Large-scale k-mer-based analysis of the informational properties of genomes, comparative genomics and taxonomy

Information theoretic approaches are ubiquitous and effective in a wide variety of bioinformatics applications. In comparative genomics, alignment-free methods, based on short DNA words, or k-mers, are particularly powerful. We evaluated the utility of varying k-mer lengths for genome comparisons by...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2021-10, Vol.16 (10), p.e0258693-e0258693
Main Authors: Bussi, Yuval, Kapon, Ruti, Reich, Ziv
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Applied mathematics
Bioinformatics
Biology
Biology and Life Sciences
Classification
Cluster analysis
Clustering
Computer and Information Sciences
Deoxyribonucleic acid
DNA
Entropy
Genomes
Genomics
Identification and classification
Information management
Information theory
Molecular biology
Nucleotide sequence
Phenetics
Phylogenetics
Phylogeny
Prokaryotes
Proteins
Research and Analysis Methods
Similarity
Taxonomy
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Information theoretic approaches are ubiquitous and effective in a wide variety of bioinformatics applications. In comparative genomics, alignment-free methods, based on short DNA words, or k-mers, are particularly powerful. We evaluated the utility of varying k-mer lengths for genome comparisons by analyzing their sequence space coverage of 5805 genomes in the KEGG GENOME database. In subsequent analyses on four k-mer lengths spanning the relevant range (11, 21, 31, 41), hierarchical clustering of 1634 genus-level representative genomes using pairwise 21- and 31-mer Jaccard similarities best recapitulated a phylogenetic/taxonomic tree of life with clear boundaries for superkingdom domains and high subtree similarity for named taxons at lower levels (family through phylum). By analyzing ~14.2M prokaryotic genome comparisons by their lowest-common-ancestor taxon levels, we detected many potential misclassification errors in a curated database, further demonstrating the need for wide-scale adoption of quantitative taxonomic classifications based on whole-genome similarity.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0258693