DOI: 10.5061/dryad.gr3ks
title: Data from: Viral tagging reveals discrete populations in Synechococcus viral genome sequence space

description: Microbes and their viruses drive myriad processes across ecosystems
 ranging from oceans and soils to bioreactors and humans. Despite this
 importance, microbial diversity is only now being mapped at scales
 relevant to nature, while the viral diversity associated with any
 particular host remains little researched. Here we quantify
 host-associated viral diversity using viral-tagged metagenomics, which
 links viruses to specific host cells for high-throughput screening and
 sequencing. In a single experiment, we screened 107 Pacific Ocean viruses
 against a single strain of Synechococcus and found that naturally
 occurring cyanophage genome sequence space is statistically clustered into
 discrete populations. These population-based, host-linked viral ecological
 data suggest that, for this single host and seawater sample alone, there
 are at least 26 double-stranded DNA viral populations with estimated
 relative abundances ranging from 0.06 to 18.2%. These populations include
 previously cultivated cyanophage and new viral types missed by decades of
 isolate-based studies. Nucleotide identities of homologous genes mostly
 varied by less than 1% within populations, even in hypervariable genome
 regions, and by 42–71% between populations, which provides benchmarks for
 viral metagenomics and genome-based viral species definitions. Together
 these findings showcase a new approach to viral ecology that
 quantitatively links objectively defined environmental viral populations,
 and their genomes, to their hosts.
description: RandomizationsX1500To estimate the variability within a population from the available metagenomic data, random candidatus genomes (CG) were generated as follows using a series of custom perl scripts. First, we recruited reads to each CG requiring at least 95% identity and a coverage of 95% of the entire length of the read. Each read was non-redundantly assigned and aligned to a CG using default parameters in MUSCLE. For each CG population, we generated 100 random CG sequences using the metagenomic data that were recruited to consensus sequences, with each base having a probability of being assigned from its relative abundance in the underlying metagenomic sequence data. Here we show the result of 1500 randomizations.ANI_2_PCAMatrix of ANI values as obtained from each a comparison of each candidatus genome and the reference genome. This file is used as the input to perform a PCA, which is the figure shown in the manuscript.Viral Tagged Metagenome 454This is identical to VT_MG.fna as it appears in CAM_P_0001068 in camera.VT_MG.fnaCommunity MetagenomeIdentical to Comm_MG.fna under CAM_P_0001068.Comm_MG.fnaGP23_SequencesGp23 Sequences amplified from the isolates, data incorporated into table 1.DATA-FIGURESTabulated data for all the figures in the manuscript.Rarefaction filesThe zip folder includes the script and tables used to generate the rarefaction curves and richness index. The tables are structured as Read, Protein, Protein ClusterRAREFACTION.zipConsensusCGsAssembly and gene predictions (CDS and aminoacid sequences) for the 26 candidatus genomes referred in the manuscript.VT_MG_ILFastq sequencing data of the simplified metagenome after a Viral Tagging Experiment.