Multibreed genomic prediction using multitrait genomic residual maximum likelihood and multitask Bayesian variable selection

Genomic prediction is applicable to individuals of different breeds. Empirical results to date, however, show limited benefits in using information on multiple breeds in the context of genomic prediction. We investigated a multitask Bayesian model, presented previously by others, implemented in a Bayesian stochastic search variable selection (BSSVS) model. This model allowed for evidence of quantitative trait loci (QTL) to be accumulated across breeds or for both QTL that segregate across breeds and breed-specific QTL. In both cases, single nucleotide polymorphism effects were estimated with information from a single breed. Other models considered were a single-trait and multitrait genomic residual maximum likelihood (GREML) model, with breeds considered as different traits, and a single-trait BSSVS model. All single-trait models were applied to each of the 2 breeds separately and to the pooled data of both breeds. The data used included a training data set of 6,278 Holstein and 722 Jersey bulls, as well as 374 Jersey validation bulls. All animals had genotypes for 474,773 single nucleotide polymorphisms after editing and phenotypes for milk, fat, and protein yields. Using the same training data, BSSVS consistently outperformed GREML. The multitask BSSVS, however, did not outperform single-trait BSSVS, which used pooled Holstein and Jersey data for training. Thus, the rigorous assumption that the traits are the same in both breeds yielded a slightly better prediction than a model that had to estimate the correlation between the breeds from the data. Adding the Holstein data significantly increased the accuracy of the single-trait GREML and BSSVS in predicting the Jerseys for milk and protein, in line with estimated correlations between the breeds of 0.66 and 0.47 for milk and protein yields, whereas only the BSSVS model significantly improved the accuracy for fat yield with an estimated correlation between breeds of only 0.05. The relatively high genetic correlations for milk and protein yields, and the superiority of the pooling strategy, is likely the result of the observed admixture between both breeds in our data. The Bayesian model was able to detect several QTL in Holsteins, which likely enabled it to outperform GREML. The inability of the multitask Bayesian models to outperform a simple pooling strategy may be explained by the fact that the pooling strategy assumes equal effects in both breeds; furthermore, this assumption may be valid for moderate- to large-sized QTL, which are important for multibreed genomic prediction.

Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

BACKGROUND

Dense SNP genotypes are often combined with complex trait phenotypes to map causal variants, study genetic architecture and provide genomic predictions for individuals with genotypes but no phenotype. A single method of analysis that jointly fits all genotypes in a Bayesian mixture model (BayesR) has been shown to competitively address all 3 purposes simultaneously. However, BayesR and other similar methods ignore prior biological knowledge and assume all genotypes are equally likely to affect the trait. While this assumption is reasonable for SNP array genotypes, it is less sensible if genotypes are whole-genome sequence variants which should include causal variants.

RESULTS

We introduce a new method (BayesRC) based on BayesR that incorporates prior biological information in the analysis by defining classes of variants likely to be enriched for causal mutations. The information can be derived from a range of sources, including variant annotation, candidate gene lists and known causal variants. This information is then incorporated objectively in the analysis based on evidence of enrichment in the data. We demonstrate the increased power of BayesRC compared to BayesR using real dairy cattle genotypes with simulated phenotypes. The genotypes were imputed whole-genome sequence variants in coding regions combined with dense SNP markers. BayesRC increased the power to detect causal variants and increased the accuracy of genomic prediction. The relative improvement for genomic prediction was most apparent in validation populations that were not closely related to the reference population. We also applied BayesRC to real milk production phenotypes in dairy cattle using independent biological priors from gene expression analyses. Although current biological knowledge of which genes and variants affect milk production is still very incomplete, our results suggest that the new BayesRC method was equal to or more powerful than BayesR for detecting candidate causal variants and for genomic prediction of milk traits.

CONCLUSIONS

BayesRC provides a novel and flexible approach to simultaneously improving the accuracy of QTL discovery and genomic prediction by taking advantage of prior biological knowledge. Approaches such as BayesRC will become increasing useful as biological knowledge accumulates regarding functional regions of the genome for a range of traits and species.

Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels

Achieving accurate genomic estimated breeding values for dairy cattle requires a very large reference population of genotyped and phenotyped individuals. Assembling such reference populations has been achieved for breeds such as Holstein, but is challenging for breeds with fewer individuals. An alternative is to use a multi-breed reference population, such that smaller breeds gain some advantage in accuracy of genomic estimated breeding values (GEBV) from information from larger breeds. However, this requires that marker-quantitative trait loci associations persist across breeds. Here, we assessed the gain in accuracy of GEBV in Jersey cattle as a result of using a combined Holstein and Jersey reference population, with either 39,745 or 624,213 single nucleotide polymorphism (SNP) markers. The surrogate used for accuracy was the correlation of GEBV with daughter trait deviations in a validation population. Two methods were used to predict breeding values, either a genomic BLUP (GBLUP_mod), or a new method, BayesR, which used a mixture of normal distributions as the prior for SNP effects, including one distribution that set SNP effects to zero. The GBLUP_mod method scaled both the genomic relationship matrix and the additive relationship matrix to a base at the time the breeds diverged, and regressed the genomic relationship matrix to account for sampling errors in estimating relationship coefficients due to a finite number of markers, before combining the 2 matrices. Although these modifications did result in less biased breeding values for Jerseys compared with an unmodified genomic relationship matrix, BayesR gave the highest accuracies of GEBV for the 3 traits investigated (milk yield, fat yield, and protein yield), with an average increase in accuracy compared with GBLUP_mod across the 3 traits of 0.05 for both Jerseys and Holsteins. The advantage was limited for either Jerseys or Holsteins in using 624,213 SNP rather than 39,745 SNP (0.01 for Holsteins and 0.03 for Jerseys, averaged across traits). Even this limited and nonsignificant advantage was only observed when BayesR was used. An alternative panel, which extracted the SNP in the transcribed part of the bovine genome from the 624,213 SNP panel (to give 58,532 SNP), performed better, with an increase in accuracy of 0.03 for Jerseys across traits. This panel captures much of the increased genomic content of the 624,213 SNP panel, with the advantage of a greatly reduced number of SNP effects to estimate. Taken together, using this panel, a combined breed reference and using BayesR rather than GBLUP_mod increased the accuracy of GEBV in Jerseys from 0.43 to 0.52, averaged across the 3 traits.

Accuracy of genomic predictions of residual feed intake and 250-day body weight in growing heifers using 625,000 single nucleotide polymorphism markers

Feed makes up a large proportion of variable costs in dairying. For this reason, selection for traits associated with feed conversion efficiency should lead to greater profitability of dairying. Residual feed intake (RFI) is the difference between actual and predicted feed intakes and is a useful selection criterion for greater feed efficiency. However, measuring individual feed intakes on a large scale is prohibitively expensive. A panel of DNA markers explaining genetic variation in this trait would enable cost-effective genomic selection for this trait. With the aim of enabling genomic selection for RFI, we used data from almost 2,000 heifers measured for growth rate and feed intake in Australia (AU) and New Zealand (NZ) genotyped for 625,000 single nucleotide polymorphism (SNP) markers. Substantial variation in RFI and 250-d body weight (BW250) was demonstrated. Heritabilities of RFI and BW250 estimated using genomic relationships among the heifers were 0.22 and 0.28 in AU heifers and 0.38 and 0.44 in NZ heifers, respectively. Genomic breeding values for RFI and BW250 were derived using genomic BLUP and 2 bayesian methods (BayesA, BayesMulti). The accuracies of genomic breeding values for RFI were evaluated using cross-validation. When 624,930 SNP were used to derive the prediction equation, the accuracies averaged 0.37 and 0.31 for RFI in AU and NZ validation data sets, respectively, and 0.40 and 0.25 for BW250 in AU and NZ, respectively. The greatest advantage of using the full 624,930 SNP over a reduced panel of 36,673 SNP (the widely used BovineSNP50 array) was when the reference population included only animals from either the AU or the NZ experiment. Finally, the bayesian methods were also used for quantitative trait loci detection. On chromosome 14 at around 25 Mb, several SNP closest to PLAG1 (a gene believed to affect stature in humans and cattle) had an effect on BW250 in both AU and NZ populations. In addition, 8 SNP with large effects on RFI were located on chromosome 14 at around 35.7 Mb. These SNP may be associated with the gene NCOA2, which has a role in controlling energy metabolism.

Validation of single nucleotide polymorphisms associated with milk production traits in dairy cattle

Single nucleotide polymorphism (SNP) associations with milk production traits found to be significant in different screening experiments, including SNP in genes hypothesized to be in gene pathways affecting milk production, were tested in a validation population to confirm their association. In total, 423 SNP were genotyped across 411 Holstein bulls, and their association with 6 milk production traits--Australian Selection Index (indicating the profitability of an animal's milk production), protein, fat, and milk yields, and protein and fat composition--were tested using single SNP regressions. Seventy-two SNP were significantly associated with one or more of the traits; their effects were in the same direction as in the screening experiment and therefore their association was considered validated. An over-representation of SNP (43 of the 423) on chromosome 20 was observed, including a SNP in the growth hormone receptor gene previously published as having an association with protein composition and protein and milk yields. The association with protein composition was confirmed in this experiment, but not the association with protein and milk yields. A multiple SNP regression analysis for all SNP on chromosome 20 was performed for all 6 traits, which revealed that this mutation was not significantly associated with any of the milk production traits and that at least 2 other quantitative trait loci were present on chromosome 20.

Short communication: Genomic selection using a multi-breed, across-country reference population

Three breeds (Fleckvieh, Holstein, and Jersey) were included in a reference population, separately and together, to assess the accuracy of prediction of genomic breeding values in single-breed validation populations. The accuracy of genomic selection was defined as the correlation between estimated breeding values, calculated using phenotypic data, and genomic breeding values. The Holstein and Jersey populations were from Australia, whereas the Fleckvieh population (dual-purpose Simmental) was from Austria and Germany. Both a BLUP with a multi-breed genomic relationship matrix (GBLUP) and a Bayesian method (BayesA) were used to derive the prediction equations. The hypothesis tested was that having a multi-breed reference population increased the accuracy of genomic selection. Minimal advantage existed of either GBLUP or BayesA multi-breed genomic evaluations over single-breed evaluations. However, when the goal was to predict genomic breeding values for a breed with no individuals in the reference population, using 2 other breeds in the reference was generally better than only 1 breed.

Accuracy of genotype imputation in sheep breeds

Although genomic selection offers the prospect of improving the rate of genetic gain in meat, wool and dairy sheep breeding programs, the key constraint is likely to be the cost of genotyping. Potentially, this constraint can be overcome by genotyping selection candidates for a low density (low cost) panel of SNPs with sparse genotype coverage, imputing a much higher density of SNP genotypes using a densely genotyped reference population. These imputed genotypes would then be used with a prediction equation to produce genomic estimated breeding values. In the future, it may also be desirable to impute very dense marker genotypes or even whole genome re-sequence data from moderate density SNP panels. Such a strategy could lead to an accurate prediction of genomic estimated breeding values across breeds, for example. We used genotypes from 48 640 (50K) SNPs genotyped in four sheep breeds to investigate both the accuracy of imputation of the 50K SNPs from low density SNP panels, as well as prospects for imputing very dense or whole genome re-sequence data from the 50K SNPs (by leaving out a small number of the 50K SNPs at random). Accuracy of imputation was low if the sparse panel had less than 5000 (5K) markers. Across breeds, it was clear that the accuracy of imputing from sparse marker panels to 50K was higher if the genetic diversity within a breed was lower, such that relationships among animals in that breed were higher. The accuracy of imputation from sparse genotypes to 50K genotypes was higher when the imputation was performed within breed rather than when pooling all the data, despite the fact that the pooled reference set was much larger. For Border Leicesters, Poll Dorsets and White Suffolks, 5K sparse genotypes were sufficient to impute 50K with 80% accuracy. For Merinos, the accuracy of imputing 50K from 5K was lower at 71%, despite a large number of animals with full genotypes (2215) being used as a reference. For all breeds, the relationship of individuals to the reference explained up to 64% of the variation in accuracy of imputation, demonstrating that accuracy of imputation can be increased if sires and other ancestors of the individuals to be imputed are included in the reference population. The accuracy of imputation could also be increased if pedigree information was available and was used in tracking inheritance of large chromosome segments within families. In our study, we only considered methods of imputation based on population-wide linkage disequilibrium (largely because the pedigree for some of the populations was incomplete). Finally, in the scenarios designed to mimic imputation of high density or whole genome re-sequence data from the 50K panel, the accuracy of imputation was much higher (86-96%). This is promising, suggesting that in silico genome re-sequencing is possible in sheep if a suitable pool of key ancestors is sequenced for each breed.

Calculation of lifetime net income per year (LTNI/year) of Australian Holstein cows to validate the Australian profit ranking of their sires. 1. Genetic analyses and prediction of LTNI/year for cows still in the herd

Birth, calving, milk yield, somatic cell count (SCC) and culling data of 274 000 AI-bred Holstein Friesian cows that were born between 1990 and 1998 from ~3400 herds were used to calculate lifetime net income per cow per year (LTNI/year). The main objective of this study was to identify an early measure of LTNI/year so that data of cows that are still in the herd can be used for predicting LTNI/year of cows. LTNI/year of cows that are still in the herd was predicted from net income per year (NI/year) assuming cows are culled at the end of each lactation and other traits that are measured early in the life of cows. LTNI/year is defined as NI up to the end of parity 9 or culling or death of cows per year of productive life. On average maximum LTNI/year was attained by cows that completed seven lactations and LTNI/year of cows was the lowest if cows completed only one lactation. For cows that at least survived to second lactation LTNI/year increased with their NI/year at the end of the first parity and their relative production compared with their herdmates but decreased with the increase in average lactation SCC. The heritability of LTNI/year was 0.09 and had a genetic and residual correlation of 0.62 and 0.71, respectively, with productive life. The genetic correlation of LTNI/year with first-parity lactation protein and fat yield was high (~0.7 or above) but near zero with calving interval and lactation SCC. The genetic correlations between LTNI/year and NI/year up to the end of parity 1, 2, 3 and 4 were 0.84, 0.96, 0.99 and 1.0, respectively. The corresponding residual correlations were 0.55, 0.89, 0.96 and 0.98. The genetic correlation between actual and predicted LTNI/year based only on cows that did not complete their lifetime (cows still in the herd) were 0.93, 0.96, 0.98 and 0.99 by the end of the first, second, third and fourth parity, respectively. The corresponding residual correlations were lower at 0.54, 0.70, 0.80 and 0.86, respectively. Estimates of genetic correlations between LTNI/year and NI/year based on calvings that happened 1 (1.0) to 4 (0.98) years earlier were unity. The corresponding residual correlations were slightly lower at 0.92 if the calvings that occurred 4 years ago and before were used, and near unity (0.98) if calvings that happened 1 year ago and before were used. In conclusion, the high genetic correlation (0.9 or above) between LTNI/year of cows and measures of lifetime NI/year based on cows that had a shorter opportunity to complete their lifetime suggests that genetic evaluation for LTNI/year is feasible even if some of the cows have incomplete lifetime data.

Calculation of lifetime net income per year (LTNI/year) of Australian Holstein cows to validate the Australian profit ranking of their sires. 2. Validation of the Australian profit ranking of sires and test for genotype by environment interaction based on LTNI/year

In Australia, the Australian Dairy Herd Improvement Scheme publishes the Australian profit ranking (APR), which is an economic index combining all economic traits. The APR is used to select sires that will breed the most profitable daughters. The objectives of this study were to test the predictive power of the APR by looking at the relationship between the APR of sires and lifetime net income per year (LTNI/year) of their future daughters and to test if this prediction was accurate in different types of herds. The importance of re-ranking was also tested by considering LTNI/year of cows in different herds as different traits and estimating the genetic correlation between LTNI/year in different herd types (herds differing in calving systems, region or production level). An additional objective was to test the value of individual trait Australian breeding values (ABV) of sires to predict LTNI/year of their future daughters. The results show that overall the relationship between the APR of bulls and the LTNI/year of their daughters was as expected. That is, the regression of daughter’s LTNI/year on sire’s APR equals 0.5 as expected because cows inherit half their genes from their sire. When LTNI/year of cows was regressed on sire’s APR separately for different herd types, the regression coefficients varied from 0.36 (low production herds) to 0.62 (high production herds). The genetic correlation for LTNI/year between herd types was always high indicating little re-ranking of sires. The lowest was 0.89 between LTNI/year of cows in seasonal and year-round calving systems as well as between Regions 3 (Gippsland and Tasmania) and Region 1 (New South Wales, Queensland, South Australia and Western Australia) herds. Thus, an APR calculated across all herd types will give a good ranking of bulls in any herd type. When LTNI/year of cows was regressed on individual sire ABV the regression coefficients were approximately half the economic weight for each trait as expected. Within seasonal calving and low production herds the regression on sire’s fertility ABV was higher than expected and the regression in year-round and high production herds was less than expected. In conclusion, over all herds the sire’s APR predicts LTNI/year of future daughters as expected. Owners of low production, seasonal calving herds will get slightly less benefit from 1 unit increase in APR than owners of high production, year-round calving herds and could perhaps benefit from placing additional emphasis on the fertility ABV when selecting sires.

Invited review: Genomic selection in dairy cattle: progress and challenges

A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or individual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.

Invited review: Genomic selection in dairy cattle: progress and challenges

A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or individual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.

Antiepileptic drug use increases rates of bone loss in older women: A prospective study

OBJECTIVE

To test the hypothesis that older women with antiepileptic drug (AED) use have increased rates of bone loss.

METHODS

AED use was ascertained and calcaneal and hip bone mineral density (BMD) measured in a cohort of 9,704 elderly community-dwelling women enrolled in the Study of Osteoporotic Fractures, and they were followed prospectively for changes in BMD. Current use of AED was assessed by interview, with verification of use from medication containers at baseline and follow-up examinations. Women were classified as continuous users, partial (intermittent) users, or nonusers. Rates of change in BMD were measured at the total hip and two subregions (average 4.4 years between examinations) and at the calcaneus (average 5.7 years between examinations).

RESULTS

After adjustment for confounders, the average rate of decline in total hip BMD steadily increased from -0.70%/year in nonusers to -0.87%/year in partial AED users to -1.16%/year in continuous AED users (p value for trend = 0.015). Higher rates of bone loss were also observed among continuous AED users at subregions of the hip and at the calcaneus. In particular, continuous phenytoin users had an adjusted 1.8-fold greater mean rate of loss at the calcaneus compared with nonusers of AED (-2.68 vs -1.46%/year; p < 0.001) and an adjusted 1.7-fold greater mean rate of loss at the total hip compared with nonusers of AED (-1.16 vs -0.70%/year; p = 0.069).

CONCLUSIONS

Continuous AED use in elderly women is associated with increased rates of bone loss at the calcaneus and hip. If unabated, the rate of hip bone loss among continuous AED users is sufficient to increase the risk of hip fracture by 29% over 5 years among women age 65 years and older.

Genetic parameters of fertility traits and their correlation with production, type, workability, liveweight, survival index, and cell count

First and second parity data on calving interval (CI, days), survival to next lactation (Surv, scored 1 or�0), calving to first service interval (CFS, days), 25-day first service non-return rate (FNRR, scored 1 or 0), and insemination or submission rate (InsemR, scored 1 or 0) of Holstein-Friesian cattle were analysed using a sire model to estimate genetic parameters. The estimated genetic parameters were used to obtain predicted transmitting ability (PTA) of sires for fertility traits and Surv, including 6-week pregnancy rate (6-w PR). PTA for 6-w PR was calculated based on an estimated heritability of 0.07 and genetic and environmental correlations with the other fertility traits and Surv. In addition, approximate genetic correlations of fertility traits and Surv with milk yield, type traits, workability (likability, milking speed, temperament), survival index (a measure of survival calculated from estimated breeding values on survival, likability, and type traits), bodyweight, and cell count were estimated. Heritability (h2) of fertility traits was 2–4% in the first parity and 1–2% in the second parity. Genetic correlations between fertility traits were generally higher in magnitude than environmental correlations, particularly in the first parity. The difference in PTA between the best and worst sires was high (21 days in CI and 21% in 6-w PR), showing the scope for selection. Approximate genetic correlations between fertility and most traits that are currently evaluated were low to moderate. Milk, protein and fat yield, body size, overall type, mammary system, udder texture, muzzle width, angularity, body depth, chest width, foot angle, and rear attachment width were unfavourably correlated (0.1–0.5) with most fertility traits. Fat and protein % were favourably correlated with both CI and 6-w PR (~0.2). Pin set was moderately favourably correlated (0.28) with 6-w PR. Surv was favourably (positively) correlated with temperament, likability, and survival index (~0.5). The wide variation in particular in CI and 6-w PR between bulls and the generally unfavourable approximate genetic correlations of fertility traits with most traits for which selection is currently practiced suggest that genetic evaluation for fertility should be introduced.

Estimates of genetic parameters for daily somatic cell count of Australian dairy cattle

Genetic parameters for daily somatic cell counts (SCC) of the first three parities were estimated for Australian Dairy Cattle. Most of the data analyses were carried out with a sire random regression model. The estimates were compared with those from conventional ten-trait analyses and animal models. In the first-parity estimates of heritabilities (h2) were low (0.04 to 0.05) at the beginning of the lactation and higher (0.11 to 0.13) at the end. The average h2 estimated from random regression sire model, random regression animal model and conventional multitrait sire model were 0.09, 0.09, and 0.08, respectively, in the first lactation. The average h2 were 0.09 and 0.11 in the second and third parities, respectively. Genetic correlations between daily log(e) SCC within parity were high for adjacent tests (nearly 1) and low (as low as 0.30) between the beginning and the end of the lactation. Generally, the genetic correlations between parities depend on how far apart they are and on whether they are on the same day in any two parities. Across parities, on average, genetic correlations between parities 1 and 3 were the lowest and those between 1 and 2 intermediate, while those between 2 and 3 were the highest. The estimated environmental correlations were lower than the genetic correlations, but the trends were generally similar. Differences in genetic parameter estimates due to model were small, except for some genetic correlations. The high residual error variances, the low h2, and the inconsistency in genetic correlations that were observed particularly at the beginning of the first lactation suggest that log(e) SCC early in the first lactation may be related to a spike in SCC as result of infection and (or) onset of lactation while SCC later in lactation represents a sustained response to infection. Accounting for the variation in heritabilities and correlations should improve the accuracy of genetic evaluations for SCC based on test day records.

Social and environmental predictors of maternal depression in current and recent welfare recipients

Depression is highly prevalent in welfare recipients, and is associated with failure to move from welfare to work. This paper examines the relationship between social and environmental factors in a large, community-based sample of mothers who currently or recently received welfare benefits. Specific and modifiable risk factors related to poverty, gender, and race were found to predict major depression beyond traditional risk factors. Research and practice implications are discussed.

An evaluation of the impact of long-range climate forecasting on the physical and financial performance of wool-producing enterprises in Victoria

Improved climate forecasting has the potential to increase the ability of farm managers to cope with a variable climate. In this study a simulation model of a breeding ewe flock was used to make a preliminary assessment of the value of climate forecasting for wool-producing enterprises in Victoria. Stocking and selling policies were modified in response to long-range forecasts of weather conditions. The effects on pasture cover, sheep welfare and financial returns were compared with those of a traditional management policy for a period of 25 years. These comparisons were made at two locations, Hamilton and Rutherglen, and at two stocking rates. The effects of different levels of accuracy of the weather forecast on the value of the changes in stocking and selling policies were also evaluated. Altering the stocking and selling policies using an accurate forecast of seasonal conditions resulted in a reduction in the death rate of adult ewes and their progeny. Timely action when adverse conditions were imminent resulted in an increase in both pasture cover during autumn and winter and minimum liveweight of the sheep. Gross returns were increased on average by more than 5%. Much of this increase was contributed by higher wool returns associated with the increase in size of the flock during favourable conditions. Expenditure on sheep purchases was lower for the traditionally managed farms; however, knowledge of forthcoming conditions did allow stock numbers to be reduced before pasture reserves were depleted in poor seasons which in turn reduced the requirement for supplementary feed. The total cash costs tended to be lower on the traditionally managed farm, but this difference was not significant. Both the cash operating surplus and net cash income were significantly increased by altering stocking and selling policies using an accurate forecast of seasonal conditions at Hamilton, but, although the same trends were evident, the effect of using the forecast at Rutherglen was not significant. Where the forecast was accurate in only 8 years in 10 or 6 years in 10, the benefits of altering the stocking and selling policies were reduced, but even at the lower level of accuracy the average cash operating surplus for the 25 years of the analysis was higher than that achieved using the traditional management regime. However, in individual years, inappropriate policies adopted due to an incorrect forecast resulted in reductions in financial returns of up to 64%. Accurate forecasts can improve land care and animal welfare by changing pasture and animal management, particularly by reducing stock numbers. However, since the profitability of sheep enterprises in Victoria is highly dependent on the choice of stocking rate, recommendations to reduce stock numbers without considering the financial viability of sheep enterprises may go unheeded. Hence, in the short-term at least, it can be difficult to achieve improvements in land care and animal welfare while at the same time maintaining profitability. This study indicated that the financial benefits for wool producers of reliable seasonal outlooks in southern Australia are probably substantially less than generally anticipated, at least for the strategies investigated. Furthermore, the accuracy of seasonal forecasting in southern Australia is such that the benefits from correct forecasts can be partly offset in other years from decisions which have been made on the basis of incorrect forecasts. The study also highlighted a number of important issues that need to be considered in evaluating climate forecasts.

The adolescent-to-adult transition: discouragement among jobless black youth

Although many youth experience difficulty in the school-to-work transition, increasing numbers of black youth face more chronic difficulties that have far-reaching developmental implications. This chapter examines both objective and subjective aspects of chronic joblessness among black youth, with emphasis on gender differences in discouragement over job searches and related developmental issues. A life cycle approach to role strain and adaptation provides a coherent framework to guide theoretical inquiry into jobless black youth in America. Role-strain adaptation processes have special appeal because they provide a coherent conceptual base for studies on the nature, antecedents, and consequences of chronic difficulty in job search. Two basic notions in the proposed role-strain adaptation approach to joblessness among black youth are that discouragement in the job search and self-blame increase the risk of maladaptive responses to objective barriers and that objective and subjective cultural resources facilitate adaptive response patterns. The role-strain adaptation paradigm not only provides a parsimonious framework but also builds on a diverse theoretical and empirical literature (Barnett, Beiner, and Baruch, 1987; Bowman, 1989; Goode, 1960; Kahn and others, 1964; Merton, 1968; Pearlin, 1983; Sarbin and Allen, 1968). Role-strain adaptation models allow one to go beyond past studies on black youth, which have primarily been descriptive rather than theoretical and predictive. In addition to the foregoing benefits, a major virtue of the life cycle approach to job search strain processes is its explanatory power throughout the life span (Allen and Vande Vliert, 1981; Erikson, 1980; George, 1980; Levinson and others, 1978). A life cycle framework avoids common misconceptions that occur with a narrow focus on job search strain among black youth that fails to consider the continuity in chronic role-strain adaptation processes. In a broader life-span framework, the interrelated concepts of human development and cultural adaptation have unique explanatory power. Elsewhere (Bowman, 1989) I have noted that to develop means to grow out of, to evolve from--where experiences at one life stage not only follow but emerge directly from preceding life experiences. The related concept of adaptation involves a continuing process of incorporating past experiences into new patterns to strategically meet the challenge of changing life demands without undue compromise. For black youth faced with chronic joblessness, effective adaptation may require preserving core cultural patterns from prior generations, while also transforming such core patterns into new strategies to cope with job search barriers in postindustrial America.(ABSTRACT TRUNCATED AT 400 WORDS)

Economics of feeding energy-based supplements to grazing ewes before mating in order to increase the reproduction rate of a wool-producing flock

The financial wisdom of feeding energy-based supplements to ewes before mating to increase fecundity was evaluated using mathematical models of sheep production systems. It was concluded that, for a wool-producing enterprise in southern Australia, feeding supplements to ewes pre-mating is likely to be highly unprofitable. This is partly because relatively few ewes would have extra ova and also because multiple embryos and lambs have a lower probability of survival than single embryos and lambs. Further more, the extra lambs reared would be associated with an increase in grazing pressure which would necessitate a reduction in either stocking rate or in ewe liveweight at mating and thus fecundity in the subsequent season.

Stress, coping, and Black mental health: preliminary findings from a national study

Despite the fact that blacks are disproportionately exposed to social conditions considered to be antecedents of psychiatric disorder, epidemiologic studies have not conclusively demonstrated that blacks exhibit higher rates of mental illness than whites. The present paper employed a research approach which considered not only rates of psychological distress, but also the stressors that blacks face and the various coping strategies used to adapt to those stressors. The data were obtained from the National Survey of Black Americans, the first study of a national probability sample of the adult black population. The information on mental health and coping was collected within the context of a single stressful personal problem. The analysis indicates that prayer was an extremely important coping response used by blacks especially among those making less than $10,000, above the age of 55 and women. The informal social network was used quite extensively as a means of coping with problems. This was true for all sociodemographic groups studied. The young (18-34) were less likely than those age 35 and above to seek professional help, while women were more likely than men to seek formal assistance. Income was not related to professional help seeking. With respect to the use of specific professional help sources, hospital emergency rooms, private physicians and ministers were used most frequently. The implications of these findings for research on black mental health and primary prevention are discussed.

Stress, coping, and Black mental health: preliminary findings from a national study

Despite the fact that blacks are disproportionately exposed to social conditions considered to be antecedents of psychiatric disorder, epidemiologic studies have not conclusively demonstrated that blacks exhibit higher rates of mental illness than whites. The present paper employed a research approach which considered not only rates of psychological distress, but also the stressors that blacks face and the various coping strategies used to adapt to those stressors. The data were obtained from the National Survey of Black Americans, the first study of a national probability sample of the adult black population. The information on mental health and coping was collected within the context of a single stressful personal problem. The analysis indicates that prayer was an extremely important coping response used by blacks especially among those making less than $10,000, above the age of 55 and women. The informal social network was used quite extensively as a means of coping with problems. This was true for all sociodemographic groups studied. The young (18-34) were less likely than those age 35 and above to seek professional help, while women were more likely than men to seek formal assistance. Income was not related to professional help seeking. With respect to the use of specific professional help sources, hospital emergency rooms, private physicians and ministers were used most frequently. The implications of these findings for research on black mental health and primary prevention are discussed.