%0 Journal Article %J Front Immunol %D 2024 %T Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. %A Niarakis, Anna %A Ostaszewski, Marek %A Mazein, Alexander %A Kuperstein, Inna %A Kutmon, Martina %A Gillespie, Marc E %A Funahashi, Akira %A Acencio, Marcio Luis %A Hemedan, Ahmed %A Aichem, Michael %A Klein, Karsten %A Czauderna, Tobias %A Burtscher, Felicia %A Yamada, Takahiro G %A Hiki, Yusuke %A Hiroi, Noriko F %A Hu, Finterly %A Pham, Nhung %A Ehrhart, Friederike %A Willighagen, Egon L %A Valdeolivas, Alberto %A Dugourd, Aurélien %A Messina, Francesco %A Esteban-Medina, Marina %A Peña-Chilet, Maria %A Rian, Kinza %A Soliman, Sylvain %A Aghamiri, Sara Sadat %A Puniya, Bhanwar Lal %A Naldi, Aurélien %A Helikar, Tomáš %A Singh, Vidisha %A Fernández, Marco Fariñas %A Bermudez, Viviam %A Tsirvouli, Eirini %A Montagud, Arnau %A Noël, Vincent %A Ponce-de-Leon, Miguel %A Maier, Dieter %A Bauch, Angela %A Gyori, Benjamin M %A Bachman, John A %A Luna, Augustin %A Piñero, Janet %A Furlong, Laura I %A Balaur, Irina %A Rougny, Adrien %A Jarosz, Yohan %A Overall, Rupert W %A Phair, Robert %A Perfetto, Livia %A Matthews, Lisa %A Rex, Devasahayam Arokia Balaya %A Orlic-Milacic, Marija %A Gomez, Luis Cristobal Monraz %A De Meulder, Bertrand %A Ravel, Jean Marie %A Jassal, Bijay %A Satagopam, Venkata %A Wu, Guanming %A Golebiewski, Martin %A Gawron, Piotr %A Calzone, Laurence %A Beckmann, Jacques S %A Evelo, Chris T %A D'Eustachio, Peter %A Schreiber, Falk %A Saez-Rodriguez, Julio %A Dopazo, Joaquin %A Kuiper, Martin %A Valencia, Alfonso %A Wolkenhauer, Olaf %A Kitano, Hiroaki %A Barillot, Emmanuel %A Auffray, Charles %A Balling, Rudi %A Schneider, Reinhard %K Computer Simulation %K COVID-19 %K drug repositioning %K Humans %K SARS-CoV-2 %K Systems biology %X

INTRODUCTION: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.

METHODS: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.

RESULTS: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.

DISCUSSION: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

%B Front Immunol %V 14 %P 1282859 %8 2023 %G eng %R 10.3389/fimmu.2023.1282859 %0 Journal Article %J Front Genet %D 2023 %T Editorial: Critical assessment of massive data analysis (CAMDA) annual conference 2021. %A Łabaj, Paweł P %A Dopazo, Joaquin %A Xiao, Wenzhong %A Kreil, David P %B Front Genet %V 14 %P 1154398 %8 2023 %G eng %R 10.3389/fgene.2023.1154398 %0 Journal Article %J Hum Mol Genet %D 2022 %T Novel genes and sex differences in COVID-19 severity. %A Cruz, Raquel %A Almeida, Silvia Diz-de %A Heredia, Miguel López %A Quintela, Inés %A Ceballos, Francisco C %A Pita, Guillermo %A Lorenzo-Salazar, José M %A González-Montelongo, Rafaela %A Gago-Domínguez, Manuela %A Porras, Marta Sevilla %A Castaño, Jair Antonio Tenorio %A Nevado, Julián %A Aguado, Jose María %A Aguilar, Carlos %A Aguilera-Albesa, Sergio %A Almadana, Virginia %A Almoguera, Berta %A Alvarez, Nuria %A Andreu-Bernabeu, Álvaro %A Arana-Arri, Eunate %A Arango, Celso %A Arranz, María J %A Artiga, Maria-Jesus %A Baptista-Rosas, Raúl C %A Barreda-Sánchez, María %A Belhassen-Garcia, Moncef %A Bezerra, Joao F %A Bezerra, Marcos A C %A Boix-Palop, Lucía %A Brión, Maria %A Brugada, Ramón %A Bustos, Matilde %A Calderón, Enrique J %A Carbonell, Cristina %A Castano, Luis %A Castelao, Jose E %A Conde-Vicente, Rosa %A Cordero-Lorenzana, M Lourdes %A Cortes-Sanchez, Jose L %A Corton, Marta %A Darnaude, M Teresa %A De Martino-Rodríguez, Alba %A Campo-Pérez, Victor %A Bustamante, Aranzazu Diaz %A Domínguez-Garrido, Elena %A Luchessi, André D %A Eirós, Rocío %A Sanabria, Gladys Mercedes Estigarribia %A Fariñas, María Carmen %A Fernández-Robelo, Uxía %A Fernández-Rodríguez, Amanda %A Fernández-Villa, Tania %A Gil-Fournier, Belén %A Gómez-Arrue, Javier %A Álvarez, Beatriz González %A Quirós, Fernan Gonzalez Bernaldo %A González-Peñas, Javier %A Gutiérrez-Bautista, Juan F %A Herrero, María José %A Herrero-Gonzalez, Antonio %A Jimenez-Sousa, María A %A Lattig, María Claudia %A Borja, Anabel Liger %A Lopez-Rodriguez, Rosario %A Mancebo, Esther %A Martín-López, Caridad %A Martín, Vicente %A Martinez-Nieto, Oscar %A Martinez-Lopez, Iciar %A Martinez-Resendez, Michel F %A Martinez-Perez, Ángel %A Mazzeu, Juliana A %A Macías, Eleuterio Merayo %A Minguez, Pablo %A Cuerda, Victor Moreno %A Silbiger, Vivian N %A Oliveira, Silviene F %A Ortega-Paino, Eva %A Parellada, Mara %A Paz-Artal, Estela %A Santos, Ney P C %A Pérez-Matute, Patricia %A Perez, Patricia %A Pérez-Tomás, M Elena %A Perucho, Teresa %A Pinsach-Abuin, Mel Lina %A Pompa-Mera, Ericka N %A Porras-Hurtado, Gloria L %A Pujol, Aurora %A León, Soraya Ramiro %A Resino, Salvador %A Fernandes, Marianne R %A Rodríguez-Ruiz, Emilio %A Rodriguez-Artalejo, Fernando %A Rodriguez-Garcia, José A %A Ruiz-Cabello, Francisco %A Ruiz-Hornillos, Javier %A Ryan, Pablo %A Soria, José Manuel %A Souto, Juan Carlos %A Tamayo, Eduardo %A Tamayo-Velasco, Alvaro %A Taracido-Fernandez, Juan Carlos %A Teper, Alejandro %A Torres-Tobar, Lilian %A Urioste, Miguel %A Valencia-Ramos, Juan %A Yáñez, Zuleima %A Zarate, Ruth %A Nakanishi, Tomoko %A Pigazzini, Sara %A Degenhardt, Frauke %A Butler-Laporte, Guillaume %A Maya-Miles, Douglas %A Bujanda, Luis %A Bouysran, Youssef %A Palom, Adriana %A Ellinghaus, David %A Martínez-Bueno, Manuel %A Rolker, Selina %A Amitrano, Sara %A Roade, Luisa %A Fava, Francesca %A Spinner, Christoph D %A Prati, Daniele %A Bernardo, David %A García, Federico %A Darcis, Gilles %A Fernández-Cadenas, Israel %A Holter, Jan Cato %A Banales, Jesus M %A Frithiof, Robert %A Duga, Stefano %A Asselta, Rosanna %A Pereira, Alexandre C %A Romero-Gómez, Manuel %A Nafría-Jiménez, Beatriz %A Hov, Johannes R %A Migeotte, Isabelle %A Renieri, Alessandra %A Planas, Anna M %A Ludwig, Kerstin U %A Buti, Maria %A Rahmouni, Souad %A Alarcón-Riquelme, Marta E %A Schulte, Eva C %A Franke, Andre %A Karlsen, Tom H %A Valenti, Luca %A Zeberg, Hugo %A Richards, Brent %A Ganna, Andrea %A Boada, Mercè %A Rojas, Itziar %A Ruiz, Agustín %A Sánchez, Pascual %A Real, Luis Miguel %A Guillén-Navarro, Encarna %A Ayuso, Carmen %A González-Neira, Anna %A Riancho, José A %A Rojas-Martinez, Augusto %A Flores, Carlos %A Lapunzina, Pablo %A Carracedo, Ángel %X

Here we describe the results of a genome-wide study conducted in 11 939 COVID-19 positive cases with an extensive clinical information that were recruited from 34 hospitals across Spain (SCOURGE consortium). In sex-disaggregated genome-wide association studies for COVID-19 hospitalization, genome-wide significance (p < 5x10-8) was crossed for variants in 3p21.31 and 21q22.11 loci only among males (p = 1.3x10-22 and p = 8.1x10-12, respectively), and for variants in 9q21.32 near TLE1 only among females (p = 4.4x10-8). In a second phase, results were combined with an independent Spanish cohort (1598 COVID-19 cases and 1068 population controls), revealing in the overall analysis two novel risk loci in 9p13.3 and 19q13.12, with fine-mapping prioritized variants functionally associated with AQP3 (p = 2.7x10-8) and ARHGAP33 (p = 1.3x10-8), respectively. The meta-analysis of both phases with four European studies stratified by sex from the Host Genetics Initiative confirmed the association of the 3p21.31 and 21q22.11 loci predominantly in males and replicated a recently reported variant in 11p13 (ELF5, p = 4.1x10-8). Six of the COVID-19 HGI discovered loci were replicated and an HGI-based genetic risk score predicted the severity strata in SCOURGE. We also found more SNP-heritability and larger heritability differences by age (<60 or ≥ 60 years) among males than among females. Parallel genome-wide screening of inbreeding depression in SCOURGE also showed an effect of homozygosity in COVID-19 hospitalization and severity and this effect was stronger among older males. In summary, new candidate genes for COVID-19 severity and evidence supporting genetic disparities among sexes are provided.

%B Hum Mol Genet %8 2022 Jun 16 %G eng %R 10.1093/hmg/ddac132 %0 Journal Article %J Mol Syst Biol %D 2021 %T COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. %A Ostaszewski, Marek %A Niarakis, Anna %A Mazein, Alexander %A Kuperstein, Inna %A Phair, Robert %A Orta-Resendiz, Aurelio %A Singh, Vidisha %A Aghamiri, Sara Sadat %A Acencio, Marcio Luis %A Glaab, Enrico %A Ruepp, Andreas %A Fobo, Gisela %A Montrone, Corinna %A Brauner, Barbara %A Frishman, Goar %A Monraz Gómez, Luis Cristóbal %A Somers, Julia %A Hoch, Matti %A Kumar Gupta, Shailendra %A Scheel, Julia %A Borlinghaus, Hanna %A Czauderna, Tobias %A Schreiber, Falk %A Montagud, Arnau %A Ponce de Leon, Miguel %A Funahashi, Akira %A Hiki, Yusuke %A Hiroi, Noriko %A Yamada, Takahiro G %A Dräger, Andreas %A Renz, Alina %A Naveez, Muhammad %A Bocskei, Zsolt %A Messina, Francesco %A Börnigen, Daniela %A Fergusson, Liam %A Conti, Marta %A Rameil, Marius %A Nakonecnij, Vanessa %A Vanhoefer, Jakob %A Schmiester, Leonard %A Wang, Muying %A Ackerman, Emily E %A Shoemaker, Jason E %A Zucker, Jeremy %A Oxford, Kristie %A Teuton, Jeremy %A Kocakaya, Ebru %A Summak, Gökçe Yağmur %A Hanspers, Kristina %A Kutmon, Martina %A Coort, Susan %A Eijssen, Lars %A Ehrhart, Friederike %A Rex, Devasahayam Arokia Balaya %A Slenter, Denise %A Martens, Marvin %A Pham, Nhung %A Haw, Robin %A Jassal, Bijay %A Matthews, Lisa %A Orlic-Milacic, Marija %A Senff Ribeiro, Andrea %A Rothfels, Karen %A Shamovsky, Veronica %A Stephan, Ralf %A Sevilla, Cristoffer %A Varusai, Thawfeek %A Ravel, Jean-Marie %A Fraser, Rupsha %A Ortseifen, Vera %A Marchesi, Silvia %A Gawron, Piotr %A Smula, Ewa %A Heirendt, Laurent %A Satagopam, Venkata %A Wu, Guanming %A Riutta, Anders %A Golebiewski, Martin %A Owen, Stuart %A Goble, Carole %A Hu, Xiaoming %A Overall, Rupert W %A Maier, Dieter %A Bauch, Angela %A Gyori, Benjamin M %A Bachman, John A %A Vega, Carlos %A Grouès, Valentin %A Vazquez, Miguel %A Porras, Pablo %A Licata, Luana %A Iannuccelli, Marta %A Sacco, Francesca %A Nesterova, Anastasia %A Yuryev, Anton %A de Waard, Anita %A Turei, Denes %A Luna, Augustin %A Babur, Ozgun %A Soliman, Sylvain %A Valdeolivas, Alberto %A Esteban-Medina, Marina %A Peña-Chilet, Maria %A Rian, Kinza %A Helikar, Tomáš %A Puniya, Bhanwar Lal %A Modos, Dezso %A Treveil, Agatha %A Olbei, Marton %A De Meulder, Bertrand %A Ballereau, Stephane %A Dugourd, Aurélien %A Naldi, Aurélien %A Noël, Vincent %A Calzone, Laurence %A Sander, Chris %A Demir, Emek %A Korcsmaros, Tamas %A Freeman, Tom C %A Augé, Franck %A Beckmann, Jacques S %A Hasenauer, Jan %A Wolkenhauer, Olaf %A Wilighagen, Egon L %A Pico, Alexander R %A Evelo, Chris T %A Gillespie, Marc E %A Stein, Lincoln D %A Hermjakob, Henning %A D'Eustachio, Peter %A Saez-Rodriguez, Julio %A Dopazo, Joaquin %A Valencia, Alfonso %A Kitano, Hiroaki %A Barillot, Emmanuel %A Auffray, Charles %A Balling, Rudi %A Schneider, Reinhard %K Antiviral Agents %K Computational Biology %K Computer Graphics %K COVID-19 %K Cytokines %K Data Mining %K Databases, Factual %K Gene Expression Regulation %K Host Microbial Interactions %K Humans %K Immunity, Cellular %K Immunity, Humoral %K Immunity, Innate %K Lymphocytes %K Metabolic Networks and Pathways %K Myeloid Cells %K Protein Interaction Mapping %K SARS-CoV-2 %K Signal Transduction %K Software %K Transcription Factors %K Viral Proteins %X

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

%B Mol Syst Biol %V 17 %P e10387 %8 2021 10 %G eng %N 10 %1 https://www.ncbi.nlm.nih.gov/pubmed/34664389?dopt=Abstract %R 10.15252/msb.202110387 %0 Journal Article %J Cancers (Basel) %D 2021 %T Mutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development. %A Millán-Esteban, David %A Peña-Chilet, Maria %A García-Casado, Zaida %A Manrique-Silva, Esperanza %A Requena, Celia %A Bañuls, José %A Lopez-Guerrero, Jose Antonio %A Rodríguez-Hernández, Aranzazu %A Traves, Víctor %A Dopazo, Joaquin %A Virós, Amaya %A Kumar, Rajiv %A Nagore, Eduardo %X

According to the divergent pathway model, cutaneous melanoma comprises a nevogenic group with a propensity to melanocyte proliferation and another one associated with cumulative solar damage (CSD). While characterized clinically and epidemiologically, the differences in the molecular profiles between the groups have remained primarily uninvestigated. This study has used a custom gene panel and bioinformatics tools to investigate the potential molecular differences in a thoroughly characterized cohort of 119 melanoma patients belonging to nevogenic and CSD groups. We found that the nevogenic melanomas had a restricted set of mutations, with the prominently mutated gene being . The CSD melanomas, in contrast, showed mutations in a diverse group of genes that included , , , and . We thus provide evidence that nevogenic and CSD melanomas constitute different biological entities and highlight the need to explore new targeted therapies.

%B Cancers (Basel) %V 13 %8 2021 Oct 18 %G eng %N 20 %R 10.3390/cancers13205219 %0 Journal Article %J Nature Genetics %D 2021 %T The NCI Genomic Data Commons %A Heath, Allison P. %A Ferretti, Vincent %A Agrawal, Stuti %A An, Maksim %A Angelakos, James C. %A Arya, Renuka %A Bajari, Rosita %A Baqar, Bilal %A Barnowski, Justin H. B. %A Burt, Jeffrey %A Catton, Ann %A Chan, Brandon F. %A Chu, Fay %A Cullion, Kim %A Davidsen, Tanja %A Do, Phuong-My %A Dompierre, Christian %A Ferguson, Martin L. %A Fitzsimons, Michael S. %A Ford, Michael %A Fukuma, Miyuki %A Gaheen, Sharon %A Ganji, Gajanan L. %A Garcia, Tzintzuni I. %A George, Sameera S. %A Gerhard, Daniela S. %A Gerthoffert, Francois %A Gomez, Fauzi %A Han, Kang %A Hernandez, Kyle M. %A Issac, Biju %A Jackson, Richard %A Jensen, Mark A. %A Joshi, Sid %A Kadam, Ajinkya %A Khurana, Aishmit %A Kim, Kyle M. J. %A Kraft, Victoria E. %A Li, Shenglai %A Lichtenberg, Tara M. %A Lodato, Janice %A Lolla, Laxmi %A Martinov, Plamen %A Mazzone, Jeffrey A. %A Miller, Daniel P. %A Miller, Ian %A Miller, Joshua S. %A Miyauchi, Koji %A Murphy, Mark W. %A Nullet, Thomas %A Ogwara, Rowland O. %A Ortuño, Francisco M. %A Pedrosa, Jesús %A Pham, Phuong L. %A Popov, Maxim Y. %A Porter, James J. %A Powell, Raymond %A Rademacher, Karl %A Reid, Colin P. %A Rich, Samantha %A Rogel, Bessie %A Sahni, Himanso %A Savage, Jeremiah H. %A Schmitt, Kyle A. %A Simmons, Trevar J. %A Sislow, Joseph %A Spring, Jonathan %A Stein, Lincoln %A Sullivan, Sean %A Tang, Yajing %A Thiagarajan, Mathangi %A Troyer, Heather D. %A Wang, Chang %A Wang, Zhining %A West, Bedford L. %A Wilmer, Alex %A Wilson, Shane %A Wu, Kaman %A Wysocki, William P. %A Xiang, Linda %A Yamada, Joseph T. %A Yang, Liming %A Yu, Christine %A Yung, Christina K. %A Zenklusen, Jean Claude %A Zhang, Junjun %A Zhang, Zhenyu %A Zhao, Yuanheng %A Zubair, Ariz %A Staudt, Louis M. %A Grossman, Robert L. %B Nature Genetics %8 Oct-02-2022 %G eng %U http://www.nature.com/articles/s41588-021-00791-5 %! Nat Genet %R 10.1038/s41588-021-00791-5 %0 Journal Article %J Nat Commun %D 2021 %T Orchestrating and sharing large multimodal data for transparent and reproducible research. %A Mammoliti, Anthony %A Smirnov, Petr %A Nakano, Minoru %A Safikhani, Zhaleh %A Eeles, Christopher %A Seo, Heewon %A Nair, Sisira Kadambat %A Mer, Arvind S %A Smith, Ian %A Ho, Chantal %A Beri, Gangesh %A Kusko, Rebecca %A Lin, Eva %A Yu, Yihong %A Martin, Scott %A Hafner, Marc %A Haibe-Kains, Benjamin %X

Reproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner. To overcome these issues, we created a cloud-based platform called ORCESTRA ( orcestra.ca ), which provides a flexible framework for the reproducible processing of multimodal biomedical data. It enables processing of clinical, genomic and perturbation profiles of cancer samples through automated processing pipelines that are user-customizable. ORCESTRA creates integrated and fully documented data objects with persistent identifiers (DOI) and manages multiple dataset versions, which can be shared for future studies.

%B Nat Commun %V 12 %P 5797 %8 2021 10 04 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/34608132?dopt=Abstract %R 10.1038/s41467-021-25974-w %0 Journal Article %J Nat Med %D 2021 %T Reporting guidelines for human microbiome research: the STORMS checklist. %A Mirzayi, Chloe %A Renson, Audrey %A Zohra, Fatima %A Elsafoury, Shaimaa %A Geistlinger, Ludwig %A Kasselman, Lora J %A Eckenrode, Kelly %A van de Wijgert, Janneke %A Loughman, Amy %A Marques, Francine Z %A MacIntyre, David A %A Arumugam, Manimozhiyan %A Azhar, Rimsha %A Beghini, Francesco %A Bergstrom, Kirk %A Bhatt, Ami %A Bisanz, Jordan E %A Braun, Jonathan %A Bravo, Hector Corrada %A Buck, Gregory A %A Bushman, Frederic %A Casero, David %A Clarke, Gerard %A Collado, Maria Carmen %A Cotter, Paul D %A Cryan, John F %A Demmer, Ryan T %A Devkota, Suzanne %A Elinav, Eran %A Escobar, Juan S %A Fettweis, Jennifer %A Finn, Robert D %A Fodor, Anthony A %A Forslund, Sofia %A Franke, Andre %A Furlanello, Cesare %A Gilbert, Jack %A Grice, Elizabeth %A Haibe-Kains, Benjamin %A Handley, Scott %A Herd, Pamela %A Holmes, Susan %A Jacobs, Jonathan P %A Karstens, Lisa %A Knight, Rob %A Knights, Dan %A Koren, Omry %A Kwon, Douglas S %A Langille, Morgan %A Lindsay, Brianna %A McGovern, Dermot %A McHardy, Alice C %A McWeeney, Shannon %A Mueller, Noel T %A Nezi, Luigi %A Olm, Matthew %A Palm, Noah %A Pasolli, Edoardo %A Raes, Jeroen %A Redinbo, Matthew R %A Rühlemann, Malte %A Balfour Sartor, R %A Schloss, Patrick D %A Schriml, Lynn %A Segal, Eran %A Shardell, Michelle %A Sharpton, Thomas %A Smirnova, Ekaterina %A Sokol, Harry %A Sonnenburg, Justin L %A Srinivasan, Sujatha %A Thingholm, Louise B %A Turnbaugh, Peter J %A Upadhyay, Vaibhav %A Walls, Ramona L %A Wilmes, Paul %A Yamada, Takuji %A Zeller, Georg %A Zhang, Mingyu %A Zhao, Ni %A Zhao, Liping %A Bao, Wenjun %A Culhane, Aedin %A Devanarayan, Viswanath %A Dopazo, Joaquin %A Fan, Xiaohui %A Fischer, Matthias %A Jones, Wendell %A Kusko, Rebecca %A Mason, Christopher E %A Mercer, Tim R %A Sansone, Susanna-Assunta %A Scherer, Andreas %A Shi, Leming %A Thakkar, Shraddha %A Tong, Weida %A Wolfinger, Russ %A Hunter, Christopher %A Segata, Nicola %A Huttenhower, Curtis %A Dowd, Jennifer B %A Jones, Heidi E %A Waldron, Levi %K Computational Biology %K Dysbiosis %K Humans %K Microbiota %K Observational Studies as Topic %K Research Design %K Translational Science, Biomedical %X

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

%B Nat Med %V 27 %P 1885-1892 %8 2021 11 %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/34789871?dopt=Abstract %R 10.1038/s41591-021-01552-x %0 Journal Article %J Genes %D 2021 %T Schuurs–Hoeijmakers Syndrome (PACS1 Neurodevelopmental Disorder): Seven Novel Patients and a Review %A Tenorio-Castaño, Jair %A Morte, Beatriz %A Nevado, Julián %A Martínez-Glez, Víctor %A Santos-Simarro, Fernando %A García-Miñaur, Sixto %A Palomares-Bralo, María %A Pacio-Míguez, Marta %A Gómez, Beatriz %A Arias, Pedro %A Alcochea, Alba %A Carrión, Juan %A Arias, Patricia %A Almoguera, Berta %A López-Grondona, Fermina %A Lorda-Sanchez, Isabel %A Galán-Gómez, Enrique %A Valenzuela, Irene %A Méndez Perez, María %A Cuscó, Ivón %A Barros, Francisco %A Pié, Juan %A Ramos, Sergio %A Ramos, Feliciano %A Kuechler, Alma %A Tizzano, Eduardo %A Ayuso, Carmen %A Kaiser, Frank %A Pérez-Jurado, Luis %A Carracedo, Ángel %A Lapunzina, Pablo %B Genes %V 12 %P 738 %8 Jan-05-2021 %G eng %U https://www.mdpi.com/2073-4425/12/5/738https://www.mdpi.com/2073-4425/12/5/738/pdf %N 5 %! Genes %R 10.3390/genes12050738 %0 Journal Article %J EPMA J %D 2020 %T 10th Anniversary of the European Association for Predictive, Preventive and Personalised (3P) Medicine - EPMA World Congress Supplement 2020. %A Golubnitschaja, Olga %A Topolcan, Ondrej %A Kucera, Radek %A Costigliola, Vincenzo %X

In 2019, the EPMA celebrated its 10th anniversary at the 5th World Congress in Pilsen, Czech Republic. The history of the International Professional Network dedicated to Predictive, Preventive and Personalised Medicine (PPPM / 3PM) is rich in achievements. Facing the coronavirus COVID-19 pandemic it is getting evident globally that the predictive approach, targeted prevention and personalisation of medical services is the optimal paradigm in healthcare demonstrating the high potential to save lives and to benefit the society as a whole. The EPMA World Congress Supplement 2020 highlights advances in 3P medicine.

%B EPMA J %P 1-133 %8 2020 Aug 19 %G eng %R 10.1007/s13167-020-00206-1 %0 Journal Article %J Cell Syst %D 2020 %T Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics. %A Yang, Mi %A Petralia, Francesca %A Li, Zhi %A Li, Hongyang %A Ma, Weiping %A Song, Xiaoyu %A Kim, Sunkyu %A Lee, Heewon %A Yu, Han %A Lee, Bora %A Bae, Seohui %A Heo, Eunji %A Kaczmarczyk, Jan %A Stępniak, Piotr %A Warchoł, Michał %A Yu, Thomas %A Calinawan, Anna P %A Boutros, Paul C %A Payne, Samuel H %A Reva, Boris %A Boja, Emily %A Rodriguez, Henry %A Stolovitzky, Gustavo %A Guan, Yuanfang %A Kang, Jaewoo %A Wang, Pei %A Fenyö, David %A Saez-Rodriguez, Julio %K Crowdsourcing %K Female %K Genomics %K Humans %K Machine Learning %K Male %K Neoplasms %K Phosphoproteins %K Proteins %K Proteomics %K Transcriptome %X

Cancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer protein levels from other omics measurements, we leveraged crowdsourcing via the NCI-CPTAC DREAM proteogenomic challenge. We asked for methods to predict protein and phosphorylation levels from genomic and transcriptomic data in cancer patients. The best performance was achieved by an ensemble of models, including as predictors transcript level of the corresponding genes, interaction between genes, conservation across tumor types, and phosphosite proximity for phosphorylation prediction. Proteins from metabolic pathways and complexes were the best and worst predicted, respectively. The performance of even the best-performing model was modest, suggesting that many proteins are strongly regulated through translational control and degradation. Our results set a reference for the limitations of computational inference in proteogenomics. A record of this paper's transparent peer review process is included in the Supplemental Information.

%B Cell Syst %V 11 %P 186-195.e9 %8 2020 08 26 %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/32710834?dopt=Abstract %R 10.1016/j.cels.2020.06.013 %0 Journal Article %J Sci Data %D 2020 %T COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms. %A Ostaszewski, Marek %A Mazein, Alexander %A Gillespie, Marc E %A Kuperstein, Inna %A Niarakis, Anna %A Hermjakob, Henning %A Pico, Alexander R %A Willighagen, Egon L %A Evelo, Chris T %A Hasenauer, Jan %A Schreiber, Falk %A Dräger, Andreas %A Demir, Emek %A Wolkenhauer, Olaf %A Furlong, Laura I %A Barillot, Emmanuel %A Dopazo, Joaquin %A Orta-Resendiz, Aurelio %A Messina, Francesco %A Valencia, Alfonso %A Funahashi, Akira %A Kitano, Hiroaki %A Auffray, Charles %A Balling, Rudi %A Schneider, Reinhard %K Betacoronavirus %K Computational Biology %K Coronavirus Infections %K COVID-19 %K Databases, Factual %K Host Microbial Interactions %K Host-Pathogen Interactions %K Humans %K International Cooperation %K Models, Biological %K Pandemics %K Pneumonia, Viral %K SARS-CoV-2 %B Sci Data %V 7 %P 136 %8 2020 05 05 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/32371892?dopt=Abstract %R 10.1038/s41597-020-0477-8 %0 Journal Article %J F1000Res %D 2020 %T The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research. %A Salgado, David %A Armean, Irina M %A Baudis, Michael %A Beltran, Sergi %A Capella-Gutíerrez, Salvador %A Carvalho-Silva, Denise %A Dominguez Del Angel, Victoria %A Dopazo, Joaquin %A Furlong, Laura I %A Gao, Bo %A Garcia, Leyla %A Gerloff, Dietlind %A Gut, Ivo %A Gyenesei, Attila %A Habermann, Nina %A Hancock, John M %A Hanauer, Marc %A Hovig, Eivind %A Johansson, Lennart F %A Keane, Thomas %A Korbel, Jan %A Lauer, Katharina B %A Laurie, Steve %A Leskošek, Brane %A Lloyd, David %A Marqués-Bonet, Tomás %A Mei, Hailiang %A Monostory, Katalin %A Piñero, Janet %A Poterlowicz, Krzysztof %A Rath, Ana %A Samarakoon, Pubudu %A Sanz, Ferran %A Saunders, Gary %A Sie, Daoud %A Swertz, Morris A %A Tsukanov, Kirill %A Valencia, Alfonso %A Vidak, Marko %A Yenyxe González, Cristina %A Ylstra, Bauke %A Béroud, Christophe %K Computational Biology %K DNA Copy Number Variations %K High-Throughput Nucleotide Sequencing %K Humans %X

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While "High-Throughput" sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR's recently established with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

%B F1000Res %V 9 %8 2020 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/34367618?dopt=Abstract %& 1229 %R 10.12688/f1000research.24887.1 %0 Journal Article %J Lancet Oncol %D 2020 %T Pazopanib for treatment of typical solitary fibrous tumours: a multicentre, single-arm, phase 2 trial. %A Martin-Broto, Javier %A Cruz, Josefina %A Penel, Nicolas %A Le Cesne, Axel %A Hindi, Nadia %A Luna, Pablo %A Moura, David S %A Bernabeu, Daniel %A de Alava, Enrique %A Lopez-Guerrero, Jose Antonio %A Dopazo, Joaquin %A Peña-Chilet, Maria %A Gutierrez, Antonio %A Collini, Paola %A Karanian, Marie %A Redondo, Andres %A Lopez-Pousa, Antonio %A Grignani, Giovanni %A Diaz-Martin, Juan %A Marcilla, David %A Fernandez-Serra, Antonio %A Gonzalez-Aguilera, Cristina %A Casali, Paolo G %A Blay, Jean-Yves %A Stacchiotti, Silvia %K Aged %K Female %K Follow-Up Studies %K Humans %K Indazoles %K Male %K Middle Aged %K Neoplasm Metastasis %K Prognosis %K Prospective Studies %K Protein Kinase Inhibitors %K Pyrimidines %K Response Evaluation Criteria in Solid Tumors %K Solitary Fibrous Tumors %K Sulfonamides %K Survival Rate %X

BACKGROUND: Solitary fibrous tumour is an ultra-rare sarcoma, which encompasses different clinicopathological subgroups. The dedifferentiated subgroup shows an aggressive course with resistance to pazopanib, whereas in the malignant subgroup, pazopanib shows higher activity than in previous studies with chemotherapy. We designed a trial to test pazopanib activity in two different cohorts of solitary fibrous tumour: the malignant-dedifferentiated cohort, which was previously published, and the typical cohort, which is presented here.

METHODS: In this single-arm, phase 2 trial, adult patients (aged ≥18 years) diagnosed with confirmed metastatic or unresectable typical solitary fibrous tumour of any location, who had progressed in the previous 6 months (by Choi criteria or Response Evaluation Criteria in Solid Tumors [RECIST]) and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2 were enrolled at 11 tertiary hospitals in Italy, France, and Spain. Patients received pazopanib 800 mg once daily, taken orally, until progression, unacceptable toxicity, withdrawal of consent, non-compliance, or a delay in pazopanib administration of longer than 3 weeks. The primary endpoint was proportion of patients achieving an overall response measured by Choi criteria in patients who received at least 1 month of treatment with at least one radiological assessment. All patients who received at least one dose of the study drug were included in the safety analyses. This study is registered in ClinicalTrials.gov, NCT02066285, and with the European Clinical Trials Database, EudraCT 2013-005456-15.

FINDINGS: From June 26, 2014, to Dec 13, 2018, of 40 patients who were assessed, 34 patients were enrolled and 31 patients were included in the response analysis. Median follow-up was 18 months (IQR 14-34), and 18 (58%) of 31 patients had a partial response, 12 (39%) had stable disease, and one (3%) showed progressive disease according to Choi criteria and central review. The proportion of overall response based on Choi criteria was 58% (95% CI 34-69). There were no deaths caused by toxicity, and the most frequent adverse events were diarrhoea (18 [53%] of 34 patients), fatigue (17 [50%]), and hypertension (17 [50%]).

INTERPRETATION: To our knowledge, this is the first prospective trial of pazopanib for advanced typical solitary fibrous tumour. The manageable toxicity and activity shown by pazopanib in this cohort suggest that this drug could be considered as first-line treatment for advanced typical solitary fibrous tumour.

FUNDING: Spanish Group for Research on Sarcomas (GEIS), Italian Sarcoma Group (ISG), French Sarcoma Group (FSG), GlaxoSmithKline, and Novartis.

%B Lancet Oncol %V 21 %P 456-466 %8 2020 03 %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/32066540?dopt=Abstract %R 10.1016/S1470-2045(19)30826-5 %0 Journal Article %J Nature %D 2020 %T Transparency and reproducibility in artificial intelligence. %A Haibe-Kains, Benjamin %A Adam, George Alexandru %A Hosny, Ahmed %A Khodakarami, Farnoosh %A Waldron, Levi %A Wang, Bo %A McIntosh, Chris %A Goldenberg, Anna %A Kundaje, Anshul %A Greene, Casey S %A Broderick, Tamara %A Hoffman, Michael M %A Leek, Jeffrey T %A Korthauer, Keegan %A Huber, Wolfgang %A Brazma, Alvis %A Pineau, Joelle %A Tibshirani, Robert %A Hastie, Trevor %A Ioannidis, John P A %A Quackenbush, John %A Aerts, Hugo J W L %K Algorithms %K Artificial Intelligence %K Reproducibility of Results %B Nature %V 586 %P E14-E16 %8 2020 10 %G eng %N 7829 %1 https://www.ncbi.nlm.nih.gov/pubmed/33057217?dopt=Abstract %R 10.1038/s41586-020-2766-y %0 Journal Article %J Nat Commun %D 2019 %T Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. %A Menden, Michael P %A Wang, Dennis %A Mason, Mike J %A Szalai, Bence %A Bulusu, Krishna C %A Guan, Yuanfang %A Yu, Thomas %A Kang, Jaewoo %A Jeon, Minji %A Wolfinger, Russ %A Nguyen, Tin %A Zaslavskiy, Mikhail %A Jang, In Sock %A Ghazoui, Zara %A Ahsen, Mehmet Eren %A Vogel, Robert %A Neto, Elias Chaibub %A Norman, Thea %A Tang, Eric K Y %A Garnett, Mathew J %A Veroli, Giovanni Y Di %A Fawell, Stephen %A Stolovitzky, Gustavo %A Guinney, Justin %A Dry, Jonathan R %A Saez-Rodriguez, Julio %K ADAM17 Protein %K Antineoplastic Combined Chemotherapy Protocols %K Benchmarking %K Biomarkers, Tumor %K Cell Line, Tumor %K Computational Biology %K Datasets as Topic %K Drug Antagonism %K Drug Resistance, Neoplasm %K Drug Synergism %K Genomics %K Humans %K Molecular Targeted Therapy %K mutation %K Neoplasms %K pharmacogenetics %K Phosphatidylinositol 3-Kinases %K Phosphoinositide-3 Kinase Inhibitors %K Treatment Outcome %X

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.

%B Nat Commun %V 10 %P 2674 %8 2019 06 17 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/31209238?dopt=Abstract %R 10.1038/s41467-019-09799-2 %0 Journal Article %J Nature Communications %D 2018 %T A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection %A Fourati, Slim %A Talla, Aarthi %A Mahmoudian, Mehrad %A Burkhart, Joshua G. %A Klén, Riku %A Henao, Ricardo %A Yu, Thomas %A Aydın, Zafer %A Yeung, Ka Yee %A Ahsen, Mehmet Eren %A Almugbel, Reem %A Jahandideh, Samad %A Liang, Xiao %A Nordling, Torbjörn E. M. %A Shiga, Motoki %A Stanescu, Ana %A Vogel, Robert %A Pandey, Gaurav %A Chiu, Christopher %A McClain, Micah T. %A Woods, Christopher W. %A Ginsburg, Geoffrey S. %A Elo, Laura L. %A Tsalik, Ephraim L. %A Mangravite, Lara M. %A Sieberts, Solveig K. %B Nature Communications %V 9 %8 Jan-12-2018 %G eng %U http://www.nature.com/articles/s41467-018-06735-8http://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-8 %N 1 %! Nat Commun %R 10.1038/s41467-018-06735-8 %0 Journal Article %J Nucleic Acids Res %D 2017 %T HGVA: the Human Genome Variation Archive. %A Lopez, Javier %A Coll, Jacobo %A Haimel, Matthias %A Kandasamy, Swaathi %A Tárraga, Joaquín %A Furio-Tari, Pedro %A Bari, Wasim %A Bleda, Marta %A Rueda, Antonio %A Gräf, Stefan %A Rendon, Augusto %A Dopazo, Joaquin %A Medina, Ignacio %K Genetic Variation %K Genome, Human %K Humans %K Internet %K Software %K User-Computer Interface %X

High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK's 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets.

%B Nucleic Acids Res %V 45 %P W189-W194 %8 2017 07 03 %G eng %U https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkx445 %N W1 %1 https://www.ncbi.nlm.nih.gov/pubmed/28535294?dopt=Abstract %R 10.1093/nar/gkx445 %0 Journal Article %J Mol Metab %D 2016 %T Stress-induced activation of brown adipose tissue prevents obesity in conditions of low adaptive thermogenesis. %A Razzoli, Maria %A Frontini, Andrea %A Gurney, Allison %A Mondini, Eleonora %A Cubuk, Cankut %A Katz, Liora S %A Cero, Cheryl %A Bolan, Patrick J %A Dopazo, Joaquin %A Vidal-Puig, Antonio %A Cinti, Saverio %A Bartolomucci, Alessandro %X

BACKGROUND: Stress-associated conditions such as psychoemotional reactivity and depression have been paradoxically linked to either weight gain or weight loss. This bi-directional effect of stress is not understood at the functional level. Here we tested the hypothesis that pre-stress level of adaptive thermogenesis and brown adipose tissue (BAT) functions explain the vulnerability or resilience to stress-induced obesity.

METHODS: We used wt and triple β1,β2,β3-Adrenergic Receptors knockout (β-less) mice exposed to a model of chronic subordination stress (CSS) at either room temperature (22 °C) or murine thermoneutrality (30 °C). A combined behavioral, physiological, molecular, and immunohistochemical analysis was conducted to determine stress-induced modulation of energy balance and BAT structure and function. Immortalized brown adipocytes were used for in vitro assays.

RESULTS: Departing from our initial observation that βARs are dispensable for cold-induced BAT browning, we demonstrated that under physiological conditions promoting low adaptive thermogenesis and BAT activity (e.g. thermoneutrality or genetic deletion of the βARs), exposure to CSS acted as a stimulus for BAT activation and thermogenesis, resulting in resistance to diet-induced obesity despite the presence of hyperphagia. Conversely, in wt mice acclimatized to room temperature, and therefore characterized by sustained BAT function, exposure to CSS increased vulnerability to obesity. Exposure to CSS enhanced the sympathetic innervation of BAT in wt acclimatized to thermoneutrality and in β-less mice. Despite increased sympathetic innervation suggesting adrenergic-mediated browning, norepinephrine did not promote browning in βARs knockout brown adipocytes, which led us to identify an alternative sympathetic/brown adipocytes purinergic pathway in the BAT. This pathway is downregulated under conditions of low adaptive thermogenesis requirements, is induced by stress, and elicits activation of UCP1 in wt and β-less brown adipocytes. Importantly, this purinergic pathway is conserved in human BAT.

CONCLUSION: Our findings demonstrate that thermogenesis and BAT function are determinant of the resilience or vulnerability to stress-induced obesity. Our data support a model in which adrenergic and purinergic pathways exert complementary/synergistic functions in BAT, thus suggesting an alternative to βARs agonists for the activation of human BAT.

%B Mol Metab %V 5 %P 19-33 %8 2016 Jan %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/26844204?dopt=Abstract %R 10.1016/j.molmet.2015.10.005 %0 Journal Article %J Nature methods %D 2015 %T Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection. %A Ewing, Adam D %A Houlahan, Kathleen E %A Hu, Yin %A Ellrott, Kyle %A Caloian, Cristian %A Yamaguchi, Takafumi N %A Bare, J Christopher %A P’ng, Christine %A Waggott, Daryl %A Sabelnykova, Veronica Y %A Kellen, Michael R %A Norman, Thea C %A Haussler, David %A Friend, Stephen H %A Stolovitzky, Gustavo %A Margolin, Adam A %A Stuart, Joshua M %A Boutros, Paul C %E ICGC-TCGA DREAM Somatic Mutation Calling Challenge participants %E Liu Xi %E Ninad Dewal %E Yu Fan %E Wenyi Wang %E David Wheeler %E Andreas Wilm %E Grace Hui Ting %E Chenhao Li %E Denis Bertrand %E Niranjan Nagarajan %E Qing-Rong Chen %E Chih-Hao Hsu %E Ying Hu %E Chunhua Yan %E Warren Kibbe %E Daoud Meerzaman %E Kristian Cibulskis %E Mara Rosenberg %E Louis Bergelson %E Adam Kiezun %E Amie Radenbaugh %E Anne-Sophie Sertier %E Anthony Ferrari %E Laurie Tonton %E Kunal Bhutani %E Nancy F Hansen %E Difei Wang %E Lei Song %E Zhongwu Lai %E Liao, Yang %E Shi, Wei %E Carbonell-Caballero, José %E Joaquín Dopazo %E Cheryl C K Lau %E Justin Guinney %K cancer %K NGS %K variant calling %X The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/. %B Nature methods %8 2015 May 18 %G eng %U http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3407.html %R 10.1038/nmeth.3407 %0 Journal Article %J Nature biotechnology %D 2015 %T Prediction of human population responses to toxic compounds by a collaborative competition. %A Eduati, Federica %A Mangravite, Lara M %A Wang, Tao %A Tang, Hao %A Bare, J Christopher %A Huang, Ruili %A Norman, Thea %A Kellen, Mike %A Menden, Michael P %A Yang, Jichen %A Zhan, Xiaowei %A Zhong, Rui %A Xiao, Guanghua %A Xia, Menghang %A Abdo, Nour %A Kosyk, Oksana %X The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson’s r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal. %B Nature biotechnology %8 2015 Aug 10 %G eng %U http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3299.html %R 10.1038/nbt.3299 %0 Journal Article %J Nature communications %D 2014 %T Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures. %A Munro, Sarah A %A Lund, Steven P %A Pine, P Scott %A Binder, Hans %A Clevert, Djork-Arné %A Ana Conesa %A Dopazo, Joaquin %A Fasold, Mario %A Hochreiter, Sepp %A Hong, Huixiao %A Jafari, Nadereh %A Kreil, David P %A Labaj, Paweł P %A Li, Sheng %A Liao, Yang %A Lin, Simon M %A Meehan, Joseph %A Mason, Christopher E %A Santoyo-López, Javier %A Setterquist, Robert A %A Shi, Leming %A Shi, Wei %A Smyth, Gordon K %A Stralis-Pavese, Nancy %A Su, Zhenqiang %A Tong, Weida %A Wang, Charles %A Wang, Jian %A Xu, Joshua %A Ye, Zhan %A Yang, Yong %A Yu, Ying %A Salit, Marc %K RNA-seq %X There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard ’dashboard’ of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols. %B Nature communications %V 5 %P 5125 %8 2014 %G eng %U http://www.nature.com/ncomms/2014/140925/ncomms6125/full/ncomms6125.html %R 10.1038/ncomms6125 %0 Journal Article %J BMC Evol Biol %D 2012 %T Diversification of the expanded teleost-specific toll-like receptor family in Atlantic cod, Gadus morhua. %A Sundaram, Arvind Y M %A Kiron, Viswanath %A Dopazo, Joaquin %A Fernandes, Jorge M O %K Amino Acid Sequence %K Animals %K Binding Sites %K Evolution, Molecular %K Fish Diseases %K Fish Proteins %K Gadus morhua %K Gene Expression Profiling %K Genetic Variation %K Gills %K Head Kidney %K Host-Pathogen Interactions %K Models, Molecular %K Molecular Sequence Data %K Multigene Family %K Phylogeny %K Protein Structure, Tertiary %K Reverse Transcriptase Polymerase Chain Reaction %K Selection, Genetic %K Sequence Analysis, DNA %K Sequence Homology, Amino Acid %K Temperature %K Toll-Like Receptors %K Vibrio %X

BACKGROUND: Toll-like receptors (Tlrs) are major molecular pattern recognition receptors of the innate immune system. Atlantic cod (Gadus morhua) is the first vertebrate known to have lost most of the mammalian Tlr orthologues, particularly all bacterial recognising and other cell surface Tlrs. On the other hand, its genome encodes a unique repertoire of teleost-specific Tlrs. The aim of this study was to investigate if these duplicate Tlrs have been retained through adaptive evolution to compensate for the lack of other cell surface Tlrs in the cod genome.

RESULTS: In this study, one tlr21, 12 tlr22 and two tlr23 genes representing the teleost-specific Tlr family have been cloned and characterised in cod. Phylogenetic analysis grouped all tlr22 genes under a single clade, indicating that the multiple cod paralogues have arisen through lineage-specific duplications. All tlrs examined were transcribed in immune-related tissues as well as in stomach, gut and gonads of adult cod and were differentially expressed during early development. These tlrs were also differentially regulated following immune challenge by immersion with Vibrio anguillarum, indicating their role in the immune response. An increase in water temperature from 4 to 12°C was associated with a 5.5-fold down-regulation of tlr22d transcript levels in spleen. Maximum likelihood analysis with different evolution models revealed that tlr22 genes are under positive selection. A total of 24 codons were found to be positively selected, of which 19 are in the ligand binding region of ectodomain.

CONCLUSION: Positive selection pressure coupled with experimental evidence of differential expression strongly support the hypothesis that teleost-specific tlr paralogues in cod are undergoing neofunctionalisation and can recognise bacterial pathogen-associated molecular patterns to compensate for the lack of other cell surface Tlrs.

%B BMC Evol Biol %V 12 %P 256 %8 2012 Dec 29 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/23273344?dopt=Abstract %R 10.1186/1471-2148-12-256 %0 Journal Article %J PLoS One %D 2012 %T Extensive translatome remodeling during ER stress response in mammalian cells. %A Ventoso, Iván %A Kochetov, Alex %A Montaner, David %A Dopazo, Joaquin %A Santoyo, Javier %K Animals %K Endoplasmic Reticulum Stress %K Humans %K Jurkat Cells %K Mice %K NIH 3T3 Cells %K Oligonucleotide Array Sequence Analysis %K Protein Biosynthesis %K RNA, Messenger %K Transcription, Genetic %X

In this work we have described the translatome of two mammalian cell lines, NIH3T3 and Jurkat, by scoring the relative polysome association of ∼10,000 mRNA under normal and ER stress conditions. We have found that translation efficiencies of mRNA correlated poorly with transcript abundance, although a general tendency was observed so that the highest translation efficiencies were found in abundant mRNA. Despite the differences found between mouse (NIH3T3) and human (Jurkat) cells, both cell types share a common translatome composed by ∼800-900 mRNA that encode proteins involved in basic cellular functions. Upon stress, an extensive remodeling in translatomes was observed so that translation of ∼50% of mRNA was inhibited in both cell types, this effect being more dramatic for those mRNA that accounted for most of the cell translation. Interestingly, we found two subsets comprising 1000-1500 mRNA whose translation resisted or was induced by stress. Translation arrest resistant class includes many mRNA encoding aminoacyl tRNA synthetases, ATPases and enzymes involved in DNA replication and stress response such as BiP. This class of mRNA is characterized by high translation rates in both control and stress conditions. Translation inducible class includes mRNA whose translation was relieved after stress, showing a high enrichment in early response transcription factors of bZIP and zinc finger C2H2 classes. Unlike yeast, a general coordination between changes in translation and transcription upon stress (potentiation) was not observed in mammalian cells. Among the different features of mRNA analyzed, we found a relevant association of translation efficiency with the presence of upstream ATG in the 5'UTR and with the length of coding sequence of mRNA, and a looser association with other parameters such as the length and the G+C content of 5'UTR. A model for translatome remodeling during the acute phase of stress response in mammalian cells is proposed.

%B PLoS One %V 7 %P e35915 %8 2012 %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/22574127?dopt=Abstract %R 10.1371/journal.pone.0035915 %0 Journal Article %J FASEB J %D 2012 %T The protease MT1-MMP drives a combinatorial proteolytic program in activated endothelial cells. %A Koziol, Agnieszka %A Gonzalo, Pilar %A Mota, Alba %A Pollán, Angela %A Lorenzo, Cristina %A Colomé, Nuria %A Montaner, David %A Dopazo, Joaquin %A Arribas, Joaquín %A Canals, Francesc %A Arroyo, Alicia G %K Animals %K Blotting, Western %K Combinatorial Chemistry Techniques %K Computational Biology %K Endothelial Cells %K Gene Expression Regulation, Enzymologic %K Inflammation %K Matrix Metalloproteinase 14 %K Mice %K Protein Array Analysis %K Reverse Transcriptase Polymerase Chain Reaction %K RNA Interference %K RNA, Small Interfering %K Transcriptome %K Tumor Necrosis Factor-alpha %X

The mechanism by which proteolytic events translate into biological responses is not well understood. To explore the link of pericellular proteolysis to events relevant to capillary sprouting within the inflammatory context, we aimed at the identification of the collection of substrates of the protease MT1-MMP in endothelial tip cells induced by inflammatory stimuli. We applied quantitative proteomics to endothelial cells (ECs) derived from wild-type and MT1-MMP-null mice to identify the substrate repertoire of this protease in TNF-α-activated ECs. Bioinformatics analysis revealed a combinatorial MT1-MMP proteolytic program, in which combined rather than single substrate processing would determine biological decisions by activated ECs, including chemotaxis, cell motility and adhesion, and vasculature development. MT1-MMP-deficient ECs inefficiently processed several of these substrates (TSP1, CYR61, NID1, and SEM3C), validating the model. This novel concept of MT1-MMP-driven combinatorial proteolysis in angiogenesis might be extendable to proteolytic actions in other cellular contexts.

%B FASEB J %V 26 %P 4481-94 %8 2012 Nov %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/22859368?dopt=Abstract %R 10.1096/fj.12-205906 %0 Journal Article %J BMC plant biology %D 2011 %T Fortunella margarita Transcriptional Reprogramming Triggered by Xanthomonas citri subsp. citri. %A Khalaf, Abeer A %A Gmitter, Frederick G %A Ana Conesa %A Dopazo, Joaquin %A Moore, Gloria A %X ABSTRACT: %B BMC plant biology %V 11 %P 159 %8 2011 %G eng %0 Journal Article %J Nature biotechnology %D 2010 %T The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. %A Shi, Leming %A Campbell, Gregory %A Jones, Wendell D %A Campagne, Fabien %A Wen, Zhining %A Walker, Stephen J %A Su, Zhenqiang %A Chu, Tzu-Ming %A Goodsaid, Federico M %A Pusztai, Lajos %A Shaughnessy, John D %A Oberthuer, André %A Thomas, Russell S %A Paules, Richard S %A Fielden, Mark %A Barlogie, Bart %A Chen, Weijie %A Du, Pan %A Fischer, Matthias %A Furlanello, Cesare %A Gallas, Brandon D %A Ge, Xijin %A Megherbi, Dalila B %A Symmans, W Fraser %A Wang, May D %A Zhang, John %A Bitter, Hans %A Brors, Benedikt %A Bushel, Pierre R %A Bylesjo, Max %A Chen, Minjun %A Cheng, Jie %A Cheng, Jing %A Chou, Jeff %A Davison, Timothy S %A Delorenzi, Mauro %A Deng, Youping %A Devanarayan, Viswanath %A Dix, David J %A Dopazo, Joaquin %A Dorff, Kevin C %A Elloumi, Fathi %A Fan, Jianqing %A Fan, Shicai %A Fan, Xiaohui %A Fang, Hong %A Gonzaludo, Nina %A Hess, Kenneth R %A Hong, Huixiao %A Huan, Jun %A Irizarry, Rafael A %A Judson, Richard %A Juraeva, Dilafruz %A Lababidi, Samir %A Lambert, Christophe G %A Li, Li %A Li, Yanen %A Li, Zhen %A Lin, Simon M %A Liu, Guozhen %A Lobenhofer, Edward K %A Luo, Jun %A Luo, Wen %A McCall, Matthew N %A Nikolsky, Yuri %A Pennello, Gene A %A Perkins, Roger G %A Philip, Reena %A Popovici, Vlad %A Price, Nathan D %A Qian, Feng %A Scherer, Andreas %A Shi, Tieliu %A Shi, Weiwei %A Sung, Jaeyun %A Thierry-Mieg, Danielle %A Thierry-Mieg, Jean %A Thodima, Venkata %A Trygg, Johan %A Vishnuvajjala, Lakshmi %A Wang, Sue Jane %A Wu, Jianping %A Wu, Yichao %A Xie, Qian %A Yousef, Waleed A %A Zhang, Liang %A Zhang, Xuegong %A Zhong, Sheng %A Zhou, Yiming %A Zhu, Sheng %A Arasappan, Dhivya %A Bao, Wenjun %A Lucas, Anne Bergstrom %A Berthold, Frank %A Brennan, Richard J %A Buness, Andreas %A Catalano, Jennifer G %A Chang, Chang %A Chen, Rong %A Cheng, Yiyu %A Cui, Jian %A Czika, Wendy %A Demichelis, Francesca %A Deng, Xutao %A Dosymbekov, Damir %A Eils, Roland %A Feng, Yang %A Fostel, Jennifer %A Fulmer-Smentek, Stephanie %A Fuscoe, James C %A Gatto, Laurent %A Ge, Weigong %A Goldstein, Darlene R %A Guo, Li %A Halbert, Donald N %A Han, Jing %A Harris, Stephen C %A Hatzis, Christos %A Herman, Damir %A Huang, Jianping %A Jensen, Roderick V %A Jiang, Rui %A Johnson, Charles D %A Jurman, Giuseppe %A Kahlert, Yvonne %A Khuder, Sadik A %A Kohl, Matthias %A Li, Jianying %A Li, Li %A Li, Menglong %A Li, Quan-Zhen %A Li, Shao %A Li, Zhiguang %A Liu, Jie %A Liu, Ying %A Liu, Zhichao %A Meng, Lu %A Madera, Manuel %A Martinez-Murillo, Francisco %A Medina, Ignacio %A Meehan, Joseph %A Miclaus, Kelci %A Moffitt, Richard A %A Montaner, David %A Mukherjee, Piali %A Mulligan, George J %A Neville, Padraic %A Nikolskaya, Tatiana %A Ning, Baitang %A Page, Grier P %A Parker, Joel %A Parry, R Mitchell %A Peng, Xuejun %A Peterson, Ron L %A Phan, John H %A Quanz, Brian %A Ren, Yi %A Riccadonna, Samantha %A Roter, Alan H %A Samuelson, Frank W %A Schumacher, Martin M %A Shambaugh, Joseph D %A Shi, Qiang %A Shippy, Richard %A Si, Shengzhu %A Smalter, Aaron %A Sotiriou, Christos %A Soukup, Mat %A Staedtler, Frank %A Steiner, Guido %A Stokes, Todd H %A Sun, Qinglan %A Tan, Pei-Yi %A Tang, Rong %A Tezak, Zivana %A Thorn, Brett %A Tsyganova, Marina %A Turpaz, Yaron %A Vega, Silvia C %A Visintainer, Roberto %A von Frese, Juergen %A Wang, Charles %A Wang, Eric %A Wang, Junwei %A Wang, Wei %A Westermann, Frank %A Willey, James C %A Woods, Matthew %A Wu, Shujian %A Xiao, Nianqing %A Xu, Joshua %A Xu, Lei %A Yang, Lun %A Zeng, Xiao %A Zhang, Jialu %A Zhang, Li %A Zhang, Min %A Zhao, Chen %A Puri, Raj K %A Scherf, Uwe %A Tong, Weida %A Wolfinger, Russell D %X

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

%B Nature biotechnology %V 28 %P 827-38 %8 2010 Aug %G eng %U http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html %0 Journal Article %J Leuk Lymphoma %D 2009 %T Functional signatures identified in B-cell non-Hodgkin lymphoma profiles. %A Aggarwal, Mohit %A Sánchez-Beato, Margarita %A Gómez-López, Gonzalo %A Al-Shahrour, Fátima %A Martínez, Nerea %A Rodríguez, Antonia %A Ruiz-Ballesteros, Elena %A Camacho, Francisca I %A Pérez-Rosado, Alberto %A de la Cueva, Paloma %A Artiga, María J %A Pisano, David G %A Kimby, Eva %A Dopazo, Joaquin %A Villuendas, Raquel %A Piris, Miguel A %K Adult %K Cluster Analysis %K Gene Expression Profiling %K Gene Expression Regulation, Leukemic %K Genetic Heterogeneity %K Humans %K Lymphoma, B-Cell %K Neoplasm Proteins %K Oligonucleotide Array Sequence Analysis %K RNA, Messenger %K RNA, Neoplasm %K Transcription, Genetic %X

Gene-expression profiling in B-cell lymphomas has provided crucial data on specific lymphoma types, which can contribute to the identification of essential lymphoma survival genes and pathways. In this study, the gene-expression profiling data of all major B-cell lymphoma types were analyzed by unsupervised clustering. The transcriptome classification so obtained, was explored using gene set enrichment analysis generating a heatmap for B-cell lymphoma that identifies common lymphoma survival mechanisms and potential therapeutic targets, recognizing sets of coregulated genes and functional pathways expressed in different lymphoma types. Some of the most relevant signatures (stroma, cell cycle, B-cell receptor (BCR)) are shared by multiple lymphoma types or subclasses. A specific attention was paid to the analysis of BCR and coregulated pathways, defining molecular heterogeneity within multiple B-cell lymphoma types.

%B Leuk Lymphoma %V 50 %P 1699-708 %8 2009 Oct %G eng %N 10 %1 https://www.ncbi.nlm.nih.gov/pubmed/19863341?dopt=Abstract %R 10.1080/10428190903189035 %0 Journal Article %J Nucleic Acids Res %D 2009 %T MODBASE, a database of annotated comparative protein structure models and associated resources %A Pieper, U. %A Eswar, N. %A Webb, B. M. %A Eramian, D. %A Kelly, L. %A Barkan, D. T. %A Carter, H. %A Mankoo, P. %A Karchin, R. %A M. A. Marti-Renom %A Davis, F. P. %A Sali, A. %K *Databases %K Molecular Mutation Polymorphism %K Protein Genomics Humans Ligands *Models %K Protein User-Computer Interface %K Single Nucleotide Protein Folding Protein Interaction Domains and Motifs *Protein Structure %K Tertiary Proteins/genetics *Structural Homology %X MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by MODPIPE, an automated modeling pipeline that relies primarily on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE currently contains 5,152,695 reliable models for domains in 1,593,209 unique protein sequences; only models based on statistically significant alignments and/or models assessed to have the correct fold are included. MODBASE also allows users to calculate comparative models on demand, through an interface to the MODWEB modeling server (http://salilab.org/modweb). Other resources integrated with MODBASE include databases of multiple protein structure alignments (DBAli), structurally defined ligand binding sites (LIGBASE), predicted ligand binding sites (AnnoLyze), structurally defined binary domain interfaces (PIBASE) and annotated single nucleotide polymorphisms and somatic mutations found in human proteins (LS-SNP, LS-Mut). MODBASE models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/). %B Nucleic Acids Res %V 37 %P D347-54 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18948282 %0 Journal Article %J Nature Methods %D 2009 %T Statistical methods for analysis of high-throughput RNA interference screens %A Birmingham, Amanda %A Selfors, Laura M %A Forster, Thorsten %A Wrobel, David %A Kennedy, Caleb J %A Shanks, Emma %A Santoyo-López, Javier %A Dunican, Dara J %A Long, Aideen %A Kelleher, Dermot %A Smith, Queta %A Beijersbergen, Roderick L %A Ghazal, Peter %A Shamu, Caroline E %K gene silencing %K regulation %K siRNA %B Nature Methods %I Nature Publishing Group %V 6 %P 569 - 575 %8 2009/08//print %@ 1548-7091 %G eng %U http://dx.doi.org/10.1038/nmeth.1351 %0 Journal Article %J Genomics %D 2008 %T Direct functional assessment of the composite phenotype through multivariate projection strategies %A A. Conesa %A Bro, R. %A Garcia-Garcia, F. %A Prats, J. M. %A Gotz, S. %A Kjeldahl, K. %A Montaner, D. %A Dopazo, J. %K Breast Neoplasms/genetics Computational Biology/*methods Databases %K Genetic Female Gene Expression Profiling/*statistics & numerical data Humans Mathematical Computing Multivariate Analysis Phenotype %X

We present a novel approach for the analysis of transcriptomics data that integrates functional annotation of gene sets with expression values in a multivariate fashion, and directly assesses the relation of functional features to a multivariate space of response phenotypical variables. Multivariate projection methods are used to obtain new correlated variables for a set of genes that share a given function. These new functional variables are then related to the response variables of interest. The analysis of the principal directions of the multivariate regression allows for the identification of gene function features correlated with the phenotype. Two different transcriptomics studies are used to illustrate the statistical and interpretative aspects of the methodology. We demonstrate the superiority of the proposed method over equivalent approaches.

%B Genomics %V 92 %P 373-83 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18652888 %0 Journal Article %J Genomics %D 2008 %T Direct functional assessment of the composite phenotype through multivariate projection strategies. %A Conesa, Ana %A Bro, Rasmus %A Garcia-Garcia, Francisco %A Prats, José Manuel %A Götz, Stefan %A Kjeldahl, Karin %A Montaner, David %A Dopazo, Joaquin %K Breast Neoplasms %K Computational Biology %K Databases, Genetic %K Female %K Gene Expression Profiling %K Humans %K Mathematical Computing %K Multivariate Analysis %K Phenotype %X

We present a novel approach for the analysis of transcriptomics data that integrates functional annotation of gene sets with expression values in a multivariate fashion, and directly assesses the relation of functional features to a multivariate space of response phenotypical variables. Multivariate projection methods are used to obtain new correlated variables for a set of genes that share a given function. These new functional variables are then related to the response variables of interest. The analysis of the principal directions of the multivariate regression allows for the identification of gene function features correlated with the phenotype. Two different transcriptomics studies are used to illustrate the statistical and interpretative aspects of the methodology. We demonstrate the superiority of the proposed method over equivalent approaches.

%B Genomics %V 92 %P 373-83 %8 2008 Dec %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/18652888?dopt=Abstract %R 10.1016/j.ygeno.2008.05.015 %0 Journal Article %J Brief Bioinform %D 2008 %T Interoperability with Moby 1.0--it's better than sharing your toothbrush! %A Wilkinson, Mark D %A Senger, Martin %A Kawas, Edward %A Bruskiewich, Richard %A Gouzy, Jerome %A Noirot, Celine %A Bardou, Philippe %A Ng, Ambrose %A Haase, Dirk %A Saiz, Enrique de Andres %A Wang, Dennis %A Gibbons, Frank %A Gordon, Paul M K %A Sensen, Christoph W %A Carrasco, Jose Manuel Rodriguez %A Fernández, José M %A Shen, Lixin %A Links, Matthew %A Ng, Michael %A Opushneva, Nina %A Neerincx, Pieter B T %A Leunissen, Jack A M %A Ernst, Rebecca %A Twigger, Simon %A Usadel, Bjorn %A Good, Benjamin %A Wong, Yan %A Stein, Lincoln %A Crosby, William %A Karlsson, Johan %A Royo, Romina %A Párraga, Iván %A Ramírez, Sergio %A Gelpi, Josep Lluis %A Trelles, Oswaldo %A Pisano, David G %A Jimenez, Natalia %A Kerhornou, Arnaud %A Rosset, Roman %A Zamacola, Leire %A Tárraga, Joaquín %A Huerta-Cepas, Jaime %A Carazo, Jose María %A Dopazo, Joaquin %A Guigó, Roderic %A Navarro, Arcadi %A Orozco, Modesto %A Valencia, Alfonso %A Claros, M Gonzalo %A Pérez, Antonio J %A Aldana, Jose %A Rojano, M Mar %A Fernandez-Santa Cruz, Raul %A Navas, Ismael %A Schiltz, Gary %A Farmer, Andrew %A Gessler, Damian %A Schoof, Heiko %A Groscurth, Andreas %K Computational Biology %K Database Management Systems %K Databases, Factual %K Information Storage and Retrieval %K Internet %K Programming Languages %K Systems Integration %X

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.

%B Brief Bioinform %V 9 %P 220-31 %8 2008 May %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/18238804?dopt=Abstract %R 10.1093/bib/bbn003 %0 Journal Article %J Brief Bioinform %D 2008 %T Interoperability with Moby 1.0–it’s better than sharing your toothbrush! %A Wilkinson, M. D. %A Senger, M. %A Kawas, E. %A Bruskiewich, R. %A Gouzy, J. %A Noirot, C. %A Bardou, P. %A Ng, A. %A Haase, D. %A Saiz Ede, A. %A Wang, D. %A Gibbons, F. %A Gordon, P. M. %A Sensen, C. W. %A Carrasco, J. M. %A Fernandez, J. M. %A Shen, L. %A Links, M. %A Ng, M. %A Opushneva, N. %A Neerincx, P. B. %A Leunissen, J. A. %A Ernst, R. %A Twigger, S. %A Usadel, B. %A Good, B. %A Wong, Y. %A Stein, L. %A Crosby, W. %A Karlsson, J. %A Royo, R. %A Parraga, I. %A Ramirez, S. %A Gelpi, J. L. %A Trelles, O. %A Pisano, D. G. %A Jimenez, N. %A Kerhornou, A. %A Rosset, R. %A Zamacola, L. %A Tarraga, J. %A Huerta-Cepas, J. %A Carazo, J. M. %A Dopazo, J. %A R. Guigo %A Navarro, A. %A Orozco, M. %A Valencia, A. %A Claros, M. G. %A Perez, A. J. %A Aldana, J. %A Rojano, M. M. %A Fernandez-Santa Cruz, R. %A Navas, I. %A Schiltz, G. %A Farmer, A. %A Gessler, D. %A Schoof, H. %A Groscurth, A. %K Computational Biology/*methods *Database Management Systems *Databases %K Factual Information Storage and Retrieval/*methods *Internet *Programming Languages Systems Integration %X

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.

%B Brief Bioinform %V 9 %P 220-31 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18238804 %0 Journal Article %J Nat Genet %D 2008 %T SNP and haplotype mapping for genetic analysis in the rat. %A Saar, Kathrin %A Beck, Alfred %A Bihoreau, Marie-Thérèse %A Birney, Ewan %A Brocklebank, Denise %A Chen, Yuan %A Cuppen, Edwin %A Demonchy, Stephanie %A Dopazo, Joaquin %A Flicek, Paul %A Foglio, Mario %A Fujiyama, Asao %A Gut, Ivo G %A Gauguier, Dominique %A Guigó, Roderic %A Guryev, Victor %A Heinig, Matthias %A Hummel, Oliver %A Jahn, Niels %A Klages, Sven %A Kren, Vladimir %A Kube, Michael %A Kuhl, Heiner %A Kuramoto, Takashi %A Kuroki, Yoko %A Lechner, Doris %A Lee, Young-Ae %A Lopez-Bigas, Nuria %A Lathrop, G Mark %A Mashimo, Tomoji %A Medina, Ignacio %A Mott, Richard %A Patone, Giannino %A Perrier-Cornet, Jeanne-Antide %A Platzer, Matthias %A Pravenec, Michal %A Reinhardt, Richard %A Sakaki, Yoshiyuki %A Schilhabel, Markus %A Schulz, Herbert %A Serikawa, Tadao %A Shikhagaie, Medya %A Tatsumoto, Shouji %A Taudien, Stefan %A Toyoda, Atsushi %A Voigt, Birger %A Zelenika, Diana %A Zimdahl, Heike %A Hubner, Norbert %K Animals %K Chromosome Mapping %K Databases, Genetic %K Genome %K Haplotypes %K Linkage Disequilibrium %K Phylogeny %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Rats %K Rats, Inbred Strains %K Recombination, Genetic %X

The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.

%B Nat Genet %V 40 %P 560-6 %8 2008 May %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/18443594?dopt=Abstract %R 10.1038/ng.124 %0 Journal Article %J Nat Genet %D 2008 %T SNP and haplotype mapping for genetic analysis in the rat %A K. Saar %A A. Beck %A M. T. Bihoreau %A E. Birney %A D. Brocklebank %A Y. Chen %A E. Cuppen %A S. Demonchy %A Dopazo, J. %A P. Flicek %A M. Foglio %A A. Fujiyama %A I. G. Gut %A D. Gauguier %A R. Guigo %A V. Guryev %A M. Heinig %A O. Hummel %A N. Jahn %A S. Klages %A V. Kren %A M. Kube %A H. Kuhl %A Kuramoto, T. %A Kuroki, Y. %A Lechner, D. %A Lee, Y. A. %A Lopez-Bigas, N. %A Lathrop, G. M. %A Mashimo, T. %A Medina, Ignacio %A Mott, R. %A Patone, G. %A Perrier-Cornet, J. A. %A Platzer, M. %A Pravenec, M. %A Reinhardt, R. %A Sakaki, Y. %A Schilhabel, M. %A Schulz, H. %A Serikawa, T. %A Shikhagaie, M. %A Tatsumoto, S. %A Taudien, S. %A Toyoda, A. %A Voigt, B. %A Zelenika, D. %A Zimdahl, H. %A Hubner, N. %K Animals Chromosome Mapping *Databases %K Genetic %K Genetic Genome *Haplotypes Linkage Disequilibrium Phylogeny *Polymorphism %K Inbred Strains/*genetics Recombination %K Single Nucleotide *Quantitative Trait Loci Rats/*genetics Rats %X

The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.

%B Nat Genet %V 40 %P 560-6 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18443594 %0 Journal Article %J Nucleic Acids Res %D 2006 %T MODBASE: a database of annotated comparative protein structure models and associated resources %A Pieper, U. %A Eswar, N. %A Davis, F. P. %A Braberg, H. %A Madhusudhan, M. S. %A Rossi, A. %A M. A. Marti-Renom %A Karchin, R. %A Webb, B. M. %A Eramian, D. %A Shen, M. Y. %A Kelly, L. %A Melo, F. %A Sali, A. %K Binding Sites *Databases %K Molecular Polymorphism %K Protein Humans Internet Ligands *Models %K Protein Systems Integration User-Computer Interface %K Single Nucleotide Protein Structure %K Tertiary Proteins/*chemistry/genetics/metabolism Software *Structural Homology %X MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models for all available protein sequences that can be matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, and improvements in the software for calculating the models. MODBASE currently contains 3 094 524 reliable models for domains in 1 094 750 out of 1 817 889 unique protein sequences in the UniProt database (July 5, 2005); only models based on statistically significant alignments and models assessed to have the correct fold despite insignificant alignments are included. MODBASE also allows users to generate comparative models for proteins of interest with the automated modeling server MODWEB (http://salilab.org/modweb). Our other resources integrated with MODBASE include comprehensive databases of multiple protein structure alignments (DBAli, http://salilab.org/dbali), structurally defined ligand binding sites and structurally defined binary domain interfaces (PIBASE, http://salilab.org/pibase) as well as predictions of ligand binding sites, interactions between yeast proteins, and functional consequences of human nsSNPs (LS-SNP, http://salilab.org/LS-SNP). %B Nucleic Acids Res %V 34 %P D291-5 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16381869 %0 Journal Article %J Nature %D 2005 %T An anaerobic mitochondrion that produces hydrogen %A Boxma, B. %A de Graaf, R. M. %A van der Staay, G. W. %A van Alen, T. A. %A Ricard, G. %A Gabaldón, T. %A van Hoek, A. H. %A Moon-van der Staay, S. Y. %A Koopman, W. J. %A van Hellemond, J. J. %A Tielens, A. G. %A Friedrich, T. %A Veenhuis, M. %A M. A. Huynen %A Hackstein, J. H. %K *Anaerobiosis Animals Ciliophora/*cytology/genetics/*metabolism/ultrastructure Cockroaches/parasitology DNA %K Mitochondrial/genetics Electron Transport Electron Transport Complex I/antagonists & inhibitors/metabolism Genome Glucose/metabolism Hydrogen/*metabolism Mitochondria/enzymology/genetics/*metabolism/ultrastructure Molecular Sequence Data Open Reading Fra %X Hydrogenosomes are organelles that produce ATP and hydrogen, and are found in various unrelated eukaryotes, such as anaerobic flagellates, chytridiomycete fungi and ciliates. Although all of these organelles generate hydrogen, the hydrogenosomes from these organisms are structurally and metabolically quite different, just like mitochondria where large differences also exist. These differences have led to a continuing debate about the evolutionary origin of hydrogenosomes. Here we show that the hydrogenosomes of the anaerobic ciliate Nyctotherus ovalis, which thrives in the hindgut of cockroaches, have retained a rudimentary genome encoding components of a mitochondrial electron transport chain. Phylogenetic analyses reveal that those proteins cluster with their homologues from aerobic ciliates. In addition, several nucleus-encoded components of the mitochondrial proteome, such as pyruvate dehydrogenase and complex II, were identified. The N. ovalis hydrogenosome is sensitive to inhibitors of mitochondrial complex I and produces succinate as a major metabolic end product–biochemical traits typical of anaerobic mitochondria. The production of hydrogen, together with the presence of a genome encoding respiratory chain components, and biochemical features characteristic of anaerobic mitochondria, identify the N. ovalis organelle as a missing link between mitochondria and hydrogenosomes. %B Nature %V 434 %P 74-9 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15744302 %0 Journal Article %J Nat Struct Mol Biol %D 2005 %T The C-type lectin fold as an evolutionary solution for massive sequence variation %A McMahon, S. A. %A Miller, J. L. %A Lawton, J. A. %A Kerkow, D. E. %A Hodes, A. %A M. A. Marti-Renom %A Doulatov, S. %A Narayanan, E. %A Sali, A. %A Miller, J. F. %A Ghosh, P. %K Amino Acid Sequence Bacterial Outer Membrane Proteins/*chemistry Bacteriophages/*metabolism Bordetella/*virology Evolution %K Bordetella/*chemistry %K C-Type/*chemistry Molecular Sequence Data Protein Conformation Protein Folding Viral Proteins/*chemistry/*genetics Virulence Factors %K Molecular Genetic Variation Genome %K Viral Lectins %X Only few instances are known of protein folds that tolerate massive sequence variation for the sake of binding diversity. The most extensively characterized is the immunoglobulin fold. We now add to this the C-type lectin (CLec) fold, as found in the major tropism determinant (Mtd), a retroelement-encoded receptor-binding protein of Bordetella bacteriophage. Variation in Mtd, with its approximately 10(13) possible sequences, enables phage adaptation to Bordetella spp. Mtd is an intertwined, pyramid-shaped trimer, with variable residues organized by its CLec fold into discrete receptor-binding sites. The CLec fold provides a highly static scaffold for combinatorial display of variable residues, probably reflecting a different evolutionary solution for balancing diversity against stability from that in the immunoglobulin fold. Mtd variants are biased toward the receptor pertactin, and there is evidence that the CLec fold is used broadly for sequence variation by related retroelements. %B Nat Struct Mol Biol %V 12 %P 886-92 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16170324 %0 Journal Article %J Nucleic Acids Res %D 2003 %T EVA: Evaluation of protein structure prediction servers %A Koh, I. Y. %A Eyrich, V. A. %A M. A. Marti-Renom %A Przybylski, D. %A Madhusudhan, M. S. %A Eswar, N. %A Grana, O. %A Pazos, F. %A Valencia, A. %A Sali, A. %A Rost, B. %K Automation Databases %K Protein %K Protein Internet *Protein Conformation Protein Folding Protein Structure %K Protein Structural Homology %K Secondary Proteins/chemistry Reproducibility of Results *Sequence Analysis %X EVA (http://cubic.bioc.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods. The evaluation is updated automatically each week, to cope with the large number of existing prediction servers and the constant changes in the prediction methods. EVA currently assesses servers for secondary structure prediction, contact prediction, comparative protein structure modelling and threading/fold recognition. Every day, sequences of newly available protein structures in the Protein Data Bank (PDB) are sent to the servers and their predictions are collected. The predictions are then compared to the experimental structures once a week; the results are published on the EVA web pages. Over time, EVA has accumulated prediction results for a large number of proteins, ranging from hundreds to thousands, depending on the prediction method. This large sample assures that methods are compared reliably. As a result, EVA provides useful information to developers as well as users of prediction methods. %B Nucleic Acids Res %V 31 %P 3311-5 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824315 %0 Journal Article %J J Immunol %D 2002 %T Use of single point mutations in domain I of beta 2-glycoprotein I to determine fine antigenic specificity of antiphospholipid autoantibodies %A Iverson, G. M. %A Reddel, S. %A Victoria, E. J. %A Cockerill, K. A. %A Wang, Y. X. %A M. A. Marti-Renom %A Sali, A. %A Marquis, D. M. %A Krilis, S. A. %A Linnik, M. D. %K Amino Acid Substitution/genetics Antibodies %K Antibody/genetics Binding %K Antiphospholipid/blood/*metabolism Antibodies %K Competitive/genetics/immunology Enzyme-Linked Immunosorbent Assay/methods Epitopes/analysis/*immunology/metabolism Glycine/genetics Glycoproteins/biosynthesis/*genetics/*immunology/isolation & purification/metabolism Humans Models %K Molecular Peptide Fragments/genetics/immunology/isolation & purification/metabolism *Point Mutation Protein Structure %K Monoclonal/blood/metabolism Antiphospholipid Syndrome/immunology Arginine/genetics *Binding Sites %K Tertiary/genetics Recombinant Proteins/biosynthesis/immunology/isolation & purification/metabolism Static Electricity beta 2-Glycoprotein I %X Autoantibodies against beta(2)-glycoprotein I (beta(2)GPI) appear to be a critical feature of the antiphospholipid syndrome (APS). As determined using domain deletion mutants, human autoantibodies bind to the first of five domains present in beta(2)GPI. In this study the fine detail of the domain I epitope has been examined using 10 selected mutants of whole beta(2)GPI containing single point mutations in the first domain. The binding to beta(2)GPI was significantly affected by a number of single point mutations in domain I, particularly by mutations in the region of aa 40-43. Molecular modeling predicted these mutations to affect the surface shape and electrostatic charge of a facet of domain I. Mutation K19E also had an effect, albeit one less severe and involving fewer patients. Similar results were obtained in two different laboratories using affinity-purified anti-beta(2)GPI in a competitive inhibition ELISA and with whole serum in a direct binding ELISA. This study confirms that anti-beta(2)GPI autoantibodies bind to domain I, and that the charged surface patch defined by residues 40-43 contributes to a dominant target epitope. %B J Immunol %V 169 %P 7097-103 %G eng %U http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12471146