15041 results for "cancer studies using rna-seq"

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• Genotype data from 'Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture.'

  Previous studies have highlighted how African genomes have been shaped by a complex series of historical events. Despite this, genome-wide data has only been obtained from a small proportion of present-day ethnolinguistic groups. By analysing new autosomal genetic variation data of 1333 individuals from over 150 ethnic groups from Cameroon, Republic of the Congo, Ghana, Nigeria and Sudan, we demonstrate a previously underappreciated fine-scale level of genetic structure within these countries, for example correlating with historical polities in western Cameroon. By comparing genetic variation patterns among populations, we infer that many northern Cameroonian and Sudanese groups share genetic links with multiple geographically disparate populations, likely resulting from long-distance migrations. In Ghana and Nigeria, we infer signatures of intermixing dated to over 2000 years ago, corresponding to reports of environmental transformations possibly related to climate change. We also infer recent intermixing signals in multiple African populations, including Congolese, that likely relates to the expansions of Bantu language-speaking peoples.

  Study EGAS00001006944

• Introducing Federated EGA Affiliates: a newly defined tier in the Federated EGA Network

  We're happy to announce that we are now accepting Affiliates in the Federated EGA Network! Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Currently, Federated EGA consists of Central EGA (CEGA), which serves the global community, and nine national Nodes that serve respective jurisdictions. Did you know that the Federated EGA (FEGA) has always envisioned a third tier within the network? This brings us to FEGA Affiliates, recently defined in the newly approved "Federated EGA Structure and Organisation" document. This new tier broadens the range of institutions or organisations that can become part of FEGA. Thus begins a new era for the network. What is a FEGA Affiliate? A FEGA Affiliate archives and serves controlled-access data within its own governance scope, while still participating in federated discovery through the EGA catalogue. Affiliates can be individual organisations or institutions, healthcare genomics initiatives, consortia of institutions, as well as project-specific consortia (national or international). In practical terms, a FEGA Affiliate: Hosts and safeguards the data it archives. Submits non-personal metadata to CEGA so studies are discoverable and can receive EGA accessions. Manages permissions and data access workflows for its datasets. Provides data access and/or distribution, along with support, to authorised users. Key takeaways about FEGA Affiliates FEGA is now organised into three tiers: CEGA, FEGA Nodes, and FEGA Affiliates. Affiliates archive data from their own organisation and/or selected partner institutions (for example, an international consortium). Affiliates make studies discoverable through the EGA catalogue by submitting non-personal metadata for accessioning. Access decisions and conditions are managed locally by the Affiliate (e.g. distribution or access in a trusted research environment). Are you considering whether your institution or project might be a good fit as a FEGA Affiliate? Would you like to learn more about this tier? We have published a blog post that addresses potential common questions, providing answers on this topic. You can read it here.

  Blog fega-affiliates

• GDAP - Genome Diversity in Africa Project (2021-02-12)

  The Genomic Diversity in Africa Project (GDAP) started with the plan to develop a genomic resource from African populations, characterise genomic diversity and population history, and facilitate clinical studies in Africa. Currently, 25 individuals from 24 ethnolinguistic groups have been whole-genome sequenced at high depth totalling 585 individuals. An additional 41 individuals have been sequenced with 10X Genomics libraries. At this stage, the initial curation of this dataset has been finished and we are performing the analysis in coordination with our collaborators. The current state of the GDAP represents a very diverse panel of African populations that maximizes geographical and ethnic variation and represents a great starting point to achieve the aforementioned goals. However, southern sub-Saharan countries, Bantu speakers and hunter gatherer groups are currently underrepresented, despite being crucial to understand the evolutionary history of the continent. After extensive effort to collate studies documentation, we finally have the opportunity to sequence 600 new individuals from these groups, including countries as Gabon, Rwanda and Zambia, and address these deficiencies. We aim to proceed with the same strategy: to sequence at high depth 25 individuals with standard PCR free libraries, with 2 additional individuals with 10X Genomics Chromium libraries per ethnolinguistic group. The former allows a good representation of variants down to low frequency in any given population, and the latter allows accurate phasing and the analysis of structural variation. By including these new populations, we want to investigate three crucial questions in African history in addition to the initial objectives: the Bantu expansion, the evolutionary history of hunter gatherers and the transatlantic slave trade. Additionally, the expanded dataset will help us better discover the genetic variation present in Africa and characterize the African pangenome. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2021-02-12.

  Dataset EGAD00001006965

• Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma

  The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT’s regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation. Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as druggability for future translational studies and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.

  Study EGAS00001008140

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001000416 study data is whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology

  Study EGAS00001000416

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Kazakhs (DNA samples from the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan; Gulnara Svyatova, Principal Investigator

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001000417 study data is whole genome sequencing of 100 unrelated Kazakhs in order to impute genotypes into PE cases and controls from Kazakhstan and to provide genetic data and infrastructure for future genetic studies in Kazakhstan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator)

  Study EGAS00001000417

• Genotypic data of the individuals in HPP project

  Dataset contains imputed SNP genetics data for human phenotype project https://humanphenotypeproject.org/. The samples are genotypes of 8958 individuals that underwent genetic sequencing based on buccal swab.Sequencing is performed at Neogen GeneSeek Laboratories using Illumina Novaseq at low-pass, targeting coverage levels of 0.5× and 1×. Imputation was done using loimpute-v0.1.0 over the aligned reads. Imputation is done for the autosomal chromosomes (1-22) using The 1000 Genomes phase 3 haplotypes (1KGP3) as a reference panel. The samples are provided in merged PLINK 1 binaries (.bed/.bim/.fam)

  Dataset EGAD00010002714

• stem cell-derived beta cells from cell lines RC9 and HUES8

  stem cell-derived beta cells differentiated using two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade). iPSC stem cell lines were differentiated to pancreatic islets using differentiation protocol as detailed by Rajaei et al. (2025, Science Translational Medicine, accepted for publication). scRNAseq was done at stage 7 of differentiation (day 30) using 10X genomics 3' sequencing. Cells were annotated then subsetted for beta cells for downstream analysis

  Dataset EGAD50000001322

• RRBS of 25 pleural mesothelioma samples (Single-end)

  The dataset contains RRBS data (bam files) for 25 pleural mesothelioma samples.The samples were sequenced on NovaSeq6000 (Illumina, San Diego, CA) in single-end 150bp mode. RRBS raw reads were trimmed for adaptor sequences using trim galore (v. 0.6.5) (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) and filtered for low-quality sequences using fastQC (v. 0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). High quality trimmed reads were mapped to the Human reference genome (UCSC genome assembly GRCh38/hg38) using Bismark (v. 0.22.3) with default parameters.

  Dataset EGAD50000002130

• WGS data of paediatric ETV6::RUNX1 B cell acute lymphoblastic leukemia (set1)

  The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of five ETV6::RUNX1 ALL patients (ALLT-380, ALLK-114, ALLT-388, ALLT-392, ALLT-394). Sequencing libraries were made using PCR free-based WGS library preparation (PCR-), using NEBNext® Ultra™ II DNA Library Prep Kit (Cat No. E7645). Both diagnostic (90x) and remission (30x) samples were sequenced using Illumina NovaSeq 6000.

  Dataset EGAD50000002285