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• HuBMAP: Single-Cell Multiplex Chromatin and RNA Interactions in Aging Human Brain

  The study employs the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique to concurrently profile multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei, revealing dynamically organized chromatin complexes in human frontal cortex samples from elderly donors. The MUSIC technique allows for the exploration of chromatin architecture and transcription at cellular resolution in complex tissues. The study includes 14 human cortex tissues and employs MUSIC to delineate diverse cortical cell types and states, revealing that nuclei with fewer short-range chromatin interactions correlate with an "older" transcriptomic signature and Alzheimer's pathology. Additionally, the study elucidates that specific cell types, characterized by chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter, are particularly susceptible to the regulatory impact of these cis eQTLs on target gene expression. Furthermore, the female cortical cells exhibit highly heterogeneous interactions between the X-inactive specific transcript (XIST) non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

  Study phs003568

• UK10K_OBESITY_GS

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The GS samples are part of the Obesity group and will undergo exome sequencing.

  Study EGAS00001000242

• Genome-wide cell-free DNA fragmentation in patients with cancer

  Cell-free DNA (cfDNA) in the blood provides a noninvasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an approach to evaluate fragmentation patterns of cfDNA across the genome and found that cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles. We applied this method to analyze fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancers and 245 healthy individuals. A machine learning model incorporating genome-wide fragmentation features had sensitivities of detection ranging from 57% to >99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation based cfDNA analyses detected 91% of cancer patients. The results of these analyses highlight important properties of cfDNA and provide a proof of principle approach for screening, early detection, and monitoring of human cancer.

  Study EGAS00001003611

• Evolutionary analysis of primary tumors and metastatic lesions from 20 breast cancer patients (99 samples in total) using exome sequencing data.

  Metastatic breast cancers are still incurable. Characterizing their evolutionary landscape including the role of metastatic axillary lymph nodes to seed distant organ metastasis can provide rational basis for effective treatments. Here, we describe the genomic analyses of the primary tumors and metastatic lesions from 20 breast cancer patients (99 samples). Our evolutionary analyses revealed diverse spreading and seeding patterns governing tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, where multiple metastatic subclones originated from primary tumor and/or other distant metastases. Synchronous axillary lymph node metastasis, a well-established prognosticator of breast cancer, was not involved in seeding distant metastasis, suggesting haematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably a significant increase in apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) associated mutagenesis. Our data provide the first genomic evidence regarding the role of axillary lymph node metastasis in seeding distant organ metastasis and elucidates the evolving mutational landscape during cancer progression.

  Study EGAS00001002737

• Whole-Genome Sequencing of Salivary Gland Adenoid Cystic Carcinoma

  Adenoid cystic carcinomas (ACCs) of the salivary glands are challenging to understand, treat, and cure. To better understand the genetic alterations underlying the pathogenesis of these tumors, we performed comprehensive genome analyses of 25 fresh-frozen tumors, including whole genome sequencing, expression and pathway analyses. In addition to the well-described MYB-NFIB fusion which was found in 11 tumors (44%), we observed five different rearrangements involving the NFIB transcription factor gene in seven tumors (28%). Taken together, NFIB translocations occurred in 15 of 25 samples (60%, 95%CI=41–77%). In addition, mRNA expression analysis of 17 tumors revealed overexpression of NFIB in ACC tumors compared with normal tissues (p=0.002). There was no difference in NFIB mRNA expression in tumors with NFIB fusions compared to those without. We also report somatic mutations of genes involved in the axonal guidance and Rho family signaling pathways. Finally, we confirm previously described alterations in genes related to chromatin regulation and Notch signaling. Our findings suggest a separate role for NFIB in ACC oncogenesis and highlight important signaling pathways for future functional characterization and potential therapeutic targeting.

  Study EGAS00001002812

• Dataset SNP tumours

  This dataset contains 30 idat files each from 15 SNP array runs on patient colitis-associated colorectal cancer tumours. All phenotypes are cancer. See Baker et al. 2018 Supplementary Table 2 for patient details of 12 tumours used in the analyses in the publication.

  Dataset EGAD00010001587

• SNPArray_Thai

  The compressed file contains plink format file for the Affymetrix Human Origins SNP array data of 452 individuals generated and analyzed in Kutanan, Liu et al 2021 study of 33 ethnolinguistic groups in Thailand and Laos.

  Dataset EGAD00010002285

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  These are 28 targeted exome sequencing fastq files (tumour and germline) generated from ovarian cancer samples which had been exposed to PARP inhibitors, for the described project.

  Dataset EGAD50000000206

• CRC cell line ATAC-seq

  ATAC-Seq data for C32, CACO2, CL11, HT29, SW403, SW480, SW948 MSS CRC cell lines, and HCEC-1CT normal colon cell line

  Dataset EGAD50000000296

• NTNU Data Access Committee for “ProstOmics: spatial and bulk multi-omics of prostate cancer” datasets archived in Federated EGA Norway

  The ProstOmics project of NTNU contains spatial and bulk multi-omics datasets of prostate cancer, and access request to these datasets are handled by this Data Access Committee on behalf of NTNU.

  Dac EGAC50000000277