Skin thickness as a potential indirect trait for genetic improvement of lamb survival : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Animal Science at Massey University, Palmerston North, New Zealand
Lamb survival, as a trait of great economic importance with low heritability, might show more response to indirect selection for traits of higher heritability that are genetically correlated with lamb survival, as a trait of high economic importance. The main objective of this thesis was to explore if ultrasonographically measured skin thickness (ST) at about nine months of age could be considered as an alternative to direct selection for lamb survival from birth to weaning (SBW). For this purpose, in the first step, the reliability of ultrasonography as an accurate and noninvasive method for measurement of ST was validated using plicometry and histometry. In the second experiment, the heritability of ultrasonographically measured ST at an age of about 9 months was estimated to be 0.21 ± 0.03 and 0.20 ± 0.03, respectively from analyses with and without adjustment for live weight at scanning (LWS), implying that the trait would respond to genetic selection. Estimates of genetic correlation of ST with SBW from the analyses with LWS considered as a covariate for ST ranged from 0.16 to 0.35 depending on the minimum number of progeny per sire for each trait, while the corresponding estimates from the analyses with LWS excluded ranged from 0.08 to 0.27. When correction was made for LWS, ST showed genetic correlations of 0.21 ± 0.07, -0.13 ± 0.09, -0.32 ± 0.12, -0.23 ± 0.09, -0.10 ± 0.10, 0.02 ± 0.11, and 0.20 ± 0.11 with fat depth (FD), eye muscle depth (EMD), weights at weaning (WWT), 8 months (LW8), scanning (LWS), and 12 months (LW12), and fleece weight at 12 months (FW12), respectively. The corresponding estimates when no adjustment was made for LWS, were respectively 0.24 ± 0.08, -0.08 ± 0.10, -0.01 ± 0.12, 0.09 ± 0.09, 0.19 ± 0.09, 0.30 ± 0.10, and 0.20 ± 0.11. In the third experiment, the role of skin thickness in thermoregulation through its effect on surface heat loss and a few other indices of cold resistance was explored in two groups of new-born lambs with the thickest skin (thick-skinned category) and the thinnest skin (thin-skinned category) exposed to cold-stress. As a result of lower skin surface temperature (as an indicator of heat loss) in thick-skinned lambs compared to thin-skinned lambs, the first group had higher rectal temperature and were more likely to maintain body temperature during cold stress, even though they produced significantly less heat (W Kg-1). This means there is less need to consume body reserves as a source of energy and consequently better conservation of body reserves in the thick-skinned lambs. In the fourth experiment, skin thickness measured at six to eight months of age was revealed to be a moderately reliable indicator of skin thickness at birth. This is of high importance from both practical and economic points of views. Measuring skin thickness at six to eight months of age is much easier than at birth for sheep farmers/breeders. Furthermore, ultrasound measurement of skin thickness at these ages facilitates simultaneous recording of other traits of importance like fat depth and eye muscle depth, which are normally taken at these ages. In the final study, the effects of genetic variation in the uncoupling protein 1 (UCP1), prolactin (PRL), and prolactin receptor (PRLR) genes on the indices of cold resistance were tested in new-born lambs exposed to cold stress. Although significant effects on some of the indices were observed at/during some time-points/periods of the cold stress, they seem to be mostly due to biases resulting from low number of lambs rather than being real. Considering all the findings, it could be generally concluded that ultrasonographically measured skin thickness at about nine months of age could be considered as a supplement to direct selection for lamb survival in genetic improvement programs. Nevertheless, the large standard errors of the correlations of ST with SBW as well as the unfavorable correlation of ST with other traits should also be considered.