TEtools facilitates big data expression analysis of transposable elements and reveals an antagonism between their activity and that of piRNA genes

Emmanuelle Lerat 1 Marie Fablet 1 Laurent Modolo 2 Hélène Lopez-Maestre 1, 3 Cristina Vieira 4, 3, 1
1 Eléments transposables, évolution, populations
GINSENG - Département génétique, interactions et évolution des génomes [LBBE]
2 Statistique en grande dimension pour la génomique
PEGASE - Département PEGASE [LBBE]
3 ERABLE - Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale
Inria Grenoble - Rhône-Alpes
4 IUF - Institut Universitaire de France
Abstract : Over recent decades, substantial efforts have been made to understand the interactions between host genomes and transposable elements (TEs). The impact of TEs on the regulation of host genes is well known, with TEs acting as platforms of regulatory sequences. Nevertheless, due to their repetitive nature it is considerably hard to integrate TE analysis into genome-wide studies. Here, we developed a specific tool for the analysis of TE expression: TEtools. This tool takes into account the TE sequence diversity of the genome, it can be applied to unannotated or unassembled genomes and is freely available under the GPL3 (https://github.com/l-modolo/TEtools). TEtools performs the mapping of RNA-seq data obtained from classical mRNAs or small RNAs onto a list of TE sequences and performs differential expression analyses with statistical relevance. Using this tool, we analyzed TE expression from five Drosophila wild-type strains. Our data show for the first time that the activity of TEs is strictly linked to the activity of the genes implicated in the piwi-interacting RNA biogenesis and therefore fits an arms race scenario between TE sequences and host control genes.
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Emmanuelle Lerat, Marie Fablet, Laurent Modolo, Hélène Lopez-Maestre, Cristina Vieira. TEtools facilitates big data expression analysis of transposable elements and reveals an antagonism between their activity and that of piRNA genes. Nucleic Acids Research, Oxford University Press, 2017, 45, pp.13. ⟨10.1093/nar/gkw953⟩. ⟨hal-01524877⟩

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