Clonal Interference and the Evolution of RNA Viruses Rosario Miralles, 1 Philip J. Gerrish, 2 * Andre ´s Moya, 1 Santiago F. Elena 1 † In asexual populations, beneﬁcial mutations that occur in different lineages compete with one another. This phenomenon, known as clonal interference, ensures that those beneﬁcial mutations that do achieve ﬁxation are of large effect. Clonal interference also increases the time between ﬁxations, thereby slowing the adaptation of asexual populations. The effects of clonal interference were measured in the asexual RNA virus vesicular stomatitis virus; rates and average effects of beneﬁcial mutations were quantiﬁed. Populations adapt through the appearance and subsequent fixation of beneficial muta- tions. In a large population, beneficial muta- tions may arise frequently enough that two or more are simultaneously present in indepen- dent lineages. Once beneficial mutations have arisen, there is a certain probability of losing them by drift while their frequency is low. However, after this period dominated by drift, they reach a substantial frequency in the population. For a sexual system, these bene- ficial mutations will eventually recombine, ensuring their fixation together. If the system is asexual, the lineages created by these ben- eficial mutations will compete; only the mu- tation with largest effect will be fixed. Thus, asexual populations must fix beneficial mu- tations sequentially (1, 2). The possibility of simultaneous fixation of beneficial mutations in sexual populations is often contrasted with the sequential fixation in asexual populations as an argument for the evolutionary advan- tage of sex (2). The idea that beneficial mutations must compete in asexual populations was original- ly proposed by Muller (3), and it has been developed theoretically (4 ), as well as exper- imentally demonstrated to be important in determining the rate of adaptation of the bac- terium Escherichia coli (5). Gerrish and Len- ski (4 ) modeled the fate of beneficial muta- tions by considering clonal interference among them as a major factor. The main conclusions of their model were as follows: (i) The probability of fixation of a given beneficial mutation decreases with both pop- ulation size and mutation rate. (ii) As popu- lation size or mutation rate increase, adaptive substitutions result in larger fitness increases. (iii) The rate of adaptation is an increasing, but decelerating, function of both population size and mutation rate. (iv) Beneficial muta- tions that become transiently common but do not achieve fixation because of interfering beneficial mutations are relatively abundant. (v) Transient polymorphisms may give rise to a “leapfrog” effect, where the most common genotype at a given moment might be less closely related to the immediately preceding one than with an earlier genotype. RNA viruses show the highest mutation rates in nature (6 ). This, together with their potentially large effective population sizes and the fact that their reproduction is not obligately sexual, suggests that clonal inter- ference may play an important role in their adaptive evolution. Our goal here is to infer the presence of clonal interference acting on viral populations. Following (4 ), for increas- ing population sizes, we predicted that (i) the fitness effect associated with fixed beneficial mutation will tend to be larger and (ii) the rate of adaptation will tend toward a limit. To detect experimentally the fixation of a beneficial mutation in a viral population, we mixed, at equal proportions, two variants of vesicular stomatitis virus (VSV) that differ only in their ability to grow in the presence of a monoclonal antibody (7 ). The two variants were selectively equivalent in the absence of monoclonal antibody (7 ), implying that they should stably coexist until a successful ben- eficial mutation appears in one of them. Sev- en different evolutionary regimes were de- signed, each one differing from the others in effective population size (N e ). As shown in Table 1, N e ranged in these seven regimes between 100 and 10 8 viral particles (8). Each regime was independently replicated five times, for a total of 35 experimental lines. Each mixture was kept under the ap- propriate batch transfer conditions (9) until one of the two variants became fixed. Then, the winner variant that carried a beneficial mutation was isolated. This variant was then placed in head-to-head competition with its nonevolved counterpart (10) to estimate the fitness effect (W ) associated with the benefi- cial mutation that drove it to fixation. For the smallest population sizes, one can expect genetic drift to play a role in fixing neutral, or even deleterious, mutations. How- ever, previous results have shown that for MARM C clone, the smallest N e used here did not have a considerable deleterious effect (11). Thus, we can safely assume that the fixation of deleterious mutations during our experiment will be minimized by purifying selection. The estimates obtained for W, under the seven different population-size regimes (12), are shown in Fig. 1. The first prediction we made on the basis of the clonal interference model is completely fulfilled: A significant correlation exists between log N e and the magnitude of the fitness effect ( S = 0.8929, n = 7, one-tailed P = 0.0034). The larger the population size is (that is, the stronger the clonal interference), the larger the magnitude of the beneficial effect needed to fix a muta- tion is. As population size increases, there is a shorter waiting time between two consecu- tive events of beneficial mutation, and there- by more beneficial mutations coexist at a given time. Each one of the W values used to generate Fig. 1 was transformed into rates of evolution by subtracting from them the fitness of the initial MARM C clone (7 ) and dividing by the approximate time it took each mutation to become fixed in the population (Table 1). Following (5), we then regressed these rates against N e using (i) a linear model, which implies that the rate of adaptation is propor- tional to the effective population size, and (ii) a hyperbolic model, which implies that clonal interference will impose a deceleration on the rate of adaptation. These data, as well as the fitting of both models, are shown in Fig. 2. 1 Institut Cavanilles de Biodiversitat i Biologı ´a Evolu- tiva and Departament de Gene `tica, Universitat de Vale `ncia, Apartado 22085, 46071 Vale `ncia, Spain. 2 Center for Disease Control and Prevention, Atlanta, GA 30333, USA. *Present address: Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. †To whom correspondence should be addressed. E- mail: santiago.elena@uv.es Table 1. Parameters describing the ﬁxation of beneﬁcial mutations under each N e . The number of lines that increased ﬁtness is reported in the second column. The third column shows the num- ber of generations elapsed until ﬁxation of a ben- eﬁcial mutation (8). A signiﬁcant correlation be- tween log N e and the time to ﬁxation has been observed ( S = 0.75, n = 5, one-tail P = 0.0261). The last column shows the probability of ﬁxation by random genetic drift (15). Log N e Lines that increased ﬁtness Time to ﬁxation P 2.0238 1 76.045  17.168 0.0440 3.4247 4 234.003  48.354 0.0113 4.3644 3 185.099  32.356 0.0001 5.2940 5 288.693  18.558 0.0001 6.2103 5 328.922  31.558 0.0001 7.1065 5 347.502  13.839 0.0001 7.9695 5 283.386  9.943 0.0001 R EPORTS www.sciencemag.org SCIENCE VOL 285 10 SEPTEMBER 1999 1745