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Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle.

Giovanna Faria MoraesLuíza Rodrigues Alves AbreuFabio Luiz Buranelo ToralIsabel Cristina FerreiraHenrique Torres VenturaJosé Aurélio Garcia BergmannIdalmo Garcia Pereira
Published in: Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie (2019)
The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two-trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.
Keyphrases
  • genome wide
  • dna methylation
  • copy number
  • body weight
  • adipose tissue
  • body mass index
  • gene expression
  • fatty acid
  • machine learning
  • electronic health record
  • deep learning