MoTrPAC
MoTrPAC maps tissue-specific gene expression changes induced by endurance exercise across 15 rat tissues and integrates these multi-tissue transcriptomic and multi-omic data with human gene-disease associations, genetic regulation of expression, and trait relationship datasets to identify trait-tissue-gene relationships relevant to complex diseases.
Key Features:
- Multi-Tissue Transcriptomic Analysis: Uses transcriptome data from 15 rat tissues collected during endurance exercise training to examine tissue-specific gene expression changes.
- Integration with Human Data: Integrates rat-derived multi-tissue gene expression changes with human gene-disease associations, genetic regulation of expression, and trait relationship datasets.
- Identification of Trait-Tissue-Gene Triplets: Employs consensus methodologies to identify 5523 trait-tissue-gene triplets linking exercise-induced expression changes to traits and diseases.
- Focus on Disease-Relevant Gene Expression: Prioritizes tissues and genes most impacted by endurance exercise in relation to disease-relevant gene expression changes.
Scientific Applications:
- Mechanistic investigation of exercise effects: Enables study of molecular mechanisms through which endurance exercise training alters gene expression across multiple tissues.
- Translational interpretation to human health: Facilitates translation of rat multi-tissue findings to human disease contexts via integration with human gene-disease and genetic regulation data.
- Prioritization of targets for follow-up: Supports identification and prioritization of trait-tissue-gene interactions for experimental validation related to complex diseases.
Methodology:
Integration of multi-omic and transcriptome data from rat models with human gene-disease targets, genetic regulation information, and trait relationship datasets; collection and analysis of transcriptome data across 15 tissues during endurance exercise training; and application of consensus methodologies to prioritize tissues and genes and identify trait-tissue-gene triplets.
Topics
Details
- Tool Type:
- web application
- Programming Languages:
- R
- Added:
- 6/18/2024
- Last Updated:
- 11/24/2024
Operations
Publications
Vetr NG, Gay NR, Adkins JN, Albertson BG, Amar D, Amper MAS, Armenteros JJA, Ashley E, Avila-Pacheco J, Bae D, Balci AT, Bamman M, Bararpour N, Barton ER, Jean Beltran PM, Bergman BC, Bessesen DH, Bodine SC, Booth FW, Bouverat B, Buford TW, Burant CF, Caputo T, Carr S, Chambers TL, Chavez C, Chikina M, Chiu R, Cicha M, Clish CB, Coen PM, Cooper D, Cornell E, Cutter G, Dalton KP, Dasari S, Dennis C, Esser K, Evans CR, Farrar R, Fernádez FM, Gadde K, Gagne N, Gaul DA, Ge Y, Gerszten RE, Goodpaster BH, Goodyear LJ, Gritsenko MA, Guevara K, Haddad F, Hansen JR, Harris M, Hastie T, Hennig KM, Hershman SG, Hevener A, Hirshman MF, Hou Z, Hsu F, Huffman KM, Hung C, Hutchinson-Bunch C, Ivanova AA, Jackson BE, Jankowski CM, Jimenez-Morales D, Jin CA, Johannsen NM, Newton RL, Kachman MT, Ke BG, Keshishian H, Kohrt WM, Kramer KS, Kraus WE, Lanza I, Leeuwenburgh C, Lessard SJ, Lester B, Li JZ, Lindholm ME, Lira AK, Liu X, Lu C, Makarewicz NS, Maner-Smith KM, Mani DR, Many GM, Marjanovic N, Marshall A, Marwaha S, May S, Melanson EL, Miller ME, Monroe ME, Moore SG, Moore RJ, Moreau KL, Mundorff CC, Musi N, Nachun D, Nair VD, Nair KS, Nestor MD, Nicklas B, Nigro P, Nudelman G, Ortlund EA, Pahor M, Pearce C, Petyuk VA, Piehowski PD, Pincas H, Powers S, Presby DM, Qian W, Radom-Aizik S, Raja AN, Ramachandran K, Ramaker ME, Ramos I, Rankinen T, Raskind A, Rasmussen BB, Ravussin E, Rector RS, Rejeski WJ, Richards CZ, Rirak S, Robbins JM, Rooney JL, Rubenstein AB, Ruf-Zamojski F, Rushing S, Sagendorf TJ, Samdarshi M, Sanford JA, Savage EM, Schauer IE, Schenk S, Schwartz RS, Sealfon SC, Seenarine N, Smith KS, Smith GR, Snyder MP, Soni T, Oliveira De Sousa LG, Sparks LM, Steep A, Stowe CL, Sun Y, Teng C, Thalacker-Mercer A, Thyfault J, Tibshirani R, Tracy R, Trappe S, Trappe TA, Uppal K, Vangeti S, Vasoya M, Volpi E, Vornholt A, Walkup MP, Walsh MJ, Wheeler MT, Williams JP, Wu S, Xia A, Yan Z, Yu X, Zang C, Zaslavsky E, Zebarjadi N, Zhang T, Zhao B, Zhen J, Montgomery SB. The impact of exercise on gene regulation in association with complex trait genetics. Nature Communications. 2024;15(1). doi:10.1038/s41467-024-45966-w. PMID:38693125. PMCID:PMC11063075.