Unknown,Transcriptomics,Genomics,Proteomics

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Differentially expressed genes after inhibition of methylation

ABSTRACT: Expression microarray of livers from 4 dpf control zebrafish larvae, larvae treated with azacytidine, and ahcy mutant larvae Comparison of expression from livers obtained from ahcy+/+ treated with vehicle, ahcy+/+ treated with azacytidine, and ahcy-/- treated with vehicle. We treated larvae starting at 2 dpf with 1 mM azacytidine or vehicle control. Livers were removed at 4 dpf, RNA isolated, and double amplified.

ORGANISM(S): Danio rerio

SUBMITTER: Randolph Matthews

PROVIDER: E-GEOD-48804 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

DNA hypomethylation causes bile duct defects in zebrafish and is a distinguishing feature of infantile biliary atresia.

Matthews Randolph P RP Eauclaire Steven F SF Mugnier Monica M Lorent Kristin K Cui Shuang S Ross Megan M MM Zhang Zhe Z Russo Pierre P Pack Michael M

Hepatology (Baltimore, Md.) 20110211 3

<h4>Unlabelled</h4>Infantile cholestatic disorders arise in the context of progressively developing intrahepatic bile ducts. Biliary atresia (BA), a progressive fibroinflammatory disorder of extra- and intrahepatic bile ducts, is the most common identifiable cause of infantile cholestasis and the leading indication for liver transplantation in children. The etiology of BA is unclear, and although there is some evidence for viral, toxic, and complex genetic causes, the exclusive occurrence of BA ...[more]

PMID: 21319190

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Project description:Cutis laxa (CL) syndromes are a heterogenous group of connective tissue disorders that share a loose, redundant skin as a common clinical feature. The systemic features vary among the different subtypes. CL is caused by mutations in genes encoding for components of the extracellular matrix (FBLN4, FBLN5, LTBP4 and ELN), encoding for elastin-modifying enzymes (ATP7A) or encoding for components that influence cellular trafficking and metabolism (ATP6V1E1, ATP6V1A, ATP6V0A2, ALDH18A1, RIN2, GORAB, PYCR1 and SLC2A10). ATP6V1E1–related CL cause loose redundant skin folds, variable mental disability, typical facial characteristics, lipodystrophy, hypotonia, and cardiopulmonary involvement including pneumothorax, hypertrophic cardiomyopathy and aortic root dilatation. The intent of this study is to investigate which genes are up- or downregulated in atp6v1e1b-deficient zebrafish larvae compared to wild-type controls. Via transcriptome analysis, we want to study the pathogenic mechanism of ATP6V1E1-induced CL syndrome. We use a zebrafish line with viral insertion in the 5’UTR of atp6v1e1b, disrupting transcription (atp6v1e1bhi577aTg/+), from the Zebrafish International Research Center (ZIRC) and we use a line harboring a two base-pair insertion followed by a three base-pair deletion in exon 5 of atp6v1e1b, c.334insGG; c.337-340delCGG, predicted to result in p.R111WfsX2 (atp6v1e1bcmg78/+) which we created ourselves by CRISPR-Cas9 mutagenesis. Overview of the experimental work-flow: - Sample collection: pool of 10 zebrafish larvae of 3 dpf/genotype in RNA-later - RNA extraction: TRIzol® Reagent,RNeasy mini kit (Qiagen) according to manufacturer’s instructions - RNA integrity: 2100 Bioanalyzer (Agilent) - Sequencing library: TruSeq® Stranded mRNA Library Prep (Illumina, San Diego, California, United States) supplemented with TruSeq® RNA Single Indexes Set A (Illumina) - Sequencing: HiSeq 3000 sequencer (Illumina) - paired-end 150 bp - sequencing facility of the Center of Medical Genetics Ghent - alignement to zebrafish GRCz10 reference genome to generate bam files - RNA-seq pipeline was used that was published by the nf-core community. This pipeline was executed using the Nextflow engine for computational workflows and comprises several processing steps. QC analysis of the RNA-seq data was performed with FastQC and MultiQC. TrimGalore was used to remove adapter contamination and to trim low-quality regions. Duplicate reads were identified with MarkDuplicates. Subsequently, all cleaned and trimmed reads that passed QC were aligned to GRCz10 using STAR aligner. Gene counts were computed using the featureCounts package. Differential expression analysis subsequently was performed on these gene counts using DESeq2. Differentially expressed genes were identified using a fold change cut-off >1 and FDR=0.05. Finally, GO enrichment & pathway analysis were performed on differentially expressed gene sets using the Generally Applicable Gene-set Enrichment for Pathway Analysis (GAGE) algorithm.

Dataset Information

Differentially expressed genes after inhibition of methylation

Publications

DNA hypomethylation causes bile duct defects in zebrafish and is a distinguishing feature of infantile biliary atresia.

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