Skip to main content
SpringerLink
Log in

How Evolutionary Systems Biology Will Help Understand Adaptive Landscapes and Distributions of Mutational Effects

  • Chapter
  • First Online:
Evolutionary Systems Biology

Part of the book series: Advances in Experimental Medicine and Biology ((volume 751))

Abstract

Population genetics and ecology have been modeling biological systems quantitatively for over 8 decades and their results have contributed greatly to our understanding of the natural world and its evolution. Theories in these areas necessarily had to focus on comparisons of the contribution of different individuals to changes in the bigger picture at the expense of ignoring much of the complexity that exists inside individuals. Current systems biology provides new insights into this complexity within organisms. Here I review developments in evolutionary systems biology that have the potential to lead to a more unified approach that integrates contributions from current systems biology and population genetics. Central integrative concepts in this approach are the adaptive landscape and distributions of mutational effects. Both capture our understanding of the fitness of individuals and how it can change. Fitness is frequently used in population genetics to summarize key properties of individuals. Such properties emerge from the complexity of molecular processes within individuals, often in interaction with the environment. The general principles of this approach are reviewed here. This work can open up new avenues for computing critical quantities for models of long-term evolution, including epistasis, the distribution of deleterious mutational effects, and the frequency of adaptive mutations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Crow JF., Kimura M (1970, 2009) An introduction to population genetics theory. Blackburn Press, Caldwell

    Google Scholar 

  2. Charlesworth B (1994) Evolution in age-structured populations. Cambridge studies in mathematical biology, vol 13, 2nd edn. Cambridge University Press, Cambridge

    Google Scholar 

  3. Brommer JE (2000) The evolution of fitness in life-history theory. Biol Rev Camb Philos Soc 75(3):377–404

    Article  PubMed  CAS  Google Scholar 

  4. Kingsolver JG, Hoekstra HE, Hoekstra JM, Berrigan D, Vignieri SN, Hill CE, Hoang A, Gibert P, Beerli P (2001) The strength of phenotypic selection in natural populations. Am Nat 157(3):245–261

    Article  PubMed  CAS  Google Scholar 

  5. Endler JA (1986) Natural selection in the wild. Monographs in population biology, vol 21. Princeton University Press, NJ

    Google Scholar 

  6. Mitton JB (1997) Selection in natural populations. Oxford University Press, Oxford

    Google Scholar 

  7. Sunyaev S, Ramensky V, Koch I, Lathe W 3rd, Kondrashov AS, Bork P (2001) Prediction of deleterious human alleles. Hum Mol Genet 10(6):591–597

    Article  PubMed  CAS  Google Scholar 

  8. Eyre-Walker A, Keightley PD (2007) The distribution of fitness effects of new mutations. Nat Rev Genet 8(8):610–618

    Article  PubMed  CAS  Google Scholar 

  9. Loewe L, Charlesworth B (2006) Inferring the distribution of mutational effects on fitness in Drosophila. Biol Lett 2(3):426–430

    Article  PubMed  Google Scholar 

  10. Loewe L, Charlesworth B, Bartolomé C, Nöel V (2006) Estimating selection on non-synonymous mutations. Genetics 172:1079–1092

    Article  PubMed  CAS  Google Scholar 

  11. Eyre-Walker A, Woolfit M, Phelps T (2006) The distribution of fitness effects of new deleterious amino acid mutations in humans. Genetics 173(2):891–900

    Article  PubMed  CAS  Google Scholar 

  12. Keightley PD, Halligan DL (2011) Inference of site frequency spectra from high-throughput sequence data: quantification of selection on nonsynonymous and synonymous sites in humans. Genetics 188(4):931–940 doi:10.1534/genetics.111.128355

    Article  PubMed  Google Scholar 

  13. Schneider A, Charlesworth B, Eyre-Walker A, Keightley PD (2011) A method for inferring the rate of occurrence and fitness effects of advantageous mutations. Genetics 189:1427–1437

    Article  PubMed  CAS  Google Scholar 

  14. Keightley PD, Eyre-Walker A (2007) Joint inference of the distribution of fitness effects of deleterious mutations and population demography based on nucleotide polymorphism frequencies. Genetics 177(4):2251–2261

    Article  PubMed  CAS  Google Scholar 

  15. Keightley PD, Eyre-Walker A (2010) What can we learn about the distribution of fitness effects of new mutations from DNA sequence data? Philos Trans Roy Soc Lond B Biol Sci 365(1544):1187–1193 doi:10.1098/rstb.2009.0266

    Article  Google Scholar 

  16. Orr HA (2005) The genetic theory of adaptation: a brief history. Nat Rev Genet 6(2):119–127

    Article  PubMed  CAS  Google Scholar 

  17. Orr HA (2010) The population genetics of beneficial mutations. Philos Trans Roy Soc Lond B Biol Sci 365:1195–1201

    Article  Google Scholar 

  18. Kitano H (2002) Computational systems biology. Nature 420(6912):206–210

    Article  PubMed  CAS  Google Scholar 

  19. Kitano H (2002) Systems biology: a brief overview. Science 295(5560):1662–1664

    Article  PubMed  CAS  Google Scholar 

  20. Loewe L (2007) Poster: An evolutionary framework for systems biology. In: 41th Population Genetics Group Meeting, Warwick, UK. http://www.populationgeneticsgroup.org/wpcontent/uploads/2010/01/PGGWarwickProgramme.pdf and http://evolution.ws/people/loewe/posters

  21. Loewe L (2009) A framework for evolutionary systems biology. BMC Syst Biol 3:27

    Article  PubMed  Google Scholar 

  22. Loewe L, Hillston J (2008) The distribution of mutational effects on fitness in a simple circadian clock. Lect Notes Bioinform 5307:156–175

    Google Scholar 

  23. Gavrilets S (2004) Fitness landscapes and the origin of species, Monographs in population biology, Princeton University Press, NJ 41:476

    Google Scholar 

  24. Joyce AR, Palsson BO (2008) Predicting gene essentiality using genome-scale in silico models. Meth Mol Biol 416:433–457

    Article  CAS  Google Scholar 

  25. Samal A, Matias Rodrigues JF, Jost J, Martin OC, Wagner A (2010) Genotype networks in metabolic reaction spaces. BMC Syst Biol 4:30

    Article  PubMed  Google Scholar 

  26. Cowperthwaite MC, Economo EP, Harcombe WR, Miller EL, Meyers LA (2008) The ascent of the abundant: how mutational networks constrain evolution. PLoS Comput Biol 4(7):e1000110

    Article  PubMed  Google Scholar 

  27. Dodd AN, Salathia N, Hall A, Kevei E, Toth R, Nagy F, Hibberd JM, Millar AJ, Webb AAR (2005) Plant circadian clocks increase photosynthesis, growth, survival, and competitive advantage. Science 309(5734):630–633

    Article  PubMed  CAS  Google Scholar 

  28. Loewe L, Hillston J (2012) Evolutionary systems biology estimates of distributions of mutational effects in a circadian clock (in preparation)

    Google Scholar 

  29. MacLean RC, Perron GG, Gardner A (2010) Diminishing returns from beneficial mutations and pervasive epistasis shape the fitness landscape for rifampicin resistance in Pseudomonas aeruginosa. Genetics 186(4):1345–1354. doi:10.1534/genetics.110.123083

    Article  PubMed  CAS  Google Scholar 

  30. You L., Yin J (2002) Dependence of epistasis on environment and mutation severity as revealed by in silico mutagenesis of phage t7. Genetics 160(4):1273–1281

    PubMed  Google Scholar 

  31. You L, Suthers PF, Yin J (2002) Effects of Escherichia coli physiology on growth of phage T7 in vivo and in silico. J Bacteriol 184(7):1888–1894

    Article  PubMed  CAS  Google Scholar 

  32. Endy D, You L, Yin J, Molineux IJ (2000) Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes. Proc Natl Acad Sci USA 97(10):5375–5380

    Article  PubMed  CAS  Google Scholar 

  33. Segre D, Deluna A, Church GM, Kishony R (2005) Modular epistasis in yeast metabolism. Nat Genet 37(1):77–83

    PubMed  CAS  Google Scholar 

  34. Medina M (2005) Genomes, phylogeny, and evolutionary systems biology. Proc Natl Acad Sci USA 102(1):6630–6635

    Article  PubMed  CAS  Google Scholar 

  35. Koonin EV, Wolf YI (2006) Evolutionary systems biology: links between gene evolution and function. Curr Opin Biotechnol 17(5):481–487

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

I thank the editor and two anonymous reviewers for helpful comments on this manuscript and the Wisconsin Institute for Discovery at the University of Wisconsin-Madison for support.

Author information

Authors and Affiliations

  1. Laboratory of Genetics and Wisconsin Institute for Discovery, University of Wisconsin-Madison, 330 North Orchard St., Madison, WI, 53715, USA

    Laurence Loewe

Authors
  1. Laurence Loewe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Laurence Loewe .

Editor information

Editors and Affiliations

  1. University of Exeter, Prince of Wales Road, Exeter, EX4 4SB, Devon, United Kingdom

    Orkun S. Soyer

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Loewe, L. (2012). How Evolutionary Systems Biology Will Help Understand Adaptive Landscapes and Distributions of Mutational Effects. In: Soyer, O. (eds) Evolutionary Systems Biology. Advances in Experimental Medicine and Biology, vol 751. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3567-9_18

Download citation

Publish with us

Policies and ethics

Search

Navigation