Search

Your search keyword '"Sylvain, Foissac"' showing total 49 results
Start Over Author "Sylvain, Foissac"
49 results on '"Sylvain, Foissac"'

1. Enriched atlas of lncRNA and protein-coding genes for the GRCg7b chicken assembly and its functional annotation across 47 tissues

Author

Fabien Degalez, Mathieu Charles, Sylvain Foissac, Haijuan Zhou, Dailu Guan, Lingzhao Fang, Christophe Klopp, Coralie Allain, Laetitia Lagoutte, Frédéric Lecerf, Hervé Acloque, Elisabetta Giuffra, Frédérique Pitel, and Sandrine Lagarrigue

Subjects
Gene atlas, Long non coding RNAs, Chicken, Genome annotation, Tissue specificity, Co-expression, Medicine, Science
Abstract

Abstract Gene atlases for livestock are steadily improving thanks to new genome assemblies and new expression data improving the gene annotation. However, gene content varies across databases due to differences in RNA sequencing data and bioinformatics pipelines, especially for long non-coding RNAs (lncRNAs) which have higher tissue and developmental specificity and are harder to consistently identify compared to protein coding genes (PCGs). As done previously in 2020 for chicken assemblies galgal5 and GRCg6a, we provide a new gene atlas, lncRNA-enriched, for the latest GRCg7b chicken assembly, integrating "NCBI RefSeq", "EMBL-EBI Ensembl/GENCODE" reference annotations and other resources such as FAANG and NONCODE. As a result, the number of PCGs increases from 18,022 (RefSeq) and 17,007 (Ensembl) to 24,102, and that of lncRNAs from 5789 (RefSeq) and 11,944 (Ensembl) to 44,428. Using 1400 public RNA-seq transcriptome representing 47 tissues, we provided expression evidence for 35,257 (79%) lncRNAs and 22,468 (93%) PCGs, supporting the relevance of this atlas. Further characterization including tissue-specificity, sex-differential expression and gene configurations are provided. We also identified conserved miRNA-hosting genes with human counterparts, suggesting common function. The annotated atlas is available at gega.sigenae.org

Published
2024
Full Text
View/download PDF

3. An integrative atlas of chicken long non-coding genes and their annotations across 25 tissues

Author

Frédéric Jehl, Kévin Muret, Maria Bernard, Morgane Boutin, Laetitia Lagoutte, Colette Désert, Patrice Dehais, Diane Esquerré, Hervé Acloque, Elisabetta Giuffra, Sarah Djebali, Sylvain Foissac, Thomas Derrien, Frédérique Pitel, Tatiana Zerjal, Christophe Klopp, and Sandrine Lagarrigue

Subjects
Medicine, Science
Abstract

Abstract Long non-coding RNAs (LNC) regulate numerous biological processes. In contrast to human, the identification of LNC in farm species, like chicken, is still lacunar. We propose a catalogue of 52,075 chicken genes enriched in LNC ( http://www.fragencode.org/ ), built from the Ensembl reference extended using novel LNC modelled here from 364 RNA-seq and LNC from four public databases. The Ensembl reference grew from 4,643 to 30,084 LNC, of which 59% and 41% with expression ≥ 0.5 and ≥ 1 TPM respectively. Characterization of these LNC relatively to the closest protein coding genes (PCG) revealed that 79% of LNC are in intergenic regions, as in other species. Expression analysis across 25 tissues revealed an enrichment of co-expressed LNC:PCG pairs, suggesting co-regulation and/or co-function. As expected LNC were more tissue-specific than PCG (25% vs. 10%). Similarly to human, 16% of chicken LNC hosted one or more miRNA. We highlighted a new chicken LNC, hosting miR155, conserved in human, highly expressed in immune tissues like miR155, and correlated with immunity-related PCG in both species. Among LNC:PCG pairs tissue-specific in the same tissue, we revealed an enrichment of divergent pairs with the PCG coding transcription factors, as for example LHX5, HXD3 and TBX4, in both human and chicken.

Published
2020
Full Text
View/download PDF

4. Major Reorganization of Chromosome Conformation During Muscle Development in Pig

Author

Maria Marti-Marimon, Nathalie Vialaneix, Yvette Lahbib-Mansais, Matthias Zytnicki, Sylvie Camut, David Robelin, Martine Yerle-Bouissou, and Sylvain Foissac

Subjects
Hi-C, chromosome conformation, chromatin structure, telomeres, pig, development, Genetics, QH426-470
Abstract

The spatial organization of the genome in the nucleus plays a crucial role in eukaryotic cell functions, yet little is known about chromatin structure variations during late fetal development in mammals. We performed in situ high-throughput chromosome conformation capture (Hi-C) sequencing of DNA from muscle samples of pig fetuses at two late stages of gestation. Comparative analysis of the resulting Hi-C interaction matrices between both groups showed widespread differences of different types. First, we discovered a complex landscape of stable and group-specific Topologically Associating Domains (TADs). Investigating the nuclear partition of the chromatin into transcriptionally active and inactive compartments, we observed a genome-wide fragmentation of these compartments between 90 and 110 days of gestation. Also, we identified and characterized the distribution of differential cis- and trans-pairwise interactions. In particular, trans-interactions at chromosome extremities revealed a mechanism of telomere clustering further confirmed by 3D Fluorescence in situ Hybridization (FISH). Altogether, we report major variations of the three-dimensional genome conformation during muscle development in pig, involving several levels of chromatin remodeling and structural regulation.

Published
2021
Full Text
View/download PDF

5. Multi-species annotation of transcriptome and chromatin structure in domesticated animals

Author

Sylvain Foissac, Sarah Djebali, Kylie Munyard, Nathalie Vialaneix, Andrea Rau, Kevin Muret, Diane Esquerré, Matthias Zytnicki, Thomas Derrien, Philippe Bardou, Fany Blanc, Cédric Cabau, Elisa Crisci, Sophie Dhorne-Pollet, Françoise Drouet, Thomas Faraut, Ignacio Gonzalez, Adeline Goubil, Sonia Lacroix-Lamandé, Fabrice Laurent, Sylvain Marthey, Maria Marti-Marimon, Raphaelle Momal-Leisenring, Florence Mompart, Pascale Quéré, David Robelin, Magali San Cristobal, Gwenola Tosser-Klopp, Silvia Vincent-Naulleau, Stéphane Fabre, Marie-Hélène Pinard-Van der Laan, Christophe Klopp, Michèle Tixier-Boichard, Hervé Acloque, Sandrine Lagarrigue, and Elisabetta Giuffra

Subjects
Functional annotation, Livestock, RNA-seq, ATAC-seq, Hi-C, Biology (General), QH301-705.5
Abstract

Abstract Background Comparative genomics studies are central in identifying the coding and non-coding elements associated with complex traits, and the functional annotation of genomes is a critical step to decipher the genotype-to-phenotype relationships in livestock animals. As part of the Functional Annotation of Animal Genomes (FAANG) action, the FR-AgENCODE project aimed to create reference functional maps of domesticated animals by profiling the landscape of transcription (RNA-seq), chromatin accessibility (ATAC-seq) and conformation (Hi-C) in species representing ruminants (cattle, goat), monogastrics (pig) and birds (chicken), using three target samples related to metabolism (liver) and immunity (CD4+ and CD8+ T cells). Results RNA-seq assays considerably extended the available catalog of annotated transcripts and identified differentially expressed genes with unknown function, including new syntenic lncRNAs. ATAC-seq highlighted an enrichment for transcription factor binding sites in differentially accessible regions of the chromatin. Comparative analyses revealed a core set of conserved regulatory regions across species. Topologically associating domains (TADs) and epigenetic A/B compartments annotated from Hi-C data were consistent with RNA-seq and ATAC-seq data. Multi-species comparisons showed that conserved TAD boundaries had stronger insulation properties than species-specific ones and that the genomic distribution of orthologous genes in A/B compartments was significantly conserved across species. Conclusions We report the first multi-species and multi-assay genome annotation results obtained by a FAANG project. Beyond the generation of reference annotations and the confirmation of previous findings on model animals, the integrative analysis of data from multiple assays and species sheds a new light on the multi-scale selective pressure shaping genome organization from birds to mammals. Overall, these results emphasize the value of FAANG for research on domesticated animals and reinforces the importance of future meta-analyses of the reference datasets being generated by this community on different species.

Published
2019
Full Text
View/download PDF

6. RNA-Seq Data for Reliable SNP Detection and Genotype Calling: Interest for Coding Variant Characterization and Cis-Regulation Analysis by Allele-Specific Expression in Livestock Species

Author

Frédéric Jehl, Fabien Degalez, Maria Bernard, Frédéric Lecerf, Laetitia Lagoutte, Colette Désert, Manon Coulée, Olivier Bouchez, Sophie Leroux, Behnam Abasht, Michèle Tixier-Boichard, Bertrand Bed’hom, Thierry Burlot, David Gourichon, Philippe Bardou, Hervé Acloque, Sylvain Foissac, Sarah Djebali, Elisabetta Giuffra, Tatiana Zerjal, Frédérique Pitel, Christophe Klopp, and Sandrine Lagarrigue

Subjects
RNA-seq, SNP calling, genotype calling, SNP annotation, allele-specific expression, livestock, Genetics, QH426-470
Abstract

In addition to their common usages to study gene expression, RNA-seq data accumulated over the last 10 years are a yet-unexploited resource of SNPs in numerous individuals from different populations. SNP detection by RNA-seq is particularly interesting for livestock species since whole genome sequencing is expensive and exome sequencing tools are unavailable. These SNPs detected in expressed regions can be used to characterize variants affecting protein functions, and to study cis-regulated genes by analyzing allele-specific expression (ASE) in the tissue of interest. However, gene expression can be highly variable, and filters for SNP detection using the popular GATK toolkit are not yet standardized, making SNP detection and genotype calling by RNA-seq a challenging endeavor. We compared SNP calling results using GATK suggested filters, on two chicken populations for which both RNA-seq and DNA-seq data were available for the same samples of the same tissue. We showed, in expressed regions, a RNA-seq precision of 91% (SNPs detected by RNA-seq and shared by DNA-seq) and we characterized the remaining 9% of SNPs. We then studied the genotype (GT) obtained by RNA-seq and the impact of two factors (GT call-rate and read number per GT) on the concordance of GT with DNA-seq; we proposed thresholds for them leading to a 95% concordance. Applying these thresholds to 767 multi-tissue RNA-seq of 382 birds of 11 chicken populations, we found 9.5 M SNPs in total, of which ∼550,000 SNPs per tissue and population with a reliable GT (call rate ≥ 50%) and among them, ∼340,000 with a MAF ≥ 10%. We showed that such RNA-seq data from one tissue can be used to (i) detect SNPs with a strong predicted impact on proteins, despite their scarcity in each population (16,307 SIFT deleterious missenses and 590 stop-gained), (ii) study, on a large scale, cis-regulations of gene expression, with ∼81% of protein-coding and 68% of long non-coding genes (TPM ≥ 1) that can be analyzed for ASE, and with ∼29% of them that were cis-regulated, and (iii) analyze population genetic using such SNPs located in expressed regions. This work shows that RNA-seq data can be used with good confidence to detect SNPs and associated GT within various populations and used them for different analyses as GTEx studies.

Published
2021
Full Text
View/download PDF

7. Author Correction: An integrative atlas of chicken long non-coding genes and their annotations across 25 tissues

Author

Frédéric Jehl, Kévin Muret, Maria Bernard, Morgane Boutin, Laetitia Lagoutte, Colette Désert, Patrice Dehais, Diane Esquerré, Hervé Acloque, Elisabetta Giuffra, Sarah Djebali, Sylvain Foissac, Thomas Derrien, Frédérique Pitel, Tatiana Zerjal, Christophe Klopp, and Sandrine Lagarrigue

Subjects
Medicine, Science
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2021
Full Text
View/download PDF

8. Cell specification and functional interactions in the pig blastocyst inferred from single cell transcriptomics

Author

Adrien Dufour, Cyril Kurilo, Jan B. Stockl, Denis Laloe, Yoann Bailly, Patrick Manceau, Frederic Martins, Ali G. Turhan, Stephane Ferchaud, Bertrand Pain, Thomas Frohlich, Sylvain Foissac, Jerome Artus, and Herve Acloque

Abstract

The early embryonic development of the pig comprises a long in utero pre- and peri-implantation development, which dramatically differs from mouse and human. During this pro-tracted peri-implantation period, an intimate dialogue between the embryo and the uterus is established through a complex series of paracrine signals. It leads to concomitant drastic changes in the embryonic morphology and uterine receptivity to implantation. From day 7 after fertilization, the spherical blastocyst elongates as ovoid, tubular and filamentous which transforms from a 0.5-1 mm diameter sphere to a 1000 mm long filamentous blastocyst at day 16. At the same time, the inner cell mass moves up to the trophoblast as the Rauber's layer disappears and evolves as an embryonic disc that is directly exposed to molecules present in the uterine fluids. These drastic changes occurring before implantation are driven and coordinated by interactions between embryonic cells and maternal tissues. To better understand the biology of pig embryos before implantation, we generated a large dataset of single-cell RNAseq at different embryonic stages (early and hatched blastocyst, spheroid and ovoid conceptus) and proteomic datasets from corresponding uterine fluids. These data were cleaned, filtered and represent a total of 34,888 cells. We first characterised the embryonic and extra-embryonic cell populations and their evolution, and identified population-specific markers of the three main populations (epiblast, trophectoderm and hypoblast). Our analysis also confirmed known functions and predicted new biological functions associated with these cell populations. We then inferred gene regulatory networks working on modules of gene regulation (regulon) and selected those that were specifically active in each embryonic population. We confirmed the relevance of the identified regulons by a meta-analysis of two other scRNAseq datasets (porcine and human preimplantation embryos). We then linked these regulons to signalling pathways and biological processes. Our results confirm the molecular specificity and functionality of the three main cell populations and identify novel stage-specific subpopulations. In particular, we discovered two previously unknown subpopulations of the trophectoderm, one characterised by the expression of LRP2, which could represent a subpopulation of progenitor cells, and the other, expressing many pro-apoptotic markers, which could correspond to the cells of the Rauber's layer. We also provide new insights into the biology of these populations, their reciprocal functional interactions and the molecular dialogue established with the maternal uterine environment.

Published
2023
Full Text
View/download PDF

9. Apports du séquençage haut-débit sur la connaissance de l'épigénome aviaire

Author

Marjorie MERSCH, Sarah-Anne DAVID, Anaïs VITORINO CARVALHO, Sylvain FOISSAC, Anne COLLIN, Frédérique PITEL, and Vincent COUSTHAM

Subjects
Animal culture, SF1-1100, Aquaculture. Fisheries. Angling, SH1-691
Abstract

Comme toutes les espèces de rente, les oiseaux d'élevage ont été sélectionnés génétiquement afin d’augmenter leurs performances. Cependant, de nombreuses études ont montré que le phénotype d’un individu n’est pas le simple résultat de son patrimoine génétique. En effet, il est également sensible aux variations de l’environnement (température, nutrition…) qui peuvent notamment induire des altérations de marques épigénétiques aboutissant à des changements durables des programmes d’expression de gènes. Il est donc essentiel de comprendre comment les épigénomes sont régulés afin d’envisager de futurs leviers ou marqueurs d’adaptation des animaux. Aujourd’hui, le séquençage à haut-débit est devenu relativement abordable et les outils bio-informatiques matures pour envisager l’étude des marques épigénétiques à l'échelle du génome. Chez les oiseaux, un nombre croissant d'études utilisent ces technologies à haut-débit pour explorer les mécanismes épigénétiques impliqués dans des processus tels que l'immunité ou l'adaptation à l’environnement. Dans cette synthèse, nous décrivons en quoi ces technologies ont contribué à enrichir les connaissances sur l'épigénome aviaire et plus particulièrement celui du poulet, en nous focalisant sur les deux types de modifications épigénétiques les plus étudiées, la méthylation de l'ADN et les modifications post-traductionnelles des histones. Nous présentons également les concepts nécessaires à la conception et la réalisation des analyses haut-débit des épigénomes aviaires. En plus des connaissances fondamentales fortement attendues par la communauté scientifique, une meilleure compréhension des mécanismes épigénétiques à l’origine de la régulation de l’expression génique en réponse aux modifications environnementales chez l’oiseau pourrait contribuer au développement d’une production avicole durable.

Published
2018
Full Text
View/download PDF

10. Identification of a t(3;4)(p1.3;q1.5) translocation breakpoint in pigs using somatic cell hybrid mapping and high-resolution mate-pair sequencing.

Author

Katia Fève, Sylvain Foissac, Alain Pinton, Florence Mompart, Diane Esquerré, Thomas Faraut, Martine Yerle, and Juliette Riquet

Subjects
Medicine, Science
Abstract

Reciprocal translocations are the most frequently occurring constitutional structural rearrangements in mammalian genomes. In phenotypically normal pigs, an incidence of 1/200 is estimated for such rearrangements. Even if constitutional translocations do not necessarily induce defects and diseases, they are responsible for significant economic losses in domestic animals due to reproduction failures. Over the last 30 years, advances in molecular and cytogenetic technologies have led to major improvements in the resolution of the characterization of translocation events. Characterization of translocation breakpoints helps to decipher the mechanisms that lead to such rearrangements and the functions of the genes that are involved in the translocation. Here, we describe the fine characterization of a reciprocal translocation t(3;4) (p1.3;q1.5) detected in a pig line. The breakpoint was identified at the base-pair level using a positional cloning and chromosome walking strategy in somatic cell hybrids that were generated from an animal that carries this translocation. We show that this translocation occurs within the ADAMTSL4 gene and results in a loss of expression in homozygous carriers. In addition, by taking this translocation as a model, we used a whole-genome next-generation mate-pair sequencing approach on pooled individuals to evaluate this strategy for high-throughput screening of structural rearrangements.

Published
2017
Full Text
View/download PDF

12. Genome-Wide Epigenetic Studies in Chicken: A Review

Author

Sarah-Anne David, Marjorie Mersch, Sylvain Foissac, Anne Collin, Frédérique Pitel, and Vincent Coustham

Subjects
high-throughput sequencing, epigenomics, poultry, bird, chicken, DNA methylation, histone post-translational modifications, Genetics, QH426-470, Biotechnology, TP248.13-248.65
Abstract

Over the years, farmed birds have been selected on various performance traits mainly through genetic selection. However, many studies have shown that genetics may not be the sole contributor to phenotypic plasticity. Gene expression programs can be influenced by environmentally induced epigenetic changes that may alter the phenotypes of the developing animals. Recently, high-throughput sequencing techniques became sufficiently affordable thanks to technological advances to study whole epigenetic landscapes in model plants and animals. In birds, a growing number of studies recently took advantage of these techniques to gain insights into the epigenetic mechanisms of gene regulation in processes such as immunity or environmental adaptation. Here, we review the current gain of knowledge on the chicken epigenome made possible by recent advances in high-throughput sequencing techniques by focusing on the two most studied epigenetic modifications, DNA methylation and histone post-translational modifications. We discuss and provide insights about designing and performing analyses to further explore avian epigenomes. A better understanding of the molecular mechanisms underlying the epigenetic regulation of gene expression in relation to bird phenotypes may provide new knowledge and markers that should undoubtedly contribute to a sustainable poultry production.

Published
2017
Full Text
View/download PDF

14. Evidence for transcript networks composed of chimeric RNAs in human cells.

Author

Sarah Djebali, Julien Lagarde, Philipp Kapranov, Vincent Lacroix, Christelle Borel, Jonathan M Mudge, Cédric Howald, Sylvain Foissac, Catherine Ucla, Jacqueline Chrast, Paolo Ribeca, David Martin, Ryan R Murray, Xinping Yang, Lila Ghamsari, Chenwei Lin, Ian Bell, Erica Dumais, Jorg Drenkow, Michael L Tress, Josep Lluís Gelpí, Modesto Orozco, Alfonso Valencia, Nynke L van Berkum, Bryan R Lajoie, Marc Vidal, John Stamatoyannopoulos, Philippe Batut, Alex Dobin, Jennifer Harrow, Tim Hubbard, Job Dekker, Adam Frankish, Kourosh Salehi-Ashtiani, Alexandre Reymond, Stylianos E Antonarakis, Roderic Guigó, and Thomas R Gingeras

Subjects
Medicine, Science
Abstract

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.

Published
2012
Full Text
View/download PDF

16. Molecular characterization of transgenerational epigenetic phenomena after genistein exposure in quail

Author

Sophie Leroux, Marie Jérémie, David Gourichon, Vincent Coustham, Tatiana Zerjal, Mireille Morisson, Olivier Bouchez, Sylvain Foissac, Frédérique Pitel, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Pôle d'Expérimentation Avicole de Tours (UE PEAT), Institut National de la Recherche Agronomique (INRA), Biologie des Oiseaux et Aviculture (BOA), Institut National de la Recherche Agronomique (INRA)-Université de Tours (UT), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Génome et Transcriptome - Plateforme Génomique (GeT-PlaGe), Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National de la Recherche Agronomique (INRA)-Université de Tours, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), and Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], genetic, genome, epigenetic
Abstract

International audience; Knowledge about transgenerational inheritance in birds is still poor. In a pilot study, we demonstrated that some effects induced by environmental stressors were transmitted over three generations, in Japanese quail (Coturnix japonica) [1]. Two "epilines" of quail (Epi + and Epi-) were produced using fertilized eggs from the same founder population, a quail line from a divergent selection on a behavioral trait, social motivation. A methylation modifier (Genistein) was injected (Epi +) or not (Epi-) before incubation. After 3 parallel generations of intra-line reproduction, without any other injection, several traits were affected by the ancestors treatment, including both reproduction (e.g. age at first egg delayed for 8 days) and behavioral traits. The mating strategy and the number of founders used allowed us to minimize the genetic variation between lines, which could have explained the phenotypic differences observed, and to test the existence of a transgenerational transmission of the effects of the environment. This study aims to complement the previous phenotypic analysis with molecular analyzes. The objective is to test the hypothesis of an epigenetic cause of the observed phenotypic variations, by characterizing the genomic regions with significant methylation differences between the animals derived from injected ancestors and the animals from control ancestors. A complementary analysis of the polymorphisms observed between the two epilines should make it possible to discern the epigenetic variability due to the treatment of the ancestors from that due to the possible genetic differences between the two epilines, these genetic variants being possibly linked to the initial treatment [2] or derived from genetic drift. The DNA was extracted from the blood of 24 G3 animals (6 males and 6 females per epiline) and analyzed by Whole Genome Bisulfite Sequencing (WGBS). An average of about 77 million reads per individual were obtained, corresponding to an average depth of 12X per position, per individual. Analyzes are underway with a pipeline based on standard tools (Bismark, methylKit, DSS). In parallel, the DNA of the same individuals was extracted from the gonads, in order to perform global methylation studies using the LUMA technique (LUminometric Methylation Assay). These analyzes did not show any difference in methylation levels between the two epilines but it showed a difference of the methylation rate between males and females.

Published
2019

17. Multi-level conservation of chromosome conformation across livestock species reveals evolutionary links between genome structure and function

Author

Sylvain Foissac, Sarah Djebali Quelen, Nathalie Vialaneix, Matthias Zytnicki, Andrea Rau, Sandrine Lagarrigue, Hervé Acloque, Elisabetta Giuffra, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Génome et Transcriptome - Plateforme Génomique (GeT-PlaGe), Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Projet GA FrAgencode, Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National de la Recherche Agronomique (INRA)-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), and ProdInra, Migration

Subjects
[SDV] Life Sciences [q-bio], [SDV.GEN]Life Sciences [q-bio]/Genetics, [SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics, [SDV]Life Sciences [q-bio], [INFO]Computer Science [cs], [SDV.GEN] Life Sciences [q-bio]/Genetics, [SDV.GEN.GA] Life Sciences [q-bio]/Genetics/Animal genetics, [MATH] Mathematics [math], [INFO] Computer Science [cs], [MATH]Mathematics [math]
Abstract

International audience; The spatial conformation of the chromatin in the nucleus of animal cells is highly organized at several levels. Little is known, however, about its evolution, mainly because of the limited number of species in which chromosome conformation experiments have been performed.In the context of the FAANG pilot project FR-AgENCODE, we realized Hi-C experiments on tissue samples from three livestock species (pig, goat and chicken livers) and integrated the resulting data with those from other assays on the same samples (RNA-seq and ATAC-seq). Within each species, general features of the genome organization -like Topologycally Associating Domains (TADs) and genome A/B compartments- could be identified. They display functional properties in line with previous reports on other model organisms like human and mouse. By comparing these structural features across species we further investigated the connections between genome conformation and function. In particular, we found a significant conservation of the gene distribution among active and inactive compartments of the chromatin throughout evolution. In addition, comparing 3D interaction profiles of orthologous regions showed that conserved TAD boundaries have stronger insulation properties than recent ones, supporting a specific selective pressure on structural components of the genome. Accordingly, various blocks of synteny contain conserved elements from several levels of organization that contribute to the gene regulatory network: sites of chromatin accessibility, orthologous genes, TADs and A/B compartments. Altogether, these results shed new light on the conservation of genome conformation from birds to mammals and illustrate the various degrees of connection between genome structure and function.

Published
2019

18. 32 Functional annotation of livestock genomes: chromatin structure and regulation of gene expression

Author

Sarah Djebali, Andrea Rau, Elisabetta Giuffra, Kylie Munyard, Sandrine Lagarrigue, Sylvain Foissac, Nathalie Vialaneix, and Hervé Acloque

Subjects
2. Zero hunger, Regulation of gene expression, 0303 health sciences, business.industry, 0402 animal and dairy science, 04 agricultural and veterinary sciences, General Medicine, Computational biology, Biology, 040201 dairy & animal science, Genome, Chromatin, 03 medical and health sciences, Functional annotation, Genetics, Oral Presentations, Animal Science and Zoology, Livestock, business, 030304 developmental biology, Food Science
Abstract

Improving the functional annotation of animal genomes is a key challenge in bridging the gap between genotype and phenotype, thus enabling predictive biology. Regarding livestock production, major outcomes are expected from a better understanding of the genetic architecture underlying quantitative traits. As part of the Functional Annotation of ANimal Genomes action (FAANG: www.faang.org), the FR-AgENCODE project generated omics data to improve the reference annotation of the cattle, pig, goat and chicken genome. High-throughput molecular assays have been performed on tissues/cells relevant to immune and metabolic traits. From two males and two females per species (pig, cattle, goat, chicken), strand-oriented RNA-seq gene expression and ATAC-seq chromatin accessibility assays were performed on liver and two PBMC-sorted T-cell types (CD4+ and CD8+). Chromosome Conformation Capture (in situ Hi-C) was also carried out on liver samples. About 4,000 samples have been collected at the INRA biorepository and registered at the EBI BioSamples registry. More than 80% of the planned experiments could be completed, generating ~11.5 billions of sequencing reads over the 3 assays. While most (50–80%) RNA-seq reads mapped to annotated exons, thousands of novel transcripts were found, with ~60K mRNAs and ~22K lncRNAs in cattle. Differentially expressed genes between cell types were enriched for immunity- or metabolism-related terms, and differentially accessible chromatin regions were identified as potential regulatory sites. Interestingly, correlations between gene expression and promoter accessibility across samples were skewed towards both positive and negative values, suggesting distinct regulatory mechanisms of gene expression. These patterns have been further investigated using human data from the Epigenome Roadmap Mapping Consortium. Altogether, this study illustrates the interest of a coordinated effort to tackle the genome-to-phenome challenge and provides a useful resource to the community. Availability: www.fragencode.org.

Published
2019

19. An atlas of chicken long non-coding RNAs gathering multiple sources : gene models and expression across more than twenty tissues

Author

Frédéric Jehl, Kévin Muret, Maria Bernard, Diane Esquerré, Hervé Acloque, Elisabetta Giuffra, Sarah Djebali, Sylvain Foissac, Thomas Derrien, Tatiana Zerjal, Christophe Klopp, Sandrine Lagarrigue, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-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), Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique (CNRS), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), European Project: 633531,H2020,H2020-SFS-2014-2,Feed-a-Gene(2015), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), and Université de Toulouse (UT)-Université de Toulouse (UT)

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], Autre (Sciences du Vivant)
Abstract

International audience; Long non-coding RNAs (lncRNAs) appear as key regulators of gene expression through numerous mechanisms. Yet, particularly in domesticated species like chicken, their annotation is incomplete and their expression in different tissues poorly characterized. Here, we used data from 4 public databases (Ensembl, NONCODE, NCBI, ALDB), a recent lncRNA catalogue, and genes models from 364 RNA-seq samples from our lab to generate an extensive annotation of the chicken genome aggregating most of the currently known lncRNAs, plus robust models of newly discovered lncRNA from our dataset. Our extended lncRNAs annotation comprises 30084 lncRNA loci versus 4640 in the Ensembl reference. These lncRNAs follow the same trends as those in the reference for their genomic localization, structure and expression. To further characterize these lncRNAs, we studied their expression in over 20 chicken tissues with minimum 6 biological replicates. This allowed us to explore expression variability of both lncRNAs and protein-coding genes (mRNAs) across tissues, and across replicates in each tissue. Across these chicken tissues, we found interesting differences in the tissue-specificity patterns between lncRNAs and mRNAs. We characterized the expressions of both types of genes in relation with (i) their tissue-specificity and/or (ii) their genomic localization relative to each other (convergent, divergent, antisense, distant or proximal) in order to highlight some lncRNA–mRNA couples with a role in the functions or the maintenance of a given organ in chicken. Finally, we started a conservation study of interesting lncRNA–mRNA couples across species. Project funded by ANR-13-ADAP and H2020-Feed-a-Gene projects.

Published
2019

20. FR-Agencode: An Update

Author

Giuffra, E., Sarah Djebali, Andrea Rau, Sandrine Lagarrigue, Acloque, H., Sylvain Foissac, Giuffra, Elisabetta, Génétique Animale et Biologie Intégrative (GABI), Université Paris-Saclay-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, and 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)

Subjects
[SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

21. Chromatin accessibility conservation across four livestock species

Author

Sarah Djebali Quelen, Sylvain Foissac, Nathalie Vialaneix, Kylie Munyard, Andrea Rau, Thomas Faraut, Sandrine Lagarrigue, Hervé Acloque, Elisabetta Giuffra, ProdInra, Migration, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), Curtin University [Perth], Planning and Transport Research Centre (PATREC), Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-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), and Projet GA FrAgencode

Subjects
[SDV.GEN]Life Sciences [q-bio]/Genetics, Bioinformatics, [SDV]Life Sciences [q-bio], Comparative genomics, ATAC-seq, [SDV.GEN] Life Sciences [q-bio]/Genetics, [SDV.GEN.GA] Life Sciences [q-bio]/Genetics/Animal genetics, [MATH] Mathematics [math], [INFO] Computer Science [cs], [SDV] Life Sciences [q-bio], [SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics, FAANG, Vertebrate livestock species, [INFO]Computer Science [cs], [MATH]Mathematics [math]
Abstract

International audience; Within the FAANG consortium, the FR-AgENCODE pilot project has generated transcriptome (RNA-seq) and chromatin accessibility (ATAC-seq) data in the liver and immune cells of 2 males and 2 females of 4 vertebrate species (cattle, goat, chicken and pig), in addition to Hi-C data (see abstract #79896 by S. Foissac et al.). The first single-assay and integrative analyses performed on these data were mostly done on each species separately. Although these analyses provided several interesting insights (https://www.biorxiv.org/content/10.1101/316091v1), they did not take full advantage of our data richness, namely the availability of the same kind of functional data on species belonging to different parts of the phylogenetic tree. Here we have investigated the relationship between chromatin accessibility conservation across vertebrates and functionality. We first defined orthologous accessible regions by projecting accessible regions from our four species to the human genome. Two accessible regions are called orthologous if their projection on the human genome overlap. In doing so we identified 19,982, 7,877 and 1,083 regions shared between 2, 3 and 4 species, respectively. Our main results are: The level of accessibility of a region, measured by ATAC-seq, increases with the number of shared accessibility-orthologues Regions with more shared accessibility-orthologues are more likely to be close to gene promoters The functional conservation of an accessible region, measured by the number of species exhibiting a tissue-differential accessibility, is correlated to sequence conservation, measured by phastCons. This confirms and reinforces previous findings in human and mouse A hierarchical clustering of ATAC-seq samples based on the correlation between the accessibility of the 1083 orthologous regions shared between 4 species shows that clustering occurs first by species and then by tissue. This is different from what we found for RNA-seq (i.e. all liver samples clustering together). Based on these findings, we are currently working to define more precisely the functional regulatory relationships in liver and immune cells in light of their conservation during evolution. We anticipate that the comparison of these relationships to known QTLs should provide interesting results.

Published
2019

22. Transcriptome and chromatin structure annotation of liver, CD4+ and CD8+ T cells from four livestock species

Author

Maria Marti-Marimon, der Laan Mp, Elisa Crisci, Matthias Zytnicki, Hervé Acloque, Kylie Munyard, Florence Mompart, Thomas Faraut, Kévin Muret, Thomas Derrien, Nathalie Vialaneix, Magali San Cristobal, Gwenola Tosser-Klopp, Stéphane Fabre, Cédric Cabau, Raphaelle Momal-Leisenring, Sylvain Marthey, David Robelin, Michèle Tixier-Boichard, Sylvain Foissac, Sonia Lacroix-Lamandé, Ignacio González, Elisabetta Giuffra, Sarah Djebali, Françoise Drouet, Fabrice Laurent, Pascale Quéré, Fany Blanc, Philippe Bardou, Christophe Klopp, Sandrine Lagarrigue, Sophie Dhorne-Pollet, Andrea Rau, Silvia Vincent-Naulleau, Diane Esquerre, and Adeline Goubil

Subjects
2. Zero hunger, 0303 health sciences, Computational biology, Genome project, Biology, Genome, Chromatin, DNA binding site, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Gene, 030217 neurology & neurosurgery, 030304 developmental biology, Synteny, Genomic organization
Abstract

BackgroundFunctional annotation of livestock genomes is a critical step to decipher the genotype-to-phenotype relationship underlying complex traits. As part of the Functional Annotation of Animal Genomes (FAANG) action, the FR-AgENCODE project (http://www.fragencode.org) aimed to profile the landscape of transcription (RNA-seq), chromatin accessibility (ATAC-seq) and conformation (Hi-C) in four livestock species representing ruminants (cattle, goat), monogastrics (pig) and birds (chicken), using three target samples related to metabolism (liver) and immunity (CD4+ and CD8+ T cells).ResultsRNA-seq assays considerably extended the available catalog of annotated transcripts and identified differentially expressed genes with unknown function, including new syntenic lncRNAs. ATAC-seq highlighted an enrichment for transcription factor binding sites in differentially accessible regions of the chromatin. Comparative analyses revealed a core set of conserved regulatory regions across species. Topologically Associating Domains (TADs) and epigenetic A/B compartments annotated from Hi-C data were consistent with RNA-seq and ATAC-seq data. Multi-species comparisons showed that conserved TAD boundaries had stronger insulation properties than species-specific ones and that the genomic distribution of orthologous genes in A/B compartments was significantly conserved across species.ConclusionsWe report the first multi-species and multi-assay genome annotation results obtained by a FAANG project. Beyond the generation of reference annotations and the confirmation of previous findings on model animals, the integrative analysis of data from multiple assays and species sheds a new light on the multi-scale selective pressure shaping genome organization from birds to mammals. Overall, these results emphasize the value of FAANG for research on domesticated animals and reinforces the importance of future meta-analyses of the reference datasets being generated by this community on different species.

Published
2018
Full Text
View/download PDF

24. Genome-Wide Epigenetic Studies in Chicken: A Review

Author

Anne Collin, Vincent Coustham, Sarah-Anne David, Marjorie Mersch, Sylvain Foissac, Frédérique Pitel, Unité de Recherches Avicoles (URA), Institut National de la Recherche Agronomique (INRA), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, ANR 'ChickStress' (ANR-13-ADAP-0014), Recherches Avicoles (SRA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]

Subjects
0301 basic medicine, bird, Health, Toxicology and Mutagenesis, [SDV]Life Sciences [q-bio], chicken, lcsh:Medicine, Biology, Biochemistry, Genetics and Molecular Biology (miscellaneous), Biochemistry, Genome, epigenomic, DNA sequencing, 03 medical and health sciences, 0302 clinical medicine, Genetics, histone post-translational modification, Epigenetics, lcsh:QH301-705.5, Epigenomics, 2. Zero hunger, Regulation of gene expression, Phenotypic plasticity, DNA methylation, poultry, lcsh:R, high-throughput sequencing, Epigenome, 030104 developmental biology, lcsh:Biology (General), Evolutionary biology, epigenomics, histone post-translational modifications, 030217 neurology & neurosurgery
Abstract

Notice à reprendre pas de Clé UT en Mai 2018; Over the years, farmed birds have been selected on various performance traits mainly through genetic selection. However, many studies have shown that genetics may not be the sole contributor to phenotypic plasticity. Gene expression programs can be influenced by environmentally induced epigenetic changes that may alter the phenotypes of the developing animals. Recently, high-throughput sequencing techniques became sufficiently affordable thanks to technological advances to study whole epigenetic landscapes in model plants and animals. In birds,a growing number of studies recently took advantage of these techniques to gain insights into the epigenetic mechanisms of gene regulation in processes such as immunity or environmental adaptation. Here, we review the current gain of knowledge on the chicken epigenome made possible by recent advances in high-throughput sequencing techniques by focusing on the two most studied epigenetic modifications, DNA methylation and histone post-translational modifications. We discuss and provide insights about designing and performing analyses to further explore avian epigenomes. A better understanding of the molecular mechanisms underlying the epigenetic regulation of gene expression in relation to bird phenotypes may provide new knowledge and markers that shouldundoubtedly contribute to a sustainable poultry production.

Published
2017
Full Text
View/download PDF

25. Long noncoding RNA repertoire in chicken liver and adipose tissue

Author

Sylvain Foissac, Morgane Boutin, Valentin Wucher, Frédéric Jehl, Colette Désert, Elisabetta Giuffra, Diane Esquerre, Frédéric Lecerf, Sandrine Lagarrigue, Christophe Klopp, Kévin Muret, Thomas Derrien, Sarah Djebali, Fabrice Legeai, Hervé Acloque, BMC, BMC, Adapting the feed, the animal and the feeding techniques to improve the efficiency and sustainability of monogastric livestock production systems - Feed-a-Gene - - H20202015-03-01 - 2020-02-29 - 633531 - VALID, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Système d'Information des GENomes des Animaux d'Elevage (SIGENAE), Institut National de la Recherche Agronomique (INRA), Institut de Génétique et Développement de Rennes (IGDR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, IN-1275570, INRA, European Project: 633531,H2020,H2020-SFS-2014-2,Feed-a-Gene(2015), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT), 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 la Recherche Agronomique (INRA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Institut National de la Recherche Agronomique (INRA)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut National de la Recherche Agronomique (INRA)-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), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Recherche Agronomique (INRA), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), and AgroParisTech-Institut National de la Recherche Agronomique (INRA)

Subjects
0301 basic medicine, Genotype, [SDV]Life Sciences [q-bio], Quantitative Trait Loci, poulet, génomique fonctionnelle, tissu adipeux, Adipose tissue, Biology, Genome, Evolution, Molecular, Transcriptome, Open Reading Frames, analyse de génome, 03 medical and health sciences, Genetics, Animals, Humans, RNA, Antisense, Genetics(clinical), RNA, Messenger, Gene, Conserved Sequence, Ecology, Evolution, Behavior and Systematics, Synteny, 030102 biochemistry & molecular biology, Gene Expression Profiling, General Medicine, Lipid Metabolism, foie, Phenotype, Long non-coding RNA, [SDV] Life Sciences [q-bio], Gene expression profiling, 030104 developmental biology, Adipose Tissue, Gene Expression Regulation, Liver, Organ Specificity, RNA, Long Noncoding, Animal Science and Zoology, Chickens, annotation fonctionnelle, Research Article
Abstract

Background Improving functional annotation of the chicken genome is a key challenge in bridging the gap between genotype and phenotype. Among all transcribed regions, long noncoding RNAs (lncRNAs) are a major component of the transcriptome and its regulation, and whole-transcriptome sequencing (RNA-Seq) has greatly improved their identification and characterization. We performed an extensive profiling of the lncRNA transcriptome in the chicken liver and adipose tissue by RNA-Seq. We focused on these two tissues because of their importance in various economical traits for which energy storage and mobilization play key roles and also because of their high cell homogeneity. To predict lncRNAs, we used a recently developed tool called FEELnc, which also classifies them with respect to their distance and strand orientation to the closest protein-coding genes. Moreover, to confidently identify the genes/transcripts expressed in each tissue (a complex task for weakly expressed molecules such as lncRNAs), we probed a particularly large number of biological replicates (16 per tissue) compared to common multi-tissue studies with a larger set of tissues but less sampling. Results We predicted 2193 lncRNA genes, among which 1670 were robustly expressed across replicates in the liver and/or adipose tissue and which were classified into 1493 intergenic and 177 intragenic lncRNAs located between and within protein-coding genes, respectively. We observed similar structural features between chickens and mammals, with strong synteny conservation but without sequence conservation. As previously reported, we confirm that lncRNAs have a lower and more tissue-specific expression than mRNAs. Finally, we showed that adjacent lncRNA-mRNA genes in divergent orientation have a higher co-expression level when separated by less than 1 kb compared to more distant divergent pairs. Among these, we highlighted for the first time a novel lncRNA candidate involved in lipid metabolism, lnc_DHCR24, which is highly correlated with the DHCR24 gene that encodes a key enzyme of cholesterol biosynthesis. Conclusions We provide a comprehensive lncRNA repertoire in the chicken liver and adipose tissue, which shows interesting patterns of co-expression between mRNAs and lncRNAs. It contributes to improving the structural and functional annotation of the chicken genome and provides a basis for further studies on energy storage and mobilization traits in the chicken. Electronic supplementary material The online version of this article (doi:10.1186/s12711-016-0275-0) contains supplementary material, which is available to authorized users.

Published
2017
Full Text
View/download PDF

26. Profiling the landscape of transcription and chromatin conformation reveals regulatory mechanisms involved in immune and metabolic functions

Author

Sylvain Foissac, Sarah Djebali Quelen, Hervé Acloque, Marie-Helene Pinard - van der Laan, Sandrine Lagarrigue, Elisabetta Giuffra, ProdInra, Archive Ouverte, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), FAANG pilot project 'FR-AgENCODE', AgroParisTech-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-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 la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]

Subjects
pig, [SDV]Life Sciences [q-bio], chicken, génome, goat, animal de rente, T cells, functional annotation, liver, cash cattle, [SDV] Life Sciences [q-bio], cattle, chromatin, annotation fonctionnelle, chromatine
Abstract

Functional annotation of livestock genomes is a critical and obvious next step to derive maximum benefit for agriculture, animal science, animal welfare and human health. The aim of the Fr-AgENCODE project is to generate multi-species functional genome annotations by applying high-throughput molecular assays on three target tissues/cells relevant to the study of immune and metabolic traits. Here we present on-going results on gene expression and chromatin conformation in hepatocytes and CD3+CD4+ (“CD4”) and CD3+CD8+ (“CD8”) T cells with a focus on the pig species (two male and two female Large White adult pigs). These samples were processed by strand-oriented RNA-seq and ATAC-seq experiments. Principal Component Analyses on log-transformed TMM-normalized read counts in genes (from RNA-seq) and regions of chromatin accessibility (from ATAC-seq) consistently highlighted the variability between liver and the T cells, and to a lesser extent within T cells (CD4 vs. CD8), as well as between the male and female samples. Comparative analyses identified differentially expressed genes between cell types as well as potential regulatory sites from differentially accessible chromatin regions. As expected, ontology annotations of differentially expressed genes were enriched for either immunity- or metabolism-related terms. Interestingly, correlations between gene expression and promoter accessibility across samples were enriched for both extreme positive and negative values, which suggests that ATAC-seq can efficiently capture distinct regulatory mechanisms of gene expression. Candidate enhancers and repressors were identified by comparing ATAC-seq regions with predicted binding sites of 500+ transcription factors. By integrating these results with those from Hi-C chromosome conformation capture on the liver samples, we investigated differences between “active” and “repressed” topological domains in terms of functional features, including gene density and general chromatin accessibility. Altogether, these results lead to a better understanding of the molecular mechanisms involved in pig immune and metabolic functions, and illustrate a useful contribution to the functional annotation effort of the FAANG initiative.

Published
2017

27. Bioinformatics Pipeline for Transcriptome Sequencing Analysis

Author

Thomas Derrien, Sylvain Foissac, Sarah Djebali, Valentin Wucher, Christophe Hitte, Erwan Corre, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut de Génétique et Développement de Rennes (IGDR), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT), and Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )

Subjects
0301 basic medicine, reconstruction, [SDV]Life Sciences [q-bio], Population, RNA-Seq, Biology, transcriptome sequencing, Bioinformatics, DNA sequencing, Transcriptome, 03 medical and health sciences, expression, read, [INFO]Computer Science [cs], protocol, education, Illumina dye sequencing, gencode, ComputingMilieux_MISCELLANEOUS, education.field_of_study, [SDV.GEN]Life Sciences [q-bio]/Genetics, rna-seq data, Gene expression profiling, [SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics, 030104 developmental biology, rna-seq, Reference genome, De facto standard, bioinformatic workflow
Abstract

International audience; The development of High Throughput Sequencing (HTS) for RNA profiling (RNA-seq) has shed light on the diversity of transcriptomes. While RNA-seq is becoming a de facto standard for monitoring the population of expressed transcripts in a given condition at a specific time, processing the huge amount of data it generates requires dedicated bioinformatics programs. Here, we describe a standard bioinformatics protocol using state-of-the-art tools, the STAR mapper to align reads onto a reference genome, Cufflinks to reconstruct the transcriptome, and RSEM to quantify expression levels of genes and transcripts. We present the workflow using human transcriptome sequencing data from two biological replicates of the K562 cell line produced as part of the ENCODE3 project.

Published
2017
Full Text
View/download PDF

30. Bioinformatics Pipeline for Transcriptome Sequencing Analysis

Author

Sarah, Djebali, Valentin, Wucher, Sylvain, Foissac, Christophe, Hitte, Erwan, Corre, and Thomas, Derrien

Subjects
Sequence Analysis, RNA, Gene Expression Profiling, Computational Biology, High-Throughput Nucleotide Sequencing, Humans, K562 Cells, Workflow
Abstract

The development of High Throughput Sequencing (HTS) for RNA profiling (RNA-seq) has shed light on the diversity of transcriptomes. While RNA-seq is becoming a de facto standard for monitoring the population of expressed transcripts in a given condition at a specific time, processing the huge amount of data it generates requires dedicated bioinformatics programs. Here, we describe a standard bioinformatics protocol using state-of-the-art tools, the STAR mapper to align reads onto a reference genome, Cufflinks to reconstruct the transcriptome, and RSEM to quantify expression levels of genes and transcripts. We present the workflow using human transcriptome sequencing data from two biological replicates of the K562 cell line produced as part of the ENCODE3 project.

Published
2016

31. Comprehensive Polyadenylation Site Maps in Yeast and Human Reveal Pervasive Alternative Polyadenylation

Author

Sang Woo Kim, Fatih Ozsolak, Bino John, A. Paula Monaghan, Elane Fishilevich, Patrice M. Milos, Philipp Kapranov, Sylvain Foissac, Helicos BioSci Corp, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Integromics, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées

Subjects
Polyadenylation, Sequence analysis, [SDV]Life Sciences [q-bio], Cleavage and polyadenylation specificity factor, Computational biology, Saccharomyces cerevisiae, Biology, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, 0302 clinical medicine, Transcription (biology), Humans, 030304 developmental biology, Genetics, 0303 health sciences, Sequence Analysis, RNA, Biochemistry, Genetics and Molecular Biology(all), Gene Expression Profiling, human cell, Alternative splicing, RNA, Post-transcriptional modification, Gene expression profiling, polymerase, Liver, gene expression, Poly A, 030217 neurology & neurosurgery
Abstract

SummaryThe emerging discoveries on the link between polyadenylation and disease states underline the need to fully characterize genome-wide polyadenylation states. Here, we report comprehensive maps of global polyadenylation events in human and yeast generated using refinements to the Direct RNA Sequencing technology. This direct approach provides a quantitative view of genome-wide polyadenylation states in a strand-specific manner and requires only attomole RNA quantities. The polyadenylation profiles revealed an abundance of unannotated polyadenylation sites, alternative polyadenylation patterns, and regulatory element-associated poly(A)+ RNAs. We observed differences in sequence composition surrounding canonical and noncanonical human polyadenylation sites, suggesting novel noncoding RNA-specific polyadenylation mechanisms in humans. Furthermore, we observed the correlation level between sense and antisense transcripts to depend on gene expression levels, supporting the view that overlapping transcription from opposite strands may play a regulatory role. Our data provide a comprehensive view of the polyadenylation state and overlapping transcription.

Published
2010
Full Text
View/download PDF

32. Genome Annotation in Plants and Fungi: EuGene as a Model Platform

Author

Pierre Rouzé, Joelle Amselem, Stephane Rombauts, Jérôme Gouzy, Sylvain Foissac, Catherine Mathé, Yves Van de Peer, Thomas Schiex, Lieven Sterck, Centro de Regulación Genómica (CRG), Universitat Pompeu Fabra [Barcelona] (UPF), Centre National de la Recherche Scientifique (CNRS), 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, Department of plant systems biology, Flanders Institute for Biotechnology, Department of Molecular Genetics, Universiteit Gent = Ghent University [Belgium] (UGENT), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, BIOlogie et GEstion des Risques en agriculture (BIOGER), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Unité associée au Département Biologie et Amélioration des Plantes (Associée BAP), Institut National de la Recherche Agronomique (INRA), Laboratoire Associé de l'INRA, and Unité de Biométrie et Intelligence Artificielle (UBIA)

Subjects
0106 biological sciences, GENE FINDING, Gene prediction, Computational biology, Vertebrate and Genome Annotation Project, Biology, GENOME ANNOTATION, 01 natural sciences, Biochemistry, Genome, 03 medical and health sciences, Annotation, Genetics, [INFO]Computer Science [cs], PLANT, [MATH]Mathematics [math], Molecular Biology, 030304 developmental biology, Whole genome sequencing, 0303 health sciences, Genome project, Computational Mathematics, FUNGUS, Proteome, Identification (biology), 010606 plant biology & botany
Abstract

International audience; In this era of whole genome sequencing, reliable genome annotations (identification of functional regions) are the cornerstones for many subsequent analyses. Not only is careful annotation important for studying the gene and gene family content of a genome and its host, but also for wide-scale transcriptome and proteome analyses attempting to describe a certain biological process or to get a global picture of a cell's behavior. Although the number of sequenced genomes is increasing thanks to the application of new technologies, genome-wide analyses will critically depend on the quality of the genome annotations. However, the annotation process is more complicated in the plant field than in the animal field because of the limited funding that leads to much fewer experimental data and less annotation expertise. This situation calls for highly automated annotation platforms that can make the best use of all available data, experimental or not. We discuss how the gene prediction (the process of predicting protein gene structures in genomic sequences) research field increasingly shifts from methods that typically exploited one or two types of data to more integrative approaches that simultaneously deal with various experimental, statistical, or other in silico evidence. We illustrate the importance of integrative approaches for producing high-quality automatic annotations of genomes of plants and algae as well as of fungi that live in close association with plants using the platform EuGène as an example.

Published
2008
Full Text
View/download PDF

33. Modeling of autosomal-dominant retinitis pigmentosa in Caenorhabditis elegans uncovers a nexus between global impaired functioning of certain splicing factors and cell type-specific apoptosis

Author

Xènia Serrat, Sylvain Foissac, Francisco Javier García-Rodríguez, Julián Cerón, David González-Knowles, Montserrat Porta-de-la-Riva, David Aristizábal-Corrales, Eric Cornes, Laura Fontrodona, Karinna Rubio-Peña, Silvia Torres, Bellvitge Biomedical Research Institute, Partenaires INRAE, Integromics, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, National Institutes of Health Office of Research Infrastructure Programs [P40 OD010440], government of Peru, La Marato de TV3 foundation [100910], Instituto de Salud Carlos III (ISCIII) [PI12/01554], and FEDER funds/European Regional Development Fund (ERDF)

Subjects
Retinal degeneration, congenital, hereditary, and neonatal diseases and abnormalities, Nematodes, Ribonucleoprotein, U4-U6 Small Nuclear, [SDV]Life Sciences [q-bio], RNA Splicing, Apoptosis, Ataxia Telangiectasia Mutated Proteins, Biology, intron retention, Article, 03 medical and health sciences, 0302 clinical medicine, RNA interference, Retinitis pigmentosa, medicine, Malalties hereditàries, Animals, [INFO]Computer Science [cs], Caenorhabditis elegans, Caenorhabditis elegans Proteins, Molecular Biology, Eye diseases, Ribonucleoprotein, U5 Small Nuclear, 030304 developmental biology, Genes, Dominant, Genetics, 0303 health sciences, Gene knockdown, Intron, medicine.disease, biology.organism_classification, Phenotype, eye diseases, Repressor Proteins, Organ Specificity, Ectopic expression, RNA Interference, spliceosome, Oftalmopaties, Genetic disorders, 030217 neurology & neurosurgery, Retinitis Pigmentosa
Abstract

Retinitis pigmentosa (RP) is a rare genetic disease that causes gradual blindness through retinal degeneration. Intriguingly, seven of the 24 genes identified as responsible for the autosomal-dominant form (adRP) are ubiquitous spliceosome components whose impairment causes disease only in the retina. The fact that these proteins are essential in all organisms hampers genetic, genomic, and physiological studies, but we addressed these difficulties by using RNAi in Caenorhabditis elegans. Our study of worm phenotypes produced by RNAi of splicing-related adRP (s-adRP) genes functionally distinguishes between components of U4 and U5 snRNP complexes, because knockdown of U5 proteins produces a stronger phenotype. RNA-seq analyses of worms where s-adRP genes were partially inactivated by RNAi, revealed mild intron retention in developing animals but not in adults, suggesting a positive correlation between intron retention and transcriptional activity. Interestingly, RNAi of s-adRP genes produces an increase in the expression of atl-1 (homolog of human ATR), which is normally activated in response to replicative stress and certain DNA-damaging agents. The up-regulation of atl-1 correlates with the ectopic expression of the pro-apoptotic gene egl-1 and apoptosis in hypodermal cells, which produce the cuticle, but not in other cell types. Our model in C. elegans resembles s-adRP in two aspects: The phenotype caused by global knockdown of s-adRP genes is cell type-specific and associated with high transcriptional activity. Finally, along with a reduced production of mature transcripts, we propose a model in which the retina-specific cell death in s-adRP patients can be induced through genomic instability.

Published
2015
Full Text
View/download PDF

35. Analysis of alternative splicing events in custom gene datasets by AStalavista

Author

Sylvain, Foissac and Michael, Sammeth

Subjects
Alternative Splicing, Computational Biology, High-Throughput Nucleotide Sequencing, Humans, Transcriptome
Abstract

Alternative splicing (AS) is a eukaryotic principle to derive more than one RNA product from transcribed genes by removing distinct subsets of introns from a premature polymer. We know today that this process is highly regulated and makes up a large part of the differences between species, cell types, and states. The key to compare AS across different genes or organisms is to tokenize the AS phenomenon into atomary units, so-called AS events. These events then usually are grouped by common patterns to investigate the underlying molecular mechanisms that drive their regulation. However, attempts to decompose loci with AS observations into events are often hampered by applying a limited set of a priori defined event patterns which are not capable to describe all AS configurations and therefore cannot decompose the phenomenon exhaustively. In this chapter, we describe working scenarios of AStalavista, a computational method that reports all AS events reflected by transcript annotations. We show how to practically employ AStalavista to study AS variation in complex transcriptomes, as characterized by the human GENCODE annotation. Our examples demonstrate how the inherent and universal AStalavista paradigm allows for an automatic delineation of AS events in custom gene datasets. Additionally, we sketch an example of an AStalavista use case including next-generation sequencing data (RNA-Seq) to enrich the landscape of discovered AS events.

Published
2015

36. De novo Assembly of the Chinese Bamboo-Partridge Genome and Comparison with Chicken

Author

Gabriel Rognon, Diane Esquerre, Sylvain Foissac, Alain Vignal, Jean-Luc Coville, Bertrand Bed'Hom, Michele Tixier-Boichard, Thomas Faraut, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], and AgroParisTech-Institut National de la Recherche Agronomique (INRA)

Subjects
genomic, chicken, [SDV]Life Sciences [q-bio]
Abstract

absent

Published
2015

37. Analysis of Alternative Splicing Events in Custom Gene Datasets by AStalavista

Author

Michael Sammeth, Sylvain Foissac, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Laboratorio Nacional de Computação Cientifica [Rio de Janeiro] (LNCC / MCT), and Picardi E.

Subjects
0106 biological sciences, rna processing, [SDV]Life Sciences [q-bio], Computational biology, Variation (game tree), bioinfrormatic, Biology, definition of alternative splicing, 01 natural sciences, as code, 03 medical and health sciences, Annotation, alternative splicing, [INFO]Computer Science [cs], Set (psychology), Gene, 030304 developmental biology, Genetics, 0303 health sciences, GENCODE, Event (computing), as event, splicing nomenclature, Alternative splicing, Intron, rna-seq, gene expression, transcriptome annotation, 010606 plant biology & botany
Abstract

PMID : 25577392; International audience; Alternative splicing (AS) is a eukaryotic principle to derive more than one RNA product from transcribed genes by removing distinct subsets of introns from a premature polymer. We know today that this process is highly regulated and makes up a large part of the differences between species, cell types, and states. The key to compare AS across different genes or organisms is to tokenize the AS phenomenon into atomary units, so-called AS events. These events then usually are grouped by common patterns to investigate the underlying molecular mechanisms that drive their regulation. However, attempts to decompose loci with AS observations into events are often hampered by applying a limited set of a priori defi ned event patterns which are not capable to describe all AS confi gurations and therefore cannot decompose the phenomenon exhaustively. In this chapter, we describe working scenarios of AStalavista, a computational method that reports all AS events refl ected by transcript annotations. We show how to practically employ AStalavista to study AS variation in complex transcriptomes, as characterized by the human GENCODE annotation. Our examples demonstrate how the inherent and universal AStalavista paradigm allows for an automatic delineation of AS events in custom gene datasets. Additionally, we sketch an example of an AStalavista use case including next-generation sequencing data (RNA-Seq) to enrich the landscape of discovered AS events.

Published
2015
Full Text
View/download PDF

38. Evidence for Transcript Networks Composed of Chimeric RNAs in Human Cells

Author

Vincent Lacroix, Sylvain Foissac, Ryan R. Murray, Sarah Djebali, Cédric Howald, Josep Lluís Gelpí, Paolo Ribeca, Alexandre Reymond, Kourosh Salehi-Ashtiani, Marc Vidal, Roderic Guigó, Thomas R. Gingeras, John A. Stamatoyannopoulos, Erica Dumais, Alexander Dobin, Bryan R. Lajoie, Tim Hubbard, Stylianos E. Antonarakis, Catherine Ucla, Ian Bell, Jacqueline Chrast, Alfonso Valencia, Modesto Orozco, Philippe Batut, Christelle Borel, Adam Frankish, Philipp Kapranov, Jorg Drenkow, Michael L. Tress, Chenwei Lin, Jennifer Harrow, Xinping Yang, Lila Ghamsari, Job Dekker, David C. Martin, Jonathan M. Mudge, Julien Lagarde, Nynke L. van Berkum, Institut de Génétique et Développement de Rennes (IGDR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Universitat Pompeu Fabra [Barcelona] (UPF), Affymetrix Inc., Geneva University Hospital (HUG), The Wellcome Trust Sanger Institute [Cambridge], Laboratoire de Génétique Cellulaire (LGC), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Université de Lausanne (UNIL), Dana-Farber Cancer Institute [Boston], Harvard University [Cambridge], Cold Spring Harbor Laboratory, Spanish National Cancer Research Centre, University of Barcelona, Sagot, Marie-France, Universitat de Barcelona, Centro de Regulación Genómica (CRG), Affymetrix, An algorithmic view on genomes, cells, and environments (BAMBOO), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Université de Genève (UNIGE), Sanger Institute, Wellcome Trust, Harvard Medical School [Boston] (HMS), Cold Spring Harbor Laboratory (CSHL), Spanish National Cancer Research Center (CNIO), Universitat de Barcelona (UB), University of Massachusetts [Amherst] (UMass Amherst), University of Massachusetts System (UMASS), University of Washington [Seattle], Universitat Pompeu Fabra [Barcelona], Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), Université de Lausanne = University of Lausanne (UNIL), Harvard University, Université de Genève = University of Geneva (UNIGE), Borel, Christelle, Ucla, Catherine, Martin, David, Reymond, Alexandre, and Antonarakis, Stylianos

Subjects
Male, Transcription, Genetic, Microarrays, [SDV]Life Sciences [q-bio], Gene Identification and Analysis, lcsh:Medicine, Gene Expression, Validation Studies as Topic, Transcriptomes, Exon, Transcriptome/physiology, 0302 clinical medicine, Transcripció genètica, Gene Regulatory Networks/genetics/physiology, RNA Isoforms, Gene expression, Molecular Cell Biology, site, ddc:576.5, Cells/metabolism, Gene Regulatory Networks, Molecular genetics, Nucleic Acid Amplification Techniques/methods, lcsh:Science, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], Genetics, 0303 health sciences, Multidisciplinary, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Genetic transcription, element, Statistics, [SDV.BBM.MN]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN], tool, Genomics, reverse transcription, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 3. Good health, encode, Chromosomes, Human, Pair 1/genetics, annotation, Chromosomes, Human, Pair 1, RNA/genetics/physiology, [SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Female, Sequence Analysis, Nucleic Acid Amplification Techniques, Algorithms, Research Article, [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], Cells, cloning, Chimerin Proteins/chemistry/genetics, Chimeric gene, Biology, Metabolisme cel·lular, Biostatistics, Models, Biological, Genètica molecular, Molecular Genetics, 03 medical and health sciences, Genome Analysis Tools, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], human genome, Chimerin Proteins/chemistry, Chimerin Proteins/genetics, Gene Expression Profiling, Gene Regulatory Networks/genetics, Gene Regulatory Networks/physiology, Humans, Microarray Analysis/methods, RNA/genetics, RNA/physiology, RNA Isoforms/chemistry, RNA Isoforms/genetics, Transcription, Genetic/genetics, Gene, 030304 developmental biology, RNA Isoforms/chemistry/genetics/metabolism, [SDV.OT] Life Sciences [q-bio]/Other [q-bio.OT], lcsh:R, Chimerin Proteins, RNA, gene fusion, Computational Biology, Microarray Analysis, Gene expression profiling, [SDV.BBM.MN] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN], Human genome, lcsh:Q, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], discovery, Genome Expression Analysis, Transcriptome, 030217 neurology & neurosurgery, Genètica, Mathematics
Abstract

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network. This work has been supported by grants U01HG003150 and U01HG003147 from the National Human Genome Research for the ENCODE project. RG was also supported by a grant from the Spanish Ministry of Education and Science. In addition, KS-A, RM, XY, CL, LG and MV were supported by a grant from the Ellison Foundation and as Institute Sponsored Research from the Dana Farber Cancer Institute Strategic Initiative. The laboratories of SA and AR were supported by grants from the Swiss National Science Foundation and the European Commission AnEUploidy Integrated Project. SA was also supported by the National Center of Excellence ‘‘Frontiers in Genetics’’, ChildCare Foundation and an ERC grant from the European Union. AF, TH and JM acknowledge support from the Wellcome Trust. The work of JLG and MO has been supported by the Spanish Ministry of Science (CTQ2005-09365-C02-02, BIO2009-10964), Instituto Nacional de Bioinformática, the Consolider E-science project (CSD2007-00050), COMBIOMED RETICS and the Fundación Marcelino Botin. JD is supported by a grant from the National Institutes of Health (HG003143) and a W. M. Keck Foundation Distinguished Young Scholar Award. JS is supported by a grant from the National Institutes of Health (U54 HG004592). The work of MT and AV was supported by Consolider E-Science (CSD2007-00050) and the Instituto Nacional de Bioinformática. MV (Center for Cancer Systems Biology, CCSB) is a ‘‘Chercheur Qualifié Honoraire’’ from the Fonds de la Recherche Scientifique (FRS-FNRS, French Community of Belgium). This work has also been funded by grant to TG by NHGRI (U54HG004557) and partially byAffymetirix, Corp

Published
2012
Full Text
View/download PDF

39. An integrated encyclopedia of DNA elements in the human genome

Author

Robert Altshuler, Laura Elnitski, Michael Anaya, Alec Victorsen, Deborah Winter, Javier Herrero, Katherine Varley, Andrea Sboner, Oscar Junhong Luo, Marco Mariotti, Cristina Sisu, Mike Kay, Timothy Dreszer, Jane Loveland, Alexandra Bignell, Ewan Birney, Tim @timjph Hubbard, Kuljeet Sandhu, Eric Haugen, Chris Gunter, Alexej Abyzov, Lucas Ward, Georgi Marinov, Michael Pazin, Thomas Gingeras, Alexander Dobin, Kimberly Foss, Xianjun Dong, Benoit Miotto, Piotr Mieczkowski, Cedric Notredame, Andrew Berry, Shawn Gillespie, Axel Visel, Shawn Levy, Richard Sandstrom, Jose M Gonzalez, Melissa Fullwood, Timo Lassmann, Michael Tress, Julien Lagarde, Kevin Yip, Leslie Adams, Sylvain Foissac, Bronwen Aken, Piero Carninci, Suganthi Balasubramanian, Andrea Tanzer, Sarah Djebali, Michael Hoffman, Gloria Despacio-Reyes, Peter Park, Felix Kokocinski, Katherine Fisher-Aylor, Juan M Vaquerizas, Peggy Farnham, Patrick Collins, Amonida Zadissa, Pedro Ferreira, Philippe Batut, Michael Snyder, Electra Tapanari, Adam Frankish, Paul Flicek, AMARTYA SANYAL, Tyler Alioto, Giovanni Bussotti, Laurence Meyer, Jingyi Jessica Li, Matthew Blow, Tristan FRUM, Roger Alexander, Rory Johnson, Charles Steward, Meizhen Zheng, Margus Lukk, Ross Hardison, Claire Davidson, Gary Saunders, Alan Boyle, Luiz Penalva, Rajinder Kaul, Lazaro Centanin, Florencia Pauli Behn, Thomas Derrien, Nathan Sheffield, Toby Hunt, Eric Nguyen, Jeff Vierstra, Konrad Karczewski, Kimberly Bell, Yanbao Yu, Hagen U Tilgner, James Taylor, Balázs Bánfai, Catherine Snow, Benjamin Vernot, Stephan Kirchmaier, Michael Sammeth, Steven Wilder, Angelika Merkel, Joanna Mieczkowska, Guoliang Li, Wei Lin, Jennifer Harrow, Thomas Oliver Auer, Daniel Barrell, Eddie Park, Alvis Brazma, Hazuki Takahashi, Nathan Johnson, Daniel Sobral, Terry Furey, Alexandre Reymond, Jonathan Mudge, Anshul Kundaje, Jose Rodriguez, Akshay Bhinge, James Gilbert, Jakub Karczewski, Venkat Malladi, Troy Whitfield, Orion Buske, Ian Dunham, Jennifer Moran, Joachim Wittbrodt, Charles B. Epstein, Laurens Wilming, Jason Gertz, Joshua Akey, Joel Rozowsky, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), National Human Genome Research Institute (NHGRI), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Antonarakis, Stylianos, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Altshuler, Robert Charles, Ernst, Jason, Kellis, Manolis, Kheradpour, Pouya, Ward, Lucas D., Eaton, Matthew Lucas, Hendrix, David A., Jungreis, Irwin, Lin, Michael F., Washietl, Stefan, Lists of participants and their affiliations appear at the end of the paper and in the 'Collaboration/Projet' field., The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein), U01HG004695 (E. Birney), U54HG004563 (G. E. Crawford), U54HG004557 (T. R. Gingeras), U54HG004555 (T. J. Hubbard), U41HG004568 (W. J. Kent), U54HG004576 (R. M. Myers), U54HG004558 (M. Snyder), U54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker), RC2HG005591 and R01HG003700 (M. C. Giddings), R01HG004456-03 (Y. Ruan), U01HG004571 (S. A. Tenenbaum), U01HG004561 (Z. Weng), RC2HG005679 (K. P. White). This project was supported in part by American Recovery and Reinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591, R01HG003541,U01HG004561,RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research Program of the NHGRI (L. Elnitski, ZIAHG200323, E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California., Dunham I, Kundaje A, Aldred SF, Collins PJ, Davis CA, Doyle F, Epstein CB, Frietze S, Harrow J, Kaul R, Khatun J, Lajoie BR, Landt SG, Lee BK, Pauli F, Rosenbloom KR, Sabo P, Safi A, Sanyal A, Shoresh N, Simon JM, Song L, Trinklein ND, Altshuler RC, Birney E, Brown JB, Cheng C, Djebali S, Dong X, Dunham I, Ernst J, Furey TS, Gerstein M, Giardine B, Greven M, Hardison RC, Harris RS, Herrero J, Hoffman MM, Iyer S, Kellis M, Khatun J, Kheradpour P, Kundaje A, Lassmann T, Li Q, Lin X, Marinov GK, Merkel A, Mortazavi A, Parker SC, Reddy TE, Rozowsky J, Schlesinger F, Thurman RE, Wang J, Ward LD, Whitfield TW, Wilder SP, Wu W, Xi HS, Yip KY, Zhuang J, Pazin MJ, Lowdon RF, Dillon LA, Adams LB, Kelly CJ, Zhang J, Wexler JR, Green ED, Good PJ, Feingold EA, Bernstein BE, Birney E, Crawford GE, Dekker J, Elnitski L, Farnham PJ, Gerstein M, Giddings MC, Gingeras TR, Green ED, Guigó R, Hardison RC, Hubbard TJ, Kellis M, Kent W, Lieb JD, Margulies EH, Myers RM, Snyder M, Stamatoyannopoulos JA, Tenenbaum SA, Weng Z, White KP, Wold B, Khatun J, Yu Y, Wrobel J, Risk BA, Gunawardena HP, Kuiper HC, Maier CW, Xie L, Chen X, Giddings MC, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Kheradpour P, Mikkelsen TS, Gillespie S, Goren A, Ram O, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Eaton ML, Kellis M, Djebali S, Davis CA, Merkel A, Dobin A, Lassmann T, Mortazavi A, Tanzer A, Lagarde J, Lin W, Schlesinger F, Xue C, Marinov GK, Khatun J, Williams BA, Zaleski C, Rozowsky J, Röder M, Kokocinski F, Abdelhamid RF, Alioto T, Antoshechkin I, Baer MT, Batut P, Bell I, Bell K, Chakrabortty S, Chen X, Chrast J, Curado J, Derrien T, Drenkow J, Dumais E, Dumais J, Duttagupta R, Fastuca M, Fejes-Toth K, Ferreira P, Foissac S, Fullwood MJ, Gao H, Gonzalez D, Gordon A, Gunawardena HP, Howald C, Jha S, Johnson R, Kapranov P, King B, Kingswood C, Li G, Luo OJ, Park E, Preall JB, Presaud K, Ribeca P, Risk BA, Robyr D, Ruan X, Sammeth M, Sandhu KS, Schaeffer L, See LH, Shahab A, Skancke J, Suzuki AM, Takahashi H, Tilgner H, Trout D, Walters N, Wang H, Wrobel J, Yu Y, Hayashizaki Y, Harrow J, Gerstein M, Hubbard TJ, Reymond A, Antonarakis SE, Hannon GJ, Giddings MC, Ruan Y, Wold B, Carninci P, Guigó R, Gingeras TR, Rosenbloom KR, Sloan CA, Learned K, Malladi VS, Wong MC, Barber GP, Cline MS, Dreszer TR, Heitner SG, Karolchik D, Kent W, Kirkup VM, Meyer LR, Long JC, Maddren M, Raney BJ, Furey TS, Song L, Grasfeder LL, Giresi PG, Lee BK, Battenhouse A, Sheffield NC, Simon JM, Showers KA, Safi A, London D, Bhinge AA, Shestak C, Schaner MR, Kim SK, Zhang ZZ, Mieczkowski PA, Mieczkowska JO, Liu Z, McDaniell RM, Ni Y, Rashid NU, Kim MJ, Adar S, Zhang Z, Wang T, Winter D, Keefe D, Birney E, Iyer VR, Lieb JD, Crawford GE, Li G, Sandhu KS, Zheng M, Wang P, Luo OJ, Shahab A, Fullwood MJ, Ruan X, Ruan Y, Myers RM, Pauli F, Williams BA, Gertz J, Marinov GK, Reddy TE, Vielmetter J, Partridge E, Trout D, Varley KE, Gasper C, Bansal A, Pepke S, Jain P, Amrhein H, Bowling KM, Anaya M, Cross MK, King B, Muratet MA, Antoshechkin I, Newberry KM, McCue K, Nesmith AS, Fisher-Aylor KI, Pusey B, DeSalvo G, Parker SL, Balasubramanian S, Davis NS, Meadows SK, Eggleston T, Gunter C, Newberry J, Levy SE, Absher DM, Mortazavi A, Wong WH, Wold B, Blow MJ, Visel A, Pennachio LA, Elnitski L, Margulies EH, Parker SC, Petrykowska HM, Abyzov A, Aken B, Barrell D, Barson G, Berry A, Bignell A, Boychenko V, Bussotti G, Chrast J, Davidson C, Derrien T, Despacio-Reyes G, Diekhans M, Ezkurdia I, Frankish A, Gilbert J, Gonzalez JM, Griffiths E, Harte R, Hendrix DA, Howald C, Hunt T, Jungreis I, Kay M, Khurana E, Kokocinski F, Leng J, Lin MF, Loveland J, Lu Z, Manthravadi D, Mariotti M, Mudge J, Mukherjee G, Notredame C, Pei B, Rodriguez JM, Saunders G, Sboner A, Searle S, Sisu C, Snow C, Steward C, Tanzer A, Tapanari E, Tress ML, van Baren MJ, Walters N, Washietl S, Wilming L, Zadissa A, Zhang Z, Brent M, Haussler D, Kellis M, Valencia A, Gerstein M, Reymond A, Guigó R, Harrow J, Hubbard TJ, Landt SG, Frietze S, Abyzov A, Addleman N, Alexander RP, Auerbach RK, Balasubramanian S, Bettinger K, Bhardwaj N, Boyle AP, Cao AR, Cayting P, Charos A, Cheng Y, Cheng C, Eastman C, Euskirchen G, Fleming JD, Grubert F, Habegger L, Hariharan M, Harmanci A, Iyengar S, Jin VX, Karczewski KJ, Kasowski M, Lacroute P, Lam H, Lamarre-Vincent N, Leng J, Lian J, Lindahl-Allen M, Min R, Miotto B, Monahan H, Moqtaderi Z, Mu XJ, O'Geen H, Ouyang Z, Patacsil D, Pei B, Raha D, Ramirez L, Reed B, Rozowsky J, Sboner A, Shi M, Sisu C, Slifer T, Witt H, Wu L, Xu X, Yan KK, Yang X, Yip KY, Zhang Z, Struhl K, Weissman SM, Gerstein M, Farnham PJ, Snyder M, Tenenbaum SA, Penalva LO, Doyle F, Karmakar S, Landt SG, Bhanvadia RR, Choudhury A, Domanus M, Ma L, Moran J, Patacsil D, Slifer T, Victorsen A, Yang X, Snyder M, Auer T, Centanin L, Eichenlaub M, Gruhl F, Heermann S, Hoeckendorf B, Inoue D, Kellner T, Kirchmaier S, Mueller C, Reinhardt R, Schertel L, Schneider S, Sinn R, Wittbrodt B, Wittbrodt J, Weng Z, Whitfield TW, Wang J, Collins PJ, Aldred SF, Trinklein ND, Partridge EC, Myers RM, Dekker J, Jain G, Lajoie BR, Sanyal A, Balasundaram G, Bates DL, Byron R, Canfield TK, Diegel MJ, Dunn D, Ebersol AK, Frum T, Garg K, Gist E, Hansen R, Boatman L, Haugen E, Humbert R, Jain G, Johnson AK, Johnson EM, Kutyavin TV, Lajoie BR, Lee K, Lotakis D, Maurano MT, Neph SJ, Neri FV, Nguyen ED, Qu H, Reynolds AP, Roach V, Rynes E, Sabo P, Sanchez ME, Sandstrom RS, Sanyal A, Shafer AO, Stergachis AB, Thomas S, Thurman RE, Vernot B, Vierstra J, Vong S, Wang H, Weaver MA, Yan Y, Zhang M, Akey JM, Bender M, Dorschner MO, Groudine M, MacCoss MJ, Navas P, Stamatoyannopoulos G, Kaul R, Dekker J, Stamatoyannopoulos JA, Dunham I, Beal K, Brazma A, Flicek P, Herrero J, Johnson N, Keefe D, Lukk M, Luscombe NM, Sobral D, Vaquerizas JM, Wilder SP, Batzoglou S, Sidow A, Hussami N, Kyriazopoulou-Panagiotopoulou S, Libbrecht MW, Schaub MA, Kundaje A, Hardison RC, Miller W, Giardine B, Harris RS, Wu W, Bickel PJ, Banfai B, Boley NP, Brown JB, Huang H, Li Q, Li JJ, Noble WS, Bilmes JA, Buske OJ, Hoffman MM, Sahu AD, Kharchenko PV, Park PJ, Baker D, Taylor J, Weng Z, Iyer S, Dong X, Greven M, Lin X, Wang J, Xi HS, Zhuang J, Gerstein M, Alexander RP, Balasubramanian S, Cheng C, Harmanci A, Lochovsky L, Min R, Mu XJ, Rozowsky J, Yan KK, Yip KY, Birney E., and Miotto, Benoit

Subjects
Encyclopedias as Topic, [SDV]Life Sciences [q-bio], DNA Footprinting, Genoma humà, Binding Sites/genetics, Histones/chemistry/metabolism, 0302 clinical medicine, Exons/genetics, ddc:576.5, 0303 health sciences, Multidisciplinary, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], DNA-Binding Proteins/metabolism, region, Chemistry, Genetic Predisposition to Disease/genetics, Genomics, Polymorphism, Single Nucleotide/genetics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Neoplasms/genetics, Chromatin, Cell biology, in vivo, Genetic Variation/genetics, 030220 oncology & carcinogenesis, Deoxyribonuclease I/metabolism, Proteins/genetics, transcription factor-binding, chromosome conformation capture, DNA Methylation/genetics, Chromosomes, Human/genetics/metabolism, Chromatin Immunoprecipitation, Mammals/genetics, DNA/genetics, determinant, Article, 03 medical and health sciences, map, Animals, Humans, Transcription Factors/metabolism, Alleles, mouse, 030304 developmental biology, Transcription, Genetic/genetics, Chromatin/genetics/metabolism, Sequence Analysis, RNA, human cell, Molecular Sequence Annotation, Regulatory Sequences, Nucleic Acid/genetics, Promoter Regions, Genetic/genetics, DNA binding site, Genòmica, Genome, Human/genetics, chromatin, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genètica, Genome-Wide Association Study
Abstract

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research. The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein); U01HG004695 (E. Birney); U54HG004563 (G. E. Crawford); U54HG004557 (T. R. Gingeras); U54HG004555 (T. J. Hubbard); U41HG004568 /n(W. J. Kent); U54HG004576 (R. M. Myers); U54HG004558 (M. Snyder);/nU54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker); RC2HG005591 and R01HG003700 (M. C. Giddings); R01HG004456-03 (Y. Ruan); U01HG004571 (S. A. Tenenbaum); U01HG004561 (Z. Weng); RC2HG005679 (K. P. White). This project was supported in part by American Recovery and/nReinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591,R01HG003541, U01HG004561, RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research/nProgram of the NHGRI (L. Elnitski, ZIAHG200323; E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California.

Published
2012
Full Text
View/download PDF

40. Landscape of transcription in human cells

Author

Tyler Alioto, Colin Kingswood, Lorian Schaffer, Sylvain Foissac, Kimberly Bell, Diane Trout, Wei Lin, Nathalie Walters, Thomas R. Gingeras, Oscar Junhong Luo, Pedro G. Ferreira, Atif Shahab, Assaf Gordon, Kata Fejes-Toth, Joao Curado, Jacqueline Chrast, Thomas Derrien, Georgi K. Marinov, Hazuki Takahashi, Alexander Dobin, Nadav Bar, Lei-Hoon See, Morgan C. Giddings, Erica Dumais, Michael Sammeth, Philipp Kapranov, Jainab Khatun, Meagan Fastuca, Jørgen Skancke, Ian Bell, Emilie Falconnet, Roderic Guigó, Huaien Wang, Kimberly Persaud, Alexandre Reymond, Carrie A. Davis, Xiaoan Ruan, Rehab F. Abdelhamid, Daniel Robyr, Joel Rozowsky, Ana Maria Suzuki, Sonali Jha, Marion S. Röder, Sudipto K. Chakrabortty, Brian A. Risk, Hagen Tilgner, Eddie Park, Stylianos E. Antonarakis, Piero Carninci, Hui Gao, Sarah Djebali, Timo Lassmann, Andrea Tanzer, Philippe Batut, Cédric Howald, Yanbao Yu, Ali Mortazavi, Felix Kokocinski, Jennifer Harrow, Mark Gerstein, Melissa J. Fullwood, Chenghai Xue, Gregory J. Hannon, Xian Chen, Igor Antoshechkin, Yoshihide Hayashizaki, Brian A. Williams, Chris Zaleski, John A. Wrobel, Radha Duttagupta, Barbara J. Wold, Julien Lagarde, David Gonzalez, Yijun Ruan, Tim Hubbard, Angelika Merkel, Rory Johnson, Jonathan B. Preall, Jorg Drenkow, Brandon King, Paolo Ribeca, Harsha P. Gunawardena, Jacqueline Dumais, Felix Schlesinger, Michael T. Baer, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Universitat Pompeu Fabra [Barcelona] (UPF), Cold Spring Harbor Laboratory, Riken Yokohama Institute, California Institute of Technology (CALTECH), University of California [Irvine] (UCI), University of California, Boise State University, Yale University [New Haven], The Wellcome Trust Sanger Institute [Cambridge], Centro Nacional de Analisis Genomico [Barcelona] (CNAG), Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Affymetrix Inc., University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Université de Lausanne (UNIL), Laboratoire de Génétique Cellulaire (LGC), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, University of Geneva [Switzerland], (IGE3 Inst Genet & Genom Geneva), University of Geneva Medical School, Genome Institute of Singapore (GIS), St Laurent Institut, Falconnet, Emilie, Robyr, Daniel, Reymond, Alexandre, Antonarakis, Stylianos, Universitat Pompeu Fabra [Barcelona], Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)

Subjects
Encyclopedias as Topic, Repetitive Sequences, Nucleic Acid/genetics, Polyadenylation, [SDV]Life Sciences [q-bio], Genoma humà, Genome, Repetitive Sequences, RNA Editing/genetics, 0302 clinical medicine, Exons/genetics, Protein Isoforms, RNA/biosynthesis/genetics, ddc:576.5, RNA Splicing/genetics, Genetics, 0303 health sciences, Multidisciplinary, Exons, Genomics, Transcriptome/genetics, Long non-coding RNA, Enhancer Elements, Genetic, 030220 oncology & carcinogenesis, Sequence Analysis, Transcription, Human, Enhancer Elements, General Science & Technology, 1.1 Normal biological development and functioning, RNA Splicing, DNA, Intergenic/genetics, Computational biology, DNA/genetics, Biology, Article, Cell Line, 03 medical and health sciences, Genetic, Underpinning research, Protein Isoforms/genetics, map, expression, Humans, Genes/genetics, genome, Gene, Alleles, Transcription, Genetic/genetics, 030304 developmental biology, Intergenic, Nucleic Acid, small rnas, Sequence Analysis, RNA, Gene Expression Profiling, Human Genome, RNA, Molecular Sequence Annotation, DNA, Regulatory Sequences, Nucleic Acid/genetics, Gene expression profiling, Genes, Genome, Human/genetics, Polyadenylation/genetics, RNA/biosynthesis, RNA/genetics, enhancer, identification, Human genome, Generic health relevance, RNA Editing, Transcriptome, Regulatory Sequences, Genètica
Abstract

Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene. This work was supported by the National Human Genome Research Institute (NHGRI) production grants U54HG004557, U54HG004555, U54HG004576 and U54HG004558, and by the NHGRI pilot grant R01HG003700. It was also supported by the NHGRI ARRA stimulus grant 1RC2HG005591, the National Science Foundation (SNF) grant 127375, the European Research Council (ERC) grant/n249968, a research grant for the RIKEN Omics Science Center from the Japanese Ministry of Education, Culture, Sports, Science and Technology, and grants BIO2011-26205, CSD2007-00050 and INB GNV-1 from the Spanish Ministry of Science

Published
2012
Full Text
View/download PDF

41. New class of gene-termini-associated human RNAs suggests a novel RNA copying mechanism

Author

Doron Lipson, Stylianos E. Antonarakis, Patrice M. Milos, Steve Roels, Philipp Kapranov, Christelle Borel, Fatih Ozsolak, Chris Hart, A. Paula Monaghan, Sang Woo Kim, Sylvain Foissac, Bino John, Helicos BioSci Corp, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, University of Geneva [Switzerland], Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]

Subjects
Poly U, Genes/*genetics, RNA, Antisense/classification/genetics/metabolism, [SDV]Life Sciences [q-bio], Genomics, Biology, polymerase-II, Article, 03 medical and health sciences, 0302 clinical medicine, Transcription (biology), Humans, RNA, Antisense, Nucleotide, ddc:576.5, Gene, genome, mouse, 030304 developmental biology, chemistry.chemical_classification, Genetics, 0303 health sciences, Multidisciplinary, Base Sequence, Models, Genetic, Nucleotides, Copying mechanism, RNA, food and beverages, Templates, Genetic, Poly A/genetics/metabolism, RNA/biosynthesis/*classification/genetics/*metabolism, Nucleotides/genetics, Genes, chemistry, Nucleic acid, Poly U/genetics/metabolism, Poly A, transcription, 030217 neurology & neurosurgery, Biogenesis, HeLa Cells
Abstract

Short (< 200 nt) RNA (sRNA) profiling of human cells using various technologies demonstrates unexpected complexity of sRNAs with 100’s of thousands of sRNA species present 1,2,3,4. Genetic and in vitro studies argue that these RNAs are not merely degradation products of longer transcripts but could indeed have function1,2,5. Furthermore, profiling of RNAs, including the sRNAs, can reveal not only novel transcripts, but also make clear predictions about the existence and properties of novel biochemical pathways operating in a cell. For example, short RNA profiling in human cells suggested existence of an unknown capping mechanism operating on cleaved RNA 2 a biochemical component of which was later identified6. Here we show that human cells contain a novel type of sRNAs that have non-genomically encoded 5’ polyU tails. Presence of these RNAs at the termini of genes, specifically at the very 3’ ends of known mRNAs strongly argues for the presence of a yet uncharacterized endogenous biochemical pathway in a cell that can copy RNA. We show that this pathway can operate on multiple genes, with specific enrichment towards transcripts encoding components of the translational machinery. Finally we show that genes are also flanked by sense, 3’ polyadenylated sRNAs that are likely to be capped.

Published
2010
Full Text
View/download PDF

42. A combinatorial code for CPE-mediated translational control

Author

Sylvain Foissac, Maria Piqué, José M. López, Roderic Guigó, Raúl Méndez, Centre for Genomic Regulation (CRG), Laboratoire de Génétique Cellulaire (LGC), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)

Subjects
Cytoplasm, RNA 3' Polyadenylation Signals, Polyadenylation, PROTEINS, Cytoplasmic polyadenylation element, [SDV]Life Sciences [q-bio], CELLCYCLE, xenopus oocyte maturation, Cyclin B, Xenopus Proteins, Biology, General Biochemistry, Genetics and Molecular Biology, CPEB, Mice, Xenopus laevis, 03 medical and health sciences, 0302 clinical medicine, cyclin, meiotic maturation, Protein biosynthesis, Animals, Humans, 3' Untranslated Regions, Progesterone, 030304 developmental biology, mRNA Cleavage and Polyadenylation Factors, Genetics, 0303 health sciences, Messenger RNA, Biochemistry, Genetics and Molecular Biology(all), phosphorylation, RNA-Binding Proteins, Translation (biology), cytoplasmic polyadenylation, Cell biology, polymerase, Meiosis, RNA, Messenger, Stored, Gene Expression Regulation, Mutagenesis, Protein Biosynthesis, Oocytes, biology.protein, Translational Activation, RNA, 030217 neurology & neurosurgery, Transcription Factors
Abstract

SummaryCytoplasmic polyadenylation plays a key role in the translational control of mRNAs driving biological processes such as gametogenesis, cell-cycle progression, and synaptic plasticity. What determines the distinct time of polyadenylation and extent of translational control of a given mRNA, however, is poorly understood. The polyadenylation-regulated translation is controlled by the cytoplasmic polyadenylation element (CPE) and its binding protein, CPEB, which can assemble both translational repression or activation complexes. Using a combination of mutagenesis and experimental validation of genome-wide computational predictions, we show that the number and relative position of two elements, the CPE and the Pumilio-binding element, with respect to the polyadenylation signal define a combinatorial code that determines whether an mRNA will be translationally repressed by CPEB, as well as the extent and time of cytoplasmic polyadenylation-dependent translational activation.

Published
2008
Full Text
View/download PDF

43. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

Author

Nan Jiang, Alfonso Valencia, Rachel A. Harte, Abigail Woodroffe, Michael Seringhaus, Andrew Haydock, Eugene Davydov, Todd M. Lowe, Peggy J. Farnham, Robert E. Thurman, Tyler Alioto, Adam Ameur, Morgan Park, Roderic Guigó, Archana Thakkapallayil, Philipp Kapranov, Francis S. Collins, Donna Karolchik, Stefan Washietl, Kerstin Lindblad-Toh, Michael L. Tress, Barbara E. Stranger, Gregory M. Cooper, Kun Wang, Thomas R. Gingeras, Serafim Batzoglou, Peter D. Ellis, Annie Yang, Stylianos E. Antonarakis, Jonghwan Kim, Robert M. Andrews, W. James Kent, Kuo Ping Chiu, Madhavan Ganesh, Jason D. Lieb, Shane Neph, Albin Sandelin, Michael Hawrylycz, Eric S. Lander, Matthew T. Weirauch, Nick Goldman, Alexander E. Urban, Ian Bell, Anason S. Halees, Jan Komorowski, Webb Miller, Kandhadayar G. Srinivasan, Evelyn Cheung, David B. Jaffe, Peter J. Good, Gregory Lefebvre, Yuko Yoshinaga, Sylvain Foissac, Alexander W. Bruce, Mark Dickson, Christoph M. Koch, Antigone S. Dimas, Zhengdong D. Zhang, Matthew J. Oberley, Paul I.W. de Bakker, Arend Sidow, Xueqing Zhang, Molly Weaver, Jane Rogers, Jacquelyn R. Idol, Jeff Goldy, Haiyan Huang, William Stafford Noble, Angie S. Hinrichs, Sandeep Patel, David A. Nix, Lluís Armengol, Siew Woh Choo, Hong Sain Ooi, Sara Van Calcar, Ivan Adzhubei, Job Dekker, Sara J. Cooper, Hari Tammana, Valerie Maduro, Jason A. Greenbaum, Bing Ren, Sharon L. Squazzo, Jennifer C. McDowell, Chikatoshi Kai, Ivo L. Hofacker, Ian Dunham, Peter J. Bickel, Nancy Holroyd, Eduardo Eyras, Julien Lagarde, Fei Yao, Man Yu, Piero Carninci, Chia-Lin Wei, Alice C. Young, Yong Yu, Daryl J. Thomas, George Asimenos, Xiaoqin Xu, Galt P. Barber, Andrea Tanzer, Juan I. Montoya-Burgos, Sujit Dike, Nathan Day, Gregory E. Crawford, Michele Clamp, Todd Richmond, Nuria Lopez-Bigas, Vishwanath R. Iyer, Ewan Birney, Richard Humbert, Gary C. Hon, David Swarbreck, Xiaobin Guan, Sarah Wilcox, Nate Heintzman, Josep F. Abril, Elaine R. Mardis, Stefan Enroth, Charlie W.H. Lee, Nicholas Matthews, Benedict Paten, Robert Castelo, Michael A. Singer, Mousheng Xu, Chiou Yu Choo, Nancy F. Hansen, Elizabeth Rosenzweig, Patrick A. Navas, Jacqueline Chrast, Brett E. Johnson, Jan O. Korbel, Simon Whelan, Stephen Hartman, Ulas Karaoz, Ingileif B. Hallgrímsdóttir, David Haussler, Michael R. Brent, Jill Cheng, Gonçalo R. Abecasis, Ann S. Zweig, Sherman M. Weissman, Michael O. Dorschner, Jin Lian, Vinsensius B. Vega, Cordelia Langford, Alexandre Reymond, Mark Gerstein, Pawandeep Dhami, Ola Wallerman, Huaiyang Jiang, Lior Pachter, James Taylor, Eric A. Stone, David R. Inman, Yijun Ruan, Peter E. Newburger, Roland Green, Ari Löytynoja, Shelley Force Aldred, Alvaro Rada-Iglesias, Baishali Maskeri, Joel Rozowsky, Jorg Drenkow, Colin N. Dewey, Srinka Ghosh, Yutao Fu, Kayla E. Smith, Xavier Estivill, Donna M. Muzny, Christine P. Bird, Tim Hubbard, Jana Hertel, Kristin Missal, Neerja Karnani, Ericka M. Johnson, Nan Zhang, Zhou Zhu, Stephen C. J. Parker, Minmei Hou, Charlotte N. Henrichsen, Heather A. Hirsch, Caroline Manzano, Laura A. Liefer, Kim C. Worley, Robert Baertsch, Mark S. Guyer, Ross C. Hardison, Zheng Lian, Hiram Clawson, Leah O. Barrera, Manja Lindemeyer, James Cuff, Chunxu Qu, Jun Kawai, Jennifer Hillman-Jackson, Eric D. Green, Robert W. Blakesley, Abel Ureta-Vidal, Rhona K. Stuart, Fabio Pardi, Peter J. Sabo, Edward A. Sekinger, John S. Mattick, Ankit Malhotra, Taane G. Clark, James G. R. Gilbert, James C. Mullikin, Deyou Zheng, Robert M. Kuhn, Tae Hoon Kim, M. Geoff Rosenfeld, Kirsten Lee, Jörg Hackermüller, Oliver M. Dovey, Deanna M. Church, Kyle J. Munn, Peter F. Stadler, Phillippe Couttet, Claudia Fried, Jaafar N. Haidar, Kris A. Wetterstrand, Wing-Kin Sung, Paul G. Giresi, Jia Qian Wu, Ruth Taylor, David A. Wheeler, Zarmik Moqtaderi, Adam Siepel, Michael Snyder, Ian Holmes, Jun Liu, Olof Emanuelsson, Kevin Struhl, Saurabh Asthana, Akshay Bhinge, Adam Frankish, Yoshihide Hayashizaki, Ghia Euskirchen, Joel D. Martin, Robert S. Fulton, Ugrappa Nagalakshmi, Heike Fiegler, Gayle K. Clelland, Shane C. Dillon, Fidencio Neri, Elliott H. Margulies, Sean Davis, Mark Bieda, Tristan Frum, Michael S. Kuehn, Heather Trumbower, Pamela J. Thomas, Kazutoyo Osoegawa, Richard A. Gibbs, Emmanouil T. Dermitzakis, Julian L. Huppert, Richard K. Wilson, Tina Graves, Zhiping Weng, Anthony Shafer, Baoli Zhu, Christopher K. Glass, Patrick J. Boyle, Hennady P. Shulha, Maxim Koriabine, Christoph Flamm, David Vetrie, Nigel P. Carter, Patrick Ng, Peter Kraus, John A. Stamatoyannopoulos, George M. Weinstock, Tim Massingham, Jane M. Lin, Damian Keefe, Jean L. Chang, Shamil R. Sunyaev, Sergey Nikolaev, Kate R. Rosenbloom, Carine Wyss, Hua Cao, Keith D. James, Michael C. Zody, Gerard G. Bouffard, Atif Shahab, Nathan D. Trinklein, James B. Brown, Erica Sodergren, Xiaodong Zhao, Rosa Luna, Sante Gnerre, Paul Flicek, Joanna C. Fowler, Andrew D. Kern, Jakob Skou Pedersen, David C. King, Anindya Dutta, Elise A. Feingold, Richard M. Myers, Richard Sandstrom, Catherine Ucla, Thomas D. Tullius, Mikhail Nefedov, Claes Wadelius, Jennifer Harrow, Christopher M. Taylor, Xiaoling Zhang, Pieter J. de Jong, Dermitzakis, Emmanouil, and Reymond, Alexandre

Subjects
DNA Replication, RNA, Messenger/genetics, Chromatin Immunoprecipitation, Heterozygote, RNA, Untranslated, Transcription, Genetic, Systems biology, Histones/metabolism, RNA, Untranslated/genetics, Pilot Projects, Genomics, Computational biology, Regulatory Sequences, Nucleic Acid, Biology, ENCODE, Genome, Article, DNase-Seq, Histones, Evolution, Molecular, Exons/genetics, Humans, ddc:576.5, Transcription Factors/metabolism, RNA, Messenger, Conserved Sequence, Chromatin/genetics/metabolism, Genetics, Transcription, Genetic/ genetics, Multidisciplinary, Genome, Human, GENCODE, Genetic Variation, Exons, Chromatin, Genetic Variation/genetics, Regulatory Sequences, Nucleic Acid/ genetics, Human genome, Conserved Sequence/genetics, Transcription Initiation Site, Functional genomics, Genome, Human/ genetics, Transcription Factors, Protein Binding
Abstract

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view about chromatin structure has emerged, including its interrelationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded novel mechanistic and evolutionary insights about the functional landscape of the human genome. Together, these studies are defining a path forward to pursue a more-comprehensive characterisation of human genome function.

Published
2007
Full Text
View/download PDF

44. Prominent use of distal 5’ transcription start sites and discovery of a large number of additional exons in ENCODE regions

Author

France Denoeud, Philipp Kapranov, Catherine Ucla, Adam Frankish, Robert Castelo, Jorg Drenkow, Julien Lagarde, Tyler Alioto, Caroline Manzano, Jacqueline Chrast, Sujit Dike, Carine Wyss, Charlotte N. Henrichsen, Nancy Holroyd, Mark C. Dickson, Ruth Taylor, Zahra Hance, Sylvain Foissac, Richard M. Myers, Jane Rogers, Tim Hubbard, Jennifer Harrow, Roderic Guigó, Thomas R. Gingeras, Stylianos E. Antonarakis, Alexandre Reymond, Chercheur indépendant, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées

Subjects
DNA, Complementary, Transcription, Genetic, [SDV]Life Sciences [q-bio], Quantitative Trait Loci, Locus (genetics), Biology, ENCODE, Genoma humà, Genome, Article, 03 medical and health sciences, Open Reading Frames, 0302 clinical medicine, Rapid amplification of cDNA ends, Human Genome Project, Genetics, Humans, ORFS, Promoter Regions, Genetic, Gene, Genetics (clinical), 030304 developmental biology, ddc:616, 0303 health sciences, Tiling array, Genome, Human, Chromosome Mapping, DNA, Complementary/genetics, Exons, 030220 oncology & carcinogenesis, Factors de transcripció, Human genome, Transcription, Genetic/ physiology
Abstract

Notice à Reprendre Sur les Auteurs; This report presents systematic empirical annotation of transcript products from 399 annotated protein-coding loci across the 1% of the human genome targeted by the Encyclopedia of DNA elements (ENCODE) pilot project using a combination of 5' rapid amplification of cDNA ends (RACE) and high-density resolution tiling arrays. We identified previously unannotated and often tissue- or cell-line-specific transcribed fragments (RACEfrags), both 5' distal to the annotated 5' terminus and internal to the annotated gene bounds for the vast majority (81.5%) of the tested genes. Half of the distal RACEfrags span large segments of genomic sequences away from the main portion of the coding transcript and often overlap with the upstream-annotated gene(s). Notably, at least 20% of the resultant novel transcripts have changes in their open reading frames (ORFs), most of them fusing ORFs of adjacent transcripts. A significant fraction of distal RACEfrags show expression levels comparable to those of known exons of the same locus, suggesting that they are not part of very minority splice forms. These results have significant implications concerning (1) our current understanding of the architecture of protein-coding genes; (2) our views on locations of regulatory regions in the genome; and (3) the interpretation of sequence polymorphisms mapping to regions hitherto considered to be "noncoding," ultimately relating to the identification of disease-related sequence alterations.

Published
2007
Full Text
View/download PDF

45. EUGENE'HOM: a generic similarity-based gene finder using multiple homologous sequences

Author

Thomas Schiex, Annick Moisan, Sylvain Foissac, Philippe Bardou, Marie-Josée Cros, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Unité de Biométrie et Intelligence Artificielle (UBIA), Institut National de la Recherche Agronomique (INRA), and Foissac, Sylvain

Subjects
0106 biological sciences, DNA, Complementary, DNA, Plant, Sequence analysis, [SDV]Life Sciences [q-bio], Codon, Initiator, Biology, 01 natural sciences, Genome, Homologous Sequences, 03 medical and health sciences, User-Computer Interface, Start codon, Similarity (network science), Sequence Homology, Nucleic Acid, Genetics, Computer Graphics, [INFO]Computer Science [cs], [MATH]Mathematics [math], Gene, 030304 developmental biology, Web site, 0303 health sciences, Internet, Sequence Analysis, DNA, Articles, Eukaryotic Cells, Genes, RNA splicing, RNA Splice Sites, Algorithms, Software, 010606 plant biology & botany
Abstract

International audience; EUGE`NE’HOM is a gene prediction software for eukaryotic organisms based on comparative analysis. EUGE` NE’HOM is able to take into account multiple homologous sequences from more or less closely related organisms. It integrates the results of TBLASTX analysis, splice site and start codon prediction and a robust coding/non-coding probabilistic model which allows EUGE`NE’HOM to handle sequences from a variety of organisms. The current target of EUGE`NE’HOM is plant sequences. The EUGE`NE’HOM web site is available at http://genopole. toulouse.inra.fr/bioinfo/eugene/EuGeneHom/cgi-bin/EuGeneHom.pl.

Published
2003
Full Text
View/download PDF

46. Efficient targeted transcript discovery via array-based normalization of RACE libraries

Author

Sarah Djebali, Philipp Kapranov, Sylvain Foissac, Julien Lagarde, Alexandre Reymond, Catherine Ucla, Carine Wyss, Jorg Drenkow, Erica Dumais, Ryan R Murray, Chenwei Lin, David Szeto, France Denoeud, Miquel Calvo, Adam Frankish, Jennifer Harrow, Periklis Makrythanasis, Marc Vidal, Kourosh Salehi-Ashtiani, Stylianos E Antonarakis, Thomas R Gingeras, Roderic Guigó, Universitat Pompeu Fabra [Barcelona], Affymetrix Inc., Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Université de Lausanne (UNIL), University of Geneva, Harvard University, University of Barcelona, The Wellcome Trust Sanger Institute [Cambridge], Centre for Genomic Regulation (CRG), Universitat Pompeu Fabra [Barcelona] (UPF), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées

Subjects
Transcription, Genetic, [SDV]Life Sciences [q-bio], Oligonucleotide Array Sequence Analysis/methods, Genètica -- Tècnica, Biochemistry, project, 0302 clinical medicine, Rapid amplification of cDNA ends, Nucleic Acid Amplification Techniques/ methods, collection, ddc:576.5, Genomic library, Cloning, Molecular, Genetics, 0303 health sciences, education.field_of_study, Perfil d'expressió gènica, Reverse Transcriptase Polymerase Chain Reaction, element, Chromosomes, Human, Pair 21/genetics, Exons, Alternative Splicing, Chromosomes, Human, Pair 22/genetics, DNA, Complementary/genetics, Gene Expression Profiling/methods, Gene Library, Genome, Human, Humans, Molecular Sequence Data, Nucleic Acid Amplification Techniques/methods, Protein Isoforms/genetics, RNA/genetics, 3. Good health, annotation, 030220 oncology & carcinogenesis, cap analysis, Biotechnology, ADN complementari, Population, Biology, Article, 03 medical and health sciences, human genome, Bancs de gens, education, cdna library, Molecular Biology, mouse, 030304 developmental biology, Tiling array, cDNA library, Alternative splicing, Cell Biology, Nucleic acid amplification technique, Gene Expression Profiling/ methods, DNA, Complementary/ genetics, gene expression, identification, RNA, Human genome, RNA/ genetics
Abstract

Rapid amplification of cDNA ends (RACE) is a widely used approach for transcript identification. Random clone selection from the RACE mixture, however, is an ineffective sampling strategy if the dynamic range of transcript abundances is large. To improve sampling efficiency of human transcripts, we hybridized the products of the RACE reaction onto tiling arrays and used the detected exons to delineate a series of reverse-transcriptase (RT)-PCRs, through which the original RACE transcript population was segregated into simpler transcript populations. We independently cloned the products and sequenced randomly selected clones. This approach, RACEarray, is superior to direct cloning and sequencing of RACE products because it specifically targets new transcripts and often results in overall normalization of transcript abundance. We show theoretically and experimentally that this strategy leads indeed to efficient sampling of new transcripts, and we investigated multiplexing the strategy by pooling RACE reactions from multiple interrogated loci before hybridization. The project at IMIM, CRG, the Universities of Lausanne and Geneva, and Affymetrix is supported by grants U01HG003150 and U01HG003147 from the National Human Genome Research Institute, NIH. Institut Municipal d’Investigació Mèdica and Center for Genomic Regulation (CRG) have also been funded by grant BIO2006-03380 from the Spanish Ministry of Education and Science and from the European BioSapiens Consortium. Affymetrix has also received funds from the National Cancer Institute, NIH, under contract no. N01-CO-12400 and by Affymetrix, Inc. The portion of this work carried out at Center for Cancer Systems Biology was funded by a grant from the Ellison Foundation (awarded to MV) and as Institute Sponsored Research from the Dana Farber Cancer Institute Strategic Initiative

Full Text
View/download PDF

47. An overview of gene expression dynamics during early ovarian folliculogenesis: specificity of follicular compartments and bi-directional dialog

Author

Sylvain Foissac, Florent Woloszyn, Nathalie Marsaud, Olivier Bouchez, Agnès Bonnet, Philippe Mulsant, Beatrice Mandon-Pepin, Cédric Cabau, Julien Sarry, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Recherches Avicoles (SRA), Institut National de la Recherche Agronomique (INRA), GeT PlaGe, Genotoul, Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés (LISBP), Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Recherche Agronomique (INRA), Biologie du Développement et Reproduction (BDR), This work was supported by an INRA 'Bioressources 2010' grant., Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Unité de Recherches Avicoles (URA), Génome et Transcriptome - Plateforme Génomique (GeT-PlaGe), Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Biologie du développement et reproduction (BDR), Centre National de la Recherche Scientifique (CNRS)-École nationale vétérinaire d'Alfort (ENVA)-Institut National de la Recherche Agronomique (INRA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de la Recherche Agronomique (INRA)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), and École nationale vétérinaire - Alfort (ENVA)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Granulosa cells, Cell Communication, Transcriptome, 0302 clinical medicine, Ovarian Follicle, microdissection, rna-seq, early folliculogenesis, molecular dialog, transcriptome, sheep, oocyte, granulosa cell, ovin, Gene expression, Biologie de la reproduction, Cluster Analysis, fonction biologique, [SDV.BDD]Life Sciences [q-bio]/Development Biology, Laser capture microdissection, Regulation of gene expression, Genetics, 0303 health sciences, Reproductive Biology, 030219 obstetrics & reproductive medicine, folliculogénèse, Wnt signaling pathway, Biologie du développement, Development Biology, Cell biology, medicine.anatomical_structure, Organ Specificity, interaction cellulaire, Female, Folliculogenesis, Research Article, Signal Transduction, Biotechnology, Cell signaling, expression génique, Biology, 03 medical and health sciences, medicine, Animals, Humans, Ovarian follicle, régulateur de transcription, 030304 developmental biology, ovaire, Computational Biology, Reproducibility of Results, Molecular Sequence Annotation, [SDV.BDLR]Life Sciences [q-bio]/Reproductive Biology, Gene Expression Regulation, Oocytes, Transcription Factors
Abstract

Chantier qualité GA; Background: Successful early folliculogenesis is crucial for female reproductive function. It requires appropriate gene specific expression of the different types of ovarian cells at different developmental stages. To date, most gene expression studies on the ovary were conducted in rodents and did not distinguish the type of cell. In mono-ovulating species, few studies have addressed gene expression profiles and mainly concerned human oocytes. Results: We used a laser capture microdissection method combined with RNA-seq technology to explore the transcriptome in oocytes and granulosa cells (GCs) during development of the sheep ovarian follicle. We first documented the expression profile of 15 349 genes, then focused on the 5 129 genes showing differential expression between oocytes and GCs. Enriched functional categories such as oocyte meiotic arrest and GC steroid synthesis reflect two distinct cell fates. We identified the implication of GC signal transduction pathways such as SHH, WNT and RHO GTPase. In addition, signaling pathways (VEGF, NOTCH, IGF1, etc.) and GC transzonal projections suggest the existence of complex cell-cell interactions. Finally, we highlighted several transcription regulators and specifically expressed genes that likely play an important role in early folliculogenesis. Conclusions: To our knowledge, this is the first comprehensive exploration of transcriptomes derived from in vivo oocytes and GCs at key stages in early follicular development in sheep. Collectively, our data advance our understanding of early folliculogenesis in mono-ovulating species and will be a valuable resource for unraveling human ovarian dysfunction such as premature ovarian failure (POF).

Full Text
View/download PDF

48. Hierarchical Agglomerative Clustering under contiguity constraint for Hi-C data analysis

Author

Randriamihamison, Nathanaël, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Méthodes avancées d’apprentissage statistique et de contrôle (ASTRAL), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Naval Group, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Quality control and dynamic reliability (CQFD), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Paul Sabatier - Toulouse III, Nathalie Villa-Vialaneix, Marie Chavent, Pierre Neuvial, Sylvain Foissac, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), and Nathalie Vialaneix

Subjects
Dendrogrammes, [SDV.GEN]Life Sciences [q-bio]/Genetics, Dendrograms, Contrainte de contiguïté, Comparaisons de moyennes multivariées, Hierarchical Agglomerative Clustering, [STAT]Statistics [stat], Tree comparisons, Contiguity constraint, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Multivariate means comparisons, Comparaisons d'arbres, Classification ascendante hiérarchique, Comparaisons d’arbres
Abstract

Spatial genome organization inside cell nuclei has a major impact over gene expression regulation, with important implications in fetal development, cell differentiation or diseases development such as cancer. This fact is the starting point of this work whose aim is the study of three-dimensional structure of genome and of its variations using Hi-C data. First, we study the question of modeling the hierarchical structure of genome using Hi-C data. To do this, we considerate the extensions of a natural statistical tool when studying hierarchical structures, the Hierarchical Agglomerative Clustering (HAC), in order to justify its application to Hi-C data. This part justifies the modeling of structures by binary trees resulting from the HAC process. We then develop a method for comparing two samples of trees in order to be able to identify differences in structures between biological conditions with statistical guarantees.; L'organisation spatiale du génome à l'intérieur du noyau des cellules a un impact majeur sur la régulation de l'expression des gènes, avec notamment des implications importantes dans le développement fœtal, la différentiation cellulaire ou le développement de maladies. Ceci constitue la motivation initiale de ce travail dont l'objet est l'étude de la structure tri-dimensionnelle du matériel génétique et de ses variations à partir de données Hi-C. Tout d'abord, on se penche sur la modélisation de la structure hiérarchique du génome à partir de données Hi-C. On étudie les extensions d'un outil statistique naturel pour l'examen de structures hiérarchiques, la Classification Ascendante Hiérarchique (CAH), pour justifier son application au Hi-C. Cela permet de justifier la modélisation des structures par des arbres binaires (issues de la CAH). On développe ensuite une méthode de comparaison de deux échantillons d'arbres pour être capable d'identifier des différences significatives.

Published
2021

49. 3D genome conformation and gene expression in fetal pig muscle at late gestation

Author

Marti-Marimon, Maria, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Université de Toulouse, and Martine Bouissou-Matet, Directrice de thèse - Sylvain Foissac co-directeur

Subjects
pig, [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], gestation, genetic, genome, these, Autre (Sciences du Vivant)
Abstract

In swine breeding industry, sows have been selected for decades on their prolificacy in order to maximize meat production. However, this selection is associated with a higher mortality of newborns. In this context, the skeletal fetal muscle is essential for the piglet’s survival, as it is necessary for motor functions and thermoregulation. Besides, the three-dimensional structure of the genome has been proven to play an important role in gene expression regulation. Thus, in this project, we have focused our interest on the 3D genome conformation and gene expression in porcine muscle nuclei at late gestation. We have initially developed an original approach in which we combined transcriptome data with information of nuclear locations (assessed by 3D DNA FISH) of a subset of genes, in order to build gene co-expression networks. This study has revealed interesting nuclear associations involving IGF2, DLK1 and MYH3 genes, and highlighted a network of muscle-specific interrelated genes involved in the development and maturity of fetal muscle. Then, we assessed the global 3D genome conformation in muscle nuclei at 90 days and 110 days of gestation by using the High-throughput Chromosome Conformation Capture (Hi-C) method. This study has allowed identifying thousands of genomic regions showing significant differences in 3D conformation between the two gestational ages. Interestingly, some of these genomic regions involve the telomeric regions of several chromosomes that seem to be preferentially clustered at 90 days. More important, the observed changes in genome structure are significantly associated with variations in gene expression between the 90th and the 110th days of gestation.

Published
2018

Catalog

Books, media, physical & digital resources
See catalog results