| Title: |
De Novo Gene Emergence: Summary, Classification, and Challenges of Current Methods |
| Authors: |
Grandchamp, Anna; Aubel, Margaux; Eicholt, Lars, A; Roginski, Paul; Luria, Victor; Karger, Amir; Dohmen, Elias |
| Contributors: |
Theories and Approaches of Genomic Complexity (TAGC); Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM); Institute for Evolution and Biodiversity (IEB); Westfälische Wilhelms-Universität Münster = University of Münster = Université de Münster Münster, Allemagne (WWU); Institut de Biologie Intégrative de la Cellule (I2BC); Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS); Department of Neuroscience, Yale University School of Medicine; Yale School of Medicine New Haven, Connecticut (YSM); Harvard Medical School Boston (HMS); Boston Children's Hospital; We thank Erich Bornberg-Bauer (E.B.-B.), Nikolaos Vakirlis, Li Zhao, Anne Lopes, Bharat Ravi Iyengar, and Andreas Lange for their useful feedback during the planning phase of the project. E.D. was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—503348080. This grant with the additional grant number BO2544-22-1 was awarded to E.B.-B. M.A. received funding from the Volkswagen foundation with grant code 98183 awarded to E.B.-B. The work by A.G. was supported by the Deutsche Forschungsgemeinschaft priority program “Genomic Basis of Evolutionary Innovations” (SPP 2349) BO 2544/20-1 to E.B.-B, and by the Human Frontier Science Program Research Grant RGP004/2023 (doi.org/10.52044/HFSP. RGP0042023.pc.gr.168590) awarded to Erich Bornberg- Bauer, Anne-Ruxandra Carvunis and Christine Brun. L.A.E. has been supported by EMBO Scientific Exchange Grant 10944. V.L. was supported by NIH grant R01NS095654 (to Nenad Sestan). We acknowledge support from the Open Access Publication Fund of the University of Münster. |
| Source: |
ISSN: 1759-6653. |
| Publisher Information: |
CCSD; Society for Molecular Biology and Evolution |
| Publication Year: |
2025 |
| Subject Terms: |
comparative transcriptomics; comparative genomics; annotation format; de novo gene emergence; [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] |
| Description: |
International audience ; A novel mechanism of de novo gene origination from nongenic sequences was first proposed in the early 2000s. Subsequent studies have since provided evidence of de novo gene emergence across all domains of life, revealing its occurrence to be more frequent than initially anticipated. While studies mainly agree on the general concept of de novo emergence from nongenic DNA, the exact methods and definitions for detecting de novo genes differ significantly. Here, we provide a comprehensive step-by-step description of the most commonly used methods for de novo gene detection. In addition, we address the limitations of nomenclature and detection methods and clarify some complex concepts that are sometimes misused. This review is accompanied by the publication of a de novo gene annotation format to standardize the reporting of methodology, enable reproducibility and improve the comparability of datasets. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1093/gbe/evaf197 |
| Availability: |
https://amu.hal.science/hal-05500619; https://amu.hal.science/hal-05500619v1/document; https://amu.hal.science/hal-05500619v1/file/evaf197.pdf; https://doi.org/10.1093/gbe/evaf197 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.BFAFF82E |
| Database: |
BASE |