Michel Termier

Genomic exploration of the hemiascomycetous yeasts: 11. Kluyveromyces lactis.

Random sequencing of the Kluyveromyces lactis genome allowed the identification of 2235–2601 open reading frames (ORFs) homologous to S. cerevisiae ORFs, 51 ORFs which were homologous to genes from other species, 64 tRNAs, the complete rDNA repeat, and a few Ty1‐ and Ty2‐like sequences. In addition, the complete sequence of plasmid pKD1 and a large coverage of the mitochondrial genome were obtained. The global distribution into general functional categories found in Saccharomyces cerevisiae and as defined by MIPS is well conserved in K. lactis. However, detailed examination of certain subcategories revealed a small excess of genes involved in amino acid metabolism in K. lactis. The sequences are deposited at EMBL under the accession numbers AL424881–AL430960.

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.

Genomic Exploration of the Hemiascomycetous Yeasts: 21. Comparative functional classification of genes

We explored the biological diversity of hemiascomycetous yeasts using a set of 22 000 newly identified genes in 13 species through BLASTX searches. Genes without clear homologue in Saccharomyces cerevisiae appeared to be conserved in several species, suggesting that they were recently lost by S. cerevisiae. They often identified well‐known species‐specific traits. Cases of gene acquisition through horizontal transfer appeared to occur very rarely if at all. All identified genes were ascribed to functional classes. Functional classes were differently represented among species. Species classification by functional clustering roughly paralleled rDNA phylogeny. Unequal distribution of rapidly evolving, ascomycete‐specific, genes among species and functions was shown to contribute strongly to this clustering. A few cases of gene family amplification were documented, but no general correlation could be observed between functional differentiation of yeast species and variations of gene family sizes. Yeast biological diversity seems thus to result from limited species‐specific gene losses or duplications, and for a large part from rapid evolution of genes and regulatory factors dedicated to specific functions.

BRASERO: A Resource for Benchmarking RNA Secondary Structure Comparison Algorithms

The pairwise comparison of RNA secondary structures is a fundamental problem, with direct application in mining databases for annotating putative noncoding RNA candidates in newly sequenced genomes. An increasing number of software tools are available for comparing RNA secondary structures, based on different models (such as ordered trees or forests, arc annotated sequences, and multilevel trees) and computational principles (edit distance, alignment). We describe here the website BRASERO that offers tools for evaluating such software tools on real and synthetic datasets.

Random generation of words of context-free languages according to the frequencies of letters

Let L be a context-free language on an alphabet X={ x 1,x2,…, xk} and n a positive integer. We consider the problem of generating at random words of L with re-spect to a given distribution of the number of occurrences of the letters. We consider two alternatives of the problem. In the first one, a vector of natural numbers (n1, n2,…,nk) such that n1 + n2+… + nk = n is given, and the words must be generated uniformly among the set of words of L which contain exactly ni letters xi (1 ≤ i ≤ k). The second alternative consists, given v = (vi,…, vk) a vector of positive real numbers such that vi +… + vk = 1, to generate at random words among the whole set of words of L of length n, in such a way that the expected number of occurrences of any letter x i equals nvi (1 ≤i ≤ k), and two words having the same distribution of letters have the same probability to be generated. For this purpose, we design and study two alternatives of the recursive method which is classically employed for the uniform generation of combinatorial structures. This type of “controlled” non-uniform generation can be applied in the field of statistical analysis of genomic sequences.