The Cluster Variation Method for Efficient Linkage Analysis on Extended Pedigrees

BACKGROUND: Computing exact multipoint LOD scores for extended pedigrees rapidly becomes infeasible as the number of markers and untyped individuals increase. When markers are excluded from the computation, significant power may be lost. Therefore accurate approximate methods which take into account all markers are desirable. METHODS: We present a novel method for efficient estimation of LOD scores on extended pedigrees. Our approach is based on the Cluster Variation Method, which deterministically estimates likelihoods by performing exact computations on tractable subsets of variables (clusters) of a Bayesian network. First a distribution over inheritances on the marker loci is approximated with the Cluster Variation Method. Then this distribution is used to estimate the LOD score for each location of the trait locus. RESULTS: First we demonstrate that significant power may be lost if markers are ignored in the multi-point analysis. On a set of pedigrees where exact computation is possible we compare the estimates of the LOD scores obtained with our method to the exact LOD scores. Secondly, we compare our method to a state of the art MCMC sampler. When both methods are given equal computation time, our method is more efficient. Finally, we show that CVM scales to large problem instances. CONCLUSION: We conclude that the Cluster Variation Method is as accurate as MCMC and generally is more efficient. Our method is a promising alternative to approaches based on MCMC sampling

Exome sequencing identifies NBEAL2 as the causative gene for gray platelet syndrome.

Gray platelet syndrome (GPS) is a predominantly recessive platelet disorder that is characterized by mild thrombocytopenia with large platelets and a paucity of α-granules; these abnormalities cause mostly moderate but in rare cases severe bleeding. We sequenced the exomes of four unrelated individuals and identified NBEAL2 as the causative gene; it has no previously known function but is a member of a gene family that is involved in granule development. Silencing of nbeal2 in zebrafish abrogated thrombocyte formation

Dynamics of gene silencing during X inactivation using allele-specific RNA-seq

Background: During early embryonic development, one of the two X chromosomes in mammalian female cells is inactivated to compensate for a potential imbalance in transcript levels with male cells, which contain a single X chromosome. Here, we use mouse female embryonic stem cells (ESCs) with non-random X chromosome inactivation (XCI) and polymorphic X chromosomes to study the dynamics of gene silencing over the inactive X chromosome by high-resolution allele-specific RNA-seq. Results: Induction of XCI by differentiation of female ESCs shows that genes proximal to the X-inactivation center are silenced earlier than distal genes, while lowly expressed genes show faster XCI dynamics than highly expressed genes. The active X chromosome shows a minor but significant increase in gene activity during differentiation, resulting in complete dosage compensation in differentiated cell types. Genes escaping XCI show little or no silencing during early propagation of XCI. Allele-specific RNA-seq of neural progenitor cells generated from the female ESCs identifies three regions distal to the X-inactivation center that escape XCI. These regions, which stably escape during propagation and maintenance of XCI, coincide with topologically associating domains (TADs) as present in the female ESCs. Also, the previously characterized gene clusters escaping XCI in human fibroblasts correlate with TADs. Conclusions: The gene silencing observed during XCI provides further insight in the establishment of the repressive complex formed by the inactive X chromosome. The association of e

Promotion, prevention and protection: interventions at the population- and community-levels for mental, neurological and substance use disorders in low- and middle-income countries

Background In addition to services within the health system, interventions at the population and community levels are also important for the promotion of mental health, primary prevention of mental, neurological and substance use (MNS) disorders, identification and case detection of MNS disorders; and to a lesser degree treatment, care and rehabilitation. This study aims to identify “best practice” and “good practice” interventions that can feasibly be delivered at these population- and community-levels in low- and middle-income countries (LMICs), to aid the identification of resource efficiencies and allocation in LMICs. Methods A narrative review was conducted given the wide range of relevant interventions. Expert consensus was used to identify “best practice” at the population-level on the basis of existing quasi-experimental natural experiments and cost effectiveness, with small scale emerging and promising evidence comprising “good practice”. At the community-level, using expert consensus, the ACE (Assessing Cost-Effectiveness in Prevention Project) grading system was used to differentiate “best practice” interventions with sufficient evidence from “good practice” interventions with limited but promising evidence. ResultsAt the population-level, laws and regulations to control alcohol demand and restrict access to lethal means of suicide were considered “best practice”. Child protection laws, improved control of neurocysticercosis and mass awareness campaigns were identified as “good practice”. At the community level, socio-emotional learning programmes in schools and parenting programmes during infancy were identified as “best practice”. The following were all identified as “good practice”: Integrating mental health promotion strategies into workplace occupational health and safety policies; mental health information and awareness programmes as well as detection of MNS disorders in schools; early child enrichment/preschool educational programs and parenting programs for children aged 2–14 years; gender equity and/or economic empowerment programs for vulnerable groups; training of gatekeepers to identify people with MNS disorders in the community; and training non-specialist community members at a neighbourhood level to assist with community-based support and rehabilitation of people with mental disorders. Conclusion Interventions provided at the population- and community-levels have an important role to play in promoting mental health, preventing the onset, and protecting those with MNS disorders. The importance of inter-sectoral enga

Haplotype Inference in General Pedigrees Using the Cluster Variation Method

We present CVMHAPLO, a probabilistic method for haplotyping in general pedigrees with many markers. CVMHAPLO reconstructs the haplotypes by assigning in every iteration a fixed number of the ordered genotypes with the highest marginal probability, conditioned on the marker data and ordered genotypes assigned in previous iterations. CVMHAPLO makes use of the cluster variation method (CVM) to efficiently estimate the marginal probabilities. We focused on single-nucleotide polymorphism (SNP) markers in the evaluation of our approach. In simulated data sets where exact computation was feasible, we found that the accuracy of CVMHAPLO was high and similar to that of maximum-likelihood methods. In simulated data sets where exact computation of the maximum-likelihood haplotype configuration was not feasible, the accuracy of CVMHAPLO was similar to that of state of the art Markov chain Monte Carlo (MCMC) maximum-likelihood approximations when all ordered genotypes were assigned and higher when only a subset of the ordered genotypes was assigned. CVMHAPLO was faster than the MCMC approach and provided more detailed information about the uncertainty in the inferred haplotypes. We conclude that CVMHAPLO is a practical tool for the inference of haplotypes in large complex pedigrees