98 research outputs found

    BCL11A deletions result in fetal hemoglobin persistence and neurodevelopmental alterations

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    A transition from fetal hemoglobin (HbF) to adult hemoglobin (HbA) normally occurs within a few months after birth. Increased production of HbF after this period of infancy ameliorates clinical symptoms of the major disorders of adult ß-hemoglobin: ß-thalassemia and sickle cell disease. The transcription factor BCL11A silences HbF and has been an attractive therapeutic target for increasing HbF levels; however, it is not clear to what extent BCL11A inhibits HbF production or mediates other developmental functions in humans. Here, we identified and characterized 3 patients with rare microdeletions of 2p15-p16.1 who presented with an autism spectrum disorder and developmental delay. Moreover, these patients all exhibited substantial persistence of HbF but otherwise retained apparently normal hematologic and immunologic function. Of the genes within 2p15-p16.1, only BCL11A was commonly deleted in all of the patients. Evaluation of gene expression data sets from developing and adult human brains revealed that BCL11A expression patterns are similar to other genes associated with neurodevelopmental disorders. Additionally, common SNPs within the second intron of BCL11A are strongly associated with schizophrenia. Together, the study of these rare patients and orthogonal genetic data demonstrates that BCL11A plays a central role in silencing HbF in humans and implicates BCL11A as an important factor for neurodevelopment

    eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs

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    The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases

    Genome-wide enhancer maps link risk variants to disease genes

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    Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complextraits, each of which could reveal insights into the mechanisms of disease(1). Many ofthe underlying causal variants may affect enhancers(2,3), but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types(4). Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577genesthat appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.Peer reviewe

    Genetic predisposition to mosaic Y chromosome loss in blood.

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    Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism1-5, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.This research has been conducted using the UK Biobank Resource under application 9905 and 19808. This work was supported by the Medical Research Council [Unit Programme number MC_UU_12015/2]. Full study-specific and individual acknowledgements can be found in the supplementary information

    Identification of constrained sequence elements across 239 primate genomes

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    Noncoding DNA is central to our understanding of human gene regulation and complex diseases1,2, and measuring the evolutionary sequence constraint can establish the functional relevance of putative regulatory elements in the human genome3–9. Identifying the genomic elements that have become constrained specifically in primates has been hampered by the faster evolution of noncoding DNA compared to protein-coding DNA10, the relatively short timescales separating primate species11, and the previously limited availability of whole-genome sequences12. Here we construct a whole-genome alignment of 239 species, representing nearly half of all extant species in the primate order. Using this resource, we identified human regulatory elements that are under selective constraint across primates and other mammals at a 5% false discovery rate. We detected 111,318 DNase I hypersensitivity sites and 267,410 transcription factor binding sites that are constrained specifically in primates but not across other placental mammals and validate their cis-regulatory effects on gene expression. These regulatory elements are enriched for human genetic variants that affect gene expression and complex traits and diseases. Our results highlight the important role of recent evolution in regulatory sequence elements differentiating primates, including humans, from other placental mammals

    The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease

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    Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.We thank members of the Cambridge BioResource Scientific Advisory Board and Management Committee for their support of our study and the National Institute for Health Research Cambridge Biomedical Research Centre for funding. K.D. is funded as a HSST trainee by NHS Health Education England. M.F. is funded from the BLUEPRINT Grant Code HEALTH-F5-2011-282510 and the BHF Cambridge Centre of Excellence [RE/13/6/30180]. J.R.S. is funded by a MRC CASE Industrial studentship, co-funded by Pfizer. J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator, and National Institute for Health Research (NIHR) Senior Investigator. S.M., S.T, M.H, K.M. and L.D. are supported by the NIHR BioResource-Rare Diseases, which is funded by NIHR. Research in the Ouwehand laboratory is supported by program grants from the NIHR to W.H.O., the European Commission (HEALTH-F2-2012-279233), the British Heart Foundation (BHF) to W.J.A. and D.R. under numbers RP-PG-0310-1002 and RG/09/12/28096 and Bristol Myers-Squibb; the laboratory also receives funding from NHSBT. W.H.O is a NIHR Senior Investigator. The INTERVAL academic coordinating centre receives core support from the UK Medical Research Council (G0800270), the BHF (SP/09/002), the NIHR and Cambridge Biomedical Research Centre, as well as grants from the European Research Council (268834), the European Commission Framework Programme 7 (HEALTH-F2-2012-279233), Merck and Pfizer. DJR and DA were supported by the NIHR Programme ‘Erythropoiesis in Health and Disease’ (Ref. NIHR-RP-PG-0310-1004). N.S. is supported by the Wellcome Trust (Grant Codes WT098051 and WT091310), the EU FP7 (EPIGENESYS Grant Code 257082 and BLUEPRINT Grant Code HEALTH-F5-2011-282510). The INTERVAL study is funded by NHSBT and has been supported by the NIHR-BTRU in Donor Health and Genomics at the University of Cambridge in partnership with NHSBT. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health of England or NHSBT. D.G. is supported by a “la Caixa”-Severo Ochoa pre-doctoral fellowship

    Differential methylation relative to breast cancer subtype and matched normal tissue reveals distinct patterns

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    Due to the heterogeneous nature of breast cancer and the widespread use of single-gene studies, there is limited knowledge of multi-gene, locus-specific DNA methylation patterns in relation to molecular subtype and clinical features. We, therefore, quantified DNA methylation of 70 candidate gene loci in 140 breast tumors and matched normal tissues and determined associations with gene expression and tumor subtype. Using Sequenom’s EpiTYPER platform, approximately 1,200CpGs were interrogated and revealed six DNA methylation patterns in breast tumors relative to matched normal tissue. Differential methylation of several gene loci was observed within all molecular subtypes, while other patterns were subtype-dependent. Methylation of numerous gene loci was inversely correlated with gene expression, and in some cases, this correlation was only observed within specific breast tumor subtypes. Our findings were validated on a larger set of tumors and matched adjacent normal tissue from The Cancer Genome Atlas dataset, which utilized methylation data derived from both Illumina Infinium 27 and 450k arrays. These findings highlight the need to control for subtype when interpreting DNA methylation results, and the importance of interrogating multiple CpGs across varied gene regions.Electronic supplementary materialThe online version of this article (doi:10.1007/s10549-013-2738-0) contains supplementary material, which is available to authorized users

    The RNA-binding protein Rbm38 is dispensable during pressure overload-induced cardiac remodeling in mice

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    The importance of tightly controlled alternative pre-mRNA splicing in the heart is emerging. The RNA binding protein Rbm24 has recently been identified as a pivotal cardiac splice factor, which governs sarcomerogenesis in the heart by controlling the expression of alternative protein isoforms. Rbm38, a homolog of Rbm24, has also been implicated in RNA processes such as RNA splicing, RNA stability and RNA translation, but its function in the heart is currently unknown. Here, we investigated the role of Rbm38 in the healthy and diseased adult mouse heart. In contrast to the heart- and skeletal muscle-enriched protein Rbm24, Rbm38 appears to be more broadly expressed. We generated somatic Rbm38 -/- mice and show that global loss of Rbm38 results in hematopoietic defects. Specifically, Rbm38 -/- mice were anemic and displayed enlarged spleens with extramedullary hematopoiesis, as has been shown earlier. The hearts of Rbm38 -/- mice were mildly hypertrophic, but cardiac function was not affected. Furthermore, Rbm38 deficiency did not affect cardiac remodeling (i.e. hypertrophy, LV dilation and fibrosis) or performance (i.e. fractional shortening) after pressure-overload induced by transverse aorta constriction. To further investigate molecular consequences of Rbm38 deficiency, we examined previously identified RNA stability, splicing, and translational targets of Rbm38. We found that stability targets p21 and HuR, splicing targets Mef2d and Fgfr2, and translation target p53 were not altered, suggesting that these Rbm38 targets are tissue-specific or that Rbm38 deficiency may be counteracted by a redundancy mechanism. In this regard, we found a trend towards increased Rbm24 protein expression in Rbm38 -/- hearts. Overall, we conclude that Rbm38 is critical in hematopoiesis, but does not play a critical role in the healthy and diseased heart
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