Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Human disease causing Kinetoplastids

ABSTRACT: Human disease causing Kinetoplastid wgs raw sequence reads

PROVIDER: PRJNA398352 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other
	NSCO01.dat.gz	Other
	NSCO01.fasta.gz	Fasta.gz
	NSCO01.master.dat	Other
	NSCR01.dat.gz	Other

Items per page:

1 - 5 of 30

Similar Datasets

S. pyogenes isolates causing invasive disease in England

Project description:Two S. pyogenes isolates causing invasive disease in England 2019

| PRJEB36425 | ENA

Streptococcus pyogenes emm1 causing invasive disease in Belgium (2020-2023)

Project description:Streptococcus pyogenes emm1 causing invasive disease in Belgium (2020-2023)

| PRJEB64886 | ENA

Rett syndrome-causing MECP2 mutations severely impact key cellular and molecular features of human astrocytes

Project description:Purpose: The goal of this RNA sequencing (RNA-seq) study is to identify aberrations in the astrocyte transcriptional landscape caused by R270X mutation in MECP2. Methods: mRNA-seq analysis was performed on total RNA extracted from human embryonic stem cell (ESCs)-derived wild-type (WT) and MECP2-R270X mutant astrocytes. The R270X mutation was inserted into ESCs (line H1) via CRISPR/Cas9 technology. Samples were generated in triplicates, sequenced by Illumina NovaSeq 6000 Sequencing System. Raw reads were first trimmed for 10 bases at the 5’end to remove reads with biased nucleotide (ACGT) distribution. Trimmed reads were then aligned to the Homo sapiens genome (GRCh38p12, GENCODE, primary assembly), using STAR aligner. Differential gene expression (DEG) analyses on the read counts were performed using DESeq2. Genes with sum of read counts across all samples with less 10 were filtered out from analysis. Results: Our RNA-seq analysis showed that 1,621 genes were dysregulated in mutant astrocytes (fold-change >1.5 or <2/3; padj < 0.05, average reads count >10 in at least one genotype)

2024-02-15 | GSE185726 | GEO

Identification of Disease-Causing Mutations in SCID using Exome-Wide Sequencing

Project description:Identification of Disease-Causing Mutations in SCID using Exome-Wide Sequencing

| PRJNA104971 | ENA

TEFM variants impair mitochondrial transcription elongation causing childhood-onset neurological disease

Project description:TEFM variants impair mitochondrial transcription elongation causing childhood-onset neurological disease

| PRJNA768394 | ENA

Characterizing Disease-causing Variants Using Personal Genomes with Large Recurrent Deletions

Project description:Characterizing Disease-causing Variants Using Personal Genomes with Large Recurrent Deletions

| PRJNA763971 | ENA

Characterizing Disease-causing Variants Using Personal Genomes with Large Recurrent Deletions

Project description:Characterizing Disease-causing Variants Using Personal Genomes with Large Recurrent Deletions

| PRJNA763972 | ENA

Pathogenic PDE12 variants impair mitochondrial RNA processing causing neonatal-onset mitochondrial disease

Project description:The PDE12 gene codes for the poly(A)-specific exoribonuclease, involved in the quality control of mitochondrial non-coding RNAs. Here, we report that disease-causing PDE12 variants in three unrelated families are associated with mitochondrial respiratory chain deficiencies. Clinically, they presented in utero and within the neonatal period with muscle and brain involvement leading to marked cytochrome c oxidase (COX) deficiency in muscle and severe lactic acidosis. To analyze perturbations in specific cellular pathways contributing to pathogenesis in our patient cohort, we used Affymetrix Clariom D transcriptome arrays to study the RNA levels in fibroblasts derived from two patient (Patient 2 and patient 3), comparing these to age-matched controls.

2024-09-29 | E-MTAB-14251 | biostudies-arrayexpress

Functional dissection of human cardiac enhancers and non-coding de novo variants in congenital heart disease

Project description:About 45% of congenital heart disease (CHD) is caused by rare gene mutations. Non-coding mutations that perturb cis-regulatory elements (CREs) likely contribute to CHD among the remaining cases without clear etiology. However, identifying CHD-causing non-coding variants has been problematic. We combined human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) differentiation and a lentivirus-mediated massively parallel reporter assay (lentiMPRA) to create a high-throughput platform to measure human cardiac enhancer activity. We tested 2451 candidate human cardiac enhancers, identified 1185 with measurable activity, and functionally dissected 123 of these by systematic tiling mutagenesis. We functionally evaluated 6761 non-coding de novo variants (ncDNVs) prioritized from the whole genome sequencing (WGS) of 749 CHD trios. 397 ncDNVs significantly affected cardiac CRE activity. Remarkably, 53% of these ncDNVs increased enhancer activity, often at regions with undetectable enhancer activity in the reference sequence. We introduced 10 of these DNVs associated with CHD genes into iPSCs and found that 4 altered expression of neighboring genes. Moreover, these 4 DNVs also altered cardiomyocyte differentiation, as assessed by single nucleus RNA sequencing. Using the MPRA data, we developed a regression model to prioritize future DNVs for functional testing and demonstrate that this model finds enrichment of DNVs in a second, independent WGS cohort. Taken together, we developed a scalable system to measure the impact of non-coding DNVs on CRE activity and deployed this platform to systematically assess the contribution of non-coding DNVs to CHD.

2022-08-05 | GSE210376 | GEO

Whole Genome Sequencing of Tongue cancer samples and cell line

Project description:Whole genome sequencing (WGS) of tongue cancer samples and cell line was performed to identify the fusion gene translocation breakpoint. WGS raw data was aligned to human reference genome (GRCh38.p12) using BWA-MEM (v0.7.17). The BAM files generated were further analysed using SvABA (v1.1.3) tool to identify translocation breakpoints. The translocation breakpoints were annotated using custom scripts, using the reference GENCODE GTF (v30). The fusion breakpoints identified in the SvABA analysis were additionally confirmed using MANTA tool (v1.6.0).

2024-02-17 | E-MTAB-12534 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data