PSEAE CF.2010

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Web supplement for 'Huse HK, Kwon T, Zlosnik JEA, Speert DP, Marcotte EM, Whiteley M, Parallel evolution in Pseudomonas aeruginosa over 39,000 generations in vivo, mBio, 1(4):pii:e00199-10 (2010) PubMed '

Correction

May 5, 2013: In reprocessing some of these data, we realized that genes were selected at a p-value < 0.05, not an FDR < 0.05. All genes in Table 1 remain significant at the more stringent FDR < 0.05 threshold in at least two of the three patients.

Figures

Fig1_PatientDiagram.1col.thumb.jpg

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Fig2_Microarray_Clustering.1col.thumb.jpg

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Fig3_Heatmap_DE_between_groups.2col.thumb.jpg

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Fig4_DEFC_within_group.1col.thumb.jpg

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Fig5_DE_VennDiagram.1col.thumb.jpg

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Supplement Tables

  • Table S1. P. aeruginosa strains used in this study MS Excel
  • Table S2. Orthologous genes from P. aeruginosa strains PAO1, PA14, PA7, and LESB58 MS Excel
  • Table S3. Affymetrix microarray annotation MS Excel
  • Table S4. Genes expressed differently in clonal groups MS Excel
  • Table S5. Genes expressed differently in ancestors and strain PA14 MS Excel
  • Table S6. Genes expressed differently within clonal groups over time MS Excel

Microarray data

CEL files

TXT files

Compressed by gzip.

Probe mapping to PAO1

A BASH shell script to run exonerate: 

EXONERATE="/home/taejoon/bin64/exonerate"
PROBE_FILE="PSEAE_1.affy_probes.fasta"

GENOME_DIR="/home/taejoon/pkgenome.data/PCAP"
TARGET_NAME="PSEAE_PAO1.NC_002516.fna"

GENOME_FILE="$GENOME_DIR/$TARGET_NAME"
GENOME_MAP_FILE=${PROBE_FILE/%fasta/$TARGET_NAME.exonerate}
echo "$PROBE_FILE vs. $GENOME_FILE"
echo "#PROBE_FILE : $PROBE_FILE" > $GENOME_MAP_FILE
echo "#GENOME_FILE : $GENOME_FILE" >> $GENOME_MAP_FILE
$EXONERATE -m affine:local -Q dna -T dna --showvulgar no --showcigar no --showalignment no \
--ryo "%qi %ti %tS %qab %qae %tab %tae %et %ei %es %em %s %C\n " $PROBE_FILE $GENOME_FILE >> $GENOME_MAP_FILE

TARGET_NAME="PSEAE_PAO1.PCAP20091123.dna.fasta"
CDNA_FILE="$GENOME_DIR/$TARGET_NAME"
CDNA_MAP_FILE=${PROBE_FILE/%fasta/$TARGET_NAME.exonerate}
echo "$PROBE_FILE vs. $CDNA_FILE"
echo "#PROBE_FILE : $PROBE_FILE" > $CDNA_MAP_FILE
echo "#CDNA_FILE : $CDNA_FILE" >> $CDNA_MAP_FILE
$EXONERATE -m affine:local -Q dna -T dna --showvulgar no --showcigar no --showalignment no \
--ryo "%qi %ti %tS %qab %qae %tab %tae %et %ei %es %em %s %C\n " $PROBE_FILE $CDNA_FILE >> $CDNA_MAP_FILE

R script for preprocessing

dataset_name <- 'Huse2010_GSE21966'
library(affy)

exp_table <- read.table(file="EXP",header=T,stringsAsFactors=FALSE,sep="\t")
files_vector <- as.vector(exp_table$Filename,mode='character')
samples_vector <- as.vector(exp_table$Sample,mode='character')
affybatch_raw <- ReadAffy(filenames=files_vector,sampleNames=samples_vector)

save(affybatch_raw, file=paste(dataset_name,'.affybatch_raw', sep=''))
write.table(intensity(affybatch_raw),
            file=paste(dataset_name,'.raw.txt', sep=''))

affybatch_corrected <- bg.correct(affybatch_raw, method='rma')
save(affybatch_corrected,
            file=paste(dataset_name,'.affybatch_corrected', sep=''))
write.table(intensity(affybatch_corrected),
            file=paste(dataset_name,'.corrected.txt', sep=''))

affybatch_normalized <- normalize(affybatch_corrected, method='quantiles')
save(affybatch_normalized,
            file=paste(dataset_name,'.affybatch_normalized',sep=''))
write.table(intensity(affybatch_normalized),
            file=paste(dataset_name,'.norm.txt', sep=''))

eset_rma <- rma(affybatch_raw)
save(eset_rma, file=paste(dataset_name,'.eset_rma',sep=''))
write.exprs(eset_rma,
            file=paste(dataset_name,'.eset_rma.txt',sep=''))

R script for ANOSIM test

library(vegan)
tbl <- read.table('Huse2010_GSE21966.gene_mean.txt',header=T,row.names='Gene')
t_tbl <- t(tbl)

tbl_dist <-  as.dist(1-cor(as.matrix(tbl),method='spearman'))
igroup <- c('A','A','A','A','A','B','B','B','B','B','B','B','Ca','Ca','Cb','Cb','Cb','R','R')
tbl_igroup_anosim <- anosim(tbl_dist,igroup)

tgroup <- c('E','M','M','M','L','E','M','M','M','L','L','L','E','L','E','M','L','R','R')
tbl_time_anosim <- anosim(tbl_dist,tgroup)

mgroup <- c('C','C','M','D','D','C','C','D','M','M','C','M','C','M','M','D','M','R','R')
tbl_morphology_anosim <- anosim(tbl_dist,mgroup)

R script for detecting differentially expressed genes

library(limma)
library(affy)

## Read target information
targets <- readTargets("EXP")
affybatch_raw <- ReadAffy(filenames = targets$Filename)
eset_rma <- rma(affybatch_raw)

## Patient - Splitting P3
igroup_detail <- factor(targets$Isogenic, levels=c("A","B","Ca","Cb","PAO1","PA14"))
design_igroup_detail <- model.matrix(~0+igroup_detail)
colnames(design_igroup_detail) <- c(levels(igroup_detail))

fit_igroup_detail <- lmFit(eset_rma, design_igroup_detail)
fit_igroup_detail <- eBayes(fit_igroup_detail)
contrast_igroup_detail <- makeContrasts(B-A,Ca-A,Cb-A,Ca-B,Cb-B,Cb-Ca,
                          levels=design_igroup_detail)
contrast_fit_igroup_detail <- contrasts.fit(fit_igroup_detail, contrast_igroup_detail)
contrast_fit_igroup_detail <- eBayes(contrast_fit_igroup_detail)
top_B_A <- topTable(contrast_fit_igroup_detail, n=nrow(contrast_fit_igroup_detail),
                        coef=1, adjust="fdr", resort.by="logFC")
write.table(top_B_A,"DE_between_group/igroup_B_A.top.txt")
top_Ca_A <- topTable(contrast_fit_igroup_detail, n=nrow(contrast_fit_igroup_detail),
                        coef=2, adjust="fdr", resort.by="logFC")
write.table(top_Ca_A,"DE_between_group/igroup_Ca_A.top.txt")
top_Cb_A <- topTable(contrast_fit_igroup_detail, n=nrow(contrast_fit_igroup_detail),
                        coef=3, adjust="fdr", resort.by="logFC")
write.table(top_Cb_A,"DE_between_group/igroup_Cb_A.top.txt")
top_Ca_B <- topTable(contrast_fit_igroup_detail, n=nrow(contrast_fit_igroup_detail),
                        coef=4, adjust="fdr", resort.by="logFC")
write.table(top_Ca_B,"DE_between_group/igroup_Ca_B.top.txt")
top_Cb_B <- topTable(contrast_fit_igroup_detail, n=nrow(contrast_fit_igroup_detail),
                        coef=5, adjust="fdr", resort.by="logFC")
write.table(top_Cb_B,"DE_between_group/igroup_Cb_B.top.txt")
top_Cb_Ca <- topTable(contrast_fit_igroup_detail, n=nrow(contrast_fit_igroup_detail),
                        coef=6, adjust="fdr", resort.by="logFC")
write.table(top_Cb_Ca,"DE_between_group/igroup_Cb_Ca.top.txt")

Raw data for DE genes between clonal groups

Raw data for DE genes within clonal groups

Genome/Annotation data

All data were downloaded from http://www.pseudomonas.com on November, 23, 2009.

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