyping. After, DNA samples were genotyped using Illumina Bovine HD Genotyping BeadChip and Illumina GGP Bovine 100K BeadChip with the help of the commercial genotyping service provider (Neogen, Geneseek, NL, USA). The Bovine HD and 100K chips possess 777,962 and 95,256 SNPs, respectively, uniformly spanning over the entire bovine genome. A total of 81,975 common markers between both SNP panels were used for the following analysis. 

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