Ontology highlight
ABSTRACT:
PROVIDER: PRJEB85531 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Whole exome sequencing BAM files and whole genome sequencing CRAM files for 722 individuals from the NIHR-BioResource Rare Diseases Consortium (SPEED project) with inherited retinal disease.
| EGAD00001002656 | EGA
Project description:<p>We investigated the cumulative contribution of rare, exonic genetic variants on the concentration of 1,487 metabolites and 53,714 metabolite ratios in urine by performing gene-based tests based on 226,233 variants from up to 4,864 participants of the German Chronic Kidney Disease (GCKD) study. There were 128 significant associations (53 metabolite-gene and 75 metabolite ratio-gene pairs) involving 30 unique genes, 16 of which are known to underlie recessively inherited inborn errors of metabolism (IEMs). Across the 30 genes, 47% of individuals carried at least one rare missense, stop or splice variant. The 30 genes were strongly enriched for shared high expression in liver and kidney (OR=65, p-FDR=3e-7), with hepatocytes and proximal tubule cells as driving cell types. Use of whole-exome sequencing data in the UK Biobank allowed for linking genes to diseases that could plausibly be explained by the identified metabolites. In silico constraint-based modeling of knockouts of the implicated genes in a virtual whole-body, organ-resolved metabolic human correctly predicted the observed direction of metabolite changes in urine and blood, highlighting the potential of linking population genetics to modeling to validate associations and to predict metabolic consequences of yet unknown IEMs. Our study extends the map of genes influencing urine metabolite concentrations, reveals metabolic processes and connected health outcomes, and implicates novel candidate variants and genes for IEMs.</p><p><br></p><p>Further links;</p><p><a href='https://www.gckd.org/' rel='noopener noreferrer' target='_blank'>German Chronic Kidney Disease (GCKD)</a></p>
2021-03-09 | MTBLS284 | MetaboLights
Project description:The raw data consist of whole exome sequencing data of cervical squamous samples
2022-02-11 | E-MTAB-11407 | biostudies-arrayexpress
Project description:Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Inherited Retinal Disorders (IRD) Rare Disease domain
| EGAD00001004520 | EGA
Project description:The human neural retina is enriched for alternative splicing, and it is estimated that more than 10% of variants associated with inherited retinal diseases (IRDs) alter splicing. Previous research mainly used short-read RNA-sequencing techniques to investigate retina-specific splicing and splicing factors. However, this technique provides limited information about transcript isoforms. To gain a deeper understanding of the human neural retina and its isoforms, we generated a proteogenomic atlas that combined PacBio long-read RNA-sequencing data with mass-spectrometry and whole-genome sequencing data from three healthy human neural retina samples. RNA-sequencing revealed that one-third of all transcripts were novel, and for IRD-associated genes, even 43% were novel. The most common novel elements of these transcripts were alternative poly(A) sites, exon elongation, and intron retention. Some novel elements affect the non-coding region but for more than 50% of the novel transcripts a novel open reading frame was predicted. Using proteomics, ten novel peptides confirmed novel isoforms in five genes. Additionally, we found novel isoforms of IMPDH1, an IRD-associated gene, with supporting peptide evidence. This study provides a comprehensive overview of the transcript and protein isoforms expressed in the healthy human neural retina. Moreover, it highlights the importance of studying tissue specific transcriptomes in greater detail to better understand tissue-specific regulation and to identify disease-causing variants.
2024-10-17 | PXD045187 | Pride
Project description:Fourteen LGSOC cell lines were interrogated using whole exome sequencing, RNA sequencing, and mass spectrometry-based proteomics. Somatic mutation, copy-number aberrations, gene and protein expression were analyzed and integrated using different computational approaches. LGSOC cell line data was compared to publicly available LGSOC tumor data (AACR GENIE cohort), and also used for predictive biomarker identification of MEK inhibitor (MEKi) efficacy. Protein interaction databases were evaluated to identify novel therapeutic targets.
2021-05-17 | PXD019544 | Pride
Project description:Purpose: There are three goals of this study: 1. To compare the genomic, exome and chromatin accessiblity profiles of the specific engineered fallopian tube cells of high-grade serous tubo-ovarian cancer (HGSC) models (this study) using whole-exome, whole-genome and ATAC-seq sequencing. Methods: For whole-exome analysis, genomic DNA was extracted from the cell lines mentioned below. Conclusions: We conclude that whole-exome, whole-genome and ATAC-seq characterization would expedite genetic network analyses and permit the dissection of complex biological functions.
2020-11-17 | GSE159253 | GEO