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Recovery housing provides substance-free living environments that use peer-support to empower individuals in recovery from substance use disorder. This study estimated the total revenue of the recovery housing industry from recovery houses, nationwide.Using survey data collected in June and July of 2020, we calculate the total revenue of the recovery housing industry and determine the share of revenue that comes from different sources for rural and nonrural houses.We find that individual recovery houses operate with an annual revenue of $250,000 and the whole industry accounts for $4.5 billion annually. COVID-19 has reduced industry revenue by 4%. Rural and nonrural houses differ significantly in their sources of revenue.Our results suggest that COVID-19 reduced the size of the recovery housing industry. Houses in nonrural regions may need more federal support due to the relatively high reliance on resident fees, which may be unreliable during COVID-19.

Although new cases of monkeypox have been expected in the Western Pacific Region (WPR) since the virus emerged in Europe earlier this year, there have been only a few reported cases across the WPR (New Zealand 2, Singapore 6, South Korea 1, Taiwan 2), other than a limited number of cases (compared to numbers of cases seen elsewhere in the world) in Australia (33), as of July 15, 2022. In our short communication, we highlight two key reasons for this: i) international travel has still not fully resumed in the WPR following the COVID-19 pandemic, and ii) local public health measures to counter the spread of COVID-19 have not been completely relaxed. We provide supporting evidence for both of these reasons.\ud \ud

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting millions of people worldwide and imposing heavy economic burdens to societies. Currently, only symptomatic treatments are available for patients, but there is ongoing research on potential therapies that can modify the course of disease. The main objective of this work is to identify and explore the challenges surrounding decision modeling for economic evaluation of interventions for AD.This article discusses the challenges in modeling the natural history of disease, particularly regarding the selection of disease progression and outcome measures, the inclusion of biomarker status in models, and the approach to model mortality. Challenges stemming from the use of long-term assumptions regarding treatment effects and the need for real-world evidence to fill data gaps are discussed. Lastly, the overwhelming economic impact of disease and the challenges in estimating these costs for modeling are addressed.Value assessment frameworks need to be reconsidered in order to demonstrate the full benefit of new disease-modifying therapies spanning beyond the scope of health systems. Data collection efforts that expand the evidence base, upon which economic models are based, will reduce the uncertainties surrounding the long-term outcomes of interventions in AD.

Aims: To facilitate regulatory learning, we evaluated similarities and differences in evidence requirements between regulatory and health technology assessment (HTA) bodies of Alzheimer’s disease (AD) approved products. Methods: The European marketing authorisation application dossiers and European public assessment reports (EPARs) of the licensed AD drugs were screened to identify the phase III randomised controlled trials (RCTs) and outcomes used. We also screened the assessment reports of the National Institute of Health and Care Excellence (NICE, England) and the National Health Care Institute (ZiN, the Netherlands) to identify the studies and outcomes used in HTA assessments. Results: The applications dossiers of donepezil, galantamine, rivastigmine, and memantine contained 16 phase III RCTs in total. These trials were also included in HTA assessments except that NICE excluded studies that were not published (n=2) or trials that included patients with other types of dementia (n=3). In the regulatory assessments the focus was on cognitive and global outcomes, and to some extent on function. In the HTA assessment of the clinical effectiveness other domains were also covered including: function, behaviour and mood, and, occasionally, quality of life. In the economic analyses of NICE the domains cognition, function, and quality of life were included. Conclusion: There was a large overlap in inclusion of trials in regulatory and HTA assessments, although the focus on specific outcomes slightly differed. Understanding the methods and perceptions of both authorities can stimulate regulatory and HTA cross-talk and further alignment, and therefore more rapid patient access to new treatments.

I review my scientific career in terms of eight areas and 16 papers. The first two areas are associated with childhood. The other six are associated with residual maximum likelihood (REML), canonical transformation, inbreeding in selected populations, average information residual maximum likelihood (AIREML), the computer program ASReml and sampling-based estimation.

Insecticide-resistant clones of the peach-potato aphid, Myzus persicae (Sulzer), have previously been shown to have a reduced response to aphid alarm pheromone compared to susceptible ones. The resulting vulnerability of susceptible and resistant aphids to attack by the primary endoparasitoid, Diaeretiella rapae (McIntosh), was investigated across three spatial scales. These scales ranged from aphids confined on individual leaves exposed to single female parasitoids, to aphids on groups of whole plants exposed to several parasitoids. In all experiments, significantly fewer aphids from insecticide-susceptible clones became parasitised compared to insecticide-resistant aphids. Investigations of aphid movement showed at the largest spatial scale that more susceptible aphids than resistant aphids moved from their inoculation leaves to other leaves on the same plant after exposure to parasitoids. The findings imply that parasitoids, and possibly other natural enemies, can influence the evolution and dynamics of insecticide resistance through pleiotropic effects of resistance genes on important behavioural traits.

New maternal breeding values have been developed for use in UK beef evaluations. To undertake multitrait BLUP evaluations, it is necessary to have a full covariance matrix. This study outlines the approach taken to construct the full covariance matrices for the four beef breeds that most widely contribute to suckler beef cows in the United Kingdom. The maternal traits investigated were age at first calving, calving interval, lifespan, mature cow weight, 200-d weight, and calving difficulty. Three terminal sire traits (weight at 400 d, ultrasonic fat depth, and muscle score) were included to estimate covariances between the new and existing traits. A sire-maternal-grandsire model was used for the estimation procedure in a series of bivariate and multivariate models. A weighted bending procedure was employed to construct positive definite covariance matrices. Parameter estimates broadly agreed with literature values, although for some traits, literature information was very scarce. Some differences between parameters for different breeds were evident.

International audience; Model selection is an essential issue in longitudinal data analysis since many different models have been proposed to fit the covariance structure. The likelihood criterion is commonly used and allows to compare the fit of alternative models. Its value does not reflect, however, the potential improvement that can still be reached in fitting the data unless a reference model with the actual covariance structure is available. The score test approach does not require the knowledge of a reference model, and the score statistic has a meaningful interpretation in itself as a goodness-of-fit measure. The aim of this paper was to show how the score statistic may be separated into the genetic and environmental parts, which is difficult with the likelihood criterion, and how it can be used to check parametric assumptions made on variance and correlation parameters. Selection of models for genetic analysis was applied to a dairy cattle example for milk production.

Previous studies have noted that the estimated positions of a large proportion of mapped quantitative trait loci (QTLs) coincide with marker locations and have suggested that this indicates a bias in the mapping methodology. In this study we predict the expected proportion of QTLs with positions estimated to be at the location of a marker and further examine the problem using simulated data. The results show that the higher proportion of putative QTLs estimated to be at marker positions compared with non-marker positions is an expected consequence of the estimation methods. The study initially focused on a single interval with no QTLs and was extended to include multiple intervals and QTLs of large effect. Further, the study demonstrated that the larger proportion of estimated QTL positions at the location of markers was not unique to linear regression mapping. Maximum likelihood produced similar results, although the accumulation of positional estimates at outermost markers was reduced when regions outside the linkage group were also considered. The bias towards marker positions is greatest under the null hypothesis of no QTLs or when QTL effects are small. This study discusses the impact the findings could have on the calculation of thresholds and confidence intervals produced by bootstrap methods.

Twenty-one clones of the peach-potato aphid, Myzus persicae (Sulzer), carrying various combinations of known mechanisms of insecticide resistance were assessed for their response to the new pyridine azomethine compound, pymetrozine, in leaf-dip bioassays. Pymetrozine was also applied as a foliar spray to populations of four different UK M persicae clones on potato plants in field-simulator chambers. Neither study showed any evidence of cross-resistance to this compound. Pymetrozine, used in conjunction with other effective aphicides, such as pirimicarb and imidacloprid, can therefore play an important role in insecticide resistance-management strategies for M persicae.

The efficiency of various trialling systems for wheat variety evaluation in New South Wales (NSW) is considered. This involved the estimation of the variance components due to genotype, genotype-by-year, genotype-by-location and genotype-by-year-by-location. It is shown that there is a significant reduction in the magnitude of these variance components by the inclusion of the interaction of genotype maturity, winter habit and aluminium tolerance with environment.

Cet article traite de l'estimation des parametres genetiques dans un modele individuel a 2 variables. On montre que, dans beaucoup de situations, le temps de calcul peut etre diminue en standardisant les caracteres et en les rendant independants par une transformation, ce qui permet une maximisation sur un espace de parametres de moindre dimension. Un exemple numerique particulier montre que le temps de calcul est divise par 8. Les avantages des differents modeles transformes sont presentes

Summary Multiple-trait and random regression models have multiplied the number of equations needed for the estimation of variance components. To avoid inversion or decomposition of a large coefficient matrix, we propose estimation of variance components by Monte Carlo expectation maximization restricted maximum likelihood (MC EM REML) for multiple-trait linear mixed models. Implementation is based on full-model sampling for calculating the prediction error variances required for EM REML. Performance of the analytical and the MC EM REML algorithm was compared using a simulated and a field data set. For field data, results from both algorithms corresponded well even with one MC sample within an MC EM REML round. The magnitude of the standard errors of estimated prediction error variances depended on the formula used to calculate them and on the MC sample size within an MC EM REML round. Sampling variation in MC EM REML did not impair the convergence behaviour of the solutions compared with analytical EM REML analysis. A convergence criterion that takes into account the sampling variation was developed to monitor convergence for the MC EM REML algorithm. For the field data set, MC EM REML proved far superior to analytical EM REML both in computing time and in memory need.

SummaryMaximum likelihood estimation methods with an individual animal model were used to analyse a bi-directional selection experiment, with control, for cannon bone length in Scottish Blackface sheep. A method is described for partitioning the likelihood to allow within- and between-line estimates of genetic variance. It is concluded that both sources of information made substantial contributions to the precision of the base population heritability estimate. The implications for different experimental designs and varying heritability are discussed.

The use of exact and approximate algorithms to calculate prediction error variances using sparse matrix methods are demonstrated for an individual animal effect including maternal effects. One exact algorithm is substantially faster than two others. An approximation of the best exact method gave an acceptable level of reliabilities and reduced the computation by a factor of approximately fifty compared with the exact computation and is routine in national beef evaluation in Britain.

SummaryFor a population undergoing mass selection, derived from an unselected base population in generation zero, the expected long-term contribution to the population of an ancestor from generation 1 was shown to be equal to that expected during random selection multiplied by (where is one half the breeding value of the ancestor for the trait under selection standardized by the phenotypic standard deviation, i the intensity of selection, and is the competitiveness which is defined by the heritability in generation 2 and k the variance reduction coefficient). It was shown that the rate of inbreeding (ΔF) could be partitioned into three components arising from expected contributions, sampling errors and sampling covariances respectively. Using this result ΔF was derived and shown to be dominated by terms that describe ΔF by variance of family size in a single generation plus a term that accounts for the expected proliferation of lines over generations from superior ancestors in generation 1. The basic prediction of ΔF was given bywhere M and F are the numbers of breeding males and females, T the number of offspring of each sex, ρm and ρt are correlations among half-sibs in generation 2 for males and females respectively, and K is a function of the intensity and competitiveness.

Estimation of genetic variance in populations under selection involves assumptions on base animals. Base animals are often considered unselected and it also has been proposed to treat selected base animals as fixed. The consequences of assumptions on base animals in the estimation of genetic variance in selected populations are not fully understood. Variance decompositions are introduced for simple designs to quantify the differences between models that treat base animals in different ways. Independent contrasts were constructed and REML estimates of variance components were compared for different designs and selection rules. The method shows how selection is accounted for in a complete model and why estimation of variance components can become biased when base animals are treated as fixed.

Lateral skull cephalograms from 50 patients who subsequently had surgical correction of their Class III malocclusion were analysed using a complete linkage cluster analysis based on skull shape. Five subgroups Were identified and are described. All subjects had a degree of mandibular prognathism while only 14 per cent had maxillary retrognathism. An increased lower face height was found in 58 per cent.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

peer-reviewed Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sampling can be used to calculate approximations of the prediction error variance, which converge to the true values if enough samples are used. However, in practical situations the number of samples, which are computationally feasible, is limited. The objective of this study was to compare the convergence rate of different formulations of the prediction error variance calculated using Monte Carlo sampling. Four of these formulations were published, four were corresponding alternative versions, and two were derived as part of this study. The different formulations had different convergence rates and these were shown to depend on the number of samples and on the level of prediction error variance. Four formulations were competitive and these made use of information on either the variance of the estimated breeding value and on the variance of the true breeding value minus the estimated breeding value or on the covariance between the true and estimated breeding values. The authors acknowledge the Irish Cattle Breeding Federation for providing funding and data. Robin Thompson acknowledges the support of the Lawes Agricultural Trust.

This paper gives a short review of the development of genetic parameter estimation over the last 40 years. The need to analyse genetic processes in both animal selection experiments and animal breeding improvement programmes motivated the majority of this work. The usage of animal model in conjunction with residual maximum likelihood (REML) techniques for mixed models has revolutionized the methods. These methods to estimate quantitative genetic parameters have recently been advocated for use in evolutionary studies of natural populations. Therefore, it is perhaps timely to discuss the development of REML methods and their application to the analysis of artificial selection experiments and breeding programmes in animals. This should give extra insight into the methods and hopefully lead to synergy between both the areas.

In selected populations, families superior for the selected trait are likely to contribute more offspring to the next generation than inferior families and, as a consequence, the rate of inbreeding is likely to be higher in selected populations than in randomly mated populations of the same structure. Methods to predict rates of inbreeding in selected populations are discussed. The method of Burrows based on probabilities of coselection is reappraised in conjunction with the transition matrix method of Woolliams. The method of Latter based on variances and covariances of family size is also examined. These methods are one-generation approaches in the sense that they only account for selective advantage over a single generation, from parents to offspring. Two-generation methods are developed that account for selective advantage over two generations, from grandparent to grandoffspring as well as from parent to offspring. Predictions are compared to results from simulation. The best one-generation method was found to underpredict rates of inbreeding by 10-25%, and the two-generation methods were found to underpredict rates of inbreeding by 9-18%.

L-splines are a large family of smoothing splines defined in terms of a linear differential operator. This article develops L-splines within the context of linear mixed models and uses the resulting mixed model L-spline to analyze longitudinal data from a grassland experiment. In the spirit of time-series analysis, a periodic mixed model L-spline is developed, which partitions data into a smooth periodic component plus smooth long-term trend.

An extension of interval mapping is presented that incorporates all intervals on the linkage map simultaneously. The approach uses a working model in which the sizes of putative QTL for all intervals across the genome are random effects. An outlier detection method is used to screen for possible QTL. Selected QTL are subsequently fitted as fixed effects. This screening and selection approach is repeated until the variance component for QTL sizes is not statistically significant. A comprehensive simulation study is conducted in which map uncertainty is included. The proposed method is shown to be superior to composite interval mapping in terms of power of detection of QTL. There is an increase in the rate of false positive QTL detected when using the new approach, but this rate decreases as the population size increases. The new approach is much simpler computationally. The analysis of flour milling yield in a doubled haploid population illustrates the improved power of detection of QTL using the approach, and also shows how vital it is to allow for sources of non-genetic variation in the analysis.

Response to the alarm pheromone, (E)-β-farnesene, produced by many species of aphids, was assessed in laboratory bioassays using an aphid pest,Myzus persicae(Sulzer), and its primary endoparasitoid,Diaeretiella rapae(McIntosh). This was done in three separate studies, the first investigating responses of a large number ofM. persicaeclones carrying different combinations of metabolic (carboxylesterase) and target site (kdr) insecticide resistance mechanisms, and the other two investigating the responses of young virgin female adult parasitoids. InM. persicae, both insecticide resistance mechanisms were associated with reduced repellence suggesting that each has a pleiotropic effect on aphid behaviour. In contrast,D. rapaefemales were attracted to the alarm pheromone source. The implications of this apparent fitness trade-off for the evolution and dynamics of insecticide resistance, and the potential for using beneficial insects to combat resistance development are discussed.

Laboratory bioassays applying the neonicotinoid insecticides imidacloprid, acetamiprid and nitenpyram against clones of the peach-potato aphid Myzus persicae (Sulzer) demonstrated that these compounds effectively circumvent the known carboxylesterase, modified acetylcholinesterase (MACE) and knock-down (kdr) insecticide resistance mechanisms in this species. However, some clones showed cross-tolerance (up to 18-fold) of these compounds relative to susceptible standards. A survey assessing the frequency of neonicotinoid tolerance in M persicae in the UK, based on samples collected from the field and glasshouses between 199711 and 2000, showed that such tolerance is still rare. Experiments on neonicotinoid-susceptible and -tolerant populations of M persicae under simulated field conditions in the laboratory showed that, although the latter were well controlled by imidacloprid applied at recommended application rates, they were more likely to survive and reproduce when this compound was applied at lower concentrations. Such conditions are probably periodically present in imidacloprid-treated field and glasshouse crops. Selection favouring tolerant forms of M persicae could lead to increases in their frequency and the evolution of more potent resistance to neonicotinoids. (C) 2003 Society of Chemical Industry.

Published information on relative performance of beef breed crosses was used to derive combined estimates of purebred breed values for predominant temperate beef breeds. The sources of information were largely from the United States, Canada, and New Zealand, although some European estimates were also included. Emphasis was on maternal traits of potential economic importance to the suckler beef production system, but some postweaning traits were also considered. The estimates were taken from comparison studies undertaken in the 1970s, 1980s and 1990s, each with representative samples of beef breeds used in temperate agriculture. Weighting factors for breed-cross estimates were derived using the number of sires and offspring that contributed to that estimate. These weights were then used in a weighted multiple regression analysis to obtain single purebred breed effects. Both direct additive and maternal additive genetic effects were estimated for preweaning traits. Important genetic differences between the breeds were shown for many of the traits. Significant regression coefficients were estimated for the effect of mature weight on calving ease, both maternal and direct additive genetic, survival to weaning direct, and birth weight direct. The breeds with greater mature weight were found to have greater maternal genetic effects for calving ease but negative direct genetic effects on calving ease. A negative effect of mature weight on the direct genetic effect of survival to weaning was observed. A cluster analysis was done using 17 breeds for which information existed on nine maternal traits. Regression was used to predict breed-cross-specific heterosis using genetic distance. Only five traits, birth weight, survival to weaning, cow fertility, and preweaning and postweaning growth rate had enough breed-cross-specific heterosis estimates to develop a prediction model. The breed biological values estimated provide a basis to predict the biological value of crossbred suckler cows and their offspring.

The recommendation of new plant varieties for commercial use requires reliable and accurate predictions of the average yield of each variety across a range of target environments and knowledge of important interactions with the environment. This information is obtained from series of plant variety trials, also known as multi-environment trials (MET). Cullis, Gogel, Verbyla, and Thompson (1998) presented a spatial mixed model approach for the analysis of MET data. In this paper we extend the analysis to include multiplicative models for the variety effects in each environment. The multiplicative model corresponds to that used in the multivariate technique of factor analysis. It allows a separate genetic variance for each environment and provides a parsimonious and interpretable model for the genetic covariances between environments. The model can be regarded as a random effects analogue of AMMI (additive main effects and multiplicative interactions). We illustrate the method using a large set of MET data from a South Australian barley breeding program.

The hydrolysis product [Ga(2)(C(3)H(7))(4)(OH)(2)].C(14)H(32)N(4), derived from the tetrakis(triisopropylgallium)-1,4,8, 11-tetramethyl-1,4,8,11-tetraazacyclotetradecane (1/1) adduct, consists of a centrosymmetric [(i)Pr(2)Ga(mgr;-OH)](2) unit hydrogen bonded through the hydroxyl group to a nitrogen on an adjacent centrosymmetric 1,4,8,11-tetramethyl-1,4,8, 11-tetraazacyclotetradecane molecule, resulting in the generation of a molecular chain through the crystal.

Termites were sampled using randomized soil pits in 64 cropping plots, each 25 x 25 m, forming an experimental agrisilvicultural system in both a 6- and an 18-year-oldTerminalia ivorensisplantation, in which canopy cover, crop, cropping system and land preparation were the principal treatment variables. The treatments were established in April 1995 and sampling was carried out in November 1995, February 1996 and July 1996. A total of 82 termite species were found, of which 67 were soil-feeders. Overall termite abundance and the abundance of soil-feeders increased between November 1995 and July 1996, reaching a mean of nearly 6000 m-2. Pooling termite data from these sampling dates, in the old plantation, the high canopy cover treatment (192 stems ha-1) had a greater abundance of termites, compared with the low canopy cover treatment (64 stems ha-1) and this effect was independent of crop type (plantain or cocoyam), cropping system (single stands or mixed crops) and land preparation (mulch retained or burned, plantain only). The young tree plantation (same tree densities as in the old plantation) showed no significant difference in termite abundance between high and low canopy (levels of tree foliage) densities, though the high canopy sheltered a greater number of termites. Analysis of covariance showed that crop yield (both plantain and cocoyam) was not directly linked to the abundance of all termite populations, but that the cocoyam yield was positively correlated with the abundance of soil-feeding termites (the majority in the assemblage) in the young plantation. This may be due to the beneficial conditioning of soil resulting from the foraging and construction activities of soil-feeders.

Zusammenfassung Verwendung von prior-Information bei Erstellung von Selektionsindices Selektionsindices aus geschatzten statt aus tatsachlichen genetischen Parametern zeigen uberschatzte Genaugkeit, die geringer ist als bei optimalen Indices. Methoden zu bending und Schranken von Selektionsindices wurden fur Situationen ausgearbeitet, wo genetische Parameter aus Nachkommen-Vatertierregressionen geschatzt worden sind. Zur uberprufung von Faktoren, inklusive bending und Schranken, die die scheinbare und tatsachliche Genauigkeit von Indices aus Nachkommen-Vatertier und aus Vatertiervarianzkomponenten beeinflussen, wurde Simulation verwendet. Der Unterschied im Selektionserfolg zwischen idealem und Index aus geschatzten genetischen Parametern nimmt mit der Zahl berucksichtigten Merkmale zu, wobei dieser Verlust relativ wenig von anderen Parametern abhangt. Der Unterschied zwischen geschatztem und tatsachlichem Erfolg ist etwa das doppelte des Genauigkeitsverlustes. Eine Approximation der Indexgenauigkeit mittels Taylor Serie war ungenau fur kleine Versuche, tendierte zu uberschatzung der Genauigkeit fur zwei und zu Unterschatzung fur 8 Merkmale. Von einem Bayesian Gesichtspunkt ist bending aquivalent der Annahme, das die genetische Kovari-anzmatrix proportional der phanotypischen sei, wobei es am wirkungsvollsten bei Zutreffen dieser Annahme war. Es war wirkungsvoller zur Steigerung der Genauigkeit als hinsichtlich ihrer uberschatzung. Schranken aller Indexgewichteum dasselbe Ausmas verandert nicht die Genauigkeit des Index, eliminiert aber deren uberschatzung. Verwendung von bent und geschrankte Schatzung bei unterschiedlicher Information wird diskutiert.

A fully efficient approach for the analysis of multi-environment early stage variety trials is considered that accommodates a general spatial covariance structure for the errors of each trial. The analysis simultaneously produces best linear unbiased predictors of the genotype and genotype by environment interaction effects and residual maximum likelihood estimates of the spatial parameters and variance components. Two motivating examples are presented and analyzed, and the results suggest that the previous approximate analyses can seriously affect estimation of the genetic merit of breeding lines, particularly for models with more complex variance structures.

In crosses between inbred lines linear regression can be used to estimate marker effects; these marker effects then allow marker-assisted selection (MAS) for quantitative traits. Weighting of marker and phenotypic information in MAS requires estimation of genetic variance associated with the markers: the usual estimators are biased, resulting in too much weight being placed on marker information relative to phenotypic information. In this paper we develop a cross-validation method to remove this bias, and show by simulation that response to selection using this method is almost as high as that achieved using optimal weighting of marker and phenotypic information.

SummaryA method based on the animal model is described which allows the estimation of continuous changes in variance components over time using restricted maximum likelihood (REML). The method was applied to the analysis of a selection experiment in which a foundation population formed from a cross between two inbred strains of mice (C57BL/6J and DBA/2J) was divergently selected for 6 week body weight over 20 generations. The analysis suggested that there was an increase in phenotypic variance of about 50% in the low selected lines over the course of the experiment which was attributed to increases in the environmental and additive variance components. Variance changes in the High selected lines were generally smaller than in the Low lines, although there was an estimated 20% increase in the environmental variance. Simple models to explain these effects involving dominance, linkage and epistasis were explored. Testing which of these was responsible for the variance changes noted in this experiment (if any) is difficult, although the epistasis and dominance models require less stringent conditions than the linkage model, and the dominance model is supported by evidence of heterosis in the F1.

The retrospective analysis of a large database on wheat variety testing in New South Wales (NSW) is considered. This analysis involved three key steps. Initially error variance heterogeneity is modelled, indicating significant differences in error variance due to trial location, year of trialling, sowing date and trial mean yield. The implication of this modelling for the estimaion of variance components is discussed.

SummaryQuantitative variation in traits that change with age is important to both evolutionary biologists and breeders. We present three new methods for estimating the phenotypic and additive genetic covariance functions of a trait that changes with age, and illustrate them using data on daily lactation records from British Holstein—Friesian dairy cattle. First, a new technique is developed to fit a continuous covariance function to a covariance matrix. Secondly, this technique is used to estimate and correct for a bias that inflates estimates of phenotypic variances. Thirdly, we offer a numerical method for estimating the eigenvalues and eigenfunctions of covariance functions. Although the algorithms are moderately complex, they have been implemented in a software package that is made freely available.Analysis of lactation shows the advantages of the new methods over earlier ones. Results suggest that phenotypic variances are inflated by as much as 39 % above the underlying covariance structure by measurement error and short term environmental effects. Analysis of additive genetic variation indicates that about 90 % of the additive genetic variation for lactation during the first 10 months is associated with an eigenfunction that corresponds to increased (or decreased) production at all ages. Genetic tradeoffs between early and late milk yield are seen in the second eigenfunction, but it accounts for less than 8 % of the additive variance. This illustrates that selection is expected to increase production throughout lactation.

1. The mineral composition of the albumen and yolk was determined in several eggs from each of a number of individual hens from the same White-Leghorn strain. X-ray fluorescent spectrometry was used to undertake two independent series of analyses. A total of 8 minerals (calcium, chlorine, iron, magnesium, phosphorus, potassium, sodium, sulphur) were included in the analyses of the yolk and the same minerals, but excluding iron (which is present in only small amounts), in the albumen. 2. There was considerable variation between individuals in the mineral concentration in their eggs (coefficients of variation ranged between 3.8% for sodium to 19.9% for calcium in the albumen, and between 4.3% for phosphorus to 11.8% for iron in the yolk). 3. At the same time, the moderately high repeatability of mineral concentration (t = 0.4-0.6) in successive eggs from the same hen for several of the minerals analysed is indicative of some positive control by the hen of the mineral composition of her eggs. 4. There was a highly significant correlation (Por = 0.001) between the mean concentration of potassium in the albumen and the hatchability of the eggs, supporting the claim that a deficiency of potassium in the egg could be the basis of some failures in hatchability. 5. The study also revealed variation among individual birds in the concentration of iron in the yolk which was negatively correlated (Por = 0.01) with hatchability. No clear basis could be suggested for this variation among individual birds.

For populations undergoing mass selection, previous studies have shown that the rate of inbreeding is directly related to the mean and variance of long-term contributions from ancestors to descendants, and thus prediction of the rate of inbreeding can be achieved via the prediction of long-term contributions. In this paper, it is shown that the same relationship between the rate of inbreeding and long-term contributions is found when selection is based on an index of individual and sib records (index selection) and where sib records may be influenced by a common environment. In these situations, rates of inbreeding may be considerably higher than under mass selection. An expression for the rate of inbreeding is derived for populations undergoing index selection based on variances of (one-generation) family size and incorporating the concept of long-term selective advantage. When the mating structure is hierarchical, and when half-sib records are included in the index, the correlation between parental breeding values and the index values of their offspring is higher for male parents than female parents. This introduces an important asymmetry between the contributions of male and female ancestors to the evolution of inbreeding which is not present when selection is based on individual and/or full-sib records alone. The prediction equation for index selection accounts for this asymmetry. The prediction is compared to rates of inbreeding calculated from simulation. The prediction is good when family size is small relative to the number selected. The reasons for overprediction in other situations are discussed.

International audience

SummaryA method is presented for the prediction of rate of inbreeding for populations with discrete generations. The matrix of Wright's numerator relationships is partitioned into ‘contribution’ matrices which describe the contribution of the Mendelian sampling of genes of ancestors in a given generation to the relationship between individuals in later generations. These contributions stabilize with time and the value to which they stabilize is shown to be related to the asymptotic rate of inbreeding and therefore also the effective population size,whereNis the number of individuals per generation and μrandare the mean and variance of long-term relationships or long-term contributions. These stabilized values are then predicted using a recursive equation via the concept of selective advantage for populations with hierarchical mating structures undergoing mass selection. Account is taken of the change in genetic parameters as a consequence of selection and also the increasing ‘competitiveness’ of contemporaries as selection proceeds. Examples are given and predicted rates of inbreeding are compared to those calculated in simulations. For populations of 20 males and 20, 40, 100 or 200 females the rate of inbreeding was found to increase by as much as 75% over the rate of inbreeding in an unselected population depending on mating ratio, selection intensity and heritability of the selected trait. The prediction presented here estimated the rate of inbreeding usually within 5% of that calculated from simulation.

In crosses between inbred lines, linear regression can be used to estimate the correlation of markers with a trait of interest; these marker effects then allow marker assisted selection (MAS) for quantitative traits. Usually a subset of markers to include in the model must be selected: no completely satisfactory method of doing this exists. We show that replacing this selection of markers by ridge regression can improve the mean response to selection and reduce the variability of selection response.

L'estimation des effets maternels genetiques et non genetiques sur le poids jeune (JBWT) a ete effectuee par maximum de vraisemblance restreinte sur 139 534 et 174 668 donnees provenant de deux populations de poulets de chair. Parmi les modeles habituellement utilises dans l'estimation des effets maternels (modeles « reduits » de Willham), le meilleur ajustement a ete obtenu avec un modele genetique permettant des effets genetiques directs et maternels correles ainsi qu'un effet maternel permanent non genetique. Les heritabilites maternelles (0,04 et 0,02) ont ete faibles en comparaison des heritabilites directes (0,32 et 0,27), les correlations genetiques entre effets directs et maternels (τAM) ont ete negatives et identiques pour les deux souches (- 0,54), les effets maternels non genetiques pour les pleins freres (0,06 et 0,05) ont ete environ deux fois plus grands que pour les demi-freres (0,03 et 0,02). On a tenu compte d'une covariance non genetique possible entre mere et produit dans le modele mixte i) en estimant la covariance entre les effets maternels non genetiques et les effets residuels non genetiques (σEC) et ii) en introduisant un effet maternel phenotypique au travers de la regression sur la phenotype de la mere (F m dans le modele de Falconer). Bien qu'ils augmentent considerablement les vraisemblances, ces modeles etendus ont abouti a des valeurs encore plus negative de τAM a cause d'estimees positives de σEC (0,04 a 0,08 et 0,03 a 0,09) et F m (0,01 a 0,14 et 0,01 a 0,11). Un modele plus detaille pour les effets fixes tenant compte des effets de milieu propres aux troupeaux parentaux a reduit les estimees de τAM (- 0,18 a - 0,33). Les resultats ont suggere une importance limitee des effets maternels genetiques non mendeliens sur JBWT. Les modeles integres « Falconer-Willham» permettant a la fois des co(variances) maternelles genetiques et une action maternelle via le phenotype de la mere dans un modele mixte pourraient offrir des alternatives interessantes aux modeles de « Willham» couramment utilises pour les mammiferes (par exemple, bovins allaitants) comme il apparait d'apres leur meilleur ajustement a des donnees simulees.

A strategy of using an average information matrix is shown to be computationally convenient and efficient for estimating variance components by restricted maximum likelihood (REML) in the mixed linear model. Three applications are described. The motivation for the algorithm was the estimation of variance components in the analysis of wheat variety means from 1,071 experiments representing 10 years and 60 locations in New South Wales. We also apply the algorithm to the analysis of designed experiments by incomplete block analysis and spatial analysis of field experiments.

SUMMARYA pedigreed control strain was divided into three lines which were maintained genetically distinct over nine generations. Mean coefficients of inbreeding of about 0·1 were attained. Results suggest that discernible genetic drift had occurred in several traits. Separate estimates of genetic variance were obtained from observed variation between and within lines. These estimates differed significantly in the case of only one of the eight traits observed. Observed variation between lines agreed reasonably well with that predicted.

The birth and fate of 818 lambs born to 571 ewes on a low-ground farm in the Scottish Borders with a history of substantial perinatal mortality were monitored with a range of physiological, biochemical and pathological measurements. In lambs which survived, the rectal temperature, birthweight and plasma concentrations of fructose, insulin, thyroxine and the third component of complement at birth, and the weight at four months of age, decreased with litter size. One hundred and thirty-seven lambs were stillborn or died within four days and seven others died later. The mothers of 77 per cent of these lambs had low condition scores, but the lamb deaths did not correlate significantly with the condition scores. From data relating to birthweight, temperature, packed cell volume and plasma composition it was deduced that placental insufficiency was involved in 24 per cent of these deaths; acute hypoxaemia at birth accounted for 35 per cent, inadequate thermogenesis for 12 per cent and starvation for 13 per cent. The remaining 16 per cent of dead lambs could not be assigned to any of these categories. Using only clinicopathological criteria, 37 per cent of the lamb deaths were attributed to antenatal influences which included immaturity, developmental anomalies, and degenerative or inflammatory changes. Thirty-three per cent of the deaths were due to post natal factors which included, in declining order of frequency, starvation, enteritis, misadventure, pneumonia, navel infections and septicaemia. No conclusions could be drawn from the pathological examinations alone in the remaining 30 per cent, although almost half of these had low rectal temperatures after birth, death being attributed to hypothermia.(ABSTRACT TRUNCATED AT 250 WORDS)

Summary The estimation of the heritability of liability for a binomial or multiple threshold categorical trait is described and demonstrated. The method is an extension of that proposed by Falconer (1965) and allows for fixed effects in both the parent and offspring generations. The probit transformation is used to relate the liability scale to observations on the probability scale. Data on fleece rot incidence and scores in Merino sheep have been used to illustrate the method. Resume Estimation de l'heritabilite de caracteristiques categoriques par la regression descendance-parents L'estimation de l'heritabilite de la responsabilite relative a un caractere binomial categorique ou d'un caractere a seuils multiples est decrite et demontree. La methode est une extension de celle proposee par Falconer (1965) et permet la consideration d'effets fixes dans les generations des parents aussi bien que dans les generations des descendants. La transformation «probit» est utilisee pour mettre en relation l'echelle de responsabilite aux observations sur l'echelle de probabilite. Les dates d'incident de putrefaction de toison et points en moutons merino ont ete utilisees pour I'illustration de la methode. Resumen Estimacion de heredabilidad de caracteristicas binomiales y categoricas por la regresion de la descendencia sobre los padres Se describe y demuestra, la estimation de la heredabilidad de propension, para una caracteristica binomial o de umbra1 multiple. El metodo es una extension del propuesto por Falconer (1965) y toma en cuenta 10s efectos fijos en ambos, los padres y de la descendencia. La transformacion «probit», es usada para relacionar la escala de exposicion por observacion, sobre la escala de probabilidad. Datos sobre incidencia de vellon podrido (en puntos) en ovejas Merino, han sido usadas para ilustrar el metodo. Zusammenfassung Schatzung der Heritabilitat kategorischer Merkmale durch Nachkommen-Elternregression Die Schatzung der Heritabilitat der Anfalligkeit bezuglich eines binomialen kategorischen Merkmales und eines solcnen mit mehrfachen Schwellen wird beschrieben und demonstriert. Die Methode ist eine Fortentwicklung der von Falconer (1965) vorgeschlagenen und gestattet die Berucksichtigung fixer Wirkungen sowohl in den Eltern wie auch in den Nachkommengenerationen. Die Probittransformation wird verwendet, um die Verbindung zwischen der zugrundeliegenden Skala der Anfalligkeit und der Beobachtungen auf der Wahrscheinlichkeitsskala herzustellen. Es werden Unterlagen von Vliessfaulebefall und -punkten in Merinoschafen zur Illustration der Methode verwendet.

A sire evaluation procedure is proposed for situations in which there is uncertainty with respect to the assignment of progeny to sires. The method requires the specification of the prior probabilities Pij that progeny i is out of sire j. Inferences about location parameters (« fixed » environmental and group effects and transmitting abilities of sires) are based on Bayesian statistical procedures. Modal values of the posterior distribution of these parameters are taken as point estimators. Finding this mode entails solving a nonlinear system of equations and several algorithms are suggested. The methodology is described for univariate evaluations obtained from normal or binary traits. Estimation of unknown variances is also addressed. A small numerical example is presented to illustrate the procedure. Potential applications to livestock breeding are discussed., Une méthode d’évaluation des pères est proposée en situation d’incertitude vis-à-vis de l’assignation des descendants à leurs pères. La méthode requiert la spécification des probabilités a priori Pij que le descendant i provienne du père j. L’inférence des paramètres de position (effets « groupe » et de milieu, considérés comme fixes et valeurs génétiques transmises des pères) est basée sur des procédures statistiques bayésiennes. Les valeurs modales de la distribution a posteriori de ces paramètres ont été prises comme estimateurs ponctuels. La recherche du mode nécessite la résolution d’un système d’équations non linéaire pour lequel plusieurs algorithmes sont proposés. La méthodologie est développée dans le cadre univariate pour des caractères normaux et binaires. Le cas de variances inconnues est également abordé. Un petit exemple numérique est présenté à titre d’illustration. Enfin, les applications possibles aux espèces domestiques sont discutées.

The precision of estimates of genetic variances and covariances obtained from multivariate selection experiments of various designs are discussed. The efficiencies of experimental designs are compared using criteria based on a confidence region of the estimated genetic parameters, with estimation using both responses and selection differentials and offspring-parent regression. A good selection criterion is shown to be to select individuals as parents using an index of the sums of squares and crossproducts of the phenotypic measurements. Formulae are given for the optimum selection proportion when the relative numbers of individuals in the parent and progeny generations are fixed or variable. Although the optimum depends on "a priori" knowledge of the genetic parameters to be estimated, the designs are very robust to poor estimates. For bivariate uncorrelated data, the variance of the estimated genetic parameters can be reduced by approximately 0.4 relative to designs of a more conventional nature when half of the individuals are selected on one trait and half on the other trait. There are larger reductions in variances if the traits are correlated.