biostudies-literatureStopkova RUniverzita Karlova v PrazeCzech Centre for Phenogenomics, Institute of Molecular Genetics of the Czech Academy of SciencesAkademie Věd České RepublikyHorizon 2020 Framework Programme8573https://www.ebi.ac.uk/biostudies/studies/S-EPMC10219973biostudies-literatureUnknown13(1)In most mammals and particularly in mice, chemical communication relies on the detection of ethologically relevant fitness-related cues from other individuals. In mice, urine is the primary source of these signals, so we employed proteomics and metabolomics to identify key components of chemical signalling. We show that there is a correspondence between urinary volatiles and proteins in the representation of genetic background, sex and environment in two house mouse subspecies Mus musculus musculus and M. m. domesticus. We found that environment has a strong influence upon proteomic and metabolomic variation and that volatile mixtures better represent males while females have surprisingly more sex-biased proteins. Using machine learning and combined-omics techniques, we identified mixturesScientific reportsVariation in mouse chemical signals is genetically controlled and environmentally modulated.PMC10219973RVO 68378050, LM2018126810224CSF 16-23773S1191419Stopka PDodokova ATalacko PPialek JSedlacek RStopkova RZacek PMatejkova TfalseVariation in mouse chemical signals is genetically controlled and environmentally modulated.In most mammals and particularly in mice, chemical communication relies on the detection of ethologically relevant fitness-related cues from other individuals. In mice, urine is the primary source of these signals, so we employed proteomics and metabolomics to identify key components of chemical signalling. We show that there is a correspondence between urinary volatiles and proteins in the representation of genetic background, sex and environment in two house mouse subspecies Mus musculus musculus and M. m. domesticus. We found that environment has a strong influence upon proteomic and metabolomic variation and that volatile mixtures better represent males while females have surprisingly more sex-biased proteins. Using machine learning and combined-omics techniques, we identified mixtures2023-01-01T00:00:00Z2023 May2026-07-15T01:34:56.459Z2025-04-04T20:57:36.899ZS-EPMC102199733723709110.1038/s41598-023-35450-8