Fitness landscape of a dynamic RNA structure

Autoři: Valerie W. C. Soo aff001;  Jacob B. Swadling aff001;  Andre J. Faure aff003;  Tobias Warnecke aff001
Působiště autorů: Medical Research Council London Institute of Medical Sciences, London, United Kingdom aff001;  Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom aff002;  Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain aff003
Vyšlo v časopise: Fitness landscape of a dynamic RNA structure. PLoS Genet 17(2): e1009353. doi:10.1371/journal.pgen.1009353
Kategorie: Research Article


RNA structures are dynamic. As a consequence, mutational effects can be hard to rationalize with reference to a single static native structure. We reasoned that deep mutational scanning experiments, which couple molecular function to fitness, should capture mutational effects across multiple conformational states simultaneously. Here, we provide a proof-of-principle that this is indeed the case, using the self-splicing group I intron from Tetrahymena thermophila as a model system. We comprehensively mutagenized two 4-bp segments of the intron. These segments first come together to form the P1 extension (P1ex) helix at the 5’ splice site. Following cleavage at the 5’ splice site, the two halves of the helix dissociate to allow formation of an alternative helix (P10) at the 3’ splice site. Using an in vivo reporter system that couples splicing activity to fitness in E. coli, we demonstrate that fitness is driven jointly by constraints on P1ex and P10 formation. We further show that patterns of epistasis can be used to infer the presence of intramolecular pleiotropy. Using a machine learning approach that allows quantification of mutational effects in a genotype-specific manner, we demonstrate that the fitness landscape can be deconvoluted to implicate P1ex or P10 as the effective genetic background in which molecular fitness is compromised or enhanced. Our results highlight deep mutational scanning as a tool to study alternative conformational states, with the capacity to provide critical insights into the structure, evolution and evolvability of RNAs as dynamic ensembles. Our findings also suggest that, in the future, deep mutational scanning approaches might help reverse-engineer multiple alternative or successive conformations from a single fitness landscape.

Klíčová slova:

Fitness epistasis – Introns – Mutation detection – Natural selection – Nucleotides – RNA structure – Tetrahymena – Tetrahymena thermophila


1. Chen Y, Carlini DB, Baines JF, Parsch J, Braverman JM, Tanda S, et al. RNA secondary structure and compensatory evolution. Genes Genet Syst. 1999;74: 271–286. doi: 10.1266/ggs.74.271 10791023

2. Umu SU, Poole AM, Dobson RC, Gardner PP, Adelman K. Avoidance of stochastic RNA interactions can be harnessed to control protein expression levels in bacteria and archaea. eLife. eLife Sciences Publications Limited; 2016;5: e13479. doi: 10.7554/eLife.13479 27642845

3. Pitt JN, Ferré-D'Amaré AR. Rapid Construction of Empirical RNA Fitness Landscapes. Science. American Association for the Advancement of Science; 2010;330: 376–379. doi: 10.1126/science.1192001 20947767

4. Petrie KL, Joyce GF. Limits of Neutral Drift: Lessons From the In Vitro Evolution of Two Ribozymes. J Mol Evol. Springer US; 2014;79: 75–90. doi: 10.1007/s00239-014-9642-z 25155818

5. Hayden EJ, Ferrada E, Wagner A. Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme. Nature. Nature Publishing Group; 2011;474: 92–95. doi: 10.1038/nature10083 21637259

6. Pressman AD, Liu Z, Janzen E, Blanco C, Müller UF, Joyce GF, et al. Mapping a Systematic Ribozyme Fitness Landscape Reveals a Frustrated Evolutionary Network for Self-Aminoacylating RNA. J Am Chem Soc. American Chemical Society; 2019;141: 6213–6223. doi: 10.1021/jacs.8b13298 30912655

7. Kobori S, Yokobayashi Y. High-Throughput Mutational Analysis of a Twister Ribozyme. Angew Chem Int Ed. 2016;55: 10354–10357. doi: 10.1002/anie.201605470 27461281

8. Andreasson JOL, Savinov A, Block SM, Greenleaf WJ. Comprehensive sequence-to-function mapping of cofactor-dependent RNA catalysis in the glmS ribozyme. Nature Communications. 2020;11: 143. doi: 10.1038/s41467-019-14093-2 31919424

9. Guy MP, Young DL, Payea MJ, Zhang X, Kon Y, Dean KM, et al. Identification of the determinants of tRNA function and susceptibility to rapid tRNA decay by high-throughput in vivo analysis. Genes & Development. Cold Spring Harbor Lab; 2014;28: 1721–1732. doi: 10.1101/gad.245936.114 25085423

10. Li C, Qian W, Maclean CJ, Zhang J. The fitness landscape of a tRNA gene. Science. American Association for the Advancement of Science; 2016;352: 837–840. doi: 10.1126/science.aae0568 27080104

11. Puchta O, Cseke B, Czaja H, Tollervey D, Sanguinetti G, Kudla G. Network of epistatic interactions within a yeast snoRNA. Science. American Association for the Advancement of Science; 2016;352: 840–844. doi: 10.1126/science.aaf0965 27080103

12. Domingo J, Diss G, Ben Lehner. Pairwise and higher-order genetic interactions during the evolution of a tRNA. Nature. Nature Publishing Group; 2018;558: 117–121. doi: 10.1038/s41586-018-0170-7 29849145

13. Zhang ZD, Nayar M, Ammons D, Rampersad J, Fox GE. Rapid in vivo exploration of a 5S rRNA neutral network. Journal of Microbiological Methods. Elsevier; 2009;76: 181–187. doi: 10.1016/j.mimet.2008.10.010 19041908

14. Li C, Zhang J. Multi-environment fitness landscapes of a tRNA gene. Nat Ecol Evol. Nature Publishing Group; 2018;2: 1025–1032. doi: 10.1038/s41559-018-0549-8 29686238

15. Lalić J, Elena SF. The impact of high-order epistasis in the within-host fitness of a positive-sense plant RNA virus. J Evolution Biol. John Wiley & Sons, Ltd; 2015;28: 2236–2247. doi: 10.1111/jeb.12748 26344415

16. Bendixsen DP, Østman B, Hayden EJ. Negative Epistasis in Experimental RNA Fitness Landscapes. J Mol Evol. Springer US; 2017;85: 159–168. doi: 10.1007/s00239-017-9817-5 29127445

17. Weinreich DM, Lan Y, Wylie CS, Heckendorn RB. Should evolutionary geneticists worry about higher-order epistasis? Current Opinion in Genetics & Development. 2013;23: 700–707. doi: 10.1016/j.gde.2013.10.007 24290990

18. Ganser LR, Kelly ML, Herschlag D, Al-Hashimi HM. The roles of structural dynamics in the cellular functions of RNAs. Nature Publishing Group. 2019;20: 474–489. doi: 10.1038/s41580-019-0136-0 31182864

19. Cech TR. Self-Splicing of Group I Introns. Annu Rev Biochem. Annual Reviews 4139 El Camino Way, P.O. Box 10139, Palo Alto, CA 94303–0139, USA; 1990;59: 543–568. doi: 10.1146/

20. Guo F, Cech TR. In vivo selection of better self-splicing introns in Escherichia coli: the role of the P1 extension helix of the Tetrahymena intron. RNA. Cold Spring Harbor Lab; 2002;8: 647–658. doi: 10.1017/s1355838202029011 12022231

21. Michel F, Hanna M, Green R, Bartel DP, Szostak JW. The guanosine binding site of the Tetrahymena ribozyme. Nature. Nature Publishing Group; 1989;342: 391–395. doi: 10.1038/342391a0 2685606

22. Price JV, Cech TR. Determinants of the 3' splice site for self-splicing of the Tetrahymena pre-rRNA. Genes & Development. Cold Spring Harbor Lab; 1988;2: 1439–1447. doi: 10.1101/gad.2.11.1439 3209068

23. Been MD, Cech TR. Sites of circularization of the Tetrahymena rRNA IVS are determined by sequence and influenced by position and secondary structure. Nucleic Acids Research. Oxford University Press; 1985;13: 8389–8408. doi: 10.1093/nar/13.23.8389 4080546

24. Narlikar GJ, Bartley LE, Herschlag D. Use of duplex rigidity for stability and specificity in RNA tertiary structure. Biochemistry. 2000;39: 6183–6189. doi: 10.1021/bi992858a 10821693

25. Bell MA, Sinha J, Johnson AK, Testa SM. Enhancing the Second Step of the Trans Excision-Splicing Reaction of a Group I Ribozyme by Exploiting P9.0 and P10 for Intermolecular Recognition. Biochemistry. American Chemical Society; 2004;43: 4323–4331. doi: 10.1021/bi035874n 15065876

26. Suh ER, Waring RB. Base pairing between the 3”exon and an internal guide sequence increases 3” splice site specificity in the Tetrahymena self-splicing rRNA intron. Molecular and Cellular Biology. American Society for Microbiology Journals; 1990;10: 2960–2965. doi: 10.1128/mcb.10.6.2960 2342465

27. Karbstein K, Lee J, Herschlag D. Probing the Role of a Secondary Structure Element at the 5‘- and 3‘-Splice Sites in Group I Intron Self-Splicing: The Tetrahymena L-16 ScaI Ribozyme Reveals a New Role of the G·U Pair in Self-Splicing. Biochemistry. American Chemical Society; 2007;46: 4861–4875. doi: 10.1021/bi062169g 17385892

28. Doudna JA, Cormack BP, Szostak JW. RNA structure, not sequence, determines the 5' splice-site specificity of a group I intron. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences; 1989;86: 7402–7406. doi: 10.1073/pnas.86.19.7402 2678103

29. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. BioMed Central; 2014;15: 550. doi: 10.1186/s13059-014-0550-8 25516281

30. Bolognesi B, Faure AJ, Seuma M, Schmiedel JM, Tartaglia GG, Ben Lehner. The mutational landscape of a prion-like domain. Nature Communications. Nature Publishing Group; 2019;10: 1–12. doi: 10.1038/s41467-018-07882-8 30602773

31. Faure AJ, Schmiedel JM, Baeza-Centurion P, Ben Lehner. DiMSum: an error model and pipeline for analyzing deep mutational scanning data and diagnosing common experimental pathologies. Genome Biol. BioMed Central; 2020;21: 1–23. doi: 10.1186/s13059-020-02091-3 32799905

32. Kemble H, Nghe P, Tenaillon O. Recent insights into the genotype–phenotype relationship from massively parallel genetic assays. Evolutionary Applications. John Wiley & Sons, Ltd; 2019;12: 1721–1742. doi: 10.1111/eva.12846 31548853

33. Chen T, Guestrin C. XGBoost: a scalable tree boosting system. 2016. pp. 785–794.

34. Lundberg SM, Lee S-I. A Unified Approach to Interpreting Model Predictions. 2017. pp. 4765–4774.

35. Lundberg SM, Erion G, Chen H, DeGrave A, Prutkin JM, Nair B, et al. From local explanations to global understanding with explainable AI for trees. Nat Mach Intell. Nature Publishing Group; 2020;2: 56–67. doi: 10.1038/s42256-019-0138-9 32607472

36. Allain FHT, Varani G. Structure of the P1 Helix from Group I Self-splicing Introns. Journal of Molecular Biology. Academic Press; 1995;250: 333–353. doi: 10.1006/jmbi.1995.0381 7608979

37. Lu X-J, Olson WK. 3DNA: a software package for the analysis, rebuilding and visualization of three-dimensional nucleic acid structures. Nucleic Acids Research. 2003;31: 5108–5121. doi: 10.1093/nar/gkg680 12930962

38. Strobel SA, Cech TR. Exocyclic amine of the conserved G.U pair at the cleavage site of the Tetrahymena ribozyme contributes to 5'-splice site selection and transition state stabilization. Biochemistry. 1996;35: 1201–1211. doi: 10.1021/bi952244f 8573575

39. Strobel SA, Cech TR. Minor groove recognition of the conserved G.U pair at the Tetrahymena ribozyme reaction site. Science. American Association for the Advancement of Science; 1995;267: 675–679. doi: 10.1126/science.7839142 7839142

40. Strobel SA, Ortoleva-Donnelly L, Ryder SP, Cate JH, Moncoeur E. Complementary sets of noncanonical base pairs mediate RNA helix packing in the group I intron active site. Nat Struct Mol Biol. Nature Publishing Group; 1998;5: 60–66. doi: 10.1038/nsb0198-60 9437431

41. Strobel SA, Cech TR. Tertiary interactions with the internal guide sequence mediate docking of the P1 helix into the catalytic core of the Tetrahymena ribozyme. Biochemistry. 1993;32: 13593–13604. doi: 10.1021/bi00212a027 7504953

42. Ferretti L, Schmiegelt B, Weinreich D, Yamauchi A, Kobayashi Y, Tajima F, et al. Measuring epistasis in fitness landscapes: The correlation of fitness effects of mutations. Journal of Theoretical Biology. Academic Press; 2016;396: 132–143. doi: 10.1016/j.jtbi.2016.01.037 26854875

43. Doerder FP. Barcodes Reveal 48 New Species of Tetrahymena, Dexiostoma, and Glaucoma: Phylogeny, Ecology, and Biogeography of New and Established Species. J Eukaryot Microbiol. John Wiley & Sons, Ltd; 2019;66: 182–208. doi: 10.1111/jeu.12642 29885050

44. Repar J, Warnecke T. Mobile Introns Shape the Genetic Diversity of Their Host Genes. Genetics. Genetics; 2017;205: 1641–1648. doi: 10.1534/genetics.116.199059 28193728

45. Goddard MR, Burt A. Recurrent invasion and extinction of a selfish gene. Proceedings of the National Academy of Sciences of the United States of America. National Acad Sciences; 1999;96: 13880–13885. doi: 10.1073/pnas.96.24.13880 10570167

46. Torgerson CD, Hiller DA, Stav S, Strobel SA. Gene regulation by a glycine riboswitch singlet uses a finely tuned energetic landscape for helical switching. RNA. Cold Spring Harbor Laboratory Press; 2018;24: 1813–1827. doi: 10.1261/rna.067884.118 30237163

47. Woodson SA, Cech TR. Alternative secondary structures in the 5' exon affect both forward and reverse self-splicing of the Tetrahymena intervening sequence RNA. Biochemistry. 1991;30: 2042–2050. doi: 10.1021/bi00222a006 1998665

48. Schmiedel JM, Ben Lehner. Determining protein structures using deep mutagenesis. Nat Genet. Nature Publishing Group; 2019;51: 1177–1186. doi: 10.1038/s41588-019-0431-x 31209395

49. Marks DS, Colwell LJ, Sheridan R, Hopf TA, Pagnani A, Zecchina R, et al. Protein 3D Structure Computed from Evolutionary Sequence Variation. Sali A, editor. PLoS ONE. Public Library of Science; 2011;6: e28766. doi: 10.1371/journal.pone.0028766 22163331

50. Morcos F, Pagnani A, Lunt B, Bertolino A, Marks DS, Sander C, et al. Direct-coupling analysis of residue coevolution captures native contacts across many protein families. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences; 2011;108: E1293–E1301. doi: 10.1073/pnas.1111471108 22106262

51. Wayne J, Xu S-Y. Identification of a thermophilic plasmid origin and its cloning within a new Thermus-E. coli shuttle vector. Gene. 1997;195: 321–328. doi: 10.1016/s0378-1119(97)00191-1 9305778

52. Sambrook J, Russell D. Molecular cloning: a laboratory manual. 3rd ed. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press; 2012.

53. Price JV, Engberg J, Cech TR. 5′ exon requirement for self-splicing of the Tetrahymena thermophila pre-ribosomal RNA and identification of a cryptic 5′ splice site in the 3′ exon. Journal of Molecular Biology. 1987;196: 49–60. doi: 10.1016/0022-2836(87)90510-9 2443717

54. Banáš P, Hollas D, Zgarbová M, Jurečka P, Orozco M, Cheatham TE III, et al. Performance of Molecular Mechanics Force Fields for RNA Simulations: Stability of UUCG and GNRA Hairpins. J Chem Theory Comput. 2010;6: 3836–3849. doi: 10.1021/ct100481h

55. Davidchack RL, Handel R, Tretyakov MV. Langevin thermostat for rigid body dynamics. The Journal of Chemical Physics. American Institute of Physics; 2009;130: 234101. doi: 10.1063/1.3149788 19548705

56. Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR. Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics. American Institute of Physics; 1998;81: 3684–3690. doi: 10.1063/1.448118

57. Salomon-Ferrer R, Götz AW, Poole D, Le Grand S, Walker RC. Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald. J Chem Theory Comput. 2013;9: 3878–3888. doi: 10.1021/ct400314y 26592383

58. Götz AW, Williamson MJ, Xu D, Poole D, Le Grand S, Walker RC. Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born. J Chem Theory Comput. 2012;8: 1542–1555. doi: 10.1021/ct200909j 22582031

59. Le Grand S, Götz AW, Walker RC. SPFP: Speed without compromise—A mixed precision model for GPU accelerated molecular dynamics simulations. Computer Physics Communications. North-Holland; 2013;184: 374–380. doi: 10.1016/j.cpc.2012.09.022

60. Roe DR, Cheatham TE. PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data. J Chem Theory Comput. 2013;9: 3084–3095. doi: 10.1021/ct400341p 26583988

61. Humphrey W, Dalke A, Schulten K. VMD: Visual molecular dynamics. Journal of Molecular Graphics. 1996;14: 33–38. doi: 10.1016/0263-7855(96)00018-5 8744570

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