DOI: 10.5061/dryad.w0vt4b8tz
title: Data from: Host phylogeny and functional traits differentiate gut microbiomes in a diverse natural community of small mammals

description: Differences in the bacteria inhabiting mammalian gut microbiomes tend to
 reflect the phylogenetic relatedness of their hosts, a pattern dubbed
 phylosymbiosis. Although most research on this pattern has compared the
 gut microbiomes of host species across biomes, understanding the
 evolutionary and ecological processes that generate phylosymbiosis
 requires comparisons across phylogenetic scales and under similar
 ecological conditions. We analyzed the gut microbiomes of 14 sympatric
 small-mammal species in a semi-arid African savanna, hypothesizing that
 there would be a strong phylosymbiosis pattern associated with the
 different body sizes and diets of the mammalian lineages present.
 Consistent with phylosymbiosis, microbiome dissimilarity
 increased with phylogenetic distance among hosts, ranging from congeneric
 sets of mice and hares that did not differ significantly in microbiome
 composition to species from different taxonomic orders that had almost no
 gut bacteria in common. While phylosymbiosis was detected among just the
 11 species of rodents, it was substantially weaker than comparisons
 involving all 14 species together. In contrast, microbiome diversity and
 composition were generally more strongly correlated with body size,
 dietary breadth, and dietary overlap in comparisons restricted to rodents
 than in those including all lineages. The starkest divides in microbiome
 composition thus reflected the broad evolutionary divergence of hosts,
 regardless of body size or dietary composition, while subtler microbiome
 differences reflected variation in ecologically important traits between
 closely related hosts. Strong phylosymbiotic patterns arose deep in the
 phylogeny, and ecological filters that promote functional differentiation
 of cooccurring host species may disrupt or obscure this pattern near the
 tips.
description: <em><strong>Microbiome data: before
 rarefying</strong></em> This dataset was
 created by running the DADA2 sequence-variant algorithm (dadaFs/Rs) on
 dereplicated paired-end sequences with their assigned error rates. After
 running the DADA2 algorithm, we merged error-free forward and reverse
 sequence reads into ASVs and removed chimeras. 
 ASV_table.csv
 <em><strong>Microbiome data: Contamination
 Removed</strong></em> We screened potential
 contaminants by comparing ASVs from the mock community sequenced with our
 samples against the sequences from the mock reference community provided
 by the manufacturer. We identified 9 ASVs that did not match the mock
 reference community for removal from all samples as putative contaminants.
 File ASV_table_contamination_removed represents the remaining ASVs after
 the removal of all contaminants.
 ASV_table_contamination_removed.csv
 <em><strong>Microbiome data:
 Rarefied</strong></em> All our microbiome
 diversity and composition comparisons were performed on the rarefied
 table. We rarefied data representing 7,720,016 sequences across 126
 samples to the lowest read depth (N = 7,017 reads per sample). This final
 dataset contained 9,887 ASVs, including singletons that were retained
 after rarefying.  ASV_table_rarefied.csv