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Coursework masters degrees in Australia have experienced rapid, decentralised growth since deregulation at the end of the 1980s. The result is an extraordinarily high level of diversity and some confusion as to standards, strategic positioning, purpose and educational approaches. Throughout this period of growth, a sense that large-scale (often distance-education based) collaboration between universities and with industry would be beneficial has not always led to successful outcomes. Using a new collaborative, industry-funded postgraduate coursework program as a case study, this paper describes the issues that decision-makers need to address and evaluates the challenges and benefits of the coursework masters in higher education. The outcomes of industry surveys, student interviews and action research suggest that postgraduate coursework can facilitate technology transfer and aid capacity building, through mechanisms similar to "mode 2" research. With some additional systems to ensure sustainability and standards, this could position coursework masters to be uniquely valuable nationally.

Mean fibre diameter measurements from yearling to 5-year-old Australian fine- and medium-wool Merino sheep were analysed using several multivariate models that varied in covariance structure. A pre-structured multivariate model was found to be the most parsimonious model in comparison with the other models fitted such as banded, autoregressive and random regression. In the preferred model, the ages of mean fibre diameter for fine-wool data were genetically partitioned into yearling, 2 years, 3 years and later ages and for medium-wool data into hogget, 2 years and later ages. The estimates of genetic correlations between mean fibre diameter measured at different ages for medium-wool sheep were higher (0.89-1.00) than those for fine-wool Merino (0.75-1.00). Appropriate genetic covariance structure should be defined among the expressions of a trait taken at different ages. For the ages of fibre diameter in Merino sheep, a pre-structured multivariate model was found to be the most parsimonious model. This would enable drawing correct inferences from the data and help devise the selection strategies. [ABSTRACT FROM AUTHOR]

The objective of this study was to estimate the value derived from using DNA information to increase the accuracy of beef sire selection in a closed seedstock herd. Breeding objectives for commercial production systems targeting 2 diverse markets were examined using multiple-trait selection indexes developed for the Australian cattle industry. Indexes included those for both maternal (self-replacing) and terminal herds targeting either a domestic market, where steers are finished on pasture, or the export market, where steers are finished on concentrate rations in feedlots and marbling has a large value. Selection index theory was used to predict the response to conventional selection based on phenotypic performance records, and this was compared with including information from 2 hypothetical marker panels. In 1 case the marker panel explained a percentage of additive genetic variance ecjual to the heritability for all traits in the breeding objective and selection criteria, and in the other case to one-half of this amount. Discounted gene flow methodology was used to calculate the value derived from the use of superior bulls selected using DNA test information and performance recording over that derived from conventional selection using performance recording alone. Resuits were ultimately calculated as discounted returns per DNA test purchased by the seedstock operator. The DNA testing using these hypothetical marker panels increased the selection response between 29 to 158%. The value of this improvement above that obtained using traditional performance recording ranged from $89 to 565 per commercial bull, and $5,332 to 27,910 per stud bull. Assuming that the entire bull calf crop was tested to achieve these gains, the value of the genetic gain derived from DNA testing ranged from $204 to 1,119 per test. All values assumed that the benefits derived from using superior bulls were efficiently transferred along the production chain to the seedstock producer incurring the costs of genotyping. These results suggest that the development of greater-accuracy DNA tests for beef cattle selection could be beneficial from an industry-wide perspective, but the commercial viability will strongly depend on price signaling throughout the production chain. [ABSTRACT FROM AUTHOR]

Coursework masters degrees in Australia have experienced rapid, decentralised growth since deregulation at the end of the 1980s. The result is an extraordinarily high level of diversity and some confusion as to standards, strategic positioning, purpose and educational approaches. Throughout this period of growth, a sense that large-scale (often distance-education based) collaboration between universities and with industry would be beneficial has not always led to successful outcomes. Using a new collaborative, industry-funded postgraduate coursework program as a case study, this paper describes the issues that decision-makers need to address and evaluates the challenges and benefits of the coursework masters in higher education. The outcomes of industry surveys, student interviews and action research suggest that postgraduate coursework can facilitate technology transfer and aid capacity building, through mechanisms similar to ‘mode 2’ research. With some additional systems to ensure sustainability and standards, this could position coursework masters to be uniquely valuable nationally. [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]

The author reflects on the developments in effective aimal breeding programmes in Australia, focusing on the adoption of technology and programmes by breeders from the science of animal breeding. Topics include the trends in the animal production systems in the country, the breeding programmes for sheep and cattle, and the challenges facing the animal breeding structure in its effort to achieve remarkable genetic gain.

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]

Australian beef cattle experience variable conditions, which may give rise to genotype-by-environment interactions depending on the genotypes' macro- and/or micro-genetic environmental sensitivity (GES). Macro-GES gives rise to genotype-by-environment interactions across definable and shared environments, while micro-GES causes heritable variation of phenotypes, e.g., the performance of progeny from one sire may be more variable than other sires. Yearling weight (YW) is a key trait in Australian Angus cattle that may be impacted by both macro- and micro-GES. Current models for genetic evaluation of YW attempt to account for macro-GES by fitting sire-by-herd interactions (S × H). Variation in micro-GES had not yet been estimated for YW in Australian Angus. The aim of this study was to estimate genetic variation due to macro- and micro-GES in YW of Australian Angus cattle. A reaction norm with contemporary group effects as the environmental covariate was fitted either as an alternative to or in combination with a random S × H effect to account for macro-GES. Double hierarchical generalised linear models (DHGLM), fitted as sire models, were used to estimate the genetic variance of the dispersion as a measure of micro-GES. Variation due to both macro- and micro-GES were found in YW. The variance of the slope of the reaction norm was 0.02-0.03 (SEs 0.00), while the S × H variance accounted for 7% of the phenotypic variance in all models. Results showed that both a random S × H effect and a reaction norm should be included to account for both macro-GES and the additional variation captured by an S × H effect. The heritability of the dispersion on the measurement scale ranged from 0.06 to 0.10 (SEs 0.00) depending on which model was used. It should therefore be possible to alter both macro- and micro-GES of YW in Australian Angus through selection. However, care should be taken to ensure an appropriate data structure when including sire-by-herd interactions in the mean part of a DHGLM; otherwise, it can cause biased estimates of micro-GES., (Copyright © 2023. Published by Elsevier B.V.)

Random regression (RR) models are recommended as an alternative to multiple-trait (MT) models for better capturing the variance-covariance structure over a trajectory and hence more accurate genetic evaluation of traits that are repeatedly measured and genetically change gradually over time. However, a limited number of studies have been done to empirically compare RR over a MT model to determine how much extra benefit could be achieved from one method over another. We compared the prediction accuracy of RR and MT models for growth traits of Australian meat sheep measured from 60 to 525 d, using 102,579 weight records from 24,872 animals. Variance components and estimated breeding values (EBVs) estimated at specific ages were compared and validated with forward prediction. The accuracy of EBVs obtained from the MT model was 0.58, 0.51, 0.54, and 0.56 for weaning, postweaning, yearling, and hogget weight stages, respectively. RR model produced accuracy estimates of 0.56, 0.51, 0.54, and 0.54 for equivalent weight stages. Regression of adjusted phenotype on EBVs was very similar between the MT and the RR models (P > 0.05). Although the RR model did not significantly increase the accuracy of predicting future progeny performance, there are other benefits of the model such as no limit to the number of records per animal, estimation of EBVs for early and late growth, no need for age correction. Therefore, RR can be considered a more flexible method for the genetic evaluation of Australian sheep for early and late growth, and no need for age correction., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Background: South Africa and Australia shares multiple important sheep breeds. For some of these breeds, genomic breeding values are provided to breeders in Australia, but not yet in South Africa. Combining genomic resources could facilitate development for across country selection, but the influence of population structures could be important to the compatability of genomic data from varying origins. The genetic structure within and across breeds, countries and strains was evaluated in this study by population genomic parameters derived from SNP-marker data. Populations were first analysed by breed and country of origin and then by subpopulations of South African and Australian Merinos., Results: Mean estimated relatedness according to the genomic relationship matrix varied by breed (-0.11 to 0.16) and bloodline (-0.08 to 0.06) groups and depended on co-ancestry as well as recent genetic links. Measures of divergence across bloodlines (F ST : 0.04-0.12) were sometimes more distant than across some breeds (F ST : 0.05-0.24), but the divergence of common breeds from their across-country equivalents was weak (F ST : 0.01-0.04). According to mean relatedness, F ST , PCA and Admixture, the Australian Ultrafine line was better connected to the SA Cradock Fine Wool flock than with other AUS bloodlines. Levels of linkage disequilibrium (LD) between adjacent markers was generally low, but also varied across breeds (r 2 : 0.14-0.22) as well as bloodlines (r 2 : 0.15-0.19). Patterns of LD decay was also unique to breeds, but bloodlines differed only at the absolute level. Estimates of effective population size (N e ) showed genetic diversity to be high for the majority of breeds (N e : 128-418) but also for bloodlines (N e : 137-369)., Conclusions: This study reinforced the genetic complexity and diversity of important sheep breeds, especially the Merino breed. The results also showed that implications of isolation can be highly variable and extended beyond breed structures. However, knowledge of useful links across these population substructures allows for a fine-tuned approach in the combination of genomic resources. Isolation across country rarely proved restricting compared to other structures considered. Consequently, research into the accuracy of across-country genomic prediction is recommended., (© 2022. The Author(s).)

Genotyping sheep for genome-wide SNPs at lower density and imputing to a higher density would enable cost-effective implementation of genomic selection, provided imputation was accurate enough. Here, we describe the design of a low-density (12k) SNP chip and evaluate the accuracy of imputation from the 12k SNP genotypes to 50k SNP genotypes in the major Australian sheep breeds. In addition, the impact of imperfect imputation on genomic predictions was evaluated by comparing the accuracy of genomic predictions for 15 novel meat traits including carcass and meat quality and omega fatty acid traits in sheep, from 12k SNP genotypes, imputed 50k SNP genotypes and real 50k SNP genotypes. The 12k chip design included 12 223 SNPs with a high minor allele frequency that were selected with intermarker spacing of 50-475 kb. SNPs for parentage and horned or polled tests also were represented. Chromosome ends were enriched with SNPs to reduce edge effects on imputation. The imputation performance of the 12k SNP chip was evaluated using 50k SNP genotypes of 4642 animals from six breeds in three different scenarios: (1) within breed, (2) single breed from multibreed reference and (3) multibreed from a single-breed reference. The highest imputation accuracies were found with scenario 2, whereas scenario 3 was the worst, as expected. Using scenario 2, the average imputation accuracy in Border Leicester, Polled Dorset, Merino, White Suffolk and crosses was 0.95, 0.95, 0.92, 0.91 and 0.93 respectively. Imputation scenario 2 was used to impute 50k genotypes for 10 396 animals with novel meat trait phenotypes to compare genomic prediction accuracy using genomic best linear unbiased prediction (GBLUP) with real and imputed 50k genotypes. The weighted mean imputation accuracy achieved was 0.92. The average accuracy of genomic estimated breeding values (GEBVs) based on only 12k data was 0.08 across traits and breeds, but accuracies varied widely. The mean GBLUP accuracies with imputed 50k data more than doubled to 0.21. Accuracies of genomic prediction were very similar for imputed and real 50k genotypes. There was no apparent impact on accuracy of GEBVs as a result of using imputed rather than real 50k genotypes, provided imputation accuracy was >90%., (© 2015 Stichting International Foundation for Animal Genetics.)

Genetic parameters were estimated for a range of meat quality traits recorded on Australian lamb meat. Data were collected from Merino and crossbred progeny of Merino, terminal and maternal meat breed sires of the Information Nucleus programme. Lambs born between 2007 and 2010 (n=8968) were slaughtered, these being the progeny of 372 sires and 5309 dams. Meat quality traits were found generally to be of moderate heritability (estimates between 0.15 and 0.30 for measures of meat tenderness, meat colour, polyunsaturated fat content, mineral content and muscle oxidative capacity), with notable exceptions of intramuscular fat (0.48), ultimate pH (0.08) and fresh meat colour a* (0.08) and b* (0.10) values. Genetic correlations between hot carcass weight and the meat quality traits were low. The genetic correlation between intramuscular fat and shear force was high (-0.62). Several measures of meat quality (fresh meat redness, retail meat redness, retail oxy/met value and iron content) appear to have potential for inclusion in meat sheep breeding objectives., (© 2013.)

Genome-wide association studies (GWAS) of attention-deficit/hyperactivity disorder (ADHD) offer the benefit of a hypothesis-free approach to measuring the quantitative effect of genetic variants on affection status. Generally the findings of GWAS relying on ADHD status have been non-significant, but the one study using quantitative measures of symptoms found SLC9A9 and SLC6A1 were associated with inattention and hyperactivity-impulsivity. Accordingly, we performed a GWAS using quantitative measures of each ADHD subtype measured with the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) scale in two community-based samples. This scale captures the full range of attention and kinetic behavior; from high levels of attention and appropriate activity to the inattention and hyperactivity-impulsivity associated with ADHD within two community-based samples. Our discovery sample comprised 1,851 participants (mean age = 22.8 years [4.8]; 50.6% female), while our replication sample comprised 155 participants (mean age = 26.3 years [3.1]; 68.4% females). Age, sex, age × sex, and age2 were included as covariates and the results from each sample were combined using meta-analysis, then analyzed with a gene-based test to estimate the combined effect of markers within genes. We compare our results with markers that have previously been found to have a strong association with ADHD symptoms. Neither the GWAS nor subsequent meta-analyses yielded genome-wide significant results; the strongest effect was observed at rs2110267 (4.62 × 10-7) for symptoms of hyperactivity-impulsivity. The strongest effect in the gene-based test was for GPR139 on symptoms of inattention (6.40 × 10-5). Replication of this study with larger samples will add to our understanding of the genetic etiology of ADHD.

Background: The Prevalence and persistence of ADHD have not been described in young Australian adults and few studies have examined how conduct problems (CP) are associated with ADHD for this age group. We estimate lifetime and adult prevalence and persistence rates for three categories of ADHD for 3795 Australian adults, and indicate how career, health and childhood risk factors differ for people with ADHD symptoms and ADHD symptoms plus CP., Methodology: Trained interviewers collected participant experience of ADHD, CP, education, employment, childhood experience, relationship and health variables. Three diagnostic definitions of ADHD used were (i) full DSM-IV criteria; (ii) excluding the age 7 onset criterion (no age criterion); (iii) participant experienced difficulties due to ADHD symptoms (problem symptoms)., Results: Prevalence rates in adulthood were 1.1%, 2.3% and 2.7% for each categorization respectively. Persistence of ADHD from childhood averaged across gender was 55.3% for full criteria, 50.3% with no age criterion and 40.2% for problem symptoms. ADHD symptoms were associated with parental conflict, poor health, being sexually assaulted during childhood, lower education, income loss and higher unemployment. The lifetime prevalence of conduct problems for adults with ADHD was 57.8% and 6.9% for adults without ADHD. The greatest disadvantage was experienced by participants with ADHD plus CP., Conclusion: The persistence of ADHD into adulthood was greatest for participants meeting full diagnostic criteria and inattention was associated with the greatest loss of income and disadvantage. The disadvantage associated with conduct problems differed in severity and was relevant for a high proportion of adults with ADHD. Women but not men with ADHD reported more childhood adversity, possibly indicating varied etiology and treatment needs. The impact and treatment needs of adults with ADHD and CP and the report of sexual assault during childhood by women and men with ADHD also deserve further study.

A multi-trait (MT) random regression (RR) test day (TD) model has been developed for genetic evaluation of somatic cell scores for Australian dairy cattle, where first, second and third lactations were considered as three different but correlated traits. The model includes herd-test-day, year-season, age at calving, heterosis and lactation curves modelled with Legendre polynomials as fixed effects, and random genetic and permanent environmental effects modelled with Legendre polynomials. Residual variance varied across the lactation trajectory. The genetic parameters were estimated using asreml. The heritability estimates ranged from 0.05 to 0.16. The genetic correlations between lactations and between test days within lactations were consistent with most of the published results. Preconditioned conjugate gradient algorithm with iteration on data was implemented for solving the system of equations. For reliability approximation, the method of Tier and Meyer was used. The genetic evaluation system was validated with Interbull validation method III by comparing proofs from a complete evaluation with those from an evaluation based on a data set excluding the most recent 4 years. The genetic trend estimate was in the allowed range and correlations between the two sets of proofs were very high. Additionally, the RR model was compared to the previous test day model. The correlations of proofs between both models were high (0.97) for bulls with high reliabilities. The correlations of bulls decreased with increasing incompleteness of daughter performance information. The correlations between the breeding values from two consecutive runs were high ranging from 0.97 to 0.99. The MT RR TD model was able to make effective use of available information on young bulls and cows, and could offer an opportunity to breeders to utilize estimated breeding values for first and later lactations.

Genetic parameters for carcass and meat quality traits of about 18-month-old Merino rams (n = 5870), the progeny of 543 sires from three research resource flocks, were estimated. The estimates of heritability for hot carcass weight (HCW) and the various fat and muscle dimension measurements were moderate and ranged from 0.20 to 0.37. The brightness of meat (colour L*, 0.18 +/- 0.03 standard error) and meat pH (0.22 +/- 0.03) also had moderate estimates of heritability, although meat relative redness (colour a*, 0.10 +/- 0.03) and relative yellowness (colour b*, 0.10 +/- 0.03) were lower. Heritability estimates for live weights were moderate and ranged from 0.29 to 0.41 with significant permanent maternal environmental effects (0.13 to 0.10). The heritability estimates for the hogget wool traits were moderate to high and ranged from 0.27 to 0.60. The ultrasound measurements of fat depth (FATUS) and eye muscle depth (EMDUS) on live animals were highly genetically correlated with the corresponding carcass measurements (0.69 +/- 0.09 FATC and 0.77 +/- 0.07 EMD). Carcass tissue depth (FATGR) had moderate to low genetic correlations with carcass muscle measurements [0.18 +/- 0.10 EMD and 0.05 +/- 0.10 eye muscle area (EMA)], while those with FATC were negative. The genetic correlation between EMD and eye muscle width (EMW) was 0.41 +/- 0.08, while EMA was highly correlated with EMD (0.89 +/- 0.0) and EMW (0.78 +/- 0.04). The genetic correlations for muscle colour with muscle measurements were moderately negative, while those with fat measurements were close to zero. Meat pH was positively correlated with muscle measurements (0.14 to 0.17) and negatively correlated with fat measurements (-0.06 to -0.18). EMDUS also showed a similar pattern of correlations to EMD with meat quality indicator traits, although FATUS had positive correlations with these traits which were generally smaller than their standard error. The genetic correlations among the meat colour traits were high and positive while those with meat pH were high and negative, which were all in the favourable direction. Generally, phenotypic correlations were similar or slightly lower than the corresponding genetic correlations. There were generally small to moderate negative genetic correlations between clean fleece weight (CFW) and carcass fat traits while those with muscle traits were close to zero. As the Merino is already a relatively lean breed, this implies that particular attention should be given to this relationship in Merino breeding programmes to prevent the reduction of fat reserves as a correlated response to selection for increased fleece weight. The ultrasound scan traits generally showed a similar pattern to the corresponding carcass fat and muscle traits. There was a small unfavourable genetic correlation between CFW and meat pH (0.19 +/- 0.07).