1
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Turcan A, Lee J, Wacholder A, Carvunis AR. Integrative detection of genome-wide translation using iRibo. STAR Protoc 2024; 5:102826. [PMID: 38217852 PMCID: PMC10826316 DOI: 10.1016/j.xpro.2023.102826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 11/21/2023] [Accepted: 12/21/2023] [Indexed: 01/15/2024] Open
Abstract
Ribosome profiling is a sequencing technique that provides a global picture of translation across a genome. Here, we present iRibo, a software program for integrating any number of ribosome profiling samples to obtain sensitive inference of annotated or unannotated translated open reading frames. We describe the process of using iRibo to generate a species' translatome from a set of ribosome profiling samples using S. cerevisiae as an example. For complete details on the use and execution of this protocol, please refer to Wacholder et al. (2023).1.
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Affiliation(s)
- Alistair Turcan
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Joint CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
| | - Jiwon Lee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Joint CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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2
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Wacholder A, Carvunis AR. Biological factors and statistical limitations prevent detection of most noncanonical proteins by mass spectrometry. PLoS Biol 2023; 21:e3002409. [PMID: 38048358 PMCID: PMC10721188 DOI: 10.1371/journal.pbio.3002409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 12/14/2023] [Accepted: 10/30/2023] [Indexed: 12/06/2023] Open
Abstract
Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry (MS) experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here, we leveraged recent advances in ribosome profiling and MS to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly expressed to be detected by shotgun MS at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for 4 noncanonical proteins in MS data, which were also supported by evolution and translation data. These results illustrate the power of MS to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly expressed proteins.
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Affiliation(s)
- Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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3
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Wacholder A, Carvunis AR. Biological Factors and Statistical Limitations Prevent Detection of Most Noncanonical Proteins by Mass Spectrometry. bioRxiv 2023:2023.03.09.531963. [PMID: 36945638 PMCID: PMC10028962 DOI: 10.1101/2023.03.09.531963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
Abstract
Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here we leveraged recent advances in ribosome profiling and mass spectrometry to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly-expressed to be detected by shotgun mass spectrometry at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for four noncanonical proteins in mass spectrometry data, which were also supported by evolution and translation data. These results illustrate the power of mass spectrometry to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly-expressed proteins.
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4
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Wacholder A, Parikh SB, Coelho NC, Acar O, Houghton C, Chou L, Carvunis AR. A vast evolutionarily transient translatome contributes to phenotype and fitness. Cell Syst 2023; 14:363-381.e8. [PMID: 37164009 PMCID: PMC10348077 DOI: 10.1016/j.cels.2023.04.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 01/30/2023] [Accepted: 04/06/2023] [Indexed: 05/12/2023]
Abstract
Translation is the process by which ribosomes synthesize proteins. Ribosome profiling recently revealed that many short sequences previously thought to be noncoding are pervasively translated. To identify protein-coding genes in this noncanonical translatome, we combine an integrative framework for extremely sensitive ribosome profiling analysis, iRibo, with high-powered selection inferences tailored for short sequences. We construct a reference translatome for Saccharomyces cerevisiae comprising 5,400 canonical and almost 19,000 noncanonical translated elements. Only 14 noncanonical elements were evolving under detectable purifying selection. A representative subset of translated elements lacking signatures of selection demonstrated involvement in processes including DNA repair, stress response, and post-transcriptional regulation. Our results suggest that most translated elements are not conserved protein-coding genes and contribute to genotype-phenotype relationships through fast-evolving molecular mechanisms.
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Affiliation(s)
- Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Saurin Bipin Parikh
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Integrative Systems Biology Program, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Nelson Castilho Coelho
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Omer Acar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Joint CMU-Pitt PhD Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Carly Houghton
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Joint CMU-Pitt PhD Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Lin Chou
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Integrative Systems Biology Program, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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5
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Van Oss SB, Parikh SB, Castilho Coelho N, Wacholder A, Belashov I, Zdancewicz S, Michaca M, Xu J, Kang YP, Ward NP, Yoon SJ, McCourt KM, McKee J, Ideker T, VanDemark AP, DeNicola GM, Carvunis AR. On the illusion of auxotrophy: met15Δ yeast cells can grow on inorganic sulfur, thanks to the previously uncharacterized homocysteine synthase Yll058w. J Biol Chem 2022; 298:102697. [PMID: 36379252 PMCID: PMC9763685 DOI: 10.1016/j.jbc.2022.102697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 11/01/2022] [Accepted: 11/05/2022] [Indexed: 11/15/2022] Open
Abstract
Organisms must either synthesize or assimilate essential organic compounds to survive. The homocysteine synthase Met15 has been considered essential for inorganic sulfur assimilation in yeast since its discovery in the 1970s. As a result, MET15 has served as a genetic marker for hundreds of experiments that play a foundational role in eukaryote genetics and systems biology. Nevertheless, we demonstrate here through structural and evolutionary modeling, in vitro kinetic assays, and genetic complementation, that an alternative homocysteine synthase encoded by the previously uncharacterized gene YLL058W enables cells lacking Met15 to assimilate enough inorganic sulfur for survival and proliferation. These cells however fail to grow in patches or liquid cultures unless provided with exogenous methionine or other organosulfurs. We show that this growth failure, which has historically justified the status of MET15 as a classic auxotrophic marker, is largely explained by toxic accumulation of the gas hydrogen sulfide because of a metabolic bottleneck. When patched or cultured with a hydrogen sulfide chelator, and when propagated as colony grids, cells without Met15 assimilate inorganic sulfur and grow, and cells with Met15 achieve even higher yields. Thus, Met15 is not essential for inorganic sulfur assimilation in yeast. Instead, MET15 is the first example of a yeast gene whose loss conditionally prevents growth in a manner that depends on local gas exchange. Our results have broad implications for investigations of sulfur metabolism, including studies of stress response, methionine restriction, and aging. More generally, our findings illustrate how unappreciated experimental variables can obfuscate biological discovery.
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Affiliation(s)
- S. Branden Van Oss
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Saurin Bipin Parikh
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Nelson Castilho Coelho
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Aaron Wacholder
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Ivan Belashov
- Department of Biological Sciences, University of Pittsburgh, Dietrich School of Arts & Sciences, Pittsburgh, Pennsylvania, USA
| | - Sara Zdancewicz
- Department of Biological Sciences, University of Pittsburgh, Dietrich School of Arts & Sciences, Pittsburgh, Pennsylvania, USA
| | - Manuel Michaca
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jiazhen Xu
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Yun Pyo Kang
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center, Tampa, Florida, USA
| | - Nathan P. Ward
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center, Tampa, Florida, USA
| | - Sang Jun Yoon
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center, Tampa, Florida, USA
| | - Katherine M. McCourt
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jake McKee
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Trey Ideker
- Departments of Medicine, Bioengineering, Computer Science and Engineering, Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Andrew P. VanDemark
- Department of Biological Sciences, University of Pittsburgh, Dietrich School of Arts & Sciences, Pittsburgh, Pennsylvania, USA
| | - Gina M. DeNicola
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center, Tampa, Florida, USA
| | - Anne-Ruxandra Carvunis
- Department of Computational and System Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,Pittsburgh Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA,For correspondence: Anne-Ruxandra Carvunis
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6
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Parikh SB, Houghton C, Van Oss SB, Wacholder A, Carvunis A. Origins, evolution, and physiological implications of de novo genes in yeast. Yeast 2022; 39:471-481. [PMID: 35959631 PMCID: PMC9544372 DOI: 10.1002/yea.3810] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 12/03/2022] Open
Abstract
De novo gene birth is the process by which new genes emerge in sequences that were previously noncoding. Over the past decade, researchers have taken advantage of the power of yeast as a model and a tool to study the evolutionary mechanisms and physiological implications of de novo gene birth. We summarize the mechanisms that have been proposed to explicate how noncoding sequences can become protein-coding genes, highlighting the discovery of pervasive translation of the yeast transcriptome and its presumed impact on evolutionary innovation. We summarize current best practices for the identification and characterization of de novo genes. Crucially, we explain that the field is still in its nascency, with the physiological roles of most young yeast de novo genes identified thus far still utterly unknown. We hope this review inspires researchers to investigate the true contribution of de novo gene birth to cellular physiology and phenotypic diversity across yeast strains and species.
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Affiliation(s)
- Saurin B. Parikh
- Department of Computational and Systems Biology, School of Medicine, Pittsburgh Center for Evolutionary Biology and EvolutionUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Carly Houghton
- Department of Computational and Systems Biology, School of Medicine, Pittsburgh Center for Evolutionary Biology and EvolutionUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - S. Branden Van Oss
- Department of Computational and Systems Biology, School of Medicine, Pittsburgh Center for Evolutionary Biology and EvolutionUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, Pittsburgh Center for Evolutionary Biology and EvolutionUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Anne‐Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, Pittsburgh Center for Evolutionary Biology and EvolutionUniversity of PittsburghPittsburghPennsylvaniaUSA
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7
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Lee J, Wacholder A, Carvunis AR. Evolutionary Characterization of the Short Protein SPAAR. Genes (Basel) 2021; 12:genes12121864. [PMID: 34946813 PMCID: PMC8702040 DOI: 10.3390/genes12121864] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 11/22/2021] [Accepted: 11/22/2021] [Indexed: 02/07/2023] Open
Abstract
Microproteins (<100 amino acids) are receiving increasing recognition as important participants in numerous biological processes, but their evolutionary dynamics are poorly understood. SPAAR is a recently discovered microprotein that regulates muscle regeneration and angiogenesis through interactions with conserved signaling pathways. Interestingly, SPAAR does not belong to any known protein family and has known homologs exclusively among placental mammals. This lack of distant homology could be caused by challenges in homology detection of short sequences, or it could indicate a recent de novo emergence from a noncoding sequence. By integrating syntenic alignments and homology searches, we identify SPAAR orthologs in marsupials and monotremes, establishing that SPAAR has existed at least since the emergence of mammals. SPAAR shows substantial primary sequence divergence but retains a conserved protein structure. In primates, we infer two independent evolutionary events leading to the de novo origination of 5' elongated isoforms of SPAAR from a noncoding sequence and find evidence of adaptive evolution in this extended region. Thus, SPAAR may be of ancient origin, but it appears to be experiencing continual evolutionary innovation in mammals.
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Affiliation(s)
- Jiwon Lee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; (J.L.); (A.W.)
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Joint CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; (J.L.); (A.W.)
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; (J.L.); (A.W.)
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Correspondence: ; Tel.: +1-412-648-3335
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8
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Affiliation(s)
- Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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9
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Vakirlis N, Acar O, Hsu B, Coelho NC, Van Oss SB, Wacholder A, Medetgul-Ernar K, Bowman RW, Hines CP, Iannotta J, Parikh SB, McLysaght A, Camacho CJ, O'Donnell AF, Ideker T, Carvunis AR. Author Correction: De novo emergence of adaptive membrane proteins from thymine-rich genomic sequences. Nat Commun 2021; 12:200. [PMID: 33398071 PMCID: PMC7782721 DOI: 10.1038/s41467-020-20609-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Nikolaos Vakirlis
- Smurfit Institute of Genetics, Trinity College Dublin, University of Dublin, Dublin 2, Ireland
| | - Omer Acar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Brian Hsu
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Nelson Castilho Coelho
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - S Branden Van Oss
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Kate Medetgul-Ernar
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Ray W Bowman
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Cameron P Hines
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, USA
| | - John Iannotta
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Saurin Bipin Parikh
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Aoife McLysaght
- Smurfit Institute of Genetics, Trinity College Dublin, University of Dublin, Dublin 2, Ireland
| | - Carlos J Camacho
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Allyson F O'Donnell
- Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA. .,Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, USA.
| | - Trey Ideker
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, USA.
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA. .,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
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10
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Vakirlis N, Acar O, Hsu B, Castilho Coelho N, Van Oss SB, Wacholder A, Medetgul-Ernar K, Bowman RW, Hines CP, Iannotta J, Parikh SB, McLysaght A, Camacho CJ, O'Donnell AF, Ideker T, Carvunis AR. De novo emergence of adaptive membrane proteins from thymine-rich genomic sequences. Nat Commun 2020; 11:781. [PMID: 32034123 PMCID: PMC7005711 DOI: 10.1038/s41467-020-14500-z] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 12/20/2019] [Indexed: 11/14/2022] Open
Abstract
Recent evidence demonstrates that novel protein-coding genes can arise de novo from non-genic loci. This evolutionary innovation is thought to be facilitated by the pervasive translation of non-genic transcripts, which exposes a reservoir of variable polypeptides to natural selection. Here, we systematically characterize how these de novo emerging coding sequences impact fitness in budding yeast. Disruption of emerging sequences is generally inconsequential for fitness in the laboratory and in natural populations. Overexpression of emerging sequences, however, is enriched in adaptive fitness effects compared to overexpression of established genes. We find that adaptive emerging sequences tend to encode putative transmembrane domains, and that thymine-rich intergenic regions harbor a widespread potential to produce transmembrane domains. These findings, together with in-depth examination of the de novo emerging YBR196C-A locus, suggest a novel evolutionary model whereby adaptive transmembrane polypeptides emerge de novo from thymine-rich non-genic regions and subsequently accumulate changes molded by natural selection. There is increasing evidence that protein-coding genes can emerge de novo from noncoding genomic regions. Vakirlis et al. propose that sequences encoding transmembrane polypeptides can emerge de novo in thymine-rich genomic regions and provide organisms with fitness benefits.
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Affiliation(s)
- Nikolaos Vakirlis
- Smurfit Institute of Genetics, Trinity College Dublin, University of Dublin, Dublin, 2, Ireland
| | - Omer Acar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Brian Hsu
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, United States
| | - Nelson Castilho Coelho
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - S Branden Van Oss
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Aaron Wacholder
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Kate Medetgul-Ernar
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, United States
| | - Ray W Bowman
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, United States
| | - Cameron P Hines
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, United States
| | - John Iannotta
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Saurin Bipin Parikh
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States.,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States
| | - Aoife McLysaght
- Smurfit Institute of Genetics, Trinity College Dublin, University of Dublin, Dublin, 2, Ireland
| | - Carlos J Camacho
- 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, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States. .,Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, United States.
| | - Trey Ideker
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA, 92093, United States.
| | - Anne-Ruxandra Carvunis
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States. .,Pittsburgh Center for Evolutionary Biology and Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, United States.
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Bergen AW, Mallick A, Nishita D, Wei X, Michel M, Wacholder A, David SP, Swan GE, Reid MW, Simons A, Andrews JA. Chronic psychosocial stressors and salivary biomarkers in emerging adults. Psychoneuroendocrinology 2012; 37:1158-70. [PMID: 22172638 PMCID: PMC3774595 DOI: 10.1016/j.psyneuen.2011.11.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2011] [Revised: 11/15/2011] [Accepted: 11/17/2011] [Indexed: 01/08/2023]
Abstract
We investigated whole saliva as a source of biomarkers to distinguish individuals who have, and who have not, been chronically exposed to severe and threatening life difficulties. We evaluated RNA and DNA metrics, expression of 37 candidate genes, and cortisol release in response to the Trier Social Stress Test, as well as clinical characteristics, from 48 individuals stratified on chronic exposure to psychosocial stressors within the last year as measured by the Life Events and Difficulties Schedule. Candidate genes were selected based on their differential gene expression ratio in circulating monocytes from a published genome-wide analysis of adults experiencing different levels of exposure to a chronic stressor. In univariate analyses, we observed significantly decreased RNA integrity (RIN) score (P = 0.04), and reduced expression of glucocorticoid receptor-regulated genes (Ps < 0.05) in whole saliva RNA from individuals exposed to chronic stressors, as compared to those with no exposure. In those exposed, we observed significantly decreased BMI (P < 0.001), increased ever-smoking and increased lifetime alcohol abuse or dependence (P ≤ 0.03), and a reduction of cortisol release. In post hoc multivariate analyses including clinical and biospecimen-derived variables, we consistently observed significantly decreased expression of IL8 (Ps<0.05) in individuals exposed, with no significant association to RIN score. Alcohol use disorders, tobacco use, a reduced acute stress response and decreased salivary IL8 gene expression characterize emerging adults chronically exposed to severe and threatening psychosocial stressors.
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Affiliation(s)
- Andrew W. Bergen
- Center for Health Sciences, SRI International, Menlo Park, CA 94025, United States,Corresponding author at: Center for Health Sciences, SRI International, 333 Ravenswood Avenue, Menlo Park, CA 94025, United States. Tel.: +1 650 859 4618; fax: +1 650 859 5099. (A.W. Bergen)
| | - Aditi Mallick
- Center for Health Sciences, SRI International, Menlo Park, CA 94025, United States,Stanford University School of Medicine, Stanford, CA 94305, United States
| | - Denise Nishita
- Center for Health Sciences, SRI International, Menlo Park, CA 94025, United States
| | - Xin Wei
- Center for Education and Human Services, SRI International, Menlo Park, CA 94025, United States
| | - Martha Michel
- Center for Health Sciences, SRI International, Menlo Park, CA 94025, United States
| | - Aaron Wacholder
- Center for Health Sciences, SRI International, Menlo Park, CA 94025, United States
| | - Sean P. David
- Center for Health Sciences, SRI International, Menlo Park, CA 94025, United States,Family & Community Medicine, Stanford University School of Medicine, Stanford, CA 94305, United States
| | - Gary E. Swan
- Center for Health Sciences, SRI International, Menlo Park, CA 94025, United States
| | - Mark W. Reid
- Oregon Research Institute, Eugene, OR 97403, United States,Department of Psychology, University of Oregon, Eugene, OR 97403, United States
| | - Anne Simons
- Department of Psychology, University of Notre Dame, Notre Dame, IN 46556, United States
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