Alain Denise

VARNA: Interactive drawing and editing of the RNA secondary structure

Description: VARNA is a tool for the automated drawing, visualization and annotation of the secondary structure of RNA, designed as a companion software for web servers and databases. Features: VARNA implements four drawing algorithms, supports input/output using the classic formats dbn, ct, bpseq and RNAML and exports the drawing as five picture formats, either pixel-based (JPEG, PNG) or vector-based (SVG, EPS and XFIG). It also allows manual modification and structural annotation of the resulting drawing using either an interactive point and click approach, within a web server or through command-line arguments. Availability: VARNA is a free software, released under the terms of the GPLv3.0 license and available at http://varna.lri.fr Contact: ponty@lri.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Generating functions for generating trees

Generating trees describe conveniently certain families of combinatorial objects: each node of the tree corresponds to an object, and the branch leading to the node encodes the choices made in the construction of the object. Generating trees lead to a fast computation of enumeration sequences (sometimes, to explicit formulae as well) while providing efficient random generation algorithms. In this paper, we investigate the relationship between structural properties of the rules defining such trees and the rationality, algebraicity, or transcendence of the corresponding generating functions.

Mechanisms for U2AF to define 3' splice sites and regulate alternative splicing in the human genome.

The U2AF heterodimer has been well studied for its role in defining functional 3′ splice sites in pre-mRNA splicing, but many fundamental questions still remain unaddressed regarding the function of U2AF in mammalian genomes. Through genome-wide analysis of U2AF-RNA interactions, we report that U2AF has the capacity to directly define ~88% of functional 3′ splice sites in the human genome, but numerous U2AF binding events also occur in intronic locations. Mechanistic dissection reveals that upstream intronic binding events interfere with the immediate downstream 3′ splice site associated either with the alternative exon, to cause exon skipping, or with the competing constitutive exon, to induce exon inclusion. We further demonstrate partial functional impairment with leukemia-associated mutations in U2AF35, but not U2AF65, in regulated splicing. These findings reveal the genomic function and regulatory mechanism of U2AF in both normal and disease states.

Towards a computational model for −1 eukaryotic frameshifting sites

Abstract Motivation: Unconventional decoding events are now well acknowledged, but not yet well formalized. In this study, we present a bioinformatics analysis of eukaryotic −1 frameshifting, in order to model this event. Results: A consensus model has already been established for −1 frameshifting sites. Our purpose here is to provide new constraints which make the model more precise. We show how a machine learning approach can be used to refine the current model. We identify new properties that may be involved in frameshifting. Each of the properties found was experimentally validated. Initially, we identify features of the overall model that are to be simultaneously satisfied. We then focus on the following two components: the spacer and the slippery sequence. As a main result, we point out that the identity of the primary structure of the so-called spacer is of great importance. Availability: Sequences of the oligonucleotides in the functional tests are available at http://www.igmors.u-psud.fr/rousset/bioinformatics/ Contact: bekaert@igmors.u-psud.frjpforest@lri.frchris@lri.fr * To whom correspondence should be addressed.

GenRGenS: software for generating random genomic sequences and structures

SUMMARY GenRGenS is a software tool dedicated to randomly generating genomic sequences and structures. It handles several classes of models useful for sequence analysis, such as Markov chains, hidden Markov models, weighted context-free grammars, regular expressions and PROSITE expressions. GenRGenS is the only program that can handle weighted context-free grammars, thus allowing the user to model and to generate structured objects (such as RNA secondary structures) of any given desired size. GenRGenS also allows the user to combine several of these different models at the same time.

Adding pyrrolysine to the Escherichia coli genetic code

Pyrrolysyl‐tRNA synthetase and its cognate suppressor tRNAPyl mediate pyrrolysine (Pyl) insertion at in frame UAG codons. The presence of an RNA hairpin structure named Pyl insertion structure (PYLIS) downstream of the suppression site has been shown to stimulate the insertion of Pyl in archaea. We study here the impact of the presence of PYLIS on the level of Pyl and the Pyl analog N‐ε‐cyclopentyloxycarbonyl‐l‐lysine (Cyc) incorporation using a quantitative lacZ–luc tandem reporter system in an Escherichia coli context. We show that PYLIS has no effect on the level of neither Pyl nor Cyc incorporation. Exogenously supplying our reporter system with d‐ornithine significantly increases suppression efficiency, indicating that d‐ornithine is a direct precursor to Pyl.

A generic method for statistical testing

This paper addresses the problem of selecting finite test sets and automating this selection. Among these methods, some are deterministic and some are statistical. The kind of statistical testing we consider has been inspired by the work of Thevenod-Fosse and Waeselynck. There, the choice of the distribution on the input domain is guided by the structure of the program or the form of its specification. In the present paper, we describe a new generic method for performing statistical testing according to any given graphical description of the behavior of the system under test. This method can be fully automated. Its main originality is that it exploits recent results and tools in combinatorics, precisely in the area of random generation of combinatorial structures. Uniform random generation routines are used for drawing paths from the set of execution paths or traces of the system under test. Then a constraint resolution step is performed, aiming to design a set of test data that activate the generated paths. This approach applies to a number of classical coverage criteria. Moreover, we show how linear programming techniques may help to improve the quality of test, i.e. the probabilities for the elements to be covered by the test process. The paper presents the method in its generality. Then, in the last section, experimental results on applying it to structural statistical software testing are reported.

Alignments of RNA Structures

We describe a theoretical unifying framework to express the comparison of RNA structures, which we call alignment hierarchy. This framework relies on the definition of common supersequences for arc-annotated sequences and encompasses the main existing models for RNA structure comparison based on trees and arc-annotated sequences with a variety of edit operations. It also gives rise to edit models that have not been studied yet. We provide a thorough analysis of the alignment hierarchy, including a new polynomial-time algorithm and an NP-completeness proof. The polynomial-time algorithm involves biologically relevant edit operations such as pairing or unpairing nucleotides. It has been implemented in a software, called gardenia, which is available at the Web server http://bioinfo.lifl.fr/RNA/gardenia.

Automated motif extraction and classification in RNA tertiary structures

We used a novel graph-based approach to extract RNA tertiary motifs. We cataloged them all and clustered them using an innovative graph similarity measure. We applied our method to three widely studied structures: Haloarcula marismortui 50S (H.m 50S), Escherichia coli 50S (E. coli 50S), and Thermus thermophilus 16S (T.th 16S) RNAs. We identified 10 known motifs without any prior knowledge of their shapes or positions. We additionally identified four putative new motifs.

Assessing the Statistical Significance of Overrepresented Oligonucleotides

Assessing statistical significance of over-representation of exceptional words is becoming an important task in computational biology. We show on two problems how large deviation methodology applies. First, when some oligomer H occurs more often than expected, e.g. may be overrepresented, large deviations allow for a very efficient computation of the so-called p-value. The second problem we address is the possible changes in the oligomers distribution induced by the over-representation of some pattern. Discarding this noise allows for the detection of weaker signals. Related algorithmic and complexity issues are discussed and compared to previous results. The approach is illustrated with three typical examples of applications on biological data.