Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise
Searched keyword : Transcriptomics
Related people (13)
Developing and evaluating bioinformatic tools for: – next generation sequencing data – genome analysis & comparison Specialties:Genome & Transcriptome Bioinformatics
Data managementData VisualizationGenomicsNon coding RNASequence analysisTranscriptomicsGenome analysisBiostatisticsProgram developmentScientific computingData and text miningBiosensors and biomarkersEpidemiology and public health
- Tissue-resident stromal cell heterogeneity(Lucie PEDUTO - Stroma, Inflammation and Tissue Repair) - In Progress
- Dissecting Peptidoglycan pathways in human near-haploid cells(Martine FANTON D\'ANDON - Biology and Genetics of Bacterial Cell Wall) - Pending
- Analysis of sequencing data from a Leishmania donovani cosmid library(Pascale PESCHER - Molecular Parasitology and Signaling) - In Progress
As a computational biologist I have been involved in various projects seeking to answer different biological questions. Those projects have allowed me to define my main research interest, namely the evolutionary study of the emergence, storage and modulation of information in biological systems assisted by computational methods. During my research career I have acquired extensive experience in the analysis of sequence data at the DNA and protein level. I’m trained both in NGS bioinformatic protocols (ChIP-seq, ATAC-seq, RNA-seq, genome assembly) and fine detail sequence analysis. Most importantly, I have gained proficiency in the use of the statistical models that are at the basis of the quantitative analysis of low and high throughput sequence data. Additionally, my experience as a lecturer and instructor has taught me that training researchers about the formal basis of bioinformatic methodologies is the key for a successful collaboration between wet and dry lab. Likewise, I have gained valuable skills by working within two international consortia (TARA Oceans project and TRANSNET): the ability to collaborate with multidisciplinary groups and to coordinate younger researchers.
AlgorithmicsGenomicsSequence analysisTranscriptomicsGenome analysisGeneticsEvolutionInteractomics
- Identification d’une mémoire épigénomique à Streptococcus pneumoniae(Christine CHEVALIER - Chromatin and Infection) - Pending
- Training project for bacterial ChIP-seq Analysis on Streptococcus agalactiae(Maria vittoria MAZZUOLI - Biology of Gram-Positive Pathogens) - In Progress
- Tissue-resident stromal cell heterogeneity(Lucie PEDUTO - Stroma, Inflammation and Tissue Repair) - In Progress
I obtained an engineering degree in Biomedical engineering from Université de Technologie de Compiègne (UTC) in 1989, a master degree in Control of Complex Systems from UTC in 1990, a PhD in Control of Complex Systems from UTC in 1993, a University Degree in Human Genetics from The University of Rennes 1 in 2001 and a master degree in Functional Genomics from University Paris Diderot (Paris 7) in 2002. I worked as a statistician at the Transcriptome and Epigenome Platform from 2002 to 2017, where I was responsible for the statistical analyses of the data and had an important training activity (on the campus and outside). Since 2015 I have been co-head of the Bioinformatics and Biostatistics Hub within the Center of Bioinformatics, Biostatistics and Integrative Biology (C3BI). I am co-director of the Pasteur course Introduction to Data Analysis and co-organiser of the sincellTE summer school (a school dedicated to single cell transcriptome and epigenome data analysis). I am also co-managing the StatOmique group which gathers more than 60 statisticians from France.
RNA-seqStatistical inferenceTranscriptomicsBiostatisticsApplication of mathematics in sciencesExploratory data analysisIllumina HiSeqStatistical experiment designSequencing
- Biomarqueurs d’identification précoce du sepsis aux urgences (BIPS)(Jean-Marc CAVAILLON - Cytokines and Inflammation) - In Progress
- Study of the early pathogenesis during Lassa fever in cynomolgus monkeys and its correlation with the outcome(Sylvain BAIZE - Biology of Viral Emerging Infections) - In Progress
- Host microbiota modification by the pathogen Listeria monocytogenes(Javier PIZARRO-CERDA - Bacteria-Cell Interactions) - Closed + 1 project
After a PhD in Biology in 2011 on population genetics and phylogeography on amazing little amphipods (Crangonyx, Crymostygius) at the University of Reykjavik (Iceland), I pursued my interest in Bioinformatics and Evolutionary Biology in various post-docs in Spain (MNCN Madrid, UB Barcelona). During this time, I investigated transcriptomic landscapes for various non-model species (groups Conus, Junco and Caecilians) using de novo assemblies and participated in the development of TRUFA, a web platform for de novo RNA-seq analysis. In July 2016, I integrated the Revive Consortium and the Epigenetic Regulation unit at Pasteur Institute, where my main focus were transcriptomic and epigenetic analyses on various thematics using short and long reads technologies, with a special interest in alternative splicing events detection. I joined the Bioinformatics and Biostatistics Hub in January 2018. My latest interests are long reads technologies, alternative splicing and achieving reproducibility in Bioinformatics using workflow managers, container technologies and literate programming.
Data managementData VisualizationSequence analysisTranscriptomicsWeb developmentGenome analysisProgram developmentExploratory data analysisSofware development and engineeringGeneticsEvolutionRead mappingWorkflow and pipeline developmentPopulation geneticsMotifs and patterns detectionGrid and cloud computing
HumanInsect or arthropodOther animalAnopheles gambiae (African malaria mosquito)Mouse
- Transcriptomics of Anopheles – Plasmodium vivax interactions towards identification of malaria transmission blocking targets(Catherine BOURGOUIN - Functional Genetics of Infectious Diseases) - In Progress
- Mapping of Enhancers from transcriptome data(Christian MUCHARDT - Epigenetic Regulation) - In Progress
Rachel Legendre is a bioinformatics engineer. She completed her master degree in apprenticeship for two years at INRA in Jouy-en-Josas in the Genetic Animal department. She was involved in a project aiming at the detection and the expression analysis of micro-RNA involved in an equine disease. In 2012, she joined the Genomic, Structure and Translation Team at Paris-Sud (Paris XI) university. She worked principally on Ribosome Profiling data analysis, a new technique that allows to identify the position of the ribosome on the mRNA at the nucleotide level. Since November 2015, she joined the Bioinformatics and Biostatistics HUB at Pasteur Institute and she’s detached to the Biomics Pole in C2RT, where she is in charge of the bioinformatics analyses for transcriptomics and epigenomics projects. She’s also involved in Long Reads (PacBio and Nanopore) developments with other bioinformaticians of Biomics Pole.
AlgorithmicsChIP-seqEpigenomicsNon coding RNATranscriptomicsGenome analysisProgram developmentScientific computingSofware development and engineeringIllumina HiSeqRead mappingSequencingWorkflow and pipeline developmentChromatin accessibility assaysPac BioRibosome profiling
BacteriaFungiParasiteHumanInsect or arthropodOther animal
- Genome-wide interactions between HP1g and RNA.(Christophe RACHEZ - Epigenetic Regulation) - In Progress
- Identification of eukaryotic 5'UTRs(Arnaud ECHARD - Membrane Traffic and Cell Division) - Closed
- Identification of Ago2-bound nuclear transcripts and genomic loci in adult zebrafish neural stem cells(Bally-Cuif LAURE - Zebrafish Neurogenetics) - Pending
I obtained a PhD in phylogeny in 2008 at the Muséum National d’Histoire Naturelle in Paris, then worked as a post-doc in Torino (Italy, 2009 – 2011) and Faro (Portugal, 2011 – 2013) where I worked on methodological aspects of phylogeny. In 2013, I have been hired as research engineer in bioinformatics at the Institut de Génétique Humaine in Montpellier where I wrote tools to analyse high-throughput sequencing data, especially small RNA-seq. This is also the kind of job I do now at Institut Pasteur, since 2016. I enjoy programming in python, I’m interested in evolutionary biology, and I find teaching the UNIX command-line a rewarding activity. My published work is available here: http://www.normalesup.org/~bli/useful.html
GenomicsNon coding RNATranscriptomicsSofware development and engineeringGeneticsWorkflow and pipeline development
Insect or arthropodOther animalDrosophila melanogaster (Fruit fly)C. elegans
- Training project for bacterial ChIP-seq Analysis on Streptococcus agalactiae(Maria vittoria MAZZUOLI - Biology of Gram-Positive Pathogens) - In Progress
- Identification of the mouse and/or rat orthologues of the human gene ANOS1, responsible for the X-chromosome-linked form of Kallmann syndrome(Jean-Pierre HARDELIN - Genetics and Physiology of Hearing) - In Progress
- Insight into the Immune System: A bioresource and data-sharing platform to study chronic inflammatory diseases (IsIShare)(helene LAUDE - Other) - Closed + 1 project
After a PhD in biochemistry of the rapeseed proteins, during which I developed my first automated scripts for handling data processing and analysis, I join Danone research facility center for developing multivariate models for the prediction of milk protein composition using infrared spectrometry.
As I was already developing my own informatics tools, I decided to join the course of informatic for biology of the Institut Pasteur in 2007. At the end of the course I was recruited by the Institute and integrate the unit of “génétique des interactions macromoléculaires” of Alain Jacquier. Within this group, I learn to handle sequencing data and I developed processing and analysis tools using python and R. I also create a genome browser and database system for storing, retrieving and visualizing microarray data. After 8 years within the Alain Jacquier’s lab, I join the Hub of bioinformatics and biostatistics as co-head of the team.
ClusteringData managementSequence analysisTranscriptomicsWeb developmentDatabaseGenome analysisProgram developmentScientific computingExploratory data analysisData and text miningIllumina HiSeqRead mappingLIMSIllumina MiSeqHigh Throughput ScreeningMultidimensional data analysisWorkflow and pipeline developmentRibosome profilingMotifs and patterns detection
- Identification of eukaryotic 5'UTRs(Arnaud ECHARD - Membrane Traffic and Cell Division) - Closed
- Super-resolution imaging and reconstructions of human cell chromosome architecture(Xian HAO - Imaging and Modeling) - In Progress
- Utilize mouse models to study infection by HIV-1(Valentina LIBRI - Center for Translational Science) - Awaiting Publication
Professional Experience Today - Institut Pasteur,Paris - HUB Team 2017 - Bioinformatician 2001 - 2017 - Institut Pasteur,Paris; CIB/DSI - Engineer 1997 - 2000 Thesis: NMR and molecular modelisation, CEA, Saclay,
Data managementSequence analysisTranscriptomicsGenome analysisProgram developmentScientific computing
FungiCandida albicansCryptococcus gattiiCryptococcus neoformans
- Trichosporon asahii NGS analysis(Marie DESNOS-OLLIVIER - Molecular Mycology) - In Progress
- Development of a bioinformatics workflow dedicated to the analysis of the viral metagenome: from NGS raw data to the identification of novel viruses(Laurent DACHEUX - Lyssavirus Dynamics and Host Adaptation) - In Progress
- Methods to identify and characterize orthologs of genes encoding small proteins(Françoise NOREL - Macromolecular Systems and Signaling) - Closed
- The resurgence of a neglected disease, Yellow fever: from jungle to urban environments(ANNA BELLA FAILLOUX - Arboviruses and Insect Vectors) - Closed
- Performing Gene Ontology Analysis on RNAseq data in Aedes aegypti(Sarah MERKLING - Insect-Virus Interactions) - Awaiting Publication
- Insect Vector Genomics(Ken VERNICK - Genetic and Genomics of Insects Vectors) - In Progress
Since February 2017 Research engineer, Hub of Bioinformatics and Biostatistics of the C3BI, Institut Pasteur 2015-2017 Post doctoral position, team MISTIS, INRIA Grenoble Topic: Robust clustering and robust non linear regression in high dimension. Collaboration with Florence Forbes (INRIA). 2012-2015 PhD thesis in Statistics, Applied Mathematics Department of Agrocampus-Ouest, IRMAR UMR 6625 CNRS, Rennes Topic: Stability of variable selection in regression and classification issues for correlated data in high dimension. Supervisor: David Causeur (Agrocampus-Ouest, IRMAR). Education 2015 PhD thesis in Statistics, Applied Mathematics Department of Agrocampus-Ouest, IRMAR UMR 6625 CNRS, Rennes 2012 ISUP degree (Institut de Statistique de l’UPMC), Université Pierre et Marie Curie, Paris 2012 Master 2 of Statistics, Université Pierre et Marie Curie, Paris
ClusteringModelingStatistical inferenceTranscriptomicsBiostatisticsExploratory data analysisDimensional reductionStatistical experiment designMultidimensional data analysis
- Determination of host response elicited by different Salmonella lifestyles(Chak Hon LUK - Dynamics of Host-Pathogen Interactions) - Pending
- Cellular plasticity during mammary gland development(HAN LI - Cellular Plasticity And Disease Modelling) - Pending
- Rainfalls and water contamination in Antananarivo over 25 years(JAMBOU RONAN - Other) - In Progress
Dr. Natalia Pietrosemoli is an Engineer with a M. Sc. in Modeling and Simulation of Complex Realities from the International Center for Theoretical Physics, ICTP and the International School of Advanced Studies, SISSA (Triest, Italy). During her M. Sc. internships she mostly worked in modeling, optimization, combinatorics and information theory applied to medical imaging. In 2012 she got a Ph. D in Computational Biology from the School of Bioengineering of Rice University (Houston, TX, US), where she specialized in computational structural biology and functional genomics. Her doctoral thesis “Protein functional features extracted with from primary sequences : a focus on disordered regions”, contributed to a better understanding of the functional and evolutionary role of intrinsic disorder in protein plasticity, complexity and adaptation to stress conditions. As part of her Ph. D., Natalia was a visiting scholar in two labs in Madrid: the Structural Computational Biology Group at the Spanish National Cancer Research Centre (CNIO), where she mainly worked in sequence analysis and the functional-structural relationships of proteins, and the Computational Systems Biology Group at the Spanish National Centre for Biotechnology (CNB-CSIC ), where she studied the functional implications of intrinsically disordered proteins at the genomic level for several organisms, collaborating with different experimental and theoretical groups. In 2013, she joined the Swiss Institute of Bioinformatics as a postdoctoral fellow in the Bioinformactics Core Facility. Her main project consisted in the molecular classification of a rare type of lymphoma, which involved the integration of transcriptomic, clinical and mutational data for the identification of molecular markers for classification, diagnosis and prognosis. This work was performed in collaboration with the Pathology Institute at the University Hospital of Lausanne (CHUV). In November of 2015 Natalia joined the Hub Team @ Pasteur C3BI as a Senior Bioinformatician. Natalia is especially interested in the integrative analysis of different omics data, both at large-scale and for small datasets, and loves collaborating in interdisciplinary environments and having feedback from her fellow experimental colleagues. Currently, she’s coordinating several projects performing functional and pathway analysis at the genomic level. By grouping genes, proteins and other biological molecules into the pathways they are involved in, the complexity of the analyses is significantly reduced, while the explanatory power increases with respect to having a list of differentially expressed genes or proteins.
AlgorithmicsData managementGenomicsImage analysisMachine learningModelingProteomicsSequence analysisStructural bioinformaticsTranscriptomicsDatabaseGenome analysisBiostatisticsScientific computingDatabases and ontologiesApplication of mathematics in sciencesData and text miningGeneticsGraphics and Image ProcessingBiosensors and biomarkersClinical researchCell biology and developmental biologyInteractomicsBioimage analysis
- Analyse transcriptionnelle du cellules cancéreuse intestinal vs normales après co-culture avec la bactérie associée au cancer Streptococcus gallolyticus(Ewa PASQUEREAU - Biology of Gram-Positive Pathogens) - Pending
- Functional interactomics of SKAP2(Jean-François BUREAU - Functional Genetics of Infectious Diseases) - Pending
- Genome annotation of sequenced bacteria of the Culture Collection of the Pasteur Institut(Mery PINA - Biological Resource Center of Institut Pasteur (CRBIP)) - Pending
After graduating from Paris VI University with a PhD in Genetics on the “Role of histone protein post-translational modifications in splicing regulation” that I performed in the Epigenetic Regulation unit at the Institut Pasteur, I carried out two post-doctoral experiences. I first worked for three years as a postdoctoral associate of the Whitehead Institute for Biomedical Research/MIT in Cambridge (USA). My main project consisted in the integration of genomic and epigenomic data in order to predict the transcription factors that are potentially at the core of the regulation of the cell-type specific gene expression programs. I then joined the Institut Curie where I deepened my experience in multi-omics data analyses and integration to identify non-coding RNAs involved in cancer progression. I have recently joined the HUB-C3BI of the Institut Pasteur where I am performing high-throughput data integration to better understand biological complexity and contribute to precision medicine development.
ATAC-seqChIP-seqEpigenomicsNon coding RNAPathway AnalysisRNA-seqSingle CellSystems BiologyTool DevelopmentTranscriptomicsData integrationGraph theory and analysisCell biology and developmental biology
Hugo Varet is a biostatistician engineer from the Ensai (Ecole Nationale de la Statistique et de l’Analyse de l’Information) and has been recruited by the hub of the C3BI (Center of Bioinformatics, Biostatistics and Integrative Biology) to work at the Transcriptome & Epigenome Platform. He is in charge of the statistical analyses of the RNA-Seq data produced by the platform and develops R pipelines that help in this task. One of them is named SARTools and is available on GitHub: https://github.com/PF2-pasteur-fr/SARTools.
ModelingSequence analysisStatistical inferenceTranscriptomicsBiostatisticsScientific computingApplication of mathematics in sciencesExploratory data analysisHigh Throughput ScreeningClinical research
- Defining Shigella-targeting of human lamina propria mononuclear cells using CyTOF technology(Katja BRUNNER - Molecular Microbial Pathogenesis) - Closed
- Exploring immunological mechanisms of human graft-verus-host disease after hematopoietic stem cell transplantation(Eleonora LATIS - Immunoregulation) - Closed
- Functional interactions between HP1 proteins and RNA.(Christophe RACHEZ - Epigenetic Regulation) - Closed
Related projects (28)
In wild life, yeast cells are able to survive in severe conditions, without nutriment for a long period of time because the cell is able to enter in stationary phase. During this phase, the cell can transform varied sources of energy and pause its growth to preserve the cells from death. It is known that most of genes are downregulated in stationary phase and the cell activity is globally reduced to its strict minimum, while a subset of “specialized” genes is induced to promote survival in extreme conditions. We are analysing the transcriptome of exponentially grown or stationary phase yeasts, investigating different level of regulation.
The increased incidences of invasive fungal infections coupled with the paucity of available antifungal drugs for treatment have driven the search for novel agents with unique fungal targets. Studies
The recent analysis of the Cryptococcus neoformans transcriptomes revealed the presence of thousands of lncRNAs. In these yeasts, different types of lncRNAs seem to exist. The ones that are antisense of coding genes (the NATs), the ones that are located between coding genes (the lincRNAs) and some others that seem to result from alternative transcription start site selection. We identified growth conditions under which the expression of some of them is regulated. We have also identified some genes implicated in the regulation of some of these lncRNAs. This project deals with the characterisation of these lncRNAs, the analysis of their regulation and the study of their function in the biology and virulence of this pathogenic yeast.
The aim of the project is to create a viewer that will help visualisation and correlation between genomic, transcriptomic, proteomic and metabolomic data generated by the comparison of amastigote and promastigote stages of the Leishmania donovani parasite.
Skeletal muscle stem cells constitute a population of cells with heterogeneous properties. Interestingly, muscle stem cells have a remarkable capacity to regenerate muscle fibres after regeneration. We are performing a molecular analysis of these stem cells.
The post-translational modification by SUMO is an essential regulatory mechanism of protein function that is involved in most challenges faced by eukaryotic cells. Gene expression is particularly regulated by sumoylation as many SUMO substrates are transcription factors and chromatin-associated proteins, including histones. The emerging paradigm for the proposed work is that sumoylation controls multiple aspects of chromatin structure and function in response to external cues. According to this view, sumoylation is expected to impact both global and specific transcriptional programs thereby affecting constitutive and inducible expression of both coding and non coding genes. Recently, we found SUMO as an integral and instructive component of chromatin in cell growth and senescence, thus establishing sumoylation as a new and paradigmatic chromatin modification. This work now paves the way for detailed understanding of the contribution of SUMO as a multifaceted modifier of chromatin.
Identification of Transcription Start Sites and small RNAs in Leptospira interrogans by transcriptome analysis
Leptospiral promoter regions are poorly characterized: experimentally proven transcription factor binding sites have not been described in the literature and promoter prediction algorithms and E. coli consensus sequences of DNA motifs are not appropriate for Leptospira. Identification of Transcription Start Sites (TSS) and promoters on a global scale will provide essential information on DNA motifs that are targets of RNA polymerases, sigma factors and transcription factors. RNA sequencing will also provide information on small regulatory RNAs. These small (~30-500 nt) non-coding RNAs (sRNAs) are an emerging class of post-transcriptional regulators which play a variety of important roles in many biological processes. Studies on sRNA regulation of gene expression in Leptospira are currently in their infancy. Our results will provide new insights into the transcriptional landscape of L. interrogans, including the repertoire of sRNA, and it will establish the foundation for future experimental work on gene regulation.
Les cyanobactéries sont des microorganismes qui prolifèrent dans de nombreux plans d’eau et perturbent leurs fonctionnements et leurs usages car elles sont capables de produire des toxines dangereuses pour la santé humaine et animale. Si la réglementation sanitaire est basée, pour l’instant, sur la surveillance d’une seule toxine, il est désormais connu que ces microorganismes sont capables d’en synthétiser un grand nombre qu’il conviendrait de mieux prendre en compte dans le futur. C’est pourquoi, dans le but de mieux connaître le potentiel toxique des cyanobactéries, ma thèse s'applique, par des études sur leur génome et par une approche de chimie, à caractériser les gènes impliqués dans la synthèse de ces métabolites ainsi que les métabolites produits par ces gènes, à déterminer sur des souches de culture et dans des échantillons naturels provenant de plans d’eau d’Ile de France quel est le potentiel de production de ces métabolites et à mieux comprendre les facteurs environnementaux qui favorisent cette production. Deux équipes de Paris (Pasteur et iEES) sont associées sur ce travail qui implique également des collaborations étrangères. S'il est désormais bien connu qu'une part importante du métabolisme des cyanobactéries qui sont des microorganismes photosynthétiques, est régulée en fonction des phases de lumière et d'obscurité, les connaissances disponibles sur la synthèse des métabolites secondaires sont en revanche beaucoup plus limitées. Ces métabolites ont pourtant un double intérêt puisque certains sont toxiques pour l'Homme alors que d'autres ont un intérêt pharmaceutique potentiel. Leur synthèse repose sur l'expression de clusters de gènes pouvant être de très grande taille (jusqu’à 100 kb par région).
Currently there is increased focus for developing novel antibacterial strategies. The demand is driven by the rise in antibiotic resistance bacteria and many Gram-negative bacteria are on the list of increasingly drug resistant agents. A major target of successful antibiotics is the bacterial cell wall. The target of these drugs is often defined but what is much less understood is the off-target impact of these very important antibiotics. We designed and executed a mutli-omics strategy centered on the Gram-negative pathogen H. pylori. Our goal is to identify potential 'therapeutically susceptible' pathways associated with the physiological response to cell wall stress.
Lassa virus (LASV) is an arenavirus causing hemorrhagic fever in human. 300 000 to 500 000 cases of LASV infection are reported every year in western Africa, including 5 000 to 6 000 deaths. LASV is highly pathogenic, and no vaccine or treatment is available in endemic areas. LASV pathogenesis mechanisms are not well documented, and further investigations are needed to understand viral and immunological factors involved during infection. As previously shown by studies conducted on patients and non-human primates infected by LASV, T-cell response and type I interferon (IFN-I) are important for an effective response to LASV infection. Among dendritic cells (DC), myeloid DC can induce T-cell activation and plasmacytoid DC are specialized in IFN-I response. DC are also the first target of LASV during the infection of a new host, and studies on in vitro differentiated DC suggest a role of DC in T-cell response to LASV infection. Therefore, plasmacytoid and myeloid DC could be important for an efficient response to LASV infection.
Over the past three decades Listeria has become a model organism for host-pathogen interactions, leading to critical discoveries in a broad range of fields including virulence-factor regulation, cell biology, and bacterial pathophysiology. More recently, the number of Listeria “omics” data produced has increased exponentially, not only in term of number, but also in term of heterogeneity of data. There are now more than 40 published Listeria genomes, around 400 different transcriptomics data and 10 proteomics studies available. The capacity to analyze these data through a systems biology approach and generate tools for biologists to analyze these data themselves is a challenge for bioinformaticians. To tackle these challenges we are developing a web-based platform named Listeriomics which integrates different type of tools for “omics” data manipulation, the two most important being: 1) a genome viewer for displaying gene expression array, tiling array, and RNASeq data along with proteomics and genomics data. 2) An expression atlas, which is a query based tool which connects every genomics elements (genes, smallRNAs, antisenseRNAs) to the most relevant “omics” data. Our platform integrates already all genomics, and transcriptomics data ever published on Listeria and will thus allow biologists to analyze dynamically all these data, and bioinformaticians to have a central database for network analysis. Finally, it has been used already several times in our laboratory for different types of studies, including transcriptomics analysis in different biological conditions, and whole genome analysis of Listeria proteins N-termini. This project is funded by an ANR Investissement d'avenir: BACNET 10-BINF-02-01
Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment
Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment.
We are interested in the cytoplasmic quality control of gene expression and more especially into the behavior of aberrant peptides which could be generated from non-conform translation events. We are now investigating the role of a Saccharomyces cerevisiae RNA helicase protein that we named Tac4 (for Translation Associated Component 4). We showed that this protein is involved in translation. We demonstrated, by sucrose gradient and affinity purification that Tac4 interacts with the ribosome. A first UV cross-linking and cDNA analysis (CRAC) experiment clearly revealed that Tac4 interacts with the 18S rRNA of the 40S ribosomal subunit and we precisely defined the crosslink point. These preliminary results also suggested an enrichment of the 3’-end regions of mRNAs. This implies that Tac4 could not only interact with the small ribosomal subunit but also directly with mRNA. Tac4 is conserved through the evolution and its mammalian homologue is involved in initiation of translation. Therefore, we thought that Tac4 could be associated with the 5’-end rather than with the 3’-end. However, recent data showed that translation reinitiation into the 3’-UTR region may occurs when translation termination is affected. The factors and molecular mechanisms implicated in these events are not known. Altogether, our preliminary results suggest that Tac4 is an excellent candidate participating to the unwinding of RNA structure or to the release of some RNA-binding proteins into the 3’-end mRNA. We now would like to 1) confirm that Tac4 preferentially interacts with the 3’-end of mRNA, 2) determine whether Tac4 interacts with a region upstream the Stop codon or in the 3’-UTR of the mRNA, 3) determine whether Tac4 could also interact with other mRNA region, such as the 5'-UTR region, 4) identify the mRNA targets to determine whether Tac4 could have a general role in translation or could only be involved in tra
Analysing the transcriptome of exponentially grown or stationary phase yeasts in a genetic background that stabilises pervasive transcipts, we identified a first subset of ≈ 140 antisense transcripts anti-correlated with gene transcripts that are specifically expressed in quiescence. We are further investigating whether these genes are subject to a transcriptional interference and what are the mechanisms underlying this regulation. More in detail, we would like to analyse the loci where an antisense ncRNA are detected.
Insect vectors durably transmit many important human and animal diseases. Insects are mobile, adaptable and difficult to control, which makes them efficient vehicles for disease emergence, spread and maintenance. Genomic tools have been applied to the study of vectors and vector control, and some insects such as the African malaria vector Anopheles gambiae have now become new model organisms for natural host-pathogen interactions. We study mosquito vectors of malaria and arboviruses, which generates four main kinds of large-scale data that requires dedicated bioinformatics expertise: i) functional dissection of mosquito immune signaling pathways by RNAseq transcriptome profiling to detect responses to pathogen infection and/or silencing of target genes, including mRNA as well as small and other non-coding RNAs, ii) next-gen genetic linkage mapping by deep sequencing of index-tagged phenotyped individual mosquitoes, iii) population genomic analysis by whole-genome sequencing of hundreds of individual 250Mb mosquito genomes, iv) metagenomic analysis of the mosquito microbiome and pathogen susceptibility, and of ecological metagenomic communities in field samples of mosquito vectors.
Cryptococcus neoformans is a ubiquitous yeast present in the environment that is able to interact closely with numerous organisms including amoeba, paramecium or nematodes. The interaction with these organisms shaped its virulence with acquisition of infectious properties as a consequence especially in mammals . The ability to survive nutrient starvation, oxidative stress, desiccation, both in the environment and during infection, indicates a high level of physiological and metabolic plasticity of the yeast. In humans, after primary infection during childhood, the yeast is able to survive within the host for years before reactivation upon immunosuppression, leading to a life threatening disseminated fungal infection. This phenomenon, called dormancy / quiescence is one of the main biological features of this fungus in relation with disease's pathogenesis. It is well known in bacteria (tuberculosis), parasites (Plasmodium, Toxoplasma). In C. neoformans, dormancy has only been demonstrated epidemiologically in our laboratory but not experimentally so far. We developed an assay where yeasts cells exhibiting characteristics of potentially dormant cells were generated. Indeed, dormant cells are characterized by a low metabolic activity sometimes undetectable under normal laboratory conditions, altered growth capacity, and the ability to resuscitate upon adequate stimulus. Dormant cells are known to have increased mitochondrial masse and activity justifying a screening strategy of a collection of KO mutants for mitochondrial proteins. In parallel the whole proteome, transcriptome and secretome will be obtain with the ambition to correlate these parameters. Our current project aims at exploring the metabolism of the dormant yeast to have a comprehensive picture of the pathways that are required for the maintenance of dormancy and fo exit from dormancy.
We study the regulation of type I interferon (IFN) response in humans and in particular the functioning of a key negative feedback regulator, USP18. A recent article reported on a predicted 897nt-long LincRNA (long intergenic non coding RNA) that may target USP18. We have collected information for this LincRNA (genomic locus, putative transcript variants, sequence similarities with USP18 RNA, predicted ORFs, homologies with other genes, etc). To draw a guideline for wet lab experiments, we need to mine databases on this LincRNA. We expect to find it up-regulated in conditions of inflammation or in specific immune cell subsets, like macrophages. We wish to interrogate existing RNA-seq and Chip-seq human databases to obtain information on expression, transcriptional regulation, function, tissue-specificity or relation with pathological conditions of this LincRNA.
The genome of the yellow fever mosquito (Aedes Aegypti) is not fully annoyed, and this project aims at discovering novel transcripts using RNAseq data.
The three HP1 proteins (Heterochromatin Protein 1 alpha, -beta, -gamma) are epigenetic markers of heterochromatin, the condensed, repressed form of chromatin. They are typically known to associate to the di-/tri-methylated lysine 9 of histone H3 (H3-K9me2/3), a repressive histone mark, HP1s are therefore linked to chromatin silencing. But on the other hand, HP1s are also linked to activated transcription, for example HP1g has been shown to localize within the body of coding genes in correlation with their transcriptional activity. We focus on the mechanisms linking HP1gamma to regulation of chromatin and transcription in response to cellular stimuli. We are dissecting the functional links between HP1 proteins and chromatin-associated RNA. For this purpose, have identified all RNA populations associated with HP1gamma factor in immortalized cell lines derived from MEF (mouse embryonic fibroblast) with or without stimuli. We are now analysing the functional impact on gene expression levels. This should allow us to understand to what extend HP1gamma is associated to transcriptional processes on the chromatin.
Chronic inflammatory diseases such as rheumatoid arthritis, inflammatory bowel disease, spondyloarthritis (SpA) and psoriasis cause significant morbidity and are a substantial burden for the affected individuals and the society. An important obstacle to early diagnosis and the development of more specific and effective therapies is the very limited understanding of the pathogenesis of these diseases. In the past years genome-wide association studies have identified many genes that were not known to be involved in pathogenesis, and have linked several genes in immune pathways to inflammatory diseases, indicating that the immune system plays an essential role in the pathogenesis of these diseases. The current challenge is to correlate these genetic variants with the effector mechanisms implicated in pathogenesis, to allow translation of the genetic data into relevant diagnostics and innovative treatment strategies. To meet this challenge, we have designed a clinical study that examines the immune signaling pathways, the transcriptional networks and the genotype in the same SpA patient, in order to establish a link between genetic variation, cellular phenotype and function, and pathology. This approach will advance our understanding of the pathogenic mechanisms, and identify novel and relevant diagnostic tools, therapeutic targets and biomarkers. The long-term outcome of this strategy will be the rational design of specific therapies tailored to the genotype of the patient.
Genomic determinants for initiation and length of natural antisense transcripts in a compact eukaryotic genome and phylogenetic analysis of related Entamoeba species
Entamoeba histolytica is a protozoan parasite and an amitochondriate pathogenic amoeba, which causes amoebiasis (dysentery and liver abscess) in humans. In addition to E. histolytica several species infect the human intestine although these do not cause disease and include in most of cases E. dispar and ocassionnally E. moshkovskii. A phylogenetically close Entamoeba, E. invadens infecting snails, is used as cellular model for Entamoeba cyst formation.
Supported by the National Agency for Research (ANR-10-GENM-0011) we developed a project to firstly study the transcriptional landscape of pathogenic E. histolytica. Among the results we discovered that 60% of ORFs present anti-sense RNAs (NATs) that map to the 3‘ end of genes. Their regulation is modified upon environmental changes. The regulation of NATs is basically governed by genomic sequences within the very short intragenic region of the amoeba genome. Secondly, we have started to conduct comparative genomics and transcriptomics approaches to understand phenotypic differences between Entamoeba species, in particular with respect to virulence.
The interferon-induced transmembrane (IFITM) proteins protect cells from diverse virus infections, including Influenza, HIV and Zika viruses, by inhibiting virus-cell fusion. We showed that IFITM proteins act additively in both productively infected cells and uninfected target cells to inhibit HIV-1 spread, potentially conferring these proteins with greater breadth and potency against enveloped viruses. We also reported that amino-terminal mutants of IFITM3 preventing ubiquitination or endocytosis are more abundantly incorporated into virions and exhibit enhanced inhibition of HIV-1 fusion. An analysis of primate genomes revealed that IFITM3 is the most ancient antiviral family member of the IFITM locus and has undergone a repeated duplication in independent host lineages. Some IFITM3 genes in nonhuman primates, including those that arose following gene duplication, carry amino-terminal mutations that modify protein localization and function. Our aim is to analyze the RNA levels of the various members of the IFITM family, in various normal or pathological human or animal tissues.
Enhancers of transcription are regulatory sequences enabling gene expression from a distance. The landscape of active enhancers is cell-type specific and provides extensive information on the transcription factors at play. Currently, enhancers are mostly mapped based on the histone modifications positioned on their DNA sequence. This type of data is abundantly available for tumor-derived tissue culture cells, but difficult to obtain when the biological material has a limited availability. As an alternative approach, it is possible to detect enhancers as sites of divergent transcription. The objective of this project will be to develop tools allowing detection of sites of divergent transcription in transcriptome and run-on data, to evaluate the quality of the prediction by comparing the outcome with existing enhancer maps, and then ultimately use this approach to identify changes in the enhancer landscape between patients with multiple sclerosis and healthy controls.
Characterization of the role of Argonaute proteins in regulating germline gene expression at the transcriptional and the post-transcriptional levels.
This research project focuses on the characterization of the role of small RNAs and their associated Argonaute proteins in transcriptional and post-transcriptional regulation of germline gene expression. Using the nematode C. elegans, we have recently showed that one of the germline-expressed Argonaute protein, CSR-1, promotes germline transcription. However, CSR-1 also possess an endonucleolytic activity that might participate in post-transcriptional silencing. Therefore, two possible functions of the protein might regulate the germline transcriptome. 1) CSR-1 promotes specific germline transcription programs in the nucleus, and 2) negatively regulates expression of target transcripts in the cytoplasm. To gain mechanistic insights into these two functions, we aim to use RNA-seq, sRNA-seq, ChIP-seq, GRO-seq, Ribo-seq, RIP-seq, iCLIP in wild type worms, knock out and catalytic inactive mutants of CSR-1 protein at different times of germline development.
The project is to identify differentially modified genes and pathways in epithelia cells when challenged with Streptococcus pneumoniae serotypes. S. pneumoniae has >90 different serotypes designated as either “carrier” or “invasive”. Some serotypes of S. pneumoniae are naturally carried within the nasopharynx (carrier), or are opportunistic serotypes that escape the nasopharynx causing disease within the host (invasive). In the case of a carrier serotype, the host is able to clear/control the infection, and develop a memory response to infection. In contrast, an invasive strain subverts the host immune response, leading to disease progression and potentially lethality. These works will extend our knowledge of genes/pathways induced between carriage and invasive serotypes of S. pneumoniae.
Cellular senescence is a complex stress response that durable (yet not irreversibly) arrests cell proliferation and is accompanied by widespread changes in chromatin structure, metabolism and gene exp
DNA Topoisomerase 1 (Top1) is a major regulator of gene expression with great impact on genome stability. Similarly, Guanine quadruplexes (G4) have recently emerged as critical elements for transcript