Since males and females have different number of X chromosome, different mechanisms have evolved to equalize dosage of gene products from the X chromosome between XX females and XY males. The aim of this study was to study X chromosome dosage compensation for growth rate (GR), Kleiber ratio (KR), efficiency of growth (EF) and relative growth rate (RGR) in Zandi sheep. A two steps procedure was adopted to analysis data. In the first step, each trait was analyzed with a series of 6 animal models including different combinations of direct and maternal effects. Using Akaike’s Information Criterion (AIC) the best model (Model I) was selected for each trait. In the second step, five additional models were fitted by adding X chromosome effects to the Model I, considering 5 strategies for modeling X chromosome dosage compensation: (1) no global dosage compensation (ngdc), (2) random inactivation in the homogametic sex (hori), (3) doubling of the single shared sex chromosome in the heterogametic sex (hedo), (4) halving expression of both sex chromosomes in the homogametic sex (hoha) or (5) inactivation of the paternal sex chromosome in the homogametic sex (hopi). Predictive ability of models was measured using the mean squared error of prediction (MSE) and Pearson’s correlation coefficient between the real and predicted values of records \((\text{r}(y,\widehat{y})).\) Correlations between traits due to autosomal- and X-linked genetic effects were estimated by bi-variate analyses. For GR and KR, models including X-linked effects lead to a much better fit of data, expressed by the strong decrease in the AIC criterion. Models including X-linked effects had also better predictive ability as they provided smaller MSE and higher \(\text{r}(y, \widehat{y}).\) For GR and KR, although all strategies for modeling X chromosome dosage compensation improved general properties of the model, the model “ngdc” fitted the data significantly better than other models. Including X-linked genetic effects in the model led to 10% (GR, KR) decrease in the autosomal additive variance, and 7% (KR) to 19% (GR) decrease in the residual variance. Estimates of autosomal heritability ( \({\mathbf{h}}_{\mathbf{a}}^{2}\) ), were 0.15 ± 0.03, 0.13 ± 0.03, 0.09 ± 0.03 and 0.13 ± 0.03 for GR, KR, EF and RGR, respectively. X-linked heritability ( \({\mathbf{h}}_{\mathbf{s}}^{2}\) ) was 0.08 ± 0.03 for GR and 0.04 ± 0.03 for KR, respectively. Maternal heritability ( \({\mathbf{h}}_{\mathbf{m}}^{2}\) ) were 0.02 ± 0.01, 0.01 ± 0.01, 0.03 ± 0.02 and 0.03 ± 0.02 for GR, KR, EF and RGR, respectively. For GR and KR, the Spearman’s correlation between breeding values obtained from the best model and model I deviated from unity, indicating re-ranking of top animals across models. The X-linked additive genetic correlation and autosomal additive genetic correlation were similar in terms of sign and magnitude in a way that they were all positive and high. As considering X-linked genetic effects resulted to an improvement in the general properties of the model and possibility of re-ranking of top animals, including these effects in the model, considering dosage compensation on the X chromosome was recommended.
