Additional file 1: of Quantitative metagenomics reveals unique gut microbiome biomarkers in ankylosing spondylitis

Table S1. Phenotype information of AS patient individuals and health controls in discovery stage (156 samples) and validation stage (55 samples). Table S2. Data production and quality control of 156 samples in discovery stage and 55 samples in validation stage. Table S3. The 8743 reference genomes from NCBI and HMP (downloaded on 15 Dec 2013). Table S4. The differentially abundant genus in AS patients (n = 73) and healthy controls (n = 83). Table S5. Assembly result of 156 samples in discovery stage. Table S6. The improvement with the repeatedly assembly. Table S7. Gene prediction of 156 samples in discovery stage. Table S8. Genes with abundance which belong to proteasome modules. All the differentially abundant genes identified in this study only belong to bacterial proteasome. Table S9. The taxonomic annotation of MGSs. Table S10. The phenotypic correlation analysis (p value) of 12 MGSs according to different clinical groups. Table S11. Comparison of the MGS in different diseases. Table S12. The taxonomic annotation of CAGs (Gene number ≥ 100). Table S13. The details of the best markers selected for five monitoring and classification models based on five kinds of bio-markers. Table S14. The 210 differentially abundant sequenced reference genome markers used for classification training. (XLSX 870 kb

Additional file 2: of Quantitative metagenomics reveals unique gut microbiome biomarkers in ankylosing spondylitis

Figure S1a. Venn diagram of three existing human gut gene catalogs. Figure S1b. Diversity of genera and species between AS patients and healthy controls. Figure S2. The Bacteroidetes/Firmicutes ratio in the AS patient group and in the healthy control group. Figure S3. Phylogenetic abundance under phylum, genus, and species levels between AS patients and healthy controls. Figure S4. Loss of richness of the gut microbiome in AS. Figure S5. The distribution of p values. Figure S6. The distribution of KEGG functional categories (statistics in Level 2) for all genes and differentially abundant genes. Figure S7. The distribution of detail pathways in four KEGG functional categories which were quite different between AS-enriched genes and control-enriched genes in Figure S6. Figure S8. The distribution of eggNOG functional categories for AS related markers. Figure S9. The distribution of KEGG module categories for AS related markers shown by number and percentage. Figure S10. Heatmap of the abundance of a random metagenomic species in both sequencing data and downloaded data. Figure S11. Taxonomic annotation of genes in CAGs by NT database. Figure S12. The NMDS (non-metric multidimensional scaling) analysis based on phylogenetic abundance profiling of all the 156 samples in the discovery cohort. (DOCX 4671 kb

Sample collections.

*<p>Numbers of samples by country of origin are listed in the <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003270#s3" target="_blank">Methods</a> section.</p><p>Case cohort names represent location of genotyping, and do not reflect country of origin of samples.</p

Association signal at the mapping intervals flanking rs34593439 and rs7553711.

<p>Association scores at 15q25.1 (panel A) and 1q25.1 (panel B). Genotyped (diamonds) and imputed (circles) SNPs are indicated and the top genotyped SNP in the interval is outlined in orange. A SNP in 15q25.1 previously associated with Diabetes is outlined in blue. The degree of red color in each diamond or circle indicates the strength of LD with the top SNP (on a scale shown in the legend at the upper left hand corner of the plot). The X-axis shows the chromosome and physical distance (kb) from the human genome reference sequence (hg19), the left Y-axis shows the negative base ten logarithm of the p-value and the right Y-axis shows recombination rate (cM/Mb) as a navy line. The genome-wide significance threshold (P<5×10⁻⁸) is given by the dashed grey line. Genes in the regions are annotated at the bottom as green arrows. Also indicated in 1q25.1 is a ∼130 kb region with no SNPs on the ImmunoChip.</p

Non-HLA narcolepsy risk variant loci reaching genome-wide significance.

<p>Chr.: Chromosome; BP: position according to NCBI build 36 (Hg18) coordinates; MAF_N: minor allele frequency in narcolepsy (_N) and controls (_C); P: P value according to variance component model (EMMAX). EMMAX does not provide OR (Odds Ratio) or adjusted allele frequencies, therefore MAF, OR, and 95% confidence intervals (CI) were calculated with Plink on subset of 8,474 samples with the greatest PCA homogeneity (see Figure S2; EV 11.21<0.004, EV 4.12<0.01).</p

Manhattan Plot of association statistics.

<p>The significance threshold used (blue line) was P = 5×10⁻⁸; The insets depict plots of 1) association results in a broad region encompassing the HLA locus (chr 6:24,067–35,474 kb) that were excluded from the present analysis (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003270#s3" target="_blank">Methods</a>) and 2) QQ plot of results for 109,777 markers after excluding a 1 Mb window surrounding the associated loci (λ = 1.004). The inflation statistic for all 111,240 tested markers is 1.04.</p