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Dr Helen Newton-Turner introduced a powerful model of bringing science into practice by working closely with breeders and the wider industry. This collaboration model has led to considerable achievements in genetic improvement in the Australian animal industries, with efficient genetic evaluation systems being implemented, providing a platform to achieve well defined breeding objectives and the introduction of new technologies such as genomic selection. The same model can be used to foster future development to achieve sustainable further improvements, allowing further technologies such as functional genomics to be used where they add value. This paper was prepared by Professor Julius van der Werf, the 2021 recipient of the Helen Newton-Turner Medal. Julius was awarded the medal for his outstanding contribution to genetic improvement of Australian livestock. [ABSTRACT FROM AUTHOR]

Context. Improving meat quality traits such as marbling is a well established breeding objective for many beef producers. More recently, the inclusion of feed efficiency is being considered. The main driving factors being the direct feed cost, as well as consumer concerns related to environmental sustainability of beef production. Aims. The main aim of this study was to examine modifying the definition of residual feed intake (RFI), by including an adjustment for intramuscular fat (IMF). The secondary aim was to further understand the genetic relationships between feed intake and a range of carcass traits. Methods. Using a population of 4034 Australian Angus animals, feed intake and carcass traits, along with pedigree and fixed effects, were analysed. This included the calculation of three definitions of RFI, being the standard definition, accounting for average daily gain and metabolic mid-weight, and two amended versions accounting for ultrasound IMF (RFIu), or carcass IMF (RFIi). Variance components, heritabilities, and genetic and phenotypic correlations were estimated and compared. Key results. All three definitions of RFI were moderately heritable (0.30-0.32) and highly correlated, both genetically (0.99) and phenotypically (0.99). Unfavourable genetic correlations were observed between RFI and carcass IMF (CIMF), and between RFIu and CIMF at 0.29 and 0.24 respectively. Similarly, there were unfavourable genetic correlations between RFI and ultrasound IMF (UIMF), between RFIi and UIMF, and between RFIu and UIMF at 0.30, 0,21 and 0.23 respectively. Conclusions. RFI can be redefined to account for traits, other than average daily gain and metabolic mid-weight, such as IMF. However due to limitations of phenotypic linear regression, and only small amounts of variation in feed intake being explained by the IMF traits, the redefinition of RFI was a suboptimal approach to breeding candidate selection. Furthermore, the present study confirmed the challenges with selecting for both feed efficiency and meat quality traits as they are generally genetically antagonist. Implications. For beef cattle breeding programs, the investigation of alternative selection approaches is warranted. This may include further understanding the genetic correlations among traits in the breeding objective and, according to their economic value, optimally weighting the related estimated breeding value. [ABSTRACT FROM AUTHOR]

1. Genetic (co)variances and parameters between body weights (BW) across the growth trajectory were estimated using a univariate random regression (RR) animal model. The effect of growth rates (GH) on age at first egg (AFE) and egg weight at first egg (EWFE) were explored using a series of univariate and bivariate analyses. 2. Body weights were taken from Thai native chickens at hatch day to 168 days of age. The model included interactions between age with hatch nested within year and sex as fixed effects, and random effects of direct additive genetic, direct permanent environmental, maternal genetic and maternal permanent environmental effects. All random effects were fitted as regressions to animals' age via quadratic Legendre polynomials and fitting six classes of residual variances was identified as an optimal variance structure to estimate parameters. 3. Genetic and phenotypic variances for BW increased with increasing age. Estimated heritabilities for direct additive (h2a) and maternal genetic (h2m) effects on BW traits ranged from 0.34 to 0.54, and 0.04 to 0.06, respectively. Estimated variance ratios for direct (c2ape) and maternal permanent environmental (c2mpe) effects ranged from 0.19 to 0.48 and 0.10 to 0.12, respectively. Estimated correlations between weights at different ages were high for all random effects. 4. Estimated h2a for six GH traits ranged from 0.06 to 0.28, while for AFE and EWFE these were 0.24 and 0.16, respectively. Estimated h2m and c2mpe were low for GH. Estimated genetic correlations between GH and AFE ranged from −0.22 to 0.02 and, between GH and EWFE, ranged from −0.05 to 0.40. These estimates suggested that selecting high GH chickens at 28 days of age can be expected to reduce AFE and to increase EWFE. [ABSTRACT FROM AUTHOR]

The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross-bred sheep populations based on single nucleotide polymorphism ( SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on 'average information restricted maximum likelihood' using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction ( GBLUP), and the accuracy of prediction was assessed based on a random 10-fold cross-validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross-bred population. In the combined cross-bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross-bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross-bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross-bred population could be overestimated if heterosis is not fitted in the model. [ABSTRACT FROM AUTHOR]

Reducing daily methane production (DMP) via selection for lower estimated daily (pasture) feed intake (DFI) has the potential to be more cost effective than direct selection for DMP. Daily feed intake has a high heritability and high genetic correlation to DMP and has a potential lower cost of measurement. This study's main aim was to determine for a breeding nucleus the optimal proportion of randomly selected young male and female cattle in which to estimate DFI. This optimum proportion was determined by modeling the measurement costs and response to selection of Angus cattle on a (standard industry) Angus breeding index (ABI) augmented with DFI and DMP in a combined breeding objective (BO), but without DMP being measured. For the assumed herd structure and considering a 20 yr planning horizon, the highest net present value (NPV) occurred when 64% of males and no females were measured for DFI. The highest breakeven DFI test cost (A$41.51/head) and highest returns on investment (ROI) occurred when 36% of males and no females had DFI estimates. Higher ROI were achieved when all males had DFI estimates before any females had DFI estimates. There was a diminishing increase in rate of genetic gain when moving from 36% to 64% of males with DFI estimates, thus ROI decreased from 29.7% to 23.1%. When 36% of males had DFI estimates (and no females), herd DMP genetic gain was slightly positive as the DMP reduction per generation from male selection (-0.086) was more than offset by the DMP increase per generation from female selection (+0.110). The selection response for DMP only became negative when at least 40% of males had DFI estimates. Having 64% of males with DFI estimates resulted in a predicted genetic decrease in DMP (-0.018 kgCO2e/head per yr), compared to an increase of 0.052 kgCO2e/head per yr when no animals had DFI estimates. The optimum proportion of males with DFI estimates (36 to 64%) depends on the breeders attitude toward ROI and the value of genetic change for DMP. Sensitivity analysis showed that the economic value (EV), heritability and genetic variance of DFI had a higher impact on the NPV and ROI outcomes than parameters related to ABI and DMP, so future work should focus on obtaining robust estimates for DFI parameters. Higher EV for feed intake and DMP would result in higher percentages of animals being profitably measured for DFI, leading to larger reductions in DMP. [ABSTRACT FROM AUTHOR]

Heritabilities and genetic correlations for milk production traits were estimated from first-parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Legm) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits. [ABSTRACT FROM AUTHOR]

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]

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnonnality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success. [ABSTRACT FROM AUTHOR]

Causal mutations affecting quantitative trait variation can be good targets for marker-assisted selection for carcass traits in beef cattle. In this study, linkage and linkage disequilibrium analysis (LDLA) for four carcass traits was undertaken using 19 markers on bovine chromosome 14. The LDLA analysis detected quantitative trait loci (QTL) for carcass weight (CWT) and eye muscle area (EMA) at the same position at around 50 cM and surrounded by the markers FABP4SNP2774C>G and FABP4_μsat3237. The QTL for marbling (MAR) was identified at the midpoint of markers BMS4513 and RM137 in a 3.5-cM marker interval. The most likely position for a second QTL for CWT was found at the midpoint of tenth marker bracket ( FABP4SNP2774C>G and FABP4_μsat3237). For this marker bracket, the total number of haplotypes was 34 with a most common frequency of 0.118. Effects of haplotypes on CWT varied from a −5-kg deviation for haplotype 6 to +8 kg for haplotype 23. To determine which genes contribute to the QTL effect, gene expression analysis was performed in muscle for a wide range of phenotypes. The results demonstrate that two genes, LOC781182 ( p = 0.002) and TRPS1 ( p = 0.006) were upregulated with increasing CWT and EMA, whereas only LOC614744 ( p = 0.04) has a significant effect on intramuscular fat (IMF) content. Two genetic markers detected in FABP4 were the most likely QTL position in this QTL study, but FABP4 did not show a significant effect on both traits (CWT and EMA) in gene expression analysis. We conclude that three genes could be potential causal genes affecting carcass traits CWT, EMA, and IMF in Hanwoo. [ABSTRACT FROM AUTHOR]

Genetic correlations for body measurements and subjectively scored traits between foals and studbook horses were estimated using bivariate linear mixed models. Observations for nine foal and eleven studbook traits in Finnhorses on 6529 foals and 6596 studbook horses and in Standardbred trotters on 3069 foals and 2112 studbook horses were available from the Finnish horse breeding shows. The number of sires with progeny in both foal and studbook data was 203 in Finnhorse and 145 in Standardbred trotters. Estimates of heritability for body measurements in foals and studbook horses using univariate models were high in both breeds (0.41-0.84). Heritability estimates for subjectively scored traits using univariate models were generally higher for foals (0.08-0.46) than for studbook horses (0.06-0.21) in both breeds. Genetic correlations between foals and studbook horses for body measurements were highly positive ranging from 0.74 to 0.96 in Finnhorses and from 0.79 to 0.99 in Standardbred trotters. Low to highly positive genetic correlations between foals and studbook horses for subjectively scored traits were obtained in Finnhorse trotters, whereas in Standardbred trotters genetic correlations for subjectively scored traits varied from moderately negative to highly positive. Higher estimates of heritability for foal traits and generally high genetic correlations between the foal and studbook traits indicate that an early selection for conformation traits would be efficient in the breeding programmes. [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]

Three microsatellite markers on goat chromosome 23 adjacent to the MHC were used to test for quantitative trait loci (QTL) affecting faecal worm egg count (WEC) and leukocyte traits in ten Australian Angora and twelve Australian Cashmere half-sib families (n = 16–57 per family). Data were collected from 280 Angora and 347 Cashmere kids over a 3- and 4-year period. A putative QTL affecting trichostrongyle WEC was found in two small families at the 5% chromosome-wise threshold level. The biggest QTL effect for WEC of 1.65 standard deviations (σp) was found within the region of OarCP73- BM1258. A significant QTL affecting blood eosinophil counts at the 1% chromosome–wise threshold level was detected at marker BM1258 (at 26 cM) in two Angora and Cashmere families. The magnitude of the putative QTL was 0.69 and 0.85 σp in Angora and Cashmere families, respectively. Due to the comparatively low power of the study these findings should be viewed as indicative rather than definitive. [ABSTRACT FROM AUTHOR]

Summary: We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software based on the mixed model equation, our method is substantially faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including multi-trait models and random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss the advantages and limitations. [ABSTRACT FROM AUTHOR]

Abstract: Neuropsychological and neuroimaging studies have implicated the human posterior parietal cortex (PPC) in sensorimotor integration and saccade planning. However, the temporal dynamics of the underlying physiology and its relationship to observations in non-human primates have been difficult to pin down. Here we review some recent work that investigates the role of human parietal neuronal synchronization in the coding and updating of visuomotor representations in saccade and anti-saccade tasks. We also discuss this work in relation to findings made on different spatial and temporal scales in monkey and human posterior parietal cortex. [Copyright &y& Elsevier]

The research domain of process discovery aims at constructing a process model (e.g. a Petri net) which is an abstract representation of an execution log. Such a model should (1) be able to reproduce the log under consideration and (2) be independent of the number of cases in the log. In this paper, we present a process discovery algorithm where we use concepts taken from the language-based theory of regions, a well-known Petri net research area. We identify a number of shortcomings of this theory from the process discovery perspective, and we provide solutions based on integer linear programming. [ABSTRACT FROM AUTHOR]

Optimal selection on a single identified quantitative trait locus (QTL) with four modes of inheritance: normal autosomal, sex-limited, imprinting and X-linked, was evaluated in four breeding structures: single line selection (SLS), two-way crossing (2WC), three-way crossing (3WC) and reciprocal crossing (RC) by comparing extra benefit from mate selection over index selection to demonstrate effectiveness of mate selection in exploiting non-additive QTL. The results showed that the superiority varied at different QTL inheritance modes, initial favourable allele frequencies and breeding structures. The superiority tended to decrease with the increase of the favourable allele frequency except for over-dominant QTL and imprinted QTL in all breeding structures. Less superiority (below 9%) was observed for a recessive and a fully dominant QTL than for an over-dominant QTL (up to 27.11%). Normal autosomal and sex-linked QTL led to a similar trend of superiority from mate selection but the magnitude of the superiority with the latter was slightly higher than with the former for most combinations of the parameters. A high superiority (6.41–41.54%) was observed from mate selection over index selection for an imprinted QTL. A maternally imprinted QTL tended to lead to higher superiority from mate selection than a paternally imprinted QTL. X-linked QTL led to less superiority from mate selection than the other modes of QTL. A larger superiority from mate selection was observed for a recessive and a fully dominant QTL in structures 3WC and 2WC than structures RC and SLS. The superiority from autosomal QTL and X-linked QTL was lower in the structure RC than in other structures examined. [ABSTRACT FROM AUTHOR]

A large series of field-scale experiments on turbulent sand-laden flows, conducted in preceding years in the LOWT and AOFT large oscillating water tunnels are reviewed and reanalysed. Using the combined experimental data sets, new insights are obtained on the detailed sand transport processes occurring in sheet-flow and ripple regime conditions. For sheet flow (i) new equations are presented relating maximum erosion depth and sheet-flow layer thickness to the maximum Shields parameter; (ii) detailed analysis of sediment flux data shows the dominance of the current-related flux in the sheet-flow layer and the different characters of the current-related flux for fine and medium sands; (iii) a RANS-diffusion type model is shown to reproduce important trends in net transport rate related to grain size, velocity and wave period and to predict the magnitude of net transport rate to within a factor 2 of measured values. For the ripple regime it is shown that (i) asymmetric waves generate negative ('offshore') streaming and the current-related suspended sediment flux associated with this streaming appears to be of the same order of magnitude as the wave-related suspended sediment flux; (ii) time-averaged near-bed transport and time-averaged suspended transport appear to be of about equal magnitude but of opposite sign, and are concentrated on the 'onshore' flank of the ripple for asymmetric wave conditions; (iii) near-bed transport along the onshore flank is generated by sand transported over the ripple crest during the 'onshore' half-cycle. Net sand transport under asymmetric waves can be 'onshore' directed or 'offshore' directed, depending on the degree of unsteadiness in the sand flux behaviour during the wave cycle. Dimensionless phase-lag parameters are presented, for sheet flow and ripples, which can discriminate between predominantly quasi-steady behaviour (resulting in 'onshore' transport) and predominantly unsteady behaviour (resulting in 'offshore transport'). [ABSTRACT FROM AUTHOR]

Genotyping of the South African, registered, Brahman cattle population for the 470del20 mutation in the CHRNE gene causing congenital myasthenic syndrome (CMS) was carried out in 1,453 animals. Overall prevalence of carriers was 0.97% (0.50 to 1.68%, 95% confidence interval). Carrier prevalence among breeding bulls in 2004 was 1.22% (0.65 to 2.15%, 95% confidence interval), and had not changed significantly since 2000. Using segregation analysis, CMS genotype probabilities were calculated for all 612,219 animals in the pedigree, leading to the identification of 2 founder animals as the most likely original carriers. Pedigree analysis revealed no ancestors common to all known carriers, but rather that the mutation had been introduced at least twice into the South African Brahman population, probably via animals imported from the United States. The effects of CMS genotype probability on adjusted birth, 200-d, 400-d, and 600-d BW, as well as on EBV for birth, 200-d, 400-d, and 600-d BW, and milk, were estimated, accounting for effects of sire. Heterozygosity for the CHRNE 470del20 mutation was associated with a 13.3-kg increase in adjusted 600-d BW (P = 0.03). Positive effects of CMS carrier status on all BW EBV were found, but no effect was found on milk EBV. We conclude that CMS carriers have a BW advantage at 600 d and possibly also at birth, 200 d, and 400 d. This may confer a selective advantage and tend to increase the frequency of the mutation. [ABSTRACT FROM AUTHOR]

Dominance (intralocus allelic interactions) plays often an important role in quantitative trait variation. However, few studies about dominance in QTL mapping have been reported in outbred animal or human populations. This is because common dominance effects can be predicted mainly for many full sibs, which do not often occur in outbred or natural populations with a general pedigree. Moreover, incomplete genotypes for such a pedigree make it infeasible to estimate dominance relationship coefficients between individuals. In this study, identity-by-descent (IBD) coefficients are estimated on the basis of population- wide linkage disequilibrium (LD), which makes it possible to track dominance relationships between unrelated founders. Therefore, it is possible to use dominance effects in QTL mapping without full sibs. Incomplete genotypes with a complex pedigree and many markers can be efficiently dealt with by a Markov chain Monte Carlo method for estimating IBD and dominance relationship matrices (DRM). It is shown by simulation that the use of DRM increases the likelihood ratio at the true QTL position and the mapping accuracy and power with complete dominance, overdominance, and recessive inheritance modes when using 200 genotyped and phenotyped individuals. [ABSTRACT FROM AUTHOR]

Within a small region (e.g., <10 cM), there can be multiple quantitative trait loci (QTL) underlying phenotypes of a trait. Simultaneous fine mapping of closely linked QTL needs an efficient tool to remove confounded shade effects among QTL within such a small region. We propose a variance component method using combined linkage disequilibrium (LD) and linkage information and a reversible jump Markov chain Monte Carlo (MCMC) sampling for model selection. QTL identity-by-descent (IBD) coefficients between individuals are estimated by a hybrid MCMC combining the random walk and the meiosis Gibbs sampler. These coefficients are used in a mixed linear model and an empirical Bayesian procedure combines residual maximum likelihood (REML) to estimate QTL effects and a reversible jump MCMC that samples the number of QTL and the posterior QTL intensities across the tested region. Note that two MCMC processes are used, i.e., an (internal) MCMC for IBD estimation and an (external) MCMC for model selection. In a simulation study, the use of the multiple-QTL model clearly removes the shade effects between three closely linked QTL located at 1.125, 3.875, and 7.875 cM across the region of 10 cM, using 40 markers at 0.25-cM intervals. It is shown that the use of combined LD and linkage information gives much more useful information compared to using linkage information alone for both single- and multiple-QTL analyses. When using a lower marker density (11 markers at 1-cM intervals), the signal of the second QTL can disappear. Extreme values of past effective size (resulting in extreme levels of LD) decrease the mapping accuracy. [ABSTRACT FROM AUTHOR]

A linkage analysis for finding inheritance states and haplotype configurations is an essential process for linkage and association mapping. The linkage analysis is routinely based upon observed pedigree information and marker genotypes for individuals in the pedigree. It is not feasible for exact methods to use all such information for a large complex pedigree especially when there are many missing genotypic data. Proposed Markov chain Monte Carlo approaches such as a single-site Gibbs sampler or the meiosis Gibbs sampler are able to handle a complex pedigree with sparse genotypic data; however, they often have reducibility problems, causing biased estimates. We present a combined method, applying the random walk approach to the reducible sites in the meiosis sampler. Therefore, one can efficiently obtain reliable estimates such as identity-by-descent coefficients between individuals based on inheritance states or haplotype configurations, and a wider range of data can be used for mapping of quantitative trait loci within a reasonable time. [ABSTRACT FROM AUTHOR]

Combined linkage disequilibrium and linkage (LDL) mapping can exploit historical as well as recent and observed recombinations in a recorded pedigree. We investigated the role of pedigree information in LDL mapping and the performance of LDL mapping in general complex pedigrees. We compared using complete and incomplete genotypic data, spanning 5 or 10 generations of known pedigree, and we used bi- or multiallelic markers that were positioned at 1- or 5-cM intervals. Analyses carried out with or without pedigree information were compared. Results were compared with linkage mapping in some of the data sets. Linkage mapping or LDL mapping with sparse marker spacing (∼5 cM) gave a poorer mapping resolution without considering pedigree information compared to that with considering pedigree information. The difference was bigger in a pedigree of more generations. However, LDL mapping with closely linked markers (∼1; cM) gave a much higher mapping resolution regardless of using pedigree information. This study shows that when marker spacing is dense and there is considerable linkage disequilibrium generated from historical recombinations between flanking markers and QTL, the loss of power due to ignoring pedigree information is negligible and mapping resolution is very high. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate an association between polymorphisms in the FABP4 gene and phenotypic variation for marbling and carcass weight (CWT) in a population of Hanwoo steers. We re-sequenced 4.3 kb of the FABP4 gene region in 24 Hanwoo bulls and identified 16 SNPs and 1 microsatellite polymorphism. Of these 16 SNPs, three SNPs [g.2774G>C (intron I), g.3473A>T (intron II) and g.3631G>A (exon III, creating a p.Met >Val amino acid substitution)] were genotyped in 583 steers to assess their association with carcass traits. The g.3473A allele showed a significant increasing effect on CWT ( P = 0.01) and the g.3631G allele was associated with higher marbling score ( P = 0.006). One haplotype of these three SNPs (CAG) was significantly associated with CWT ( P = 0.02) and marbling score ( P = 0.05) and could potentially be of value for marker assisted selection in Hanwoo cattle. The CAG haplotype effect for CWT was larger (11.14 ± 5.03 kg) than the largest single locus effect of g.3473A>T (5.01 ± 2.2 kg). [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.

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]

This study explores the interaction between genetic potential for growth in Merino lambs and their birth type (BT) or rearing type (RT). Data on birthweight (BWT), weaning weight (WWT), post-weaning weight (PWWT), scan fat (PFAT) and eye muscle depth (PEMD) were used from 3920 single and 4492 twin-born lambs from 285 sires and 5279 dams. Univariate analysis showed a significant sire × BT interaction accounting for 1.59% and 2.49% of the phenotypic variation for BWT and WWT, respectively, and no significant effect for PWWT, PFAT and PEMD. Sire × RT interaction effects were much smaller and only significant for PEMD. Bivariate analysis indicated that the genetic correlation (rg) between trait expression in lambs born and reared as singles versus those born and reared as twins were high for BWT, WWT, PWWT (0.91 ± 0.02 – 0.96 ± 0.01), whereas rg for PFAT and PEMD were lower (0.81 ± 0.03 and 0.86 ± 0.02). The rg between traits expressed in lambs born and reared as singles versus those born as twins but reared as singles were lower: 0.77 ± 0.08, 0.88 ± 0.03, 0.66 ± 0.06 and 0.61 ± 0.08 for WWT, PWWT, PFAT and PEMD, respectively. A different RT only affected the expression of breeding values for PFAT and PEMD (rg 0.62 ± 0.04 and 0.47 ± 0.03, respectively). This study showed genotype × environment interaction for BWT and WWT (sire × BT interaction) and for PEMD (sire by RT interaction). However, sires' breeding value of a model that accounts for sire × BT interaction provides a very similar ranking of sires compared with a model that ignores it, implying that there is no need to correct for the effect in models for genetic evaluation. This study explored whether breeding values for bodyweight are equally expressed in lambs with different birth or rearing type. The correlation between breeding values for early growth of lamb when expressed in single or twin birth types was less than one whereas different rearing type influenced expression of breeding value at late growth. However, this interaction between genotype and birth or rearing type did not affect ranking of sire's breeding value in these two different environments, implying that there is no need to account for the effect of genetic evaluation. [ABSTRACT FROM AUTHOR]

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]

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%. [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]

A model of the sheep breeding industry with nucleus flocks, multiplier flocks and commercial sheep flocks was used to examine the value of genomic selection. The model reflected a dual-purpose Merino breeding objective, with genomic information improving selection accuracy by 39% for rams at 6 months of age and by 17% at 18 months. The current level of net dollar benefit to the sheep industry from selection, but without genomic testing, can be improved by 10-14% for a closed three-tiered breeding structure with rams used at 18 months. If the rams are first used at 6-7 months then the dollar gains can be improved by 15-17%, since genomic information can provide proportionately greater gains for young animals that have limited phenotypic information. In a two-tiered breeding system, with nucleus flocks selling rams direct to commercial producers, rather than through multiplier flocks, the dollar gains to industry from genomic testing increased to ~12-13% for rams bred at 18 months, and 20-22% if nucleus rams are used at 6-7 months. The optimal structure requires two-stage selection, with an initial selection based on information available without genomic testing, to limit the cost of testing to only the superior rams. However, the optimum proportion of rams tested depends on the system and the cost of testing. In order to recover the cost of genomic testing, the nucleus flocks must recover up to 5% of the extra genetic gain as extra profit from sale of rams to commercial sheep producers. A model of the sheep breeding industry examined the value of genomic information in sheep breeding programs. Benefits can be obtained by both the traditional three-tiered wool industry structure and studs using genomic information and selling directly to commercial producers, with most of the benefits retained by the commercial producers. The proportion of nucleus rams that use genetic tests must be optimised to achieve the maximum economic benefit. [ABSTRACT FROM AUTHOR]

The heritability of attention-deficit/hyperactivity disorder (ADHD) is higher for children than adults. This may be due to increasing importance of environment in symptom variation, measurement inaccuracy when two raters report behavior of a twin-pair, a contrast effect resulting from parental comparison of siblings and/or dimensionality of measures. We examine rater contrast and sex effects in ADHD subtypes using a dimensional scale and compare the aetiology of self, versus maternal-report. Data were collected using the Strengths and Weaknesses of ADHD and Normal Behaviour Scale (SWAN): maternal-report for 3,223 twins and siblings (mean age 21.2, SD = 6.3) and self-report for 1,617 twins and siblings (mean age 25.5, SD = 3.2). Contrast effects and magnitude of genetic and environmental contributions to variance of ADHD phenotypes (inattention, hyperactivity-impulsivity, combined behaviours) were examined using structural equation modeling. Contrast effects were evident for maternal-report hyperactivity-impulsivity ( b = −0.04) and self-report inattention (−0.09) and combined ADHD (−0.08). Dominant genetic effects were shared by raters for inattention, hyperactivity-impulsivity and combined ADHD. Broad-sense heritability was equal across sex for maternal-report inattention, hyperactivity-impulsivity and combined ADHD (0.72, 0.83, 0.80). Heritability for corresponding subtypes in self-reported data were best represented by sex (0.46, 0.30, 0.39 for males; 0.69, 0.41, 0.65 for females). Heritability difference between maternal and self-report ADHD was due to greater variance of male specific environment in self-report data. Self-reported ADHD differed across sex by magnitude of specific environment and genetic effects. [ABSTRACT FROM AUTHOR]

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]

The objective of this study was to predict the accuracy of genomic prediction for 26 traits, including weight, muscle, fat, and wool quantity and quality traits, in Australian sheep based on a large, multi-breed reference population. The reference population consisted of two research flocks, with the main breeds being Merino, Border Leicester (BL), Poll Dorset (PD), and White Suffolk (WS). The genomic estimated breeding value (GEBV) was based on GBLUP (genomic best linear unbiased prediction), applying a genomic relationship matrix calculated from the 50K Ovine SNP chip marker genotypes. The accuracy of GEBV was evaluated as the Pearson correlation coefficient between GEBV and accurate estimated breeding value based on progeny records in a set of genotyped industry animals. The accuracies of weight traits were relatively low to moderate in PD and WS breeds (0.11-0.27) and moderate to relatively high in BL and Merino (0.25-0.63). The accuracy of muscle and fat traits was moderate to relatively high across all breeds (between 0.21 and 0.55). The accuracy of GEBV of yearling and adult wool traits in Merino was, on average, high (0.33-0.75). The results showed the accuracy of genomic prediction depends on trait heritability and the effective size of the reference population, whereas the observed GEBV accuracies were more related to the breed proportions in the multi-breed reference population. No extra gain in within-breed GEBV accuracy was observed based on across breed information. More investigations are required to determine the precise effect of across-breed information on within-breed genomic prediction. Use of genomic data for estimation of breeding value in rams can considerably increase the accuracy of selection of sheep for increased profitability. In this study we found the accuracy of genomic prediction for weight, muscle, fat and wool traits to be moderate to high in Merinos and moderate in terminal and maternal sheep breeds. These results provide confidence to use genomic selection in sheep breeding. [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]

Increasing milk yields in modern dairy cows cause concern that high yield may impair the cows' health and welfare, for example, via negative effects on metabolic status and hypothalamo-pituitary-adrenocortical (HPA) function. This study aims to investigate whether a high level of milk production, and the associated metabolic status, affects HPA function in dairy cows and changes their adaptive capacity. Additionally, it aims to establish whether possible effects of milk production level only show under challenging conditions. Holstein-Friesian cows, which produced on average 11,443 and 7727 kg of fat and protein-corrected milk (FPCM)/305 d in their previous lactation, were compared. During the dry period, the cows were fed to requirements or overfed. High milk yield and the concomitant large energy deficit were associated with 1) increased pituitary (re)activity, i.e., increased ACTH baseline concentrations and higher ACTH concentrations after corticotropin-releasing hormone (CRH) administration, and 2) decreased adrenocortical reactivity, i.e., lower cortisol responses after ACTH administration. Although significant, the effects of milk production level on HPA function were relatively small. Animals showed seemingly normal hormonal responses to CRH and ACTH administration. Also, cortisol baseline concentrations were unaffected. It seems, therefore, unlikely that the adaptive capacity of the high-producing cows was significantly impaired compared with their low-producing herdmates. [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 data used in the present study consisted of 24 535 worm egg count records on sheep observed from 63 to 560 days of age under conditions of the natural challenge of trichostrongylid species. Records were extracted from the Information Nucleus Flock database of the Australia Sheep Cooperative Research Centre program from 2007 to 2011. Records were observed at various ages and subdivided into weaning (W, ~3 months), post-weaning (P, ~4 months), yearling (Y, ~12 months) and hogget (H, ~18 months) age stages and were used to investigate genetic variation at different age stages in univariate analyses and estimate genetic correlations between age stages in multi-trait analyses. The full data were also analysed by random regression models to study how heritability and genetic correlations varied with age. Heritability estimates from univariate analyses were 0.20 ± 0.05, 0.15 ± 0.02, 0.36 ± 0.09, 0.22 ± 0.06 for W, P, Y and H age stages respectively. A similar trend of heritability over ages was found from random regression analyses, which decreased from 0.16 at 90 days to 0.09 at 120 days, following a steady increase to 0.32 at ~410 days, and then decreased afterwards to 0.24 at 520 days. Strong genetic correlations (>0.8) were found between W and P age stages, along with Y and H age stages. Sire by flock interaction effects were significant, and accounted for the reduced estimates of heritability and increased genetic correlations between age stages. The results indicated that a multiple-trait approach is required for genetic evaluation of worm egg count when measurements are at different ages, and the accuracy of evaluations would benefit from recording at least two separate age stages. Faecal worm egg count (WEC) is an important trait for breeding for host resistance to parasites in sheep. The aim of the present study was to investigate whether genetic parameters differed for WEC measured at weaning, post-weaning, yearling and hogget age stages. The results showed lower variation and heritability at younger ages, and genetic correlations across ages significantly lower than unity, indicating that breeders would benefit by recording WEC at two or more different ages. [ABSTRACT FROM AUTHOR]

Theory to predict selection response in traditional livestock breeding programs has been well developed, validated and implemented in software in the past decades, for example in SelAction (Rutten et al. 2002), which has been successful as a tool to predict selection response in traditional livestock breeding programs for a wide range of population structures and selection strategies. This software used standard quantitative genetics theory and selection index theory to develop deterministic recursive equations, which model changes of trait means and variance-covariance structures to predict asymptotic response to multiple trait selection using best linear unbiased prediction (BLUP) estimated breeding values (EBV). Nowadays genetic improvement can further be enhanced by genomic predictions, which provide more accurate estimates of breeding values of animals in their earlier life and can improve the efficiency of breeding programs. While statistical methods to estimate genomic breeding values are now widely available, optimizing the use of genomics in practical livestock breeding programs is limited due to the lack of computer software that implements available theories. We're hereby to present a computer program that extends SelAction. Genomic information is included as the average phenotype of groups of individuals with both genotypic and phenotypic information following Wientjes et al. (2016). The heterogeneity of genomic information is considered in terms of the degree of relationship between selection candidates and the individuals that are both genotyped and phenotyped (van der Werf et al., 2015). This software can be used by breeders to reliably compare alternative breeding programs and for investment decisions for breeding programs that include genomic information. Funded by USDA-NIFA grant #2017-67015-26299. [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]

Genetic correlations between 29 wool production and quality traits and 25 meat quality and nutritional value traits were estimated for Merino sheep from an Information Nucleus (IN). Genetic correlations among the meat quality and nutritional value traits are also reported. The IN comprised 8 flocks linked genetically and managed across a range of sheep production environments in Australia. The wool traits included over 5,000 yearling and 3,700 adult records for fleece weight, fiber diameter, staple length, staple strength, fiber diameter variation, scoured wool color, and visual scores for breech and body wrinkle. The meat quality traits were measured on samples from the M. longissimus thoracis et lumborum and included over 1,200 records from progeny of over 170 sires for intramuscular fat (IMF), shear force of meat aged for 5 d (SF5), 24 h postmortem pH (pH24LL; also measured in the semitendinosus muscle, pH24ST), fresh and retail meat color and meat nutritional value traits such as iron and zinc levels, and long-chain omega-3 and omega-6 polyunsaturated fatty acid levels. Estimated heritabilities for IMF, SF5, pH24LL, pH24ST, retail meat color lightness (L*), myoglobin, iron, zinc and across the range of long-chain fatty acids were 0.58 ± 0.11, 0.10 ± 0.09, 0.15 ± 0.07, 0.20 ± 0.10, 0.59 ± 0.15, 0.31 ± 0.09, 0.20 ± 0.09, 0.11 ± 0.09, and range of 0.00 (eicosapentaenoic, docosapentaenoic, and arachidonic acids) to 0.14 ± 0.07 (linoleic acid), respectively. The genetic correlations between the wool production and meat quality traits were low to negligible and indicate that wool breeding programs will have little or no effect on meat quality. There were moderately favorable genetic correlations between important yearling wool production traits and the omega-3 fatty acids that were reduced for corresponding adult wool production traits, but these correlations are unlikely to be important in wool/ meat breeding programs because they have high SE, and the omega-3 traits have little or no genetic variance. Significant genetic correlations among the meat quality traits included IMF with SF5 (-0.76 ± 0.24), fresh meat color L* (0.50 ± 0.18), and zinc (0.41 ± 0.19). Selection to increase IMF will improve meat tenderness and color which may address some of the issues with Merino meat quality. These estimated parameters allow Merino breeders to combine wool and meat objectives without compromising meat quality. [ABSTRACT FROM AUTHOR]

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro fertilisation and embryo transfer (JIVET) can produce multiple offspring per mating in sheep and cattle. In breeding programs this allows for higher female selection intensity and, in the case of JIVET, a reduction in generation interval, resulting in higher rates of genetic gain. Low selection accuracy of young females entering JIVET has often dissuaded producers from using this technology. However, genomic selection (GS) could increase selection accuracy of candidates at a younger age to help increase rates of genetic gain. This increase might vary for different traits in multiple trait breeding programs depending on genetic parameters and the practicality of recording, particularly for hard to measure traits. This study used both stochastic (animals) and deterministic (GS) simulation to evaluate the effect of reproductive technologies on the genetic gain for various traits in sheep breeding programs, both with and without GS. Optimal contribution selection was used to manage inbreeding and to optimally assign reproductive technologies to individual selection candidates. Two Australian sheep industry indexes were used - a terminal sire index that focussed on growth and carcass traits (the 'Lamb 2020' index) and a Merino index that focuses on wool traits, bodyweight, and reproduction (MP+). We observed that breeding programs using artificial insemination or natural mating (AI/N) + MOET, compared with AI/N alone, yielded an extra 39% and 27% genetic gain for terminal and Merino indexes without GS, respectively. However, the addition of JIVET to AI/N + MOET without GS only yielded an extra 1% genetic gain for terminal index and no extra gain in the Merino index. When GS was used in breeding programs, we observed AI/N + MOET + JIVET outperformed AI/N + MOET by 21% and 33% for terminal and Merino indexes, respectively. The implementation of GS increased genetic gain where reproductive technologies were used by 9-34% in Lamb 2020 and 37-98% in MP+. Individual trait response to selection varied in each breeding program. The combination of GS and reproductive technologies allowed for greater genetic gain in both indexes especially for hard to measure traits, but had limited effect on the traits that already had a large amount of early age records. [ABSTRACT FROM AUTHOR]

Genomic 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. [ABSTRACT FROM AUTHOR]

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations ( DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born ( NLB), litter size ( LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction ( GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values ( GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording. [ABSTRACT FROM AUTHOR]

Genetic correlations between 29 wool production and quality traits and 14 whole carcass measures and carcass component traits were estimated from the Information Nucleus of 8 flocks managed across a range of Australian sheep production environments and genetically linked. Wool data were from over 5,000 Merino progeny born over 5 yr, whereas carcass data were from over 1,200 wether progeny of over 176 sires, slaughtered at about 21 kg carcass weight, on average. Wool traits included yearling and adult records for wool weight, fiber diameter, fiber diameter variation, staple strength, scoured color, and visual scores for breech and body wrinkle. Whole carcass measures included HCW, dressing percentage (DP), and various measures of fat depth and eye muscle dimensions. Carcass components were obtained by dissection, and lean meat yield (LMY) was predicted. Heritability estimates for whole carcass measures ranged from 0.12 ± 0.08 to 0.35 ± 0.10 and ranged from 0.17 ± 0.10 to 0.46 ± 0.10 for carcass dissection traits, with no evidence of important genotype × environment interactions. Genetic correlations indicated that selection for increased clean wool weight will result in reduced carcass fat (−0.17 to −0.34) and DP (−0.48 ± 0.15), with little effect on carcass muscle. Selection for lower fiber diameter will reduce HCW (−0.48 ± 0.15) as well as carcass fat (0.14 to 0.27) and muscle (0.21 to 0.50). There were high genetic correlations between live animal measures of fat and muscle depth and the carcass traits (generally greater than 0.5 in size). Selection to increase HCW (and DP) will result in sheep with fewer wrinkles on the body (−0.57 ± 0.10) and barer breeches (−0.74 ± 0.12, favorable), with minor deterioration in scoured wool color (reduced brightness and increased yellowness). Selection for reduced fat will also result in sheep with fewer body wrinkles (−0.42 to −0.79). Increasing LMY in Merinos through selection would result in a large reduction in carcass fat and DP (−0.66 to −0.84), with a smaller increase in carcass muscle and some increase in wool weight and wrinkles. Although no major antagonisms are apparent between the wool and carcass traits, developing selection indexes for dualpurpose wool and meat breeding objectives will require accurate estimates of genetic parameters to ensure that unfavorable relationships are suitably considered. The findings will aid development of dual-purpose wool and meat breeding objectives. [ABSTRACT FROM AUTHOR]

Genetic correlations between 29 wool production and quality traits and live weight and ultrasound fat depth (FAT) and eye muscle depth (EMD) traits were estimated from the Information Nucleus (IN). The IN comprised 8 genetically linked flocks managed across a range of Australian sheep production environments. The data were from a maximum of 9,135 progeny born over 5 yr from 184 Merino sires and 4,614 Merino dams. The wool traits included records for yearling and adult fleece weight, fiber diameter (FD), staple length (SL), fiber diameter CV (FDCV), scoured color, and visual scores for breech and body wrinkle. We found high heritability for the major yearling wool production traits and some wool quality traits, whereas other wool quality traits, wool color, and visual traits were moderately heritable. The estimates of heritability for live weight generally increased with age as maternal effects declined. Estimates of heritability for the ultrasound traits were also higher when measured at yearling age rather than at postweaning age. The genetic correlations for fleece weight with live weights were positive (favorable) and moderate (approximately 0.5 ± 0.1), whereas those with FD were approximately 0.3 (unfavorable). The other wool traits had lower genetic correlations with the live weights. The genetic correlations for FAT and EMD with FD and SL were positive and low, with FDCV low to moderate negative, but variable with wool weight and negligible for the other wool traits. The genetic correlations for FAT and EMD with postweaning weight were positive and high (0.61 ± 0.18 to 0.75 ± 0.14) but were generally moderate with weights at other ages. Selection for increased live weight will result in a moderate correlated increase in wool weight as well as favorable reductions in breech cover and wrinkle, along with some unfavorable increases in FD and wool yellowness but little impact on other wool traits. The ultrasound meat traits, FAT and EMD, were highly positively genetically correlated (0.8), and selection to increase them would result in a small unfavorable correlated increase in FD, moderately favorable reductions in breech cover and wrinkle, but equivocal or negligible changes in other wool traits. The estimated parameters provide the basis for calculation of more accurate Australian Sheep Breeding Values and selection indexes that combine wool and meat objectives in Merino breeding programs. [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]

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]

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]

Lameness is a major problem in modern dairy husbandry and has welfare implications and other negative consequences. The behavior of dairy cows is influenced by lameness. Automated lameness detection can, among other methods, be based on day-to-day variation in animal behavior. Activity sensors that measure lying time, number of lying bouts, and other parameters were used to record behavior per cow per day. The objective of this research was to develop and validate a lameness detection model based on daily activity data. Besides the activity data, milking data and data from the computerized concentrate feeders were available as input data. Locomotion scores were available as reference data. Data from up to 100 cows collected at an experimental farm during 23 mo in 2010 and 2011 were available for model development. Behavior is cow-dependent, and therefore quadratic trend models were fitted with a dynamic linear model on-line per cow for 7 activity variables and 2 other variables (milk yield per day and concentrate leftovers per day). It is assumed that lameness develops gradually; therefore, a lameness alert was given when the linear trend in 2 or more of the 9 models differed significantly from zero in a direction that corresponded with lameness symptoms. The developed model was validated during the first 4 mo of 2012 with almost 100 cows on the same farm by generating lameness alerts each week. Performance on the model validation data set was comparable with performance on the model development data set. The overall sensitivity (percentage of detected lameness cases) was 85.5% combined with specificity (percentage of nonlame cow-days that were not alerted) of 88.8%. All variables contributed to this performance. These results indicate that automated lameness detection based on day-to-day variation in behavior is a useful tool for dairy management. [ABSTRACT FROM AUTHOR]

Summary: Addition of 10 mg prednisone daily to a methotrexate-based tight control strategy does not lead to bone loss in early rheumatoid arthritis (RA) patients receiving preventive treatment for osteoporosis. A small increase in lumbar bone mineral density (BMD) during the first year of treatment was recorded, regardless of use of glucocorticoids. Introduction: This study aims to describe effects on BMD of treatment according to EULAR guidelines with a methotrexate-based tight control strategy including 10 mg prednisone daily versus the same strategy without prednisone in early RA patients who received preventive therapy for osteoporosis. Methods: Early RA patients were included in the CAMERA-II trial: a randomized, placebo-controlled, double-blind 2-year trial, in which effects of addition of 10 mg prednisone daily to a methotrexate-based tight control strategy were studied. All patients received calcium, vitamin D and bisphosphonates. Disease activity was assessed every 4 weeks. Radiographs of hands and feet and dual-energy X-ray absorptiometry of lumbar spine and left hip were performed at baseline and after 1 and 2 years of treatment. Results: BMD increased significantly over time in both treatment groups at the lumbar spine with a mean of 2.6 % during the first year ( p < 0.001), but not at the hip; at none of the time points did BMD differ significantly between the prednisone and placebo group. Higher age and lower weight at baseline and higher disease activity scores during the trial, but not glucocorticoid therapy, were associated with lower BMD at both the lumbar spine and the hip in mixed-model analyses. Conclusion: Addition of 10 mg prednisone daily to a methotrexate-based tight control strategy does not lead to bone loss in early RA patients on bisphosphonates. A small increase in lumbar BMD during the first year of treatment was found, regardless of use of glucocorticoids. [ABSTRACT FROM AUTHOR]