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Evolution by Small Jerks

Lin Chao
Department of Biology, University of California, San Diego, La Jolla, CA 92039-0116; LChao@biomail.ucsd.edu

Adaptive evolution by the substitution of many mutations of small effect is key to both the modern synthesis and some of the current views of evolutionary biology because it provides the explanation for a variety of phenomena such as the continuity of species variation, polygenic inheritance, the gradualism of phenotypic evolution, and rate variation of molecular clocks (Charlesworth et al. 1982; Lande 1983; Orr and Coyne 1992; Chao 1997). The theoretical explanation for why adaptive evolution should be by small steps is attributed to Fisher (1930), who argued this viewpoint using a geometric model of evolution in multi-dimensional phenotypic space. In Fisher’s model a population is assumed to begin a distance from an adaptive optimum (or peak). As natural selection moves the population towards the peak, Fisher theorized that the approach should be by small steps because advantageous mutations of small effect should be more abundant than those of large effect. The bias against large advantageous mutations results because large mutations (in general) are more likely to have deleterious pleiotropic (side) effects, and the bias increases with the number of phenotypic dimensions, which presumably is correlated with the complexity of the genome (see Burch and Chao 1999).

Testing experimentally whether and why adaptive evolution proceeds by small steps is difficult because it requires a system that can be manipulated and monitored over evolutionary time scales. We have designed a test by taking advantage of the high genomic mutation rate and short generation time of RNA viruses. We tested whether viral evolution involves small steps, but we also devised a test that uses the prediction that advantageous mutations of small effect are more abundant than those of large effect. The latter test considers the fact that, although advantageous mutations of smaller effect may be more common, they should have a smaller selective advantage, and hence a smaller probability of fixation (Crow and Kimura 1970). As a result, in a population that is sufficiently large to harbor advantageous mutations of both large and small effect, evolution should proceed by large steps due to the higher probability of fixation of large mutations. In a small population, however, small advantageous mutations are the only ones sufficiently common to appear. Once they appear, they are swept to fixation by selection, despite their lower probability of fixation, and evolution is by small steps. Thus, when corrected for the probability of fixation, Fisher’s model makes the second prediction that step size during adaptive evolution should be smaller with decreasing size of the population under selection.

We tested both predictions by building on two known results for the RNA bacteriophage 6. First, if 6 is subjected to successive population bottlenecks of one phage, the resulting genetic drift is sufficiently strong to cause the fixation (increase to a frequency of 100%) of deleterious mutations and a decrease in the mean fitness of the population (Chao 1990). Second, if the population that had accrued the fitness decrease is then propagated through a succession of larger bottlenecks, fitness increases because natural selection is now sufficiently strong to override genetic drift (Chao et al. 1992; Chao et al. 1997). We combined these results by determining whether fitness during the decline and the recovery phases in a single population lineage changed by a different number of steps. Additionally, we varied the size of the bottleneck during recovery to determine the effect of population size on step size.

Our results (Burch and Chao 1999) provide strong support for Fisher’s geometric model and evolution by small steps. First, we find that when a population with a deleterious mutation is allowed to recover fitness by natural selection, the recovery is often by many mutations of effects smaller than the magnitude of the initial deleterious mutation. However, our strongest result in support of Fisher’s model comes from the finding a positive relationship between step size and bottleneck. This result confirms qualitatively the model’s major prediction, which is that advantageous mutations of small effect should be more abundant than those of large effect. Such a positive relationship between step size and population size is additionally important because it argues that previous reports of adaptive evolution by both large and small mutations (Orr and Coyne 1992) are not at odds with Fisher’s model. These results may have been mixed because the size of the evolving populations was not taken into consideration, and it may well be that population size could explain the varied outcome. Roush and McKenzie (1987) used a similar reasoning in suggesting that population size could be the explanation for why insecticide resistance is generally due to just one or two loci in natural populations, whereas selection for resistance in (smaller) laboratory populations more commonly produces polygenic resistance.

Our finding of support for Fisher was not entirely expected. A concern had been raised as to whether pleiotropy was sufficiently strong in any organism for Fisher’s explanation to apply (Orr and Coyne 1992), and whether an RNA virus would have a sufficiently complex genetic system to generate the required pleiotropy was uncertain. In fact, because we examined first recovery in the larger populations sizes, in which large steps were observed, we were initially lead to believe that evolution by small steps did not apply to RNA viruses. However, our combined results show clearly that small mutations are possible and that a major prediction of Fisher’s hypothesis, that advantageous mutations of small effect are more common than advantageous mutations of large effect, is supported. This suggests that pleiotropy may indeed be universal (Wright 1968; Gimelfarb 1996), and if 6, an RNA virus with a genome of slightly more than 10⁴ nucleotides and encoding only 13 proteins (Gottlieb et al. 1988), is sufficiently complex, organisms with larger genomes and more elaborate developmental systems and phenotypes must surely also be sufficiently complex.

References
Burch, C. L. and L. Chao. 1999. Evolution by small steps and Rugged Landscapes in the RNA Virus 6. Genetics 151:921-927.

Chao, L., 1990 Fitness of RNA virus decreased by Muller’s ratchet. Nature 348: 454-55.

Chao, L., T. Tran, and C. Matthews, 1992 Muller’s ratchet and the advantage of sex in the RNA virus 6. Evolution 46: 289-299.

Chao, L., T. T. Trang, and T. T. Trang, 1997 The Advantage of Sex in the RNA Virus 6. Genetics 147: 953-959.

Charlesworth, B., R. Lande, and M. Slatkin, 1982 A neo-Darwinian commentary on macroevolution. Evolution 36: 474-98.

Crow, J. F. and M. Kimura, 1970 An Introduction to Population Genetics Theory. Harper and Row, Publishers, New York.

Fisher, R. A., 1930 The Genetical Theory of Natural Selection. Oxford University Press, Oxford. 2nd revised edition, 1958. Dover Publications, Inc., New York.

Gimelfarb, A., 1996 Pleiotropy as a factor maintaining genetic variation in quantitative characters under stabilizing selection. Genetical Research 68: 65-74.

Gottlieb, P., S. Metzger, M. Romantschuk, J. Carton, J. Strassman, D. H. Bamford, N. Kalkkinen, and L. Mindich, 1988. Nucleotide sequence of the middle dsRNA segment of bacteriophage f6: placement of the genes of membrane-associated proteins. Virology 163: 183-190.

Kimura, M., 1983 The Neutral Theory of Molecular Evolution. Cambridge University Press, Cambridge.

Lande, R., 1983 The response to selection on major and minor mutations affecting a metrical trait. Heredity 50: 47-65.

Orr, H. A. and J. A. Coyne, 1992 The Genetics of Adaptation: A Reassessment. The American Naturalist 140: 725-742.

Roush, R. T., and J. A. McKenzie, 1987 Ecological genetics of insecticide and acaricide resistance. Annual Review of Entomology 32: 361-380.

Abstract - Presented at the Virus Evolution Workshop
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October 21 - 24th, 1999

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