Co-evolution between genes can occur for a variety of reasons, including co-expression of genes, epistatic interactions between them, physical interactions of gene products and many others. Co-evolutionary partners of a gene are therefore of great interest in identifying potential factors that contribute to any phenotype of interest. State-of-the-art approaches to detect these interactions use correlations of evolutionary rates across a broader phylogeny, and so by necessity identify interactions only among genes that are present across long evolutionary time periods. This makes the methods unwieldy when interest lies in a single focal organism in which the genes of interest may have evolved in the recent evolutionary past. Here, we present a new approach to calculating evolutionary rate correlations which focuses on extracting maximum coverage for a single focal species, while retaining signals of co-evolution across large clades. We show how this approach is able to identify potential interactions even in highly studied species and highly studied genes, with a focus on the D. melanogaster sex-determiner, Sxl, using data from 72 species of Dipterans.
Crisis support teams’ technological openness and learning attitudes toward the AI based virtual patient system crisis support VR
BackgroundAgainst the backdrop of escalating global humanitarian crises, innovative didactic simulations are becoming increasingly important. A promising alternative to traditional classroom-based didactics for learning psychological