The Early Positive Approaches to Support (E-PAtS) study: study protocol for a feasibility cluster randomised controlled trial of a group programme (E-PAtS) for family caregivers of young children with intellectual disability

Background: Children with intellectual disability have an IQ < 70, associated deficits in adaptive skills and are at increased risk of having clinically concerning levels of behaviour problems. In addition, parents of children with intellectual disability are likely to report high levels of mental health and other psychological problems. The Early Positive Approaches to Support (E-PAtS) programme for family caregivers of young children (5 years and under) with intellectual and developmental disabilities is a group-based intervention which aims to enhance parental psychosocial wellbeing and service access and support positive development for children. The aim of this study is to assess the feasibility of delivering E-PAtS to family caregivers of children with intellectual disability by community parenting support service provider organisations. The study will inform a potential, definitive RCT of the effectiveness and cost-effectiveness of E-PAtS. Methods: This study is a feasibility cluster randomised controlled trial, with embedded process evaluation. Up to 2 family caregivers will be recruited from 64 families with a child (18 months to 5 years) with intellectual disability at research sites in the UK. Participating families will be allocated to intervention: control on a 1:1 basis; intervention families will be offered the E-PAtS programme immediately, continuing to receive usual practice, and control participants will be offered the opportunity to attend the E-PAtS programme at the end of the follow-up period and will continue to receive usual practice. Data will be collected at baseline, 3 months post-randomisation and 12 months post-randomisation. The primary aim is to assess feasibility via the assessment of: recruitment of service provider organisations; participant recruitment; randomisation; retention; intervention adherence; intervention fidelity and the views of participants, intervention facilitators and service provider organisations regarding intervention delivery and study processes. The secondary aim is preliminary evaluation of a range of established outcome measures for individual family members, subsystem relationships and overall family functioning, plus additional health economic outcomes for inclusion in a future definitive trial. Discussion: The results of this study will inform a potential future definitive trial, to evaluate the effectiveness and cost-effectiveness of the E-PAtS intervention to improve parental psychosocial wellbeing. Such a trial would have significant scientific impact internationally in the intellectual disability field

Connecting Planetary Composition with Formation

The rapid advances in observations of the different populations of exoplanets, the characterization of their host stars and the links to the properties of their planetary systems, the detailed studies of protoplanetary disks, and the experimental study of the interiors and composition of the massive planets in our solar system provide a firm basis for the next big question in planet formation theory. How do the elemental and chemical compositions of planets connect with their formation? The answer to this requires that the various pieces of planet formation theory be linked together in an end-to-end picture that is capable of addressing these large data sets. In this review, we discuss the critical elements of such a picture and how they affect the chemical and elemental make up of forming planets. Important issues here include the initial state of forming and evolving disks, chemical and dust processes within them, the migration of planets and the importance of planet traps, the nature of angular momentum transport processes involving turbulence and/or MHD disk winds, planet formation theory, and advanced treatments of disk astrochemistry. All of these issues affect, and are affected by the chemistry of disks which is driven by X-ray ionization of the host stars. We discuss how these processes lead to a coherent end-to-end model and how this may address the basic question.Comment: Invited review, accepted for publication in the 'Handbook of Exoplanets', eds. H.J. Deeg and J.A. Belmonte, Springer (2018). 46 pages, 10 figure

Drosophila Duplication Hotspots Are Associated with Late-Replicating Regions of the Genome

Duplications play a significant role in both extremes of the phenotypic spectrum of newly arising mutations: they can have severe deleterious effects (e.g. duplications underlie a variety of diseases) but can also be highly advantageous. The phenotypic potential of newly arisen duplications has stimulated wide interest in both the mutational and selective processes shaping these variants in the genome. Here we take advantage of the Drosophila simulans–Drosophila melanogaster genetic system to further our understanding of both processes. Regarding mutational processes, the study of two closely related species allows investigation of the potential existence of shared duplication hotspots, and the similarities and differences between the two genomes can be used to dissect its underlying causes. Regarding selection, the difference in the effective population size between the two species can be leveraged to ask questions about the strength of selection acting on different classes of duplications. In this study, we conducted a survey of duplication polymorphisms in 14 different lines of D. simulans using tiling microarrays and combined it with an analogous survey for the D. melanogaster genome. By integrating the two datasets, we identified duplication hotspots conserved between the two species. However, unlike the duplication hotspots identified in mammalian genomes, Drosophila duplication hotspots are not associated with sequences of high sequence identity capable of mediating non-allelic homologous recombination. Instead, Drosophila duplication hotspots are associated with late-replicating regions of the genome, suggesting a link between DNA replication and duplication rates. We also found evidence supporting a higher effectiveness of selection on duplications in D. simulans than in D. melanogaster. This is also true for duplications segregating at high frequency, where we find evidence in D. simulans that a sizeable fraction of these mutations is being driven to fixation by positive selection

A model species for agricultural pest genomics: the genome of the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera: Chrysomelidae)

The Colorado potato beetle is one of the most challenging agricultural pests to manage. It has shown a spectacular ability to adapt to a variety of solanaceaeous plants and variable climates during its global invasion, and, notably, to rapidly evolve insecticide resistance. To examine evidence of rapid evolutionary change, and to understand the genetic basis of herbivory and insecticide resistance, we tested for structural and functional genomic changes relative to other arthropod species using genome sequencing, transcriptomics, and community annotation. Two factors that might facilitate rapid evolutionary change include transposable elements, which comprise at least 17% of the genome and are rapidly evolving compared to other Coleoptera, and high levels of nucleotide diversity in rapidly growing pest populations. Adaptations to plant feeding are evident in gene expansions and differential expression of digestive enzymes in gut tissues, as well as expansions of gustatory receptors for bitter tasting. Surprisingly, the suite of genes involved in insecticide resistance is similar to other beetles. Finally, duplications in the RNAi pathway might explain why Leptinotarsa decemlineata has high sensitivity to dsRNA. The L. decemlineata genome provides opportunities to investigate a broad range of phenotypes and to develop sustainable methods to control this widely successful pest

The Drosophila melanogaster Genetic Reference Panel

A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype&ndash;phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype&ndash;phenotype mapping using the power of Drosophila genetics

Bayesian model to detect phenotype-specific genes for copy number data

<p>Abstract</p> <p>Background</p> <p>An important question in genetic studies is to determine those genetic variants, in particular CNVs, that are specific to different groups of individuals. This could help in elucidating differences in disease predisposition and response to pharmaceutical treatments. We propose a Bayesian model designed to analyze thousands of copy number variants (CNVs) where only few of them are expected to be associated with a specific phenotype.</p> <p>Results</p> <p>The model is illustrated by analyzing three major human groups belonging to HapMap data. We also show how the model can be used to determine specific CNVs related to response to treatment in patients diagnosed with ovarian cancer. The model is also extended to address the problem of how to adjust for confounding covariates (e.g., population stratification). Through a simulation study, we show that the proposed model outperforms other approaches that are typically used to analyze this data when analyzing common copy-number polymorphisms (CNPs) or complex CNVs. We have developed an <monospace><b>R</b></monospace> package, called <monospace><b>bayesGen</b></monospace>, that implements the model and estimating algorithms.</p> <p>Conclusions</p> <p>Our proposed model is useful to discover specific genetic variants when different subgroups of individuals are analyzed. The model can address studies with or without control group. By integrating all data in a unique model we can obtain a list of genes that are associated with a given phenotype as well as a different list of genes that are shared among the different subtypes of cases.</p