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Papadopoulos C, Arbes H, Cornu D, Chevrollier N, Blanchet S, Roginski P, Rabier C, Atia S, Lespinet O, Namy O, Lopes A. The ribosome profiling landscape of yeast reveals a high diversity in pervasive translation. Genome Biol 2024; 25:268. [PMID: 39402662 PMCID: PMC11472626 DOI: 10.1186/s13059-024-03403-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 09/26/2024] [Indexed: 10/19/2024] Open
Abstract
BACKGROUND Pervasive translation is a widespread phenomenon that plays a critical role in the emergence of novel microproteins, but the diversity of translation patterns contributing to their generation remains unclear. Based on 54 ribosome profiling (Ribo-Seq) datasets, we investigated the yeast Ribo-Seq landscape using a representation framework that allows the comprehensive inventory and classification of the entire diversity of Ribo-Seq signals, including non-canonical ones. RESULTS We show that if coding regions occupy specific areas of the Ribo-Seq landscape, noncoding regions encompass a wide diversity of Ribo-Seq signals and, conversely, populate the entire landscape. Our results show that pervasive translation can, nevertheless, be associated with high specificity, with 1055 noncoding ORFs exhibiting canonical Ribo-Seq signals. Using mass spectrometry under standard conditions or proteasome inhibition with an in-house analysis protocol, we report 239 microproteins originating from noncoding ORFs that display canonical but also non-canonical Ribo-Seq signals. Each condition yields dozens of additional microprotein candidates with comparable translation properties, suggesting a larger population of volatile microproteins that are challenging to detect. Our findings suggest that non-canonical translation signals may harbor valuable information and underscore the significance of considering them in proteogenomic studies. Finally, we show that the translation outcome of a noncoding ORF is primarily determined by the initiating codon and the codon distribution in its two alternative frames, rather than features indicative of functionality. CONCLUSION Our results enable us to propose a topology of a species' Ribo-Seq landscape, opening the way to comparative analyses of this translation landscape under different conditions.
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Affiliation(s)
- Chris Papadopoulos
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Hugo Arbes
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | - David Cornu
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | | | - Sandra Blanchet
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | - Paul Roginski
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | - Camille Rabier
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | - Safiya Atia
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | - Olivier Lespinet
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | - Olivier Namy
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France
| | - Anne Lopes
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, Cedex, 91198, France.
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Chen JH, Landback P, Arsala D, Guzzetta A, Xia S, Atlas J, Sosa D, Zhang YE, Cheng J, Shen B, Long M. Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.14.567139. [PMID: 38045239 PMCID: PMC10690195 DOI: 10.1101/2023.11.14.567139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
New genes (or young genes) are genetic novelties pivotal in mammalian evolution. However, their phenotypic impacts and evolutionary patterns over time remain elusive in humans due to the technical and ethical complexities of functional studies. Integrating gene age dating with Mendelian disease phenotyping, our research shows a gradual rise in disease gene proportion as gene age increases. Logistic regression modeling indicates that this increase in older genes may be related to their longer sequence lengths and higher burdens of deleterious de novo germline variants (DNVs). We also find a steady integration of new genes with biomedical phenotypes into the human genome over macroevolutionary timescales (~0.07% per million years). Despite this stable pace, we observe distinct patterns in phenotypic enrichment, pleiotropy, and selective pressures across gene ages. Notably, young genes show significant enrichment in diseases related to the male reproductive system, indicating strong sexual selection. Young genes also exhibit disease-related functions in tissues and systems potentially linked to human phenotypic innovations, such as increased brain size, musculoskeletal phenotypes, and color vision. We further reveal a logistic growth pattern of pleiotropy over evolutionary time, indicating a diminishing marginal growth of new functions for older genes due to intensifying selective constraints over time. We propose a "pleiotropy-barrier" model that delineates higher potentials for phenotypic innovation in young genes compared to older genes, a process that is subject to natural selection. Our study demonstrates that evolutionarily new genes are critical in influencing human reproductive evolution and adaptive phenotypic innovations driven by sexual and natural selection, with low pleiotropy as a selective advantage.
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Affiliation(s)
- Jian-Hai Chen
- Department of Ecology and Evolution, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
- Institutes for Systems Genetics, West China University Hospital, Chengdu 610041, China
| | - Patrick Landback
- Department of Ecology and Evolution, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
| | - Deanna Arsala
- Department of Ecology and Evolution, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
| | - Alexander Guzzetta
- Department of Pathology, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
| | - Shengqian Xia
- Department of Ecology and Evolution, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
| | - Jared Atlas
- Department of Ecology and Evolution, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
| | - Dylan Sosa
- Department of Ecology and Evolution, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
| | - Yong E. Zhang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Jingqiu Cheng
- Institutes for Systems Genetics, West China University Hospital, Chengdu 610041, China
| | - Bairong Shen
- Institutes for Systems Genetics, West China University Hospital, Chengdu 610041, China
| | - Manyuan Long
- Department of Ecology and Evolution, The University of Chicago, 1101 E 57th Street, Chicago, IL 60637
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Houghton CJ, Coelho NC, Chiang A, Hedayati S, Parikh SB, Ozbaki-Yagan N, Wacholder A, Iannotta J, Berger A, Carvunis AR, O'Donnell AF. Cellular processing of beneficial de novo emerging proteins. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.28.610198. [PMID: 39257767 PMCID: PMC11384008 DOI: 10.1101/2024.08.28.610198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2024]
Abstract
Novel proteins can originate de novo from non-coding DNA and contribute to species-specific adaptations. It is challenging to conceive how de novo emerging proteins may integrate pre-existing cellular systems to bring about beneficial traits, given that their sequences are previously unseen by the cell. To address this apparent paradox, we investigated 26 de novo emerging proteins previously associated with growth benefits in yeast. Microscopy revealed that these beneficial emerging proteins preferentially localize to the endoplasmic reticulum (ER). Sequence and structure analyses uncovered a common protein organization among all ER-localizing beneficial emerging proteins, characterized by a short hydrophobic C-terminus immediately preceded by a transmembrane domain. Using genetic and biochemical approaches, we showed that ER localization of beneficial emerging proteins requires the GET and SND pathways, both of which are evolutionarily conserved and known to recognize transmembrane domains to promote post-translational ER insertion. The abundance of ER-localizing beneficial emerging proteins was regulated by conserved proteasome- and vacuole-dependent processes, through mechanisms that appear to be facilitated by the emerging proteins' C-termini. Consequently, we propose that evolutionarily conserved pathways can convergently govern the cellular processing of de novo emerging proteins with unique sequences, likely owing to common underlying protein organization patterns.
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Affiliation(s)
- Carly J Houghton
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Nelson Castilho Coelho
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Annette Chiang
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, United States
| | - Stefanie Hedayati
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, United States
| | - Saurin B Parikh
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Nejla Ozbaki-Yagan
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, United States
| | - Aaron Wacholder
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - John Iannotta
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Alexis Berger
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Anne-Ruxandra Carvunis
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Allyson F O'Donnell
- Pittsburgh Center for Evolutionary Biology and Medicine (CEBaM), Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, United States
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Mohsen JJ, Mohsen MG, Jiang K, Landajuela A, Quinto L, Isaacs FJ, Karatekin E, Slavoff SA. Cellular function of the GndA small open reading frame-encoded polypeptide during heat shock. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.29.601336. [PMID: 38979229 PMCID: PMC11230408 DOI: 10.1101/2024.06.29.601336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Over the past 15 years, hundreds of previously undiscovered bacterial small open reading frame (sORF)-encoded polypeptides (SEPs) of fewer than fifty amino acids have been identified, and biological functions have been ascribed to an increasing number of SEPs from intergenic regions and small RNAs. However, despite numbering in the dozens in Escherichia coli, and hundreds to thousands in humans, same-strand nested sORFs that overlap protein coding genes in alternative reading frames remain understudied. In order to provide insight into this enigmatic class of unannotated genes, we characterized GndA, a 36-amino acid, heat shock-regulated SEP encoded within the +2 reading frame of the gnd gene in E. coli K-12 MG1655. We show that GndA pulls down components of respiratory complex I (RCI) and is required for proper localization of a RCI subunit during heat shock. At high temperature GndA deletion (ΔGndA) cells exhibit perturbations in cell growth, NADH+/NAD ratio, and expression of a number of genes including several associated with oxidative stress. These findings suggest that GndA may function in maintenance of homeostasis during heat shock. Characterization of GndA therefore supports the nascent but growing consensus that functional, overlapping genes occur in genomes from viruses to humans.
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Affiliation(s)
- Jessica J. Mohsen
- Department of Chemistry, Yale University, New Haven, CT 06511
- Institute for Biomolecular Design and Discovery, Yale University, West Haven, CT 06516
| | - Michael G. Mohsen
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511
- Howard Hughes Medical Institute, Yale University, New Haven, CT 06511
| | - Kevin Jiang
- Department of Chemistry, Yale University, New Haven, CT 06511
- Institute for Biomolecular Design and Discovery, Yale University, West Haven, CT 06516
| | - Ane Landajuela
- Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT 06510
- Nanobiology Institute, Yale University, West Haven, CT 06516
| | - Laura Quinto
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511
- Systems Biology Institute, Yale University, West Haven, CT 06516
| | - Farren J. Isaacs
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511
- Systems Biology Institute, Yale University, West Haven, CT 06516
| | - Erdem Karatekin
- Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT 06510
- Nanobiology Institute, Yale University, West Haven, CT 06516
- Wu Tsai Institute, Yale University, New Haven, CT 06511
- Université de Paris, Saints-Pères Paris Institute for the Neurosciences (SPPIN), Centre National de la Recherche Scientifique (CNRS), 75006 Paris, France
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511
| | - Sarah A. Slavoff
- Department of Chemistry, Yale University, New Haven, CT 06511
- Institute for Biomolecular Design and Discovery, Yale University, West Haven, CT 06516
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511
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Hannon Bozorgmehr J. Four classic "de novo" genes all have plausible homologs and likely evolved from retro-duplicated or pseudogenic sequences. Mol Genet Genomics 2024; 299:6. [PMID: 38315248 DOI: 10.1007/s00438-023-02090-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Accepted: 10/15/2023] [Indexed: 02/07/2024]
Abstract
Despite being previously regarded as extremely unlikely, the idea that entirely novel protein-coding genes can emerge from non-coding sequences has gradually become accepted over the past two decades. Examples of "de novo origination", resulting in lineage-specific "orphan" genes, lacking coding orthologs, are now produced every year. However, many are likely cases of duplicates that are difficult to recognize. Here, I re-examine the claims and show that four very well-known examples of genes alleged to have emerged completely "from scratch"- FLJ33706 in humans, Goddard in fruit flies, BSC4 in baker's yeast and AFGP2 in codfish-may have plausible evolutionary ancestors in pre-existing genes. The first two are likely highly diverged retrogenes coding for regulatory proteins that have been misidentified as orphans. The antifreeze glycoprotein, moreover, may not have evolved from repetitive non-genic sequences but, as in several other related cases, from an apolipoprotein that could have become pseudogenized before later being reactivated. These findings detract from various claims made about de novo gene birth and show there has been a tendency not to invest the necessary effort in searching for homologs outside of a very limited syntenic or phylostratigraphic methodology. A robust approach is used for improving detection that draws upon similarities, not just in terms of statistical sequence analysis, but also relating to biochemistry and function, to obviate notable failures to identify homologs.
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Chen J. Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection. RESEARCH SQUARE 2023:rs.3.rs-3632644. [PMID: 38045389 PMCID: PMC10690325 DOI: 10.21203/rs.3.rs-3632644/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
New genes (or young genes) are structural novelties pivotal in mammalian evolution. Their phenotypic impact on humans, however, remains elusive due to the technical and ethical complexities in functional studies. Through combining gene age dating with Mendelian disease phenotyping, our research reveals that new genes associated with disease phenotypes steadily integrate into the human genome at a rate of ~ 0.07% every million years over macroevolutionary timescales. Despite this stable pace, we observe distinct patterns in phenotypic enrichment, pleiotropy, and selective pressures between young and old genes. Notably, young genes show significant enrichment in the male reproductive system, indicating strong sexual selection. Young genes also exhibit functions in tissues and systems potentially linked to human phenotypic innovations, such as increased brain size, bipedal locomotion, and color vision. Our findings further reveal increasing levels of pleiotropy over evolutionary time, which accompanies stronger selective constraints. We propose a "pleiotropy-barrier" model that delineates different potentials for phenotypic innovation between young and older genes subject to natural selection. Our study demonstrates that evolutionary new genes are critical in influencing human reproductive evolution and adaptive phenotypic innovations driven by sexual and natural selection, with low pleiotropy as a selective advantage.
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7
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Affiliation(s)
- April Rich
- Department of Computational and Systems Biology, Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh Medical School, Pittsburgh, PA, USA
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh Medical School, Pittsburgh, PA, USA.
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