Systematic identification of unannotated ORFs in Drosophila reveals evolutionary heterogeneity

De novo gene origination, where a previously non-genic genomic sequence becomes genic through evolution, has been increasingly recognized as an important source of evolutionary novelty across diverse taxa. Many de novo genes have been proposed to be protein-coding, and in several cases have been experimentally shown to yield protein products. However, the systematic study of de novo proteins has been hampered by doubts regarding the translation of their transcripts without the experimental observation of protein products. Using a systematic, ORF-focused mass-spectrometry-first computational approach, we identify almost 1000 unannotated open reading frames with evidence of translation (utORFs) in the model organism Drosophila melanogaster , 371 of which have canonical start codons. To quantify the comparative genomic similarity of these utORFs across Drosophila and to infer phylostratigraphic age, we further develop a synteny-based protein similarity approach. Combining these results with reference datasets on tissue- and life-stage-specific transcription and conservation, we identify heterogeneity amongst these utORFs. Contrary to expectations, the fastest-evolving utORFs are not the youngest evolutionarily. We observed more utORFs in the brain than in the testis. Most of the identified utORFs may be of de novo origin, even accounting for the possibility of false-negative similarity detection. Finally, sequence divergence after an inferred de novo origin event remains substantial, raising the possibility that de novo proteins turn over frequently. Our results suggest that there is substantial unappreciated diversity in de novo protein evolution: many more may exist than have been previously appreciated; there may be divergent evolutionary trajectories; and de novo proteins may be gained and lost frequently. All in all, there may not exist a single characteristic model of de novo protein evolution, but rather complex origins and evolutionary trajectories for de novo proteins. of homology. Here, we employ a systematic, ORF-focused MS-first computational approach, to identify unannotated open reading frames with evidence of translation (utORFs) in Drosophila melanogaster . Combined with reference datasets on tissue- and life stage-specific transcription and conservation, this data suggests heterogeneity amongst these utORFs with respect to their evolutionary and functional properties. We further develop a synteny-based protein similarity approach to quantify the comparative genomic similarity of these utORFs across Drosophila , to estimate their phylostratigraphic age, and finally to infer possible de novo origin for the vast majority of these utORFs. Finally, we independently support a subset of these utORFs via additional MS empirical data and ribosome profiling data. show that evolution of young proteins may progress along different, distinct trajectories in Drosophila . Whether similarly distinct trajectories are apparent in other model species such as yeast or mammals remains to be seen. Of note, Drosophila is a taxon of multicellular organisms with a large effective population size, so selective processes are more efficient; mammals – especially primates and Homo – are evolutionarily young and have a smaller effective population size, while yeasts are unicellular. If these factors affect general evolutionary properties, such as the selective cost of translation of lowly functional proteins and the probability of fixation by drift, it is possible that they may affect the evolution of de novo proteins. In the case of Homo , all these factors may be more favorable to the fixation of new de novo proteins, and the availability of broad and varied -omics data is unparalleled. It would