Evaluating the genetic components of growth in ostriches with multi-trait and random regression models

1. The heritability (h²) of liveweight (LW) in ostriches can be highly variable, depending on age at recording. The objective of this study was to consider random regression (RR) as an alternative to the multi-trait (MT) structure for the analysis of repeated measures of LW.2. The data included 74 683 LW phenotypes recorded from 10 052 birds aged between 20 and 410 days (d) of age. Statistical analysis included single trait (ST), MT and RR analysis in a linear mixed model framework using the ASREML V4.2 software.3. For ST and MT, six traits were defined to represent LW at 28, 77, 150, 230, 300 and 365 d of age. Random variance components included direct genetic and maternal permanent environment (PE) effects. A MT analysis including all six traits converged.4. For RR, the data was transformed (LW + 10)^-0.5 due to difficulty in dealing with large scale effects. The final RR model fitted direct genetic and animal PE components as third degree Legendre polynomials and heterogeneous residuals.5. The h² estimates was in agreement across analysis, ranging from moderate (0.16-0.20) for W28 to high (0.41-0.51) for W230 to W365. Importantly, the genetic relationship between LW recorded as a chick and juvenile was only moderate (~0.35 to 0.55). The correlations between RR and MT EBVs for the six traits were 0.85, 0.54, 0.65, 0.75, 0.83 and 0.91, showing a considerable level of re-ranking.6. This study reaffirmed age dependent genetic variation when determining LW in ostriches. The RR structure was useful for overcoming the dimension problem of MT analysis, but was susceptible to scale effects present in the data, despite transformation. It remains unknown whether the need for cubic terms reflected scale or animal effects.