Computational protocol: Novel Genes Critical for Hypoxic Preconditioning in Zebrafish Are Regulators of Insulin and Glucose Metabolism

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Protocol publication

[…] High-quality RNA was amplified with the MessageAmp kit (Ambion) and labeled fluorescently with Cy3 or Cy5-dUTP (Amersham) in a reverse-transcription reaction using Superscript (Invitrogen). Labeled cDNA was rinsed and pooled with 20 μg of each of salmon sperm DNA, poly-A RNA, and tRNA, which were then concentrated to a small volume in a Microcon YM-30 column. Samples were added to full-genome zebrafish microarrays designed using the Zv7 genome assembly and containing 385,000 probes at approximately 12 probes for each of 37,157 genes (071105_Zv7_EXPR; NimbleGen, Inc.) (). Hybridization, washes, and scanning were performed per standard protocol. Biological replicates were performed with “dye-flipping” so that each duplicate sample was labeled with the opposite dye as the first experimental sample. The resulting dataset was filtered and analyzed with R/Bioconductor and Limma to confirm normal distributions of intensities and the absence of significant region-specific artifact prior to inclusion into the dataset for normalization and downstream analysis. An established empirical Bayesian method for differential expression in microarrays (eBayes) was used to determine P values of individual genes taking into account multiple hypothesis testing, the overall data distribution for all genes, and the small number of biological replicates typical in genome-wide datasets (, ). Microarray source data are available at NCBI GEO (Accession number: GSE68473;, and the R code used for the analysis can be reviewed in full in the Supporting Information, File S1. Top hypoxia-induced genes were filtered to retain only those genes that had a single unambiguous probe BLAT match to the later Zv9 genome assembly, for which RNA-seq or EST evidence was available (UCSC genome browser, Z-seq) (), and for which an identifiable human homolog existed in RefSeq and/or Ensembl databases (Table S1 and Table S2). […]

Pipeline specifications

Software tools limma, BLAT
Databases UCSC Genome Browser
Applications RNA-seq analysis, Genome data visualization
Organisms Danio rerio, Homo sapiens
Diseases Kidney Diseases
Chemicals Glucose