Computational Methods for Tracing the Evolutionary History of Human Microproteins Encoded by Intronless Genes

MicroProteins (miPs), small functional proteins derived from short open reading frames (sORFs), play pivotal roles in posttranslational regulation by interacting with multidomain proteins. Acting as dominant-negative regulators, miPs modulate transcriptional activity and protein complex assembly. Their compact structure and functional versatility make them indispensable in cellular regulation, with significant implications in diseases such as cancer and neurodegenerative disorders. Intronless genes (IGs, characterized by the absence of introns in their coding sequences, are linked to key regulatory functions in development, cell proliferation, and disease pathways. While the roles of many IG-encoded proteins are well established, the potential of these genes to encode miPs, as well as their evolutionary history, remain largely unexplored. This chapter introduces a computational framework integrating three bioinformatics tools to investigate the evolution in vertebrates and the functional roles of miPs encoded by IGs. The framework begins with miPFinder2, which identifies potential miPs by annotating small peptides. Next, IGFinder classifies IGs based on genomic and UTR features. Finally, REvolutionH-tl reconstructs evolutionary histories that comprehend orthogroups, orthologs, paralogs, gene trees, species trees, and species tree/gene tree reconciliations. This integrative approach provides comprehensive insights into the structural, functional, and evolutionary reconstruction of miPs encoded by IGs, contributing to advancements in functional genomics, evolutionary biology, and disease research.