DOI: 10.5061/dryad.8mr56
title: Data from: Gene expression associated with white syndromes in a reef building coral, Acropora hyacinthus

description: Background: Corals are capable of launching diverse immune defenses at the
 site of direct contact with pathogens, but the molecular mechanisms of
 this activity and the colony-wide effects of such stressors remain poorly
 understood. Here we compared gene expression profiles in eight healthy
 Acropora hyacinthus colonies against eight colonies exhibiting tissue loss
 commonly associated with white syndromes, all collected from a natural
 reef environment near Palau. Two types of tissues were sampled from
 diseased corals: visibly affected and apparently healthy. Results:
 Tag-based RNA-Seq followed by weighted gene co-expression network analysis
 identified groups of co-regulated differentially expressed genes between
 all health states (disease lesion, apparently healthy tissues of diseased
 colonies, and fully healthy). Differences between healthy and diseased
 tissues indicate activation of several innate immunity and tissue repair
 pathways accompanied by reduced calcification and the switch towards
 metabolic reliance on stored lipids. Unaffected parts of diseased
 colonies, although displaying a trend towards these changes, were not
 significantly different from fully healthy samples. Still, network
 analysis identified a group of genes, suggestive of altered immunity
 state, that were specifically up-regulated in unaffected parts of diseased
 colonies. Conclusions: Similarity of fully healthy samples to apparently
 healthy parts of diseased colonies indicates that systemic effects of
 white syndromes on A. hyacinthus are weak, which implies that the coral
 colony is largely able to sustain its physiological performance despite
 disease. The genes specifically up-regulated in unaffected parts of
 diseased colonies, instead of being the consequence of disease, might be
 related to the originally higher susceptibility of these colonies to
 naturally occurring white syndromes.
description: Count
 dataTable of count data from
 processed reads. Columns are samples. Rows are genes.25july_diseasecounts.tabDESeq2 scriptDESeq2 script to analyze gene expression from count data. This script will call for the counts file.deseq2_Ahya_Final.RPrincipal coordinate analysis scriptScript for principal coordinate analysis of gene expression data with the R package vegan. This script will call for variance stabilized data generated in DESeq2.PCoA_Ahya_Final.RVariance stabilized gene expression data and p-valuesVariance stabilized gene expression and p-values were generated using the R package DESeq2. Row names are gene names. Column names are either sample names (columns 1-24) or p-values (columns 25-30). The letters following the p-value (pval or padj, for unadjusted and FDR corrected p-values respectively) indicate the contrast used to generate the pvalue: AH = ahead of the lesion to healthy, DA = disease to ahead of the lesion, DH = disease to healthy.VSDandPVALS_disease.csvWGCNA scriptScript for network analysis of gene expression using the R package WGCNA. The script will require variance stabilized gene expression data for all samples and a table of trait values for each sample.WGCNA_Ahya_Final.RVariance stabilized gene expression data for WGCNAVariance stabilized gene expression data for all samples from the top differentially expressed genes (unadjusted p-value &lt; 0.1) for network analysis with the R package WGCNA. Rows are genes. Columns are samples.genes4WGCNA.csvSamples and traits for WGCNATable of traits for samples for network analysis with the R package WGCNA. Rows are samples. Columns are traits. Values are binary indicators of whether the sample is positive for that trait. Traits are AL, H, and D for the three disease states (ahead of the lesion, healthy, and diseased) and 1-16 for each genotype.diseasetraits_reps.csvAcropora hyacinthus transcriptomeThe version of the transcriptome used for this analysis.ahyac_jan2012.fasta