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Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins

De novo gene origination, where a previously nongenic genomic sequence becomes genic through evolution, is increasingly recognized as an important source of novelty. Many de novo genes have been proposed to be protein-coding, and a few have been experimentally shown to yield protein products. Howeve...

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Autores principales: Zheng, Eric B, Zhao, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560153/
https://www.ncbi.nlm.nih.gov/pubmed/36178469
http://dx.doi.org/10.7554/eLife.78772
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author Zheng, Eric B
Zhao, Li
author_facet Zheng, Eric B
Zhao, Li
author_sort Zheng, Eric B
collection PubMed
description De novo gene origination, where a previously nongenic genomic sequence becomes genic through evolution, is increasingly recognized as an important source of novelty. Many de novo genes have been proposed to be protein-coding, and a few have been experimentally shown to yield protein products. However, the systematic study of de novo proteins has been hampered by doubts regarding their translation without the experimental observation of protein products. Using a systematic, mass-spectrometry-first computational approach, we identify 993 unannotated open reading frames with evidence of translation (utORFs) in Drosophila melanogaster. To quantify the similarity of these utORFs across Drosophila and infer phylostratigraphic age, we develop a synteny-based protein similarity approach. Combining these results with reference datasets ontissue- 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, suggesting 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 previously appreciated; there may be divergent evolutionary trajectories, and they may be gained and lost frequently. All in all, there may not exist a single characteristic model of de novo protein evolution, but instead, there may be diverse evolutionary trajectories.
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spelling pubmed-95601532022-10-14 Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins Zheng, Eric B Zhao, Li eLife Evolutionary Biology De novo gene origination, where a previously nongenic genomic sequence becomes genic through evolution, is increasingly recognized as an important source of novelty. Many de novo genes have been proposed to be protein-coding, and a few have been experimentally shown to yield protein products. However, the systematic study of de novo proteins has been hampered by doubts regarding their translation without the experimental observation of protein products. Using a systematic, mass-spectrometry-first computational approach, we identify 993 unannotated open reading frames with evidence of translation (utORFs) in Drosophila melanogaster. To quantify the similarity of these utORFs across Drosophila and infer phylostratigraphic age, we develop a synteny-based protein similarity approach. Combining these results with reference datasets ontissue- 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, suggesting 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 previously appreciated; there may be divergent evolutionary trajectories, and they may be gained and lost frequently. All in all, there may not exist a single characteristic model of de novo protein evolution, but instead, there may be diverse evolutionary trajectories. eLife Sciences Publications, Ltd 2022-09-30 /pmc/articles/PMC9560153/ /pubmed/36178469 http://dx.doi.org/10.7554/eLife.78772 Text en © 2022, Zheng and Zhao https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Evolutionary Biology
Zheng, Eric B
Zhao, Li
Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins
title Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins
title_full Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins
title_fullStr Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins
title_full_unstemmed Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins
title_short Protein evidence of unannotated ORFs in Drosophila reveals diversity in the evolution and properties of young proteins
title_sort protein evidence of unannotated orfs in drosophila reveals diversity in the evolution and properties of young proteins
topic Evolutionary Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560153/
https://www.ncbi.nlm.nih.gov/pubmed/36178469
http://dx.doi.org/10.7554/eLife.78772
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