14970 results for "cancer studies using rna-seq"

in 26.66 milliseconds.

• RNA-seq of high-grade serous ovarian cancer in long-term survivors (MOCOG study)

  RNA-seq dataset of high-grade serous ovarian cancer (HGSC) tumours from long-term survivors performed as part of the Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) study. The dataset includes fastq files from 56 HGSC tumours (53 primary tumours and 3 recurrent tumours) from 53 long-term survivor patients. Libraries were generated using the Illumina Stranded mRNA Prep and 150 bp paired-end sequencing was performed to a minimum of 100 million reads on Illumina NovaSeq 6000 instruments.

  Dataset EGAD00001008537

• 10x Genomics VDJ single cell sequencing and 10x Genomics sc RNA-Seq (5 individuals/17 VDJ runs,19 scRNA runs))

  single cell RNAseq and TCR sequencing data of 5 individuals. 10x Genomics VDJ single cell sequencing (17 runs) and 10x Genomics sc RNA-Seq (19 runs). The VDJ sequencing was done on a Nextseq 550 using the Chromium Single Cell VDJ Reagent Kit. The RNA-Seq was done either on HiSeq4000 or NovaSeq 6000 using the Chromium Single Cell 5 Reagent Kit.

  Dataset EGAD00001009986

• The Adhesion GPCR ADGRL2 Engages Galpha13 to Enable Epidermal Differentiation

  We sought to determine the role of ADGRL2 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. ADGRL2, working through GNA13, was found to promote epidermal differentiation through the ADGRL2 intracellular loop 3 (ICL3) loop, using the methods of RNA-seq and Perturb-seq.

  Study phs004223

• Prostate Cancer - RNA-Seq unmapped reads

  Prostate Cancer - RNA-Seq unmapped reads

  Dataset EGAD00001003756

• RNA-Seq of serially passaged TIC-enriched spheres of colorectal cancer

  18 samples of RNA-Seq of serially passaged TIC-enriched spheres of colorectal cancer (CRC), sequenced on HiSeq2000 and HiSeq2500

  Dataset EGAD00001006264

• RNA-SEQ for the Caldas Lab breast cancer PDTX collection

  RNA-SEQ for the Caldas Lab breast cancer PDTX collection. This includes both single and paired end runs

  Dataset EGAD00001006307

• RNA-Seq datasets in human islets cultured in low glucose conditions

  7 RNA-Seq datasets in human pancreatic islets from 7 donors, where islets were using low (4mM) glucose conditions.

  Dataset EGAD00001005208

• Differential Presence of Exons in Cell-Free DNA Reveals Different Patterns in Colorectal Cancer Between Metastatic and Non-Metastatic Patients

  Tumor genotyping during disease follow-up is gaining an increasing interest for monitoring and clinical management in colorectal cancer (CRC). Growing evidences suggest that single biopsies are inefficient for molecular profiling, due to clonal evolution and intratumoral heterogeneity of primary tumors and/or metastasis. Circulating free DNA (cfDNA) has emerged as an alternative source of genetic material that seems to be representative of the continuously changing tumor molecular features. Thus, the so-called 'liquid biopsy' also offers the additional advantages of accessibility and non-invasiveness for the patient. Novel strategies based on next-generation sequencing (NGS) of cfDNA are being currently developed, with most studies focusing on targeted deep sequencing panels of potential clinically actionable genes. Here we describe an alternative approach, consisting of exome-sequencing in cfDNA at a relatively shallower depth to provide a more general overview of the circulating genome. In this study, two groups of colorectal cancer patients, with either disseminated (M) or localized disease (N), were compared using whole-exome sequencing and a RNA-seq bioinformatics analysis pipeline. Thus, a set of 379 exons present at different levels in cfDNA from both groups were identified, giving rise to a completely new concept in this field, termed as 'Differential Presence of Exons'. Differentially present exons (DPEs) were subsequently used for M and N patients clustering and classification, allowing for the design of a predictive algorithm with encouraging preliminary results in a small subset of patients that could not be initially classified attending to the selection criteria (U group, unassignable).

  Study EGAS00001002687

• Leiomyosarcoma RNA-Seq

  RNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic12 relapses) and 13 tumors treated with radiation(7 primaries, 6 metastatic relapses). RNA-Seq sequencing was performed using established protocols on Illumina HiSeq 2500

  Dataset EGAD00001006628

• Single RNA-Seq of fCAB treated tRNAs from VDH01

  Single RNA-seq of fCAB treated tRNAs from vdh01 samples (5 replicates). tRNAs were extracted using Mirvana° Invitrogen kit. The samples were prepped with Il TruSeq Small RNA and sequenced on Illumina NextSeq550.

  Dataset EGAD00001008743

• Genomic Characterization CS-MATCH-0007 Arm Z1D

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and posttreatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm Z1D is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with MMR deficiency are treated with nivolumab. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001859

• Genomic Characterization CS-MATCH-0007 Arm Y

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm Y is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with AKT mutations are treated with AZD5363. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001904

• Genomic Characterization CS-MATCH-0007 Arm H

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm H is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRAF V600K/V600E mutations are treated with Dabrafenib and Trametinib. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001888

• RNA-seq from Glioblastoma treated with Indisulam

  The dataset includes RNA-sequencing results from four patient-derived glioblastoma cell lines treated with DMSO (vehicle control) or the splicing modulating-drug indisulam (at 6 and 16 hours), resulting in 12 RNA-seq samples. Paired-end sequencing produced 24 FASTQ.gz files. The RNA libraries were prepared using PolyA selection and ERCC spike-ins and sequenced on a NovaSeq platform. This dataset supports the analysis of drug-induced transcriptomic changes and the prediction of subsequent non-canonical tumor-specific antigens (ncTSAs) using the NovumRNA pipeline.

  Dataset EGAD50000000957

• BPH Tissues for Cell Culture and Analysis - A Patient-Derived Xenograft Model Using Benign Prostatic Tissues

  Our goal was to establish and characterize a patient-derived xenograft model for benign prostatic hyperplasia (BPH) using human benign prostatic tissues. Characterization of the model was done by histology, immunohistochemistry, proteomics, and transcriptome analysis (RNAseq). The RNAseq data will be deposited in dbGaP. Subjects were undergoing prostatectomy for prostate or bladder cancer, with concurrent BPH, and consented to the use of surplus tissue for research studies. The RNAseq studies included 6 patients. Phenotypic data include patient age, sex, prostate size, serum prostate-specific antigen (PSA) level, and international prostate symptom score (IPSS). Sequencing was done on an Illumina NovaSeq 6000, and data were analyzed using Kallisto. Data are submitted as raw sequencing (fastq) files.

  Study phs003692

• Single-Cell RNA-seq of Primary High Grade Serous Carcinoma

  Single-cell RNA Sequencing of CD45- cancer cells.

  Study EGAS50000000068

• RNA alignment

  RNAseq aligned to hg38.p14 using nfcore/RNA-seq

  Dataset EGAD50000000428

• RNA-seq of CRC patient-derived xenograft tumors

  We developed a novel antibody-drug conjugate (ADC), 84-EBET. To analyze mechanism of action of 84-EBET, we obtained bulk RNA-seq data of the patient-derived xenograft (PDX) model derived from colorectal cancer (CRC) patient. The PDX model was treated with 5-fluorouracil + oxaliplatin, 84-EBET or vehicle, and then gene expression changes were analyzed with bulk RNA-seq.

  Study EGAS50000000598

• Genentech Small Cell Lung Cancer (SCLC) Screen

  Exome capture, RNA-Seq, whole genome sequencing of set of Small Cell Lung Cancer samples.

  Study EGAS00001000334

• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. FInally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Study EGAS00001004064

• RNA-Seq of response to Tozinameran vaccination in individuals with KTx/dialysis or healthy controls.

  Low-input RNA-Seq (~200 cells per sample) of CD4+ T cells in patients with kidney transplants, dialysis, or healthy controls after the second dose of Tozinameran COVID-19 vaccine. RNA-Seq was performed using the Smart-Seq v4 ultra-low input protocol. The dataset includes 4 healthy control samples, 3 kidney transplant recipients, and 4 patients undergoing dialysis.

  Dataset EGAD00001007689

• Gastric cancer RNA-seq data

  strand-specific RNA-seq data from 19 gastric tumors and their adjacent normal tissues, plus 16 gastric cancer cell lines, one normal gastric cell line, and 3 normal stomach RNAs

  Dataset EGAD00001003448

• Prostate Cancer - RNA-Seq unmapped reads

  Prostate Cancer - RNA-Seq unmapped reads

  Dataset EGAD00001004424

• Transcriptomic Profiles of Neoantigen-Reactive T Cells in Human Gastrointestinal Cancers

  This study explores the transcriptomic profiles of neoantigen-reactive tumor-infiltrating lymphocytes (TILs) from human bile duct and pancreatic cancer. The submitted data are bulk tumor RNA-Seq, tumor and germline whole-exome sequencing from 10 patients, and single cell RNA-Seq data from TIL of 5 of these patients.

  Study phs002765

• Multi-omics analysis of cocaine use disorder in postmortem brain tissue of the ventral striatum [Proteomics data to study EGAS50000000623]

  We performed a multi-omics analysis of cocaine use disorder in postmortem human brain tissue of the ventral striatum in N=41 individuals (N=20 CUD cases, N=21 non-affected individuals). From the postmortem brain tissue samples, we generated miRNA-seq, RNA-seq, proteomics, and snRNA-seq data. The miRNA-seq, RNA-seq and snRNA-seq datasets can be found in the EGA under study ID EGAS50000000623. Proteomics data is deposited under study ID EGAS00001007945 (this study). The proteomic dataset was obtained using TMT-labeling. Measurement was performed on an Orbitrap Fusion Lumos device.

  Study EGAS00001007945

• Whole Genome Sequencing of HCC

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002888

• OncoArray: Oral and Pharynx Cancer

  Genetic factors play an important role in susceptibility to head and neck cancer and could also explain differences in response to treatment and outcome. The goal of this project is to investigate genetic variation involved in oral and oropharyngeal cancer susceptibility by performing the largest GWAS on these diseases, using a novel genotyping tool specifically designed for cancer studies by the OncoArray Network. This project encompasses data from approximately 6000 oral and pharynx cancer cases and 4000 controls derived from 12 epidemiological studies most of case-control design. The genotyping was centralized at the Center for Inherited Disease Research (CIDR), and the epidemiological data harmonization and analysis were completed at the International Agency for Research on Cancer (IARC). This study was supported by National Institute of Dental and Craniofacial Research (NIDCR) with direct funding to CIDR.

  Study phs001202

• RNA-Seq data from tumor samples collected from 12 UTSW translocation renal cell carcinoma (tRCC) patients.

  This study investigates differentially expressed genes associated with the progression of translocation renal cell carcinoma (tRCC) by analyzing RNA-Seq data from 23 tumor samples obtained from 12 patients. The samples were collected from affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital and Children’s Medical Center. RNA isolated from tumor samples was sequenced using the Illumina platform.

  Study EGAS50000000127

• Exploring_the_heterogeneity_of_sarcoma_using_single_cell_sequencing_

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002866

• 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

• Understanding the Progression of Metastatic Colorectal Cancer

  This study is to understand (1) the clonal evolution of metastatic colorectal cancer using DNA sequencing and (2) long non-coding RNAs associated with metastatic colon cancer using RNA sequencing. Our goal is to better understand the progression of aggressive colorectal cancer.

  Study phs001722

• RNA-seq reads

  Cancer RNA-seq consisting of FASTQ paired-end reads from ovary samples

  Dataset EGAD00001003918

• The cellular state space of AML unveils novel NPM1 subtypes with distinct clinical outcomes and immune evasion properties

  Acute myeloid leukemia (AML) is a genetically and cellularly heterogeneous disease. We characterized 120 AMLs using bulk genomic and transcriptomic analyses (WES, MP-WGS, RNA-seq), and single-cell RNA sequencing (scRNA-seq). Our results reveal an extensive cellular heterogeneity that distorts the bulk transcriptomic profiles. Notably, NPM1 mutated AML could be stratified into two novel, clinically relevant classes (NPM1class I and NPM1class II).

  Study EGAS50000001084

• Landscape of somatic mutations and DNA copy number alterations and transcriptomic profiling identifies metabolic reprogramming as a hallmark of ibrutinib resistance

  Whole-exome sequencing (WES) was conducted on the clinical specimens of 14 cases that had sufficient isolated tumor DNA, including 7 ibrutinib-sensitive cases and 7 ibrutinib-resistant cases. Whole transcriptome sequencing (RNA-seq) was performed on clinical specimens isolated from 14 ibrutinib-sensitive and 7 ibrutinib-resistant cases. Unsupervised hierarchical clustering of MCL tumors using RNA-seq gene expression data showed a response-specific gene expression signature.

  Study EGAS00001003418

• Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation

  We tested the efficiency and reproducibility of 10 RNA isolation methods on 5 different biofluids. Pooled human plasma and serum, bile and urine were used along with cell culture supernatants from human embryonic stem cells (hESC), primary neonatal rat ventricular myocytes (NRVM) and human cholangiocarcinoma cells (KMBC). 4 RNA isolation methods designed to isolate total RNA from bio fluids without enrichment of exRNA carriers were used. 6 methods that preferentially enriched for exRNA carriers were also compared. Small RNA libraries were constructed using the NEBNext small-RNA library prep. The efficiency and reproducibility of the different RNA isolation methods was compared using small-RNA seq.

  Study phs002143

• Single-cell RNA-seq and TCR-seq of synovial tissue and peripheral blood CD4+ and CD8+ T cells from patients with immune-mediated refractory arthritis

  In this study, we investigated CD4+ and CD8+ T lymphocytes from the synovial tissue and peripheral blood of patients with treatment-resistant immune-mediated arthritis using paired single-cell RNA and TCR-sequencing.

  Study EGAS50000000528

• A Phase I Study with a Personalized Neoantigen Cancer Vaccine in Melanoma

  Effective anti-tumor immunity in humans has been associated with presence of T cells targeting neoantigens that arise from non-silent tumor-specific mutations. Here we conducted whole-exome sequencing of tumor and normal cells from individual patients to identify mutations. We assessed the expression of mutated alleles by RNA-sequencing of tumor. We demonstrated the feasibility, safety and immunogenicity of a vaccine that targets up to 20 personal neoantigens predicted to be presented by the autologous patient tumor.Antigen-specific CD8+ T cells that can recognize and eliminate cancer cells play a crucial role in anti-tumor immune responses. Here we conducted single-cell sequencing of cells infiltrating melanoma specimens originating from 4 patients and determine the TCR clonality of the CD8+ tumor infiltrating cells. We investigated the relationship between T cell clonality and phenotypic cell states coupling single-cell transcriptome to single-cell TCR seq. The surface expression of a panel of protein was detected in parallel using CITE-Seq antibodies. Sorted tumor and peripheral blood specimens were processed in parallel.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out matched ribosome profiling (Ribo-seq), RNA-sequencing, and whole genome sequencing on one of the patients, as well as Ribo-seq on an additional patient. We used it to discover novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001451

• RNA-seq study of a Princess Margaret Cancer Centre human acute myeloid leukemia patient cohort

  The PMCC AML RNAseq dataset consists of 81 AML patient samples (clinical data in Supplemental Table 11 of manuscript), processed in two batches. These patient samples are able to engraft in the NSG (NOD.Cg PrkdcscidIl2rgtm1Wjl /SzJ) mouse model. Five patients (90543, 598, 90240, 110484, 100500) were included in both batches. Viaably frozen material from the Leukemia Tissue Bank at Princess Margaret Cancer Centre/ University Health Network were thawed by dropwise addition of X-VIVO + 50% fetal calf serum supplemented with DNase (100μg/mL final concentration, Roche). RNA was extracted from bulk peripheral blood mononuclear cells (PBMC) using the RNeasy Micro Kit (Qiagen Inc.). A paired-end 76 base-pair flow-cell lane Illumina High seq 2000 yielded an average of 240 million sequence reads aligning to genome per sample at the Genome Sciences Centre, BC Cancer Agency for cohort 1. Cohort 2 was subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Centre for Applied Genomics, Sick Kids Hospital.

  Dataset EGAD00001006576

• Genomic Characterization of Metastatic Castration Resistant Prostate Cancer

  Biopsies of castration resistant prostate cancer metastases were subjected to whole genome sequencing (WGS), along with RNA-sequencing (RNA-Seq). The overarching goal of the study is to illuminate molecular mechanisms of acquired resistance to therapeutic agents, and particularly androgen signaling inhibitors, in the treatment of metastatic castration resistant prostate cancer (mCRPC).

  Study phs001648

• Endometrial Cancer Association Consortium - OncoArray Genotypes

  The data come from 9 studies participating in the Endometrial Cancer Association Consortium (ECAC). ECAC data included in this dbGaP submission include OncoArray data from 4486 endometrial cancer cases genotyped at the Center for Inherited Disease Research (CIDR). Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in O'Mara et al, Identification of nine new susceptibility loci for endometrial cancer. Nature Communications (PMID:30093612).

  Study phs001885

• RNA-seq of iPSC-derived hepatocyte-like cells

  We performed RNA-seq on polyA-enriched mRNA isolated from the original liver biopsy tissue (Liver tissue), primary liver cells (PLC), hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs), and iPSCs. RNA libraries were prepared using the Illumina TruSeq Stranded mRNA Sample Preparation protocol (ref. RS-122-2101, Illumina, San Diego CA, US) and sequenced using the Illumina HiSeq2500 platform following the manufacturer’s protocol. Samples were sequenced in paired-end mode to a length of 2x76 base pairs. Images from the instrument were processed using the manufacturer’s software to generate FASTQ sequence files.

  Dataset EGAD00001003770

• University of Washington Cerebrospinal Fluid Biomarker Study for Parkinson disease

  There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis and monitoring disease progression. In this study we evaluated cerebrospinal fluid (CSF) proteins, which are known to be critically involved in PD or identified in our preliminary profiling studies, aptamers, and RNAs as potential PD biomarkers. Access to subjects for this study was via the Pacific Northwest Udall Center (PANUC) and the Alzheimer's Disease Research Center (ADRC) at the University of Washington and Oregon Health and Sciences University (OHSU). Using CSF samples from 30 well-characterized patients with PD and 30 age-, sex-matched healthy controls, we prepared RNA seq libraries and performed deep sequencing of all RNA species, including small and long RNA, mRNAs, noncoding RNAs and differentially spliced transcripts. We then tried several methods for RNAseq data analysis to optimize our analysis pipeline. We identified a total of 3381 transcripts corresponding to 182 long intergenic RNAs (LincRNAs), 11 microRNAs (miRNAs), 2861 protein-coding transcripts, 200 pseudogenes and 127 antisense RNAs; some of them were differentially expressed between PD and control groups. Selected differentially expressed RNAs have been validated in the same set of CSF samples using real-time PCR (RT-PCR). Further validations in independent, larger cohorts of samples are still ongoing. Our results obtained so far suggested that CSF proteins and RNAs could be used as good indexes for PD diagnosis and disease severity/progression. This study is a part of the NIDDS-funded Parkinson's Disease Biomarkers Program (PDBP).

  Study phs000901

• RNA-seq

  Stranded RNA-seq libraries were performed for 150 ng of mRNA using the TruSeq library kit (Illumina, San Diego, CA, USA). Libraries were sequenced on a NextSeq 2000 (Illumina) in a 2x50bp length.

  Dataset EGAD00001010841

• Human tumor single-nuclei RNA-seq

  We profiled 4 patient neuroblastoma-FORX2 tumor samples by single-nuclei RNA-seq using 10X Chromium 3'. The raw fastqs are provided.

  Dataset EGAD00001010903

• Functional Enhancer Elements Drive Subclass-Selective Expression From Mouse to Human Neocortex

  A complete epigenomic map of human brain cell types will be necessary to fully understand their genetic regulation, and to create the next generation of non-species-restricted genetic tools for their functional characterization. Here we performed both bulk and single-nucleus ATAC-seq studies of fresh human neocortical samples excised during neurosurgery, in order to discover the functional genomic elements that discriminate cell types. This dataset contains 78 bulk layer-dissected ATAC-seq samples, and 3660 single-nucleus ATAC-seq samples from fresh acutely isolated human neurosurgical samples. Furthermore, from these data we identified and validated several enhancers for use in AAV context. We also provide validation single cell RNA-seq for 456 human acutely labeled neurosurgical neurons labeled by 3 unique enhancer-AAV vectors, and single cell RNA-seq for 1483 mouse neurons labeled in vivo by 11 unique enhancer-AAV vectors. Together these datasets provide high-resolution maps of single human neocortical cell types, as well as proof of the functional utility of the genomic elements discovered. As a whole these data will be important to furnish the next generation of cell type-specific functional tools and therapies in neuroscience.  

  Study phs002292

• RNA-Seq files for St. Jude Clinical Pilot

  This dataset contains whole genome sequencing BAM files for 78 tumor-normal pairs (a total of 156 samples) used in the St. Jude Clinical Pilot. Mapping was performed using BWA. This dataset accompanies the paper "Clinical Cancer Genomic Profiling by Three-Platform Sequencing of Whole Genome, Whole Exome and Transcriptome"

  Dataset EGAD00001004280

• DRIP-seq data for Molecular Characterization of ETMRs

  This dataset contains DRIP-seq data from 2 patients. DNA–RNA hybrids were extracted from tissue derived from ETMR patient-derived xenograft (PDX) models (BT183) that were treated using topotecan or saline as described previously27. Tumours were subsequently frozen and pelleted using ultracentrifugation. DNA–RNA hybrids were extracted as described previously using the same protocol that is applied for cultured cells21. DNA was extracted using proteinase K followed by phenol–chloroform extraction and ethanol precipitation. Subsequently the DNA was fragmented using the restriction enzymes HindIII, EcoRI, BsrGI, XbaI and SspI (New England Biolabs). Digested DNA was subsequently incubated with the anti-DNA–RNA hybrid anti- body S9.6 (Merck, MABE1095) and immunoprecipitated using agarose beads. Bound DNA–RNA hybrids were eluted and incubated with pro- teinase K and cleaned with an additional phenol–chloroform–ethanol extraction. The DNA was subsequently sonicated and sequenced using a Hiseq 2000 machine with a 50-bp single-read protocol. Each treat- ment condition was performed in duplicate and both RNase H and the input was included as negative controls resulting in 10 Fastq files.

  Dataset EGAD00001006219

• RNA-seq on patients 1-4, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. RNA-seq of twelve samples, tumour and benign tissue, from the four initial patients.

  Dataset EGAD00001001345

• RNA-seq assessment of the impact of fasting-mimicking diet on tumor tissue specimens from early-stage breast cancer patients

  RNA-seq data (44 samples) from tumor tissue specimens pre and post fasting-mimicking diet from 22 early-stage breast cancer patients.

  Dataset EGAD00001006860

• Prostate Cancer and Normal Adjacent Prostate RNA-seq samples, NGS-ProToCol

  The dataset "Prostate Cancer and Normal Adjacent Prostate RNA-seq samples, NGS-ProToCol" includes 41 Normal Adjacent Prostate and 51 ribo-depleted Prostate Cancer RNA-seq samples. ---- Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data Youri Hoogstrate, Malgorzata A. Komor, René Böttcher, Job van Riet, Harmen J. G. van de Werken, Stef van Lieshout, Ralf Hoffmann, Evert van den Broek, Anne S. Bolijn, Natasja Dits, Daoud Sie, David van der Meer, Floor Pepers, Chris H. Bangma, Geert J. L. H. van Leenders, Marcel Smid, Pim French, John W.M. Martens, Wilbert van Workum, Peter J. van der Spek, Bart Janssen, Eric Caldenhoven, Christian Rausch, Mark de Jong, Andrew P. Stubbs, Gerrit A. Meijer, Remond J.A. Fijneman, Guido Jenster

  Study EGAS00001002816

• RNA-seq

  The RNA was extracted using the AS1390 PROMEGA kit according to the manufacturer’s instructions. The samples underwent sequencing using a Novaseq 6000 machine, equipped with an SP 200 cycles v1.5 cartridge. The sequencing process varied slightly across batches based on the input RNA and the library preparation kits used.

  Dataset EGAD50000002023

• National Cancer Institute (NCI) Biospecimen Pre-analytical Variables (BPV) Analysis

  The Biospecimen Pre-analytical Variables (BPV) Program is a National Cancer Institute-sponsored study to systematically assess the effects of pre-analytical factors on the molecular profile of biospecimens. A robust biospecimen collection infrastructure was established to prospectively collect biospecimens using rigorous standard operating procedures to control for most variables while introducing experimental conditions to study specific biospecimen handling issues, including the cold ischemic time (delay to formalin fixation), time in formalin, freezing methods, and storage temperatures and durations. RNA and DNA from biospecimens collected under these conditions was analyzed on multiple molecular platforms. The potential effects of these pre-analytical conditions on protein integrity and detection of metabolites were also examined. Data from this study will be used to develop evidence-based biospecimen standard operating procedures and best practices for fit-for-purpose collection, processing, and storage of biospecimens. The BPV Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following sub-studies below or in the "Substudies" box located on the right hand side of this top-level study page phs001304 BPV Cohort. The substudy links will be active once they are released by dbGaP. Preanalytical Impacts on Global Metabolite Profiling - plasma (MassSpec by Metabolon) This study was to evaluate the impact of the storage temperature (s) (-80°C and LN2 vapor) and the length of storage on human plasma quality using LC-MS/MS (liquid-chromatography-mass spectrometry/mass spectrometry) based global metabolite profiling. The study includes 240 plasma samples collected from 40 donors. Investigate the effect of the delay to fixation on the proteome and phosphoproteome -FFPE (MassSpec by Caprion). The study is to do proteome and phosphoproteome analysis on Delay to fixation was carried out using FFPE tumor samples from colon and ovarian cancer patients comparing 2, 3, and 12hr delay to fixation to the 1hr time point. The study includes 100 samples 20 donors. Investigate the effect of storage conditions of tumor specimens on the proteome and phosphoproteome profiling- Frozen tissue and plasma (MassSpec by Caprion). The study was to evaluate the effects of storage conditions on tumor specimens. Plasma samples from 40 cancer patients stored at two different temperatures (-80°C and LN2) for a given period (0-2, 6-8, and 12-14 months) were evaluated. Frozen kidney tumor samples from 20 patients were compared for effects of different snap frozen (dry ice vs. LN2) and storage temperatures (-80°C and LN2). The study includes 100 tissue and 240 plasma samples from 60 donors. Preanalytical Impacts on Genomic Sequencing by Next Generation Sequencing (NGS) technology (mRNA/miRNA and WES by Expression Analysis). The goal of the study is to determine the effects of cold ischemic delay-to-fixation (4 time points) and formalin preservation (FFPE) on the nature and quality of genomic profiles using the matched freshly frozen sample as the gold standard, which including WES, RNAseq. The study includes 395 samples from 37 donors. Preanalytical Impacts on Copy Number Variation (CNV) Detection by aCGH technology (aCGH by Georgetown University). This study was to use aCGH to evaluate the effect of variation in cold ischemia time and time in formalin fixation on CNV in DNA extracted from kidney cancer specimens. The study includes 235 samples from 40 donors. Evaluation of frozen conditions on mRNA profiling by TaqMan assay (mRNA expression by Georgetown University). This study was to utilize gene expression profiling, using custom TaqMan arrays, to compare the molecular profiles of RNA from frozen tumor samples collected using two freezing methods (dry ice or LN2), two storage temperatures (-80°C or LN2 vapor), as well as Optimal Cutting Temperature (OCT) compound and non-OCT embedded. The study includes 100 samples from 20 donors. mRNA signature for stratification by cold ischemia time (mRNA expression by IBBL). The study was to determine the effects of cold ischemic time (delay-to-fixation) and formalin preservation (FFPE) on mRNA detection by Taqman assay using tumor tissue specimens from kidney, colon and ovarian cancer patients. There are160 samples from 40 donors. The Biospecimen PV cohort is utilized in the following dbGaP individual studies. To view molecular data, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001304 Biospecimen PV cohort. phs001634 CIT mRNA phs001635 CNV aCGH phs001636 Fixation Delay phs001637 Global Metabolite Profiling phs001638 mRNA TaqMan phs001639 NGS phs001640 Tumor Storage

  Study phs001304

• RNA-seq data of proliferative vitreoretinal diseases and healthy human retinal pigment epithelium

  This dataset contains RNA-seq data generated from surgical specimens of proliferative vitreoretinal diseases (including proliferative vitreoretinopathy and epiretinal membranes) and from retinal pigment epithelial cells isolated from post-mortem donor eyes. Total RNA was extracted and cDNA libraries were prepared using the Ovation Solo RNA-seq Kit (Tecan). Sequencing was performed on the Illumina NovaSeq 6000 platform. Raw FASTQ files are included to enable downstream analyses such as gene expression profiling.

  Dataset EGAD50000001780

• RNA-Seq data of S24 cells for the publication Recording physiological history of cells with chemical labeling.

  Recordings of elevated calcium levels allowed selections of cells from heterogenous populations for transcriptomic analysis. Paired RNA-Seq from S24 cells using Takara SMARTer Ultra Low Input RNA v4 kit and sequencing on a Illumina NovaSeq 6000.

  Dataset EGAD50000000082

• 110 "KOREAN" never-smoker female adenocarcinoma RNA-seq

  All sequencing was performed within the DNAlink (Korea) by using the Solexa sequencing technology (Illumina, San Diego, CA). mRNA was isolated from total RNA using poly-T oligo-attached magnetic beads and was fragmented with fragmentation buffer to an average size of 300 bp. The libraries were prepared by using TruSeq RNA Library Prep Kit v2 (Illumina) and were sequenced on the Illumina HiSeq2000 using the manufacturer’s recommended protocols

  Dataset EGAD00001005358

• Spatially resolved transcriptomics reveals profound subclonal heterogeneity and T cell dysfunction in extramedullary myeloma

  Investigating the spatial architecture and microenvironment of EMD lesions in Multiple Myeloma patients using spatial whole transcriptome sequencing (10X Visium), tomography for spatially resolved transcriptomics (TOMO-seq), and single-cell RNA sequencing (scRNAseq)

  Study EGAS50000000227

• InsPIRE islets

  We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

  Study EGAS00001003997

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169

• Epigenetic, transcriptome and TF analysis of human NK cell and T cells

  RNA-seq 10 subsets; 5 donors. ATAC-seq 9 subsets, 4 donors; Histone modification profiling 10 subsets, 2 donors all using human NK cell and T cell subsets. TF ChIP-seq Bcl11b, Bach2, Runx2, Gata3, PLZF. Illuminia sequencing platform, ATAC-seq is Paired-end, RNA-seq/ChIP-seq is Single-end

  Dataset EGAD00001008449

• Human tumor single-cell RNA-seq

  We profiled 16 patient tumor samples by single-cell or single-nuclei RNA-seq using 10X Chromium 3'. It includes 4 low-grade gliomas and 12 ependymomas. The raw fastqs are provided.

  Dataset EGAD00001011315

• single cell RNA-seq of small cell lung cancer circulating tumor cells

  This study investigated the transcriptomic profile of circulating tumor cells from three small cell lung cancer patients. CTCs were enriched from the blood of three SCLC patients using the CTC-iChip followed by magnetic depletion of RBCs. The enriched samples were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system.

  Study EGAS50000001401

• The single plasma-cell transcriptional landscape in POEMS syndrome

  POEMS syndrome is a rare monoclonal plasma cell disorder that shows unique symptoms distinct from other plasma cell neoplasms, including high levels of serum VEGF; however, none of the previous studies have succeeded in direct identification of plasma cell clones in POEMS syndrome, leaving their real nature obscure.���We herein performed single-cell RNA sequencing (scRNA-Seq) of bone marrow (BM) plasma cells from patients with POEMS syndrome. These data unveil unique features of POEMS clones among plasma cell neoplasms and enhance our understanding of the pathogenesis of POEMS syndrome.

  Study JGAS000289

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Tissue Biopsy Study

  The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits (QTs). Most of the variants associated with T2D and related traits (glucose and insulin, anthropometrics, lipids) through genome-wide association studies (GWAS) occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Regulatory element activity is often tissue-specific, which further complicates discovery of the causal/functional variation. Therefore, there is a critical need to identify the appropriate cell type, regulatory elements, target genes, and causal variants(s) in T2D-relevant tissues. We hypothesize that a subset of T2D and related variants alter gene expression regulation in skeletal muscle and adipose tissue - two major insulin target tissues and play key roles in insulin resistance. To that end, our study contains a comprehensive survey of genomics, epigenomics and transcriptomics in skeletal muscle and adipose tissue from individuals with glucose tolerance categories ranging from normal to T2D.For this FUSION Tissue Biopsy Study, we obtained RNA-Seq, microRNA (miRNA)-Seq, and DNA methylation (methyl)-Seq data on biopsy samples from 331 individuals from across the range of glucose tolerance: 124 normal glucose tolerance (NGT), 77 impaired glucose tolerance (IGT), 44 impaired fasting glucose (IFG), and 86 newly-diagnosed T2Ds. Participants completed two study visits, two weeks apart. First visits comprised most of the clinical phenotyping, including four-point OGTT (fasting, and 30, 60, and 120 minute post-load); BMI, WHR; lipids; blood pressure; and many other variables. Participants also completed FUSION health history, medication, and lifestyle questionnaires. On the second visit, we obtained ~250mg vastus lateralis skeletal muscle, ~750mg abdominal subcutaneous adipose, and a ~5x15mm section of abdominal skin. Visits were completed in March 2013. RNA isolation is ongoing in the Collins laboratory at the NIH, RNA and miRNA sequencing at the NIH Intramural Sequencing Center (NISC), and genotyping at the Center for Inherited Disease Research (CIDR). Individual-level data is available here for the 306 individuals who consented to data deposit. To focus on evaluation of gene expression and its regulation in skeletal muscle, we analyzed mRNA extracted from vastus lateralis skeletal muscle obtained from 271 of the 331 individual subjects from Finland, along with genome-wide genotypes. Individual-level data is available here for the 250 subjects who consented to the use of their data.Release phs001048.v2.p1 adds muscle data for an additional 42 subjects and data from adipose tissue for 276 subjects. Total RNA was isolated using Trizol extraction in the Collins laboratory at the NIH. The mRNA was poly-A selected, 24-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol and RNA sequencing was performed on HiSeq2000 sequencers using 101bp paired-end reads at NISC. miRNA libraries were prepared from total RNA from 296 muscle and 270 adipose samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. Data for 272 muscle and 251 adipose samples are available here for individuals with consent for data deposit. DNA was extracted from blood in the Collins laboratory, and genotyping on the Illumina Omni2.5M array was performed at CIDR. Genotypes were imputed using the HRC 2016 reference panel. In order to assess regions of open chromatin in skeletal muscle, we obtained muscle tissue from a commercial provider to perform ATAC-seq; these samples were sequenced at the University of Michigan DNA Sequencing Core.Release phs001048.v3.p1 adds single-nucleus (sn) RNA-seq and ATAC-seq data in 287 skeletal muscle samples out of the original 331 individuals. Individual-level data is available here for the 265 subjects who consented to the use of their data. The frozen tissue biopsy samples were processed in ten batches, each consisting of 40-41 samples. These batches were organized using a randomized block design to protect against experimental contrasts of interest including cohort, age, sex, BMI among others. Samples in each batch were pulverized, pooled together followed by nuclei isolation. The nuclei were processed on the 10X Genomics Chromium platform separately for snATAC-seq and snRNA-seq (v. 3.1 chemistry for snRNA-seq).Release phs001048.v4.p1 adds additional phenotypes and provides some corrections to several previous phenotypes.

  Study phs001048

• RNA-seq data from 27 glioblastoma samples

  27 Fresh frozen tissue specimens were crushed by mortar and pestle, homogenized using the QIAShredder kit (Qiagen), and genomic DNA and total RNA were extracted using the AllPrep DNA/RNA Mini kit (Qiagen), according to the manufacturer’s instructions. RNA libraries were synthesized using 200 ng of total RNA using the Ilumina TruSeq Stranded RNA LT Sample Prep Kit (Illumina), and subsequently sequenced on the NextSeq550 platform to a read depth of 80 million clusters and 160 million paired end reads (75 bp X 75 bp) using V2 chemistry.

  Dataset EGAD00001008362

• Breast Cancer - immune clusters - RNA-seq

  In this study we use expression data from breast cancer tumors to define immune clusters in breast cancer. Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further using gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.

  Study EGAS00001003631

• Single-nuclei RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei RNA sequencing of 9 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. snRNA-seq was performed using the ‘Frankenstein’ protocol (dx.doi.org/10.17504/protocols.io.bqxymxpw). Briefly, nuclei were extracted from frozen tissues and subjected to fluorescence-activated nuclei sorting (FANS) using 4′,6-diamidino-2-phenylindole (DAPI). Sorting was performed using a BD FACSaria 2 instrument, sorting between 3000 and 10,000 nuclei per sample, capturing both diploid and tetraploid populations. FAN-sorted nuclei were immediately processed using either the 10x Chromium Single Cell 5’ (PN-1000006, 4 samples) or 3’ (PN-1000075, 4 samples) Library & Gel Bead Kit (10x Genomics, USA). Once processed, snRNA-seq libraries were sequenced on the Illumina Nova-Seq 6000 (Illumina, USA) using 150bp paired-end sequencing. This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000505

• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Single-cell RNA sequencing was performed on a cetuximab-sensitive metastatic colorectal cancer (mCRC) patient-derived xenograft (PDX) model. The objective of this analysis was to assess whether the transcriptional patterns identified in the single-cell RNA-seq data of matched organoids were preserved in the in vivo context.

  Study EGAS50000001459

• RNA-seq dataset

  RNA-seq data from CD20+ sorted cells obtained from peripheral blood and lymph node Follicular Lymphoma patients. These samples were unstimulated after thawing and additionally, peripheral blood samples were stimulated during 7 days in culture as described in Dobaño-López C et al. Stranded RNA-seq libraries were performed using the TruSeq library kit (Illumina, San Diego, CA, USA). Libraries were sequenced on a NextSeq 2000 (Illumina) in a 2x50bp length.

  Dataset EGAD50000000347

• An Ultrasensitive Method for Detection of Cell-Free RNA

  Our study describes the development of a novel method for cell free RNA (cfRNA) analysis called RARE-Seq (Random priming & Affinity capture of cell-free RNA fragments for Enrichment analysis by Sequencing). We find RARE-Seq improves the limit of detection for tumor-naïve cancer detection while maintaining high specificity. We explore the potential utility of RARE-Seq in diverse clinical applications, including non-invasive ctRNA genotyping, treatment resistance monitoring, and molecular characterization of non-malignant conditions.

  Study phs004091

• Genomic landscape of metastases from 97 patients with metastatic urothelial carcinoma

  Data generated from three prospective institution-wide tumor sequencing studies (SHIVA01 [NCT01771458], MOSCATO-01 [NCT02613962], and MATCH-R [NCT02517892]) to analyze the genomic landscape of metastases from 97 patients with mUC by performing both whole exome sequencing (WES) and whole-transcriptome sequencing (RNA-seq)

  Dataset EGAD50000000550

• Microbiome cross talk, Fusobacterium n. and formate metabolite

  This data comes into 2 pairs of experiments: - RNA-seq Control versus Formate treated colorectal cancer T18 cells - Humix device, RNA-seq of control versus co-culture colorectal cancer T18 cells with Fusobacterium nucleatum

  Dataset EGAD00001008533

• UIC HNSCC RNA-Seq and miRNA-Seq Data

  This dataset contains matched RNA-Seq and miRNA-Seq fastq files from 109 match samples of 34 human Papillomavirus-negative Head and Neck cancer patients, including 72 lymph nodes, 29 tumor and 8 normal samples.

  Dataset EGAD00001004489

• Human Pancreatic Islet RNAseq - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004042

• GWAS data on human pancreatic islets from 191 donors - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004044