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• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Dataset EGAD00001006427

• RNA-seq study of human long-term and short-term hematopoietic stem cells from umblical cord blood with lentiviral overexpression of S1PR3

  To investigate the molecular and biological pathways altered by S1PR3OE in human hematopoietic stem cells (HSC), we performed RNA-sequencing (RNA-seq) of LT- and ST-HSC 3 days after transduction with control or S1PR3 overexpression (OE) lentiviral vectors. LT-HSC and ST-HSC from 3 pool of CB lin- were FACS-purified, cells were prestimulated for 4 hours and transduced with lentiviral vectors. At day 3, 2000-5300 BFP+ cells were FACS-purified for RNA isolation with a PicoPure kit. We were able to isolate only 1600-1800 BFP+ cells from LT-HSC control samples as opposed to 4000-5400 BFP+ cells from S1PR3OE samples. Thus, we pooled all control BFP+ LT-HSC cells into one sample for RNA-seq analysis. BFP- LT-HSC from control vector transduction were purified from CB1 as an additional LT-HSC control. Nextera libraries generated from 10 ng RNA from 5 LT-HSC samples (2 controls, 3 S1PR3OE) and 6 ST-HSC samples (3 controls, 3 S1PR3OE) were subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Center for Applied Genomics, Sick Kids Hospital.

  Dataset EGAD00001006582

• scRNA-seq of HSPC treated with gemcitabine and carboplatin

  4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. The raw FASTQ-files are available as read 1 and read 2 files from 4 lanes for each sample giving a total of 16 FASTQ-files. The FASTQ-files were also processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression (dge) for each cell of each sample. This has resulted in one dge text file and one dge summary text file per sample. These 8 text-files with dge data are found in the zip-compressed analysis data-file.

  Dataset EGAD00001006080

• Whole exome sequencing of a representative cohort of AML

  The Genomic DNA Clean & Concentrator kit (ZYMO Research) was used to remove EDTA from the DNA samples. Sample libraries were prepared using 100 ng of input according to the KAPA HyperPlus Kit (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Exomes were captured using the SeqCap EZ MedExome (Roche Nimblegen) according to SeqCap EZ HyperCap Library v1.0 Guide (Roche) with the xGen Universal blockers – TS Mix (Integrated DNA Technologies, Inc.). The amplified captured sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina) and aligned to the hg19 reference genome using the Burrows-Wheeler Aligner (BWA)3, v0.7.15-r1140.

  Dataset EGAD00001007580

• Mult-omics Palbociclib Resistance Study in HR+/HER2– Metastatic Breast Cancer

  This study is multi-omics study of a Asian longitudinal metastatic breast cancer (MBC) cohort treated with palbociclib plus endocrine therapy. It contains NGS of baseline (BL) and progressive disease (PD) from 70 patients, consisting of 79 tumor/normal matched whole exome sequencing (WES) from 62 patients and 90 tumor whole transcriptome sequecing samples (WTS) from 70 patients. There were 56 BL biopsies profiled by WES and 64 by WTS; 23 PD biopsies were profiled by WES and 26 by WTS. Twenty and 23 patients had paired BL and PD biopsies profiled by WES and WTS, respectively.

  Dataset EGAD00001008314

• 59 CLPD-NK cases WGS & WTS data

  For the cohort of 59 samples, we performed TruSeq DNA PCR-Free whole-genome sequencing library preparation according to manufacturer’s instructions (llumina, ILMN, San Diego, CA) on the automated NGS Star liquid handling platform (Hamilton, Bonaduz, Switzerland) followed by 2x150 bp paired-end sequencing on the HiSeqX or NovaSeq6000 (ILMN). An average coverage of >100x was achieved. For whole transcriptome analysis, the TruSeq Total Stranded RNA kit was used, starting with 250 ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (ILMN). 2x100bp paired-end reads were sequenced on the NovaSeq 6000 with a median of 50 mio. reads per sample (ILMN).

  Dataset EGAD00001008558

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010914

• Whole exome sequencing of tumors from the Precision Medicine Program in Pediatric and Adolescent Patients with Recurrent Malignancies

  Sequencing libraries were constructed according to standard procedures from 600 ng of tumor and paired constitutional DNA. WES was captured using Agilent SureSelect V5 (50 Mb), Clinical Research Exome (54 Mb) kit, SureSelect XT human All exon CRE version 1 or 2, or Twist Human Core Exome Enrichment System. Sequencing of subsequent libraries was performed using Illumina sequencers (Next-Seq 500 or Hiseq 2000/2500/4000) in 75 bp paired-end mode, aiming for a mean depth of coverage of 100x.

  Dataset EGAD00001010928

• Genomic Origins and Admixture in Latinos (GOAL)

  The GOAL Study was designed to comprehensively evaluate the genomic architecture of diverse Hispanic/Latino individuals with origins from the Caribbean, Central and South America, and to understand the impact of this diversity on genetic disease studies. Population structure and admixture are key confounders in genome-wide association and medical resequencing studies. In particular, accounting for difference in ancestry among cases and controls, both in terms of genomic and geographic location, is critical for proper analysis and interpretation of studies with multi- and trans-ethnic samples. Genomic studies of Hispanics/Latinos, the largest and fastest growing minority group in the US, reveal that they are a highly genetically heterogeneous admixed group with immense variation among individuals and populations in the proportions of African, European, and Native American ancestry. Knowledge of the underlying complex genetic structure of US Hispanic/Latino and Caribbean populations is, therefore, essential to ensuring robustness of genotype-phenotype associations and understanding the medical relevance of associated variants across diverse populations in the US and throughout the Americas. Furthermore, since much is known about the African and European migrations into the Americas over the past 500 years, population genetic studies of Hispanics/Latinos serve as an excellent model for developing novel algorithms and approaches for characterizing fine-scale genetic structure of admixed populations, in general. This project extends current studies of population genetic structure in US Hispanics/Latinos by densely genotyping parent-offspring triads from individuals (sampled in the US) of Caribbean-descent from six Latin American countries: Puerto Rico, Cuba, Dominican Republic, Haiti, Honduras and Colombia. This study will provide immediate insights and new statistical methods to improve study design and genetic analysis for medical genomic studies in Hispanics/Latinos, other complex admixed groups, and multi- and trans-ethnic studies.

  Study phs000750

• NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate

  The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741.

  Study phs001359