Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 23, 2026.

Evolutionary Accessibility of Mutational Pathways

Jasper Franke, Alexander Klözer, J. Arjan G. M. de Visser and 1 more

PLoS Computational Biology · 2011

doi:10.1371/journal.pcbi.1002134

Abstract

Functional effects of different mutations are known to combine to the total effect in highly nontrivial ways. For the trait under evolutionary selection ('fitness'), measured values over all possible combinations of a set of mutations yield a fitness landscape that determines which mutational states can be reached from a given initial genotype. Understanding the accessibility properties of fitness landscapes is conceptually important in answering questions about the predictability and repeatability of evolutionary adaptation. Here we theoretically investigate accessibility of the globally optimal state on a wide variety of model landscapes, including landscapes with tunable ruggedness as well as neutral 'holey' landscapes. We define a mutational pathway to be accessible if it contains the minimal number of mutations required to reach the target genotype, and if fitness increases in each mutational step. Under this definition accessibility is high, in the sense that at least one accessible pathway exists with a substantial probability that approaches unity as the dimensionality of the fitness landscape (set by the number of mutational loci) becomes large. At the same time the number of alternative accessible pathways grows without bounds. We test the model predictions against an empirical 8-locus fitness landscape obtained for the filamentous fungus Aspergillus niger. By analyzing subgraphs of the full landscape containing different subsets of mutations, we are able to probe the mutational distance scale in the empirical data. The predicted effect of high accessibility is supported by the empirical data and is very robust, which we argue reflects the generic topology of sequence spaces. Together with the restrictive assumptions that lie in our definition of accessibility, this implies that the globally optimal configuration should be accessible to genome wide evolution, but the repeatability of evolutionary trajectories is limited owing to the presence of a large number of alternative mutational pathways.

Full text

Its licence does not allow us to show the full text. Read it at PubMed Central:

Read at PubMed Central

References 49

  1. 1.

    Phillips PC. Epistasis - the essential role of gene interactions in the structure and evolution of genetic systems. Nat Rev Genet. 2008;9:855-867.

    Not in our library10.1038/nrg2452

  2. 2.

    Hall BG. Predicting evolution by in vitro evolution requires determining evolutionary pathways. Antimicrob Agents Chemother. 2002;46:3035-3038.

    Not in our library10.1128/aac.46.9.3035-3038.2002

  3. 3.

    Weinreich DM, Delaney NF, DePristo MA, Hartl DM. Darwinian evolution can follow only very few mutational paths to fitter proteins. Science. 2006;312:111-114.

    Not in our library10.1126/science.1123539

  4. 4.

    Lozovsky ER, Chookajorn T, Brown KM, Imwong M, Shaw PJ, et al. Stepwise acquisition of pyrimethamine resistance in the malaria parasite. Proc Natl Acad Sci U S A. 2009;106:12025-12030.

    Not in our library10.1073/pnas.0905922106

  5. 5.

    Segrè D, DeLuna A, Church GM, Kishony R. Modular epistasis in yeast metabolism. Nat Genet. 2005;37:1.

    Not in our library10.1038/ng1489

  6. 6.

    Weinreich DM, Watson RA, Chao L. Perspective: Sign epistasis and genetic constraints on evolutionary trajectories. Evolution. 2005;59:1165-1174.

    Not in our library

  7. 7.

    Poelwijk FJ, Kiviet DJ, Weinreich DM, Tans SJ. Empirical fitness landscapes reveal accessible evolutionary paths. Nature. 2007;445:383-386.

    Not in our library10.1038/nature05451

  8. 8.
  9. 9.

    Lunzer M, Miller SP, Felsheim R, Dean AM. The biochemical architecture of an ancient adaptive landscape. Science. 2005;310:4899-501.

    Not in our library10.1126/science.1115649

  10. 10.

    de Visser JAGM, Park SC, Krug J. Exploring the effect of sex on empirical fitness landscapes. Am Nat. 2009;174:S15-S30.

    Not in our library10.1086/599081

  11. 11.

    Kogenaru M, de Vos MGJ, Tans SJ. Revealing evolutionary pathways by fitness landscape reconstruction. Crit Rev Biochem Mol. 2009;44:169-174.

    Not in our library10.1080/10409230903039658

  12. 12.

    Dawid A, Kiviet DJ, Kogenaru M, de Vos M, Tans SJ. Multiple peaks and reciprocal sign epistasis in an empirically determined genotype-phenotype landscape. Chaos. 2010;20:026105.

    Not in our library10.1063/1.3453602

  13. 13.

    da Silva J, Coetzer M, Nedellec R, Pastore C, Mosier DE. Fitness epistasis and constraints on adaptation in a human immunodeficiency virus type I protein region. Genetics. 2010;185:293-303.

    Not in our library10.1534/genetics.109.112458

  14. 14.

    Tan L, Serene S, Chao HX, Gore J. Hidden randomness between fitness landscapes limits reverse evolution. Phys Rev Lett. 2011;106:198102.

    Not in our library10.1103/physrevlett.106.198102

  15. 15.

    Chou HH, Chiu HC, Delaney NF, Segré D, Marx CJ. Diminishing returns epistasis among beneficial mutations decelerates adaptation. Science. 2011;332:1190-1192.

    Not in our library10.1126/science.1203799

  16. 16.

    Khan AI, Dinh DM, Schneider D, Lenski RE, Cooper TF. Negative epistasis between beneficial mutations in an evolving bacterial population. Science. 2011;332:1193-1196.

    Not in our library10.1126/science.1203801

  17. 17.

    de Visser JAGM, Hoekstra RF, van den Ende H. Test of interaction between genetic markers that affect fitness in Aspergillus niger. Evolution. 1997;51:1499-1505.

    Not in our library10.1111/j.1558-5646.1997.tb01473.x

  18. 18.

    Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear ED, et al. The genetic landscape of a cell. Science. 2010;327:425-431.

    Not in our library10.1126/science.1180823

  19. 19.

    Fisher RA. The genetical theory of natural selection. 1958.

    Not in our library

  20. 20.

    Wright S. The roles of mutatation, inbreeding, cross-breeding and selection in evolution. Proc Sixth Int Cong Genet. 1932;1:356-366.

    Not in our library

  21. 21.

    Kauffman SA. The Origins of Order. 1993.

    Not in our library

  22. 22.

    Gillespie JH. Population Genetics: A concise guide. 2004.

    Not in our library

  23. 23.

    Hartl DL, Clark AG. Principles of Population Genetics. 1997.

    Not in our library

  24. 24.

    Jain K, Krug J. Deterministic and stochastic regimes of asexual evolution on rugged fitness landscapes. Genetics. 2007;175:1275-1288.

    Not in our library10.1534/genetics.106.067165

  25. 25.

    Gillespie JH. Some properties of finite populations experiencing strong selection and weak mutation. Am Nat. 1983;121:691-708.

    Not in our library

  26. 26.

    Orr HA. The population genetics of adaptation: The adaptation of DNA sequences. Evolution. 2002;56:1317-1330.

    Not in our library10.1111/j.0014-3820.2002.tb01446.x

  27. 27.

    Weinreich DM, Chao L. Rapid evolutionary escape by large populations from local fitness peaks is likely in nature. Evolution. 2005;59:1175-1182.

    Not in our library

  28. 28.

    Weissman DB, Desai MM, Fisher DS, Feldman MW. The rate at which asexual populations cross fitness valleys. Theor Popul Biol. 2009;75:286-300.

    Not in our library10.1016/j.tpb.2009.02.006

  29. 29.

    Kauffman S, Levin S. Towards a general theory of adaptive walks on rugged landscapes. J Theor Biol. 1987;128:11-45.

    Not in our library10.1016/s0022-5193(87)80029-2

  30. 30.

    Gokhale CS, Iwasa Y, Nowak MA, Traulsen A. The pace of evolution across fitness valleys. J Theor Biol. 2009;259:613-620.

    Not in our library10.1016/j.jtbi.2009.04.011

  31. 31.

    Wagner A. Neutralism and selectionism: a network-based reconciliation. Nat Rev Genet. 2008;9:965-974.

    Not in our library10.1038/nrg2473

  32. 32.

    Carneiro M, Hartl DL. Adaptive landscapes and protein evolution. Proc Natl Acad Sci U S A. 2010;107:1747-1751.

    Not in our library10.1073/pnas.0906192106

  33. 33.

    Kingman JFC. A simple model for the balance between mutation and selection. J Appl Prob. 1978;15:1-12.

    Not in our library

  34. 34.

    Franke J, Wergen G, Krug J. Records and sequences of records from random variables with a linear trend. J Stat Mech: Theory Exp. 2010;P10013.

    Not in our library

  35. 35.

    Aita T, Uchiyama H, Inaoka T, Nakajima M, Kokubo T, et al. Analysis of a local fitness landscape with a model of the rough Mt. Fuji-type landscape: Application to protyl endopeptidase and thermolysis. Biopolymers. 2000;54:64-79.

    Not in our library10.1002/(sici)1097-0282(200007)54:1<64::aid-bip70>3.0.co;2-r

  36. 36.

    Kauffman SA, Weinberger ED. The NK model of rugged fitness landscapes and its application to maturation of the immune response. J Theor Biol. 1989;141:211-245.

    Not in our library10.1016/s0022-5193(89)80019-0

  37. 37.

    Durrett R, Limic V. Rigorous results for the NK model. Ann Prob. 2003;31:1713-1753.

    Not in our library

  38. 38.

    Limic V, Pemantle R. More rigorous results on the Kauffman Levin model of evolution. Ann Prob. 2004;32:2149-2178.

    Not in our library

  39. 39.

    Kimura M. The neutral theory of molecular evolution. 1983.

    Not in our library

  40. 40.

    Maynard Smith J. Natural selection and the concept of a protein space. Nature. 1970;225:563-564.

    Not in our library10.1038/225563a0

All 49 references

Cited by papers we hold 6

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.