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• A transcriptome atlas of human skeletal muscles

  We generated a large transcriptome atlas of human skeletal muscles by collecting biopsies from 6 different muscles to determine molecular signatures that may be distinct between leg muscles. The biopsies were collected from gracilis (GR), semitendinosus (ST), vastus lateralis (VL), vastus medialis (VM), rectus femoris (RF), and gastrocnemius lateralis (GL) muscles. We also investigated molecular differences within the muscle by including two biopsies from the middle and distal sides of the semitendinosus muscle (STM and STD, respectively). In total, 128 samples from 20 individuals (aged 25 ± 3.6 yr) were analyzed.

  Study EGAS00001005904

• Diagnosis of multisystem inflammatory syndrome in children by a whole-blood transcriptional signature

  To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki Disease (KD), bacterial infections and viral infections. Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020-April 2021 were prospectively recruited. Whole blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C to those from children with KD, definite bacterial and viral infections. Data deposited here comprises samples from patients recruited into the DIAMONDS study.

  Study EGAS00001007409

• Targeted Myeloid DNA-Panelsequencing, DKFZ

  Targeted myeloid DNA-Panelsequencing from purified bone marrow blasts of 104 treatment naive AML patients from the discovery cohort. For more details, we refere to Jayavelu, Wolf, Buettner et al. Libraries were prepared from 40 ng DNA using the QIASeq Human Myeloid Neoplasms Panel (Qiagen) according to the manufacturer’s protocol. Samples were tagged with the QIAseq 96-Unique Dual Index Set A for Illumina platforms (Qiagen) to yield unique combinations of i5 and i7 barcodes for each sample. Sample fragment size distribution and concentration was estimated using the Agilent High Sensitivity DNA kit on a 2100 Bioanalyzer (Agilent). Samples were pooled in an equimolar fashion, denatured, and diluted to 1.5 pM according to Illumina’s recommendations. The diluted library was sequenced on a NextSeq 500 benchtop sequencer (Illumina) using NextSeq High Output cartridges. Demultiplexing was performed using the BaseSpace cloud platform (Illumina).

  Dataset EGAD00001008501

• The effect of freezing delay of cell-type specific transcriptome responses in human brain via snRNA-seq

  In other analysis in the current manuscript, we find a similar gene signature (to dissociation based artifacts in mouse and human tissue) is present in post-mortem microglia and astrocytes, across all snRNA-seq datasets analyzed, although it is highly variable between subjects. ​ Using acutely-resected neurosurgical tissue, we performed single-nucleus RNA-seq and reveal that a similar signature can be detected in microglia following prolonged exposure to room temperature. Tissue handling and methods details, as well as sequencing and analysis details) can be found in the methods section of related manuscript (Marsh et al., 2022). Together, these results suggest that the presence of this signature in post-mortem brain samples may be the result of a combination of acute pre-mortem (agonal state, cause of death, comorbidities, etc.) and post-mortem (post-mortem interval (PMI), storage time, RNA quality, etc.) variables and may not represent normally present cell state.

  Dataset EGAD00001008541

• Convergent somatic evolution from early life in a germline ribosomopathy

  Clonal tracking of stem cells and their progeny by whole genome sequencing permits exploration of evolutionary genetics in human disease. In this study, we performed phylogenetic reconstruction of haematopoiesis using somatically acquired mutations in 323 single haematopoietic stem and progenitor cell-derived colonies from 10 individuals with an inherited disorder of ribosome assembly, Shwachman-Diamond syndrome. We observed numerous clonal expansions, with recurrent acquisition of mutually exclusive mutations (EIF6, TP53, RPL5, RPL22, PRPF8, chromosomes 7 and 15) in multiple different clones in utero or early childhood converging on the p53-dependent nucleolar surveillance pathway that monitors ribosome integrity. In contrast to clones carrying biallelic TP53 mutations, genomes derived from colonies carrying mono-allelic TP53 mutations displayed no increase in mutation burden or specific mutational signatures. Our study highlights striking loss of clonal diversity with convergent somatic evolution on the p53-dependent nucleolar surveillance pathway from early life to offset the deleterious effects of a germline mutation in a Mendelian haematopoietic disorder.

  Dataset EGAD00001009061

• NEOPREDICT-Lung: longitudinal whole exome sequencing of non-small cell lung cancers under immunotherapy

  In 43 patients pretreatment tumor biopsies, resected tumors and normal tissue of sufficient quality and quantity were obtained to longitudinally explore the mutational profiles of a comprehensive set of cancer-related genes. For tumor samples, one to four FFPE sections (10 µm thickness, number depending on sample size) were lysed for genomic DNA isolation. Isolation was performed semi-automatically on the Maxwell purification system (Maxwell RSC DNA FFPE Kit, AS1450, Promega) as specified by the manufacturer. DNA was eluted in 50 µl RNase-free water and quantified fluorescently for library preparation using a Qubit 2.0 fluorometer (Life Technology) with its appertaining DNA broad-range assay. Corresponding normal DNA was isolated from blood or PBMCs using routinely available QIAGEN technology. DNA was stored at -20°C before use. Whole-exome sequencing (WES) was performed using the Twist Human Core + RefSeq + Mitochondrial Panel (Twist Bioscience), and 2 x 100 bp fragment sizes were sequenced using a NovaSeq6000 (Illumina). Demultiplexing of sequenced reads was achieved using bcl2fastq (version 2.2).

  Dataset EGAD00001015362

• Transcriptional consequences of SETBP1 variants in developmental disorders and malignancies

  The SETBP1 gene encodes a DNA-binding nuclear protein that regulates gene expression across multiple tissues. Precise control of SETBP1 dosage is essential for normal cellular function, as both loss- and gain-of-function variants of SETBP1 can lead to severe phenotypic consequences. De novo germline gain-of-function point mutations that prolong SETBP1 half-life result in Schinzel-Giedion syndrome (SGS), an ultra-rare and severe congenital disorder associated with extensive developmental abnormalities and health complications. These SGS-associated variants cluster within a hotspot in the SKI-homology domain of SETBP1, overlapping with somatic mutations recurrently observed in myeloid leukaemia with poor prognosis. Thus far, the precise mechanisms by which these SETBP1 mutations drive disease remain largely unclear. Here, through single-cell and single-nucleus mRNA sequencing of a rare collection of primary patient samples with SGS and myeloid leukaemia, we examined the transcriptional consequences of SETBP1 gain-of-function variants in haematopoietic cells, comparing their impacts when acquired in the germline and somatically in malignancies.

  Dataset EGAD00001015482

• Genomic and Functional Profiling of Acral Melanoma from the admixed Brazilian Population Reveals Disease Drivers and Targetable Vulnerabilities

  Acral melanoma, a subtype of melanoma characterized by its occurrence on palms, soles, and beneath the nails, presents unique challenges in diagnosis and treatment due to its distinct genetic and environmental factors. Despite recent advancements in targeted therapies for melanoma, the efficacy of treatments in acral melanoma remains limited, emphasizing the urgent need for a deeper understanding of its genetic landscape. CRISPR-based functional genomics screening has emerged as a powerful tool for uncovering genetic dependencies and potential therapeutic targets in various cancers. In this project, we present the results of CRISPR screening performed on acral melanoma cell lines to identify genes essential for cell survival and proliferation collectively termed “fitness". Through this screening approach, we aim to elucidate the molecular mechanisms underlying the pathogenesis of acral melanoma and identify novel therapeutic vulnerabilities. Our findings reveal key genetic drivers and pathways implicated in acral melanoma progression, offering potential targets for the development of precision therapies tailored to this aggressive subtype of melanoma

  Dataset EGAD00001015690

• A next-generation dual guide CRISPR system for genetic interaction library screening

  Raw sgRNA sequencing data from a pilot CRISPR screening library to test the dual guide vector system (8,914 guide pairs), and from a large scale genetic interaction screen (~100,136 guide pairs) in HT-29 cells. This data refers to Burgold et al. Nature Communications 2025.

  Dataset EGAD00001015754

• The mutational landscape of normal human endometrial epithelium

  All normal somatic cells are thought to acquire mutations. However, characterisation of the patterns and consequences of somatic mutation in normal tissues is limited. Uterine endometrium is a dynamic tissue undergoing cyclical shedding and reconstitution lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands showed that most are clonal cell populations derived from a recent common ancestor, with mutation burdens differing from other normal cell types and many fold lower than endometrial cancers. Mutational signatures found ubiquitously account for most mutations. Many, in some women all, endometrial glands are colonised by cell clones carrying driver mutations in cancer genes, often with multiple drivers. Total and driver mutation burdens increase with age, but are also influenced by other factors, including body mass index and parity, and clones with drivers often originate during early decades of life. The somatic mutational landscapes of normal cells differ between cell types and are revealing the procession of neoplastic change leading to cancer.

  Dataset EGAD00001004547