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Context: Coping with high levels of cold stress should be beneficial to survival of lambs, given the high mortality rate associated with severe winter storms. The Elsenburg Merino selection experiment involved divergent selection for reproduction. Phenotypic results comparing the positively selected H-Lines and negatively selected L-Lines suggested that cold-stress adaption could have contributed to the favourable genetic trends for survival of H-Line lambs. However, observing the genetic merit of better adapted animals depends on the presence of cold stress at the time of recording. A genotype by environment component (G × E) could, thus, be important when assessing survival/mortality phenotypes. Aim: This study proposed the genetic analysis of this possible G × E component and compared the H- and L-Lines in this regard. Methods: The sire model allowed the use of progeny phenotypes for neonatal mortality recorded during different levels of cold stress, and the possible G × E could be investigated through the reaction-norm approach. Genetic parameters were evaluated as random regression components by implementing a Gibbs sampling approach. A data set of 5723 individual lamb records was analysed as the progeny of 213 sires. Results: A modelled G × E component played an important role in mortality outcomes, with the mean estimate (and 95% confidence interval) for the slope ( σ s b 2 = 0.113 [ 0.0019 – 0.28 ] AN22464_IE1.gif) only marginally smaller than the corresponding estimate for the intercept ( σ s a 2 = 0.124 [ 0.003 – 0.26 ] AN22464_IE2.gif). The reaction-norm model showed a higher heritability (h 2 ± posterior standard deviation) for mortality at 3 days of age during high cold-stress (0.22 ± 0.16 at ~1100 KJm−2h−1) than during mild (0.13 ± 0.10 at ~960 KJm−2h−1) conditions, suggesting a greater ability to discriminate between sires at increasing stress levels. Conclusions: Failure to account for this G × E component putatively contributes to the low h 2 commonly reported for survival traits. The higher h 2 at increased levels of cold stress could have played an important part in the higher survival of the H-Line progeny, who were better at coping with cold, wet and windy conditions. Implications: Larger studies representing a wider environmental trajectory are recommended. This should be very feasible since cold stress can be derived from commonly available weather-station data. Animals better adapted to cope with cold stress conditions should have higher survival rates, but the merit of these animals would not be visible under mild conditions. Accounting for the level of cold stress in the earliest days after birth allows for new ways to evaluate the genetic merit of survival or mortality traits. Cold-stress adaption is likely to have been an important part of the very favourable survival rate of the Elsenburg Merino H-Line. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: With the new opportunities from DNA technology, multitier breeding schemes have the potential to become more effective and more integrated. Integrated breeding schemes can also be better adapted to account for potential genotype by environment interactions (G × E) between tiers. In this case, phenotypic and genotype information from lower tiers becomes more valuable as it involves measurement of traits that directly represent the breeding objective. The objective of this study was to compare scenarios that represented different selection strategies and their economic effectiveness in fine‐wool commercial sheep operations that exploit multitier breeding structures. Genomic selection (GS) applied in the multiplier and the commercial tier presented the largest additional revenue among all scenarios, as it resulted in the largest amount of genetic progress. The largest benefits from GS were outweighed by the genotyping costs, which made DNA parentage the most feasible strategy for the multiplier tier, resulting in the highest cumulative net present value (CNPV). The benefits of phenotypes and genotype information from the commercial environment were larger in the presence of G × E between the nucleus and the commercial tier. The CNPV was larger with a 50% reduction in genotyping costs, which increased the returns of GS scenarios by 2.7‐fold on average. Higher selection intensity when selecting multiplier rams also resulted in larger benefits. In this case, returns for the breeding scheme were 3.5‐fold higher when 33% of multiplier males were selected based on commercial information, compared to scenarios selecting 50% of the available multiplier rams. The benefits of collecting commercial phenotypes and genotypes were long term, which means that return on investment often took more than 10 years to be achieved, and were largely dependent on two‐stage selection to reduce cost while maintaining selection efficiency and on the cost of a genotype test. [ABSTRACT FROM AUTHOR]

Breeding programmes for livestock require economic weights for traits that reflect the most profitable animal in a given production system, which affect the response in each trait after selection. The profitability of sheep production systems is affected by changes in pasture growth as well as grain, meat and wool prices between seasons and across years. Annual pasture growth varies between regions within Australia’s Mediterranean climate zone from low growth with long periods of drought to high growth with shorter periods of drought. Therefore, the objective of this study was to assess whether breeding objectives need to be adapted for regions, depending on how reliable the pasture growth is across years. We modelled farms with Merino sheep bred for wool and meat in 10 regions in Western Australia. Across these 10 regions, mean annual pasture growth decreased, and the CV of annual pasture growth increased as pasture growth for regions became less reliable. We calculated economic values for nine traits, optimising management across 11 years, including variation for pasture growth and wool, meat and grain prices between and within years from 2002 to 2012. These economic values were used to calculate responses to selection for each trait for the 10 regions. We identified two potential breeding objectives, one for regions with low or high reliability and the other for regions with medium reliability of pasture growth. Breeding objectives for high or low pasture growth reliability had more emphasis on live weight traits and number of lambs weaned. Breeding objectives for medium reliability of pasture growth had more emphasis on decreasing fibre diameter. Relative economic weights for fleece weight did not change across the regions. Regions with low or high pasture reliability had similar breeding objectives and response to selection, because the relationship between the economic values and CV of pasture growth were not linear for live weight traits and the number of lambs weaned. This non-linearity was caused by differences in distribution of pasture growth between regions, particularly during summer and autumn, when ewes were pregnant, with increases in energy requirements affecting the value of lambs weaned. In addition, increasing live weight increased the intake capacity of sheep, which meant that more poor quality pasture could be consumed during summer and autumn, which had more value in regions with low and high pasture reliability. We concluded that breeding values for sheep production systems should be customised depending on the reliability of pasture growth between years. [ABSTRACT FROM PUBLISHER]

Merino sheep in Australia experience periods of variable feed supply. Merino sheep can be bred to be more resilient to this variation by losing less BW when grazing poor quality pasture and gaining more BW when grazing good quality pasture. Therefore, selection on BW change might be economically attractive but correlations with other traits in the breeding objective need to be known. The genetic correlations (r g ) between BW, BW change, and reproduction were estimated using records from approximately 7,350 fully pedigreed Merino ewes managed at Katanning in Western Australia. Number of lambs and total weight of lambs born and weaned were measured on approximately 5,300 2-yr-old ewes, approximately 4,900 3-yr-old ewes, and approximately 3,600 4-yr-old ewes. On a proportion of these ewes BW change was measured: approximately 1,950 2-yr-old ewes, approximately 1,500 3-yr-old ewes, and approximately 1,100 4-yr-old ewes. The BW measurements were for 3 periods. The first period was during mating period over 42 d on poor pasture. The second period was during pregnancy over 90 d for ewes that got pregnant on poor and medium quality pasture. The third period was during lactation over 130 d for ewes that weaned a lamb on good quality pasture. Genetic correlations between weight change and reproduction were estimated within age classes. Genetic correlations were tested to be significantly greater magnitude than 0 using likelihood ratio tests. Nearly all BW had significant positive genetic correlations with all reproduction traits. In 2-yr-old ewes, BW change during the mating period had a positive genetic correlation with number of lambs weaned (rg = 0.58); BW change during pregnancy had a positive genetic correlation with total weight of lambs born (rg = 0.33) and a negative genetic correlation with number of lambs weaned (rg = -0.49). All other genetic correlations were not significantly greater magnitude than 0 but estimates of genetic correlations for 3-yr-old ewes were generally consistent with these findings. The direction of the genetic correlations mostly coincided with the energy requirements of the ewes and the stage of maturity of the ewes. In conclusion, optimized selection strategies on BW changes to increase resilience will depend on the genetic correlations with reproduction and are dependent on age. [ABSTRACT FROM AUTHOR]

Sheep in Australia experience periods with different feed supply causing them to gain and lose BW during the year. It is more efficient if ewes lose less BW during periods of poor nutrition and gain more BW during periods of good nutrition. We investigated whether BW loss during periods of poor nutrition and BW gain during periods of good nutrition are genetically different traits. We used BW measurements from 2,336 adult Merino ewes managed over 5 yr in a Mediterranean climate in Katanning, Australia. Body weight loss is the difference between 2 BW measured 42 d apart during mating, a period of poor nutrition. Body weight gain is the difference between 2 BW measured 131 d apart during a period of good nutrition between prelambing and weaning. We estimated variance components of BW change using 3 methods: 1) as a trait calculated by subtracting the first BW from the second, 2) multivariate analysis of BW traits, and 3) random regression analysis of BW. The h2 and genetic correlations (rg) estimated using the multivariate analysis of BW andthe BW change trait were very similar whereas the random regression analysis estimated lower heritabilities and more extreme negative genetic correlations between BW loss and gain. The multivariate model fitted the data better than random regression based on Akaike and Bayesian information criterion so we considered the results of the multivariate model to be more reliable. The heritability of BW loss (h2 = 0.05-0.16) was smaller than that of BW gain (h2 = 0.14-0.37). Body weight loss and gain can be bred for independently at 2 and 4 yr of age (rg = 0.03 and -0.04) whereas at 3 yr of age ewes that genetically lost more BW gained more BW (rg = -.41). Body weight loss is genetically not the same trait at different ages (rg range 0.13-0.39). Body weight gain at age 3 yr is genetically the same trait at age 4 yr (rg = 0.99) but is different between age 2 yr and the older ages (rg = 0.53 and 0.51). These results suggest that as the ewes reach their mature BW, BW gain at different ages becomes the same trait. This does not apply to BW loss. We conclude that BW change could be included in breeding programs to breed adult Merino ewes that are more tolerant to variation in feed supply. [ABSTRACT FROM AUTHOR]

In genome-wide association studies, failure to remove variation due to population structure results in spurious associations. In contrast, for predic-tions of future phenotypes or estimated breeding values from dense SNP data, exploiting population structure arising from relatedness can actually increase the accu-racy of prediction in some cases, for example, when the selection candidates are offspring of the reference popu-lation where the prediction equation was derived. In populations with large effective population size or with multiple breeds and strains, it has not been demonstrated whether and when accounting for or removing variation due to population structure will affect the accuracy of genomic prediction. Our aim in this study was to deter-mine whether accounting for population structure would increase the accuracy of genomic predictions, both with-in and across breeds. First, we have attempted to decom-pose the accuracy of genomic prediction into contribu-tions from population structure or linkage disequilib-rium (LD) between markers and QTL using a diverse multi-breed sheep (Ovis aries) data set, genotyped for 48,640 SNP. We demonstrate that SNP from a single chromosome can achieve up to 86% of the accuracy for genomic predictions using all SNP. This result suggests that most of the prediction accuracy is due to population structure, because a single chromosome is expected to capture relationships but is unlikely to contain all QTL. We then explored principal component analysis (PCA) as an approach to disentangle the respective contribu-tions of population structure and LD between SNP and QTL to the accuracy of genomic predictions. Results showed that fitting an increasing number of principle components (PC; as covariates) decreased within breed accuracy until a lower plateau was reached. We specu-late that this plateau is a measure of the accuracy due to LD. In conclusion, a large proportion of the accuracy for genomic predictions in our data was due to varia-tion associated with population structure. Surprisingly, accounting for this structure generally decreased the accuracy of across breed genomic predictions. [ABSTRACT FROM AUTHOR]

This paper presents results from a mapping experiment to detect quantitative trait loci (QTL) for resistance to Haemonchus contortus infestation in merino sheep. The primary trait analysed was faecal worm egg count in response to artificial challenge at 6 months of age. In the first stage of the experiment, whole genome linkage analysis was used for broad-scale mapping. The animal resource used was a designed flock comprising 571 individuals from four half-sib families. The average marker spacing was about 20 cM. For the primary trait, 11 QTL (as chromosomal/family combinations) were significant at the 5% chromosome-wide level, with allelic substitution effects of between 0.19 and 0.38 phenotypic standard deviation units. In general, these QTL did not have a significant effect on faecal worm egg count recorded at 13 months of age. In the second stage of the experiment, three promising regions (located on chromosomes 1, 3 and 4) were fine-mapped. This involved typing more closely spaced markers on individuals from the designed flock as well as an additional 495 individuals selected from a related population with a deeper pedigree. Analysis was performed using a linkage disequilibrium–linkage approach, under additive, dominant and multiple QTL models. Of these, the multiple QTL model resulted in the most refined QTL positions, with resolutions of <10 cM achieved for two regions. Because of the moderate size of effect of the QTL, and the apparent age and/or immune status specificity of the QTL, it is suggested that a panel of QTL will be required for significant genetic gains to be achieved within industry via marker-assisted selection. [ABSTRACT FROM AUTHOR]

Data from seven research resource flocks across Australia were combined to provide accurate estimates of genetic correlations among production traits in Merino sheep. The flocks represented contemporary Australian Merino fine, medium and broad wool strains over the past 30 years. Over 110 000 records were available for analysis for each of the major wool traits, and 50 000 records for reproduction and growth traits with over 2700 sires and 25 000 dams. Individual models developed from the single trait analyses were extended to the various combinations of two-trait models to obtain genetic correlations among six wool traits [clean fleece weight (CFW), greasy fleece weight, fibre diameter (FD), yield, coefficient of variation of fibre diameter and standard deviation of fibre diameter], four growth traits [birth weight, weaning weight, yearling weight (YWT), and hogget weight] and four reproduction traits [fertility, litter size, lambs born per ewe joined, lambs weaned per ewe joined (LW/EJ)]. This study has provided for the first time a comprehensive matrix of genetic correlations among these 14 wool, growth and reproduction traits. The large size of the data set has also provided estimates with very low standard errors. A moderate positive genetic correlation was observed between CFW and FD (0.29 ± 0.02). YWT was positively correlated with CFW (0.23 ± 0.04), FD (0.17 ± 0.04) and LWEJ (0.58 ± 0.06), while LW/EJ was negatively correlated with CFW (−0.26 ± 0.05) and positively correlated with FD (0.06 ± 0.04) and LS (0.68 ± 0.04). These genetic correlations, together with the estimates of heritability and other parameters provide the basis for more accurate prediction of outcomes in complex sheep-breeding programmes designed to improve several traits. [ABSTRACT FROM AUTHOR]

A study was conducted to find early predictors of the Booroola gene in several generations of a crossbred sheep population. Merino carriers of the Booroola gene were mated with Texel sheep to improve prolificacy of the latter. Ovulation rate at 8 months of age, litter size at 1 and 2 years of age and FSH and inhibin levels at 3, 4, 5 and 6 weeks of age were determined in about 700 females.Gibbs sampling was applied for inference in a mixed inheritance model. Estimates for the gene effect in heterozygous females were +1·5 corpora lutea and +1·3 lambs at 2 years of age. The gene effect on litter size at 1 year was small. The only significant major gene effect for hormone levels found was for lnINH4 (–0·66).A number of hormone levels and combinations of hormone levels appeared to be useful predictors of carrier status of individual animals. In comparison with a situation where only parents' genotype is known, posterior probabilities for non-carriers were on average increased from 50 to over 95% when FSH levels were used. However, the combined posterior probabilities of carriers and non-carriers increased only up to 67%. So in general, classification with Gibbs sampling resulted in too few animals being identified as carrier. The sum of FSH levels at 3, 4, 5 and 6 weeks of age is proposed as a predictor of presence of the Booroola gene in an animal. Multivariate analysis of mixed inheritance models could help to find more effective combinations. [ABSTRACT FROM PUBLISHER]

Context: Genetic evaluation of Australian sheep is conducted for millions of animals for more than 100 traits. Currently, the Australian sheep genetic-analysis software (OVIS) applies a pre-adjustment of phenotype for fixed effects rather than fitting all fixed and random effects jointly in a linear mixed model to estimate breeding values. However, the current correction factors might be outdated and potential interactions among fixed effects not accounted for, which could lead to bias in estimated breeding values (EBVs). Aims: This study aimed to assess whether correction factors used in OVIS for early bodyweights recorded in meat sheep breeds are appropriate, so as to explore whether the pre-adjustment method is still suitable and how this compares with a linear mixed model, and to estimate the significance of interactions between fixed effects. Methods: Correlations between EBVs from different models and regression slopes from forward prediction were calculated, using weaning-weight data on 365 956 White Suffolk and 370 649 Poll Dorset sheep and post-weaning weight data on 292 538 White Suffolk and 303 864 Poll Dorset sheep. Key results: The current OVIS procedure resulted in regression slopes of progeny performance on sire EBVs (averaged over breeds) of 0.37 and 0.35 for weaning and post-weaning weights respectively. Updated pre-adjustment factors improved the regression slopes to 0.40 and 0.38 respectively. Analysis with a linear mixed model produced significantly better regression slopes than did pre-adjustment (0.47 and 0.44 respectively). Further, regression slopes obtained from the linear mixed model with flock by sex by age interaction averaged over breeds were 0.48 for weaning and 0.46 for post-weaning weight respectively, which was a moderate improvement over the current OVIS model. Including a flock by sex by age interaction produced significantly better improvement in Poll Dorset sheep and modest improvement in White Suffolk sheep than did linear mixed model without interaction. Conclusions: Using a linear mixed model with a flock by sex by age interaction significantly improves the utility of estimated breeding values for weaning and post-weaning weight in predicting the performance of future progeny. Implications: To account for systematic environmental effects, a linear mixed model should be used in OVIS to jointly estimate the fixed effects and EBVs. Genetic evaluation of Australian sheep is conducted for millions of animals for more than 100 traits. Prediction of genetic merit of animals includes correcting observed phenotypes for environmental effects to allow fair genetic comparisons among animals, and is conducted by using old sheep data solutions because it was hard to fit these effects in each analysis. In the current scenario with more computing power, fitting all effects together and accounting for flock by sex by age interaction improves the utility of the model in predicting the performance of future progeny for weight traits. [ABSTRACT FROM AUTHOR]

The present study assessed the effectiveness and cost–benefit of several genotyping strategies for breeding poll Merino sheep in a closed nucleus with different initial allele frequencies and assuming a single-gene responsible for the horn or poll phenotype. We assumed that selection was based on phenotypes or genotypes for a single gene conferring polledness via a complete-dominance model. Under such a model, a complete fixation of the 'polled allele' (P) requires genotyping of the ewe-selection candidates. Testing a higher proportion of female candidates resulted in a faster fixation of the P-allele. Fixation ranged from 1 year of selection with a high starting P-allele frequency of 0.9, to 7 years for low starting P-allele frequencies of 0.3. When premiums of AU$50 or AU$100 were paid for rams with a PP genotype, breeding for PP genotypes was not profitable when the starting P-allele frequency was below 0.7. If the starting allele frequency was above 0.7, net profitability was positive over 10 years when premiums of AU$200 were paid for known PP-genotype rams. While fixing the P-allele, genetic gain for production traits was slowed down in the first 5 years of selection by up to 23% and 3% for initial P allele-frequencies of 0.3 and 0.9 respectively. Lost genetic gain due to fixing the P-allele, which can never be recovered in a closed nucleus, incurred 200–800% higher costs than the DNA testing costs. Rates of genetic gain recovered to pre-P-allele selection level rates of genetic gain once the P-allele was fixed. Testing a maximum of 25% ewe-selection candidates was the least expensive strategy across all starting allele frequencies and premiums. To avoid large losses of genetic gain in a closed nucleus with low P-allele starting frequencies, opening the nucleus should be considered to increase starting P-allele frequencies and also to potentially increase rates of genetic gain to offset the economic loss caused by P-selection. Australian Merino sheep can be bred with horns or without (polled). There is evidence suggesting polled rams are becoming more desirable due to increased welfare standards for both the individual sheep and their human handlers. As such there is indication that ram buyers will pay a premium for polled rams at present. This paper investigates breeding strategies to infuse the poll gene into a flock and the cost–benefit to the ram breeder. [ABSTRACT FROM AUTHOR]

The present paper covers reproductive performance in an artificial-insemination (AI) program of the Sheep CRC Information Nucleus with 24 699 lambs born at eight locations in southern Australia across five lambings between 2007 and 2011. Results from AI with frozen semen compared well with industry standards for natural mating. Conception rates averaged 72%, and 1.45 lambs were born per ewe pregnant for Merino ewes and 1.67 for crossbreds. Lamb deaths averaged 21% for Merino ewes and 15% for crossbreds and 19%, 22% and 20% for lambs from ewes that were mated to terminal, Merino and maternal sire types, respectively. Net reproductive rates were 82% for Merino ewes and 102% for crossbreds. From 3198 necropsies across 4 years, dystocia and starvation-mismothering accounted for 72% of lamb deaths within 5 days of lambing. Major risk factors for lamb mortality were birth type (single, twin or higher order), birthweight and dam breed. Losses were higher for twin and triplet lambs than for singles and there was greater mortality at relatively lighter and heavier birthweights. We conclude that reproductive rate in this AI program compared favourably with natural mating. Lamb birthweight for optimum survival was in the 4-8-kg range. Crossbred ewes had greater reproductive efficiency than did Merinos. Artificial insemination is widespread in the Australian sheep industry so it is important to know if lamb mortality is comparable as with natural mating. This project showed that lamb mortality was similar to natural mating at around 20% with dystocia and starvation-mismothering accounting for 72% of lamb deaths. Therefore artificial insemination can be validly used for sheep reproduction studies. [ABSTRACT FROM AUTHOR]

The aims of this study were to quantify the relationship between age of first oestrus and yearling reproductive performance in maternal-cross ewes in the Information Nucleus Flock data and to estimate genetic and phenotypic correlations between early and later reproductive performance defined as three ages, yearling, hogget and adult in both Merino and maternal-cross ewes. Information on 2218 yearling records, 2047 hogget records and 910 age of first oestrus records were used in the analysis of maternal-cross ewes, whereas 3286 hogget and 2518 adult reproductive records were used in analysis of Merino ewes. Heritability estimates for yearling reproductive performance in maternal-cross ewes ranged from 0.08 ± 0.09 for ewe fecundity to 0.16 ± 0.05 for number of lambs born and were generally higher than hogget heritability estimates for both maternal-cross and Merino ewes. Age at first oestrus was found to have a low heritability, 0.02 with standard errors of 0.07 and 0.06 with and without weight fitted as a covariate. Genetic correlations between age at first oestrus with and without weight fitted as a covariate and yearling reproductive performance were positive, ranging from 0.07 ± 0.49 with lamb survival to 0.94 ± 0.39 with number of lambs born, which was unexpected. Correlations between traits from the same age class were high in both breed groups. Genetic correlations between yearling and hogget performance in maternal-cross ewes were generally lower than one, ranging from 0.46 ± 0.68 for lamb survival and 0.79 ± 0.50 for fertility suggesting that yearling and later reproductive performance are related but genetically different traits. In Merino ewes, the genetic correlations between hogget and adult performance followed a similar pattern. The small number of records in this study generated high standard errors for estimates, which restricts the conclusions that can be drawn. Overall, this study supports current practice used by 'Sheep Genetics', the Australian genetic evaluation system for sheep, in considering yearling reproductive performance as a trait separate from later parities for genetic evaluation purposes. Reproductive rate is an important profit driver in sheep enterprises. The aims of this study were to quantify the relationships between age at first oestrus and yearling reproductive performance, and reproduction performance across age classes in sheep. Our results support the current practice of analysing yearling reproductive performance as a separate trait from later reproductive performance in Australia's genetic evaluation system and indicate that age at first oestrus is not a reliable measure of sexual maturity in sheep. [ABSTRACT FROM AUTHOR]