Pathway analysis for liver transcripts from <i>R. catesbeiana</i> (CAT) and <i>X. laevis</i> (LAE).

<p>Top 25 impacted pathways after TH treatment for <i>R. catesbeiana</i> ranked by the highest proportion of overall observed genes. The pathway names are indicated in the center of the figure with the total number of genes known in each IGA pathway indicated. The asterisk indicates those pathways that are found in the top 25 list of <i>X. laevis</i>. The colour coded bar plots illustrate the percentage of the total number of gene transcripts in a pathway that are downregulated (blue), non-responsive (yellow), upregulated (red) or not observed in the experiment (gray) relative to the control condition. Differentially expressed transcripts were determined using a p-value threshold of 5%.</p

RNA-seq data and transcriptome assembly results.

<p>Sequences were generated using 75 bp paired end reads.</p><p>RNA-seq data and transcriptome assembly results.</p

Gene ontology classification of DESeq-selected, TH-responsive <i>R. catesbeiana</i> and <i>X. laevis</i> liver transcripts with UniProtKB AC numbers.

<p>The two series in each stacked bar plot correspond to differentially expressed <i>R. catesbeiana</i> (CAT) and <i>X. laevis</i> (LAE) transcripts, with a p-value threshold of 5%.</p

Gene ontology classification of all reconstructed <i>R</i>. <i>catesbeiana</i> and <i>X. laevis</i> liver transcripts with UniProtKB AC numbers.

<p>The two series in each stacked bar plot correspond to all <i>R. catesbeiana</i> (CAT) and <i>X. laevis</i> (LAE) transcripts.</p

Differential expression of assembled transcripts for (A) <i>R. catesbeiana</i> and (B) <i>X. laevis</i>.

<p>Three shades of purple designate p-values of differential expression estimates 0.05, 0.02 and 0.002, lighter colours indicating lower thresholds.</p

Unweighted UniFrac distances

The unweighted UniFrac distance (Lozupone and Knight AEM 2005) matrix of the 9511 fecal samples used in the American Gut paper. UniFrac was computed using Striped UniFrac (https://github.com/biocore/unifrac). Prior to execution of UniFrac, Deblur (Amir et al mSystems 2017) was run on the samples, all bloom sOTUs were removed (Amir et al mSystems 2017), and samples were rarefied to a depth of 1250 reads (Weiss et al Microbiome 2017). For the phylogeny, fragments were inserted using SEPP (Mirarab et al Pac Symp Biocomput 2012) into the Greengenes 13_5 99% OTU tree (McDonald et al ISME 2012)

Full American Gut Project mapping file

The full American Gut Project mapping file, includes non-fecal samples

movie_s2.mp4

Placing changes in the microbiome in the context of the American Gut. We accumulated samples over sequencing runs to demonstrate the structural consistency in the data. We demonstrate that while the ICU dataset (https://www.ncbi.nlm.nih.gov/pubmed/27602409) falls within the American Gut samples, they do not fall close to most samples at any of the body sites. We then highlight samples from the United Kingdom, Australia, the United States and other countries to show that nationality does not overcome the variation in body site. We then highlight the utility of the American Gut in meta-analysis by reproducing results from (https://www.ncbi.nlm.nih.gov/pubmed/20668239) and (https://www.ncbi.nlm.nih.gov/pubmed/23861384), using the AGP dataset as the context for dynamic microbiome changes instead of the HMP dataset. We show rapid, complete recovery of C. diff patients following fecal material transplantation and also contextualized the change in an infant gut over time until it settles into an adult state. This demonstrates the power of the American Gut dataset, both as a cohesive study and as a context for other investigations

ag_tree.tre

The SEPP (Mirarab et al Pac Symp Biocomput 2012) fragment insertion tree used for phylogenetic analyses