TY - JOUR T1 - Protein structure-based gene expression signatures JF - bioRxiv DO - 10.1101/2020.06.03.133066 SP - 2020.06.03.133066 AU - R. Rahman AU - Y. Xiong AU - J. G. C. van Hasselt AU - J. Hansen AU - E. A. Sobie AU - M. R. Birtwistle AU - E. Azeloglu AU - R. Iyengar AU - A. Schlessinger Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/06/04/2020.06.03.133066.abstract N2 - Gene expression signatures (GES) connect phenotypes to mRNA expression patterns, providing a powerful approach to define cellular identity, function, and the effects of perturbations. However, the use of GES has suffered from vague assessment criteria and limited reproducibility. The structure of proteins defines the functional capability of genes, and hence, we hypothesized that enrichment of structural features could be a generalizable representation of gene sets. We derive structural gene expression signatures (sGES) using features from various levels of protein structure (e.g. domain, fold) encoded by the transcribed genes in GES, to describe cellular phenotypes. Comprehensive analyses of data from the Genotype-Tissue Expression Project (GTEx), ARCHS4, and mRNA expression of drug effects on cardiomyocytes show that structural GES (sGES) are useful for identifying robust signatures of biological phenomena. sGES also enables the characterization of signatures across experimental platforms, facilitates the interoperability of expression datasets, and can describe drug action on cells.Competing Interest StatementR.R and A.S. are co-founders of Aichemy ER -