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• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  This study included samples from metastatic breast cancer patients who underwent a biopsy in the context of SAFIR01 (NCT01414933), SAFIR02 (NCT02299999), SHIVA (NCT01771458) and MOSCATO (NCT01566019) prospective trials. These French multicentre trials used high throughput genome analysis on fresh frozen tumor biopsies as a therapeutic decision tool for metastatic cancer patients, with solid cancers (SHIVA, MOSCATO) or specifically with breast cancer (SAFIR01, SAFIR02). All patients gave their informed consent for translational research and genetic analyses of their somatic DNA. Overall, whole-exome sequencing for a total of 216 pairs of metastatic tumor and unmutated DNA derived from corresponding blood samples was performed using Illumina technology. The results of the analysis of the mutational profile of metastatic breast cancer was reported in Lefebvre et al. (PMID:28027327).

  Study EGAS00001001695

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Dataset EGAD00001005448

• NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort

  The CATHeterization GENetics (CATHGEN) biorepository collected biospecimens and clinical data on individuals age ≥18 undergoing cardiac catheterization for concern of ischemic heart disease at a single center (Duke University Medical Center) from 2000-2010; a total of N=9334 individuals were collected. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included subject demographics, cardiometabolic risk factors, cardiac history including symptoms, age-of-onset of cardiovascular diseases, coronary anatomy and cardiac function at catheterization, laboratory data, and yearly follow-up for hospitalizations, vital status, medication use and lifestyle factors. AF cases were defined as individuals who had ever had AF based on any ECG available at Duke University or ICD-9 code for AF used for inpatient or outpatient billing.

  Study phs001600

• Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation

  As part of the study "Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation" we wanted to identiffy the SNVs that are located in STRC and which ones in STRCP1. For this we applied targeted long-read sequencing.

  Dataset EGAD00001011305

• Harnessing transposons for drug resistance gene discovery in cancer

  This study involves a forward genetic screen to identify common insertion sites in drug resistant clones. We will be utilising piggybac transposon systems in order to generate multiple drug resistant clones in a range of human cancer cell lines.

  Dataset EGAD00001000980

• Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular environment

  For two cases of breast cancers, semibulk RNA-seq and single cell RNA-seq were performed.

  Study JGAS000387

• Genome-Wide associations of Lung Health Study (LHS)

  The 'Genome-Wide Associations Environmental Interactions in the Lung Health Study' at Johns Hopkins University aims to test for association between lung function decline as a primary outcome associated with chronic obstructive pulmonary disease (COPD) using banked DNA and phenotype data on 4,287 European Americans from the longitudinal, multicenter Lung Health Study (LHS). The broad goals of the LungGO/ESP-GO falls into two general categories: (i) discovery of all variants (i.e., common and rare) in all protein-coding regions of the human genome (i.e., the exome) conferring risk to complex pulmonary diseases including COPD, in a subset of the LHS cohort. The Johns Hopkins University LHS cohort offers a unique opportunity to elucidate genetic variants that cause COPD. The Lung Health Study I was a randomized multicenter clinical trial with 5887 participants carried out from October 1986 to April 1994, designed to test the effectiveness of smoking cessation and bronchodilator administration in smokers aged 35 to 60 with mild lung function impairment. Participants were randomly assigned to one of three groups: usual care, who received no intervention smoking intervention with the inhaled bronchodilator ipratroprium bromide smoking intervention with an inhaled placebo. The effect of intervention was evaluated by the rate of decline of forced expiratory volume in one second (FEV1). For the GWAS, only the subset of European American LHS participants for whom lung function data from three time points or more are available. Thus, the GWAS represents 73% of the 5,887 volunteers who participated in the LHS study. Importantly, LHS subjects included had similar demographics (including age, gender and BMI) and rates of lung function decline (mean annual change in FEV1% predicted: -0.96 %/yr vs. -0.99 %/yr, p=0.57) compared with those not included in the GWAS, reflecting little selection bias for our primary outcome. They were, however, more likely to have quit smoking after 5 years. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to lung function through large-scale genome-wide association studies of smokers enrolled in a multicenter clinical trial. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000335

• Therapeutic Genetics and Disease Modeling in LAMA2-CMD

  Merosin-deficient congenital muscular dystrophy (MDC1A) is an autosomal recessive disorder caused by mutations in the LAMA2 gene, resulting in a defective form of the extracellular matrix protein laminin-α2 (LAMA2). Individuals diagnosed with MDC1A exhibit progressive muscle wasting and declining neuromuscular functions. No treatments for this disorder are currently available. This study involves transcriptomic comparison analysis between MDC1A patient fibroblasts and healthy control fibroblasts to reveal changes in gene expression that contribute to LAMA2 congenital muscular dystrophy (LAMA2-CMD).

  Study phs003250

• genetic analysis of carcinogenesis in GAPPS

  Gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS) is an autosomal dominant syndrome characterized by polyposis localized in the gastric body and fundus with a strong tendency for adenocarcinoma. The genetic mutations that accumulate during the progression from normal mucosa through fundic gland polyps (FGPs) to carcinoma in GAPPS remain unclear.We investigated the evolutionary process from normal mucosa to FGPs and carcinoma in GAPPS. Through comprehensive mutational and transcriptome analyses, we aimed to provide insights into the biology of this disease.

  Study JGAS000843

• Spatial multiomic analyses reveal carcinogenic pathways in end-stage renal disease

  Patients with end-stage renal disease (ESRD) are at increased risk for acquired cystic kidney disease (ACKD) and renal tumours, but the molecular basis of such disorders remains elusive. Here, we performed spatial immunogenomic analyses on specimens from 43 patients with ACKD and associated tumours. In this study, we characterized the genomic and transcriptomic features of renal tumours in ESRD. Second, we elucidated the genetic background and microenvironment of cysts in ACKD via comprehensive spatial transcriptomics.

  Study JGAS000855

• Immune Biomarkers in Metastatic Castration-resistant Prostate Cancer

  Background: Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease in which molecular stratification is needed to improve clinical outcomes. The identification of predictive biomarkers can have a major impact on the care of these patients, but the availability of metastatic tissue samples for research in this setting is limited. Objective: To study the prevalence of immune biomarkers of potential clinical utility to immunotherapy in mCRPC by tumour RNA sequencing, and to determine their association with overall survival (OS).

  Study EGAS50000001269

• MYD88/TLR mutations in CLL

  The Chronic Lymphocytic Leukemia (CLL) Genome Project aims to identify genetic alterations involved in the development and progression of the CLL, which are still unknown, with the objective of generating a comprehensive catalogue of genetic alterations in 500 independent tumours. The CLL Genome Project, as a contributing member of the International Cancer Genome Consortium (ICGC), has the purposes of creating diagnostic tools, discovering therapeutic targets and developing new strategies that will allow a customized therapy for CLL in order to make it more precise and effective.

  Study EGAS00001000772

• Paired exome analysis in urothelial carcinoma

  In this study we characterized genomic alterations in two to five metachronous tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth), Ultra deep targeted sequencing (~6,809x mean read depth) and whole transcriptome RNA-seq was performed for all samples. In addition multiregional WES was performed on 8 adjacent regions from a single tumor.

  Study EGAS00001001686

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004193

• The Melbourne Urological Research Alliance (MURAL) Collection of Patient-Derived Models of Prostate Cancer

  1. Low-Dose Carboplatin Modifies the Tumor Microenvironment to Augment CAR T Cell Efficacy in Human Prostate Cancer Models.Single-cell RNA sequencing (scRNA-seq) was performed to analyze the transcriptional modifications in the tumor microenvironment of prostate cancer patient-derived xenografts (PDX). The analyzed PDX tumor was PDX-287R from the MURAL collection of PDXs (PMID: 34413304). Mice harboring PDX tumors were treated with the carboplatin chemotherapy, and tumors were harvested 3 weeks later. RNA sequencing (RNA-Seq) was used to define immune and non-immune cell populations and anti-tumor innate immune signaling within the tumor microenvironment.To investigate the response of tumor cells to carboplatin treatment in more detail, RNA-Seq was performed on FACs-isolated tumor cells from PDX-287R at one week post-treatment. Gene set enrichment analysis showed an enrichment for apoptotic pathways, with significantly increased expression of the pro-apoptotic genes FAS, BAX, BBC3, IFI6, and JUN. Previously, carboplatin has been shown to activate the cGAS/STING pathway, and here we also found an increase in STING signaling, with an enrichment for the cytosolic DNA sensing pathway and increased expression of STING1, STAT1 and STAT2. There was also a significant increase in the expression of genes involved in T cell chemotaxis, including CXCL10, CXCL11, and CCL20. Collectively, carboplatin-induced cell death in tumor cells likely initiated a pro-inflammatory phenotype in prostate cancer PDXs.2. Co-Targeting BET, CREBBP, and EP300 Inhibits Neuroendocrine Signaling in Androgen Receptor-Null Prostate Cancer.The landscape of castration-resistant prostate cancer (CRPC) is characterized by a multitude of phenotypes, among which neuroendocrine disease holds a prominent position, each displaying unique responses to therapeutic interventions. The efficacy of inhibitors targeting BET and CREBBP/EP300 in prostate cancer treatment is widely acknowledged, primarily due to their ability to attenuate androgen receptor (AR) signaling. However, the effectiveness of these inhibitors in prostate cancers devoid of AR remains uncertain.This investigation sought to elucidate the role of BRD4, CREBBP, and EP300, which are co-expressed in both AR-positive and AR-null prostate cancer. Our study revealed that a compound targeting all three proteins, NEO2734, exhibited efficacy in suppressing the growth of organoids from both AR-positive and AR-null tumors, as evidenced by alterations in viability, size, and cellular composition. Furthermore, NEO2734 treatment consistently led to transcriptional downregulation of cell cycle pathways across various models. In the context of neuroendocrine prostate cancer (NEPC), NEO2734 demonstrated notable efficacy. Treatment with NEO2734 resulted in decreased expression of ASCL1 and other neuroendocrine markers (including SYP) , accompanied by a reduction in tumor growth in vivo. These findings collectively underscore the potential of epigenome-targeted inhibitors in impeding the growth of neuroendocrine prostate cancer, by disrupting lineage regulators in a phenotype-dependent manner. Consistent with the NEPC organoids and explants, NKX3-1 was upregulated in NEO2734-treated PDXs.In this study, we examined the impact of NEO2734 treatment on 6 organoids (treated for 24 hrs), 3 explants treated with JQ1 (for 48 hrs) and 2 PDXs (at two time points) using bulk RNA sequencing (RNA-Seq). These results are available through this dbGaP submission. The implications of these results warrant further exploration and development of compounds possessing similar activities for clinical applications. The ability of NEO2734 to mitigate the growth of both AR-positive and AR-null prostate cancer underscores its potential as a versatile therapeutic agent. Moreover, its efficacy in targeting neuroendocrine phenotypes offers promising avenues for addressing a subtype of CRPC that poses significant clinical challenges. In conclusion, this study sheds light on the intricate interplay between epigenetic regulators and prostate cancer phenotypes. The observed effects of NEO2734 on growth inhibition and phenotype-specific disruption highlight the importance of continued research into compounds with similar epigenome-targeting mechanisms for advancing precision medicine approaches in the treatment of prostate cancer.3. Defining Focal Neuroendocrine Differentiation as a Transcriptionally Distinct Form of Prostate Cancer Pathology Characterized by the Expression of Androgen ReceptorsThe study aimed to understand the transcriptional differences among different neuroendocrine pathologies of prostate cancer. The study hypothesized that the diverse neuroendocrine pathology observed in prostate might be attributable to differences in transcriptional level that remain hidden in bulk RNA-Seq data. To investigate, we employed scRNA-seq to generate gene expression profiles of 18,632 individual tumor cells from 9 PDX models representing five distinct neuroendocrine pathologies of prostate cancer. Our analysis identified 3-8 transcriptionally distinct sub-populations per PDX. The expression of key oncogenic signaling pathways and master regulator activity varied across in neuroendocrine pathologies, with each type of pathology displaying a unique set of transcriptional sub-populations. We discovered that, like the amphicrine pathology, focal neuroendocrine differentiation (focal NED) cells maintain androgen receptor (AR) signaling. However, the expression profiles of focal NED cells differed from the other pathologies, indicating it should be considered as a distinct type of neuroendocrine pathology in prostate cancer. Analysis of copy number alterations suggested little clonal divergence between focal NED cells and neighboring adenocarcinoma cells, emphasizing the transcriptional distinctiveness of focal NED.Overall, the findings suggest potential differences in treatment approaches for tumors from prostate cancer patients showing neuroendocrine pathology, especially focal NED.4. Reprogramming of Androgen Receptor Activity in Castration-Resistant Prostate Cancer is Shaped by Truncated Variants.Under the influence of treatments that target the androgen receptor (AR) axis, prostate cancer cells undergo various changes to the AR gene. This includes the production of truncated AR variants that lack the ligand binding domain and are constitutively active. However, the exact role of these truncated variants in shaping the AR signaling axis and their importance in therapy resistance is not yet fully understood. By examining the AR cistrome in a group of patient-derived prostate cancer models with different mechanisms of castration resistance, we observed diverse changes in AR activity in metastatic prostate cancer, including castration-resistant models. Specifically, we identified a unique subset of tumors characterized by the expression of ARv567es, a variant resulting from structural rearrangements of the AR gene. Tumors positive for ARv567es showed a distinct AR binding profile and epigenome compared to those without ARv567es, which was linked to an altered transcriptional profile. The presence of ARv567es is associated with poor responses to treatments, such as castration and bipolar androgen therapy (BAT), regardless of the presence of full-length AR. This involves disruption of the autoregulatory loop that controls AR gene transcription and reduced transcriptional responses to treatment. Overall, this study demonstrates that ARv567es can lead to transcriptional reprogramming in advanced prostate cancer and drive therapy resistance. 5. The MURAL Collection of Prostate Cancer Patient-Derived Xenografts Enables Discovery Through Preclinical Models of Uro-Oncology.We created a comprehensive PDX resource for prostate cancer to facilitate the rapid and systematic evaluation of new therapies. This collection includes 59 tumors from 30 patients, gathered between 2012 and 2020, aligning with the availability of abiraterone and enzalutamide in the clinic. The PDXs cover the clinical, pathological, and genomic spectrum of prostate cancer, ranging from treatment-naïve primary tumors to castration-resistant metastases. We characterized heterogeneity in adenocarcinoma and neuroendocrine phenotypes using bulk and single-cell RNA sequencing. Additionally, organoids were cultured from PDXs, enhancing our preclinical study capabilities. Employing a 1x1x1 design, we quickly identified tumors with responses to combination therapies. To manage the distribution of PDXs, we established the Melbourne Urological Research Alliance (MURAL). This PDX collection significantly enhances our ability to test and prioritize effective treatments for future clinical trials in prostate cancer.6. Prostate Cancer Associated Fibroblasts Have Distinct Morpho-Mechanical Features That Are Associated With Patient Outcome.The tumor stroma, including cancer-associated fibroblasts (CAFs), has a crucial role in tumor progression. This study focused on the morphological and mechanical properties of CAFs and normal prostatic fibroblasts. The findings revealed that CAFs had distinct morphological and mechanical characteristics compared to normal fibroblasts, such as differences in nuclear size, shape, F-actin arrangement, cellular volumes, and elasticity. Additionally, the study correlated these biophysical properties with transcriptomic data, identifying pathways and cellular components linked to the observed changes. Overall, high-throughput assessments of biophysical properties in prostate cancer cells and stromal components may serve as predictive tools for patient outcomes and help identify new therapeutic approaches targeting the tumor stroma.

  Study phs003369

• NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)

  ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID: 18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID: 20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID: 21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID: 24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252.

  Study phs001472

• Single cell transcriptomics of hESC-derived midbrain dopaminergic neurons generated by a new human development-based protocol

  Recent advances in stem cell technologies provide new opportunities for regenerative medicine and Parkinson’s disease modelling. However, the precise composition and quality of human embryonic stem cell (hESC)-derived preparations at the single cell level, compared to endogenous brain standards, remains to be determined. In addition, multiple developmental pathways important for midbrain dopaminergic (mDA) neuron development remain to be implemented in hESCs. Here we use mouse developmental knowledge and human single cell RNA-sequencing (scRNA-seq) data to generate a new development-based protocol to differentiate hESCs into mDA neurons. We found that Laminin 511, dual WNT activation with CHIR99021 and WNT5A, together with FGF8b, improved different aspects of midbrain patterning. Moreover, mDA neurogenesis and differentiation were enhanced by activation of liver X receptors and inhibition of fibroblast growth factor signaling. Analysis of hESC-derived midbrain cultures by scRNA-seq revealed multiple hESC-derived clusters, which resembled those in the endogenous human ventral midbrain. Moreover, high quality mDA neurons were detected and found to progressively acquire functionality in vitro. Thus, we hereby provide a hESC differentiation protocol that recapitulates several aspects of endogenous mDA neuron development, and a strategy to determine cell composition and quality of hESC-derived preparations that can be useful for disease modeling and cell therapy.

  Study EGAS00001006313

• Kibbutzim Family study

  The Kibbutzim Family Study (KFS) was established in 1992 to investigate the environmental and genetic determinants of cardiometabolic risk factors and their change over time. The participants belong to large families living in close-knit communities, called “Kibbutzim”, in Northern Israel. The Kibbutz has been a communal settlement, which has created a relatively homogeneous environment for its members. Kibbutz members are mostly of Ashkenazi Jewish ancestry, with the remaining members belonging to other Jewish subgroups. Participants were recruited in two phases from six Kibbutzim. In the first recruitment phase of the study (1992–1993) 500 individuals from 80 extended families (range 2 to 43) were examined. During the second phase (1999–2000), all participants from the first phase were invited for repeat examinations (80% response rate) and additional new participants were recruited, giving a total of 922 individuals from 150 extended families (range 2 to 55). Families were invited to participate if they consisted of at least four individuals who (i) lived in the Kibbutz, (ii) spanned at least two generations, and (iii) were at least 15 years old. Families were retained if at least two family members consented to participate in the study. Overall, 1033 participants were recruited; 111 were examined only in the first phase, 533 only in the second phase, and 389 were included in both. 901 individuals were successfully genotyped using Illumina HumanCoreExome BeadChip.

  Study EGAS00001002782

• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847

• Roifman DAC

  This Data Access Committee will oversee all requests for data submitted by Dr. Chaim Roifman at the Hospital for Sick Children in Toronto, Canada. Requests should be directed by email to chaim.roifman@sickkids.ca.

  Dac EGAC50000000396

• RNASeq files for Mullighan_GL_reALL RNASEQ1

  RNASeq files for Mullighan_GL_reALL RNASEQ1 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005511

• RNASeq files for Mullighan ECOG2993 data

  RNASeq files for paper titled "Molecular classification improves risk assessment in adult B-lineage ALL: Patients on the international UKALLXII-ECOG2993 trial."

  Dataset EGAD00001006380

• RNAseq files for Mullighan_GL_reALL RNASEQ2

  RNAseq files for Mullighan_GL_reALL RNASEQ2 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005510