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Dominik, Sonja
- PublicationAccuracy of estimated genomic breeding values for wool and meat traits in a multi-breed sheep population(CSIRO Publishing, 2010)
; ; Hayes, B JEstimated breeding values for the selection of more profitable sheep for the sheep meat and wool industries are currently based on pedigree and phenotypic records. With the advent of a medium-density DNA marker array, which genotypes ~50 000 ovine single nucleotide polymorphisms, a third source of information has become available. The aim of this paper was to determine whether this genomic information can be used to predict estimated breeding values for wool and meat traits. The effects of all single nucleotide polymorphism markers in a multi-breed sheep reference population of 7180 individuals with phenotypic records were estimated to derive prediction equations for genomic estimated breeding values (GEBV) for greasy fleece weight, fibre diameter, staple strength, breech wrinkle score, weight at ultrasound scanning, scanned eye muscle depth and scanned fat depth. Five hundred and forty industry sires with very accurate Australian sheep breeding values were used as a validation population and the accuracies of GEBV were assessed according to correlations between GEBV and Australian sheep breeding values. The accuracies of GEBV ranged from 0.15 to 0.79 for wool traits in Merino sheep and from –0.07 to 0.57 for meat traits in all breeds studied. Merino industry sires tended to have more accurate GEBV than terminal and maternal breeds because the reference population consisted mainly of Merino haplotypes. The lower accuracy for terminal and maternal breeds suggests that the density of genetic markers used was not high enough for accurate across-breed prediction of marker effects. Our results indicate that an increase in the size of the reference population will increase the accuracy of GEBV. - PublicationImpact of young ewe fertility rate on risk and genetic gain in sheep-breeding programs using genomic selectionGenomic selection could be useful in sheep-breeding programs, especially if rams and ewes are first mated at an earlier age than is the current industry practice. However, young-ewe (1 year old) fertility rates are known to be lower and more variable than those of mature ewes. The aim of the present study was to evaluate how young-ewe fertility rate affects risk and expected genetic gain in Australian sheep-breeding programs that use genomic information and select ewes and rams at different ages. The study used stochastic simulation to model different flock age structures and young-ewe fertility levels with and without genomic information for Merino and maternal sheep-breeding programs. The results from 10 years of selection were used to compare breeding programs on the basis of the mean and variation in genetic gain. Ram and ewe age, availability of genomic information on males and young-ewe fertility level all significantly (P < 0.05) affected expected genetic gain. Higher young-ewe fertility rates significantly increased expected genetic gain. Low fertility rate of young ewes (10%) resulted in net genetic gain similar to not selecting ewes until they were 19 months old and did not increase breeding-program risk, as the likelihood of genetic gain being lower than the range of possible solutions from a breeding program with late selection of both sexes was zero. Genomic information was of significantly (P < 0.05) more value for 1-year-old rams than for 2-year-old rams. Unless genomic information was available, early mating of rams offered no greater gain in Merino breeding programs and increased breeding-program risk. It is concluded that genomic information decreases the risk associated with selecting replacements at 7 months of age. Genetic progress is unlikely to be adversely affected if fertility levels above 10% can be achieved. Whether the joining of young ewes is a viable management decision for a breeder will depend on the fertility level that can be achieved in their young ewes and on other costs associated with the early mating of ewes.
- PublicationNeglecting genotype x environment interaction results in biased predictions from selection index calculationsThis study investigated effects of neglecting genotype × environment (G × E) interaction on the efficiency of index selection, genetic gain and dollar response. Two indices were established. Index P (P for practical) represents an index that would be used in practice. It assumed that no effects of G × E interactions were present. Index T (T for true) accounted for a prevailing level of G × E interactions in a real data set. Since the true underlying genetic parameters of the data set were unknown, different instances of possible G × E interaction levels for Index T were generated through a sampling procedure. The average difference between the genetic correlations used in Index P and T reduced the efficiency of Index P by between 1% and 24.8%. The total dollar response per year was on average 33% overpredicted, but this could be as high as 114%. Larger differences between the correlations resulted in higher variation in efficiency. Larger G × E interactions resulted in larger overpredictions in total dollar response. The effects of not accommodating or assuming the wrong extent of G × E interaction can be considerable in index calculations.
- PublicationDesign and phenotyping procedures for recording wool, skin, parasite resistance, growth, carcass yield and quality traits of the SheepGENOMICS mapping flock(CSIRO Publishing, 2012)
; ; ; - PublicationGenetic parameters for methane emissions in Australian sheep measured in portable accumulation chambers in grazing and controlled environments(CSIRO Publishing, 2022-03-10)
; ; ; ; ; ; Context. Genotype by environment interaction or sire re-ranking between measurements of methane emission in different environments or from using different measurement protocols can affect the efficiency of selection strategies to abate methane emission. Aim. This study tested the hypothesis that measurements of methane emission from grazing sheep under field conditions, where the feed intake is unknown, are genetically correlated to measurements in a controlled environment where feed intake is known. Methods. Data on emission of methane and carbon dioxide and uptake of oxygen were measured using portable accumulation chambers from 499 animals in a controlled environment in New South Wales and 1382 animals in a grazing environment in Western Australia were analysed. Genetic linkage between both environments was provided by 140 sires with progeny in both environments. Multi-variate animal models were used to estimate genetic parameters for the three gas traits corrected for liveweight. Genetic groups were fitted in the models to account for breed differences. Genetic correlations between the field and controlled environments for the three traits were estimated using bivariate models. Key results. Animals in the controlled environment had higher methane emission compared to the animals in the field environment (37.0 ± s.d 9.3 and 35.3 ± s.d 9.4 for two protocols vs 12.9 ± s.d 5.1 and 14.6 ± s.d 4.8 mL/min for lambs and ewes (±s.d); P < 0.05) but carbon dioxide emission and oxygen uptake did not significantly differ. The heritability estimates for methane emission, carbon dioxide emission and oxygen uptake were 0.15, 0.06 and 0.11 for the controlled environment and 0.17, 0.27 and 0.35 for the field environment. The repeatability for the traits in the controlled environment ranged from 0.51 to 0.59 and from 0.24 to 0.38 in the field environment. Genetic correlations were high (0.85–0.99) but with high standard errors. Conclusion. Methane emission phenotypes measured using portable accumulation chambers in grazing sheep can be used in genetic evaluation to estimate breeding values for genetic improvement of emission related traits. The combined measurement protocol-environment did not lead to re-ranking of sires. Implication. These results suggest that both phenotypes could be used in selection for reduced methane emission in grazing sheep. However, this needs to be consolidated using a larger number of animals and sires with larger progeny groups in different environments.
- PublicationBreeding Focus 2018 - Reducing Heat Stress(University of New England, Animal Genetics and Breeding Unit, 2018)
; “Breeding Focus 2018 - Reducing Heat Stress” is the third workshop in the series. The Breeding Focus series was developed to provide an opportunity for exchange between industry and research across a number of agricultural industry sectors. With this goal in mind, workshops have included presentations across the livestock and aquaculture industries to take participants outside their area of expertise and encouraged them to think outside the box. This year we increased the scope even further by also inviting presentations from the cropping and horticulture industries. Since the topic of heat stress has recently gained increased attention, we will discuss a wide range of aspects associated with heat stress, such as the physiology of heat stress and phenotypic indicators, genetic approaches and industry impacts. - PublicationThe effect of including immune competence in Merino sheep breeding programs(Association for the Advancement of Animal Breeding and Genetics (AAABG), 2017-07)
; The effect of including general immune competence (IC) as a novel trait in a fibre production (FP) and a dual purpose selection (DP) index was investigated. Two levels of economic values were assumed for IC and the sensitivity of index responses to these were tested. The results showed that the addition of IC to a selection index requires careful consideration in order to achieve the envisaged improvements in health and welfare outcomes expected while addressing primary production objectives.
- PublicationGenetic and phenotypic parameters for reproduction, production and bodyweight traits in Australian fine-wool Merino sheepThe present study estimated phenotypic and genetic relationships between wool production, reproduction and bodyweight traits in Australian fine-wool Merino sheep. The data for the study originated from the CSIRO Fine Wool Project, Armidale, Australia. Data on wool characteristics, measured at ~10 and 22 months of age, bodyweight and several reproduction traits across consecutive lambing opportunities were analysed. The genetic correlations were moderately negative between fibre diameter measured as yearling and adult, and lamb survival (rg = -0.34 ± 0.15 and rg = -0.28 ± 0.14 respectively) and total number of lambs weaned (rg = -0.32 ± 0.21 and rg = -0.40 ± 0.21 respectively). The genetic correlations of yearling and adult greasy and clean fleece weights with number of lambs weaned and fecundity showed moderately to highly negative relationships and a moderately negative correlation with the number of fetuses at pregnancy scanning. Phenotypic correlations between reproduction and wool production traits were estimated to be zero, with the exception of bodyweight showing low to moderate positive phenotypic correlations with total number of lambs born and weaned. Genetic variances were generally low for the reproduction traits and resulted in low heritability estimates (from h2 = 0.03 ± 0.01 to h2 = 0.12 ± 0.13), with the exception of total number of lambs born (h2 = 0.25 ± 0.03). The study indicated that parameter estimation and trait definition of lifetime reproduction records require careful consideration and more work in this area is required.
- PublicationGenetic solutions(Elsevier Ltd, 2017)
; - PublicationBreeding Focus 2016 - Improving WelfareThe inaugural 'Breeding Focus' workshop was held in 2014 to outline and discuss avenues for genetic improvement of resilience. The Breeding Focus workshop was developed to provide a forum for exchange between industry and research across livestock and aquaculture industries. The objective of Breeding Focus is to cross-foster ideas and to encourage discussion between representatives from different industries because the challenges faced by individual breeding organisations are similar across species. This book accompanies the Breeding Focus 2016 workshop. The topic of this workshop is 'Breeding Focus 2016 - Improving welfare'.
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