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• Data for noninvasive lung cancer subtyping study

  This dataset included cfMethyl-Seq data of 15 plasma cfDNA samples from 15 lung cancer patients and RRBS data of 58 lung tumor tissue samples from 58 lung cancer patients. The data were generated following the standard protocols.

  Dataset EGAD00001015344

• Dataset for Ewing_sarcoma_PNET-WHOLE_GENOME

  Rare cancer sequencing data of 18 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008874

• Fecal 16S HV sequencing data

  Fecal 16S-V4 rRNA gene sequence data from NCT02749630 healthy volunteers. Stool samples were collected at screening as well as on days 29, 43, 64, 85, and 134 processed for 16SV4 rRNA gene sequencing

  Dataset EGAD00001008840

• Dataset for colorectal_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 54 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008872

• Dataset for LCPlus_WES

  WES/WGS sequencing data of 86 chromothriptic tumor and control runs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001009273

• 17 scRNAseq samples

  17 samples were processed for single cell RNA sequencing (SORT-seq)

  Dataset EGAD00001007523

• Dataset for NSCLC-EXON

  Rare cancer sequencing data of 42 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008892

• WGS of T-cell and NK-cell lymphoma for ICGC (NKTL-SG)

  WGS of T-cell and NK-cell lymphoma The tumor samples were sequenced with Illumina HiSeq 2500 platform and the resulting FASTq files have been uploaded.

  Dataset EGAD00001003271

• Bulk RNA from sorted CD8+ T cells after 48h co-culture with human Mito-DsRed MSCs.

  For human samples, total cellular RNA was isolated from post-sorted Mito+ and Mito CD8+ cells using the RNeasy Mini Kit (Qiagen). Stranded RNA libraries were created using SMARTSeq Stranded.

  Dataset EGAD00001011082

• paired-end FASTQ files from the study: Identification of the cause of juvenile parkinsonism in a case_SYNJ1

  The dataset consists of three samples: two controls and one case of juvenile Parkinsonism. Whole Exome Sequencing (WXS) was performed on these samples using hybrid selection for library preparation. Sequencing was carried out on the Illumina NextSeq 500 platform. For each sample, two FASTQ files containing paired-end reads (R1 and R2) were generated. The data deposited consists of the corresponding FASTQ files.

  Dataset EGAD50000000413

• ST dataset from subcortical white matter MS lesions (CA & CI) and controls

  This dataset contains the FASTQ files, the correspondent H&E pictures with the fiducial frames and the json files that were used for the spatial transcriptomic analysis in our paper (n=19). Within the json files names, one can find the information about the slide name (V11M111-111) and the capture area (A1) for each sample.

  Dataset EGAD50000000520

• RNA-seq of der(1;7)(q10;p10) myeloid neopalsms

  This data set contains the RNA-seq BAM files for der(1;7)(q10;p10) MDS cases, -7/del(7q) MDS cases, and OTHER MDS cases. The CD34 selected RNA were collected from patient BM/PB. The dataset was used to identify the unique expression profiles for der(1;7)(q10;p10) MDS cases compared to non-der(1;7)(q10;p10) MDS cases.

  Dataset EGAD50000000985

• scRNA-seq of Patient-derived tumor fragments (PDTFs)

  scRNA-seq of Patient-derived tumor fragments (PDTFs) which were treated with either Isotype (DP47), Isotype-IL2v (DP47-IL2v), anti-PD1 (PembroPGLALA) or PD1-IL2v (PembroPGLALA-IL2v) for 48 hours. Dataset content: 10 samples from 3 donors File type: paired-end fastq files Protocol: Chromium Single Cell 3' Reagent Kits User Guide (Dual Index) with Feature Barcoding technology for Cell Surface Protein (CG000317) Technology: Illumina sequencing Experimentation: scRNA-seq using the 10X technology

  Dataset EGAD50000000584

• Emirati Phased Diploid Trio-Assemblies (27 Individuals, 54 Assemblies)

  This dataset comprises 27 phased diploid genome assemblies (i.e., 54 haplotypes) from Emirati family trios, provided in FASTA format. Sequencing used PacBio HiFi reads generated on the Revio platform at ≥25× coverage for each parent and offspring. Assemblies were produced with hifiasm (trio mode), then scaffolded with NTLink and reference-guided merging via RagTag against CHM13v2. The collection offers haplotype-resolved references suitable for downstream variant discovery and pangenome analyses.

  Dataset EGAD50000001755

• RNA-seq TPMs quantification for baseline tumor samples originating from IMpower150, and relevant clinical metadata

  This dataset includes full tumor transcriptomes from 558 advanced NSCLC tumors. These data originate from pre-treatment samples from a clinical trial for first-line non-small cell lung cancer (IMpower150). The patients in this trial were treated with the PD-L1 inhibitor atezolizumab +bevacizumab + chemotherapy or bevacizumab + chemotherapy or atezolizumab + chemotherapy.

  Dataset EGAD50000001814

• Khoe-San Genome Project

  The dataset contains BAM files of whole genome sequencing data of African Khoe-San population (n=169, 30X coverage). DNA extracted from blood underwent 2 × 150 bp sequencing on the Illumina HiSeq X instrument (Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research). Raw sequencing reads were aligned against human reference hg38 including alternative contigs using bwa (v.0.7.15). The Genome Analysis Toolkit (GATK, v.3.5-0) was used for duplicate marking, indel realignment and base quality recalibration.

  Dataset EGAD50000002043

• Transcriptional profiles of Kleefstra syndrome (EHMT1 and EHMT2) and healthy iPSCs

  This dataset contains FASTQ files from RNA sequencing (RNA-seq) of induced pluripotent stem cells (iPSCs) derived from a healthy donor (control), a patient with Kleefstra syndrome (KSP), and two patients carrying pathogenic variants in EHMT2 (P1 and P2). Poly(A)-selected RNA was used for library preparation, and strand-specific libraries were generated for paired-end sequencing on the MGI DNBSEQ PE100 platform.

  Dataset EGAD50000002344

• Phenotype and Genotype determination of 400 individuals from Northern Germany

  Phenotype determination by SNP-Typing using PCR and snapshotPCR with subsequent fragment analysis. We investigated 400 individuals from Northern Germany and detected up to 12 different SNPs to determine eye, hair and skin colour. More than 1000 different runs on a ABI3130 were performedThis dataset includes:- Phenotype information for 400 samples- Summary and complete genotype calls for 12 SNPs on 400 samples.

  Dataset EGAD00001001315

• Evolution of four ER+ breast cancers

  The evolution of four breast cancers was analyzed using longitudinal samples collected over 2-15 years. Whole-genome sequencing and single-cell RNA-Seq were used to analyze evolution. We have deposited VCF files for SNV, indel, and structural variant calls from WGS data, and a text file showing transcripts per million (TPM) expression for the single-cell RNA-Seq data.

  Dataset EGAD00001003303

• Distinct genomic profile and specific targeted drug responses in adult cerebellar glioblastoma

  This dataset includes genomic information of 19 adult cerebellar glioblastomas (C-GBMs). Whole-exome sequencing data are available for 9 C-GBMs and their 8 corresponding matched blood samples, and glioma-specific targeted-DNA sequencing (GliomaSCAN) data from additional 10 C-GBMs are also available. Among them, Whole-transcriptome sequencing data were conducted for 6 C-GBM tumors.

  Dataset EGAD00001003417

• Multi-Region WES of Metastatic Colorectal Cancer

  In order to reconstruct the evolutionary history of metastatic colorectal cancer, we performed whole-exome sequencing of 12 metastatic colorectal cancer patients for whom the primary tumor and matched distant metastases to the brain (n=10) and liver (n=2). For 8 of the 12 patients, multiple regions (n=3-7) of the primary tumor and distant metastases were sequenced.

  Dataset EGAD00001004896

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Gene Discovery in Autosomal Dominant Focal Segmental Glomerulosclerosis (FSGS)

  Focal segmental glomerulosclerosis (FSGS) is a frequent cause of end-stage renal disease. The pathogenesis of FSGS has not been precisely defined and there are no consistently effective treatments. Recent studies identifying causal genes in rare, inherited FSGS, including our own study, have associated mutations in at least six genes with familial FSGS, and each discovery has clarified molecular mechanisms of glomerular injury. To build on this productive line of inquiry, we have ascertained and carefully characterized 118 families with familial FSGS. We have screened the remainder of our families for mutations in genes known to cause FSGS and identified the causal mutations in an additional 6 kindreds; the genetic basis of disease in the remaining 111 families is unknown. The objective of this proposal is to use this valuable and unique family resource to systematically identify causal genes for familial FSGS. Limitations of current conventional linkage and positional cloning approaches include their requirement for large, multiplex families. In addition, narrowing candidate areas in traditional linkage analysis can be difficult due to large regions that lack recombination events and hence these regions have required cumbersome and lengthy screening for causative mutations. Powerful new genetic tools can facilitate this screening process and improve variant discovery in smaller families. In particular, efficient whole-exome sequencing, the targeted capture of protein-coding gene sequences, should be particularly useful in our studies since most Mendelian disorders are caused by mutations affecting exomes of the target gene. Thus, by combining genome-wide linkage analysis (GWLS) and whole-exome sequencing, we can maximize impact of our family data and accelerate identification of novel mutations in FSGS. In preliminary studies, we have used this combination to identify a novel variant in the WT1 (Wilms' Tumor-1) gene in one FSGS family, and we have evidence suggesting it is the causal mutation. This success provides proof-of-concept and provides a roadmap of how genes will be identified and evaluated in the proposed studies. Our hypothesis is that causes of inherited FSGS in our cohort of families will be sequence variants in the coding region of genes not previously associated with familial FSGS. We aim to: 1) Use GWLS and whole-exome sequencing to identify genetic variants associated with familial FSGS. 2) Characterize functional consequences of candidate causative mutations and 3) Determine the prevalence in the Duke FSGS dataset of these new causative mutations identified in Aim 2. Any genes found to have causative mutations will be sequenced in the remaining families and take full advantage of our family resource. By combining genome-wide linkage analysis (GWLS), whole-exome sequencing, and characterization of variants' functional consequences, we will significantly improve understanding of normal glomerular biology and of the pathogenesis of FSGS and related glomerular diseases. Moreover, our discoveries are likely to reveal new opportunities to improve therapy for a disease that currently has few effective treatments.

  Study phs000777

• Combined hereditary and somatic mutations of replication error repair genes result in rapid onset of ultra-hypermutated cancers

  DNA replication-associated mutations are repaired by two components: polymerase proofreading and mismatch repair. The mutational consequences of disruption to both repair components in humans are not well studied. We sequenced cancer genomes from children with inherited biallelic mismatch repair deficiency (bMMRD). High-grade bMMRD brain tumors exhibited massive numbers of substitution mutations (>250/Mb) – higher than all childhood and most cancers (>7000 analyzed). All ultra-hypermutated bMMRD cancers acquired early somatic driver mutations in DNA polymerases epsilon or delta. The ensuing mutation signatures and numbers are unique and diagnostic of childhood germline bMMRD (p<10e-13). Sequential tumor biopsy analysis revealed that bMMRD/polymerase mutant cancers rapidly amass an excess of simultaneous mutations (~600 mutations/cell division), reaching but not exceeding ~20,000 exonic mutations in <6 months. Thus implying a threshold compatible with cancer cell survival. We suggest a new mechanism of cancer progression in which mutations develop in a rapid burst after ablation of replication repair.

  Study EGAS00001001112

• Targeted Sequencing of GWAS Loci in Cleft Lip and Palate

  Nonsyndromic cleft lip and palate (NSCL/P) is a complex disorder caused by both genetic and environmental factors and has been the focus of an extensive effort to identify genetic risk factors. A number of candidate gene studies have been performed but have not been widely replicated. To date, four independent genome wide association studies have been performed as well as a meta-analysis. Together these studies have identified many loci associated with NSCL/P. The goal of this project is to use targeted sequencing to further characterize these regions and to progress from the association signals identified by GWAS to the identification of causative genes and/or variants. This study is part of the GWASeq project, a collaboration of five disease studies, which will sequence genomic regions from GWAS to characterize the genetic variation underlying these diseases and to compare study design and methods for the follow-up of GWAS studies by sequencing. The goal of this study is to sequence 1000+ NSCL/P case-parent trios from China and the Philippines and 400 trios of European ancestry. Targeted sequencing was performed on intervals ranging between 60kb to 1Mb surrounding 13 genes/loci previously associated with NSCL/P including: IRF6, MAFB, ARHGAP29, 8q24, PAX7, VAX1, NTN1, NOG, FOXE1, MSX1, BMP4, FGFR2, PTCH1.

  Study phs000625

• 5- FU treated organoids

  5-Fluorouracil (5-FU) is a chemotherapeutic drug component that is commonly used for the treatment of solid cancers. The anticancer properties of 5-FU have been attributed to interference with nucleotide synthesis and through direct incorporation into the DNA as being a pyrimidine analog. As both mechanisms of action may have a mutational impact on surviving tumor cells, we performed three independent analyses to characterize the genomic consequences of 5-FU treatment: i) in vitro treatment of intestinal organoids with 5-FU followed by whole genome sequencing, ii) genome-wide mutation analyses in tumor samples from 5-FU treated patients with breast or colorectal cancer, and iii) analysis of paired biopsies from patients treated with 5-FU between biopsies. Our results demonstrate that both in vitro and in vivo 5-FU causes a mutational pattern that is dominated by T>G substitutions in a CTT context and with strong resemblance to COSMIC signature 17. Interestingly, this signature is also found in non 5-FU treated patients, most prominently in esophageal tumors, indicating that distinct endogenous and exogenous triggers can converge into highly similar mutational signatures. Furthermore, our results suggest that 5-FU may have adverse mutagenic effects on healthy cells and contributes to genetic variability in surviving cancer cells thereby contributing to tumor evolution.

  Study EGAS00001003592

• EDi019-A / SAMEA4774918 WGS data

  The iPSC line EDi019-A / SAMEA4774918 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi019-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001029

• RCi009-A / SAMEA4339688 WGS data

  The iPSC line RCi009-A / SAMEA4339688 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi009-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001030

• EDi018-A / SAMEA4771918 WGS data

  The iPSC line EDi018-A / SAMEA4771918 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi018-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001027

• EDi016-A / SAMEA4562366 WGS data

  The iPSC line EDi016-A / SAMEA4562366 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi016-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001032

• EDi017-A / SAMEA4768918 WGS data

  The iPSC line EDi017-A / SAMEA4768918 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi017-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001033

• EDi019-C / SAMEA4777168 WGS data

  The iPSC line EDi019-C / SAMEA4777168 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi019-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001036

• EDi010-A / SAMEA4459354 WGS data

  The iPSC line EDi010-A / SAMEA4459354 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi010-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001038

• BIONi010-C / SAMEA3158050 WGS data

  The iPSC line BIONi010-C / SAMEA3158050 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001039

• UKKi019-C / SAMEA17626918 WGS data

  The iPSC line UKKi019-C / SAMEA17626918 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi019-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001042

• EDi011-B / SAMEA4459359 WGS data

  The iPSC line EDi011-B / SAMEA4459359 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi011-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001044

• EDi011-C / SAMEA4459360 WGS data

  The iPSC line EDi011-C / SAMEA4459360 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi011-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001045

• EDi012-A / SAMEA4459361 WGS data

  The iPSC line EDi012-A / SAMEA4459361 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi012-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001046

• EDi015-A / SAMEA4459373 WGS data

  The iPSC line EDi015-A / SAMEA4459373 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi015-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001047

• EDi015-C / SAMEA4459376 WGS data

  The iPSC line EDi015-C / SAMEA4459376 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi015-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001048

• EDi017-B / SAMEA4770418 WGS data

  The iPSC line EDi017-B / SAMEA4770418 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi017-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001049

• EDi011-A / SAMEA4459357 WGS data

  The iPSC line EDi011-A / SAMEA4459357 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi011-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001050

• EDi013-B / SAMEA4459367 WGS data

  The iPSC line EDi013-B / SAMEA4459367 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi013-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001052

• BIONi010-A / SAMEA3105765 WGS data

  The iPSC line BIONi010-A / SAMEA3105765 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001054

• BIONi010-B / SAMEA3158000 WGS data

  The iPSC line BIONi010-B / SAMEA3158000 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001055

• EDi010-B / SAMEA4459356 WGS data

  The iPSC line EDi010-B / SAMEA4459356 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi010-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001056

• EDi013-A / SAMEA4459365 WGS data

  The iPSC line EDi013-A / SAMEA4459365 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi013-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001057

• RBi001-A / SAMEA3368212 WGS data

  The iPSC line RBi001-A / SAMEA3368212 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RBi001-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001058

• RCi006-A / SAMEA3962402 WGS data

  The iPSC line RCi006-A / SAMEA3962402 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi006-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001059

• UKKi017-C / SAMEA17621668 WGS data

  The iPSC line UKKi017-C / SAMEA17621668 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi017-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001061

• EDi012-B / SAMEA4459363 WGS data

  The iPSC line EDi012-B / SAMEA4459363 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi012-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001063

• EDi012-C / SAMEA4459364 WGS data

  The iPSC line EDi012-C / SAMEA4459364 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi012-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001064

• EDi013-C / SAMEA4459368 WGS data

  The iPSC line EDi013-C / SAMEA4459368 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi013-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001065

• EDi015-B / SAMEA4459375 WGS data

  The iPSC line EDi015-B / SAMEA4459375 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi015-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001066

• UKKi018-C / SAMEA103988380 WGS data

  The iPSC line UKKi018-C / SAMEA103988380 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi018-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001067

• RCi004-A / SAMEA3106011 WGS data

  The iPSC line RCi004-A / SAMEA3106011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi004-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001069

• RCi004-B / SAMEA3106205 WGS data

  The iPSC line RCi004-B / SAMEA3106205 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi004-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001070

• RCi005-A / SAMEA3961534 WGS data

  The iPSC line RCi005-A / SAMEA3961534 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi005-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001071

• RCi007-C / SAMEA4084916 WGS data

  The iPSC line RCi007-C / SAMEA4084916 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi007-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001072

• UOXFi007-A / SAMEA103988274 WGS data

  The iPSC line UOXFi007-A / SAMEA103988274 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UOXFi007-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001079

• EDi018-B / SAMEA4773418 WGS data

  The iPSC line EDi018-B / SAMEA4773418 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi018-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001080

• EDi018-C / SAMEA4774168 WGS data

  The iPSC line EDi018-C / SAMEA4774168 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi018-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001081

• UKKi020-C / SAMEA103988344 WGS data

  The iPSC line UKKi020-C / SAMEA103988344 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi020-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001082

• UKKi021-B / SAMEA103988346 WGS data

  The iPSC line UKKi021-B / SAMEA103988346 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi021-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001083

• UKKi022-C / SAMEA103988349 WGS data

  The iPSC line UKKi022-C / SAMEA103988349 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi022-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001084

• WTSIi009-A / SAMEA2593858 WGS data

  The iPSC line WTSIi009-A / SAMEA2593858 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line WTSIi009-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001085

• EDi016-B / SAMEA4767418 WGS data

  The iPSC line EDi016-B / SAMEA4767418 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi016-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001086

• EDi017-C / SAMEA4771168 WGS data

  The iPSC line EDi017-C / SAMEA4771168 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi017-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001087

• UOXFi008-B / SAMEA103887561 WGS data

  The iPSC line UOXFi008-B / SAMEA103887561 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UOXFi008-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001089

• EDi016-C / SAMEA4768168 WGS data

  The iPSC line EDi016-C / SAMEA4768168 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi016-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001090

• EDi019-B / SAMEA4776418 WGS data

  The iPSC line EDi019-B / SAMEA4776418 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi019-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001091

• UKKi019-A / SAMEA17624668 WGS data

  The iPSC line UKKi019-A / SAMEA17624668 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi019-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001094

• UKKi019-B / SAMEA17626168 WGS data

  The iPSC line UKKi019-B / SAMEA17626168 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi019-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001096

• 5 scRNA-seq with TCR Enrichment of Tumour-Involved Lymph Nodes, Malignant Seromas and Patient-Derived Xenografts from 18 T-Cell Lymphoma Patients

  This raw data contains 5' scRNA-seq with TCR enrichment data from 18 individual patients analysing cells taken from tumour-involved lymph nodes (LN), malignant seromas and patient-derived xenografts (PDX) including systemic/nodal ALK+ ALCL (n=3 PDX), BIA-ALCL (n=2 seromas), PTCL-NOS (n=5 nodal tumours), nodal T follicular helper lymphoma - angioimmunoblastic type (nTFHL-AI) (n=1), nTFHL, not otherwise specified (nTFHL, NOS, n=1), TLBL (n=5) and 1 case of Sezary Syndrome (SS, cutaneous tumour). Droplet-based 5’ scRNA-seq with TCR enrichment (10x Chromium platform) was performed for all live cells, or the viable CD45+CD3- and CD45+CD3+ fractions following cell sorting by flow cytometry.

  Dataset EGAD00001015703

• Human Dorsal Root Ganglion RNA Landscape Profiling for Neuropathic and Chronic Pain

  Bulk and spatial RNA sequencing were performed on human Dorsal Root Ganglia (DRGs), peripheral sensory nerves and nodose ganglia and relative gene abundances were calculated. Various analyses were performed: Human DRG gene expression profiles were contrasted with a panel of gene expression profiles of relevant tissues in human and mouse (integrating, among other sources, datasets from ENCODE and GTex) in order to identify. DRG-enriched gene expression, co-expression modules of DRG-expressed genes, and key transcriptional regulators in humans. Contrasting the human and mouse DRG transcriptomes to identify DRG-enriched gene expression patterns that were conserved between human and mouse, identifying putative cell types of expression of these genes, and potential known drugs that might target the corresponding gene products. Characterization of non-coding RNA profile of human and mouse DRGs. Characterization of DRG-enriched alternative splicing and alternative transcription start site usage based transcript variants in humans and mouse, and the overlap between these two species. Contrasting of human DRG and GTex human tibial nerve samples to identify putative axonally transported mRNAs in sensory neurons. Human DRG and peripheral nerves transcriptomes from donors suffering from neuropathic and/or chronic pain were contrasted with controls to identify. Differentially expressed genes, pathways and regulators path play a potential role in neuronal plasticity, electrophysiological activity, immune signaling and response. Predictive models (Random Forests) were built to jointly predict the sex and pain state of samples based on information contained solely in autosomal gene expression profile. Gene co-expression modules were identified and gene set enrichment analysis performed.to identify sample - pathway associations, and to broadly characterize plasticity in human DRG cell types. Spatial transcriptomics was performed on human DRGs and nodose ganglia to obtain near single-neuron resolution. We identified distinct clusters of human DRG sensory neurons. We characterized the expression of different gene families (e.g., GPCRs, sodium channels, potassium channels, etc.). We investigated differences between male and female neurons.

  Study phs001158

• Mayo Clinic and Illumina Collaborative Early Stage Ovarian Cancer (ESOC) Study

  Twenty five patients with early stage carcinoma (Stage I and II) of the ovary were consented for this study. As part of a collaborative agreement with Illumina Inc, Tumor-DNA and patient matched normal DNA from blood underwent whole genome sequencing and microarray genotyping and RNA underwent RNASeq. Tissue also underwent IHC staining for TP53 mutations. The aim of the study was to profile the genomic landscape of these early tumors to discover biomarkers for early detection or subgrouping into different genomic or outcome subgroups. Analyses performed include somatic mutation analysis, RNASeq mutation analysis, LOH analysis, structural variant detection. The current release of this study focusses on 17 patients with serous carcinoma and stage 1 or 2 and with high grade (3 or 4).

  Study phs000897

• Whole Genome Sequencing for Metastatic Mutational Burden in Extraskeletal Myxoid Chondrosarcoma

  Extraskeletal myxoid chondrosarcoma (EMC) is an ultra-rare cancer. Though it has a favorable prognosis and an indolent course, it has high rates of local recurrence and metastasis to the lungs. EMC is most often characterized by a translocation involving the NR4A3 gene most often fusing with EWSR1, leading to constitutive expression of NR4A3, the biological significance of which is unknown. Our study presents a case of EMC with case-matched lung and advanced pelvic metastases. We conducted Whole Genome Sequencing to examine differences in the mutational landscape at two different stages of metastasis. This is the first study to our knowledge to analyze mega-base scale structural variants (SVs) in EMC. Our data validates copy number variants (CNVs) found in previous studies. While the primary tumor and lung metastasis had similar somatic variations and CNVs, the pelvic metastasis had more SVs with especially increased mutational burden of SVs in chromosome 2. This suggests that different molecular drivers appear in more advanced, relapsing EMC compared with the primary tumor and early lung metastasis. The sequencing data is available through dbGaP.

  Study phs003305

• DHODH is a synthetic-lethal vulnerability in BCOR-deficient acute myeloid leukemia

  Acute Myeloid Leukemia (AML) remains challenging to treat, especially in cases with mutations in the BCL-6 co- repressor (BCOR), which are associated with poor prognosis and chemo-resistance. In this study, we reveal a synthetic lethal interaction between BCOR and dihydroorotate dehydrogenase (DHODH). We demonstrate that BCOR-deficient cells have a heightened sensitivity to DHODH inhibitors such as brequinar and leflunomide, that are already in clinical use. We confirm that DHODH inhibition selectively induces cell death in BCOR-mutant cells in multiple cellular models, in malignant and non-malignant cells, through chemical and genetic manipulation. Interestingly, we find that the dependency on DHODH does not stem from its role in de novo pyrimidine biosynthesis disruption. Rather, DHODH’s role in the electron transport chain, essential for mitigating reactive oxygen species, may be the physiological vulnerability that pushes BCOR-mutant cells toward cell death when DHODH is inhibited. DHODH inhibitors could be repurposed as targeted therapies for BCOR-mutant tumors, offering a promising strategy for precision medicine in AML and other cancers.

  Study EGAS50000001108

• DHODH is a synthetic-lethal vulnerability in BCOR-deficient acute myeloid leukemia

  Acute Myeloid Leukemia (AML) remains challenging to treat, especially in cases with mutations in the BCL-6 co- repressor (BCOR), which are associated with poor prognosis and chemo-resistance. In this study, we reveal a synthetic lethal interaction between BCOR and dihydroorotate dehydrogenase (DHODH). We demonstrate that BCOR-deficient cells have a heightened sensitivity to DHODH inhibitors such as brequinar and leflunomide, that are already in clinical use. We confirm that DHODH inhibition selectively induces cell death in BCOR-mutant cells in multiple cellular models, in malignant and non-malignant cells, through chemical and genetic manipulation. Interestingly, we find that the dependency on DHODH does not stem from its role in de novo pyrimidine biosynthesis disruption. Rather, DHODH’s role in the electron transport chain, essential for mitigating reactive oxygen species, may be the physiological vulnerability that pushes BCOR-mutant cells toward cell death when DHODH is inhibited. DHODH inhibitors could be repurposed as targeted therapies for BCOR-mutant tumors, offering a promising strategy for precision medicine in AML and other cancers.

  Study EGAS50000001060

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Adult RNA (2025-10-14)

  Animal studies have demonstrated that resident memory T (Trm) cells provide enhanced protective responses to a broad array of tissue-tropic pathogens, thus making Trm cells promising targets for novel vaccination strategies. However, the biological pathways that enable the long-term survival of Trm cells are poorly understood in humans. Here, we will employ a unique human intestinal transplantation setting that allows us to study the retention of persistent T cells in the grafts and the temporal development of resident T-cell populations from recruited recipient T cells. We will integrate high resolution transcriptomics, epigenetics, proteomics and immune repertoire single-cell data from purified intestinal T cells. These single-cell multiomics approaches will uncover the diversity and differentiation of the T cell populations in the human intestine, allowing us to temporally resolve the generation and maintenance of gut resident T cells. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015739

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• Identification of genetic mutations characteristic for recurrence and metastasis of lymphoma.

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent B cell lymphoma, and the purpose of this study is to find the characteristics of recurrent B cell lymphoma by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000087

• Identification of genetic mutations characteristic for recurrence and metastasis of gastric cancer.

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent / metastatic gastric cancer, and the purpose of this study is to find the characteristics of recurrent / metastatic gastric cancers by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000086

• HCA Female Reproductive Adult WSSS RNA

  HCA Endometrium_LM The endometrium regenerates monthly and its transformation is executed through dynamic changes in states and interactions of multiple cell types. Using transcriptomics methods we seek to profile changes of the endometrium across the menstrual cycle. Our map will have implications in women's health and cancer, by enabling the interpretation of GWAS analyses or the studying functional consequences of somatic mutations. 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/

  Dataset EGAD00001007909

• ATAC-seq in hiPSC-derived neurons after BDNF and KCl stimulations

  Brain-Derived Neurotrophic Factor (BDNF) is crucial for neuronal survival, differentiation, synaptic plasticity, memory formation, and neurocognitive health. Molecular mechanisms of BDNF promoting cellular survival and synaptic plasticity have been intensely studied, yet its role in genome regulation is obscure. Using human induced pluripotent stem cell (hiPSC)-derived neurons via lentiviral delivery of the neuronal transcription factor Ngn2, we performed a temporal profiling (1h, 6h and 10h) of chromatin accessibility upon BDNF treatment or depolarization (KCl) to identify BDNF-specific chromatin-to-gene expression programs.

  Dataset EGAD00001009100

• Identification of drug resistance genes in melanoma by small RNAs expression analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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/

  Dataset EGAD00001003245

• Identification of drug resistance genes in melanoma by mRNA gene expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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/

  Dataset EGAD00001003244

• CCA WGS data (16 CCA with matched normal, 4 cell-line)

  Fastq files for WGS for 16 CCAs (with matched normal tissues), and 4 cell lines in an AA-treatment experiment (0, 10, 20, 40ug AA treatment after 180 days; 2 runs each for 10ug and 40ug experiments). Genomic DNA was extracted using DNeasy Blood and Tissue Kit (Qiagen). Sequencing libraries were prepared from DNA extracted using the SureSelect XT2 Target Enrichment System for the Illumina Multiplexed Sequencing platform (Illumina) according to the manufacturer’s instructions. Whole genome sequencing was performed on Illumina HiSeq4000 sequencer with paired-end sequencing.

  Dataset EGAD00001012100

• Mayo Clinic - Fecal Microbiota and Adenomas

  Background: Adenomatous polyps are the most common precursor to colorectal cancer (CRC), the second leading cause of cancer death in the United States. We sought to learn more about early events of carcinogenesis by investigating shifts in the gut microbiota of patients with adenomas. Methods: We analyzed 16S rRNA gene sequences from the fecal microbiota of patients with adenomas (n=233) and without (n=547). Results: Multiple taxa were significantly more abundant in patients with adenomas, including Bilophila, Desulfovibrio, pro-inflammatory bacteria in the genus Mogibacterium, and multiple Bacteroidetes species. Patients without adenomas had greater abundances of Veillonella, Firmicutes (Order Clostridia), and Actinobacteria (family Bifidobacteriales). Many of our findings were consistent with previously reported shifts in the gut microbiota of CRC patients. Importantly, the altered adenoma profile is predicted to increase primary and secondary bile acid production, as well as starch, sucrose, lipid, and phenylpropanoid metabolism. Conclusions: These data suggest that diets rich in refined sugar, protein, and lipids may lead to increased bile acid production, creating a colonic environment that promotes the growth of bile-tolerant microbes such as Bilophilia and Desulfovibrio. In turn, these microbes may produce genotoxic or inflammatory metabolites such as H2S and secondary bile acids, catalyzing adenoma development and eventually CRC. Impact: This study suggests a plausible biological mechanism to explain the links between diet, shifts in the microbiota, and CRC. This represents a first step toward resolving the complex interactions that shape the adenoma-carcinoma sequence of CRC and may facilitate personalized therapeutics focused on the microbiota.

  Study phs001204

• Phenotypic and Genotypic Study of Keratoconus

  Keratoconus, a disease in which the cornea is abnormally steep and thin, affects approximately 1 in 2000 individuals and usually begins in the second decade of life. Keratoconus is a progressive disorder that results in loss of vision that cannot be alleviated by contact lenses or glasses alone and is a leading indication for corneal transplantation in developed countries (Udar et al., 2006, PMID: 16877401). Keratoconus has a strong genetic component, and while several causative genes are clearly suspected, the underlying pathogenic processes have not yet been identified. The goal of our research is to identify genes that harbor mutations contributing to keratoconus and underlying biochemical processes relevant to keratoconus pathogenesis and to develop a better understanding of the etiology of keratoconus, leading to improved detection, treatment, and management. We will enroll isolated keratoconus along with familial cases and unaffected relatives when available. The subject population will consist of individuals diagnosed with keratoconus and unaffected relatives in families. Individuals/families will be ascertained through support groups and clinical collaborators. The identities of the study participants will be known only to Dr. Chakravarti, the study coordinator, physicians in the team and the post-doctoral fellow(s) working directly on the project. DNA, lymphocytes, and lymphoblastoid cell lines may be prepared from the blood samples for future use. Molecular analyses using markers and sequencing and statistical analyses of these data will be used to identify regions of human chromosomes where putative keratoconus disease genes reside. Analyses of coding DNA sequences within genes from keratoconus subjects will be compared to published control sequences to identify disease specific variants. Additionally, to understand disease pathogenesis, subsets of patients may be asked to provide tear samples. Study subjects will not directly benefit from participation and results will not be disclosed to participants nor their health care providers, unless medically relevant.

  Study phs003168

• The last addition to the list of clonal evolution studies in the EGA

  Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

  Blog the-last-addition-to-the-list-of-clonal-evolution-studies-in-the-ega

• Birth Defects: Moebius Syndrome and Related Congenital Facial Weakness Disorders

  It is estimated that about 1 in every 33 infants in the United States is born with a birth defect. Among these, the subset of birth defect syndromes associated with facial weakness and lack of facial expression can have profound implications for social interactions and psychosocial development. Moebius syndrome is defined by congenital and non-progressive facial weakness and limited eye abduction, and most cases are believed to result from dysfunction of cranial nuclei/nerves VI and VII. Although rare, this syndrome causes significant impairment because of facial weakness and associated intellectual disabilities, autism, hearing loss, difficulty swallowing and breathing, peripheral neuropathy, muscle hypotonia, heart defects, chest wall abnormalities, and limb malformations. The phenotypic spectrum and the associated genetic and environmental factors underlying Moebius syndrome are poorly understood. The goal of this research is to identify causative gene mutations for Moebius syndrome and related conditions, such as Moebius-Poland or -Robin sequence, hereditary congenital facial paresis (HCFP), and oculoauriculovertebral dysplasia (Goldenhar syndrome). This proposal builds on an ongoing collaboration among researchers at Mount Sinai Medical Center, Boston Children's Hospital, NHGRI intramural program, and the Moebius Syndrome Foundation, but aims to greatly extend that work by collaboration with investigators in the NIH Clinical Center (CC). Our groups have already defined a new autosomal dominant syndrome with Moebius syndrome, Kallmann syndrome, cyclic vomiting resulting from a TUBB3 E410K substitution. We have also identified a new autosomal recessive Moebius-related syndrome with bilateral facial palsy, hearing loss, and strabismus resulting from a HOXB1 R207C substitution. Through collaborative efforts of these extramural teams with intramural investigators, whole exome sequencing (WES) has been conducted for four families with Moebius-like features, and data analyses are ongoing. The overall goal of this new grant application will be to conduct extensive phenotype analysis on approximately 24 families per year with Moebius and other undefined syndromes with facial weakness. Studies to be conducted at the CC include neurology, psychiatry, neurocognitive, rehabilitation medicine (muscle strength, speech/language pathology), ophthalmology, audiology, and genetics evaluations; autism screening; electromyography, nerve conduction, and blink reflex studies; videoscopy of quantitative eye movement recordings; 3D-CT craniofacial imaging; MRI of the brain, orbit, internal auditory canals, posterior fossa including brain diffusion tensor imaging for tractography; and genetic counseling. Jointly with the extramural teams, WES analysis and variant confirmation will be performed. A more comprehensive definition of the phenotypic and genotypic spectrum of these birth defects will have a significant impact on our understanding of the molecular pathways underlying dysmorphologies, cranial nerve development, and more common childhood disorders such as autism. Thus, this project will lead to strategies for prevention and treatment of birth defects.

  Study phs001383

• Inhibiton of the GABPB1L-containing GABP tetramer is sufficient to reverse replicative immortality in TERT promoter mutant glioblastoma cells.

  Over 50 types of cancer acquire TERT promoter mutations. These single point mutations reactivate telomerase, allowing for indefinite maintenance of telomere length and enabling cellular immortalization. The transcription factor binding site created by the point mutations specifically recruit the ETS factor GABP, a multimeric transcription factor composed of the GABPα and GABPβ subunits. GABP can form two functionally independent transcription factor species – a dimer or a tetramer – depending on which of the structurally distinct GABPβ isoforms is incorporated into the complex. In this study, we show that genetic disruption of GABPβ1L, a tetramer forming isoform of GABPβ that is dispensable in normal development, results in TERT silencing in a TERT promoter mutation dependent manner. Failure to activate TERT expression by GABPβ1L culminates in telomere dysfunction, DNA damage, and mitotic cell death exclusively in TERT promoter mutant cells. Furthermore, exogenous expression of TERT is sufficient to prevent telomere degradation and loss of cell viability in GABPβ1L-reduced lines bearing the mutant TERT promoter. Orthotopic injection of tetramer-deficient mutant TERT promoter GBM cells rendered lower tumor burden and prolonged the overall survival of the tumor-bearing mice. These results highlight the potentially widespread role of GABPB1L in enabling replicative immortality of TERT promoter cancers.

  Study EGAS00001002582

• University of Zurich (UZH) - Snedeker lab

  Authorised Personnel: The individuals at the User Institution to whom University of Zurich (UZH) grants access to the Data. This includes the User, the individuals listed in Appendix II and any other individuals for whom the User Institution subsequently requests access to the Data. Details of the initial Authorised Personnel are set out in Appendix II. Data: The managed access datasets to which the User Institution has requested access. Data Producers: UZH and the collaborators listed in Appendix I responsible for the development, organisation, and oversight of these Data. External Collaborator: A collaborator of the User, working for an institution other than the User Institution. Project: The project for which the User Institution has requested access to these Data. A description of the Project is set out in Appendix II. Publications: Includes, without limitation, articles published in print journals, electronic journals, reviews, books, posters and other written and verbal presentations of research. Research Participant: An individual whose data form part of these Data. Research Purposes: Shall mean research that is seeking to advance the understanding of genetics and genomics, including the treatment of disorders, and work on statistical methods that may be applied to such research. User: The principal investigator for the Project. User Institution(s): The Institution that has requested access to the Data. UZH: University of Zurich, Raemistrasse 71, 8001 Zurich, Switzerland

  Dac EGAC50000000817

• Genome-Wide Association Study of Sporadic and Familial Testicular Germ Cell Tumors

  Case-Control Study:Testicular germ cell cancer has been increasing among men during most of the 20th century. Despite this increase, the etiology of testicular cancer is poorly understood. To better understand the molecular epidemiology of testicular cancer, the National Cancer Institute and the Department of Defense are conducting a case-control study of testicular cancer among military servicemen. The project includes obtaining biosamples and questionnaire data from all participants. Pre-diagnostic serum samples are available from the approximately 1,000 cases and 1,000 controls enrolled in the study. Multiple-Case Family Study:In a parallel project, we are also studying families in which 2 or more testicular cancers have occurred. Among those men diagnosed with testicular cancer, about 1-3 percent report a family history of the disease (FTGCT). Brothers of affected individuals are 8 to 10 times more likely to develop testicular cancer, and men whose fathers had testicular cancer are four times more likely to develop testicular cancer, when compared with the relatives of men who have never had testicular cancer. Large-scale genetic linkage studies have failed to identify one or more rare, highly-penetrant testicular susceptibility genes. Rather, it appears that these familial clusters are due to the combined effects of multiple more common genes with low penetrance (so-called "polygenic inheritance"). Our cohort of FTGCT families was assembled to characterize this syndrome's clinical phenotype, and to discover the full range of cancer susceptibility loci that influence TGCT pathogenesis.

  Study phs001303

• Comparison of the treated celiac disease microbiome to that of controls

  Coeliac disease (CeD) is an immune-mediated disorder primarily affecting the small intestine, characterised by an inflammatory immune reaction to dietary gluten. CeD onset results from a multifaceted interplay of genetic and environmental factors. While recent data show that alterations in gut microbiome composition could play an important role, many current studies are constrained by small sample sizes and limited resolution. To address these limitations, we analysed faecal gut microbiota from two Dutch cohorts, CeDNN (128 treated CeD patients (tCeD), 106 controls) and the Lifelines Dutch Microbiome Project (24 self-reported tCeD, 654 controls), using shotgun metagenomic sequencing. Self-reported IBS (570 cases, 1710 controls) and IBD (93 cases, 465 controls) were used as comparative conditions of the gastrointestinal tract. Interindividual variation within the case and control groups was calculated at whole microbiome and strain level. Finally, species-specific gene repertoires were analysed in tCeD patients and controls. Within-individual microbiome diversity was decreased in patients with self-reported IBS and IBD but not in tCeD patients. Each condition displayed a unique microbial pattern and, in addition to confirming previously reported microbiome associations, we identify an increase in the levels of Clostridium sp. CAG:253, Roseburia hominis, and Eggerthella lenta, amongst others. We further show that the observed changes can partially be explained by gluten-free diet adherence. We also observe increased interindividual variation of gut microbiome composition among tCeD patients and a higher bacterial mutation frequency in tCeD that contributes to higher interindividual variation at strain level. In addition, the immotile European subspecies of Eubacterium rectale, which has a distinct carbohydrate metabolism potential, was nearly absent in tCeD patients. Our study sheds light on the complex interplay between the gut microbiome and CeD, revealing increased interindividual variation and strain-level variation in tCeD patients. These findings expand our understanding of the microbiome’s role in intestinal health and disease. Note that some of the data in this study belong to the Lifelines cohort. Access to this dataset can be requested via the page of the EGA data access committee EGAC00001001996. The phenotype data can be requested, for a fee, by filling the application form at https://www.lifelines.nl/researcher/how-to-apply/apply-here.

  Study EGAS50000000959

• Nala TAS-LRS PGx Study

  Sequencing was performed on the PromethION Flow Cell R10 (M version) using the P2 Solo Sequencer (MinION release 24.02.16). The library was divided into three portions and loaded in a tapered manner across three time points. At the first time point, the initial portion of the library was loaded, and sequencing began in whole-genome mode (without adaptive sampling), to monitor QC (N50 within the expected range). After one hour, adaptive sampling was activated. A custom BED file was used to define the target regions (N=326). Each region was extended by 20 kb upstream and downstream, and overlapping regions were merged into non-redundant intervals using bedtools43, covering a total of 1.3% of the human genome. At the second time point (20–24 hours after sequencing began, or when fewer than 2000 pores remained active), the flow cell was washed following ONT’s Flow Cell Wash Kit protocol, and the second portion of the library was loaded. At the third time point (40–48 hours), the second portion of the library was retrieved, and merged with the third portion. The flow cell was washed and reloaded with the mixed library. POD5 files were basecalled using Dorado v0.8.1 in super-accuracy (SUP) mode with the dna_r10.4.1_e8.2_400bps_SUP@v5.0.0. Reads from the initial 1 h Whole Genome Sequencing (WGS) and subsequent 72 h adaptive sampling were filtered for Q-scores >10. Passing reads were demultiplexed using Dorado’s demux function, then combined per sample and mapped to the GRCh38 reference genome using Minimap2 v2.22. Files were converted to CRAM using samtools.

  Dataset EGAD50000001609

• Sequence Analysis of Mutations and Translocations Across Breast Cancer Subtypes

  This study combined whole exome (103 samples) and whole genome (22 samples) sequencing over a total of 108 breast tumors and matched normal DNA to identify novel mutations and translocations. Samples were subjected to paired-end Illumina sequencing with goal of 30x coverage of tumor/normal for whole genomes and 100x tumor/normal coverage for whole exomes. From these sequences, we used various computational techniques to identify somatic point mutations, insertion/deletions and structural rearrangements in these tumors. From these data, we identified new insights into the rates of background mutations in these cancers, novel recurrent mutated genes, and multiple gene rearrangements. One of these rearrangements appears to be a recurrent event in breast cancer.

  Study phs000369

• Epilepsy Genetics Initiative

  The Epilepsy Genetics Initiative (EGI) was created in 2014 with the goal of amassing a database of clinically-generated exome sequence data for patients with epilepsy who have had diagnostic whole exome sequencing. Most of the subjects enrolled in the study did not receive a secure genetic diagnosis from their initial sequencing. Following participant/family consent, EGI transfers raw data from the respective clinical lab to the Institute for Genomic Medicine at Columbia University Medical Center. The strategy of the initiative has been to carry out systematic reanalysis of data to identify new diagnoses that were not possible or missed at the time of initial sequencing and to aid in novel gene discovery in epilepsy.

  Study phs001551

• Single-cell RNA sequencing of pediatric Hodgkin Lymphoma to study the inhibition of T cell subtypes

  Here, we applied single-cell RNA-sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same cHL tumors. This allowed us to identify genes of cell surface proteins that are consistently overexpressed in HRS cells and can potentially be used as targets for antibody-drug conjugates or CAR T cells. Finally, we identify potential interactions by which HRS cells inhibit T cells, among which the Galectin-1/CD69 and HLA-DRA/LAG3 interactions. However, high levels of inter-patient heterogeneity of the interaction strength were observed. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets.

  Study EGAS50000000432

• Splicing signature analysis of RNU2-2 samples

  Dominant pathogenic variants in the snRNA RNU2-2 were recently reported as a cause of neurodevelopmental disorders. In our study we identified additional individuals with dominant variants (n.4G>A and n.35A>G) and we also identified biallelic variants as a novel frequent cause of neurodevelopmental disorder. We obtained blood samples and performed short-term lymhocytes cultures for 19 cases (5 n.4; 5 n.35; 9 biallelic). We generated exome-capture RNA-Seq for these cases that we compared to 49 controls (probands affected from a neurodevelopmental disorder but without RNU2-2 variants). We observed that RNU2-2 variants mainly disturb alternative exon skipping, although affecting different exons.

  Study EGAS50000001410