DOI: 10.5061/dryad.612jm6487
title: Data from: Virus community structuring is shaped by habitat heterogeneity and resource utilisation strategies

description: After decades of disconcerted research, we still recognise large gaps in
 the understanding of mechanisms that govern disease dynamics in complex
 biological communities. To determine how spatial structuring of plant
 communities caused by anthropic disturbance affects resource utilisation
 traits of viruses, we combine high-throughput, network, and metacommunity
 approaches. We find that the disturbance gradient corresponded to network
 modules and habitat specificity exhibited by a majority of viruses.
 Communities were connected through key hub species of either generalist
 viruses or high potential host reservoirs. Spatial dependencies were
 evident in regression models of species richness and correlations between
 metacommunity structure and both host range and transmission mode at finer
 spatial resolutions. We propose that virus community assembly is
 influenced by variation in niche opportunities. Distinctions in virus
 community composition caused by resource compartmentalisation can be used
 to track ecological traits important in forecasting transmission risk.
description: We conducted 78 collections at
 23 sampling sites between July 2015 and June 2017 in the Vega del
 Tajo-Tajuña agricultural region of the south-central plateau of the
 Iberian Peninsula. Total RNA
 extractions were conducted for the detection of all virus genome types (+ssRNA, -ssRNA, dsRNA,
 ssDNA, and dsDNA).
 Individual RNA extracts
 were pooled by plant species and collection (i.e., a single instance of
 sampling at a study site) to obtain a single preparation for HTS.
 Together, the HTS sample comprised 323 libraries of 2,037 pooled
 individual samples. High throughput sequencing was outsourced (CRG,
 Barcelona, Spain; http://www.crg.eu/). All library preparation included a
 step for rRNA depletion. Paired-end reads of 125 or 150 nt. were sequenced
 on Illumina HiSeq platforms. All reads were provided with Phred quality
 scores greater or equal to Q30. The trimming of adapter contamination was
 conducted using cutadapt
 v1.8.3. To
 standardise the counts of
 OTUs, the following pipeline was applied to the BLAST query matches of
 each read library. Reads were retained only if: 1) the query coverage was
 100%; 2) the alignment length was greater or equal to 125 nt.; 3) the
 matches were paired-reads only; 4) where each read-pair of a given library
 matched a single reference genome only; 5) and matched with a single
 region of that reference; and 6) where the difference between the maximum
 and minimum of query start positions relative to a reference genome, had a
 span of more than 1% of the length of the reference. Local BLAST queries were conducted with Blast+
 version 2.2.29 to identify
 virus OTUs. The queries were conducted against a database of plant virus
 genomic references of +ssRNA, -ssRNA, dsRNA, ssDNA, and
 dsDNA available from NCBIs
 Viral Genome Browser.
 Information
 about virus and host taxonomy was merged with the BLAST query output. The
 data represent all raw query results before the application of the
 readible read filtering pipeline. The column headers of the data table
 consist of the following:
 "lib" (sequencing library code),
 "ncbi" (NCBI accession code), "read" (read
 orientation), "pident" (standard BLAST flag), "length"
 (standard BLAST flag),
 "sstart" (standard
 BLAST flag), "send" (standard
 BLAST flag), "bitscore" (standard
 BLAST flag), "qcovs" (standard
 BLAST flag), "taxon" (host species
 name), "host.family" (host family name), "habitat"
 (habitat category), "site" (code of study site),
 "collection" (code of collection), "title" (virus OTU
 species title), "vir.abbr" (virus OTU
 abbreviation), "vir.family" (virus OTU
 family), "genera" (virus OTU genus), and "genome"
 (virus genome type).
description: A text editor or Microsoft Excel can be used to open the
 data.