Program > Browse abstracts by author > Teycheney Pierre-Yves

Endogenous viral sequences (EVEs) result from the integration of full or part of viral genomes into the genome of eukaryotic or prokaryotic hosts. EVEs sometimes represent a significant part of the host genome. In addition, they provide access to unique viral sequences that can be useful in paleovirology approaches to study the evolution of viruses over time steps through several million years. However, EVEs are frequently ignored in genome annotation due to the lack of dedicated bioinformatics tools for their detection and characterization, which have long relied on manual processes. In plants, most of the known EVEs belong to the family Caulimoviridae, the only family of retrotranscribed plant viruses. However, Caulimoviridae EVEs (ECVs) are often confused with transposable elements owing to their similarity with Ty3/Gypsy elements (family Metaviridae). Here we present "CAULIFINDER", a bioinformatics software package for the automatic characterization and annotation of ECVs in plant genomes. CAULIFINDER consists of two complementary pipelines. The first one detects repetitive ECVs and performs a reconstruction of consensus sequences. The consensus sequences are then used to annotate all matching ECV copies in the analyzed genome. The second pipeline searches for the ECV marker gene ‘reverse transcriptase' in a given plant genome and integrates the representative sequences in a phylogenetic tree of the Caulimoviridae, allowing the diversity of ECVs to be assessed regardless of their copy number. CAULIFINDER is a versatile tool for producing an annotation of ECVs in plant genomes and for collecting fossil sequences that can be used to conduct evolutionary studies of Caulimoviridae using paleovirology approaches. It is distributed in a Docker open-access image. We will present the design and evaluation of CAULIFINDER, carried out on sequence data from several plant genomes, and discuss the generic scope of our work for studying the evolution of viruses over long time steps.