Seminaires

Les séminaires ont lieu les mardis à 14h dans l'amphithéâtre du CGFB (sauf avis contraire)

 

Prochain Séminaire :

16 Mars 2021 - Misbah Razzac, Inserm,  équipe Vintage-U1219

Abstract :

An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism.

Pulmonary embolism is a severe and potentially fatal condition characterized by the presence of a blood clot (or thrombus) in the pulmonary artery. Pulmonary embolism is often the consequence of the migration of a thrombus from a deep vein to the lung. Together with deep vein thrombosis, pulmonary embolism forms the so-called venous thromboembolism, the third most common cardiovascular disease, and its prevalence strongly increases with age. While pulmonary embolism is observed in ~40% of patients with deep vein thrombosis, there is currently limited biomarkers that can help to predict which patients with deep vein thrombosis are at risk of pulmonary embolism.  To fill this need, we implemented two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximation of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome-wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (p = 5.3x10-7) at the PLXNA4 locus, with lead SNP rs1424597 at which the minor A allele was further shown to associate with an increased risk of PE (OR = 1.49 [1.12 – 1.98], p = 6.1x10-3). Further association analysis in EOVT revealed that, in the combined MARTHA and EOVT samples, the rs1424597-A allele was associated with increased PE risk (OR = 1.74 [1.27 – 2.38,  p = 5.42x10-4) in patients over 37 years of age but not in younger patients (OR = 0.96 [0.65 – 1.41], p = 0.848). 

 

 

Séminaires à venir

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Séminaires passés

2 Mars 2021 - Corentin Dechaud (IGFL), équipe Genomique Evolutive des Poissons (http://igfl.ens-lyon.fr/equipes/j.-n.-volff-fish-evolutionary-genomics)

Abstract :

Assessing the role of transposable elements in the control of sexual genes in teleost fish

In teleost fish, sexual reproduction modes and sexual gene regulatory networks are highly variable. Sex can be determined either environmentally or genetically and is controlled by different genes depending on the species investigated. Sexual development and maintenance also appears variable in this clade. Possible genetic determinants at the origin of this diversity are transposable elements. Transposable elements are endogenous DNA sequences able to insert, and by this way to copy themselves in genomes. Even if they are often neutral or deleterious for their host, transposable elements can also be a source of evolutionary innovations, thanks to the regulatory sequences, such as transcription factor binding sites, they carry and spread in genomes. Their diversity in fish genomes constitutes a reservoir of numerous ready-to-use regulatory sequences that could be involved in the fast evolution of some gene regulatory networks. To test this hypothesis, we used RNA sequencing data from male and female gonads from teleost fish species of the genus Oryzias. We looked for transposable element families enriched in the vicinity of sex-biased genes. Doing so we were in particular able to detect different candidate families over-represented in the 5’ untranslated region of testis-biased genes. We focused on one of these TE families and showed that it harbors transcription factor binding sites for transcription factors involved in sexual function. This work brings new insights into the role of transposable elements in the fast evolution of gene regulatory networks and is paving the way for future functional studies.

8 Décembre 2020 - Jean Delmotte, Université de Montpellier (IHPE, UMR 5244), France

Abstract :

Phylogeography, genetic diversity and connectivity of Ostreid herpesvirus-1 population in France

 

Recurrent mortalities have been affecting juvenile Pacific oysters (Crassostrea gigas) for more than 30 years. Among the pathogens involved, the preponderant role of the Ostreid herpesvirus 1 (OsHV-1) virus in the mortality syndrome called “Pacific Oyster Mortality Syndrome” (POMS) has recently been demonstrated. The OsHV-1 epidemics in oyster farming areas have made this virus a major threat to the oyster industry. However, genomic epidemiology in certain regions at risk, in particular in France, remains limited. We report 21 OsHV-1 genomes generated using high-throughput sequencing during mass mortality episodes in 3 regions of the French coast. Using new bioinformatics methodology and adopting a three-set genomic variation analysis strategy, we reveal the connectivity of OsHV-1 viral population in France. The main source is probably the Marenne d'Oléron area, the viruses are then introduced into other shellfish-growing areas, probably following the transfer of oyster spat. The spatial heterogeneity of the transmission of OsHV-1 calls into question the surveillance of malacoherpesviruses and disease control measures.

24 Novembre 2020 - Tiffany Delhomme (IRB Barcelone, Espagne)

Abstract :

Dessiner le paysage des mutations génétiques à partir de l’analyse de données “difficiles” à l’aide de needlestack et hyperstack.

La génomique moderne possède un fort potentiel d'application en cancérologie, et tient actuellement toutes ces promesses grâce au séquençage nouvel génération (NGS). Cette puissante technologie permet de déterminer les séquences ADN de plusieurs centaines voire milliers d'individus en coût et en temps raisonnables, et s’applique aussi depuis peu à la détection du génome de cellules individuelles. Néanmoins, elle est propice aux erreurs deux types: de séquençage, et d’amplification dans le cas du séquençage de cellules uniques. Dans un premier temps, je vais vous présenter needlestack, un nouvel outil bioinformatique qui permet de détecter efficacement les mutations somatiques, même présentes en faible proportion, à partir de données NGS, et ses applications en détection précoce du cancer. Dans un second temps, je vais vous présenter hyperstack, une adaptation de needlestack pour la reconstruction des profiles mutationels à partir de données de cellules uniques. Hyperstack integre une etape d’apprentissage automatique supplémentaire afin d’estimer les erreurs d’amplification, en plus des erreurs de séquençage estimées par needlestack. Finalement, je présenterais une application d’hyperstack à des données d’ADN de cellules uniques à couverture très faible.

11 Février 2020 - Anais Baudot (Marseille Medical Genetics Institute, Aix-Marseille Université )

Mining networks to study rare and common diseases

Abstract :

Networks are scaling-up the analysis of gene and protein functions, thereby offering new avenues to study the diseases in which these macromolecules are involved. I will discuss the exploration of -omics networks containing thousands of physical and functional interactions between genes and proteins. In particular, we now focus on multiplex networks, i.e., networks composed of layers containing the same nodes but different interaction categories, such as protein-protein interactions, molecular complexes or correlations of expression.

We develop algorithms (e.g., community detections, random walks) to explore these large and complex biological networks, integrate information (e.g., expression), and mine the functional knowledge they contain. I will show how we use these tools to study rare and common genetic diseases, in particular premature aging diseases and diseases-disease comorbidity relationships.

Associated publications

  • The DREAM Module Identification Challenge Consortium, Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Fang T, et al. Assessment of network module identification across complex diseases. Nature Methods. 2019 Sep;16(9):843–52.
  • Valdeolivas A, Tichit L, Navarro C, Perrin S, Odelin G, Levy N, et al. Random Walk with Restart on Multiplex and Heterogeneous Biological Networks. Bioinformatics. 2018 Jul 18;
  • Ibáñez K, Boullosa C, Tabarés-Seisdedos R, Baudot A, Valencia A. Molecular Evidence for the Inverse Comorbidity between Central Nervous System Disorders and Cancers Detected by Transcriptomic Meta-analyses. Horwitz MS, editor. PLoS Genetics. 2014 Feb 20;10(2):e1004173.

 

4 Février 2020- Alexandra Calteau (LABGeM bioinformatics team of the UMR 8030 Genomics Metabolics, research structure of Genoscope )

TITRE : MicroScope: an integrated platform for the annotation and exploration of microbial gene functions through genomic, pangenomic and metabolic comparative analysis
Résumé :
Le séquençage du génome à grande échelle et l'utilisation de plus en plus massive d'approches à haut débit produisent une grande quantité de nouvelles informations qui transforment complètement notre compréhension de milliers d'espèces microbiennes. Cependant, malgré le développement d'approches bioinformatiques puissantes, l'interprétation complète du contenu de ces génomes reste une tâche difficile. Lancée en 2005, la plate-forme MicroScope (https://www.genoscope.cns.fr/agc/microscope) est en développement continu et fournit des analyses pour des projets de génomes procaryotes ainsi que la reconstruction de réseaux métaboliques et des expériences post-génomiques permettant aux utilisateurs d'améliorer la compréhension des fonctions génétiques. Récemment, de nouveaux outils et pipelines ont été développés pour effectuer des analyses comparatives sur des centaines de génomes à partir de graphiques de pangénomes.
À ce jour, MicroScope contient des données pour plus de 12 300 génomes microbiens, dont une partie est conservée et entretenue manuellement par des microbiologistes (> 4700 comptes personnels en janvier 2020). La plateforme permet un travail collaboratif dans un contexte génomique comparatif riche et améliore les efforts de conservation communautaires.

 

22 Octobre 2019  - Guillaume Bernard (Sorbonne university, MNHN, Paris)

Next-generation phylogenomics: alignment-free approaches, sequence similarity networks and more.

 

8 Octobre 2019 - Laurent Brehelin (LIRMM, Montpellier)

Probing transcriptional regulation with statistical models

 

21 Mai 2019 - Eduardo Rocha (Institut Pasteur)

Horizontal gene transfer: from acquisition to functional innovation

 

7 Mai 2019 - Florian Thibord (UPMC Université Paris 6)

Alignement des données miRseq

 

26 Mars 2019 - Julien Chiquet (AgroParisTech)

A collection of Poisson lognormal models for multivariate analysis of count data

 

19 Février 2019 - Magali Champion (Université Paris Descartes)

AMARETTO: Multi-omics data fusion for cancer data

 

8 Janvier 2019 - Warren Francis (University of Southern Denmark)

Comparative genomics and the nature of placozoan species

 

29 Novembre 2018 - Antonio Marco (University of Essex, UK), TBA

On sex, mothers and microRNA

 

11 Novembre 2018 - Clovis Galliez (Université de Grenoble)

Making sense of the metagenomics mixture: identifying bacterial hosts from phage sequences and binning billions of contigs