67 research outputs found

    Informing disease modelling with brain-relevant functional genomic annotations

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    The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two

    Smoking Gun or Circumstantial Evidence? Comparison of Statistical Learning Methods using Functional Annotations for Prioritizing Risk Variants

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    Although technology has triumphed in facilitating routine genome sequencing, new challenges have been created for the data-analyst. Genome-scale surveys of human variation generate volumes of data that far exceed capabilities for laboratory characterization. By incorporating functional annotations as predictors, statistical learning has been widely investigated for prioritizing genetic variants likely to be associated with complex disease. We compared three published prioritization procedures, which use different statistical learning algorithms and different predictors with regard to the quantity, type and coding. We also explored different combinations of algorithm and annotation set. As an application, we tested which methodology performed best for prioritizing variants using data from a large schizophrenia meta-analysis by the Psychiatric Genomics Consortium. Results suggest that all methods have considerable (and similar) predictive accuracies (AUCs 0.64-0.71) in test set data, but there is more variability in the application to the schizophrenia GWAS. In conclusion, a variety of algorithms and annotations seem to have a similar potential to effectively enrich true risk variants in genome-scale datasets, however none offer more than incremental improvement in prediction. We discuss how methods might be evolved for risk variant prediction to address the impending bottleneck of the new generation of genome re-sequencing studies

    Human-lineage-specific genomic elements are associated with neurodegenerative disease and APOE transcript usage.

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    Knowledge of genomic features specific to the human lineage may provide insights into brain-related diseases. We leverage high-depth whole genome sequencing data to generate a combined annotation identifying regions simultaneously depleted for genetic variation (constrained regions) and poorly conserved across primates. We propose that these constrained, non-conserved regions (CNCRs) have been subject to human-specific purifying selection and are enriched for brain-specific elements. We find that CNCRs are depleted from protein-coding genes but enriched within lncRNAs. We demonstrate that per-SNP heritability of a range of brain-relevant phenotypes are enriched within CNCRs. We find that genes implicated in neurological diseases have high CNCR density, including APOE, highlighting an unannotated intron-3 retention event. Using human brain RNA-sequencing data, we show the intron-3-retaining transcript to be more abundant in Alzheimer's disease with more severe tau and amyloid pathological burden. Thus, we demonstrate potential association of human-lineage-specific sequences in brain development and neurological disease

    BG Ind: the nearest doubly eclipsing, compact hierarchical quadruple system

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    BG Ind is a well-studied, bright, nearby binary consisting of a pair of F stars in a 1.46-d orbit. We have discovered in the TESS light curve for TIC 229804573 (aka BG Ind), a second eclipsing binary in the system with a 0.53-d period. Our subsequent analyses of the recent TESS and archival ground-based photometric and radial velocity (RV) data reveal that the two binaries are gravitationally bound in a 721-d period, moderately eccentric orbit. We present the results of a joint spectro-photodynamical analysis of the eclipse timing variation curves of both binaries based on TESS and ground-based archival data, the TESS light curve, archival RV data, and the spectral energy distribution, coupled with the use of PARSEC stellar isochrones. We confirm prior studies of BG Ind that found that the brighter binary A consists of slightly evolved F-type stars with refined masses of 1.32 and 1.43 M-circle dot, and radii of 1.59 and 2.34 R-circle dot. The previously unknown binary B has two less massive stars of 0.69 and 0.64 M-circle dot and radii of 0.64 and 0.61 R-circle dot. Based on a number of different arguments that we discuss, we conclude that the three orbital planes are likely aligned to within 17 degrees

    Out of Sight but Not out of Mind: Alternative Means of Communication in Plants

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    Current knowledge suggests that the mechanisms by which plants communicate information take numerous forms. Previous studies have focussed their attention on communication via chemicals, contact and light; other methods of interaction between plants have remained speculative. In this study we tested the ability of young chilli plants to sense their neighbours and identify their relatives using alternative mechanism(s) to recognised plant communication pathways. We found that the presence of a neighbouring plant had a significant influence on seed germination even when all known sources of communication signals were blocked. Furthermore, despite the signalling restriction, seedlings allocated energy to their stem and root systems differently depending on the identity of the neighbour. These results provide clear experimental evidence for the existence of communication channels between plants beyond those that have been recognized and studied thus far

    Rare coding variants in ten genes confer substantial risk for schizophrenia

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    Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3–50, P < 2.14 × 10−6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-d-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach

    Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus.

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    Systemic lupus erythematosus (SLE) is a genetically complex autoimmune disease characterized by loss of immune tolerance to nuclear and cell surface antigens. Previous genome-wide association studies (GWAS) had modest sample sizes, reducing their scope and reliability. Our study comprised 7,219 cases and 15,991 controls of European ancestry, constituting a new GWAS, a meta-analysis with a published GWAS and a replication study. We have mapped 43 susceptibility loci, including ten new associations. Assisted by dense genome coverage, imputation provided evidence for missense variants underpinning associations in eight genes. Other likely causal genes were established by examining associated alleles for cis-acting eQTL effects in a range of ex vivo immune cells. We found an over-representation (n = 16) of transcription factors among SLE susceptibility genes. This finding supports the view that aberrantly regulated gene expression networks in multiple cell types in both the innate and adaptive immune response contribute to the risk of developing SLE

    A case of behavioural diversification in male floral function – the evolution of thigmonastic pollen presentation

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    The authors gratefully acknowledge funding provided by an Else-Neumann-Stipendium (http://www.fu-berlin.de/sites/promovieren/drs/nachwuchs/nachwuchs/nafoeg.html), Deutscher Akademischer Austausch Dienst (DAAD) and botconsult GmbH at different stages of data acquisition. We thank Tobias Grass, Joana Bergmann and Franziska Weber (Freie Universität Berlin) for help with data collection in the field and in the greenhouse. Nicole Schmandt, Federico Luebert, Juliana Chacón and Dietmar Quant (Universität Bonn) provided help in the molecular laboratory and the edition of the molecular dataset. We furthermore thank Markus Ackermann (Koblenz) for providing photographs, Philipp Klein (Berlin) for editing the video and Katy Jones (Berlin) for helpful comments on an earlier version of the manuscript. Rafael Acuña has been supported by the ALECOSTA scholarship program. Coverage of the article processing charge by the German Research Foundation via the Open Access Publication Fund of the Freie Universität Berlin is gratefully acknowledged.Peer reviewedPublisher PD
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