Catherine Belleannée

Logol: Expressive Pattern Matching in Sequences. Application to Ribosomal Frameshift Modeling

Most of the current practice of pattern matching tools is oriented towards finding efficient ways to compare sequences. This is useful but insufficient: as the knowledge and understanding of some functional or structural aspects of living systems improve, analysts in molecular biology progressively shift from mere classification tasks to modeling tasks. People need to be able to express global sequence architectures and check various hypotheses on the way their sequences are structured. It appears necessary to offer generic tools for this task, allowing to build more expressive models of biological sequence families, on the basis of their content and structure. This article introduces Logol, a new application designed to achieve pattern matching in possibly large sequences with customized biological patterns. Logol consists in both a language for describing patterns, and the associated parser for effective pattern search in sequences (RNA, DNA or protein) with such patterns. The Logol language, based on an high level grammatical formalism, allows to express flexible patterns (with mispairings and indels) composed of both sequential elements (such as motifs) and structural elements (such as repeats or pseudoknots). Its expressive power is presented through an application using the main components of the language : the identification of -1 programmed ribosomal frameshifting (PRF) events in messenger RNA sequences. Logol allows the design of sophisticated patterns, and their search in large nucleic or amino acid sequences. It is available on the GenOuest bioinformatics platform at http://logol.genouest.org. The core application is a command-line application, available for different operating systems. The Logol suite also includes interfaces, e.g. an interface for graphically drawing the pattern.

First landscape of binding to chromosomes for a domesticated mariner transposase in the human genome: diversity of genomic targets of SETMAR isoforms in two colorectal cell lines

Setmar is a 3-exons gene coding a SET domain fused to a Hsmar1 transposase. Its different transcripts theoretically encode 8 isoforms with SET moieties differently spliced. In vitro, the largest isoform binds specifically to Hsmar1 DNA ends and with no specificity to DNA when it is associated with hPso4. In colon cell lines, we found they bind specifically to two chromosomal targets depending probably on the isoform, Hsmar1 ends and sites with no conserved motifs. We also discovered that the isoforms profile was different between cell lines and patient tissues, suggesting the isoforms encoded by this gene in healthy cells and their functions are currently not investigated.