Derivation of a new lamb survival trait for the New Zealand sheep industry.

Previous research identified that a review of the current industry New Zealand lamb survival trait was necessary as its recording accuracy was reliant on farmers notifying their Sheep Improvement Limited bureau of lamb deaths. This paper reports the decision rules and genetic parameters for a new lamb survival trait for the New Zealand sheep industry. These rules define the new lamb survival trait (NEWSUR) using lamb birth fate (BFATE) codes and the presence/absence of lamb weight measurements. Six univariate animal models were tested and used to estimate variance or covariance components and the resulting direct and maternal heritabilities for NEWSUR. The models differed in the way they adjust for the effect of day of birth, the exclusion or inclusion of a litter (dam/year of birth) random effect, and the application or not of a logit transformation of the phenotypes. For both the linear and logistic methods, models including the random effect of litter provided the best fit for NEWSUR according to log-likelihood values. Log-likelihoods for the linear and logistic models cannot be compared; therefore, a cross-validation method was used to assess whether the logit transformation was appropriate by analyzing the predictive ability of the models. The mean square errors were slightly lower for the linear compared with the logistic model, and therefore, the linear model was recommended for industry use. The heritability attributed to direct effects ranged from 2 to 5.5%. A direct heritability of 5.5% resulted from a linear model without litter effect and omitting the effect of day of birth on survival, whereas a direct heritability of 2% resulted from the logistic model fitting a random litter effect. The heritability attributed to maternal genetic effects ranged from 1.9 to 7.7%. A maternal genetic heritability of 7.7% resulted from the logistic model omitting the litter effect, whereas a maternal genetic heritability of 1.9% resulted from the linear model fitting a random litter effect. The addition of the litter random effect substantially decreased the maternal heritabilities in all cases and was recommended for industry use to avoid overestimation of the maternal genetic variance. Sheep Improvement Limited has implemented NEWSUR and the associated genetic evaluation model based on information described in this paper. Industry-wide implementation will enable sheep breeders to produce more accurate genetic evaluations to their commercial clients.

Genomic prediction of breeding values in the New Zealand sheep industry using a 50K SNP chip.

The aim of genomic prediction is to predict breeding value from genomic data. We describe the development of genomic prediction equations and accuracies for molecular breeding values (MBV) for industry use, focusing on the methodology used to deal with predictions for the New Zealand sheep population structure. This is made up of a mixture of pure and crossbred animals, but principally Romney based. In particular, we used pedigree-based EBV for 8 traits (weaning weight as a direct effect, weaning weight as a maternal effect, live weight at 8 mo, live weight at 12 mo, greasy fleece weight at 12 mo, lamb fleece weight, adult fleece weight, and number of lambs born) and Illumina OvineSNP50 BeadChip genotypes from 13,420 animals to investigate BLUP with different genomic relationship matrices (GRM) based on SNP markers and to investigate varying sets of older animals (training sets) to predict the MBV of younger animals (validation sets). The GRM tested included modifications to account for allele frequency differences between breeds, rescaling so that the mean GRM is equal to the mean of the traditional pedigree numerator relationship matrix A: , and combining of the GRM with A: using a convex combination with a weight estimated by maximizing a conditional restricted likelihood. We found that these modifications were beneficial and recommend using a breed-adjusted GRM combined with A: . Training data sets with Romney, Coopworth, and Perendale animals all together usually predicted better than using just a pure breed training data set for all traits. But predictions for the breed Perendale were more accurate with a Perendale training set for 3 of the 8 traits. We concluded that using a mixed-breed training set for all combinations of traits and breeds was best but advise that increasing the number of Perendale animals genotyped should be a priority to increase the MBV accuracies obtained for that breed.

Towards genomic selection for facial eczema disease tolerance in the New Zealand sheep industry.

Pithomycotoxicosis, more commonly known as facial eczema (FE), is a liver disease that occurs predominantly in New Zealand because of its toxigenic Pithomyces chartarum strains. The first reported case was in sheep in 1887. Since the 1930s, a number of studies have been conducted in an attempt to mitigate the problems FE has on the sheep and dairy industries. The research in these studies included work on fungicide and biological control of the saprophytic fungus, use of different pasture plants to inhibit fungal growth, stock management with respect to pasture fungal spore counts and the use of zinc prophylaxis on animals. The finding that there was a genetic basis in FE sensitivity in sheep prompted research for a genetic approach to mitigation in the form of a diagnostic DNA test for susceptibility to the disease. Recently, we have used the Illumina OvineSNP50 BeadChip to develop a genome-enabled prediction approach to screen for FE-tolerant sheep. Our current best genomic prediction for FE is for the Romney breed and has an accuracy of 0.38. This prediction accuracy is not as high as the individual accuracy gained by an artificial challenge test (0.64). However, it has the advantage of being a non-invasive test and can be provided as part of genomic testing for other traits at minimal cost.

Genetic parameters for lamb birth weight, survival and death risk traits.

This paper reports genetic parameters for lamb survival and mortality traits on sheep farms in New Zealand. Lamb survival and mortality records were obtained from 38 flocks (103,357 lambs) from 5 yr of lambing data (2007 to 2011) and include many breeds and their crosses (predominantly Romney, Perendale, Coopworth, and Texel). A number of models were tested, all including environmental weather effects and investigating the random environmental effect of dam and litter (dam/year) as well as logit transformation for binary traits. Total heritability (direct + maternal) estimates were low for lamb viability at birth (0.01), lamb death risk to dystocia (0.01), and lamb death risk to starvation exposure (0.01) from birth to 3 d of age in an analysis accounting for direct and maternal genetic effects and the maternal environmental effects. Lamb survival heritabilities reported are very low (total heritabilities range from 0.02 to 0.06). The total heritabilities for the lamb death risk traits are lower than reported estimates of survival to 3 d of age or to weaning suggesting selection for the postmortem traits are not warranted at this time within these flocks. The total heritability for lamb birth weight was moderate (0.38) and the genetic correlations with the lamb death risk traits suggested that directional selection on lamb birth weight would have an effect on survival, although it is likely to have a nonlinear effect and therefore an optimum birth weight at which survival is maximized. This study has also shown that the total heritabilities may be overestimated when not accounting for maternal genetic and environment effects and in particular not accounting for the random environmental effect of litter (dam/year).