Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 12 (12), e1005066
eCollection

Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms

Affiliations

Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms

Thomas LaBar et al. PLoS Comput Biol.

Abstract

A major aim of evolutionary biology is to explain the respective roles of adaptive versus non-adaptive changes in the evolution of complexity. While selection is certainly responsible for the spread and maintenance of complex phenotypes, this does not automatically imply that strong selection enhances the chance for the emergence of novel traits, that is, the origination of complexity. Population size is one parameter that alters the relative importance of adaptive and non-adaptive processes: as population size decreases, selection weakens and genetic drift grows in importance. Because of this relationship, many theories invoke a role for population size in the evolution of complexity. Such theories are difficult to test empirically because of the time required for the evolution of complexity in biological populations. Here, we used digital experimental evolution to test whether large or small asexual populations tend to evolve greater complexity. We find that both small and large-but not intermediate-sized-populations are favored to evolve larger genomes, which provides the opportunity for subsequent increases in phenotypic complexity. However, small and large populations followed different evolutionary paths towards these novel traits. Small populations evolved larger genomes by fixing slightly deleterious insertions, while large populations fixed rare beneficial insertions that increased genome size. These results demonstrate that genetic drift can lead to the evolution of complexity in small populations and that purifying selection is not powerful enough to prevent the evolution of complexity in large populations.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Final genome size as a function of population size.
Red lines are the median values for each population size. The upper and lower limits of each box denote the third and first quartile, respectively. Whiskers are 1.5 times the relevant quartile value. Plus signs denote those data points beyond the whiskers. Data represent only those populations that did not go extinct.
Fig 2
Fig 2. Proportion of slightly-deleterious insertions as a function of population size.
Red lines are the median values for each population size. The upper and lower limits of each box denote the third and first quartile, respectively. Whiskers are 1.5 times the relevant quartile value. Plus signs denote those data points beyond the whiskers. Data represent only those populations that did not go extinct.
Fig 3
Fig 3. Proportion of insertions under positive selection as a function of population size.
Red lines are the median values for each population size. The upper and lower limits of each box denote the third and first quartile, respectively. Whiskers are 1.5 times the relevant quartile value. Plus signs denote those data points beyond the whiskers. Data represent only those populations that did not go extinct.
Fig 4
Fig 4. Final number of evolved phenotypic traits as a function of population size.
Red lines are the median values for each population size. The upper and lower limits of each box denote the third and first quartile, respectively. Whiskers are 1.5 times the relevant quartile value. Plus signs denote those data points beyond the whiskers. Data represent only those populations that did not go extinct.
Fig 5
Fig 5. Correlation between the final genome size and the final number of evolved traits.
Black circles represent the combined data from populations with 10, 100, 1000, and 10000 individuals. Only replicates that survived all 2.5×105 generations were included.

Similar articles

See all similar articles

Cited by 5 PubMed Central articles

References

    1. Bonner JT. The evolution of complexity by means of natural selection. Princeton: Princeton University Press; 1988.
    1. Adami C, Ofria C, Collier TC. Evolution of biological complexity. Proceedings of the National Academy of Sciences. 2000;97:4463–4468. 10.1073/pnas.97.9.4463 - DOI - PMC - PubMed
    1. Koonin EV. A non-adaptationist perspective on evolution of genomic complexity or the continued dethroning of man. Cell Cycle. 2004;3:278–283. 10.4161/cc.3.3.745 - DOI - PubMed
    1. Lynch M. The frailty of adaptive hypotheses for the origins of organismal complexity. Proceedings of the National Academy of Sciences. 2007;104(Suppl 1):8597–8604. 10.1073/pnas.0702207104 - DOI - PMC - PubMed
    1. Tenaillon O, Silander OK, Uzan JP, Chao L. Quantifying organismal complexity using a population genetic approach. PLoS One. 2007;2:e217 10.1371/journal.pone.0000217 - DOI - PMC - PubMed

Publication types

Grant support

This work was supported by a Michigan State University Distinguished Fellowship to TL, and by the National Science Foundation’s BEACON Center for the Study of Evolution in Action, under contract No. DBI-0939454. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Feedback