MetaPGN: a pipeline for construction and graphical visualization of annotated pangenome networks

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Dokumenter

  • MetaPGN

    Forlagets udgivne version, 655 KB, PDF-dokument

  • Ye Peng
  • Shanmei Tang
  • Dan Wang
  • Huanzi Zhong
  • Huijue Jia
  • Xianghang Cai
  • Zhaoxi Zhang
  • Minfeng Xiao
  • Huanming Yang
  • Jian Wang
  • Kristiansen, Karsten
  • Xun Xu
  • Junhua Li

Pangenome analyses facilitate the interpretation of genetic diversity and evolutionary history of a taxon. However, there is an urgent and unmet need to develop new tools for advanced pangenome construction and visualization, especially for metagenomic data. Here, we present an integrated pipeline, named MetaPGN, for construction and graphical visualization of pangenome networks from either microbial genomes or metagenomes. Given either isolated genomes or metagenomic assemblies coupled with a reference genome of the targeted taxon, MetaPGN generates a pangenome in a topological network, consisting of genes (nodes) and gene-gene genomic adjacencies (edges) of which biological information can be easily updated and retrieved. MetaPGN also includes a self-developed Cytoscape plugin for layout of and interaction with the resulting pangenome network, providing an intuitive and interactive interface for full exploration of genetic diversity. We demonstrate the utility of MetaPGN by constructing Escherichia coli pangenome networks from five E. coli pathogenic strains and 760 human gut microbiomes,revealing extensive genetic diversity of E. coli within both isolates and gut microbial populations. With the ability to extract and visualize gene contents and gene-gene physical adjacencies of a specific taxon from large-scale metagenomic data, MetaPGN provides advantages in expanding pangenome analysis to uncultured microbial taxa.

OriginalsprogEngelsk
Artikelnummergiy121
TidsskriftGigaScience
Vol/bind7
Udgave nummer11
Sider (fra-til)1-11
ISSN2047-217X
DOI
StatusUdgivet - 2018

Antal downloads er baseret på statistik fra Google Scholar og www.ku.dk


Ingen data tilgængelig

ID: 209801065