Supplementary Table 1

Bacterial reads assigned to the genus level in all samples analyzed, as identified by sample ID and subject ID. Samples have been pre-filtered for singleton OTUs and sub-sampled at a depth of 1,500 sequences.<br

Additional file 2: Figure S1. of Commensal microbiota modulate gene expression in the skin

Quality control of RNA-sequencing data. (A) Mean quality score per base for each of the 16 samples. (B) Number of reads mapping to the mouse reference genome for each sample. (C) Relative abundance of reads mapping to each biotype. (D) Percentage of the genome covered by mapped reads per sample. (EPS 1354 kb

Additional file 9: Figure S4. of Commensal microbiota modulate gene expression in the skin

Analysis of skin immune cell populations supports gene expression findings. (A) Toluidine blue staining for mast cells. (B) Immunofluorescence staining of CD3, a pan T cell marker. Significance testing was performed on an aggregate of three experiments with n = 3 GF and SPF mice each. (C) Flow cytometry analysis of GF and SPF (n = 5 each) of IL-1α and IL-1β production by cell subset. Comparisons that are significantly different with a p value < 0.05 are denoted with * and those with a p value < 0.01 with **. (D) Barplots showing normalized gene expression values for IL-1α and IL-1β. Lines depict standard error and padj represents the FDR-corrected p value (1-prob) calculated by NOISeqBio. (E) Boxplot of normalized gene expression of terminal differentiation markers Krt1 and Krt14, with padj indicating the FDR-corrected p value (1-prob) calculated by NOISeqBio. (EPS 85855 kb

Additional file 3: of Commensal microbiota modulate gene expression in the skin

Dataset S1. Results from differential expression analysis. Rows contain the 15,448 features analyzed. Columns contain Ensembl feature id, mean expression of GF samples, mean expression of SPF samples, the NOISeq differential expression statistic theta, the probability of differential expression (equal to 1-FDR-corrected p value when using NOISeqBio, DEGs defined as those with prob. > 0.9), the log2 fold change in expression (upregulated in GF > 0, downregulated in GF < 0), feature length, chromosome, feature start and end coordinates, feature biotype, and feature symbol. (XLSX 2289 kb

Additional file 1: Table S1. of Commensal microbiota modulate gene expression in the skin

Sample summary statistics. Rows contain the 16 samples analyzed; with columns containing associated sequencing statistics and metadata. (XLSX 56 kb

Additional file 7: Table S2. of Commensal microbiota modulate gene expression in the skin

WGCNA gene module characterization. Top 5 significantly enriched biological process gene ontology terms (Bonferroni p < 0.05) associated with each WGCNA module. (XLSX 47 kb

Additional file 10: Figure S5. of Commensal microbiota modulate gene expression in the skin

DGCA analysis identified significantly correlated DEGs that share potential transcription factor binding sites. Analysis with oppossum3 identified enriched transcription factors in positively correlated DGCA gene sets, using Z scores to assess significance. The y-axis identifies significant transcription factors, while x-axis represents the significance metric, with higher values indicating greater significance, and the shape indicating whether the metric score was 1 or 2 standard deviations (SD) above the mean. Z scores are significant when greater than 2 SD above the mean. Size of each point reflects the percentage of all DGCA +/+ DEGs containing a binding region for each TF and color indicates colonization status of the DGCA +/+ DEGs. (EPS 1582 kb

Le Cri du peuple : journal politique quotidien

13 octobre 18881888/10/13 (A5,N1815)-1888/10/13

Le Cri du peuple : journal politique quotidien

04 février 18901890/02/04 (A7,N1996)-1890/02/04