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Exome analysis and functional classification of identified variants in racing Quarter Horses.

Rogério Abdallah CuriG L PereiraM V N AlvarezW A BaldassiniO R Machado NetoL A L Chardulo
Published in: Animal genetics (2020)
The main objectives of this study were to identify and functionally classify SNPs and indels by exome sequencing of animals of the racing line of Quarter Horses. Based on the individual genomic estimated breeding values (GEBVs) for maximum speed index (SImax) obtained for 349 animals, two groups of 20 extreme animals were formed. Of these individuals, 20 animals with high GEBVs for SImax and 19 with low GEBVs for SImax had their exons and 5' and 3' UTRs sequenced. Considering SNPs and indels, 105 182 variants were identified in the expressed regions of the Quarter Horse genome. Of these, 72 166 variants were already known and 33 016 are new variants and were deposited in a database. The analysis of the set of gene variants significantly related (Padjusted  < 0.05) to extreme animals in conjunction with the predicted impact of the changes and the physiological role of protein product pointed to two candidate genes potentially related to racing performance: SLC3A1 on ECA15 and CCN6 on ECA10.
Keyphrases
  • copy number
  • genome wide
  • dna methylation
  • climate change
  • deep learning
  • machine learning
  • single cell
  • amino acid
  • genome wide identification