Iso-VIG14.1.0 (Metagenome Derived Viral Genomes, WA/IA/KS)

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Description

Soil samples were collected in triplicate in the Fall of 2017 across the three grassland locations having differences in historical annual precipitation (WA-TmG.1.0, KS-TmG.1.0, and IA-TmG.1.0). For each location, one deeply sequenced composite metagenome (> 1 terabase) were screened for viruses,In addition, each of the three field soil samples were individually sequenced to provide three replicate metagenomes (WA-TmG.2.0, KS-TmG.2.0, and IA-TmG.2.0) for statistical comparison in addition to screening for viral soil contigs for assessing the impact of historical annual precipitation. 

 

Viral genome sequencing identified from a metagenome and/or metatranscriptome dataset. Viral genomes are the result of computational analysis where metagenome datasets contained mixed genetic material information from sample sequences recovered directly from the natural environment. The version described in this paper is the first version. Dataset download contains functional annotations, computational analysis files, and a MIUVIG.soil.5.0 metadata file.

Data Package Resource Files:

Items below available from Download Button:

 

  1. 14_complete_V_genome.fasta (WA & KS only) [1.2 MB;1 item]
  2. Supporting Information Material [13.4 MB; 8 items]
  • SI1 Differences in soil chemistry of the grasslands across precipitation gradient
  • SI2 Prokaryotic community compositions of the grasslands across precipitation gradient
  • SI3 Host assignments and clustering information of each identified viral contigs
  • SI4 Visualization of the complete viral genomes assembled from soil metagenomes
  • SI5 Statistical information of the ‘large’ (TmG.1.0) and ‘replicate’ (TmG.2.0) metagenomes 
  • SI6 Viral Pfam list for viral gene annotation
  • SI7 Network of viral clustering using tetranucleotide frequency method
  • SI8 An interactive network of the viral clustering (html)

 

Related Experimental Data

TmG.1.0 Metagenomes: 10.25584/WATmG1/1635002 | 10.25584/KSTmG1/1635004 | 10.25584/IATmG1/1635005 

TmG.2.0 Metagenomes: 10.25584/WATmG2/1770324 | 10.25584/KSTmG2/1770332 | 10.25584/IATmG2/1770333

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Lindsey Anderson’s research has been dedicated to the identification and characterization of novel, targeted and non-targeted, functional metabolic interactions using a high-throughput systems biology and computational biology approach. Her expertise in functional metabolism and multidisciplinary...

Dr. Jason McDermott, senior research scientist, has extensive research experience in molecular and structural virology and data resource design, data integration and prediction of biological networks, bridging experimental and computational biology. Currently, his research interests include data...

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