Deep conservation does not amplify proteomic detection of reverse-strand shadow ORFs in vertebrates
Abstract
Reverse-strand overlapping open reading frames ("shadow ORFs") are pervasive antisense to protein-coding genes, but whether evolutionary conservation amplifies their translation has not been tested at the class level. We catalogued shadow ORFs in 318 deeply conserved human genes and ran a pre-specified mass-spectrometry enrichment test on three size- and length-matched peptide sets of 958 each: conserved candidates (T), low-conservation reverse controls (C), and shuffled decoys (S), searched under identical criteria across six public proteomes. T exceeded S (union OR = 2.63, P = 1.1 × 10⁻¹¹), confirming assay resolution; however, T showed no class-level enrichment over C (OR = 0.81, P = 0.076; 80% power for OR ≥ 1.35). Cross-dataset recurrence did not separate conserved from control peptides (10 vs 12 confident in ≥ 3 datasets), and one shuffled decoy recurred in four of six datasets, quantifying an empirical false-positive floor. Strand-specific RNA-seq detected sparse antisense transcription (0.9–3.9% of sense) that did not track recurring peptides. The chief output is a calibrated, three-arm false-positive floor for proteogenomic searches of non-canonical ORFs, plus ten recurring peptides (led by EGLN1 and BTBD3) as uncertainty-annotated leads for targeted validation.
References
(1) Mudge, J. M.; Ruiz-Orera, J.; Prensner, J. R.; et al. Standardized annotation of translated open reading frames. Nat. Biotechnol. 2022, 40 (7), 994–1003. DOI: 10.1038/s41587-022-01369-0
(2) Deutsch, E. W.; Kok, L. W.; Mudge, J. M.; et al. Expanding the human proteome with microproteins and peptideins. Nature 2026, 654, 813–825. DOI: 10.1038/s41586-026-10459-x
(3) Zehentner, B.; Ardern, Z.; Kreitmeier, M.; Scherer, S.; Neuhaus, K. A novel pH-regulated, unusual 603 bp overlapping protein coding gene pop is encoded antisense to ompA in Escherichia coli O157:H7 (EHEC). Front. Microbiol. 2020, 11, 377. DOI: 10.3389/fmicb.2020.00377
(4) Iyengar, B. R.; Grandchamp, A.; Bornberg-Bauer, E. How antisense transcripts can evolve to encode novel proteins. Nat. Commun. 2024, 15 (1), 6187. DOI: 10.1038/s41467-024-50550-3
(5) Michel, A. M.; Choudhury, K. R.; Firth, A. E.; Ingolia, N. T.; Atkins, J. F.; Baranov, P. V. Observation of dually decoded regions of the human genome using ribosome profiling data. Genome Res. 2012, 22 (11), 2219–2229. DOI: 10.1101/gr.133249.111
(6) Duncan, C. D. S.; Mata, J. The translational landscape of fission yeast meiosis and sporulation. Nat. Struct. Mol. Biol. 2014, 21 (7), 641–647. DOI: 10.1038/nsmb.2843
(7) Brunet, M. A.; Brunelle, M.; Lucier, J. F.; et al. OpenProt: a more comprehensive guide to explore eukaryotic coding potential and proteomes. Nucleic Acids Res. 2019, 47 (D1), D403–D410. DOI: 10.1093/nar/gky936
(8) Katoh, K.; Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 2013, 30 (4), 772–780. DOI: 10.1093/molbev/mst010
(9) Frankish, A.; Carbonell-Sala, S.; Diekhans, M.; et al. GENCODE: reference annotation for the human and mouse genomes in 2023. Nucleic Acids Res. 2023, 51 (D1), D942–D949. DOI: 10.1093/nar/gkac1071
(10) Wen, B.; Zhang, B. PepQuery2 democratizes public MS proteomics data for rapid peptide searching. Nat. Commun. 2023, 14 (1), 2213. DOI: 10.1038/s41467-023-37747-8
(11) Prensner, J. R.; Abelin, J. G.; Kok, L. W.; et al. What can Ribo-seq, immunopeptidomics, and proteomics tell us about the noncanonical proteome? Mol. Cell. Proteomics 2023, 22 (9), 100631. DOI: 10.1016/j.mcpro.2023.100631
(12) ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 2012, 489 (7414), 57–74. DOI: 10.1038/nature11247
(13) Dobin, A.; Davis, C. A.; Schlesinger, F.; et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29 (1), 15–21. DOI: 10.1093/bioinformatics/bts635
(14) Gronostajski, R. M. Roles of the NFI/CTF gene family in transcription and development. Gene 2000, 249 (1–2), 31–45. DOI: 10.1016/S0378-1119(00)00140-2
(15) Uhlén, M.; Fagerberg, L.; Hallström, B. M.; et al. Tissue-based map of the human proteome. Science 2015, 347 (6220), 1260419. DOI: 10.1126/science.1260419
(16) Aggarwal, S.; Yadav, A. K. The Achilles' heel of proteogenomics: false discovery rate. Brief. Bioinform. 2022, 23 (4), bbac163. DOI: 10.1093/bib/bbac163
(17) Li, Q.; Shortreed, M. R.; Wenger, C. D.; et al. A global approach for proteogenomic discovery of noncanonical reading frames and frame-shifted peptides. BMC Genomics 2016, 17, 1032. DOI: 10.1186/s12864-016-3327-5
(18) Blakeley, P.; Overton, I. M.; Hubbard, S. J. Addressing statistical biases in nucleotide-derived protein databases for proteogenomic search strategies. J. Proteome Res. 2012, 11 (11), 5221–5234. DOI: 10.1021/pr300411q
(19) Wacholder, A.; Carvunis, A. R. Biological factors and statistical limitations prevent detection of most noncanonical proteins by mass spectrometry. PLoS Biol. 2023, 21 (8), e3002409. DOI: 10.1371/journal.pbio.3002409
(20) Ulitsky, I. Evolution to the rescue: using comparative genomics to understand long non-coding RNAs. Nat. Rev. Genet. 2016, 17 (10), 601–614. DOI: 10.1038/nrg.2016.85
(21) Zhou, Q.; Jiang, Y.; Cai, C.; et al. Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs. Life Sci. Alliance 2023, 6 (6), e202302002. DOI: 10.26508/lsa.202302002
(22) Ruiz-Orera, J.; Albà, M. M. Conserved regions in long non-coding RNAs contain abundant translation and protein–RNA interaction signatures. NAR Genomics Bioinform. 2019, 1 (2), lqz002. DOI: 10.1093/nargab/lqz002
(23) Willensdorfer, M.; Bürger, R.; Nowak, M. A. Phenotypic mutation rates and the abundance of abnormal proteins in yeast. PLoS Comput. Biol. 2007, 3 (11), e203. DOI: 10.1371/journal.pcbi.0030203
(24) Sydow, J. F.; Cramer, P. RNA polymerase fidelity and transcriptional proofreading. Curr. Opin. Struct. Biol. 2009, 19 (6), 732–739. DOI: 10.1016/j.sbi.2009.10.009
(25) Thomas, M. J.; Platas, A. A.; Hawley, D. K. Transcriptional fidelity and proofreading by RNA polymerase II. Cell 1998, 93 (4), 627–637. DOI: 10.1016/S0092-8674(00)81191-5
(26) Jeon, C.; Agarwal, K. Fidelity of RNA polymerase II transcription controlled by elongation factor TFIIS. Proc. Natl. Acad. Sci. U.S.A. 1996, 93 (24), 13677–13682. DOI: 10.1073/pnas.93.24.13677
(27) Traverse, C. C.; Ochman, H. Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles. Proc. Natl. Acad. Sci. U.S.A. 2016, 113 (12), 3311–3316. DOI: 10.1073/pnas.1525329113
(28) Merino, E.; Balbas, P.; Puente, J. L.; Bolivar, F. Antisense overlapping open reading frames in genes from bacteria to human. Trends Genet. 1994, 10 (5), 160–164. DOI: 10.1016/0168-9525(94)90125-2
(29) Silke, J. The majority of long non-stop reading frames on the antisense strand can be explained by biased codon usage. Gene 1997, 194 (1), 143–155. DOI: 10.1016/S0378-1119(97)00199-6
(30) Rother, K. I.; Silke, J.; Georgiev, O.; Schaffner, W.; Matsuo, K. Influence of DNA sequence and methylation status on the open reading frames in the antisense strand of the Hsp70 and PrP genes. Biol. Chem. 1997, 378 (12), 1521–1530. DOI: 10.1515/bchm.1997.378.12.1521
(31) Forsdyke, D. R. Sense in antisense? J. Mol. Evol. 1995, 41 (5), 582–586. DOI: 10.1007/bf00175816
(32) Merino, E.; Balbás, P.; Puente, J. L.; Bolívar, F. Antisense overlapping open reading frames in genes from bacteria to humans. Nucleic Acids Res. 1994, 22 (10), 1903–1908. DOI: 10.1093/nar/22.10.1903
(33) Michel, A. M.; Fox, G.; Kiran, A. M.; et al. GWIPS-viz: development of a ribo-seq genome browser. Nucleic Acids Res. 2014, 42 (D1), D859–D864. DOI: 10.1093/nar/gkt1035
(34) Michel, A. M.; Kiniry, S. J.; O'Connor, P. B. F.; Mullan, J. P. A.; Baranov, P. V. GWIPS-viz: 2018 update. Nucleic Acids Res. 2018, 46 (D1), D823–D830. DOI: 10.1093/nar/gkx790
(35) Sabath, N.; Landan, G.; Graur, D. A method for the simultaneous estimation of selection intensities in overlapping genes. PLoS One 2008, 3 (12), e3996. DOI: 10.1371/journal.pone.0003996
(36) Monit, C.; Goldstein, R. A.; Towers, G. J.; et al. Positive selection analysis of overlapping reading frames is invalid. AIDS Res. Hum. Retroviruses 2015, 31 (11), 1147–1148. DOI: 10.1089/aid.2015.0150
(37) Wei, X.; Zhang, J. A simple method for estimating the strength of natural selection on overlapping genes. Genome Biol. Evol. 2014, 6 (9), 2453–2461. DOI: 10.1093/gbe/evu294
(38) Nelson, C. W.; Ardern, Z.; Wei, X. OLGenie: estimating natural selection to predict functional overlapping genes. Mol. Biol. Evol. 2020, 37 (1), 265–279. DOI: 10.1093/molbev/msaa087
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