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Pedigree reconstruction and population structure using SNP markers in Gir cattle.

Arielly Oliveira GarciaPamela Itajara OttoLuiz Afonso Glatzl JuniorRenata de Fátima Bretanha RochaMateus Guimarães Dos SantosDaniele Alves de OliveiraMarcos Vinicius Gualberto Barbosa da SilvaJoão Cláudio do Carmo PanettoMarco Antônio MachadoRui da Silva VernequeSimone Eliza Facioni Guimarães
Published in: Journal of applied genetics (2023)
Our objective was to establish a SNPs panel for pedigree reconstruction using microarrays of different densities and evaluate the genomic relationship coefficient of the inferred pedigree, in addition to analyzing the population structure based on genomic analyses in Gir cattle. For parentage analysis and genomic relationship, 16,205 genotyped Gir animals (14,458 females and 1747 males) and 1810 common markers to the four SNP microarrays were used. For population structure analyses, including linkage disequilibrium, effective population size, and runs of homozygosity (ROH), genotypes from 21,656 animals were imputed. Likelihood ratio (LR) approach was used to reconstruct the pedigree, deepening the pedigree and showing it is well established in terms of recent information. Coefficients for each relationship category of the inferred pedigree were adequate. Linkage disequilibrium showed rapid decay. We detected a decrease in the effective population size over the last 50 generations, with the average generation interval around 9.08 years. Higher ROH-based inbreeding coefficient in a class of short ROH segments, with moderate to high values, was also detected, suggesting bottlenecks in the Gir genome. Breeding strategies to minimize inbreeding and avoid massive use of few proven sires with high genetic value are suggested to maintain genetic variability in future generations. In addition, we recommend reducing the generation interval to maximize genetic progress and increase effective population size.
Keyphrases
  • genome wide
  • copy number
  • dna methylation
  • high density
  • healthcare
  • gene expression
  • magnetic resonance imaging
  • high intensity
  • health information
  • hiv infected
  • genetic diversity