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• Linguistic utterance counts for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_225CaboVerde_FreeSpeech_Utterance_counts_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See See Material and Methods in Romain Laurent et al. 2022 - doi pendingColumn 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See Material and Methods in Laurent R et al. eLife 2023

  Dataset EGAD00001008978

• Papua New Guinean Genome Diversity Project (PGDP)

  The PGDP dataset includes 58 whole genome sequences for Papua New Guinean individuals from different locations. DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer. The PGDP dataset provides Fastq and BAM files.

  Dataset EGAD00001007783

• Dataset for leiomyosarcoma-RNA

  Rare cancer sequencing data of 87 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008849

• Dataset for head_and_neck_cancer-RNA

  Rare cancer sequencing data of 92 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008861

• BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle

  BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle (2 paired tumor-normal samples and 11 tumor-only samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from 13 patients with chordoid glioma of the third ventricle using the QIAamp DNA FFPE Tissue Kit (Qiagen). Genomic DNA was also extracted from leukocytes in a peripheral blood sample from one of the patients and a non-neoplastic gastric biopsy specimen from one of the patients. Capture-based next-generation DNA sequencing was performed at the University of California, San Francisco Clinical Cancer Genomics Laboratory, using an assay that targets all coding exons of approximately 500 cancer-related genes, select introns of 47 genes, and TERT promoter with a total sequencing footprint of 2.8 Mb (UCSF500 Cancer Panel). Sequencing libraries were prepared from genomic DNA, and target enrichment was performed by hybrid capture using a custom oligonucleotide library (Nimblegen SeqCap EZ Choice). Captured libraries were sequenced as paired-end 100 bp reads on an Illumina HiSeq 2500 instrument. Duplicate sequencing reads were removed computationally to allow for accurate allele frequency determination and copy number calling.

  Dataset EGAD00001003818

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010117

• Genetic-epigenetic tissue mapping for plasma DNA: applications in prenatal testing, transplantation and oncology

  We developed Genetic-Epigenetic Tissue Mapping (GETMap) to determine the tissue composition of plasma DNA carrying genetic variants not present in the constitutional genome through comparing their methylation profiles with relevant tissues.

  Dataset EGAD00001007041

• Molecular Evolution of Cancer

  Recently developed methods that utilize partitioning of long genomic DNA fragments, and barcoding of shorter fragments derived from them, have succeeded in retaining long-range information in short sequencing reads. These so-called read cloud approaches represent a powerful, accurate, and cost-effective alternative to single-molecule long-read sequencing. We developed software, GROC-SVs, that takes advantage of read clouds for structural variant detection and assembly. We apply the method to two 10x Genomics data sets, one chromothriptic sarcoma with several spatially separated samples, and one breast cancer cell line, all Illumina-sequenced to high coverage. Comparison to short-fragment data from the same samples, and validation by mate-pair data from a subset of the sarcoma samples, demonstrate substantial improvement in specificity of breakpoint detection compared to short-fragment sequencing, at comparable sensitivity, and vice versa. The embedded long-range information also facilitates sequence assembly of a large fraction of the breakpoints; importantly, consecutive breakpoints that are closer than the average length of the input DNA molecules can be assembled together and their order and arrangement reconstructed, with some events exhibiting remarkable complexity. These features facilitated an analysis of the structural evolution of the sarcoma. In the chromothripsis, rearrangements occurred before copy number amplifications, and using the phylogenetic tree built from point mutation data, we show that single nucleotide variants and structural variants are not correlated. We predict significant future advances in structural variant science using 10x data analyzed with GROC-SVs and other read cloud-specific methods.

  Study phs001255

• High-Resolution Clonal Mapping of Multi-Organ Metastasis, and Resistance to Neoadjuvant Chemotherapy, in Triple Negative Breast Cancer

  Clonal dynamics during metastasis were studied in two patient-derived xenograft (PDX) models established from treatment-naive primary breast tumors from TNBC patients diagnosed with concurrent metastatic disease. Genomic sequencing and barcode-mediated clonal tracking revealed robust alterations in clonal architecture between primary tumors and metastases. Polyclonal seeding and maintenance of low-abundance subclones was observed in each metastatic lesion examined. Lung, liver, and brain metastases were enriched for an identical population of subclones. Clones dominating multi-organ metastases shared a genomic lineage. Thus, properties of rare mammary tumor subclones enabled the seeding and colonization of metastases in multiple secondary organ sites. In this study, patient-derived xenograft (PDX) models of treatment-naive TNBC and serial biopsies from TNBC patients undergoing NACT were used to elucidate mechanisms of chemoresistance in the neoadjuvant setting. Barcode-mediated clonal tracking and genomic sequencing of PDX tumors revealed that residual tumors remaining after chemotherapy maintained the subclonal architecture of untreated tumors yet their transcriptomes, proteomes, and histologic features were distinct from those of untreated tumors. Once treatment was halted, residual tumors gave rise to chemotherapy-sensitive tumors with similar transcriptomes, proteomes, and histological features to those of untreated tumors. Taken together, these results demonstrated that tumors can adopt a reversible drug-tolerant state that does not involve clonal selection as a chemotherapy resistance mechanism. Serial biopsies obtained from patients with TNBC undergoing NACT revealed similar histologic changes as well as maintenance of stable subclonal architecture, demonstrating that PDXs capture molecular features characteristic of human TNBC chemoresistance.

  Study phs001742

• Impact of Glycolysis Inhibition on the Epigenome of Synovial Fluid T Cells in Juvenile Idiopathic Arthritis

  Juvenile Idiopathic Arthritis (JIA) encompasses a group of childhood-onset autoimmune conditions characterized by joint inflammation and mononuclear cell infiltration, especially of activated CD4+ memory/effector T (Tmem/Teff) cells in synovial fluid (SF). JIA CD4+ T cells exhibit a distinct inflammation-associated epigenomic profile, though the underlying molecular mechanisms remain unclear. This study investigates the role of glycolysis in shaping the epigenomic landscape of JIA SF CD4+ T cells, with a focus on H3K27ac histone modifications. Using an ex vivo model of antigen stimulation, CD4+ T cells were isolated from peripheral blood (PB) of healthy controls (HC) and synovial fluid from JIA patients. Cells were activated in vitro with anti-CD3/CD28 for 24 hours, and changes in H3K27ac were assessed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). To explore the specific role of glycolysis, cells were also treated with 2-deoxyglucose (2DG), an inhibitor of glucose-6-phosphate production. This inhibition impacted both H3K27ac acetylation patterns and gene expression associated with the activated epigenomic regions. Additionally, HC CD4+ T cells were activated in vitro in the presence of 30% SF or 30% plasma from JIA patients. RNA sequencing (RNA-seq) was performed to examine SF-induced transcriptional changes, providing insight into the metabolic dysregulation and epigenomic alterations observed in JIA SF CD4+ T cells. This dataset includes ChIP-seq and RNA-seq data that collectively advance our understanding of how glycolysis and the SF environment contribute to the epigenetic and transcriptional regulation in JIA CD4+ T cells.

  Study EGAS50000000808