Back to Search Start Over

Exploring Repetitive DNA Landscapes Using REPCLASS, a Tool That Automates the Classification of Transposable Elements in Eukaryotic Genomes

Authors :
Nirmal Ranganathan
Marcel L. Guibotsy
David Levine
Cédric Feschotte
Umeshkumar Keswani
Source :
Genome Biology and Evolution
Publication Year :
2009
Publisher :
Oxford University Press, 2009.

Abstract

Eukaryotic genomes contain large amount of repetitive DNA, most of which is derived from transposable elements (TEs). Progress has been made to develop computational tools for ab initio identification of repeat families, but there is an urgent need to develop tools to automate the annotation of TEs in genome sequences. Here we introduce REPCLASS, a tool that automates the classification of TE sequences. Using control repeat libraries, we show that the program can classify accurately virtually any known TE types. Combining REPCLASS to ab initio repeat finding in the genomes of Caenorhabditis elegans and Drosophila melanogaster allowed us to recover the contrasting TE landscape characteristic of these species. Unexpectedly, REPCLASS also uncovered several novel TE families in both genomes, augmenting the TE repertoire of these model species. When applied to the genomes of distant Caenorhabditis and Drosophila species, the approach revealed a remarkable conservation of TE composition profile within each genus, despite substantial interspecific covariations in genome size and in the number of TEs and TE families. Lastly, we applied REPCLASS to analyze 10 fungal genomes from a wide taxonomic range, most of which have not been analyzed for TE content previously. The results showed that TE diversity varies widely across the fungi “kingdom” and appears to positively correlate with genome size, in particular for DNA transposons. Together, these data validate REPCLASS as a powerful tool to explore the repetitive DNA landscapes of eukaryotes and to shed light onto the evolutionary forces shaping TE diversity and genome architecture.

Details

Language :
English
ISSN :
17596653
Volume :
1
Database :
OpenAIRE
Journal :
Genome Biology and Evolution
Accession number :
edsair.doi.dedup.....62e369e0030f950407de1b72cb1886fd