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• High Density SNP Association Analysis of Lung Cancer

  This research builds upon an extensive resource of a case-control study that has been ongoing at the UT MD Anderson Cancer Center since 1991. To identify risk variants for lung cancer, we conducted a genome-wide association study. Cases are newly diagnosed, histologically-confirmed patients presenting at MD Anderson Cancer and who had not previously received treatment other than surgery. Controls are healthy individuals seen for routine care at Kelsey-Seybold Clinics, the largest physician group-practice plan in the Houston Metropolitan area. This lung GWAS led to the identification of a susceptibility locus for lung cancer at 15q25.1. We used data from 315,450 tagging SNPs in 1,154 current and former (ever) smoking cases of European ancestry and 1,137 frequency-matched, ever-smoking controls from Houston, Texas in the discovery followed by the replication of the ten SNPs most significantly associated with lung cancer in an additional 711 cases and 632 controls from Texas and 2,013 cases and 3,062 controls from the UK. Two SNPs, rs1051730 and rs8034191, were significantly associated with risk of lung cancer with combined analysis yielded odds ratios of 1.32 (P < 1X10-17) for both SNPs. These two SNPs mapped to a region of strong linkage disequilibrium within 15q25.1 containing PSMA4 and the nicotinic acetylcholine receptor subunit genes CHRNA3 and CHRNA5. (Nat Genet. 2008 May;40(5):616-22. PMID:18385676)

  Study phs000753

• A Genome-Wide Association Study in Patients Experiencing Breast Events While Receiving Adjuvant Aromatase Inhibitors for Early Breast Cancer on NCIC CTG Trial MA.27

  Source of patients:The source of the patients for this genome-wide case-control study was MA.27, which was conducted as a multi-cooperative group effort under the auspices of the NCI Breast Cancer Intergroup of North America. The NCIC Clinical Trials Group (CTG) serves as the coordinating group, with participation by the NCI-sponsored North Central Cancer Treatment Group, Eastern Cooperative Oncology Group (ECOG), Southwest Oncology Group, and Cancer and Leukemia Group B (CALGB). MA.27 involved postmenopausal women with histologically confirmed and completely resected invasive breast cancer with surgical margins clear of invasive carcinoma in the following TMN categories (AJCC Version 6): pT1, pT2, pT3; pNx, pN0, pN1, pN2, pN3 (only when the sole basis is presence of 10 or more involved axillary nodes); MO. The primary tumor must have been estrogen receptor (ER) and/or progesterone receptor positive. Patients were stratified by lymph node status at diagnosis, prior adjuvant chemotherapy, and trastuzumab use and were randomized to 5 years of adjuvant therapy with anastrozole or exemestane. The trial was activated on May 26, 2003, and reached its accrual objectives on July 31, 2008, after the randomization of 6827 North American patients, with the majority (79%) providing DNA and consent for genetic testing. Non-North American patients were also entered by the International Breast Cancer Study Group but they did not contribute DNA. From 2003 to December 21, 2004, patients also underwent a second randomization to celecoxib 400 mg twice daily or placebo but, after the entry of 1,622 patients, this treatment was discontinued because of reports of increased cardiovascular risk associated with celecoxib. The final results of this study have been published, see Goss et al., 2013 (23358971). The patients in this analysis came from three cohorts: Cohort 1 consisted of 870 patients genotyped on the Illumina Human610-Quad BeadChip studied in a GWAS with the phenotype of musculoskeletal adverse event, see Ingle et al., 2010 (20876420), Cohort 2 consisted of 882 patients genotyped on the Illumina OmniExpress platform studied in a GWAS with the phenotype of fragility fractures, see Liu et al., 2014 (25148458), and the remaining 2913 patients were genotyped with the Illumina OmniExpressExome platform.

  Study phs001043

• Resuscitation Outcomes Consortium (ROC) Trauma Epidemiologic Registry (Trauma Epistry) (ROC-Trauma Epistry-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.Available Data: This dataset only includes traumatic injury participants. For ROC cardiac arrest Epistry data please see: ROC-Cardiac Epistry 1 and 2 and ROC-Cardiac Epistry 3.Objectives: To build a prospective population-based registry of participants with out-of-hospital traumatic injury responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of people that experience traumatic injury; to more fully establish the burden of traumatic injury; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Traumatic injury is a major public health problem generating substantial morbidity, mortality, and economic burden on society. The majority of seriously injured persons are initially evaluated and cared for by prehospital providers, however the effect of EMS systems, EMS clinical care, and EMS interventions on trauma patient outcomes is largely unknown. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region.The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Previous trauma registries have generally focused primarily on hospitalized patients with limited prehospital information. Registries may also exclude trauma cases at far ends of the spectrum, such as those who die in the field or in a non-trauma center and/or patients that are treated and released. These limitations do not allow for detailed, outcome-based assessments of EMS system factors necessary to define prehospital resuscitation best practices. Therefore there was a need for standardized data collection of out-of-hospital traumatic injuries matched to hospital-based outcomes in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 13,830 traumatic events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital traumatic injuries in the ROC regions. Cases were identified through review of emergency response system records including dispatch centers, EMS ground agencies, and air medical services. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Sites submitted data using a web-based interface or batch uploads (Newgard, et al., 2008, PMID: 18482792).

  Study phs003809

• RNA-seq of atypical 3q26 samples

  RNA was isolated using phenol-chloroform extraction followed by DNase digestion or using the Qiagen Allprep DNA/RNA kit and protocol (Qiagen, #80204). cDNA synthesis was done using the SuperScript II Reverse Transcriptase kit (Invitrogen). Quantitative real-time PCR was performed by using primers as described previously13,21 on the 7500 Fast Real-time PCR System (Applied Biosystems). Relative levels of gene expression were calculated using the ΔΔCt method

  Dataset EGAD00001006106

• Small variants in mtDNA Canary Islands - WES Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005678

• Small variants in mtDNA Canary Islands - WGS Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005679

• Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005677

• The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

  Acute lymphoblastic leukaemia (ALL) is the most common childhood malignancy, and implementation of risk-adapted therapy has been instrumental in the dramatic improvements in clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions, notably ETV6-RUNX1, TCF3-PBX1 and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing (RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as drivers in ALL, and identification of these new entities will contribute to refining ALL risk stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of including RNA-seq in standard of care diagnostic pipelines to detect gene rearrangements and IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard of care diagnostics. KMT2A-rearrangements (MLL), whilst usually identified, were the most commonly missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not detected by standard of care testing in nine patients. These were found in patients who were not classifiable using standard molecular assessment. We developed an approach to detect the commonest IKZF1 deletion from RNA-seq data and validated this using a RQ-PCR assay. We applied an expression classifier to identify Ph-like B-ALL patients. T-ALL proved a rich source of novel gene fusions which have clinical implications or provide insights into disease biology. Our experience shows that RNA-seq can be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of ALL.

  Study EGAS00001004212

• EGA submission account terms

  Submission account terms Each EGA submission account has a dedicated submission box. To ensure continued service to all submitters EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. Those that are near to or exceeding this value will be monitored on a weekly basis by the helpdesk team and the submitter will be contacted and guidance provided accordingly on completing their metadata registration. You will be able to register your metadata associated with the files in your submission account via EGA Submitter Portal, Webin or the EGA REST API. EGA also requests that metadata is submitted within 60 days of upload data to a submission box. When we detect files that are over 60 days old in a submission box we will notify the submitter requesting that metadata be submitted or the files removed from the submission box. It is important to note that data is not archived at the EGA until the metadata describing the files has been associated and the archival process has completed. It is only when associated metadata has been submitted that the archival process into EGA is fully triggered. EGA removes files from the submission box once they have been successfully archived, so no action is required by a submitter to remove successfully archived files. Files over 90 days old will be deleted from the submission box unless EGA Helpdesk has been contacted and confirmed an exemption with the submitter.

  Documentation submission/terms

• A Chromatin Accessibility Atlas of the Developing Human Telencephalon

  Gene expression differs between cell types and regions within complex tissues such as the developing brain. To discover regulatory elements underlying this specificity, we generated genome-wide maps of chromatin accessibility in nine anatomically-defined regions of the developing human telencephalon. Additionally, we defined the histone modification landscape of the prefrontal cortex and generated chromatin accessibility maps of its upper and deep layers. We predicted a subset of open chromatin regions (18%) that are most likely to be active enhancers, many of which are dynamic with 26% differing between early and late mid-gestation and 28% present in only one brain region. These predicted regulatory elements (pREs) are enriched proximal to genes with expression differences across developmental stages, regions, and cortical laminae; they harbor distinct sequence motifs that suggest potential upstream regulators. We leveraged this atlas to predict and validate novel regulatory elements of genes that control cortex laminar identity and genes associated with autism spectrum disorder (ASD). These include enhancers proximal to FEZF2 and BCL11A that were validated in mouse, and an enhancer of ASD gene SLC6A1 containing two functional de novo mutations in individuals with ASD whose enhancer function we validated via CRISPRa. We also include data for transcription factor binding in mid-fetal cortex tissues, using CUT&RUN methods.

  Study phs002033