A tutorial of diverse genome analysis tools found in the CoGe web-platform using Plasmodium spp. As a model

Andreina I. Castillo, Andrew D.L. Nelson, Asher K. Haug-Baltzell, Eric Lyons

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Integrated platforms for storage, management, analysis and sharing of large quantities of omics data have become fundamental to comparative genomics. CoGe (https://genomevolution.org/coge/) is an online platform designed to manage and study genomic data, enabling both data- and hypothesis-driven comparative genomics. CoGe's tools and resources can be used to organize and analyse both publicly available and private genomic data from any species. Here, we demonstrate the capabilities of CoGe through three example workflows using 17 Plasmodium genomes as a model. Plasmodium genomes present unique challenges for comparative genomics due to their rapidly evolving and highly variable genomic AT/GC content. These example workflows are intended to serve as templates to help guide researchers who would like to use CoGe to examine diverse aspects of genome evolution. In the first workflow, trends in genome composition and amino acid usage are explored. In the second, changes in genome structure and the distribution of synonymous (Ks) and non-synonymous (Kn) substitution values are evaluated across species with different levels of evolutionary relatedness. In the third workflow, microsyntenic analyses of multigene families' genomic organization are conducted using two Plasmodium-specific gene families - serine repeat antigen, and cytoadherence-linked asexual gene - as models. In general, these example workflows show how to achieve quick, reproducible and shareable results using the CoGe platform. We were able to replicate previously published results, as well as leverage CoGe's tools and resources to gain additional insight into various aspects of Plasmodium genome evolution. Our results highlight the usefulness of the CoGe platform, particularly in understanding complex features of genome evolution.

Original languageEnglish (US)
JournalDatabase
Volume2018
Issue number2018
DOIs
StatePublished - Jan 1 2018

ASJC Scopus subject areas

  • Information Systems
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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