{"has_accepted_license":"1","article_processing_charge":"Yes","date_created":"2024-11-10T23:01:59Z","publication_identifier":{"eissn":["1091-6490"],"issn":["0027-8424"]},"intvolume":" 121","oa":1,"OA_place":"publisher","date_updated":"2024-11-11T09:32:05Z","issue":"44","abstract":[{"text":"As their statistical power grows, genome-wide association studies (GWAS) have identified an increasing number of loci underlying quantitative traits of interest. These loci are scattered throughout the genome and are individually responsible only for small fractions of the total heritable trait variance. The recently proposed omnigenic model provides a conceptual framework to explain these observations by postulating that numerous distant loci contribute to each complex trait via effect propagation through intracellular regulatory networks. We formalize this conceptual framework by proposing the “quantitative omnigenic model” (QOM), a statistical model that combines prior knowledge of the regulatory network topology with genomic data. By applying our model to gene expression traits in yeast, we demonstrate that QOM achieves similar gene expression prediction performance to traditional GWAS with hundreds of times less parameters, while simultaneously extracting candidate causal and quantitative chains of effect propagation through the regulatory network for every individual gene. We estimate the fraction of heritable trait variance in cis- and in trans-, break the latter down by effect propagation order, assess the trans- variance not attributable to transcriptional regulation, and show that QOM correctly accounts for the low-dimensional structure of gene expression covariance. We furthermore demonstrate the relevance of QOM for systems biology, by employing it as a statistical test for the quality of regulatory network reconstructions, and linking it to the propagation of nontranscriptional (including environmental) effects.","lang":"eng"}],"month":"10","article_number":"e2402340121","project":[{"name":"Collective behaviour of cells in pancreatic Islets of Langerhans","_id":"7bec9174-9f16-11ee-852c-ded9fe5f810e"},{"name":"Can evolution minimize spurious signaling crosstalk to reach optimal performance?","_id":"2665AAFE-B435-11E9-9278-68D0E5697425","grant_number":"RGP0034/2018"}],"day":"29","title":"Quantitative omnigenic model discovers interpretable genome-wide associations","publication_status":"published","acknowledgement":"N.R.acknowledges the support of the Austrian Academy of Sciences through the Doctoral Fellowship Programme (DOC) of the Austrian Academy of Sciences 26917. M.H. and G.T. were supported in part by the Human Frontiers Science Program Grant RGP0034/2018. We thank Nicholas H. Barton, Fyodor Kondrashov, and Matthew R. Robinson for fruitful discussions.","date_published":"2024-10-29T00:00:00Z","file_date_updated":"2024-11-11T09:31:00Z","year":"2024","_id":"18525","file":[{"date_created":"2024-11-11T09:31:00Z","file_size":25529709,"success":1,"relation":"main_file","file_id":"18536","access_level":"open_access","creator":"dernst","content_type":"application/pdf","date_updated":"2024-11-11T09:31:00Z","file_name":"2024_PNAS_Ruzickova.pdf","checksum":"d930e2ccf9ec900c7d7509a78cfb3564"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","doi":"10.1073/pnas.2402340121","type":"journal_article","publication":"Proceedings of the National Academy of Sciences of the United States of America","language":[{"iso":"eng"}],"volume":121,"oa_version":"Published Version","publisher":"National Academy of Sciences","OA_type":"hybrid","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)"},"author":[{"full_name":"Ruzickova, Natalia","id":"D2761128-D73D-11E9-A1BF-BA0DE6697425","last_name":"Ruzickova","first_name":"Natalia"},{"id":"4171253A-F248-11E8-B48F-1D18A9856A87","last_name":"Hledik","first_name":"Michal","full_name":"Hledik, Michal"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","last_name":"Tkačik","full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455"}],"scopus_import":"1","citation":{"short":"N. Ruzickova, M. Hledik, G. Tkačik, Proceedings of the National Academy of Sciences of the United States of America 121 (2024).","ama":"Ruzickova N, Hledik M, Tkačik G. Quantitative omnigenic model discovers interpretable genome-wide associations. Proceedings of the National Academy of Sciences of the United States of America. 2024;121(44). doi:10.1073/pnas.2402340121","chicago":"Ruzickova, Natalia, Michal Hledik, and Gašper Tkačik. “Quantitative Omnigenic Model Discovers Interpretable Genome-Wide Associations.” Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences, 2024. https://doi.org/10.1073/pnas.2402340121.","apa":"Ruzickova, N., Hledik, M., & Tkačik, G. (2024). Quantitative omnigenic model discovers interpretable genome-wide associations. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.2402340121","ista":"Ruzickova N, Hledik M, Tkačik G. 2024. Quantitative omnigenic model discovers interpretable genome-wide associations. Proceedings of the National Academy of Sciences of the United States of America. 121(44), e2402340121.","mla":"Ruzickova, Natalia, et al. “Quantitative Omnigenic Model Discovers Interpretable Genome-Wide Associations.” Proceedings of the National Academy of Sciences of the United States of America, vol. 121, no. 44, e2402340121, National Academy of Sciences, 2024, doi:10.1073/pnas.2402340121.","ieee":"N. Ruzickova, M. Hledik, and G. Tkačik, “Quantitative omnigenic model discovers interpretable genome-wide associations,” Proceedings of the National Academy of Sciences of the United States of America, vol. 121, no. 44. National Academy of Sciences, 2024."},"status":"public","department":[{"_id":"GaTk"},{"_id":"NiBa"}],"ddc":["570"],"article_type":"original","corr_author":"1"}