Search

Accurate and fast computation of quantitative genetic variance parameters is of great importance in both natural and breeding populations. For experimental designs with complex relationship structures it can be important to include both additive and dominance variance components in the statistical model. In this study, we introduce a Bayesian Gibbs sampling approach for estimation of additive and dominance genetic variances in the traditional infinitesimal model. The method can handle general pedigrees without inbreeding. To optimize between computational time and good mixing of the Markov chain Monte Carlo (MCMC) chains, we used a hybrid Gibbs sampler that combines a single site and a blocked Gibbs sampler. The speed of the hybrid sampler and the mixing of the single-site sampler were further improved by the use of pretransformed variables. Two traits (height and trunk diameter) from a previously published diallel progeny test of Scots pine (Pinus sylvestris L.) and two large simulated data sets with different levels of dominance variance were analyzed. We also performed Bayesian model comparison on the basis of the posterior predictive loss approach. Results showed that models with both additive and dominance components had the best fit for both height and diameter and for the simulated data with high dominance. For the simulated data with low dominance, we needed an informative prior to avoid the dominance variance component becoming overestimated. The narrow-sense heritability estimates in the Scots pine data were lower compared to the earlier results, which is not surprising because the level of dominance variance was rather high, especially for diameter. In general, the hybrid sampler was considerably faster than the blocked sampler and displayed better mixing properties than the single-site sampler.

A new effective Bayesian quantitative trait locus (QTL) mapping approach for the analysis of single-tail selected samples of the phenotype distribution is presented. The approach extends the affected-only tests to single-tail sampling with quantitative traits such as the log-normal survival time or censored/selected traits. A great benefit of the approach is that it enables the utilization of multiple-QTL models, is easy to incorporate into different data designs (experimental and outbred populations), and can potentially be extended to epistatic models. In inbred lines, the method exploits the fact that the parental mating type and the linkage phases (haplotypes) are known by definition. In outbred populations, two-generation data are needed, for example, selected offspring and one of the parents (the sires) in breeding material. The idea is to statistically (computationally) generate a fully complementary, maximally dissimilar, observation for each offspring in the sample. Bayesian data augmentation is then used to sample the space of possible trait values for the pseudoobservations. The benefits of the approach are illustrated using simulated data sets and a real data set on the survival of F~ mice following infection with Listeria monocytogenes.

Abstract Background Day care centre (DCC) attendees play a central role in maintaining the circulation of Streptococcus pneumoniae (pneumococcus) in the population. Exposure within families and within DCCs are the main risk factors for colonisation with pneumococcal serotypes in DCC attendees. Methods Transmission of serotype specific carriage was analysed with a continuous time event history model, based on longitudinal data from day care attendees and their family members. Rates of acquisition, conditional on exposure, were estimated in a Bayesian framework utilising latent processes of carriage. To ensure a correct level of exposure, non-participating day care attendees and their family members were included in the analysis. Posterior predictive simulations were used to quantify transmission patterns within day care cohorts, to estimate the basic reproduction number for pneumococcal carriage in a population of day care cohorts, and to assess the critical vaccine efficacy against carriage to eliminate pneumococcal transmission. Results The model, validated by posterior predictive sampling, was successful in capturing the strong temporal clustering of pneumococcal serotypes in the day care cohorts. In average 2.7 new outbreaks of pneumococcal carriage initiate in a day care cohort each month. While 39% of outbreaks were of size one, the mean outbreak size was 7.6 individuals and the mean length of an outbreak was 2.8 months. The role of families in creating and maintaining transmission was minimal, as only 10% of acquisitions in day care attendees were from family members. Considering a population of day care cohorts, a child-to-child basic reproduction number was estimated as 1.4 and the critical vaccine efficacy against acquisition of carriage as 0.3. Conclusion Pneumococcal transmission occurs in serotype specific outbreaks of carriage, driven by within-day-care transmission and between-serotype competition. An amplifying effect of the day care cohorts enhances the spread of pneumococcal serotypes within the population. The effect of vaccination, in addition to reducing susceptibility to pneumococcal carriage in the vaccinated, induces a herd effect, thus creating a counter-effect to the amplifying effect of the cohort. Consequently, the critical vaccine efficacy against carriage, required for elimination of transmission, is relatively low. Use of pneumococcal conjugate vaccines is expected to induce a notable herd protection against pneumococcal disease.

Abstract Background Streptococcus pneumoniae (pneumococcus) causes a wide range of clinical manifestations that together constitute a major burden of disease worldwide. The main route of pneumococcal transmission is through asymptomatic colonisation of the nasopharynx. Studies of transmission are currently of general interest because of the impact of the new conjugate-polysaccharide vaccines on nasopharyngeal colonisation (carriage). Here we report the first longitudinal study of pneumococcal carriage that records serotype specific exposure to pneumococci simultaneously within the two most important mixing groups, families and day care facilities. Methods We followed attendees (N = 59) with their family members (N = 117) and the employees (N = 37) in three Finnish day care centres for 9 months with monthly sampling of nasopharyngeal carriage. Pneumococci were cultured, identified and serotyped by standard methods. Results Children in day care constitute a core group of pneumococcal carriage: of the 36 acquisitions of carriage with documented exposure to homologous pneumococci, the attendee had been exposed in her/his day care centre in 35 cases and in the family in 9 cases. Day care children introduce pneumococci to the family: 66% of acquisitions of a new serotype in a family were associated with simultaneous or previous carriage of the same type in the child attending day care. Consequently, pneumococcal transmission was found to take place as micro-epidemics driven by the day care centres. Each of the three day care centres was dominated by a serotype of its own, accounting for 100% of the isolates of that serotype among all samples from the day care attendees. Conclusion The transmission of pneumococci is more intense within than across clusters defined by day care facilities. The ensuing micro-epidemic behaviour enhances pneumococcal transmission.

Abstract Background Cognitive traits derived from neuropsychological test data are considered to be potential endophenotypes of schizophrenia. Previously, these traits have been found to form a valid basis for clustering samples of schizophrenia patients into homogeneous subgroups. We set out to identify such clusters, but apart from previous studies, we included both schizophrenia patients and family members into the cluster analysis. The aim of the study was to detect family clusters with similar cognitive test performance. Methods Test scores from 54 randomly selected families comprising at least two siblings with schizophrenia spectrum disorders, and at least two unaffected family members were included in a complete-linkage cluster analysis with interactive data visualization. Results A well-performing, an impaired, and an intermediate family cluster emerged from the analysis. While the neuropsychological test scores differed significantly between the clusters, only minor differences were observed in the clinical variables. Conclusions The visually aided clustering algorithm was successful in identifying family clusters comprising both schizophrenia patients and their relatives. The present classification method may serve as a basis for selecting phenotypically more homogeneous groups of families in subsequent genetic analyses.