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Genetic evaluation using multi-trait and random regression models in Simmental beef cattle.

R R Mota1, L F A Marques, P S Lopes

  • 1Departamento de Zootecnia, Universidade Federal de Viçosa, Viçosa, MG, Brasil. rreismota@hotmail.com

Genetics and Molecular Research : GMR
|August 28, 2013
PubMed
Summary
This summary is machine-generated.

Random regression models (RRM) offer a recommended approach for genetic evaluation in Simmental beef cattle, accurately modeling growth trajectories without pre-adjusting weights to standard ages.

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Area of Science:

  • Animal Genetics
  • Quantitative Genetics
  • Livestock Breeding

Background:

  • Accurate genetic parameter estimation is crucial for improving Simmental beef cattle productivity.
  • Traditional multi-trait models (MTM) may require pre-adjustment of weights, potentially introducing bias.
  • Growth trajectory analysis is essential for optimizing breeding strategies in beef cattle.

Purpose of the Study:

  • To compare multi-trait models (MTM) and random regression models (RRM) for estimating genetic parameters in Simmental beef cattle growth.
  • To determine the optimal RRM order for modeling variance structures in growth trajectories.
  • To provide recommendations for genetic evaluation of Simmental beef cattle in Brazil.

Main Methods:

  • Utilized 29,510 records from 10,659 Simmental beef cattle.
  • Estimated (co)variance components and genetic parameters using restricted maximum likelihood (REML).
  • Compared MTM and RRM, with RRM of third order selected for direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects.

Main Results:

  • A third-order RRM adequately modeled variance structures for Simmental beef cattle growth.
  • (Co)variance components were similar between MTM and RRM.
  • Direct heritabilities estimated by RRM (0.16-0.45) were slightly higher than MTM (0.04-0.42).
  • High positive additive direct correlations were observed between traits at similar ages.

Conclusions:

  • Random regression models (RRM) are suitable for genetic evaluation of Simmental beef cattle, eliminating the need for weight pre-adjustment.
  • RRM provides reliable estimates of genetic parameters for growth trajectories.
  • The study recommends RRM for optimizing genetic selection in Brazilian Simmental beef cattle populations.