RNA Locally Optimal Secondary Structures

International audienceRNA locally optimal secondary structures provide a concise and exhaustive description of all possible secondary structures of a given RNA sequence, and hence a very good representation of the RNA folding space. In this paper, we present an efficient algorithm which computes all locally optimal secondary structures for any folding model that takes into account the stability of helical regions. This algorithm is implemented in a software called regliss that runs on a publicly accessible web server

Searching for alternate RNA structures in genomic sequences

International audienceWe introduce the concept of RNA multi-structures, that is a formal grammar based framework specifically designed to model a set of alternate RNA secondary structures. Such alternate structures can either be a set of suboptimal foldings, or distinct stable folding states, or variants within an RNA family. We provide several such examples and propose an efficient algorithm to search for RNA multi-structures within a genomic sequence

The Galactic Isotropic γ\gamma-ray Background and Implications for Dark Matter

We present an analysis of the radial angular profile of the galacto-isotropic (GI) $\gamma$-ray flux--the statistically uniform flux in circular annuli about the Galactic center. Two different approaches are used to measure the GI flux profile in 85 months of Fermi-LAT data: the BDS statistic method which identifies spatial correlations, and a new Poisson ordered-pixel method which identifies non-Poisson contributions. Both methods produce similar GI flux profiles. The GI flux profile is well-described by an existing model of bremsstrahlung, $\pi^0$ production, inverse Compton scattering, and the isotropic background. Discrepancies with data in our full-sky model are not present in the GI component, and are therefore due to mis-modeling of the non-GI emission. Dark matter annihilation constraints based solely on the observed GI profile are close to the thermal WIMP cross section below 100 GeV, for fixed models of the dark matter density profile and astrophysical $\gamma$-ray foregrounds. Refined measurements of the GI profile are expected to improve these constraints by a factor of a few.Comment: 20 pages, 15 figures, references adde

Determination of Angle of Light Deflection in Higher-Derivative Gravity Theories

Gravitational light deflection is known as one of three classical tests of general relativity and the angle of deflection may be computed explicitly using approximate or exact solutions describing the gravitational force generated from a point mass. In various generalized gravity theories, however, such explicit determination is often impossible due to the difficulty with obtaining an exact expression for the deflection angle. In this work, we present some highly effective globally convergent iterative methods to determine the angle of semiclassical gravitational deflection in higher- and infinite-derivative formalisms of quantum gravity theories. We also establish the universal properties that the deflection angle always stays below the classical Einstein angle and is a strictly decreasing function of the incident photon energy, in these formalisms.Comment: 32 pages, 8 figure

Lipopolysaccharide from crypt-specific core microbiota modulates the colonic epithelial proliferation-to-differentiation balance

We identified a crypt-specific core microbiota (CSCM) dominated by strictly aerobic, nonfermentative bacteria in murine cecal and proximal colonic (PC) crypts and hypothesized that, among its possible functions, it may affect epithelial regeneration. In the present work, we isolated representative CSCM strains using selective media based upon our initial 16S rRNA-based molecular identification (i.e., Acinetobacter, Delftia, and Stenotrophomonas). Their tropism for the crypt was confirmed, and their influence on epithelial regeneration was demonstrated in vivo by monocolonization of germfree mice. We also showed that lipopolysaccharide (LPS), through its endotoxin activity, was the dominant bacterial agonist controlling proliferation. The relevant molecular mechanisms were analyzed using colonic cryptderived organoids exposed to bacterial sonicates or highly purified LPS as agonists. We identified a Toll-like receptor 4 (TLR4)-dependent program affecting crypts at different stages of epithelial differentiation. LPS played a dual role: it repressed cell proliferation through RIPK3-mediated necroptosis of stem cells and cells of the transit-amplifying compartment and concurrently enhanced cell differentiation, particularly the goblet cell lineage

Prediction and pattern matching algorithms for RNA multi-structures

L'ARN (acide ribonucléique) est une molécule ubiquitaire qui joueplusieurs rôles fondamentaux au sein de la cellule: synthèse desprotéines avec les ARN messagers, activité catalytique ou implicationdans la régulation, les ARN non-codants. Les nouvelles technologies deséquençage à haut- débit permettent de produire des milliards de séquences à moindre coût, posant de manière cruciale la question de l'analyse de ces données.L'objectif de cette thèse est de définir de nouvelles méthodescomputationnelles pour aider à l'analyse de ces séquences dans le casdes ARN non-codants. Dans cette perspective, la "structuresecondaire" d'un ARN, formée par l'ensemble des appariements entrebases, délivre des informations utiles pour étudier la fonction del'ARN. Notre travail se concentre plus particulièrement surl'ensemble des structures potentielles que peut adopter une séquenced'ARN donnée, ensemble que nous appelons "multi-structure". Nousapportons deux contributions: un algorithme pour générersystématiquement toutes les structures localement optimales composantune multi-structure, et un algorithme basé sur la recherche d'unemulti-structure pour identifier un ARN non-codant dans une séquencegénomique. Ces résultats ont été mis en oeuvre dans deux logiciels,Alterna et Regliss, appliqués avec succès à des ensembles de test.RNA (ribonucleic acid) molecules have various functions in cells. Justas they can store and deliver the DNA message for the proteinsynthesis (messenger RNAs), they can also directly catalyze chemicalreactions or act as a regulator (functional RNAs, also callednon-coding RNAs). Nowadays, recent sequencing technologies yield billions of genomic sequences - DNA, RNA - at a very small cost. However, sequencing isonly the first step: The function of the sequence remains open forinvestigation. The objective of the thesis is to define newcomputational methods to help sequence and structure analysis ofnon-coding RNAs. In this perspective, the "secondary structure" of an RNA,made with base pairs, provides useful hints to further study itsfunction. Our work is focused on sets of all possible RNA structuresfor a given sequence, introducing the concept of "RNAmulti-structures". The thesis details how such sets can be constructed systematically to generate all locally optimal secondary structures, and how they can be used as a pattern to identify non-coding RNAs in genomic sequences.We provide efficient algorithms for these two problems. Thesealgorithms have been implementated in the software tools Alterna andRegliss and tested on real data, providing new insight into RNAstructures

Algorithmes de prédiction et de recherche de multi-structures d'ARN

RNA (ribonucleic acid) molecules have various functions in cells. Just as they can store and deliver the DNA message for the protein synthesis (messenger RNAs), they can also directly catalyze chemical reactions or act as a regulator (functional RNAs, also called non-coding RNAs). Nowadays, recent sequencing technologies yield billions of genomic sequences - DNA, RNA - at a very small cost. However, sequencing is only the first step: The function of the sequence remains open for investigation. The objective of the thesis is to define new computational methods to help sequence and structure analysis of non-coding RNAs. In this perspective, the "secondary structure" of an RNA,made with base pairs, provides useful hints to further study its function. Our work is focused on sets of all possible RNA structures for a given sequence, introducing the concept of "RNA multi-structures". The thesis details how such sets can be constructed systematically to generate all locally optimal secondary structures, and how they can be used as a pattern to identify non-coding RNAs in genomic sequences. We provide efficient algorithms for these two problems. These algorithms have been implementated in the software tools Alterna and Regliss and tested on real data, providing new insight into RNA structuresL'ARN (acide ribonucléique) est une molécule ubiquitaire qui joue plusieurs rôles fondamentaux au sein de la cellule: synthèse des protéines avec les ARN messagers, activité catalytique ou implicationdans la régulation, les ARN non-codants. Les nouvelles technologies de séquençage à haut-débit permettent de produire des milliards de séquences à moindre coût, posant de manière cruciale la question de l'analyse de ces données. L'objectif de cette thèse est de définir de nouvelles méthodes computationnelles pour aider à l'analyse de ces séquences dans le cas des ARN non-codants. Dans cette perspective, la "structure secondaire" d'un ARN, formée par l'ensemble des appariements entrebases, délivre des informations utiles pour étudier la fonction de l'ARN. Notre travail se concentre plus particulièrement sur l'ensemble des structures potentielles que peut adopter une séquence d'ARN donnée, ensemble que nous appelons "multi-structure". Nous apportons deux contributions: un algorithme pour générer systématiquement toutes les structures localement optimales composantune multi-structure, et un algorithme basé sur la recherche d'unemulti-structure pour identifier un ARN non-codant dans une séquence génomique. Ces résultats ont été mis en oeuvre dans deux logiciels, Alterna et Regliss, appliqués avec succès à des ensembles de test

Algorithmes de prédiction et de recherche de multi-structures d'ARN

RNA (ribonucleic acid) molecules have various functions in cells. Just as they can store and deliver the DNA message for the protein synthesis (messenger RNAs), they can also directly catalyze chemical reactions or act as a regulator (functional RNAs, also called non-coding RNAs). Nowadays, recent sequencing technologies yield billions of genomic sequences - DNA, RNA - at a very small cost. However, sequencing is only the first step: The function of the sequence remains open for investigation. The objective of the thesis is to define new computational methods to help sequence and structure analysis of non-coding RNAs. In this perspective, the "secondary structure" of an RNA,made with base pairs, provides useful hints to further study its function. Our work is focused on sets of all possible RNA structures for a given sequence, introducing the concept of "RNA multi-structures". The thesis details how such sets can be constructed systematically to generate all locally optimal secondary structures, and how they can be used as a pattern to identify non-coding RNAs in genomic sequences. We provide efficient algorithms for these two problems. These algorithms have been implementated in the software tools Alterna and Regliss and tested on real data, providing new insight into RNA structuresL'ARN (acide ribonucléique) est une molécule ubiquitaire qui joue plusieurs rôles fondamentaux au sein de la cellule: synthèse des protéines avec les ARN messagers, activité catalytique ou implicationdans la régulation, les ARN non-codants. Les nouvelles technologies de séquençage à haut-débit permettent de produire des milliards de séquences à moindre coût, posant de manière cruciale la question de l'analyse de ces données. L'objectif de cette thèse est de définir de nouvelles méthodes computationnelles pour aider à l'analyse de ces séquences dans le cas des ARN non-codants. Dans cette perspective, la "structure secondaire" d'un ARN, formée par l'ensemble des appariements entrebases, délivre des informations utiles pour étudier la fonction de l'ARN. Notre travail se concentre plus particulièrement sur l'ensemble des structures potentielles que peut adopter une séquence d'ARN donnée, ensemble que nous appelons "multi-structure". Nous apportons deux contributions: un algorithme pour générer systématiquement toutes les structures localement optimales composantune multi-structure, et un algorithme basé sur la recherche d'unemulti-structure pour identifier un ARN non-codant dans une séquence génomique. Ces résultats ont été mis en oeuvre dans deux logiciels, Alterna et Regliss, appliqués avec succès à des ensembles de test

Modeling alternate RNA structures in genomic sequences.

International audienceWe introduce the concept of RNA multistructures, which is a formal grammar-based framework specifically designed to model a set of alternate RNA secondary structures. Such alternate structures can either be a set of suboptimal foldings, or distinct stable folding states, or variants within an RNA family. We provide several such examples and propose an efficient algorithm to search for RNA multistructures within a genomic sequence