Detect de novo expressed ORFs in transcriptomes with DESwoMAN.

De novo gene emergence refers to the process by which new genes arise from mutations in previously non-coding genomic regions. Investigating early stages of de novo gene emergence is essential for understanding the mechanisms that enable gene formation from scratch. Several workflows have been developed to detect and study the early stage of de novo gene emergence in specific species. However, no software currently exists that can automatically identify and characterize novel, unannotated open reading frames from a transcriptome, and analyse their mutations and fixation patterns within or across species. We introduce DESwoMAN (D e novo  Emergence Study With Outgroup MutAtioNs), a software tool designed to (i) detect newly expressed non-canonical ORFs (neORFs) in transcriptomes, (ii) filter neORFs with no homology to outgroup genes, and (iii) search for syntenic sequences homologous to neORFs in outgroup genomes (and optionally transcriptomes) and analyse mutations in coding features between these sequences. We applied DESwoMAN with two different strategies to three setups. Our results highlight the tool's capabilities and demonstrate its potential for elucidating the early stages of de novo gene emergence. DESwoMAN is available at https://github.com/AnnaGrBio/DESWOMAN. It is implemented in Python3 and comes with a docker image on DockerHub for easy installation and execution including all dependencies.