Patterns and ecological drivers of ocean viral communities

By Jennifer R. Brum, J. Ignacio-Espinoza, Simon Roux, Guilhem Doulcier, Silvia G. Acinas, A. Alberti, Samuel Chaffron, C. Cruaud, C. de Vargas, J. Gasol and 21 more. Science, 2015

679 citations recorded by the source corpus.

Subfields: Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/adfc3c88d887818149b8aa672e96cd11313bbcd6

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Citations in the corpus

Computational approaches to predict bacteriophage–host relationships (2015, background): “Phage communities are highly stratified in space and time (Flo-res et al. 2011; Flores, Valverde and Weitz 2013; Koskella 2014; Brum et al. 2015; Lima-Mendez et al. 2015).”
Computational pan-genomics: status, promises and challenges (2016, background): “Abundant metagenomic data is currently being generated from various environments such as human hosts [12, 31], the world’s oceans [32, 33], and soil [34].”
Scientists’ warning to humanity: microorganisms and climate change (2019, neutral): “Nevertheless, biogeographic distinctions occur for many microbial species, with dispersal, lifestyle (for example, host association) and environmental factors strongly influencing community composition and function 54,101–103 .”
Determinants of community structure in the global plankton interactome (2015, methodology): “We derived viral, prokaryotic, and eukaryotic abundance profiles from clusters of metagenomic contigs, Illumina-sequenced metagenomes (mitags), and 18S ribosomalDNA (rDNA) V9 sequences, respectively (table S1) (10, 18, 19) and collected environmental data from on-site and satellite measurements (17,”
Structure and function of the global ocean microbiome (2015, methodology): “Here we analyzed prokaryoteenriched size fractions, whereas related papers studied viral ecology (19), cross-kingdom species interactions (21), and planktonic community connectivity across an ocean circulation chokepoint (22).”
A global ocean atlas of eukaryotic genes (2018, neutral): “[3,5] (5,10] (10,20] (20,30] (30,40] (40,50] (50,100] (100,500] (500,1.”
VIRIDIC—A Novel Tool to Calculate the Intergenomic Similarities of Prokaryote-Infecting Viruses (2020, background): “For example, several metagenomic studies grouped viral contigs into populations using an ANI of >95% over at least 80% of their genes [29,30].”
Microbiota Transfer Therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study (2017, methodology): “Then, a non-redundant dataset of viral contigs was generated by clustering all viral contigs with Cd-hit [53] using the thresholds previously established (95% ANI on 80% of the shortest sequence) [54, 55].”