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1. Searching for homozygous haplotype deficiency in Manech Tête Rousse dairy sheep revealed a nonsense variant in the MMUT gene affecting newborn lamb viability

Author

Ben Braiek, Maxime, Moreno-Romieux, Carole, André, Céline, Astruc, Jean-Michel, Bardou, Philippe, Bordes, Arnaud, Debat, Frédéric, Fidelle, Francis, Granado-Tajada, Itsasne, Hozé, Chris, Plisson-Petit, Florence, Rivemale, François, Sarry, Julien, Tadi, Némuel, Woloszyn, Florent, and Fabre, Stéphane

Published
2024
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2. A pangenome graph reference of 30 chicken genomes allows genotyping of large and complex structural variants

Author

Rice, Edward S., Alberdi, Antton, Alfieri, James, Athrey, Giridhar, Balacco, Jennifer R., Bardou, Philippe, Blackmon, Heath, Charles, Mathieu, Cheng, Hans H., Fedrigo, Olivier, Fiddaman, Steven R., Formenti, Giulio, Frantz, Laurent A. F., Gilbert, M. Thomas P., Hearn, Cari J., Jarvis, Erich D., Klopp, Christophe, Marcos, Sofia, Mason, Andrew S., Velez-Irizarry, Deborah, Xu, Luohao, and Warren, Wesley C.

Published
2023
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6. Uncovering structural variants in Creole cattle from Guadeloupe and their impact on environmental adaptation through whole genome sequencing.

Author

Ben-Jemaa, Slim, Boussaha, Mekki, Mandonnet, Nathalie, Bardou, Philippe, and Naves, Michel

Subjects
WHOLE genome sequencing, BODY temperature regulation, CHROMOSOMAL rearrangement, MUSCLE tone, GENETIC variation, TRANSFER RNA, OLFACTORY receptors
Abstract

Structural variants play an important role in evolutionary processes. Besides, they constitute a large source of inter individual genetic variation that might represent a major factor in the aetiology of complex, multifactorial traits. Their importance in adaptation is becoming increasingly evident in literature. Yet, the characterization of the genomic landscape of structural variants in local breeds remains scarce to date. Herein, we investigate patterns and gene annotation of structural variants in the Creole cattle from Guadeloupe breed using whole genome sequences from 23 bulls representative of the population. In total, we detected 32821 ascertained SV defining 15258 regions, representing ~ 17% of the Creole cattle genome. Among these, 6639 regions have not been previously reported in the Database of Genomic Variants archive. Average number of structural variants detected per individual in the studied population is in the same order of magnitude of that observed in indicine populations and higher than that reported in taurine breeds. We observe an important within-individual variability where approximately half of the detected structural variants have low frequency (MAF < 0.25). Most of the detected structural variants (55%) occurred in intergenic regions. Genic structural variants overlapped with 7793 genes and the predicted effect of most of them is ranked as "modifier". Among the structural variants that were predicted to have a high functional impact on the protein, a 5.5 Kb in length, highly frequent deletion on chromosome 2, affects ALPI, a gene associated with the interaction between gut microbiota and host immune system. The 6639 newly identified structural variants regions include three deletions and three duplications shared by more than 80% of individuals that are significantly enriched for genes related to tRNA threonylcarbamoyladenosine metabolic process, important for temperature adaptation in thermophilic organisms, therefore suggesting a potential role in the thermotolerance of Creole cattle from Guadeloupe cattle to tropical climate. Overall, highly frequent structural variants that are specific to the Creole cattle population encompass olfactory receptor and immunity genes as well as genes involved in muscle tone, muscle development and contraction. Beyond mapping and characterizing structural variants in the Creole cattle from Guadeloupe breed, this study provides valuable information for a better understanding of the potential role of chromosomal rearrangements in adaptive traits in cattle. [ABSTRACT FROM AUTHOR]

Published
2024
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7. The BioMart community portal: an innovative alternative to large, centralized data repositories.

Author

Smedley, Damian, Haider, Syed, Durinck, Steffen, Pandini, Luca, Provero, Paolo, Allen, James, Arnaiz, Olivier, Awedh, Mohammad Hamza, Baldock, Richard, Barbiera, Giulia, Bardou, Philippe, Beck, Tim, Blake, Andrew, Bonierbale, Merideth, Brookes, Anthony J, Bucci, Gabriele, Buetti, Iwan, Burge, Sarah, Cabau, Cédric, Carlson, Joseph W, Chelala, Claude, Chrysostomou, Charalambos, Cittaro, Davide, Collin, Olivier, Cordova, Raul, Cutts, Rosalind J, Dassi, Erik, Di Genova, Alex, Djari, Anis, Esposito, Anthony, Estrella, Heather, Eyras, Eduardo, Fernandez-Banet, Julio, Forbes, Simon, Free, Robert C, Fujisawa, Takatomo, Gadaleta, Emanuela, Garcia-Manteiga, Jose M, Goodstein, David, Gray, Kristian, Guerra-Assunção, José Afonso, Haggarty, Bernard, Han, Dong-Jin, Han, Byung Woo, Harris, Todd, Harshbarger, Jayson, Hastings, Robert K, Hayes, Richard D, Hoede, Claire, Hu, Shen, Hu, Zhi-Liang, Hutchins, Lucie, Kan, Zhengyan, Kawaji, Hideya, Keliet, Aminah, Kerhornou, Arnaud, Kim, Sunghoon, Kinsella, Rhoda, Klopp, Christophe, Kong, Lei, Lawson, Daniel, Lazarevic, Dejan, Lee, Ji-Hyun, Letellier, Thomas, Li, Chuan-Yun, Lio, Pietro, Liu, Chu-Jun, Luo, Jie, Maass, Alejandro, Mariette, Jerome, Maurel, Thomas, Merella, Stefania, Mohamed, Azza Mostafa, Moreews, Francois, Nabihoudine, Ibounyamine, Ndegwa, Nelson, Noirot, Céline, Perez-Llamas, Cristian, Primig, Michael, Quattrone, Alessandro, Quesneville, Hadi, Rambaldi, Davide, Reecy, James, Riba, Michela, Rosanoff, Steven, Saddiq, Amna Ali, Salas, Elisa, Sallou, Olivier, Shepherd, Rebecca, Simon, Reinhard, Sperling, Linda, Spooner, William, Staines, Daniel M, Steinbach, Delphine, Stone, Kevin, Stupka, Elia, Teague, Jon W, Dayem Ullah, Abu Z, Wang, Jun, and Ware, Doreen

Subjects
Humans, Neoplasms, Proteomics, Genomics, Internet, Database Management Systems, Developmental Biology, Environmental Sciences, Biological Sciences, Information and Computing Sciences
Abstract

The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Published
2015

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

Author

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

Published
2019
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10. Fourth Report on Chicken Genes and Chromosomes 2022

Author

Smith, Jacqueline, Alfieri, James M., Anthony, Nick, Arensburger, Peter, Athrey, Giridhar N., Balacco, Jennifer, Balic, Adam, Bardou, Philippe, Barela, Paul, Bigot, Yves, Blackmon, Heath, Borodin, Pavel M., Carroll, Rachel, Casono, Meya C., Charles, Mathieu, Cheng, Hans, Chiodi, Maddie, Cigan, Lacey, Coghill, Lyndon M., Crooijmans, Richard, Das, Neelabja, Davey, Sean, Davidian, Asya, Degalez, Fabien, Dekkers, Jack M., Derks, Martijn, Diack, Abigail B., Djikeng, Appolinaire, Drechsler, Yvonne, Dyomin, Alexander, Fedrigo, Olivier, Fiddaman, Steven R., Formenti, Giulio, Frantz, Laurent A.F., Fulton, Janet E., Gaginskaya, Elena, Galkina, Svetlana, Gallardo, Rodrigo A., Geibel, Johannes, Gheyas, Almas A., Godinez, Cyrill John P., Goodell, Ashton, Graves, Jennifer A.M., Griffin, Darren K., Haase, Bettina, Han, Jian Lin, Hanotte, Olivier, Henderson, Lindsay J., Hou, Zhuo Cheng, Howe, Kerstin, Huynh, Lan, Ilatsia, Evans, Jarvis, Erich D., Johnson, Sarah M., Kaufman, Jim, Kelly, Terra, Kemp, Steve, Kern, Colin, Keroack, Jacob H., Klopp, Christophe, Lagarrigue, Sandrine, Lamont, Susan J., Lange, Margaret, Lanke, Anika, Larkin, Denis M., Larson, Greger, Layos, John King N., Lebrasseur, Ophélie, Malinovskaya, Lyubov P., Martin, Rebecca J., Cerezo, Maria Luisa Martin, Mason, Andrew S., McCarthy, Fiona M., McGrew, Michael J., Mountcastle, Jacquelyn, Muhonja, Christine Kamidi, Muir, William, Muret, Kévin, Murphy, Terence D., Ng'ang'a, Ismael, Nishibori, Masahide, O'Connor, Rebecca E., Ogugo, Moses, Okimoto, Ron, Ouko, Ochieng, Patel, Hardip R., Perini, Francesco, Pigozzi, María Ines, Potter, Krista C., Price, Peter D., Reimer, Christian, Rice, Edward S., Rocos, Nicolas, Rogers, Thea F., Saelao, Perot, Schauer, Jens, Schnabel, Robert D., Schneider, Valerie A., Simianer, Henner, Smith, Adrian, Stevens, Mark P., Stiers, Kyle, Tiambo, Christian Keambou, Tixier-Boichard, Michele, Torgasheva, Anna A., Tracey, Alan, Tregaskes, Clive A., Vervelde, Lonneke, Wang, Ying, Warren, Wesley C., Waters, Paul D., Webb, David, Weigend, Steffen, Wolc, Anna, Wright, Alison E., Wright, Dominic, Wu, Zhou, Yamagata, Masahito, Yang, Chentao, Yin, Zhong Tao, Young, Michelle C., Zhang, Guojie, Zhao, Bingru, Zhou, Huaijun, Smith, Jacqueline, Alfieri, James M., Anthony, Nick, Arensburger, Peter, Athrey, Giridhar N., Balacco, Jennifer, Balic, Adam, Bardou, Philippe, Barela, Paul, Bigot, Yves, Blackmon, Heath, Borodin, Pavel M., Carroll, Rachel, Casono, Meya C., Charles, Mathieu, Cheng, Hans, Chiodi, Maddie, Cigan, Lacey, Coghill, Lyndon M., Crooijmans, Richard, Das, Neelabja, Davey, Sean, Davidian, Asya, Degalez, Fabien, Dekkers, Jack M., Derks, Martijn, Diack, Abigail B., Djikeng, Appolinaire, Drechsler, Yvonne, Dyomin, Alexander, Fedrigo, Olivier, Fiddaman, Steven R., Formenti, Giulio, Frantz, Laurent A.F., Fulton, Janet E., Gaginskaya, Elena, Galkina, Svetlana, Gallardo, Rodrigo A., Geibel, Johannes, Gheyas, Almas A., Godinez, Cyrill John P., Goodell, Ashton, Graves, Jennifer A.M., Griffin, Darren K., Haase, Bettina, Han, Jian Lin, Hanotte, Olivier, Henderson, Lindsay J., Hou, Zhuo Cheng, Howe, Kerstin, Huynh, Lan, Ilatsia, Evans, Jarvis, Erich D., Johnson, Sarah M., Kaufman, Jim, Kelly, Terra, Kemp, Steve, Kern, Colin, Keroack, Jacob H., Klopp, Christophe, Lagarrigue, Sandrine, Lamont, Susan J., Lange, Margaret, Lanke, Anika, Larkin, Denis M., Larson, Greger, Layos, John King N., Lebrasseur, Ophélie, Malinovskaya, Lyubov P., Martin, Rebecca J., Cerezo, Maria Luisa Martin, Mason, Andrew S., McCarthy, Fiona M., McGrew, Michael J., Mountcastle, Jacquelyn, Muhonja, Christine Kamidi, Muir, William, Muret, Kévin, Murphy, Terence D., Ng'ang'a, Ismael, Nishibori, Masahide, O'Connor, Rebecca E., Ogugo, Moses, Okimoto, Ron, Ouko, Ochieng, Patel, Hardip R., Perini, Francesco, Pigozzi, María Ines, Potter, Krista C., Price, Peter D., Reimer, Christian, Rice, Edward S., Rocos, Nicolas, Rogers, Thea F., Saelao, Perot, Schauer, Jens, Schnabel, Robert D., Schneider, Valerie A., Simianer, Henner, Smith, Adrian, Stevens, Mark P., Stiers, Kyle, Tiambo, Christian Keambou, Tixier-Boichard, Michele, Torgasheva, Anna A., Tracey, Alan, Tregaskes, Clive A., Vervelde, Lonneke, Wang, Ying, Warren, Wesley C., Waters, Paul D., Webb, David, Weigend, Steffen, Wolc, Anna, Wright, Alison E., Wright, Dominic, Wu, Zhou, Yamagata, Masahito, Yang, Chentao, Yin, Zhong Tao, Young, Michelle C., Zhang, Guojie, Zhao, Bingru, and Zhou, Huaijun

Abstract

Chicken Genomic Diversity consortium: large-scale genomics to unravel the origins and adaptations of chickens

Published
2023

11. Chicken Genomic Diversity consortium: large-scale genomics to unravel the origins and adaptations of chickens

Author

Fiddaman, Steven R, Klopp, Christophe, Charles, Mathieu, Bardou, Philippe, Lebrasseur, Ophélie, Derks, Martijn F. L., Schauer, Jens, Reimer, Christian, Geibel, Johannes, Gheyas, Almas, Smith, Adrian L., Schnabel, Robert, Cerezo, Maria Luisa Martin, Nishibori, Masahide, Godinez, Cyrill John P., Layos, John King N., Alfieri, James M., Blackmon, Heath, Athrey, Giridhar N., Larson, Greger, Ng’ang’a, Ismael, Muir, William, Lange, Margaret, Wright, Dominic, Cheng, Hans H, Simianer, Henner, Weigend, Steffen, Warren, Wesley, Crooijmans, Richard P. M. A., Hanotte, Olivier, Smith, Jacqueline, Tixier-Boichard, Michele, and Frantz, Laurent Af

Abstract

On October 25-26, 2019, a satellite meeting devoted to the preparation of a Chicken Genome Diversity Consortium was organised after the 11th European Symposium of Poultry Genetics in Prague. Researchers involved in chicken genomics from Europe, Africa and China, discussed the objectives of such a consortium with some presenting their data. However, the technical aspects of how to share and jointly analyse the data were not finalized, nor was the funding model for the cost of data storage and computation. In 2021, an opportunity arose with the call for projects of the SuperMUC computing cluster of the Leibniz-Rechenzentrum in Germany. A new consortium of scientists re-launched the discussion to establish a project with the aim to explore how the high-throughput genomics age can be harnessed to answer evolutionary questions surrounding the chicken. The FARMGENOMIC project (23826) was accepted for funding in autumn 2021, gathering around 20 members from 10 institutions in Europe, North America, and Africa. This newly formed Chicken Genomic Diversity consortium brings together members from a variety of disciplines, including genomics, palaeogenetics, animal breeding, immunology, organismal biology, evolutionary biology, and archaeology. Central to the consortium are the concepts of inclusivity and openness – all data are to be made available to all members of the consortium, and later distributed to the wider community, and collaborations between groups are fostered and actively encouraged. It is hoped this state-of-the-art resource, curated in-house by bioinformaticians, will enable the community to answer previously intractable questions in chicken evolution.

Published
2023
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12. An open-source tool to assess the carbon footprint of research

Author

Mariette, Jérôme, primary, Blanchard, Odile, additional, Berné, Olivier, additional, Aumont, Olivier, additional, Carrey, Julian, additional, Ligozat, AnneLaure, additional, Lellouch, Emmanuel, additional, Roche, Philippe-Emmanuel, additional, Guennebaud, Gaël, additional, Thanwerdas, Joel, additional, Bardou, Philippe, additional, Salin, Gérald, additional, Maigne, Elise, additional, Servan, Sophie, additional, and Ben-Ari, Tamara, additional

Published
2022
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13. Y-chromosomal haplotypes in domestic and wild goats reveal ancient paternal bottlenecks and recent introgressions

Author

Vargoats Consortium, Nijman, Isaäc, Rosen, Benjamin, Faraut, Thomas, Bardou, Philippe, Cumer, Tristan, Daly, Kevin, Zheng, Zhuqing, Yu, Jiang, Lei, Chuzhao, Cai, Yudong, Bâlteanu, Valentin, Barfield, Diana, Beard, Hailey, Berger, Beate, Blichfeldt, Thor, Boink, Geert, Carolan, Sean, Colli, Licia, Cubric Curik, Vlatka, Drew, Louise, Droegemueller, Cord, and Kantanen, Juha

Subjects
Y chromosome, Haplotypes, Domestic and wild goats
Abstract

By its paternal transmission, Y-chromosomal haplotypes are sensitive markers of population history and male-mediated introgression. Previous studies have identified in domestic goats four major Y chromosomal haplotypes Y1A, Y1B, Y2A and Y2B with a marked geographic differentiation and several regional variants. In this study we combine whole-genome sequences (WGSs) of 392 male goats from 64 modern breeds and 7 wild goat species generated by the Vargoats goat genome project, 136 entries in the Short-Read Archive and genotypes of diagnostic SNPs of several modern and ancient samples. We identified single-copy male- specific SNPs in four scaffolds, containing SRY, ZFY, DBY with SSX3Y and UTY, and USP9Y with UMN2001, respectively. Phylogenetic analyses indicated haplogroups corresponding to Y1B, Y2A and Y2B, respectively, but Y1A is split into Y1AA and Y1AB. All these haplogroups were detected in ancient DNA samples from southeast Europe. In different branches of the tree, the haplotypes from domestic goats, Iranian bezoars and Anatolian bezoars, respectively, have separate positions. Notably, the Anatolian haplotypes are near the roots of the tree or of subtrees, suggesting that the Iranian bezoars are closer to the wild ancestors of domestic sheep. Haplogroup distributions for 150 domestic breeds indicates on all three continents ancient paternal population bottlenecks, especially during the migration into northern Europe. In addition, sharing of haplogroups reveals male-mediated introgression of Boer goat into Uganda, Kenya, Tanzania, Malawi and Zimbabwe, and of European goats into the native Korean goat population. This study illustrates the power of the Y-chromosomal variation for the reconstructing the history of mammalian species with a wide geographic range.

Published
2022

16. MINTIA: a metagenomic INserT integrated assembly and annotation tool

Author

Bardou, Philippe, Laguerre, Sandrine, Maman Haddad, Sarah, Legoueix Rodriguez, Sabrina, Laville, Elisabeth, Dumon, Claire, Potocki-Veronese, Gabrielle, Klopp, Christophe, 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), Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Toulouse White Biotechnology (TWB), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), 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)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), 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)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRAE)

Subjects
[SDV.BIO]Life Sciences [q-bio]/Biotechnology, Bioinformatics, Activity-based metagenomics, Functional annotation, [SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology, Biodiversity, Software package, Biochemistry, Microbiology, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Medicine, Functional metagenomics, Biotechnology, Metagenomic fosmid, Sequence assembly
Abstract

International audience; The earth harbors trillions of bacterial species adapted to very diverse ecosystems thanks to specific metabolic function acquisition. Most of the genes responsible for these functions belong to uncultured bacteria and are still to be discovered. Functional metagenomics based on activity screening is a classical way to retrieve these genes from microbiomes. This approach is based on the insertion of large metagenomic DNA fragments into a vector and transformation of a host to express heterologous genes. Metagenomic libraries are then screened for activities of interest, and the metagenomic DNA inserts of active clones are extracted to be sequenced and analysed to identify genes that are responsible for the detected activity. Hundreds of metagenomics sequences found using this strategy have already been published in public databases. Here we present the MINTIA software package enabling biologists to easily generate and analyze large metagenomic sequence sets, retrieved after activity-based screening. It filters reads, performs assembly, removes cloning vector, annotates open reading frames and generates user friendly reports as well as files ready for submission to international sequence repositories. The software package can be downloaded from https://github.com/Bios4Biol/MINTIA .

Published
2021
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17. A Nonsense Variant in CCDC65 Gene Causes Respiratory Failure Associated with Increased Lamb Mortality in French Lacaune Dairy Sheep

Author

Ben Braiek, Maxime, primary, Moreno-Romieux, Carole, additional, Allain, Charlotte, additional, Bardou, Philippe, additional, Bordes, Arnaud, additional, Debat, Frédéric, additional, Drögemüller, Cord, additional, Plisson-Petit, Florence, additional, Portes, David, additional, Sarry, Julien, additional, Tadi, Némuel, additional, Woloszyn, Florent, additional, and Fabre, Stéphane, additional

Published
2021
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18. Additional file 9 of VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Author

Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, St��fan, Orvain, C��line, Palhi��re, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Masiga, Clet Wandui, Pompanon, Fran��ois, Rosen, Benjamin D., Stella, Alessandra, Van Tassell, Curtis P., and Tosser-Klopp, Gwenola

Abstract

Additional file 9: Figure S5. Sex assignment for the 1159 goats sampled in VarGoats. Representation of the ratio of read number between the autosomes and the X chromosome and the read number on the Y chromosome for each animal to determine its sex. The horizontal bar corresponds to the threshold of 25 reads from the Y scaffold allowing to differentiate males from females.

Published
2021
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19. Additional file 6 of VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Author

Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, St��fan, Orvain, C��line, Palhi��re, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Masiga, Clet Wandui, Pompanon, Fran��ois, Rosen, Benjamin D., Stella, Alessandra, Van Tassell, Curtis P., and Tosser-Klopp, Gwenola

Abstract

Additional file 6: Figure S4. Tranche plot produced by VariantRecalibrator for SNPs. Description: Partition of the call sets into quality tranches. The tranches correspond to certain levels of sensitivity relative to the truth sets (the highest tranche corresponds to a high accuracy call set but with the lowest value of sensitivity).

Published
2021
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20. Additional file 3 of VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Author

Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, St��fan, Orvain, C��line, Palhi��re, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Masiga, Clet Wandui, Pompanon, Fran��ois, Rosen, Benjamin D., Stella, Alessandra, Van Tassell, Curtis P., and Tosser-Klopp, Gwenola

Abstract

Additional file 3: Figure S1. Distribution of the concordance rates. Concordance rates (CR) between sequence variants and 50 k genotypes for 457 individuals. The figure shows a clear disruption in the distribution of CR, thus we found it easy and relevant to discard the samples below a concordance rate of 70% between sequence and chip SNP data.

Published
2021
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21. Additional file 5 of VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Author

Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, St��fan, Orvain, C��line, Palhi��re, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Masiga, Clet Wandui, Pompanon, Fran��ois, Rosen, Benjamin D., Stella, Alessandra, Van Tassell, Curtis P., and Tosser-Klopp, Gwenola

Abstract

Additional file 5: Figure S3. Pairwise comparisons of the annotations chosen in VQSR for InDels. Description: Modeling report generated by GATK VariantRecalibrator for every pairwise combination of annotations used (QD, DP, FS, MQRankSum, ReadPosRankSum and SOR), with a 2D projection of the Gaussian mixture model.

Published
2021
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22. 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

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

Published
2021
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23. Analysis of Polycerate Mutants Reveals the Evolutionary Co-option of HOXD1 for Horn Patterning in Bovidae

Author

Allais-Bonnet, Aurélie, Hintermann, Aurélie, Deloche, Marie-Christine, Cornette, Raphaël, Bardou, Philippe, Naval-Sanchez, Marina, Pinton, Alain, Haruda, Ashleigh, Grohs, Cécile, Zakany, Jozsef, Bigi, Daniele, Medugorac, Ivica, Putelat, Olivier, Greyvenstein, Ockert, Hadfield, Tracy, Jemaa, Slim Ben, Bunevski, Gjoko, Menzi, Fiona, Hirter, Nathalie, Paris, Julia M, Hedges, John, Palhiere, Isabelle, Rupp, Rachel, Lenstra, Johannes A, Gidney, Louisa, Lesur, Joséphine, Schafberg, Renate, Stache, Michael, Wandhammer, Marie-Dominique, Arbogast, Rose-Marie, Guintard, Claude, Blin, Amandine, Boukadiri, Abdelhak, Rivière, Julie, Esquerré, Diane, Donnadieu, Cécile, Danchin-Burge, Coralie, Reich, Coralie M, Riley, David G, van Marle-Koster, Este, Cockett, Noelle, Hayes, Benjamin J, Drögemüller, Cord, Kijas, James, Pailhoux, Eric, Tosser-Klopp, Gwenola, Duboule, Denis, Capitan, Aurélien, Allais-Bonnet, Aurélie, Hintermann, Aurélie, Deloche, Marie-Christine, Cornette, Raphaël, Bardou, Philippe, Naval-Sanchez, Marina, Pinton, Alain, Haruda, Ashleigh, Grohs, Cécile, Zakany, Jozsef, Bigi, Daniele, Medugorac, Ivica, Putelat, Olivier, Greyvenstein, Ockert, Hadfield, Tracy, Jemaa, Slim Ben, Bunevski, Gjoko, Menzi, Fiona, Hirter, Nathalie, Paris, Julia M, Hedges, John, Palhiere, Isabelle, Rupp, Rachel, Lenstra, Johannes A, Gidney, Louisa, Lesur, Joséphine, Schafberg, Renate, Stache, Michael, Wandhammer, Marie-Dominique, Arbogast, Rose-Marie, Guintard, Claude, Blin, Amandine, Boukadiri, Abdelhak, Rivière, Julie, Esquerré, Diane, Donnadieu, Cécile, Danchin-Burge, Coralie, Reich, Coralie M, Riley, David G, van Marle-Koster, Este, Cockett, Noelle, Hayes, Benjamin J, Drögemüller, Cord, Kijas, James, Pailhoux, Eric, Tosser-Klopp, Gwenola, Duboule, Denis, and Capitan, Aurélien

Published
2021

24. VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Author

Agence Nationale de la Recherche (France), Région Occitanie / Pyrénées-Méditerranée, Ministère de l’Enseignement supérieur et de la Recherche (France), Biotechnology and Biological Sciences Research Council (UK), Bill & Melinda Gates Foundation, Department for International Development (UK), Center for Tropical Studies and Conservation (US), University of Edinburgh, Scottish Government's Rural and Environment Science and Analytical Services, Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, Stefan, Orvain, Céline, Palhière, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Wandui Masiga, Clet, Pompanon, François, Rosen, Benjamin D., Stella, Alessandra, Van Tassell, Curtis P., Tosser-Klopp, Gwenola, VarGoats Consortium, Agence Nationale de la Recherche (France), Région Occitanie / Pyrénées-Méditerranée, Ministère de l’Enseignement supérieur et de la Recherche (France), Biotechnology and Biological Sciences Research Council (UK), Bill & Melinda Gates Foundation, Department for International Development (UK), Center for Tropical Studies and Conservation (US), University of Edinburgh, Scottish Government's Rural and Environment Science and Analytical Services, Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, Stefan, Orvain, Céline, Palhière, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Wandui Masiga, Clet, Pompanon, François, Rosen, Benjamin D., Stella, Alessandra, Van Tassell, Curtis P., Tosser-Klopp, Gwenola, and VarGoats Consortium

Abstract

[Background]: Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra., [Findings]: A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin., [Conclusions]: We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies.

Published
2021

25. Analysis of Polycerate Mutants Reveals the Evolutionary Co-option of HOXD1 for Horn Patterning in Bovidae

Author

Allais-Bonnet, Aurélie, primary, Hintermann, Aurélie, additional, Deloche, Marie-Christine, additional, Cornette, Raphaël, additional, Bardou, Philippe, additional, Naval-Sanchez, Marina, additional, Pinton, Alain, additional, Haruda, Ashleigh, additional, Grohs, Cécile, additional, Zakany, Jozsef, additional, Bigi, Daniele, additional, Medugorac, Ivica, additional, Putelat, Olivier, additional, Greyvenstein, Ockert, additional, Hadfield, Tracy, additional, Jemaa, Slim Ben, additional, Bunevski, Gjoko, additional, Menzi, Fiona, additional, Hirter, Nathalie, additional, Paris, Julia M, additional, Hedges, John, additional, Palhiere, Isabelle, additional, Rupp, Rachel, additional, Lenstra, Johannes A, additional, Gidney, Louisa, additional, Lesur, Joséphine, additional, Schafberg, Renate, additional, Stache, Michael, additional, Wandhammer, Marie-Dominique, additional, Arbogast, Rose-Marie, additional, Guintard, Claude, additional, Blin, Amandine, additional, Boukadiri, Abdelhak, additional, Rivière, Julie, additional, Esquerré, Diane, additional, Donnadieu, Cécile, additional, Danchin-Burge, Coralie, additional, Reich, Coralie M, additional, Riley, David G, additional, Marle-Koster, Este van, additional, Cockett, Noelle, additional, Hayes, Benjamin J, additional, Drögemüller, Cord, additional, Kijas, James, additional, Pailhoux, Eric, additional, Tosser-Klopp, Gwenola, additional, Duboule, Denis, additional, and Capitan, Aurélien, additional

Published
2021
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26. The Medicago genome provides insight into the evolution of rhizobial symbioses

Author

Young, Nevin D., Debellé, Frédéric, Oldroyd, Giles E. D., Geurts, Rene, Cannon, Steven B., Udvardi, Michael K., Benedito, Vagner A., Mayer, Klaus F. X., Gouzy, Jérôme, Schoof, Heiko, Van de Peer, Yves, Proost, Sebastian, Cook, Douglas R., Meyers, Blake C., Spannagl, Manuel, Cheung, Foo, De Mita, Stéphane, Krishnakumar, Vivek, Gundlach, Heidrun, Zhou, Shiguo, Mudge, Joann, Bharti, Arvind K., Murray, Jeremy D., Naoumkina, Marina A., Rosen, Benjamin, Silverstein, Kevin A. T., Tang, Haibao, Rombauts, Stephane, Zhao, Patrick X., Zhou, Peng, Barbe, Valérie, Bardou, Philippe, Bechner, Michael, Bellec, Arnaud, Berger, Anne, Bergès, Hélène, Bidwell, Shelby, Bisseling, Ton, Choisne, Nathalie, Couloux, Arnaud, Denny, Roxanne, Deshpande, Shweta, Dai, Xinbin, Doyle, Jeff J., Dudez, Anne-Marie, Farmer, Andrew D., Fouteau, Stéphanie, Franken, Carolien, Gibelin, Chrystel, Gish, John, Goldstein, Steven, González, Alvaro J., Green, Pamela J., Hallab, Asis, Hartog, Marijke, Hua, Axin, Humphray, Sean J., Jeong, Dong-Hoon, Jing, Yi, Jöcker, Anika, Kenton, Steve M., Kim, Dong-Jin, Klee, Kathrin, Lai, Hongshing, Lang, Chunting, Lin, Shaoping, Macmil, Simone L., Magdelenat, Ghislaine, Matthews, Lucy, McCorrison, Jamison, Monaghan, Erin L., Mun, Jeong-Hwan, Najar, Fares Z., Nicholson, Christine, Noirot, Céline, O’Bleness, Majesta, Paule, Charles R., Poulain, Julie, Prion, Florent, Qin, Baifang, Qu, Chunmei, Retzel, Ernest F., Riddle, Claire, Sallet, Erika, Samain, Sylvie, Samson, Nicolas, Sanders, Iryna, Saurat, Olivier, Scarpelli, Claude, Schiex, Thomas, Segurens, Béatrice, Severin, Andrew J., Sherrier, Janine D., Shi, Ruihua, Sims, Sarah, Singer, Susan R., Sinharoy, Senjuti, Sterck, Lieven, Viollet, Agnès, Wang, Bing-Bing, Wang, Keqin, Wang, Mingyi, Wang, Xiaohong, Warfsmann, Jens, Weissenbach, Jean, White, Doug D., White, Jim D., Wiley, Graham B., Wincker, Patrick, Xing, Yanbo, Yang, Limei, Yao, Ziyun, Ying, Fu, Zhai, Jixian, Zhou, Liping, Zuber, Antoine, Dénarié, Jean, Dixon, Richard A., May, Gregory D., Schwartz, David C., Rogers, Jane, Quétier, Francis, Town, Christopher D., and Roe, Bruce A.

Published
2011
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28. Interest of Genotyping-by-Sequencing technologies as an alternative to low density SNP chips for genomic selection in layer chicken

Author

Herry, Florian, Herault, Frédéric, Picard Druet, David, Bardou, Philippe, Eché, Camille, Varenne, Amandine, Burlot, Thierry, Le Roy, Pascale, Allais, Sophie, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Novogen, 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, GeT PlaGe, Genotoul, 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), 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-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)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), 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 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], Université Toulouse III - Paul Sabatier (UT3), and 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)

Subjects
Imputation accuracy, génotypage, [SDV]Life Sciences [q-bio], Genotyping-by-Sequencing, Genomic selection, Low density panel, Genomic evaluation accuracy, laying hen, évaluation génomique, sélection génomique, poule pondeuse, précision de sélection, genomic selection
Abstract

To reduce the cost of genomic selection, low density SNP chip can be used in combination with imputation for genotyping the selection candidates instead of using high density (HD) SNP chip. Concurrently, next-generation sequencing (NGS) techniques has been increasingly used in livestock species but remain expensive to be routinely used in selection. An alternative and costefficient solution is the Genotyping by Genome Reducing and Sequencing (GGRS) techniques to sequence only a fraction of the genome by using restriction enzymes. This approach was simulated from sequences of 1027 individuals in a pure layer line, using four enzymes (EcoRI, TaqI, AvaII and PstI). Imputation accuracy on HD genotypes was assessed as the mean correlation between true and imputed genotypes. Egg weight, egg shell color, egg shell strength and albumen height were evaluated with single-step GBLUP methodology. The impact of imputation errors on the genomic estimated breeding values (GEBV) was also investigated.AvaII or PstI led to the detection of more than 10K SNPs in common with the HD SNP chip resulting in imputation accuracy higher than 0.97. The impact of imputation errors on the ranking of the selection candidates was reduced with Spearman correlation (between GEBV calculated on true and imputed genotypes) higher than 0.97 for AvaII and PstI. Finally, the GGRS approach can be an interesting alternative to low density SNP chip for genomic selection. However, with real data, heterogeneity between individuals with missing data has to be taken into account.

Published
2019

29. VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity.

Author

Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, Stéfan, Orvain, Céline, Palhière, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Masiga, Clet Wandui, Pompanon, François, and Rosen, Benjamin D.

Subjects
GOATS, GENOME-wide association studies, GOAT breeds, GENETIC variation, GENETIC distance, SINGLE nucleotide polymorphisms
Abstract

Background: Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra. Findings: A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin. Conclusions: We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies. [ABSTRACT FROM AUTHOR]

Published
2021
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30. MOESM1 of Multi-species annotation of transcriptome and chromatin structure in domesticated animals

Author

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

Abstract

Additional file 1 Additional file 1: Supplementary figures (S1-S26) and tables (S1-S15).

Published
2019
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31. Livestock genome annotation: transcriptome and chromatin structure profiling in cattle, goat, chicken and pig

Author

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

Subjects
Functional annotation, Livestock, RNA-seq, ATAC-seq, Hi-C
Abstract

Functional 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 aims at profiling the landscape of transcription (RNA-seq) and chromatin accessibility and conformation (ATAC-seq and 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). Standardized protocols were applied to produce transcriptome and chromatin datasets for the four species. RNA-seq assays allowed to considerably extend the available catalog of protein-coding and non-coding transcripts. Gene expression profiles were consistent with known metabolic/immune functions and revealed differentially expressed transcripts with unknown function, including new lncRNAs in syntenic regions. The majority of ATAC-seq peaks of chromatin accessibility mapped to putative regulatory regions, with an enrichment of predicted transcription factor binding sites in differentially accessible peaks. Hi-C provided the first set of genome-wide maps of three-dimensional interactions across livestock and showed consistency with results from gene expression and chromatin accessibility in topological compartments of the genomes. We report the first multi-species and multi-assay genome annotation results obtained by a FAANG pilot project. The global consistency between gene expression and chromatin structure data in these four livestock species adds up to previous findings in model animals. Overall, these results emphasize the value of FAANG for the research on domesticated animals and strengthen the importance of future meta-analyses of the reference datasets being generated by this community on different species.

Published
2018

32. Profiling the landscape of transcription, chromatin accessibility and chromosome conformation of cattle, pig, chicken and goat genomes [FAANG pilot project]

Author

Foissac, Sylvain, Djebali Quelen, Sarah, ACLOQUE, Hervé, Bardou, Philippe, Blanc, Fany, Cabau, Cédric, Derrien, Thomas, Drouet, Françoise, Esquerre, Diane, Fabre, Stéphane, Gaspin, Christine, GONZALEZ, Ignacio, Goubil, Adeline, Klopp, Christophe, Laurent, Fabrice, Marthey, Sylvain, Marti-Marimon, Maria, Mompart, Florence, Munyard, Kylie, Muret, Kévin, Pollet, Sophie, Quéré, Pascale, Rau, Andrea, Robelin, David, San Cristobal, Magali, Tixier-Boichard, Michele, Tosser-Klopp, Gwenola, Villa-Vialaneix, Nathalie, Vincent-Naulleau, Silvia, Zytnicki, Matthias, Pinard - Van Der Laan, Marie-Helene, Lagarrigue, Sandrine, Giuffra, Elisabetta, Institut National de la Recherche Agronomique - INRA (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), 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-École nationale supérieure agronomique de Toulouse [ENSAT], Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Infectiologie Animale et Santé Publique - IASP (Nouzilly, France), Institut National de la Recherche Agronomique (INRA), Dynamiques Forestières dans l'Espace Rural (DYNAFOR), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-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), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), FR-AgENCODE, Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Infectiologie et Santé Publique (UMR ISP), Institut National de la Recherche Agronomique (INRA)-Université de Tours (UT), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), 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 Institut National de la Recherche Agronomique (INRA)-Université de Tours

Subjects
multispecies, Hi-C, [SDV]Life Sciences [q-bio], Multispecies, Biologie animale, Functional annotation of animal genome (FAANG), functional annotation of animal genome (FAANG), ATAC-seq, RNA-seq
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. An extensive collection of stored samples from other tissues is available for further use (FAANG Biosamples ‘FR-AGENCODE’). From each of two males and two females per species (pig, cattle, goat, chicken), strand-oriented RNA-seq and chromatin accessibility ATAC-seq assays were performed on liver tissue and on two T-cell types (CD3+CD4+&CD3+CD8+) sorted from blood (mammals) or spleen (chicken). Chromosome Conformation Capture (in situ Hi-C) was also carried out on liver. Sequencing reads from the 3 assays were processed using standard processing pipelines. While most (50–70%) RNA-seq reads mapped to annotated exons, thousands of novel transcripts and genes were found, including extensions of annotated protein-coding genes and new lncRNAs (see abstract #69857). Consistency of ATAC-seq results was confirmed by the significant proportion of called peaks in promoter regions (36–66%) and by the specific accumulation pattern of peaks around gene starts (TSS) v. gene ends (TTS). Principal Component Analyses for RNA-seq (based on quantified gene expression) and ATAC-seq (based on quantified chromatin accessibility) highlighted clusters characterised by cell type and sex in all species. From Hi-C data, we generated 40kb-resolution interaction maps, profiled a genome-wide Directionality Index and identified from 4,100 (chicken) to 12,100 (pig) topologically-associating do- mains (TADs). Correlations were reported between RNA-seq and ATAC-seq results (see abstract #71581). In summary, we present here an overview of the first multi-species and -tissue annotations of chromatin accessibility and genome architecture related to gene expression for farm animals.

Published
2017

34. Genome wide association analysis on semen volume and milk yield using different strategies of imputation to whole genome sequence in French dairy goats.

Author

Talouarn, Estelle, Bardou, Philippe, Palhière, Isabelle, Oget, Claire, Clément, Virginie, The VarGoats Consortium, Tosser-Klopp, Gwenola, Rupp, Rachel, and Robert-Granié, Christèle

Subjects
*GOATS, *MILK yield, *SEMEN analysis, *GOAT diseases, *NUCLEOTIDE sequencing, *GENOMES, *SINGLE nucleotide polymorphisms
Abstract

Background: Goats were domesticated 10,500 years ago to supply humans with useful resources. Since then, specialized breeds that are adapted to their local environment have been developed and display specific genetic profiles. The VarGoats project is a 1000 genomes resequencing program designed to cover the genetic diversity of the Capra genus. In this study, our main objective was to assess the use of sequence data to detect genomic regions associated with traits of interest in French Alpine and Saanen breeds. Results: Direct imputation from the GoatSNP50 BeadChip genotypes to sequence level was investigated in these breeds using FImpute and different reference panels: within-breed, all Capra hircus sequenced individuals, European goats and French mainland goats. The best results were obtained with the French goat panel with allele and genotype concordance rates reaching 0.86 and 0.75 in the Alpine and 0.86 and 0.73 in the Saanen breed respectively. Mean correlations tended to be low in both breeds due to the high proportion of variants with low frequencies. For association analysis, imputation was performed using FImpute for 1129 French Alpine and Saanen males using within-breed and French panels on 23,338,436 filtered variants. The association results of both imputation scenarios were then compared. In Saanen goats, a large region on chromosome 19 was significantly linked to semen volume and milk yield in both scenarios. Significant variants for milk yield were annotated for 91 genes on chromosome 19 in Saanen goats. For semen volume, the annotated genes include YBOX2 which is related to azoospermia or oligospermia in other species. New signals for milk yield were detected on chromosome 2 in Alpine goats and on chromosome 5 in Saanen goats when using a multi-breed panel. Conclusion: Even with very small reference populations, an acceptable imputation quality can be achieved in French dairy goats. GWAS on imputed sequences confirmed the existence of QTLs and identified new regions of interest in dairy goats. Adding identified candidates to a genotyping array and sequencing more individuals might corroborate the involvement of identified regions while removing potential imputation errors. [ABSTRACT FROM AUTHOR]

Published
2020
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35. Author Correction: A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content

Author

Martin, Pauline, primary, Palhière, Isabelle, additional, Maroteau, Cyrielle, additional, Bardou, Philippe, additional, Canale-Tabet, Kamila, additional, Sarry, Julien, additional, Woloszyn, Florent, additional, Bertrand-Michel, Justine, additional, Racke, Ines, additional, Besir, Hüseyin, additional, Rupp, Rachel, additional, and Tosser-Klopp, Gwenola, additional

Published
2018
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36. E-formations en bioinformatique

Author

Maman Haddad, SARAH, Malipier, Frédérique, Herry, Catherine, Bardou, Philippe, 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, Service formation permanente nationale, and Institut National de la Recherche Agronomique (INRA)

Subjects
[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], bioinformatique e-learning, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2016

38. Additional file 8: of Characterization of an extensive rainbow trout miRNA transcriptome by next generation sequencing

Author

Juanchich, Amelie, Bardou, Philippe, RuĂŠ, Olivier, Jean-Charles Gabillard, Gaspin, Christine, Bobe, Julien, and Guiguen, Yann

Subjects
fungi
Abstract

Webpage available for each miRNAs. All 3271 loci have a webpage describing miRNA features, structure and reporting the different isoforms produced by each loci. (PDF 490 kb)

Published
2016
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39. Additional file 1: of Characterization of an extensive rainbow trout miRNA transcriptome by next generation sequencing

Author

Juanchich, Amelie, Bardou, Philippe, RuĂŠ, Olivier, Jean-Charles Gabillard, Gaspin, Christine, Bobe, Julien, and Guiguen, Yann

Subjects
heterocyclic compounds
Abstract

Samples list and read counts. The list of the 38 samples that have been used in the study. The samples used for the tissue expression analysis are in bold. (PPT 91 kb)

Published
2016
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40. Additional file 3: of Characterization of an extensive rainbow trout miRNA transcriptome by next generation sequencing

Author

Juanchich, Amelie, Bardou, Philippe, RuĂŠ, Olivier, Jean-Charles Gabillard, Gaspin, Christine, Bobe, Julien, and Guiguen, Yann

Abstract

sRNA-seq reads length repartition in the 38 samples. Each panel represents the read length distribution of the 38 RNA samples. The box highlights the gonadal tissues. Each numbers are in reference to the corresponding sample in additional file 1. Highlighted samples (black box with numbers 2, 26, 27, 28 and 29) are gonadal samples. (PPT 727 kb)

Published
2016
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41. Additional file 5: of Characterization of an extensive rainbow trout miRNA transcriptome by next generation sequencing

Author

Juanchich, Amelie, Bardou, Philippe, RuĂŠ, Olivier, Jean-Charles Gabillard, Gaspin, Christine, Bobe, Julien, and Guiguen, Yann

Abstract

qPCR validation of 9 miRNAs. Each panel represents expression of a miRNA in a set of tissues. Nine miRNAs were checked by qPCR: miR-15, miR-29, miR-101, miR-122, miR-126, miR-148, miR-202, miR-221 and miR-301. qPCR expression of each miRNA was normalized using 18S expression. (PPT 112 kb)

Published
2016
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42. A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content

Author

Martin, Pauline, primary, Palhière, Isabelle, additional, Maroteau, Cyrielle, additional, Bardou, Philippe, additional, Canale-Tabet, Kamila, additional, Sarry, Julien, additional, Woloszyn, Florent, additional, Bertrand-Michel, Justine, additional, Racke, Ines, additional, Besir, Hüseyin, additional, Rupp, Rachel, additional, and Tosser-Klopp, Gwenola, additional

Published
2017
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43. Genome-Wide Identification of the Mutation Underlying Fleece Variation and Discriminating Ancestral Hairy Species from Modern Woolly Sheep

Author

Demars, Julie, primary, Cano, Margarita, additional, Drouilhet, Laurence, additional, Plisson-Petit, Florence, additional, Bardou, Philippe, additional, Fabre, Stéphane, additional, Servin, Bertrand, additional, Sarry, Julien, additional, Woloszyn, Florent, additional, Mulsant, Philippe, additional, Foulquier, Didier, additional, Carrière, Fabien, additional, Aletru, Mathias, additional, Rodde, Nathalie, additional, Cauet, Stéphane, additional, Bouchez, Olivier, additional, Pirson, Maarten, additional, Tosser-Klopp, Gwenola, additional, and Allain, Daniel, additional

Published
2017
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45. Towards a high density SNP International Goat Chip

Author

Tosser-Klopp, Gwenola, Jiken, Abdullah Johari, Bardou, Philippe, Cabau, Cédric, Dehais, Patrice, Faraut, Thomas, Heuven, Henri, Klopp, Christophe, Martin, Patrice, Moreno-Romieux, Carole, Mulsant, Philippe, Pailhoux, Eric, Palhiere, Isabelle, Rupp, Rachel, Sarry, Julien, Wang, J., Wang, W., Yu, Tun-Ping, Zhang, Wenguang, 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), Strategic Livestock Research Centre, Malaysian Agricultural Research Development Institute, Utrecht Universtiy, Faculty of Veterinary Medicine, Unité de Biométrie et Intelligence Artificielle (UBIA), Institut National de la Recherche Agronomique (INRA), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Station d'Amélioration Génétique des Animaux (SAGA), Biologie du Développement et Reproduction (BDR), BGI-Shenzhen, Bejing Genome Institute, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences [Beijing] (CAS)-Chinese Academy of Sciences [Beijing] (CAS), DNA Landmarks, caprinisp, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, AgroParisTech-Institut National de la Recherche Agronomique (INRA), 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), and Beijing Genomics Institute [Shenzhen] (BGI)

Subjects
[SDV]Life Sciences [q-bio], goat, snp
Abstract

According to FAO, in 2009, the world population of goats was estimated to be around 868 million animals and was steadily growing either in developed or developing countries. Goat breeds include dairy, meat and fiber breeds, are adapted to a wide range of breeding conditions and have thus a great economic importance. However, they benefit from fewer genomic research tools, as compared to cattle or sheep. Recently, several research projects were conducted in different laboratories to improve goat genome knowledge and develop new research tools. Goat genome was sequenced de novo (see W. Zhang presentation, this meeting), a RH panel was developed (see B. Sayre presentation, this meeting). In France, a collaborative SNP discovery research programme, CAPRISNIP, was launched by INRA and breeding organisations CAPGENES and APIS-GENE in 2009. At least two other SNP discovery projects were launched in other countries, using either reduced representations of the genome (University of Utrecht, Netherlands) or whole genome de novo sequencing (Malaysian Agricultural Research and Development Institute). RNA-sequencing projects conducted by different research groups at INRA may also be a valuable source for SNP discovery and annotation. We propose to federate these several SNP discovery and RNA-seq research programmes within the frame of the International Goat Genome Consortium in order to develop an international versatile high density SNP chip. Collection of the data is underway. SNP detection will be done in early 2011. The work plan includes i) alignment of the different sequences on de novo assembled goat contigs ii) ordering of contigs on ovine or bovine genome reference sequence iii)SNP discovery and annotation iv) small set SNP test generation v) determination of the SNP panel vi) raw data access to all partners. A first international chip order is planned for autumn 2011.

Published
2011

46. rnaspace.org - a web application for noncoding RNA identification

Author

Cros, Marie-Josée, de Monte, Antoine, Mariette, Jérôme, Bardou, Philippe, Gautheret, Daniel, Touzet, Helene, Gaspin, Christine, Unité de Biométrie et Intelligence Artificielle (UBIA), Institut National de la Recherche Agronomique (INRA), Université des Sciences et Technologies (Lille 1) (USTL), Algorithms for large scale sequence analysis (SEQUOIA2), Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria), Plateforme Bio-Informatique - Génotoul, 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, Plateforme SIGENAE, Université Paris-Sud - Paris 11 (UP11), Unité de Biométrie et Intelligence Artificielle (ancêtre de MIAT) (UBIA), Université de Lille, Sciences et Technologies, 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]Life Sciences [q-bio], [INFO]Computer Science [cs], [MATH]Mathematics [math], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2010

47. Jflow: a workflow management system for web applications

Author

Mariette, Jérôme, primary, Escudié, Frédéric, additional, Bardou, Philippe, additional, Nabihoudine, Ibouniyamine, additional, Noirot, Céline, additional, Trotard, Marie-Stéphane, additional, Gaspin, Christine, additional, and Klopp, Christophe, additional

Published
2015
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48. Design and Characterization of a 52K SNP Chip for Goats

Author

Amills i Eras, Marcel, Tosser-Klopp, Gwenola, Bardou, Philippe, Bouchez, Olivier, Cabau, Cédric, Crooijmans, Richard, Dong, Yang, Donnadieu-Tonon, Cécile, Eggen, André, Heuven, Henri C. M., Jamli, Saadiah, Johari Jiken, Abdullah, Klopp, Christophe, Lawley, Cynthia T., McEwan, John, Martin, Patrice, Moreno, Carole R., Mulsant, Philippe, Nabihoudine, Ibouniyamine, Pailhoux, Eric, Palhière, Isabelle, Rupp, Rachel, Sarry, Julien, Sayre, Brian L., Tircazes, Aurélie, Wang, Jun, Wang, Wen, Zhang, Wenguang, International Goat Genome Consortium, Amills i Eras, Marcel, Tosser-Klopp, Gwenola, Bardou, Philippe, Bouchez, Olivier, Cabau, Cédric, Crooijmans, Richard, Dong, Yang, Donnadieu-Tonon, Cécile, Eggen, André, Heuven, Henri C. M., Jamli, Saadiah, Johari Jiken, Abdullah, Klopp, Christophe, Lawley, Cynthia T., McEwan, John, Martin, Patrice, Moreno, Carole R., Mulsant, Philippe, Nabihoudine, Ibouniyamine, Pailhoux, Eric, Palhière, Isabelle, Rupp, Rachel, Sarry, Julien, Sayre, Brian L., Tircazes, Aurélie, Wang, Jun, Wang, Wen, Zhang, Wenguang, and International Goat Genome Consortium

Abstract

The success of Genome Wide Association Studies in the discovery of sequence variation linked to complex traits in humans has increased interest in high throughput SNP genotyping assays in livestock species. Primary goals are QTL detection and genomic selection. The purpose here was design of a 50-60,000 SNP chip for goats. The success of a moderate density SNP assay depends on reliable bioinformatic SNP detection procedures, the technological success rate of the SNP design, even spacing of SNPs on the genome and selection of Minor Allele Frequencies (MAF) suitable to use in diverse breeds. Through the federation of three SNP discovery projects consolidated as the International Goat Genome Consortium, we have identified approximately twelve million high quality SNP variants in the goat genome stored in a database together with their biological and technical characteristics. These SNPs were identified within and between six breeds (meat, milk and mixed): Alpine, Boer, Creole, Katjang, Saanen and Savanna, comprising a total of 97 animals. Whole genome and Reduced Representation Library sequences were aligned on >10 kb scaffolds of the de novo goat genome assembly. The 60,000 selected SNPs, evenly spaced on the goat genome, were submitted for oligo manufacturing (Illumina, Inc) and published in dbSNP along with flanking sequences and map position on goat assemblies (i.e. scaffolds and pseudo-chromosomes), sheep genome V2 and cattle UMD3.1 assembly. Ten breeds were then used to validate the SNP content and 52,295 loci could be successfully genotyped and used to generate a final cluster file. The combined strategy of using mainly whole genome Next Generation Sequencing and mapping on a contig genome assembly, complemented with Illumina design tools proved to be efficient in producing this GoatSNP50 chip. Advances in use of molecular markers are expected to accelerate goat genomic studies in coming years.

Published
2014

50. RNAbrowse: RNA-Seq De Novo Assembly Results Browser

Author

Mariette, Jérôme, primary, Noirot, Céline, additional, Nabihoudine, Ibounyamine, additional, Bardou, Philippe, additional, Hoede, Claire, additional, Djari, Anis, additional, Cabau, Cédric, additional, and Klopp, Christophe, additional

Published
2014
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