SNP in human ARHGEF3 promoter is associated with DNase hypersensitivity, transcript level and platelet function, and Arhgef3 KO mice have increased mean platelet volume

Genome-wide association studies have identified a genetic variant at 3p14.3 (SNP rs1354034) that strongly associates with platelet number and mean platelet volume in humans. While originally proposed to be intronic, analysis of mRNA expression in primary human hematopoietic subpopulations reveals that this SNP is located directly upstream of the predominantly expressed ARHGEF3 isoform in megakaryocytes (MK). We found that ARHGEF3, which encodes a Rho guanine exchange factor, is dramatically upregulated during both human and murine MK maturation. We show that the SNP (rs1354034) is located in a DNase I hypersensitive region in human MKs and is an expression quantitative locus (eQTL) associated with ARHGEF3 expression level in human platelets, suggesting that it may be the causal SNP that accounts for the variations observed in human platelet traits and ARHGEF3 expression. In vitro human platelet activation assays revealed that rs1354034 is highly correlated with human platelet activation by ADP. In order to test whether ARHGEF3 plays a role in MK development and/or platelet function, we developed an Arhgef3 KO/LacZ reporter mouse model. Reflecting changes in gene expression, LacZ expression increases during MK maturation in these mice. Although Arhgef3 KO mice have significantly larger platelets, loss of Arhgef3 does not affect baseline MK or platelets nor does it affect platelet function or platelet recovery in response to antibody-mediated platelet depletion compared to littermate controls. In summary, our data suggest that modulation of ARHGEF3 gene expression in humans with a promoter-localized SNP plays a role in human MKs and human platelet function-a finding resulting from the biological follow-up of human genetic studies. Arhgef3 KO mice partially recapitulate the human phenotype.Financial support was provided by NIH grants DK094934, DK086267, and DK0724429 to DSK, HL102482 to PB, the Cardeza Foundation for Hematologic Research (PB), and American Heart Association Fellowship 14PRE20480196 to LMS. MF is supported by the BHF Cambridge Centre of Excellence RE/13/6/30180. PvdH is supported by the Landsteiner Foundation for Blood Transfusion Research grant LSBR1133. LAT was supported by Leukaemia & Lymphoma Research Fellowship 09018. Research in the Ouwehand laboratory is supported by EU-FP7 project BLUEPRINT (282510) and by program grants from the National Institute for Health Research (NIHR); and the British Heart Foundation under numbers RP-PG- 0310-1002 and RG/09/12/28096. The laboratory receives funding from NHS Blood and Transplant for facilities

Genetic determinants of co-accessible chromatin regions in activated T cells across humans.

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms

A Robust Statistical Method for Association-Based eQTL Analysis

Background: It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS) is statistical inference of linkage disequilibrium (LD) between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation. Methodology: We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations. Results/Conclusions: The analyses show that the new method confers an improved statistical power for detecting genuin

Determination of genetic structure of germplasm collections: are traditional hierarchical clustering methods appropriate for molecular marker data?

Despite the availability of newer approaches, traditional hierarchical clustering remains very popular in genetic diversity studies in plants. However, little is known about its suitability for molecular marker data. We studied the performance of traditional hierarchical clustering techniques using real and simulated molecular marker data. Our study also compared the performance of traditional hierarchical clustering with model-based clustering (STRUCTURE). We showed that the cophenetic correlation coefficient is directly related to subgroup differentiation and can thus be used as an indicator of the presence of genetically distinct subgroups in germplasm collections. Whereas UPGMA performed well in preserving distances between accessions, Ward excelled in recovering groups. Our results also showed a close similarity between clusters obtained by Ward and by STRUCTURE. Traditional cluster analysis can provide an easy and effective way of determining structure in germplasm collections using molecular marker data, and, the output can be used for sampling core collections or for association studies

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability; For ethical and legal reasons access to INTERVAL data are subject to controls. Bona fide scientists can seek access to relevant de-identified individual participant data—including genetic, haematology analyser and proteomic data—and a copy of the trial’s data dictionary by applying to the INTERVAL Data Access Committee using the email address [email protected]. The INTERVAL Data Access Committee (supplemented, when required, by expertise from additional external scientists) meets several times a year to review applications according to the usual academic criteria of scientific validity and feasibility. Following approval by the INTERVAL Data Access Committee, a material transfer or research collaboration agreement will be agreed and signed with the applicants. Applicants might be requested to provide reimbursement of data management or preparation costs, as the INTERVAL trial is no longer in receipt of funding. Applicants will be required to provide updates to the INTERVAL Data Access Committee on their use of the INTERVAL trial data, including provision of copies of any publications. Applicants will be required to adhere in publications with the INTERVAL trial’s policy for acknowledgment of the trial’s funders, stakeholders, and scientific or technical contributors. The GRCh37 genome reference build is available for download from https://grch37.ensembl.org/info/data/ftp/index.html. Genomewide summary statistics may be downloaded by anonymous ftp from ftp://ftp.sanger.ac.uk/pub/project/humgen/summary_statistics/sysmex_blood_cell_genetics. The data from Ulirsch et al.29 are available from https://github.com/caleblareau/singlecell_bloodtraits/, from the Gene Expression Omnibus (GEO) under accession GSE119453 and from the Sequence Read Archive (SRA) under accession PRJNA491478. Other MK epigenetic data were generated by the BLUEPRINT project and are available in the EGA dataset EGAD00001001871.Code availability: The R code used for the association analysis is available in the git repository: https://github.com/ParsaAkbari/UKBB500K-Conditional-Analysis.Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes-including cell-type specific measures of granularity, nucleic acid content and reactivity-in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating with proteomic data we identify the transcription factor FOG2 as an early regulator of platelet formation and α-granularity. Finally, we show that colocalisation of our associations with disease risk signals can suggest aetiological cell-types-variants in IL2RA and ITGA4 respectively mirror the known effects of daclizumab in multiple sclerosis and vedolizumab in inflammatory bowel disease

A gain-of-function variant in DIAPH1 causes dominant macrothrombocytopenia and hearing loss

Macrothrombocytopenia (MTP) is a heterogeneous group of disorders characterized by enlarged and reduced numbers of circulating platelets, sometimes resulting in abnormal bleeding. In most MTP, this phenotype arises because of altered regulation of platelet formation from megakaryocytes (MKs). We report the identification of DIAPH1, which encodes the Rho-effector diaphanous-related formin 1 (DIAPH1), as a candidate gene for MTP using exome sequencing, ontological phenotyping, and similarity regression. We describe 2 unrelated pedigrees with MTP and sensorineural hearing loss that segregate with a DIAPH1 R1213* variant predicting partial truncation of the DIAPH1 diaphanous autoregulatory domain. The R1213* variant was linked to reduced proplatelet formation from cultured MKs, cell clustering, and abnormal cortical filamentous actin. Similarly, in platelets, there was increased filamentous actin and stable microtubules, indicating constitutive activation of DIAPH1. Overexpression of DIAPH1 R1213* in cells reproduced the cytoskeletal alterations found in platelets. Our description of a novel disorder of platelet formation and hearing loss extends the repertoire of DIAPH1-related disease and provides new insight into the autoregulation of DIAPH1 activity.The NIHR BioResource- Rare Diseases and the associated BRIDGE genome sequencing projects are supported by the National Institute for Health Research (NIHR; http://www.nihr.ac.uk). B.N. was supported by the Deutsche Forschungsgemeinschaft (SFB 688). S.S. was supported by a grant of the German Excellence Initiative to the Graduate School of Life Sciences, University of Würzburg. ET, DG, JCS, SP, IS, CJP, RM, SAsh, ST and KS are supported by the NIHR BioResource - Rare Diseases. KF, CT, and CVG are supported by the Fund for Scientific Research-Flanders (FWO-Vlaanderen, Belgium, G.0B17.13N) and by the Research Council of the University of Leuven (BOF KU Leuven‚ Belgium, OT/14/098). WNE is supported by the Cancer Council Western Australia. Research in the Ouwehand laboratory is supported by program grants from the European Commission, NIHR to WJA, SM, MK, RP, SBJ and WHO under numbers RP-PG-0310-1002; the laboratory also receives funding from NHS Blood and Transplant; CL and SKW are supported by Medical Research Council (MRC) Clinical Training Fellowships (number MR/K023489/1) and TKB by a British Society of Haematology/NHS Blood and Transplant grant. MAL and CL are supported by the Imperial College London Biomedical Research Centre; JRB acknowledges support by the NIHR Cambridge Biomedical Research Centre and SR by the Medical Research Council and Cambridge Biomedical Research Centre. CVG is holder of the Bayer and Norbert Heimburger (CSL Behring) Chairs. ADM is supported by the NIHR Bristol Cardiovascular Biomedical Research Unit

Publisher Correction:Network inference from glycoproteomics data reveals new reactions in the IgG glycosylation pathway

Correction to: Nature Communications (2017) 8:1231. doi:10.1038/s41467-017-01525-