SI text 1: Automated Intergenic Spacer Analysis (ARISA) and sequence processing
workflows.
Sequencing was performed at Research and Testing Laboratories (Lubbock, Texas,
USA). For the bacteria the V4-V6 hypervariable region of the 16S gene was sequenced
on the Roche 454 FLX+ system (Roche, Basel, Switzerland); for the eukaryotes the V4
hypervariable region of the 18S rRNA gene was sequenced on the Illumina MiSeq
platform. Raw sequences were denoised (only 454 sequencing data) and quality trimmed
in mothur v.1.33.3 (Schloss et al. 2009) and submitted to SILVAngs (Quast et al. 2013)
for taxonomic classification. Clustering of OTUs was performed at 97% sequence
identity and taxonomic classification at 93% sequence identity on genus level. Sequence
counts were adjusted to the minimum number of sequences per sample (454 sequencing:
5249,
Illumina sequencing:
19474).
Single
OTU occurrences
and sequence
contaminations from animals and E. acroides were removed prior to the analysis of the
eukaryotic dataset (Logares et al. 2014). Sample C1 was dominated by OTUs assigned to
an annelid worm. After the removal of contaminating sequences, OTU richness in sample
C1 was much lower than in the other samples presumably due to the compositional
character of DNA samples, i.e. because of the presence of a highly dominant OTU, DNA
belonging to rare organisms was less likely to be sequenced than in samples with a more
even distribution. The larger number of eukaryotic OTUs in comparison to the bacterial
dataset was due to the increased sequencing effort with the Illumina technology. After
rarefying the eukaryotic sequences to the minimum of the bacterial sequence counts and
accounting for the large proportion of rare bacterial OTUs, i.e. comparing the number of
eukaryotic OTUs to the Chao1 estimated bacterial OTU richness, there were
approximately twice as many bacterial as eukaryotic OTUs. The eukaryotic community
data was further converted to presence/absence to account for multicellularity and
variations in rRNA gene copy number per genome (Prokopowich et al. 2003; Logares et
al. 2014).
SI references:
Logares, R. et al., 2014. Patterns of rare and abundant marine microbial eukaryotes.
Current biology : CB, 24(8), pp.813–821.
Prokopowich, C.D., Gregory, T.R. & Crease, T.J., 2003. The correlation between rDNA
copy number and genome size in eukaryotes. Genome, 46, pp.48–50.
Quast, C. et al., 2013. The SILVA ribosomal RNA gene database project: improved data
processing and web-based tools. Nucleic acids research, 41(Database issue),
pp.D590–6.
Schloss, P.D. et al., 2009. Introducing mothur: open-source, platform-independent,
community-supported software for describing and comparing microbial
communities. Applied and environmental microbiology, 75(23), pp.7537–41.