236 research outputs found

    Dynamic, mating-induced gene expression changes in female head and brain tissues of Drosophila melanogaster

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    BACKGROUND: Drosophila melanogaster females show changes in behavior and physiology after mating that are thought to maximize the number of progeny resulting from the most recent copulation. Sperm and seminal fluid proteins induce post-mating changes in females, however, very little is known about the resulting gene expression changes in female head and central nervous system tissues that contribute to the post-mating response. RESULTS: We determined the temporal gene expression changes in female head tissues 0-2, 24, 48 and 72 hours after mating. Females from each time point had a unique post-mating gene expression response, with 72 hours post-mating having the largest number of genes with significant changes in expression. At most time points, genes expressed in the head fat body that encode products involved in metabolism showed a marked change in expression. Additional analysis of gene expression changes in dissected brain tissues 24 hours post-mating revealed changes in transcript abundance of many genes, notably, the reduced transcript abundance of genes that encode ion channels. CONCLUSIONS: Substantial changes occur in the regulation of many genes in female head tissues after mating, which might underlie aspects of the female post-mating response. These results provide new insights into the physiological and metabolic changes that accompany changes in female behaviors

    Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood

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    Severe obesity is a rapidly growing global health threat. Although often attributed to unhealthy lifestyle choices or environmental factors, obesity is known to be heritable and highly polygenic; the majority of inherited susceptibility is related to the cumulative effect of many common DNA variants. Here we derive and validate a new polygenic predictor comprised of 2.1 million common variants to quantify this susceptibility and test this predictor in more than 300,000 individuals ranging from middle age to birth. Among middle-aged adults, we observe a 13-kg gradient in weight and a 25-fold gradient in risk of severe obesity across polygenic score deciles. In a longitudinal birth cohort, we note minimal differences in birthweight across score deciles, but a significant gradient emerged in early childhood and reached 12 kg by 18 years of age. This new approach to quantify inherited susceptibility to obesity affords new opportunities for clinical prevention and mechanistic assessment. © 2019 Author(s)National Human Genome Research Institute (1K08HG0101)Wellcome Trust (202802/Z/16/Z)University of Bristol NIHR Biomedical Research Centre (S- BRC-1215-20011)National Human Genome Research Institute (HG008895)National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300025CNational Heart, Lung, and Blood Institute (NHLBI) HHSN268201300026CNational Heart, Lung, and Blood Institute (NHLBI) HHSN268201300027CNational Heart, Lung, and Blood Institute (NHLBI) HHSN268201300028CNational Heart, Lung, and Blood Institute (NHLBI) HHSN268201300029CNational Heart, Lung, and Blood Institute (NHLBI) HHSN268200900041CNational Institute on Aging (AG0005)NHLBI (AG0005)National Human Genome Research Institute (U01-HG004729)National Human Genome Research Institute (U01-HG04424)National Human Genome Research Institute (U01-HG004446)Wellcome (102215/2/13/2

    Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium

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    Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories consider. Deciding how to weigh each type of evidence is difficult, and standards have been needed. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases. Nine molecular diagnostic laboratories involved in the Clinical Sequencing Exploratory Research (CSER) consortium piloted these guidelines on 99 variants spanning all categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign). Nine variants were distributed to all laboratories, and the remaining 90 were evaluated by three laboratories. The laboratories classified each variant by using both the laboratory's own method and the ACMG-AMP criteria. The agreement between the two methods used within laboratories was high (K-alpha = 0.91) with 79% concordance. However, there was only 34% concordance for either classification system across laboratories. After consensus discussions and detailed review of the ACMG-AMP criteria, concordance increased to 71%. Causes of initial discordance in ACMG-AMP classifications were identified, and recommendations on clarification and increased specification of the ACMG-AMP criteria were made. In summary, although an initial pilot of the ACMG-AMP guidelines did not lead to increased concordance in variant interpretation, comparing variant interpretations to identify differences and having a common framework to facilitate resolution of those differences were beneficial for improving agreement, allowing iterative movement toward increased reporting consistency for variants in genes associated with monogenic disease

    The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside

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    Background: Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. Results: We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action. Conclusions: This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine. Availability: TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql

    An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

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    BACKGROUND: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data was donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

    Inherited CHST11/MIR3922 deletion is associated with a novel recessive syndrome presenting with skeletal malformation and malignant lymphoproliferative disease

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    Glycosaminoglycans (GAGs) such as chondroitin are ubiquitous disaccharide carbohydrate chains that contribute to the formation and function of proteoglycans at the cell membrane and in the extracellular matrix. Although GAG-modifying enzymes are required for diverse cellular functions, the role of these proteins in human development and disease is less well understood. Here, we describe two sisters out of seven siblings affected by congenital limb malformation and malignant lymphoproliferative disease. Using Whole-Genome Sequencing (WGS), we identified in the proband deletion of a 55 kb region within chromosome 12q23 that encompasses part of CHST11 (encoding chondroitin-4-sulfotransferase 1) and an embedded microRNA (MIR3922). The deletion was homozygous in the proband but not in each of three unaffected siblings. Genotyping data from the 1000 Genomes Project suggest that deletions inclusive of both CHST11 and MIR3922 are rare events. Given that CHST11 deficiency causes severe chondrodysplasia in mice that is similar to human limb malformation, these results underscore the importance of chondroitin modification in normal skeletal development. Our findings also potentially reveal an unexpected role for CHST11 and/or MIR3922 as tumor suppressors whose disruption may contribute to malignant lymphoproliferative disease

    Somatic sex-specific transcriptome differences in Drosophila revealed by whole transcriptome sequencing

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    <p>Abstract</p> <p>Background</p> <p>Understanding animal development and physiology at a molecular-biological level has been advanced by the ability to determine at high resolution the repertoire of mRNA molecules by whole transcriptome resequencing. This includes the ability to detect and quantify rare abundance transcripts and isoform-specific mRNA variants produced from a gene.</p> <p>The sex hierarchy consists of a pre-mRNA splicing cascade that directs the production of sex-specific transcription factors that specify nearly all sexual dimorphism. We have used deep RNA sequencing to gain insight into how the Drosophila sex hierarchy generates somatic sex differences, by examining gene and transcript isoform expression differences between the sexes in adult head tissues.</p> <p>Results</p> <p>Here we find 1,381 genes that differ in overall expression levels and 1,370 isoform-specific transcripts that differ between males and females. Additionally, we find 512 genes not regulated downstream of <it>transformer </it>that are significantly more highly expressed in males than females. These 512 genes are enriched on the × chromosome and reside adjacent to dosage compensation complex entry sites, which taken together suggests that their residence on the × chromosome might be sufficient to confer male-biased expression. There are no transcription unit structural features, from a set of features, that are robustly significantly different in the genes with significant sex differences in the ratio of isoform-specific transcripts, as compared to random isoform-specific transcripts, suggesting that there is no single molecular mechanism that generates isoform-specific transcript differences between the sexes, even though the sex hierarchy is known to include three pre-mRNA splicing factors.</p> <p>Conclusions</p> <p>We identify thousands of genes that show sex-specific differences in overall gene expression levels, and identify hundreds of additional genes that have differences in the abundance of isoform-specific transcripts. No transcription unit structural feature was robustly enriched in the sex-differentially expressed transcript isoforms. Additionally, we found that many genes with male-biased expression were enriched on the × chromosome and reside adjacent to dosage compensation entry sites, suggesting that differences in sex chromosome composition contributes to dimorphism in gene expression. Taken together, this study provides new insight into the molecular underpinnings of sexual differentiation.</p
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