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1. Genome Size Variation and Comparative Genomics Reveal Intraspecific Diversity in Brassica rapa

Author

Julien Boutte, Loeiz Maillet, Thomas Chaussepied, Sébastien Letort, Jean-Marc Aury, Caroline Belser, Franz Boideau, Anael Brunet, Olivier Coriton, Gwenaëlle Deniot, Cyril Falentin, Virginie Huteau, Maryse Lodé-Taburel, Jérôme Morice, Gwenn Trotoux, Anne-Marie Chèvre, Mathieu Rousseau-Gueutin, and Julie Ferreira de Carvalho

Subjects
Brassica, genome evolution, transposable elements, LTR Gypsy, intraspecific diversity, ribosomal DNA, Plant culture, SB1-1110
Abstract

Traditionally, reference genomes in crop species rely on the assembly of one accession, thus occulting most of intraspecific diversity. However, rearrangements, gene duplications, and transposable element content may have a large impact on the genomic structure, which could generate new phenotypic traits. Comparing two Brassica rapa genomes recently sequenced and assembled using long-read technology and optical mapping, we investigated structural variants and repetitive content between the two accessions and genome size variation among a core collection. We explored the structural consequences of the presence of large repeated sequences in B. rapa ‘Z1’ genome vs. the B. rapa ‘Chiifu’ genome, using comparative genomics and cytogenetic approaches. First, we showed that large genomic variants on chromosomes A05, A06, A09, and A10 are due to large insertions and inversions when comparing B. rapa ‘Z1’ and B. rapa ‘Chiifu’ at the origin of important length differences in some chromosomes. For instance, lengths of ‘Z1’ and ‘Chiifu’ A06 chromosomes were estimated in silico to be 55 and 29 Mb, respectively. To validate these observations, we compared using fluorescent in situ hybridization (FISH) the two A06 chromosomes present in an F1 hybrid produced by crossing these two varieties. We confirmed a length difference of 17.6% between the A06 chromosomes of ‘Z1’ compared to ‘Chiifu.’ Alternatively, using a copy number variation approach, we were able to quantify the presence of a higher number of rDNA and gypsy elements in ‘Z1’ genome compared to ‘Chiifu’ on different chromosomes including A06. Using flow cytometry, the total genome size of 12 Brassica accessions corresponding to a B. rapa available core collection was estimated and revealed a genome size variation of up to 16% between these accessions as well as some shared inversions. This study revealed the contribution of long-read sequencing of new accessions belonging to different cultigroups of B. rapa and highlighted the potential impact of differential insertion of repeat elements and inversions of large genomic regions in genome size intraspecific variability.

Published
2020
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2. Associations between nitric oxide synthase genes and exhaled NO-related phenotypes according to asthma status.

Author

Emmanuelle Bouzigon, Florent Monier, Mekki Boussaha, Nicole Le Moual, Hélène Huyvaert, Régis Matran, Sébastien Letort, Jean Bousquet, Isabelle Pin, Mark Lathrop, Francine Kauffmann, Florence Demenais, Rachel Nadif, and EGEA Cooperative Group

Subjects
Medicine, Science
Abstract

BACKGROUND: The nitric oxide (NO) pathway is involved in asthma, and eosinophils participate in the regulation of the NO pool in pulmonary tissues. We investigated associations between single nucleotide polymorphisms (SNPs) of NO synthase genes (NOS) and biological NO-related phenotypes measured in two compartments (exhaled breath condensate and plasma) and blood eosinophil counts. METHODOLOGY: SNPs (N = 121) belonging to NOS1, NOS2 and NOS3 genes were genotyped in 1277 adults from the French Epidemiological study on the Genetics and Environment of Asthma (EGEA). Association analyses were conducted on four quantitative phenotypes: the exhaled fraction of NO (Fe(NO)), plasma and exhaled breath condensate (EBC) nitrite-nitrate levels (NO2-NO3) and blood eosinophils in asthmatics and non-asthmatics separately. Genetic heterogeneity of these phenotypes between asthmatics and non-asthmatics was also investigated. PRINCIPAL FINDINGS: In non-asthmatics, after correction for multiple comparisons, we found significant associations of Fe(NO) levels with three SNPs in NOS3 and NOS2 (P ≤ 0.002), and of EBC NO2-NO3 level with NOS2 (P = 0.002). In asthmatics, a single significant association was detected between Fe(NO) levels and one SNP in NOS3 (P = 0.004). Moreover, there was significant heterogeneity of NOS3 SNP effect on Fe(NO) between asthmatics and non-asthmatics (P = 0.0002 to 0.005). No significant association was found between any SNP and NO2-NO3 plasma levels or blood eosinophil counts. CONCLUSIONS: Variants in NO synthase genes influence Fe(NO) and EBC NO2-NO3 levels in adults. These genetic determinants differ according to asthma status. Significant associations were only detected for exhaled phenotypes, highlighting the critical relevance to have access to specific phenotypes measured in relevant biological fluid.

Published
2012
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3. Transcription reprogramming during root nodule development in Medicago truncatula.

Author

Sandra Moreau, Marion Verdenaud, Thomas Ott, Sébastien Letort, Françoise de Billy, Andreas Niebel, Jérôme Gouzy, Fernanda de Carvalho-Niebel, and Pascal Gamas

Subjects
Medicine, Science
Abstract

Many genes which are associated with root nodule development and activity in the model legume Medicago truncatula have been described. However information on precise stages of activation of these genes and their corresponding transcriptional regulators is often lacking. Whether these regulators are shared with other plant developmental programs also remains an open question. Here detailed microarray analyses have been used to study the transcriptome of root nodules induced by either wild type or mutant strains of Sinorhizobium meliloti. In this way we have defined eight major activation patterns in nodules and identified associated potential regulatory genes. We have shown that transcription reprogramming during consecutive stages of nodule differentiation occurs in four major phases, respectively associated with (i) early signalling events and/or bacterial infection; plant cell differentiation that is either (ii) independent or (iii) dependent on bacteroid differentiation; (iv) nitrogen fixation. Differential expression of several genes involved in cytokinin biosynthesis was observed in early symbiotic nodule zones, suggesting that cytokinin levels are actively controlled in this region. Taking advantage of databases recently developed for M. truncatula, we identified a small subset of gene expression regulators that were exclusively or predominantly expressed in nodules, whereas most other regulators were also activated under other conditions, and notably in response to abiotic or biotic stresses. We found evidence suggesting the activation of the jasmonate pathway in both wild type and mutant nodules, thus raising questions about the role of jasmonate during nodule development. Finally, quantitative RT-PCR was used to analyse the expression of a series of nodule regulator and marker genes at early symbiotic stages in roots and allowed us to distinguish several early stages of gene expression activation or repression.

Published
2011
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4. Genome Size Variation and Comparative Genomics Reveal Intraspecific Diversity in Brassica rapa

Author

Gwenn Trotoux, Jean-Marc Aury, Loeiz Maillet, Anael Brunet, Franz Boideau, Virginie Huteau, Jérôme Morice, Mathieu Rousseau-Gueutin, Olivier Coriton, Cyril Falentin, Sébastien Letort, Julien Boutte, Maryse Lodé-Taburel, Anne-Marie Chèvre, Gwenaëlle Deniot, Julie Ferreira de Carvalho, Thomas Chaussepied, Caroline Belser, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), H2020 Marie Skłodowska-Curie Actions, Agence Nationale de la Recherche, This work was made possible by financial support of the European Union and a Marie Sklodowska-Curie grant (No. 791908) awarded to JF as well as a BOOST’EUROPE financed by the Conseil régional de Bretagne. FB was supported by a fellowship from BAP INRAE and Conseil régional de Bretagne. This work was additionally supported by the France Génomique National infrastructure, funded as part of the «Investissements d’Avenir » program managed by the Agence Nationale pour la Recherche (contract ANR-10-INBS-09, ANR-10-INBS-0009,France-Génomique,Organisation et montée en puissance d'une Infrastructure Nationale de Génomique(2010), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)

Subjects
0106 biological sciences, 0301 basic medicine, Genome evolution, Plant Science, Brassica, Biology, lcsh:Plant culture, genome evolution, 01 natural sciences, Genome, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, 03 medical and health sciences, Brassica rapa, lcsh:SB1-1110, Copy-number variation, Genome size, Gene, Comparative genomics, ribosomal DNA, LTR Gypsy, Phenotypic trait, 030104 developmental biology, Evolutionary biology, intraspecific diversity, transposable elements, 010606 plant biology & botany
Abstract

International audience; Traditionally, reference genomes in crop species rely on the assembly of one accession, thus occulting most of intraspecific diversity. However, rearrangements, gene duplications, and transposable element content may have a large impact on the genomic structure, which could generate new phenotypic traits. Comparing two Brassica rapa genomes recently sequenced and assembled using long-read technology and optical mapping, we investigated structural variants and repetitive content between the two accessions and genome size variation among a core collection. We explored the structural consequences of the presence of large repeated sequences in B. rapa 'Z1' genome vs. the B. rapa 'Chiifu' genome, using comparative genomics and cytogenetic approaches. First, we showed that large genomic variants on chromosomes A05, A06, A09, and A10 are due to large insertions and inversions when comparing B. rapa 'Z1' and B. rapa 'Chiifu' at the origin of important length differences in some chromosomes. For instance, lengths of 'Z1' and 'Chiifu' A06 chromosomes were estimated in silico to be 55 and 29 Mb, respectively. To validate these observations, we compared using fluorescent in situ hybridization (FISH) the two A06 chromosomes present in an F1 hybrid produced by crossing these two varieties. We confirmed a length difference of 17.6% between the A06 chromosomes of 'Z1' compared to 'Chiifu.' Alternatively, using a copy number variation approach, we were able to quantify the presence of a higher number of rDNA and gypsy elements in 'Z1' genome compared to 'Chiifu' on different chromosomes including A06. Using flow cytometry, the total genome size of 12 Brassica accessions corresponding to a B. rapa available core collection was estimated and revealed a genome size variation of up to 16% between these accessions as well as some shared inversions. This study revealed the contribution of long-read sequencing of new accessions belonging to different cultigroups of B. rapa and highlighted the potential impact of differential insertion of repeat elements and inversions of large genomic regions in genome size intraspecific variability.

Published
2020

5. Biallelic Variants in UBA5 Reveal that Disruption of the UFM1 Cascade Can Result in Early-Onset Encephalopathy

Author

Estelle Colin, Jens Daniel, Alban Ziegler, Jamal Wakim, Aurora Scrivo, Tobias B. Haack, Salim Khiati, Anne-Sophie Denommé, Patrizia Amati-Bonneau, Majida Charif, Vincent Procaccio, Pascal Reynier, Kyrieckos A. Aleck, Lorenzo D. Botto, Claudia Lena Herper, Charlotte Sophia Kaiser, Rima Nabbout, Sylvie N’Guyen, José Antonio Mora-Lorca, Birgit Assmann, Stine Christ, Thomas Meitinger, Tim M. Strom, Holger Prokisch, Antonio Miranda-Vizuete, Georg F. Hoffmann, Guy Lenaers, Pascale Bomont, Eva Liebau, Dominique Bonneau, Emmanuelle Génin, Dominique Campion, Jean-François Dartigues, Jean-François Deleuze, Jean-Charles Lambert, Richard Redon, Thomas Ludwig, Benjamin Grenier-Boley, Sébastien Letort, Pierre Lindenbaum, Vincent Meyer, Olivier Quenez, Christian Dina, Céline Bellenguez, Camille Charbonnier -Le Clézio, Joanna Giemza, Stéphanie Chatel, Claude Férec, Hervé Le Marec, Luc Letenneur, Gaël Nicolas, Karen Rouault, Delphine Bacq, Anne Boland, Doris Lechner, Service de génétique [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), MitoVasc - Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC), Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Biologie Neurovasculaire et Mitochondriale Intégrée (BNMI), Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Institut des Neurosciences de Montpellier (INM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Epilepsies de l'Enfant et Plasticité Cérébrale (U1129), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Clinique Médicale Pédiatrique, Centre hospitalier universitaire de Nantes (CHU Nantes), Institute of Human Genetics, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)-Helmholtz Zentrum München = German Research Center for Environmental Health, Mitochondrie : Régulations et Pathologie, Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC), Institut des Neurosciences de Montpellier - Déficits sensoriels et moteurs (INM), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)-German Research Center for Environmental Health-Helmholtz-Zentrum München (HZM), Inst MitoVasc, Equipe MitoLab, Université d'Angers (UA), and Technische Universität München [München] (TUM)-Helmholtz-Zentrum München (HZM)-German Research Center for Environmental Health

Subjects
0301 basic medicine, Male, Microcephaly, Movement disorders, [SDV]Life Sciences [q-bio], Ubiquitin-Activating Enzymes, Endoplasmic Reticulum, Synaptic Transmission, Exome, Genetics(clinical), Age of Onset, Child, Zebrafish, Genetics (clinical), Caenorhabditis elegans, Genetics, Brain Diseases, Brain Mapping, Movement Disorders, biology, Magnetic Resonance Imaging, Cholinergic Neurons, 3. Good health, Child, Preschool, Female, medicine.symptom, Encephalopathy, Genes, Recessive, 03 medical and health sciences, Intellectual Disability, Report, medicine, Gene silencing, Animals, Humans, Caenorhabditis elegans Proteins, Gene, Ubiquitins, Alleles, Epilepsy, Ubiquitin, Endoplasmic reticulum, Proteins, Fibroblasts, Zebrafish Proteins, biology.organism_classification, medicine.disease, 030104 developmental biology, Mutation
Abstract

International audience; Via whole-exome sequencing, we identified rare autosomal-recessive variants in UBA5 in five children from four unrelated families affected with a similar pattern of severe intellectual deficiency, microcephaly, movement disorders, and/or early-onset intractable epilepsy. UBA5 encodes the E1-activating enzyme of ubiquitin-fold modifier 1 (UFM1), a recently identified ubiquitin-like protein. Biochemical studies of mutant UBA5 proteins and studies in fibroblasts from affected individuals revealed that UBA5 mutations impair the process of ufmylation, resulting in an abnormal endoplasmic reticulum structure. In Caenorhabditis elegans, knockout of uba-5 and of human orthologous genes in the UFM1 cascade alter cholinergic, but not glutamatergic, neurotransmission. In addition, uba5 silencing in zebrafish decreased motility while inducing abnormal movements suggestive of seizures. These clinical, biochemical, and experimental findings support our finding of UBA5 mutations as a pathophysiological cause for early-onset encephalopathies due to abnormal protein ufmylation.

Published
2016

6. Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks

Author

Joachim Heinrich, Arthur W. Musk, Dan L. Nicolae, Magnus Wickman, Anita L. Kozyrskyj, George T. O'Connor, Sven Michel, John Beilby, Nicole Probst-Hensch, André G. Uitterlinden, Ulrike Gehring, Eugene R. Bleecker, Markku Heliövaara, Christer Janson, Janine Altmüller, Tatsuhiko Tsunoda, Kathleen C. Barnes, Johan G. Eriksson, Alexey Polonikov, Penelope E. Graves, Andrea von Berg, Philip J. Thompson, Sina A. Gharib, Johan C. de Jongste, Miriam F. Moffatt, Adaikalavan Ramasamy, Kristin M. Burkart, Thomas J. Hudson, Marjo-Riitta Järvelin, Rasika A. Mathias, Kathleen M. Donohue, Gonneke Willemsen, Yuliya Fedorova, Michael Kabesch, Jing Hua Zhao, Ashok Kumar, Kenji Matsumoto, Vivi Schlünssen, Dara G. Torgerson, Terri H. Beaty, Florence Demenais, Julie E. Park, Tari Haahtela, Aarno Palotie, Elisabeth Widen, Hamida Mohamdi, Vladimir P. Ivanov, Tarja Laitinen, Emiko Noguchi, Lewis J. Smith, Valérie Siroux, Christopher E. Brightling, P. A. Selivanova, Frank D. Gilliland, Johannes Waage, Deborah A. Meyers, Unnur Thorsteinsdottir, Melanie C. Matheson, Hiroshi Hirose, Sébastien Letort, Andrew Bush, Alan James, Kari Stefansson, Robert A. Scott, Isabelle Romieu, Mads Melbye, Albert M. Levin, Laura R. Loehr, Guo Li, Veikko Salomaa, Celeste Eng, Esteban G. Burchard, Ralf J. P. van der Valk, Bjarke Feenstra, Daan W. Loth, Atsushi Takahashi, Lies Lahousse, Denise Daley, Stephen S. Rich, Carla M. T. Tiesler, Liming Liang, L. Keoki Williams, Susanne Lau, Nicholas J. Wareham, Erik Melén, Cameron D. Palmer, Medea Imboden, Patricia Margaritte-Jeannin, Unnur S. Bjornsdottir, Ludmila M. Ogorodova, Erika von Mutius, Gerard H. Koppelman, Susan R. Heckbert, Rachel A. Myers, Martin Farrall, Moira Chan-Yeung, Jim Gauderman, Frank Geller, Sailaja Vedantam, Rajesh Kumar, Kian Fan Chung, Jon Genuneit, John Henderson, David B. Kantor, Carole Ober, Alexessander Couto Alves, Craig E. Pennell, Inge M. Wouters, Catherine Laprise, Terho Lehtimäki, Colin F. Robertson, Emmanuelle Bouzigon, Maxim B. Freidin, William O.C.M. Cookson, Bruno H. Stricker, John A. Curtin, Albert Hofman, Muhammad T. Salam, Blanca E. Del-Rio-Navarro, Young-Ae Lee, Liesbeth Duijts, Klaus Bønnelykke, Vincent W. V. Jaddoe, Göran Pershagen, Dirkje S. Postma, Pekka Jousilahti, Hans Bisgaard, Dorret I. Boomsma, Amaury Vaysse, Deborah Jarvis, Maria Solodilova, Gudmar Thorleifsson, James J. Yang, V. P. Puzyrev, Manuel A. R. Ferreira, Maartje A.E. Nieuwenhuis, Jouke J. Hottenga, Ingileif Jonsdottir, Graham Jones, Myriam Brossard, Jennie Hui, Judith M. Vonk, Allan B. Becker, Elza Khusnutdinova, Wendy L. McArdle, Benjamin A. Raby, Olli T. Raitakari, Wendy B. White, Mark Lathrop, Adnan Custovic, Ingo Marenholz, Joel N. Hirschhorn, Fernando J. Martinez, Mikko Kuokkanen, Michiaki Kubo, Patrick G. Holt, Torben Sigsgaard, Eskil Kreiner, Stephanie J. London, Daniel F. Gudbjartsson, Mika Kähönen, Guy Brusselle, Blanca E. Himes, R. Graham Barr, Scott T. Weiss, David P. Strachan, Hamdi Mbarek, Wei Ang, A. S. Karunas, Marie Standl, Angela Simpson, Dick Heederik, Zofia K. Z. Gajdos, Raquel Granell, Ani Manichaikul, Fondation Jean-Dausset-CEPH, INSERM U946, Institut National de la Santé et de la Recherche Médicale (INSERM), Variabilité Génétique et Maladies Humaines, Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Medicine [Aurora, CO, USA], University of Colorado [Denver], National Heart and Lung Institute (NHLI), Imperial College London, Cologne Center for Genomics (CCG), Cologne Center for Genomics-University of Cologne, Johns Hopkins University (JHU), Pediatrics and Child Health, University of Manitoba [Winnipeg], University of Arizona, King‘s College London, Méthodologie statistique et épidémiologie génétique de maladies multifactorielles, Université d'Évry-Val-d'Essonne (UEVE)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Respiratory Medicine and Thoracic Surgery, University of Leicester-Institute for Lung Health, Ghent University Hospital, Department of Paediatric Respiratory Medicine, Imperial College London-Royal Brompton Hospital-National Heart and Lung Institute [UK], Airway Disease Section, National Heart and Lung Institute, The Generation R Study group, Erasmus University Medical Centre, Medstar Research Institute, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Université Paris-Sorbonne - Paris 4 - École supérieure du professorat et de l'éducation - Académie de Paris (ESPE Paris), Université Paris-Sorbonne (UP4), Population Genetics Laboratory [Tomsk, Russia], Research Institute for Medical Genetics [Tomsk, Russia], University of Southern California (USC), Utrecht University [Utrecht], Institute of Epidemiology, Universität Ulm - Ulm University [Ulm, Allemagne], MRC Integrative Epidemiology Unit [Bristol, Royaume-Uni] (MRC IEU), University of Bristol [Bristol], Arizona Respiratory Center, Helsinki University Hospital, Division of Occupational and Environmental Health, Institute for Risk Assessment (IRAS), Ludwig Maximilian University [Munich] (LMU), National Institute of Health and Welfare, MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Department of Mathematics, University of Warwick, Warwick Mathematics Institute (WMI), University of Warwick [Coventry]-University of Warwick [Coventry], Sir Charles Gairdner Hospital, Swiss Tropical and Public Health Institute [Basel], The Generation R Study, Pediatrics, Epidemiology, Uppsala University, Institute of Health Sciences and Biocenter Oulu, University of Oulu, Tampere University Hospital, Institute of Biochemistry and Genetics of Ufa Scientific Centre, Russian Academy of Sciences [Moscow] (RAS), Pediatric Pulmonology, Allergology & Epidemiology, University of Groningen [Groningen]-University Medical Center Groningen [Groningen] (UMCG)-Beatrix Children's Hospital-Groningen Research Institute for Asthma and COPD, National Center for Atmospheric Research [Boulder] (NCAR), Epidemiology & Public Health, Swiss Tropical and Public Health Institute [Basel]-Medical School University of Basel, Department of Respiratory Medicine, Departments of Pulmonary Medicine and Medical Genetics, Université du Québec à Chicoutimi (UQAC), McGill University and Genome Quebec Innovation Centre, Department of Pediatric Pneumology and Immunology, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Max Delbrück Center for Molecular Medicine [Berlin] (MDC), Helmholtz-Gemeinschaft = Helmholtz Association, Faculty of Medicine and Life Sciences [Tampere], University of Tampere [Finland], Laboratoire des interactions plantes micro-organismes (LIPM), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), China Agricultural University (CAU), Harvard School of Public Health, Department of Epidemiology, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC)-UNC Gillings School of Global Public Health-Carolina Center for Genome Sciences, National Institute for Environmental Health Sciences Research Triangle Park, National Institute for Materials Science (NIMS), Dept. of Epidemiology Research, Statens Serum Institut [Copenhagen], Institute of Environmental Medicine [Stockholm, Sweden], Karolinska Institutet [Stockholm]-Karolinska University Hospital [Stockholm]-Astrid Lindgren Children's Hospital, Center for Human Genomics, Wake Forest University, Université de Tsukuba = University of Tsukuba, Head of Medical Sequencing, Institute of environmental medicine, Karolinska Institute, Respiratory Epidemiology and Public Health, Imperial College London-School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU)-MRC-HPA Centre for Environment and Health, Centre International de Recherche contre le Cancer (CIRC), Department of Chronic Disease Prevention, National Institute for Health and Welfare [Helsinki], Aarhus University [Aarhus], Institute of Metabolic Science, MRC, Section of Environment Occupation & Health, University of Manchester [Manchester], Epidémiologie et Biostatistique, Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Santé et de la Recherche Médicale (INSERM), deCODE Genetics, deCODE genetics [Reykjavik], Population Health Sciences and Education, St George's University of London, Drug Safety Unit, Inspectorate for Health Care, Tohoku University [Sendai], Department of Oceanography, University of Hawai‘i [Mānoa] (UHM), University of California [San Francisco] (UCSF), University of California, Asthma and Allergy Department, University Children's Hospital-Ludwig Maximilians University, IT University of Copenhagen, MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge [UK] (CAM), Sachs’ Children and Youth Hospital [Stockholm, Sweden], Genetic Epidemiology Unit, Addenbrooke's Hospital, University of Illinois [Chicago] (UIC), University of Illinois System, Titu Maiorescu University Bucharest, Titu Maiorescu University = Universitatea Titu Maiorescu [Buchares] (UTM), Pulmonary Medicine, Erasmus MC other, Internal Medicine, Biological Psychology, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Vaysse, Amaury, University of Oxford, University of California [San Francisco] (UC San Francisco), University of California (UC), University Children's Hospital-Ludwig-Maximilians University [Munich] (LMU), IT University of Copenhagen (ITU), Groningen Research Institute for Asthma and COPD (GRIAC), Medical Research Council (MRC), National Institute for Health Research, Wellcome Trust, Wareham, Nicholas [0000-0003-1422-2993], Zhao, Jing Hua [0000-0003-4930-3582], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, HAY-FEVER, Netherlands Twin Register (NTR), [SDV]Life Sciences [q-bio], Genome-wide association study, [SDV.GEN] Life Sciences [q-bio]/Genetics, VARIANTS, Australian Asthma Genetics Consortium (AAGC) collaborators, Epigenesis, Genetic, 0302 clinical medicine, Pleiotropy, immune system diseases, Leukocytes, Promoter Regions, Genetic, AUTOIMMUNE-DISEASE, 11 Medical and Health Sciences, ComputingMilieux_MISCELLANEOUS, Genetics & Heredity, 3. Good health, Histone Code, [SDV] Life Sciences [q-bio], Enhancer Elements, Genetic, Phenotype, TWINS, Hay fever, POPULATIONS, Life Sciences & Biomedicine, Risk, EXPRESSION, Coronacrisis-Taverne, Biology, [SDV.GEN.GH] Life Sciences [q-bio]/Genetics/Human genetics, 03 medical and health sciences, Immune system, SDG 3 - Good Health and Well-being, medicine, Genetics, Journal Article, Humans, Genetic Predisposition to Disease, Allele, GENOME-WIDE ASSOCIATION, Alleles, METAANALYSIS, Genetic association, Asthma, Autoimmune disease, [SDV.GEN]Life Sciences [q-bio]/Genetics, Science & Technology, Rhinitis, Allergic, Seasonal, 06 Biological Sciences, medicine.disease, GENE, respiratory tract diseases, 030104 developmental biology, 030228 respiratory system, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Genetic Loci, Immunology, Developmental Biology, Genome-Wide Association Study
Abstract

We examined common variation in asthma risk by conducting a meta-analysis of worldwide asthma genome-wide association studies (23,948 asthma cases, 118,538 controls) of individuals from ethnically diverse populations. We identified five new asthma loci, found two new associations at two known asthma loci, established asthma associations at two loci previously implicated in the comorbidity of asthma plus hay fever, and confirmed nine known loci. Investigation of pleiotropy showed large overlaps in genetic variants with autoimmune and inflammatory diseases. The enrichment in enhancer marks at asthma risk loci, especially in immune cells, suggested a major role of these loci in the regulation of immunologically related mechanisms.

Published
2018

7. Narcisse: a mirror view of conserved syntenies

Author

Sébastien Letort, Olivier Stahl, Yoann Beausse, Emmanuel Courcelle, Jérôme Gouzy, Catherine Ngom-Bru, Romain Fremez, Thomas Faraut, Unité mixte de recherche interactions plantes-microorganismes, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut National de la Recherche Agronomique (INRA), Laboratoire de Génétique Cellulaire (LGC), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP)

Subjects
Sequence alignment, Genomics, Computational biology, Genome browser, syntenie, Biology, Genome, Synteny, DNA sequencing, Conserved sequence, 03 medical and health sciences, User-Computer Interface, 0302 clinical medicine, Genetics, Animals, Humans, [SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biochemistry [q-bio.BM], Conserved Sequence, 030304 developmental biology, Whole genome sequencing, 0303 health sciences, Internet, Base Sequence, génome, food and beverages, Chromosome Mapping, Articles, Rats, 030220 oncology & carcinogenesis, BASE DE DONNEES NARCISSE, Databases, Nucleic Acid, Sequence Alignment, Genome, Bacterial, Genome, Plant
Abstract

International audience; New methods and tools are needed to exploit the unprecedented source of information made available by the completed and ongoing whole genome sequencing projects. The Narcisse database is dedicated to the study of genome conservation, from sequence similarities to conserved chromosomal segments or conserved syntenies, for a large number of animals, plants and bacterial completely sequenced genomes. The query interface, a comparative genome browser, enables to navigate between genome dotplots, comparative maps and sequence alignments. The Narcisse database can be accessed at http://narcisse.toulouse.inra.fr.

Published
2007

8. Population Stratification of Rare Variants

Author

Emmanuelle Génin, Marie-Claude Babron, and Sébastien Letort

Subjects
Evolutionary biology, Biology, Population stratification, Allele frequency, Stratification (mathematics)
Abstract

Population stratification has been the focus of many recent studies that evidenced allele frequency differences between populations even at fine geographic scales. Patterns of stratification are influenced by different phenomena and found to vary between common and rare variants. In the different studies performed so far and reviewed in this chapter, rare variants were found to display stronger stratification patterns. This is an important issue that needs to be accounted for when testing for association with rare variants to avoid false-positive results. We show that there is an urgent need for novel methodological developments in this field as the performances of the methods developed to correct for common variant stratification are significantly reduced when testing for association with rare variants.

Published
2015

9. Contents Vol. 77, 2014

Author

Alison Shaw, Hasan Al-Dhekri, Taisa Manuela Bonfim Machado, I. Christopher Lloyd, Fernanda Bender, Nima Rezaei, Nadia Al-Hashmi, Alessandro Gialluisi, Lihadh Al-Gazali, Christine Petit, Hanan Hamamy, Mourad Sahbatou, Mohammad Jalal Abbasi-Shavazi, Insaf Rejeb, Kristen L. Sund, Marion D. Teare, Yosra Bouyacoub, Khalid Abdulhadi, Stavit A. Shalev, Trevor J. Pemberton, Nicholas J. Schork, Diego Vozzi, Mariem Ben Rekaya, Mohamed-Ridha Barbouche, Anne-Louise Leutenegger, Simona Ferrari, Graeme C.M. Black, Khalid Yunis, Noah A. Rosenberg, Nizar Ben Halim, Paolo Giorgi Rossi, Faten Ben Rhouma, Meimanat Hosseini-Chavoshi, Ramin Badii, Majdi Nagara, Steven Gazal, Habib Messai, Martina C. Cornel, Rym Kefi, Liliana Uribe-Bruce, Laura H. Goetz, Moza Khalifa Alkowari, Danjuma Quarless, Watfa Al-Mamari, Zafar Iqbal, Hussein A. Abbas, Emmanuelle Génin, Roberto Giugliani, Crystel Bonnet, Lilia Romdhane, Rachel L. Gillespie, M. Mazharul Islam, Olfa Messaoud, Ondrej Libiger, Tatiana Boa Sorte, Lidewij Henneman, Angelina Xavier Acosta, Said A. Al-Yahyaee, Sandra Leistner-Segal, Kiyoko Abe-Sandes, Giovanni Romeo, Druckerei Stückle, Hans van Bokhoven, Thais Bomfim, Catherine Rehder, Alan H. Bittles, Zied Riahi, Fabiana Moura Costa-Motta, Satz Mengensatzproduktion, Khalid Al-Thihli, Tommaso Pippucci, Andrea Finocchi, Waleed Al-Herz, Elizabeth C. Goyder, Danniel da Silva, Valentina Di Pierro, Marieke E. Teeuw, Leo P. ten Kate, Ken McElreavey, Hervé Perdry, Ibrahim M. Gosadi, Caterina Cancrini, Massimo Mezzavilla, Sonia Abdelhak, Alberto Magi, Joël Zlotogora, Paolo Gasparini, Dragana Vuckovic, Giorgia Girotto, Anu Bashamboo, Giulia Angelino, Roberta Zuntini, Fathiya Al-Murshedi, Sébastien Letort, Alan Bittles, and Peter C. Corry

Subjects
Genetics, Genetics (clinical)
Published
2014

10. Inbreeding Coefficient Estimation with Dense SNP Data: Comparison of Strategies and Application to HapMap III

Author

Sébastien Letort, Steven Gazal, Emmanuelle Génin, Anne-Louise Leutenegger, Hervé Perdry, Mourad Sahbatou, Variabilité Génétique et Maladies Humaines, Université Paris Diderot - Paris 7 ( UPD7 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Fondation Jean Dausset CEPH, Troubles du comportement alimentaire de l'adolescent ( UMR_S 669 ), Université Paris-Sud - Paris 11 ( UP11 ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Centre Hospitalier Régional Universitaire de Brest ( CHRU Brest ), Inserm U1078, équipe ECLA, Génétique, génomique fonctionnelle et biotechnologies (UMR 1078), Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université de Brest ( UBO ) -EFS-Institut Brestois Santé Agro Matière ( IBSAM ), Université de Brest ( UBO ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université de Brest ( UBO ) -EFS-Institut Brestois Santé Agro Matière ( IBSAM ), Université de Brest ( UBO ), Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Troubles du comportement alimentaire de l'adolescent (UMR_S 669), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Sud - Paris 11 (UP11), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Génétique, génomique fonctionnelle et biotechnologies (UMR 1078) (GGB), Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO)-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO)-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM), Gazal, Steven, Université Paris-Sud - Paris 11 (UP11)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), EFS-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-EFS-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Brestois Santé Agro Matière (IBSAM), and Université de Brest (UBO)

Subjects
Linkage disequilibrium, Population, homozygosity-by-descent, Locus (genetics), [SDV.GEN] Life Sciences [q-bio]/Genetics, HapMap Project, Runs of Homozygosity, Biology, Polymorphism, Single Nucleotide, Consanguinity, run of homozygosity, Statistics, Genetics, Humans, Computer Simulation, Inbreeding, International HapMap Project, education, Allele frequency, hidden Markov model, Genetics (clinical), education.field_of_study, Likelihood Functions, [SDV.GEN]Life Sciences [q-bio]/Genetics, Models, Genetic, HapMap III, Estimator, Genetics, Population, Haplotypes, [ SDV.GEN ] Life Sciences [q-bio]/Genetics, linkage disequilibrium
Abstract

Background/Aims: If the parents of an individual are related, it is possible for the individual to have received at 1 locus 2 identical-by-descent alleles that are copies of a single allele carried by the parents' common ancestor. The inbreeding coefficient measures the probability of this event and increases with increasing relatedness between the parents. It is traditionally computed from the observed inbreeding loops in the genealogies and its accuracy thus depends on the depth and reliability of the genealogies. With the availability of genome-wide genetic data, it has become possible to compute a genome-based inbreeding coefficient f, and different methods have been developed to estimate f and identify inbred individuals in a sample from the observed patterns of homozygosity at markers. Methods: For this paper, we performed simulations with known genealogies using different SNP panels with different levels of linkage disequilibrium (LD) to compare several estimators of f, including single-point estimates, methods based on the length of runs of homozygosity (ROHs) and different methods that use hidden Markov models (HMMs). We also compared the performances of some of these estimators to identify inbred individuals in a sample using either HMM likelihood ratio tests or an adapted version of the ERSA software. Results: Single-point methods were found to have higher standard deviations than other methods. ROHs gave the best estimates provided the correct length threshold is known. HMMs on sparse data gave equivalent or better results than HMMs modeling LD. Provided LD is correctly accounted for, the inbreeding estimates were very similar using the different SNP panels. The HMM likelihood ratio tests were found to perform better at detecting inbred individuals in a sample than the adapted ERSA. All methods accurately detected inbreeding up to second-cousin offspring. We applied the best method on release 3 of the HapMap phase III project, found up to 4% of inbred individuals, and created HAP1067, an unrelated and outbred dataset of this release. Conclusions: We recommend using HMMs on multiple sparse maps to estimate and detect inbreeding in large samples. If the sample of individuals is too small to estimate allele frequencies, we advise to estimate them on reference panels or to use 1,500-kb ROHs. Finally, we suggest to investigators using HapMap to be careful with inbred individuals, especially in the GIH (Gujarati Indians from Houston in Texas) population.

Published
2014

11. Associations between nitric oxide synthase genes and exhaled NO-related phenotypes according to asthma status

Author

Mekki Boussaha, Emmanuelle Bouzigon, Florent Monier, Régis Matran, Hélène Huyvaert, Rachel Nadif, Mark Lathrop, Jean Bousquet, Florence Demenais, Francine Kauffmann, Sébastien Letort, Isabelle Pin, Nicole Le Moual, Centre d'Etude du Polymorphisme Humain (CEPH), Fondation Jean Dausset-Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Diderot - Paris 7 (UPD7), Variabilité Génétique et Maladies Humaines, Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris Diderot - Paris 7 (UPD7), Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Service d'explorations fonctionnelles respiratoires [Lille], Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Département pneumologie et addictologie [Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Arnaud de Villeneuve, Institut d'oncologie/développement Albert Bonniot de Grenoble (INSERM U823), Université Joseph Fourier - Grenoble 1 (UJF)-CHU Grenoble-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de pédiatrie, CHU Grenoble-Hôpital Michallon, Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), This research is funded in part by PHRC-Paris, PHRC-Grenoble, ANR 05-SEST-020-02/05-9-97, ANR-06-CEBS, ANR-CES-2009, Region Nord Pas-de-Calais, Merck Sharp & Dohme (MSD), the GA2LEN project, Global Allergy and Asthma European Network and GABRIEL, a multidisciplinary study to identify the genetic and environmental causes of asthma in the European Community (contract 018996 from the European Commission)., the EGEA Cooperative Group, Université Paris Diderot - Paris 7 (UPD7)-Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7)-Fondation Jean Dausset, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), and Nadif, Rachel

Subjects
Male, Pulmonology, MESH: Asthma, Epidemiology, lcsh:Medicine, Biochemistry, 0302 clinical medicine, Pathology, Exhaled breath condensate, lcsh:Science, 0303 health sciences, Multidisciplinary, MESH: Middle Aged, MESH: Polymorphism, Single Nucleotide, Neurochemistry, respiratory system, Middle Aged, 3. Good health, Phenotype, Breath Tests, Genetic Epidemiology, Medicine, Female, MESH: Nitric Oxide Synthase, Neurochemicals, Research Article, Adult, NOS1, Single-nucleotide polymorphism, Biology, Nitric Oxide, MESH: Phenotype, Polymorphism, Single Nucleotide, 03 medical and health sciences, Diagnostic Medicine, Genetics, medicine, Humans, SNP, Allele, 030304 developmental biology, Asthma, Evolutionary Biology, MESH: Humans, Population Biology, Genetic heterogeneity, lcsh:R, Computational Biology, MESH: Adult, medicine.disease, MESH: Male, respiratory tract diseases, MESH: Breath Tests, 030228 respiratory system, Genetic epidemiology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Nitric Oxide, Immunology, Genetic Polymorphism, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, lcsh:Q, Nitric Oxide Synthase, MESH: Female, Population Genetics, Biomarkers, Neuroscience, General Pathology
Abstract

International audience; BACKGROUND: The nitric oxide (NO) pathway is involved in asthma, and eosinophils participate in the regulation of the NO pool in pulmonary tissues. We investigated associations between single nucleotide polymorphisms (SNPs) of NO synthase genes (NOS) and biological NO-related phenotypes measured in two compartments (exhaled breath condensate and plasma) and blood eosinophil counts. METHODOLOGY: SNPs (N = 121) belonging to NOS1, NOS2 and NOS3 genes were genotyped in 1277 adults from the French Epidemiological study on the Genetics and Environment of Asthma (EGEA). Association analyses were conducted on four quantitative phenotypes: the exhaled fraction of NO (Fe(NO)), plasma and exhaled breath condensate (EBC) nitrite-nitrate levels (NO2-NO3) and blood eosinophils in asthmatics and non-asthmatics separately. Genetic heterogeneity of these phenotypes between asthmatics and non-asthmatics was also investigated. PRINCIPAL FINDINGS: In non-asthmatics, after correction for multiple comparisons, we found significant associations of Fe(NO) levels with three SNPs in NOS3 and NOS2 (P ≤ 0.002), and of EBC NO2-NO3 level with NOS2 (P = 0.002). In asthmatics, a single significant association was detected between Fe(NO) levels and one SNP in NOS3 (P = 0.004). Moreover, there was significant heterogeneity of NOS3 SNP effect on Fe(NO) between asthmatics and non-asthmatics (P = 0.0002 to 0.005). No significant association was found between any SNP and NO2-NO3 plasma levels or blood eosinophil counts. CONCLUSIONS: Variants in NO synthase genes influence Fe(NO) and EBC NO2-NO3 levels in adults. These genetic determinants differ according to asthma status. Significant associations were only detected for exhaled phenotypes, highlighting the critical relevance to have access to specific phenotypes measured in relevant biological fluid.

Published
2012

12. Mobyle: a new full web bioinformatics framework

Author

Sébastien Letort, Julien Maupetit, Bertrand Néron, Nicolas Joly, Pierre Tufféry, Catherine Letondal, Corinne Maufrais, Sébastien Carrère, Hervé Ménager, Centre d'Informatique pour la Biologie, Institut Pasteur [Paris], Molécules Thérapeutiques in silico (MTI), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire des interactions plantes micro-organismes (LIPM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), Institut Pasteur [Paris] (IP), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Agence Nationale de la Recherche : GPLA06026G, and Letondal, Catherine

Subjects
Statistics and Probability, Databases, Factual, Computer science, Bioinformatics, Data management, Databases and Ontologies, computer.software_genre, Biochemistry, web, World Wide Web, 03 medical and health sciences, User-Computer Interface, Software, Server, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], Molecular Biology, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], 030304 developmental biology, 0303 health sciences, Internet, End user, business.industry, 030302 biochemistry & molecular biology, Computational Biology, Original Papers, Computer Science Applications, Data flow diagram, Computational Mathematics, Computational Theory and Mathematics, The Internet, [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], User interface, Web service, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], business, computer
Abstract

Motivation: For the biologist, running bioinformatics analyses involves a time-consuming management of data and tools. Users need support to organize their work, retrieve parameters and reproduce their analyses. They also need to be able to combine their analytic tools using a safe data flow software mechanism. Finally, given that scientific tools can be difficult to install, it is particularly helpful for biologists to be able to use these tools through a web user interface. However, providing a web interface for a set of tools raises the problem that a single web portal cannot offer all the existing and possible services: it is the user, again, who has to cope with data copy among a number of different services. A framework enabling portal administrators to build a network of cooperating services would therefore clearly be beneficial. Results: We have designed a system, Mobyle, to provide a flexible and usable Web environment for defining and running bioinformatics analyses. It embeds simple yet powerful data management features that allow the user to reproduce analyses and to combine tools using a hierarchical typing system. Mobyle offers invocation of services distributed over remote Mobyle servers, thus enabling a federated network of curated bioinformatics portals without the user having to learn complex concepts or to install sophisticated software. While being focused on the end user, the Mobyle system also addresses the need, for the bioinfomatician, to automate remote services execution: PlayMOBY is a companion tool that automates the publication of BioMOBY web services, using Mobyle program definitions. Availability: The Mobyle system is distributed under the terms of the GNU GPLv2 on the project web site (http://bioweb2.pasteur.fr/projects/mobyle/). It is already deployed on three servers: http://mobyle.pasteur.fr, http://mobyle.rpbs.univ-paris-diderot.fr and http://lipm-bioinfo.toulouse.inra.fr/Mobyle. The PlayMOBY companion is distributed under the terms of the CeCILL license, and is available at http://lipm-bioinfo.toulouse.inra.fr/biomoby/PlayMOBY/. Contact: mobyle-support@pasteur.fr; mobyle-support@rpbs.univ-paris-diderot.fr; letondal@pasteur.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Published
2009

13. BioWorkFlow: Web Services toolkit and workflow applications evaluation to deploy a confidence network

Author

Marc Wessner, Martin Senger, Franck Samson, Philippe Picouet, François Moreews, Hervé Ménager, Véronique Martin, Sébastien Letort, Catherine Letondal, Mark HOEBEKE, Jerome Gouzy, Jean-François Gibrat, Erwan Corre, Olivier Collin, Sébastien Carrere, Christophe Caron, Pierre Tufféry, Bertrand Néron, Unité de Biologie du développement et biotechnologies (JOUY BIOLOG DEVELOP BIOTECHNOL), Institut National de la Recherche Agronomique (INRA), Physiologie Moléculaire du Transport des Sucres chez les Végétaux (PhyMoTS), Université de Poitiers-Centre National de la Recherche Scientifique (CNRS), Unité Mathématique Informatique et Génome (MIG), Département Logique des Usages, Sciences sociales et Sciences de l'Information (LUSSI), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Lab-STICC_TB_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Biological systems and models, bioinformatics and sequences (SYMBIOSE), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Institut Pasteur [Paris] (IP), Laboratoire Statistique et Génome (SG), Institut National de la Recherche Agronomique (INRA)-Université d'Évry-Val-d'Essonne (UEVE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des interactions plantes micro-organismes (LIPM), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Végétaux marins et biomolécules, Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-GOEMAR-Centre National de la Recherche Scientifique (CNRS), Bioinformatique génomique et moléculaire ((U 726)), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Modélisation mathématique et statistique en biologie et médecine, Ecologie et biologie des interactions (EBI), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne-Université européenne de Bretagne - European University of Brittany (UEB), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut Pasteur [Paris], Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), Unité Mathématique, Informatique et Génome (MIG), Unité de Biologie du développement et biotechnologies ( JOUY BIOLOG DEVELOP BIOTECHNOL ), Institut National de la Recherche Agronomique ( INRA ), Ecologie et biologie des interactions ( EBI ), Université de Poitiers-Centre National de la Recherche Scientifique ( CNRS ), Unité Mathématique Informatique et Génome ( MIG ), Département Logique des Usages, Sciences sociales et Sciences de l'Information ( LUSSI ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance ( Lab-STICC ), École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ) -École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ), Biological systems and models, bioinformatics and sequences ( SYMBIOSE ), Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ), Institut national de la recherche agronomique [Toulouse] ( INRA Toulouse ), Laboratoire Statistique et Génome ( SG ), Institut National de la Recherche Agronomique ( INRA ) -Université d'Évry-Val-d'Essonne ( UEVE ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire des interactions plantes micro-organismes ( LIPMO ), Institut National de la Recherche Agronomique ( INRA ) -Centre National de la Recherche Scientifique ( CNRS ), Unité Mathématique, Informatique et Génome ( MIG ), Végétaux marins et biomolécules ( UMR7139 ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -GOEMAR-Centre National de la Recherche Scientifique ( CNRS ), Bioinformatique génomique et moléculaire, Université Paris Diderot - Paris 7 ( UPD7 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Diderot - Paris 7 (UPD7)

Subjects
[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2008

14. Transcription Reprogramming during Root Nodule Development in Medicago truncatula

Author

Marion Verdenaud, Sébastien Letort, Pascal Gamas, Andreas Niebel, Françoise de Billy, Jérôme Gouzy, Sandra Moreau, Fernanda de Carvalho-Niebel, Thomas Ott, Laboratoire des interactions plantes micro-organismes (LIPM), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Marie-Curie Intra-European Fellowship (024587-Nodule Remorin), ANR-06-GPLA-0005,LEGOO,LEGOO : a bioinformatics gateway towards integrative legume biology(2006), ANR-08-GENM-0015,SYMbiMICS,Dissection moléculaire de l'interaction symbiotique rhizobium-légumineuse : une approche combinée de micro-dissection laser et de séquençage massif d?ESTs(2008), European Project: FP6-GLIP, Unité mixte de recherche interactions plantes-microorganismes, Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), EU INRA, Marie-Curie Intra-European Fellowship : 024587-Nodule Remorin, and Agence Nationale de la Recherche : ANR LEGoo GPLA06026G, ANR SYMbiMICS PCS-08-GENO-106

Subjects
0106 biological sciences, Root nodule, Transcription, Genetic, Plant Science, modèle, Plant Roots, 01 natural sciences, Transcriptome, Plant Microbiology, Gene Expression Regulation, Plant, Plant Genomics, Jasmonate, Regulator gene, Plant Growth and Development, Regulation of gene expression, 0303 health sciences, Sinorhizobium meliloti, Multidisciplinary, Ecology, biology, food and beverages, Cell Differentiation, Genomics, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, Medicago truncatula, Functional Genomics, Cell biology, Community Ecology, Medicine, Root Nodules, Plant, symbiose, Research Article, nodule, Science, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, légumineuse, 03 medical and health sciences, Model Organisms, Nitrogen Fixation, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Botany, Symbiosis, Biology, 030304 developmental biology, Gene Expression Profiling, gène, biology.organism_classification, racine, Gene expression profiling, Species Interactions, Genome Expression Analysis, MEDICAGO TRUNCATULA, Transcription Factors, Developmental Biology, 010606 plant biology & botany
Abstract

International audience; Many genes which are associated with root nodule development and activity in the model legume Medicago truncatula have been described. However information on precise stages of activation of these genes and their corresponding transcriptional regulators is often lacking. Whether these regulators are shared with other plant developmental programs also remains an open question. Here detailed microarray analyses have been used to study the transcriptome of root nodules induced by either wild type or mutant strains of Sinorhizobium meliloti. In this way we have defined eight major activation patterns in nodules and identified associated potential regulatory genes. We have shown that transcription reprogramming during consecutive stages of nodule differentiation occurs in four major phases, respectively associated with (i) early signalling events and/or bacterial infection; plant cell differentiation that is either (ii) independent or (iii) dependent on bacteroid differentiation; (iv) nitrogen fixation. Differential expression of several genes involved in cytokinin biosynthesis was observed in early symbiotic nodule zones, suggesting that cytokinin levels are actively controlled in this region. Taking advantage of databases recently developed for M. truncatula, we identified a small subset of gene expression regulators that were exclusively or predominantly expressed in nodules, whereas most other regulators were also activated under other conditions, and notably in response to abiotic or biotic stresses. We found evidence suggesting the activation of the jasmonate pathway in both wild type and mutant nodules, thus raising questions about the role of jasmonate during nodule development. Finally, quantitative RT-PCR was used to analyse the expression of a series of nodule regulator and marker genes at early symbiotic stages in roots and allowed us to distinguish several early stages of gene expression activation or repression.

Published
2011

15. Large genomic variants reveal unexplored intraspecific diversity in Brassica rapa genomes

Author

Jean-Marc Aury, Olivier Coriton, Loeiz Maillet, Anael Brunet, Virginie Huteau, Julie Ferreira de Carvalho, Maryse Lodé, Cyril Falentin, Franz Boideau, Thomas Chaussepied, Gwenn Trotoux, Gwenaëlle Deniot, Jérôme Morice, Mathieu Rousseau-Gueutin, Caroline Belser, Sébastien Letort, Julien Boutte, and Anne-Marie Chèvre

Subjects
0106 biological sciences, Comparative genomics, Transposable element, 0303 health sciences, Phenotypic trait, Biology, 01 natural sciences, Genome, 03 medical and health sciences, Evolutionary biology, Brassica rapa, Copy-number variation, Genome size, Gene, 030304 developmental biology, 010606 plant biology & botany
Abstract

Traditionally, reference genomes in crop species rely on the assembly of one accession, thus occulting most of intraspecific diversity. However, rearrangements, gene duplications and transposable element content may have a large impact on the genomic structure, which could generate new phenotypic traits. Using two Brassica rapa genomes recently sequenced and assembled using long-read technology and optical mapping, we investigated structural variants and repetitive content between the two accessions and genome size variation among a core collection.We explored the structural consequences of the presence of large repeated sequences in B. rapa ‘Z1’ genome versus the B. rapa ‘Chiifu’ genome, using comparative genomics and cytogenetic approaches. First, we showed that large genomic variants on chromosomes A05, A06, A09 and A10 are due to large insertions and inversions when comparing B. rapa ‘Z1’ and B. rapa ‘Chiifu’ at the origin of important length differences in some chromosomes. For instance, lengths of ‘Z1’ and ‘Chiifu’ A06 chromosomes were estimated in silico to be 55Mb and 29Mb, respectively. To validate these observations, we compared using fluorescent in-situ hybridization (FISH) the two A06 chromosomes present in a F1 hybrid produced by crossing these two varieties. We confirmed a length difference of 17.6% between the A06 chromosomes of ‘Z1’ compared to ‘Chiifu’. Alternatively, using a Copy Number Variation approach, we were able to quantify the presence of a higher number of rDNA and Gypsy elements in ‘Z1’ genome compared to ‘Chiifu’ on different chromosomes including A06. Using flow cytometry, the total genome size of 12 Brassica accessions corresponding to a B. rapa available core collection was estimated and revealed a genome size variation of up to 16% between these accessions as well as some shared inversions.This study revealed the contribution of long-read sequencing of new accessions belonging to different cultigroups of B. rapa and highlighted the potential impact of differential insertion of repeat elements and inversions of large genomic regions in genome size intraspecific variability.

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