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• Shallow Whole Genome Sequencing of Patient Derived Xenografts

  Chemotherapy is the standard-of-care treatment for metastatic colorectal cancer (mCRC) and benefits some patients, but what distinguishes responders from non-responders is unclear. In this study, we leveraged a comprehensive collection of 27 molecularly annotated patient-derived xenografts to uncover functional predictors of response to 5-FU and irinotecan combination therapy (FOLFIRI) in mCRC. Genetic analyses revealed that treatment sensitivity was marked by genomic scars indicative of BRCAness, suggesting homologous recombination (HR) deficiency as a key determinant. Accordingly, we surveyed a manually curated panel of 44 genes with a documented role in HR for the potential presence of pathogenic mutations. We did not observe a specific enrichment of HR gene mutations based on response to FOLFIRI. This result, combined with the absence of widespread biallelic inactivation of the analyzed genes and the predominance of mutations categorized as variants of unknown significance, suggests that FOLFIRI sensitivity is not primarily governed by underlying mutations in HR genes responsible for mitigating the genotoxic effects of this therapeutic regimen.

  Study EGAS50000000191

• Exome Sequecning of MDS xenografted samples

  Pre-clinical research of Myelodysplastic Syndromes (MDS) is hampered by a lack of feasible disease models. Previously, we have established a robust patient-derived xenograft (PDX) model for MDS. Here, we demonstrate for the first time that this model is applicable as a pre-clinical platform to address pending clinical questions by interrogating the efficacy and safety of the thrombopoietin receptor agonist eltrombopag. Our pre-clinical study included n=49 xenografts generated from n=9 MDS patient samples. Substance efficacy was evidenced by FACS-based human platelet quantification, and clonal bone marrow evolution was reconstructed by serial whole exome sequencing of the PDX samples. In contrast to clinical trials in humans, this experimental setup allowed vehicle- and replicate-controlled analyses on a patient-individual level deciphering substance-specific effects from natural disease progression. We found that eltrombopag effectively stimulated thrombopoiesis in MDS PDX without adversely affecting the patients’ clonal composition. In conclusion, our MDS PDX model is a useful tool for testing new therapeutic concepts in MDS preceding clinical trials.

  Study EGAS00001005329

• Genomic Sequencing of Cervical Cancers

  Cervical cancer is responsible for 10-15% of cancer related deaths in women worldwide. The etiological role of infection with high-risk human papilloma viruses (HPV) in carcinomas of the cervix is well established. In general, the development of cervical carcinomas follows a progression from persistent HPV infection through precancerous lesions to invasive cancer. Previous studies have implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS as well as chromosome-arm level copy number alterations in the pathogenesis of cervical carcinomas. Here, we report whole exome sequencing analysis of 118 cervical carcinoma-normal paired samples from patients in Norway and Mexico, as well as transcriptome sequencing of 80 cases and whole genome sequencing of 13 tumor-normal pairs. Novel somatic mutations include recurrent E322K substitutions in the MAPK1 gene encoding the ERK2 kinase and inactivating mutations in the HLA-B gene. In addition, recurrent somatic mutations in FBXW7, EP300, and NFE2L2 are novel in the context of primary cervical carcinomas. Analysis of HPV integration sites revealed recurrent integration into the RAD51B locus as well as co-occurrence of HPV genome integration and copy number gains within several genomic loci. These findings shed new light on the pathogenesis of cervical carcinomas and suggest potential novel therapeutic targets.

  Study phs000600

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line WXS derived

  The lack of a well-characterized model system for many subtypes of leukemia hinders the development of targeted therapy and immunotherapy. A novel in-house-made pediatric MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line was characterized. This cell line is highly presentative for the major clone of the original material and thus a valuable resource to examine novel therapeutic for MEF2D fused patients.

  Study EGAS00001006801

• Genomic landscape of malignant peripheral nerve sheath tumor (MPNST)

  Neurofibromatosis type 1 (NF1) is the most common tumor predisposition syndrome, and is associated with an aggressive soft-tissue sarcoma, malignant peripheral nerve sheath tumours (MPNSTs), the greatest cause of morbidity and mortality in people with NF1. The only potentially curative therapy involves surgery which is not always possible. Even therapy with curative intent is associated with poor overall survival for both sporadic and NF1-related MPNSTs. The development of novel therapies has been largely hindered by a lack of understanding of the molecular events underpinning MPNST pathogenesis. This is a comprehensive multi-omic study of MPNST evolution based on whole genome sequencing and transcriptomic data.

  Study EGAS00001006069

• Minnesota Center for Twin and Family Research (MCTFR) Genome-Wide Association Study of Behavioral Disinhibition

  This is an epidemiological study of substance abuse and related psychopathology in which the subjects have been drawn from the Minnesota Center for Twin and Family Research (MCTFR). The MCTFR is a large, ongoing, family-based study. It is in part a longitudinal study of two cohorts of adolescent twins and their parents. It additionally includes a parallel longitudinal study of adolescent adoptive siblings, biologically related siblings, and their parents. Over 1500 twin families and 350 adoptive and biological sibling families have been studied, with follow-up assessments occurring approximately every 3 years. The MCTFR gathered detailed, standardized data on study participants including DSM-IIIR and DSM-IV diagnostic interview and questionnaire data. For the Genome-Wide Association Study of Behavioral Disinhibition, parental intake data plus that adolescent data gathered closest to the children 17th birthday (between ages 16.5 and 21) was used.

  Study phs000620

• Analysis of tumor periphery and center-specific mutations in renal cell carcinoma

  Renal cell carcinoma (RCC) is a genomically heterogeneous tumor. In the present project, the question whether intratumoral heterogeneity follows a zonal pattern indicating spatial niches was addressed. Whole exome sequencing of 16 paired samples from tumor periphery and center revealed a number of region-specific functional SNVs and Indels. Therefore, RCCs are not composed of evenly admixed tumor cells but show topological differences in their clonal composition.

  Dataset EGAD00001002067

• Whole exome sequencing of young onset Primary Sclerosing Cholangitis

  Primary sclerosing chloangitis is a rare autoimmune disease of the liver (prevalence =10/100,000) with a mean age of onset of 40 years. We are currently undertaking GWASand immunochip experiments to identify loci underlying PSC susceptibility. Through ourcollaborators at the University of Calgary we have access to DNA from three parent-offspringtrios where the children required liver transplants due to PSC before the age of 9. These areextremely rare cases indeed and we believe that exome-sequencing represents a powerfulmeans of identifying the causal mutation underlying this severe phenotype.

  Dataset EGAD00001000671

• Oral microbiota composition assessed with 16S rRNA sequencing from adults aged over 65 years old.

  This is a oral microbiota amplicon dataset derived from adult participants aged over 65 years old. It consists a total number of 491 samples, stored in 982 paired-end FASTQ files with sequence lengths of 200 nucleotides generated with a Illumina MiSeq. Of those 491 samples, 347 were used in analysis, the remaining 144 samples are control samples.

  Dataset EGAD00001007705

• Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

  Diseases with a complex genetic architecture, such as amyotrophic lateral sclerosis (ALS) as a most prominent example, are hard to disentangle. "Human mind-friendly" methods, such as linear approaches used in genome wide association studies (GWAS), remain blind to many genetic variants that matter. On the other hand, methods that are sufficiently sophisticated to entirely capture the characteristic interplay of genetic variants remain black boxes for the human mind. Here, we give this a decided, and as we argue, a very promising try. We present DiseaseCapsule, a capsule network-based approach that enables us to predict prevalence/occurrence of a genetically complex disease from individual genotype profiles. Importantly, capsule networks are considerably easier to decompose into their components than ordinary deep neural networks, which promotes the interpretability of their results. The data we used are from Project MinE, a large-scale study that aims to reveal the genetic and epigenetic mechanisms that underlie ALS in the framework of a globally concerted collaboration. Specifically, we used data from the Dutch cohort of the project, which contains 7213 healthy ('control') individuals and 3192 individuals affected with ALS. The cohort includes 5208 females and 5197 males. All participants of the study were genotyped using an Illumina 2.5M SNP array.

  Study phs003146

• The long term effects of chemotherapy on normal blood - Nanoseq dataset

  In developed countries, ~10% of individuals are exposed to systemic chemotherapy for cancer and other diseases. Many chemotherapeutic agents act by increasing DNA damage in cancer cells, hence triggering cell death. However, there is limited understanding of the extent and consequences of collateral DNA damage to normal tissues. To investigate the impact of chemotherapy on mutation burdens and cell population structure of a normal tissue we sequenced blood cell genomes from 23 individuals, aged 3-80 years, treated with a range of chemotherapy regimens. Substantial additional mutation loads with characteristic mutational signatures were imposed by some chemotherapeutic agents, but there were differences in burden between different classes of agent, different agents of the same class and different blood cell types. Chemotherapy also induced premature changes in the cell population structure of normal blood, similar to those of normal ageing. The results constitute an initial survey of the long-term biological consequences of cytotoxic agents to which a substantial fraction of the population is exposed during the course of their disease management, raising mechanistic questions and highlighting opportunities for mitigation of adverse effects.

  Dataset EGAD00001015340

• WGS data for Pancreatic Cancer samples (misc.)

  WGS data for pancreatic cancer samples. These are miscellaneous samples which are part of a tandem duplicator phenotype paper (Farooq et al, NPJ Precision Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina NovaSeq 6000 and aligned against GRCh38 (n=7 tumour/normal pairs).

  Dataset EGAD50000001833

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001676

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Victorian Collaborative AuTism Study (CATS): Family and Community Study of the Genetics of Autism Spectrum Disorder

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002044

• FaceBase Study of Facial Shape in Tanzania: CIDR

  The goals of this project are to identify loci that underlie major genetic determinants of orofacial shape, by means of a GWAS in a cohort of normal African children (from Tanzania) from whom we have collected 3D digitized facial morphometric scans, and a subsequent replication study of normal children from the same population. These studies are part of the NIDCR FaceBase initiative (https://www.facebase.org/). In addition to dbGaP, all study genotype and phenotype data (including primary facial scans and landmarks) will be available for data-sharing with qualified investigators via the NIDCR FaceBase Hub (www.facebase.org/), following approval by the NIDCR FaceBase Data Access Committee.

  Study phs000622

• DNA Methylation age and mortality in the Lothian Birth Cohorts of 1921 and 1936

  The study examined the association between DNA methylation age and mortality. Methylation age was estimated in 4 cohorts (including the Lothian Birth Cohorts of 1921 and 1936) and related to subsequent time-to-death. Across all four cohorts there was a strong correlation between predicted methylation age and chronological age. For individuals with a 5 year age acceleration (DNA methylation age - chronological age = 5), there was a meta analysed hazard ratio of mortality of 1.21 [1.14, 1.29]. Phenotype data associated with the study are available through dbGaP, the methylation raw data are available through the European Genome-phenome Archive (EGA; accession number EGAS00001000910).

  Study phs000821

• Assessing the impact of low frequency coding variants on disease risk using the Exomechip

  Following several rounds of Genome Wide Association (GWA) scans and subsequent meta-analyses of results multiple risk loci have been identified for many common diseases. However, in most instances the implicated common variants identified so far explain only a modest fraction of the genetic risk. In parallel to our efforts to identify the causative variants in the known loci it is necessary to assess the full spectrum of sequence variants for disease risk and in particular low frequency and rare variants that have not been tested in a comprehensive way so far. To this end an international effort by investigators who have performed whole exome sequencing in circa 12,000 individuals have assembled a set of ~250,000 exonic variants of low frequency – defined as seen in at least two studies and a minimum of three individuals (non-sysnonymous) or two individuals for SNPs altering splice sites / stop codons. The SNP content from the exome studies was complemented with additional interesting SNP sets totalling 25,000 markers (GWA tag SNPs, grid of common variants, HLA, Mitochondrial, Y-chromosome etc) and were used to generate a custom iSELECT array, the exome chip. Adequately powered association studies to test low frequency variants for association to disease risk are still very expensive if conducted by whole exome sequencing. The exome chip provides a cost efficient way to undertake such an experiment and the Wellcome Trust Cases Control Consortium will be applying this approach to eight diseases, type 1 and type 2 diabetes, coronary artery disease, hypertension, multiple sclerosis, rheumatoid arthritis, bipolar, and ankylosing spondylitis. The first objective will be to generate a large set of at least 10,000 common UK controls as analysis of lower frequency variants will require large sample sizes. This includes ~6000 samples from the 1958 Birth Cohort.

  Study EGAS00001000584

• Women's Ischemia Syndrome Evaluation (WISE-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: This is a National Heart, Lung and Blood Institute sponsored, four-center study designed to: 1) optimize symptom evaluation and diagnostic testing for ischemic heart disease; 2) explore mechanisms for symptoms and myocardial ischemia in the absence of epicardial coronary artery stenoses, and 3) evaluate the influence of reproductive hormones on symptoms and diagnostic test response.Background: Women tend to have a higher prevalence of chest pain than men, yet a lower prevalence of epicardial coronary stenoses, and diagnostic tests such as exercise-induced ECG changes tend to have a higher false-positive rate in women than in men. Thus, accurate diagnosis of ischemic heart disease in women is a major challenge to physicians. In addition, prognosis in women with abnormal diagnostic tests is largely unknown and the role reproductive hormones play in this diagnostic uncertainty is unexplored. Moreover, the significance and pathophysiology of ischemia in the absence of significant epicardial coronary stenoses is unknown.Participants: In Phase I (1996-1997), a pilot phase, 256 women were studied. During Phase II (1997-1999) angiographic and baseline data were collected on an additional 680 women to bring total enrollment to 936. Baseline data was also collected on a reference population of 70 women.Conclusions: Among women without CAD, abnormal Magnetic Resonance Spectroscopy (MRS) consistent with myocardial ischemia predicted cardiovascular outcome, notably higher rates of anginal hospitalization, repeat catherization, and greater treatment costs.

  Study phs004310

• Identification of biomarkers of response to preoperative talazoparib monotherapy in treatment naïve gBRCA+ breast cancers

  Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.

  Study EGAS00001005676

• Discovering the Genetic Basis of Human Neuroblastoma: A Gabriella Miller Kids First Pediatric Research Program (Kids First) Project

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Children with disseminated neuroblastoma have a very high risk of treatment failure and death despite receiving intensified chemotherapy, radiation therapy and immunotherapy. The long-term goal of our research program is to ultimately improve neuroblastoma cure rates by first comprehensively defining the genetic basis of the disease. The central hypothesis to be tested here is that neuroblastoma arises largely due to the epistatic interaction of common and rare heritable DNA variation. Here we will perform a comprehensive whole genome sequencing of 563 quartets of neuroblastoma patient germline and diagnostic tumor DNAs and germline DNAs from both parents. The case series was recently collected through a Children's Oncology Group epidemiology clinical trial and is robustly annotated with complete demographic (age, sex, race, ethnicity), clinical (e.g. age at diagnosis, stage, risk group), epidemiologic (parental dietary and exposure questionnaire) and biological (e.g. tumor MYCN status and multiple other tumor genomic measures) co-variates. Subjects were consented for genetic research and DNA is immediately available for shipment for sequencing. We propose Illumina-based whole genome sequencing in the 593 "trio" germline samples (Aim 1; due to missing parent: 487 full neuroblastoma triads, 106 child-single parent dyads = 1673 whole genome sequences) and matched diagnostic tumor DNA (Aim 2; N=366) at 30x sequencing depth (N=2039 whole genome sequences). Also in Aim 2 we will perform whole exome (100x) and RNA sequencing on the 366 tumor DNA and 228 tumor RNA samples from this cohort. Finally, we propose a pilot study of structural variation using long-range sequencing in 10 non-overlapping tumor samples chosen based on potentially relevant chromosomal alterations discovered with conventional NGS. Thus, a total of 2277 individual samples and 2655 sequences will be generated. We will use our established analytic pipeline that is currently being used to study the germline genomes of all cases sequenced through the NCI supported Therapeutically Applicable Research to Generate Effective Treatments program. We plan a three-stage analytic approach, first focusing on classic de novo and inherited Mendelian damaging alterations. We will next integrate our extensive epigenomic data from human neuroblastoma cell lines and genome-wide association study data (N=5,703 neuroblastoma cases to date) to guide a comprehensive assessment of noncoding variants that influence tumor initiation with a recently established analytic pipeline. Finally, we will utilize the tumor DNA analyses to inform relevance via somatic gain or loss of function effects at the sequence and/or copy number levels. All data generated in this project will be immediately placed into the Genomic Data Commons (GDC) and we will compute within this environment by importing our analytic pipelines into the GDC. These data will be fully integrated into the Kids First Data Resource and freely shared with all academically qualified petitioners. This comprehensive data set derived from a large and richly phenotyped series of neuroblastoma DNA quartets will be integrated with existing germline and/or tumor genomic data from over 6,000 neuroblastoma subjects (but none with matched patient-parent germline sequencing data) to provide an unparalleled opportunity to comprehensively discover the genetic basis of neuroblastoma.

  Study phs001436

• Whole exome sequencing (WES) of EBV- primary central nervous system lymphoma (PCNSL)

  This dataset contains whole exome sequencing (WES) of 29 HIV- EBV- primary central nervous system lymphoma (PCNSL) tumors and 5 activated B-cell-like PCNSL (ABC-PCNSL) and activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL) cell lines (TK, HKBML, OCI-Ly3, HBL-1, TMD-8). Cases with secondary involvement of the CNS were excluded. DNA was extracted with AllPrep DNA/RNA FFPE kit and libraries were prepared using the Agilent SureSelect Human All Exon v6 + UTR kit. Paired end reads were aligned to GRCh37 using bwa mem v.0.7.17, and reads were sorted and duplicated were marked in the final BAM files. Access to this data is controlled. There are a number of steps that a researcher must take to obtain access to this data, including execution of a Data Access Agreement between the institutions. The process is overseen by the Technology Development Office; please contact our general email address TDOadmin@phsa.ca. Please only click the "request data" button on the EGA website after a Data Access Agreement is fully executed.

  Dataset EGAD50000000451

• RaScALL: Rapid screening of RNA-seq in acute lymphoblastic leukaemia

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accerelated risk-stratification and therapeutic triage.

  Study EGAS00001006460

• Pediatric Obesity Transcriptomics Data Access Committee

  The Pediatric Obesity Transcriptomics Data Access Committee is responsible for reviewing and approving requests for access to controlled-access transcriptomic and associated phenotypic data generated within the study "Circulating mRNA and miRNA signatures used as predictive markers of lifestyle modification outcomes in pediatric obesity management". Access requests are evaluated with regard to scientific merit, ethical compliance, consistency with participant consent, data protection regulations, and proposed data security measures.

  Dac EGAC50000001050

• Autozygosity pilot - Born in Bradford (2014-11-20)

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing cohort samples from the Born In Bradford study will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consist of low coverage whole exome sequencing on these samples.Data Access is controlled by the Wellcome Trust Sanger Institute DAC and the Born In Bradford Executive Group. This dataset contains all the data available for this study on 2014-11-20.

  Dataset EGAD00001001079

• Passive and active DNA methylation and the interplay with genetic variation in gene regulation

  DNA methylation is an essential1 epigenetic mark whose role in gene regulation and its dependency on genomic sequence and environment are not yet fully understood2,3. In this study we provide novel insights into the mechanistic relationships between genetic variation, DNA methylation and transcriptome sequencing data in three different cell-types of the GenCord human population cohort4. We find that the association between DNA methylation and gene expression variation among individuals are likely due to different mechanisms from those establishing methylation-expression patterns during differentiation. Furthermore, cell-type differential DNA methylation may delineate a platform in which more local inter-individual changes may respond to or act in gene regulation. We show that unlike genetic regulatory variation, DNA methylation alone does not significantly drive allele specific expression.. Finally, inferred mechanistic relationships using genetic variation as well as correlations with TF abundance reveal both a passive and active role of DNA methylation to regulatory interactions influencing gene expression.

  Study EGAS00001000446