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• CLUSTER Consortium RNAseq PBMC Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq PBMC dataset (paired FASTQ files, n = 82 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. Total PBMC were isolated from pre-treated blood of JIA patients and clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001457

• CLUSTER Consortium RNAseq CD8 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD8 dataset (paired FASTQ files, n = 85 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD8 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001456

• CLUSTER Consortium RNAseq CD4 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD4 dataset (paired FASTQ files, n = 86 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD4 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001455

• CLUSTER Consortium RNAseq CD14 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD14 dataset (paired FASTQ files, n = 80 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD14 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001458

• CLUSTER Consortium RNAseq CD19 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD19 dataset (paired FASTQ files, n = 83 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD19 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001459

• HTAN MCL Pre-Cancer Atlas Pilot Project - Targeted Sequencing Development Study

  The HTAN-MCL Pre-Cancer Atlas Pilot Project (PCAPP) is the result of a collaboration between the seven members of the MCL consortium. Across four organ types, PCAPP's goal is to collect and profile pre-malignant lesions for gene expression, DNA mutations, single-cell gene expression and immune-environment. Most PML are small in size and only available come from formalin fixed paraffin embedded archived tissue. The primary goal of PCAPP is to 1) understand the logistical challenges of PML specimen collection, 2) document technical limitations of the assays that are specific to the PML and 3) overcome them to support the generation of a more comprehensive Pre-Cancer Atlas in the future. The current upload provides RNA and DNA sequencing from participants with DCIS who were studied at the University of San Diego and the University of Vermont. Description of the overall study: A. Background/Significance One of the critical barriers to developing new approaches for cancer detection and prevention is the lack of understanding of the key molecular and cellular changes that cause cancer initiation and progression. Unlike the extensive work that has been done profiling advanced stage tumors, few studies have comprehensively profiled the molecular alterations found in precancerous tissues. Premalignant lesions are currently characterized by histologic changes that precede the development of invasive carcinoma1,2.These lesions can often be identified in regions surrounding an invasive tumor or in biopsies taken from patients undergoing diagnostic evaluation for suspicion of cancer. Currently, limited metrics exist to identify lesions that will likely progress to carcinoma and require intervention from those that will naturally regress or remain stable3,4. Characterization of the molecular alterations in premalignant lesions and the corresponding changes in the microenvironment would hasten the development of biomarkers for early detection and risk stratification as well as suggest preventive interventions to reverse or delay the development of cancer. Our pilot study will establish the feasibility of transcriptomic, genomic and immune profiling of FFPE premalignant lesions from multiple organ sites, collected and profiled with uniform SOPs across multiple institutions within the MCL consortium. We will characterize the molecular alterations in precancerous lesions and the corresponding microenvironment in four major organ sites, in order to uncover the molecular and cellular determinants of premalignancy, and establish standardized sequencing and immunohistochemistry protocols on FFPE precancerous tissue. We will also evaluate the technical feasibility of single nuclei sequencing of small FFPE pre-cancer lesions. Successful completion of the proposed pilot study will set the stage for expansion and development of a comprehensive Pre-Cancer Atlas (PCA) as part of the NCI's moonshot.B. Specific Aims Aim 1: Collect premalignant lesions (PML) and their associated microenvironment via LCM from FFPE tissue across four organ sites (breast, lung, pancreas & prostate). Aim 2: Perform bulk RNA and DNA seq on premalignant FFPE samples (and flash frozen tissue where available) and compare the genomic/transcriptomic alterations within and across organ sites. C. ApproachAim 1: Collect premalignant lesions (PML) and their associated microenvironment via LCM from FFPE tissue across four organ sites (breast, lung, pancreas & prostate). MethodsI. Patient Population/Sample Collection: Overview of the sites collecting PML tissue from the respective organs is provided in Table 1 and a full description of the biospecimens to be obtained is described in detail for each organ type below. Table 1. Breakdown of cohort by tissue type and collection site.Organ siteBreastLungPancreasProstateType of PMLDCISAAH, Squamous Dysplasia/CISIPMNsPINCollection of PatientsUCSF/UCSDUVMBU*/UCLAVanderbilt/MoffittMDACC*JHUStanford*# of Patients201920 (10 of each type)20 (10 of each type)242020Total patients per Organ39402440Note: single nuclei/cell RNA-Seq will be performed on 4-5 FFPE samples from each of the organ types 1. DCIS lesions from breast tissue: DCIS lesions will be collected from 39 patients (20 from UCSF/UCSD & 19 from UVM) with primary low or high-grade DCIS diagnosed from a breast core biopsy. Subsequent resected lumpectomy or mastectomy tissues will be prospectively sampled in the vicinity of the prior biopsy site using multiple approaches: 1) Live cells (heterogeneous mix) will be obtained as a cell scrape slurry from the lesion surface or by fine needle aspirate (FNA); 2) For a subset of specimens where size is sufficient, a block of breast tissue with DCIS will be fresh-frozen; 3) The remainder of the specimen will be taken for routine formalin-fixation and paraffin-embedding (FFPE). The FFPE sample will be annotated to identify the matched FFPE tissue block adjacent to the fresh-frozen sample and will be sectioned for use in bulk and single nuclei sequencing . We will dissect DCIS, adjacent normal and when available, associated carcinoma. In addition, when possible, normal tissue will be collected from a tissue block lacking lesions as well as collection of blood. A subset of patients (n = 5 | FFPE, flash frozen and fresh) will be sent to the Broad Institute for single nuclei/cell sequencing.2. AAH and squamous dysplastic/CIS lesions from airway and lung tissue: For squamous cell lung cancer, we will collect endobronchial biopsies from abnormal airway regions identified on autofluroscence bronchoscopy or identify PMLs in the margins of resected lung tissue. We will study 20 patients (5 each from BU/UCLA/Vanderbilt/Moffitt) with pre-invasive squamous lesions (moderate-severe dysplasia or carcinoma in situ (CIS)) identified on pathologic examination. LCM of the premalignant region and adjacent normal epithelium will be performed as well as the invasive tumor for those collected from the resection margin (n=5 from UCLA). On a subset of lesions collected at bronchoscopy (n=5), we will collect additional biopsies that will be flash frozen and fresh for single nuclei and cell sequencing, respectively, performed at the Broad Institute. In parallel to the work at the Broad, BU will perform single cell RNA-seq on these freshly cell sorted tissues (n = 5). Blood will be collected on all patients for genomic studies. For lung adenocarcinoma, we will collect resected FFPE lung tissues from 20 patients (10 from UCLA and 10 from Vanderbilt/Moffitt) with early stage lung adenocarcinoma that harbor atypical adenomatous (AAH) premalignant lesions in the resection margin. We will LCM multiple AAH regions (3-5 per patient) as well as adjacent regions of normal epithelium and invasive adenocarcinoma. In addition, blood will be collected on all patients for genomic studies. 3. IPMNs from pancreatic tissue: For pancreatic cancer PML, we will collect low and high grade lesions from 24 patients representing macroscopic Intraductal Papillary Mucinous Neoplasms (IPMN) (n=24) from surgically resected specimens along with blood samples. Archival FFPE specimens of microscopic PanIN lesions, occurring multi-focally adjacent to invasive PDAC, and archival IPMN lesions (with or without associated invasive cancer), along with the adjacent normal tissue, will undergo LCM and utilized for bulk DNA and RNA sequencing. If matched frozen tissues are available for a subset of these FFPE samples, we will bank for comparison of profiles. Because IPMNs are macroscopic lesions, they provide an opportunity for obtaining the samples fresh and therefore can be used for single cell sequencing (in contrast to PanINs). Therefore, 5 freshly obtained IPMNs will be used for the single cell RNA sequencing studies performed at both the Broad Institute and MDACC, and the matched FFPE and/or frozen sections from these lesions (obtained from the adjacent PML) will be sent to Broad Institute as a pilot to assess "single nuclei" RNA sequencing.4. PINs from prostate tissue: For prostate cancer PML, there will be 40 samples of Prostatic Intraepithelial Neoplasia (PIN) collected between the Stanford and JHU sites (20 cases per site). At the Stanford site, 20 prostate specimens detected by PSA screening who have/will undergo surgery (radical prostatectomy) for clinically localized disease will make up the final cohort. The age range of the participants would be 40-75, and we anticipate that 18 will be Caucasian, 1 Asian and 1 Latino or African American based on the practice demographics practice at Stanford. Clinical and MRI data will also be collected for these samples. We will collect low grade (e.g. Gleason score of 6/Grade group 1; n=10) and high grade (Gleason score 4+3=7 or higher/Grade group 3 or higher; n=10) PINs from FFPE samples that have prostate carcinoma. In addition to obtaining LCM archival samples of low and high grade PIN, we will also obtain normal prostatic epithelial from the peripheral, central and transition zones as well as multiple samples of prostate carcinoma in order to obtain the spectrum of Gleason grades in the carcinoma as needed. LCM samples will be used for bulk DNA and RNA sequencing. In addition, single cells will be dissected from FFPE samples to prepare single cell RNA seq libraries using techniques developed at Stanford, and FFPE tissue will be sent to the Broad for single nuclei sequencing. When available, flash frozen and fresh samples from these prostates will be archived and prepared for single nuclei and cell sequencing, respectively, at the Broad Institute and at Stanford (single cell only). JHU will also capture 10 cases (5 grade group 1 and 5 grade group 2) of high grade PIN, normal and invasive adenocarcinoma using frozen sections from fresh frozen tissues. When possible these will be from the same patients as the FFPE samples. Since frozen sections can be quite challenging to morphologically determine high grade PIN from normal epithelium, for these samples we will perform a number of additional tissue-based characterizations. These will include a multicolor combined basal cells (p63 and CK903) and PIN/carcinoma markers (AMACR) referred to in the cocktail as "PIN4", c-MYC (referred to as MYC) protein5, by IHC and mRNA by in situ hybridization (AM De Marzo, Q Zheng unpublished observations), telomere length by in situ hybridization6 and the 5'ETS/45S rRNA7. For these slides, the whole slides will be scanned with a Hammamatsu Nanozoomer with a 40x objective and regions of interest will be annotated as a guide for LCM.II. Laser-capture microdissection (LCM): FFPE tissue blocks will be sectioned at 7μm thickness and serial sections will be stained with H&E. LCM will be performed utilizing standard LCM systems, such as Leica LMD7000 and ArcturusXT at each site. Regions of premalignancy will be dissected and RNA/DNA will be extracted from microdissected cells using the Qiagen All Prep DNA/RNA FFPE Kit. Aim 2: Perform bulk RNA and DNA seq on premalignant FFPE samples and compare the genomic/transcriptomic alterations within and across organ sites. Rationale: There have been limited studies characterizing the genomic and transcriptomic landscape of premalignant lesions associated with breast, pancreatic, lung or prostate cancers. Characterizing the molecular determinants of premalignant disease that are unique and shared across multiple organs will enable new candidate biomarkers for early detection and novel therapeutic strategies for early intervention. MethodsBulk RNA-seq of LCM FFPE tissue: All participating sites will perform bulk RNA-seq in accordance with SOPs developed at BU. In brief, total RNA will be isolated from LCM'd lesion and associated microenvironment tissue using the Qiagen All Prep DNA/RNA FFPE Kit and quality will be assessed with the Agilent Bioanalyzer. Libraries will be generated with the Illumina TruSeq Access kit (for FFPE samples). They will be sequenced on the Illumina HiSeq2500 with 75base-pair paired-end reads. Quality of FASTQ files will be assessed with FastQC. Reads will be aligned to the human genome with STAR and gene-level and isoform-level expression will be quantified with RSEM. Splice junction saturation, transcript integrity, and biotype distributions will be calculated for each sample with RSeQC. DESeq2 and EdgeR will be used to identify associations between gene expression profiles and clinical variables while controlling for confounding covariates. BU will serve as an RNA-seq Core to assess reproducibility of FFPE RNA-seq methods across sites. We will perform RNA-seq according to the SOP listed above on a subset of samples for each organ type (total n ~ 20). Bulk seq of DNA from FFPE tissue: All participating sites will perform targeted or whole exome-seq (WES) in accordance with SOPs. In brief, DNA from laser captured material will be isolated using the Qiagen All Prep DNA/RNA FFPE Kit and undergo stringent quality control to ensure high quality input material for genomic profiling. Purified DNA (ideally 100-200 ng) will be used for library preparation and amplification, followed by next generation sequencing using standard protocols distributed by CDMG. Exome-seq methods are considered standardized, thus we will not need a DNA-seq Core to assess reproducibility across sites. We anticipate local centers will use Illumina paired end reads, following the following general approach. 1) DNA library preparation: Paired-end libraries will be prepared following the manufacturer's protocols (Illumina and Agilent), fragmented to 150-200 bp 2) Capture of targeted exome: Whole exome capture will be carried out using the protocol for Agilent's SureSelect Human All Exon kit. Purified capture products will be amplified using the SureSelect GA PCR primers (Agilent) for 12 cycles. 3) Sequencing will be carried out for the captured libraries using at least 100 bp paired-end reads. To achieve high level sensitivity and accuracy for detecting all the mutations in the whole exome, each sample will be sequenced at 200X mean depth. 4) Read mapping and alignment and variant analysis: Sequence short reads will be aligned to a reference genome (NCBI human genome assembly build 38) using BWA-MEM. Local realignment of aligned reads will be performed using Genome Analysis Toolkit (GATK).Data QC: To ensure scientific rigor and consistency among sites in RNA and DNA processing we will include a preliminary analysis of steps in processing and analysis. Protocols for extraction of high quality RNA and DNA from formalin fixed paraffin embedded (FFPE) tissues, which will be used extensively in these studies continue to improve and may have variable implementation among the sites participating in this study. To evaluate consistency of preliminary steps in processing and downstream analyses, we will initially distribute slides from one large FFPE fixed cancer of origin from prostate, breast, lung and pancreatic cancer. Analysis of these samples will allow us to review the DNA and RNA characteristics (yield, purity and strand length) among sites. Downstream analysis of these same samples will also allow us to compare among sites the consistency of variant calls among centers. We will be able to identify if there are some times of calls (such as small insertion deletions) that are more variable among centers versus other types of calls (such as relative gene expression or single base pair substitutions) that we expect to be less variable and to characterize the reliability of findings across sites. We are also including a 5% blind duplicate analysis of RNA sequencing. Samples will be analysed by the participating genomics cores without knowledge of the phenotype. RNA seq and CNA analyses are normalized for batch effects. We will also compare the observed sex to the self-reported sex as based on RNA profiles and exome sequencing of X chromosome genes as another check for processing accuracy and sample management. D. References 1. Wacholder, S. Precursors in Cancer Epidemiology: Aligning Definition and Function. Cancer Epidemiol. Prev. Biomark. 22, 521-527 (2013). PMID: 23549395.2. Berman, J. J. Precancer: The Beginning and the End of Cancer. (Jones & Bartlett Learning, 2011).3. Nasiell, K., Nasiell, M. & Vaćlavinková, V. Behavior of moderate cervical dysplasia during long-term follow-up. Obstet. Gynecol. 61, 609-614 (1983). PMID: 6835614.4. Merrick, D. T. et al. Persistence of Bronchial Dysplasia Is Associated with Development of Invasive Squamous Cell Carcinoma. Cancer Prev. Res. (Phila. Pa.) 9, 96-104 (2016). PMID: 26542061.5. Gurel, B. et al. Nuclear MYC protein overexpression is an early alteration in human prostate carcinogenesis. Mod. Pathol. Off. J. U. S. Can. Acad. Pathol. Inc 21, 1156-1167 (2008). PMID: 18567993.6. Meeker, A. K. et al. Telomere shortening is an early somatic DNA alteration in human prostate tumorigenesis. Cancer Res. 62, 6405-6409 (2002). PMID: 12438224.7. Guner, G. et al. Novel Assay to Detect RNA Polymerase I Activity In Vivo. Mol. Cancer Res. MCR 15, 577-584 (2017). PMID: 28119429.

  Study phs002225

• Whole-Transcriptomic Profiling of Sorted Human Renal Cell Carcinoma Immune Populations

  It is poorly understood how the tumor immune micro-environment influences disease progression in renal cell carcinoma (RCC). Here we performed whole-transcriptomic profiling of immune cell populations which were derived from RCC patients representing distinct flow-sorted immune lineages.

  Study EGAS00001006593

• WES on tumor DNA and germline DNA in pediatric cancer

  This dataset contains whole exome sequencing (WES) data from tumor DNA samples of various pediatric cancer entities. Files are provided in fastq format. Samples were sequenced on a Novaseq6000 or Hiseq2500 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Study EGAS00001005429

• Singapore Adult Metabolism Study - Phase 2 (SAMS2)

  Singapore Adult Metabolism Study - Phase 2 (SAMS2) was an interventional study where hundreds of donors aged 21-45 were recruited to participate in a 16-week weight loss program. Study individuals selected (see below for more detailed selection standards) were sedentary (exercise 1 or fewer times a week), obese or overweight with a body fat mass greater than 24% and a BMI between 23-35 kg/m2. For this study, we adjusted BMI definition for Asian population, based on the WHO Consultation 2002, and the BMI cut-off is 23 kg/m2 for overweight and 27.5 kg/m2 for obese. The weight loss program included a combination of dietary interventions, structured exercise sessions, and additional physical activity performed in participants' own time. Energy and protein requirements were calculated based on each participant's weight, height, and physical activity level, with the goal of achieving a 40% calorie deficit. Participants' calorie intake was tracked using food recalls and questionnaires. Additionally, subjects attended structured exercise sessions at least three times per week, supervised by a coach. Each session consisted of 90 minutes of aerobic and strength training exercises, designed to burn approximately 500 kcal per session. To monitor daily physical activity, participants wore pedometers throughout the study. In total, the exercise sessions (500 kcal per session) and daily physical activity (targeting an additional 500 kcal) were aimed at achieving a total caloric expenditure of 2000 kcal per week. We collected clinical data and skeletal muscle biopsies from 54 overweight/obese Asian individuals before and after a 16-week lifestyle intervention, which resulted in an average ~10% weight loss, accompanied by a ~30% increase in insulin-stimulated glucose uptake. Improvements were observed in 118 of 252 clinical traits and six blood lipids. Transcriptomic analysis of paired skeletal muscle biopsies identified 505 differentially expressed genes enriched in mitochondrial function and insulin sensitivity. Thousands of muscle-specific e/sQTLs were detected pre- and post- intervention, including hundreds of lifestyle-responsive e/sQTLs. Notably, approximately 4.2% of eQTLs and 7.3% of sQTLs showed Asian specificity. Joint analysis with GWAS identified 16 putative metabolic risk genes. Our study reveals gene-by-lifestyle interactions and how lifestyle modulates gene regulation in skeletal muscle.

  Study phs004078

• Whole exome sequence of human XXY fibroblasts

  This dataset contains Whole exome sequence generated using human skin fibroblast sample (ID 419281) from Klinefelter XXY syndrome patient fibroblasts. These fibroblasts were used to generate autosomally isogenic human iPSCs. The sample DNA was collected using commercial kit and Human All Exon v5 capture paired library was sequenced using Illumina HiSeq device. The fastq file (ID 493224) and analysis (ID 3209) bam files have been deposited.

  Dataset EGAD50000001362

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set2)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of four B-other ALL patients (ALLT-321, ALLT-311, ALLT-314, ALLT-319). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using TruSeq DNA PCRfree library preparation kit v1. Both diagnostic (60x) and remission (30x) samples were sequenced using HiSeq X.

  Dataset EGAD50000002156

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set1)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of five B-other ALL patients (ALLT-327, ALLT-334, ALLT-357, ALLK-108, ALLT-361). Sequencing library was made using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (60x) and remission (30x) samples were sequenced using HiSeq X.

  Dataset EGAD50000002157

• Whole-exome sequencing of P2RY8-CRLF2-positive ALL on Illumina HiSeq 2000, 100 bp paired-end

  Genomic DNA from leukemic and remission bone marrow mononuclear cells was isolated with the QIAamp DNA Blood Extraction Kit (Qiagen, Venlo, The Netherlands). Libraries were prepared using Nextera Rapid Capture Exome Kit (Illumina, San Diego, USA). Paired-end sequencing of 100 bp reads was performed on a HiSeq 2000 (Illumina) to obtain at least a 50 x coverage.

  Dataset EGAD00001002666

• H3K27ac ChIP-seq of human acute leukemias and healthy donors

  H3K27ac ChIP-seq of 79 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). In addition, 4 samples derived from CD34+ cord blood cells of healthy donors were included.

  Dataset EGAD00001011060

• Heterogeneity in Lysosomal Storage Disorders

  Gaucher disease (GD) is an inherited lysosomal storage disorder caused by biallelic pathogenic variants in GBA1, which encodes glucocerebrosidase. Additionally, GBA1 variants are a well-established genetic risk factor for Parkinson's disease (PD), leading some PD research centers to incorporate GBA1 screening to identify patients who may benefit from targeted therapeutics. However, detecting GBA1 variants remains challenging due to the gene's high sequence homology with its pseudogene, which can give rise to complex recombinant alleles. This study evaluates the performance of Gauchian, a recently developed software tool for identifying GBA1 variants from whole genome sequencing (WGS) data. The assessment was conducted in a cohort of 90 individuals with GD and five GBA1 heterozygotes, all previously characterized through Sanger sequencing. While Gauchian successfully identified the most common genotypes, it demonstrated limitations in detecting rare or de novo variants due to its restricted internal database and heavy reliance on intergenic structural variants. These limitations led to misclassified homozygosity, incomplete genotyping, and undetected recombination events, ultimately reducing the tool's utility for comprehensive variant screening and precluding its application in diagnostic settings. The study dataset includes WGS from the 90 individuals used in the Gauchian pipeline. This data will be available through dbGaP to facilitate further research on GBA1 variant detection, genotype-phenotype correlations in GD and PD, and the development of improved bioinformatics tools for complex variant identification.

  Study phs003459

• Sensitive Monogenic Noninvasive Prenatal Diagnosis by Targeted Haplotyping

  During pregnancy, cell-free DNA (cfDNA) in maternal blood encompasses a small percentage of cell-free fetal DNA (cffDNA), an easilyaccessible source for determination of fetal disease status in risk families through non-invasive procedures. In case of monogenic heritabledisease, background maternal cfDNA prohibits direct observation of the maternally inherited allele. Non-invasive prenatal diagnostics(NIPD) of monogenic diseases therefore relies on parental haplotyping and statistical assessment of inherited alleles from cffDNA,techniques currently unavailable for routine clinical practice. Here, we present monogenic NIPD (MG-NIPD), which requires a bloodsample from both parents, for targeted locus amplification (TLA)-based phasing of heterozygous variants selectively at a gene of interest.Capture probes-based targeted sequencing of cfDNA from the pregnant mother and a tailored statistical analysis enables predicting fetalgene inheritance. MG-NIPD was validated for 18 pregnancies, focusing on CFTR, CYP21A2, and HBB. In all cases we could predict theinherited alleles with >98% confidence, even at relatively early stages (8 weeks) of pregnancy. This prediction and the accuracy ofparental haplotyping was confirmed by sequencing of fetal material obtained by parallel invasive procedures. MG-NIPD is a robustmethod that requires standard instrumentation and can be implemented in any clinic to provide families carrying a severe monogenicdisease with a prenatal diagnostic test based on a simple blood draw.

  Study EGAS00001002622

• Homozygous loss-of-function variants in European cosmopolitan and isolate populations

  Homozygous loss of function (HLOF) variants provide a valuable window on gene function in humans, as well as an inventory of the human genes that are not essential for survival and reproduction. All humans carry at least a few HLOF variants, but the exact number of inactivated genes that can be tolerated is currently unknown-as are the phenotypic effects of losing function for most human genes. Here, we make use of 1432 whole exome sequences from five European populations to expand the catalogue of known human HLOF mutations; after stringent filtering of variants in our dataset, we identify a total of 173 HLOF mutations, 76 (44%) of which have not been observed previously. We find that population isolates are particularly well suited to surveys of novel HLOF genes because individuals in such populations carry extensive runs of homozygosity, which we show are enriched for novel, rare HLOF variants. Further, we make use of extensive phenotypic data to show that most HLOFs, ascertained in population-based samples, appear to have little detectable effect on the phenotype. On the contrary, we document several genes directly implicated in disease that seem to tolerate HLOF variants. Overall HLOF genes are enriched for olfactory receptor function and are expressed in testes more often than expected, consistent with reduced purifying selection and incipient pseudogenisation.

  Study EGAS00001001606

• Breast cancer DNA repair

  Tumors of germline BRCA1/2 mutated carriers show homologous recombination (HR) deficiency (HRD), resulting in impaired DNA double strand break (DSB) repair and high sensitivity to Poly-(ADP-Ribose)-Polymerase (PARP) inhibitors. Although this therapy is expected to be effective beyond germline BRCA1/2 mutated carriers, a robust validated test to detect HRD tumors is lacking. In the present study we therefore evaluated a functional HR assay exploiting the formation of RAD51 foci in proliferating cells after ex vivo irradiation of fresh breast cancers (BrC) tissue: the RECAP test.Methods Fresh samples of 170 primary BrC were analyzed using the RECAP test. The molecular explanation for the HRD phenotype was investigated by exploring BRCA deficiencies, mutational signatures, tumor infiltrating lymphocytes (TILs) and microsatellite instability (MSI).Results RECAP was completed successfully in 148 out of 170 samples (87%). 24 tumors showed HRD (16%), while 6 tumors were HR intermediate (HRi) (4%). HRD was explained by BRCA deficiencies (mutations, promoter hypermethylation, deletions) in 16 cases. Several non-BRCA deficient HRD tumors showed BRCAness mutational signatures, suggesting that they are also bona fide HRD cases. HRD tumors showed an increased incidence of high TIL counts (p=0.023) compared to HR proficient (HRP) tumors and MSI was more frequently observed in the HRD group (2/20, 10%) than expected in BrC (1%) (p=0.017).Conclusion The RECAP test is a robust assay detecting both BRCA1/2 deficient and BRCA1/2 proficient HRD tumors, suggesting that this test identifies approximately 50% more patients that may benefit from PARPi treatment than BRCA gene testing only.

  Study EGAS00001002792

• Genomic landscape of poorly differentiated thyroid carcinoma

  Poorly differentiated thyroid carcinoma (PDTC) is a rare and aggressive subtype of thyroid cancer with limited molecular characterization. This study aims to define the somatic mutational landscape of PDTC using whole-genome sequencing. Paired tumour and matched normal blood samples were collected from six patients undergoing surgery. The overarching goal is to identify recurrent mutations, structural variants, and other genomic alterations associated with tumour aggressiveness and poor clinical outcomes.

  Study EGAS50000001134

• Sequencing of liver cancer cell lines

  Liver cancer is a dreadful disease with limited therapeutic options. How to translate genomic findings into biomarkers and precision treatment is challenging. A large cell line-based platform was established, termed as Liver Cancer Model Repository. Heterogeneities in patients were faithfully recapitulated by 81 liver cancer cell lines at genomic and transcriptomic levels. This platform provides a rich resource and models to study cancer drivers and drug responses in liver cancer.

  Study EGAS00001002237

• Exome sequences of AL amyloidosis (ALA), multiple myeloma (MM) and ALA+MM hematological malignancies

  DNA was isolated from aberrant plasma cells (aPCs) and peripheral blood of 12 ALA, 10 ALA+MM and 29 MM individuals. DNA from aPCs was amplified using REPLI-g Mini Kit (Qiagen). Totally, we analyzed 51 patients, 102 samples. One batch of exome libraries (paired tumor-normal samples from 12 ALA, 10 ALA+MM and 6 MM) was prepared using SureSelect Human All Exon V5 Kit (Agilent Technologies) and sequenced on Illumina HiSeq 4000 platform, 100 cycles. Second batch (23 MM samples; IDs ARK01-ARK26) was prepared using SureSelect Human All Exon V5 + IGH, IGK, IGL, MYC (Agilent Technologies) library preparation kit and sequenced on Illumina HiSeq 2000 platform in paired-end settings, 75 cycles. The reads were mapped using BWA-MEM on human genome GRCh38 without alternate loci.

  Dataset EGAD00001006047

• An integrated single-cell reference atlas of the human endometrium

  This dataset includes both the anchor scRNA-seq and snRNA-seq datasets used to build the Human Endometrial Cell Atlas (HECA). HECA provides a comprehensive definition of endometrial cell types and states throughout the menstrual cycle in donor with and without endometriosis. It identifies consensus cell types across datasets generated by teams worldwide, as well as previously unreported cell types, all of which are validated and mapped in situ using spatial transcriptomics. Processed data is available from ArrayExpress with accession number E-MTAB-14039. See Marečková, M., Garcia-Alonso, L., Moullet, M. et al. An integrated single-cell reference atlas of the human endometrium. Nat Genet 56, 1925–1937 (2024) https://doi.org/10.1038/s41588-024-01873-w for more information.

  Dataset EGAD00001015446

• Exome sequencing data from tumor progression cohort

  This dataset, named Stockholm tumor progression cohort, contains exome-sequencing samples of matched primary and metastasis samples from 20 metastatic breast cancer patients. All patients have one or more sequenced normal samples as well. The total number of samples is 125. The dataset has been used, apart from other studies, to explore tumor evolution patterns in metastatic breast cancer at Karolinska Institute Stockholm.

  Dataset EGAD00001003837

• scRNA transcriptome and TCR sequencing data modeling treatment responses in eight renal cell carcinoma patient

  Single cell RNA sequencing and coupled TCR sequencing data generated following immunological treatments in patient-derived ex vivo tumor models. Dataset consist of 46 sequencing samples originating from eight individual patient-derived ex vivo models. Single cell RNA and TCR sequencing data is generated using 10X Genomics platform with 5´ sequencing. The submission contains 46 Fastq files where each patient-derived ex vivo model and it's transcriptomic response to specified treatment is a unique sequencing run. TCR sequencing runs are submitted as one file per individual model, gathering all the treatment conditions.

  Dataset EGAD50000001934

• Strabismus, CCDD and other anomalies

  Strabismus is one of the most common ophthalmological diseases affecting our population. It has many detrimental effects for affected individuals, including functional visual loss from amblyopia, secondary psychosocial difficulties, and limited employment opportunities. Strabismus also imposes a significant economical burden on society from the cost of screening programs, surgical correction, and lost productivity. Congenital incomitant strabismus is a broad term that encompasses congenital ocular motility disorders with restricted movement in one or more directions of gaze, and includes various forms of Duane's retraction syndrome, horizontal gaze palsy, congenital fibrosis of extraocular muscles, and Moebius syndrome. Incomitant strabismus together with a group of related disorders such as congenital ptosis and congenital facial palsy have been collectively redefined as congenital cranial dysinnervation disorders (CCDDs). This redefinition stemmed from previous studies in the Engle lab showing that these disorders can be caused by mutations in genes encoding transcription factors critical to ocular cranial motor neuron development and by genes that encode proteins essential to the proper growth and guidance of developing axons. Thus, while these disorders account for only a small percent of strabismus, understanding their genetic etiology has led to our ability to provide genetic testing and counseling, and has provided the first insights into the molecular etiologies of strabismus. While the Engle lab has identified all seven CCDD genes published to date, our cohort still includes >100 familial CCDD pedigrees that are mutation-negative. We continue to utilize co-segregation analysis and whole exome or whole genome sequencing technologies to identify new disease genes in this mutation-negative cohort.

  Study phs000478