Kavli Affiliate: Li Zhao
| Authors: Eric B Zheng and Li Zhao
| Summary:
Abstract 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 different properties 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. Impact statement The analysis of mass-spectrometry data for all possible open reading frames reveals protein evidence for evolutionarily young, unannotated proteins with distinct characters. Competing Interest Statement The authors have declared no competing interest.