GCevobase: an evolution-based database for GC content in eukaryotic genomes
Author(s) -
Dapeng Wang
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty068
Subject(s) - gc content , genome , phylogenetic tree , codon usage bias , biology , genome size , phylum , taxonomic rank , phylogenetics , clade , gene , computational biology , evolutionary biology , database , genetics , computer science , taxon , botany
How to comprehend the underlying mechanism behind the origin and evolution of genome composition such as GC content has been regarded as a long-standing crucial question, highlighting its biological significance and functional relevance. To varying extents, several systematically identified patterns of GC content variations are shown to be linked to a set of genomic features in the events of replication, transcription, translation and recombination, with strong contrasts between diverse phylogenetic or taxonomical groups. In this situation, we develop a repository-GCevobase-which houses compositional and size related data presented in various forms from 1118 genomes including 5 major clades of eukaryotic species such as vertebrates, invertebrates, plants, fungi and protists. It analyzes the cautiously selected sequences with clearly-defined bases and structures them under the taxonomical classification system (kingdom, phylum, class, order and family) at the genome and gene scales. It uses the diversified and intelligible graphs to show the statistical measurements of GC content in the sequence, at the three codon positions and at 4-fold degenerate sites and CDS length and their genome-wide correlations and display the evolutionary pathways of GC content by taking into account between-species orthologs and within-species paralogs for each annotated gene. In addition, a lot of internal and external links have been created, making it an effective communication between the data from individual genomes and the raw data are downloadable.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom