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Biomedical subjects

Paulo R A Campos

Publications and source records attributed to Paulo R A Campos.

11 recordsLinked to original sources

Muller's ratchet in random graphs and scale-free networks.

Muller's ratchet is an evolutionary process that has been implicated in the extinction of asexual species, the evolution of mitochondria, the degeneration of the Y chromosome, the evolution of sex and recombination and the evolution of microbes. Here we study the speed of Muller's ratchet in a population subdivided into many small subpopulations connected by migration, and distributed on a network. We compare the speed of the ratchet in two distinct types of topologies: scale free networks and random graphs. The difference between the topologies is noticeable when the average connectivity of the network and the migration rate is large. In this situation we observe that the ratchet clicks faster in scale free networks than in random graphs. So contrary to intuition, scale free networks are more prone to loss of genetic information than random graphs. On the other hand, we show that scale free networks are more robust to the random extinction than random graphs. Since these complex networks have been shown to describe well real-life systems, our results open a framework for studying the evolution of microbes and disease epidemics.

Algorithms↗

Adaptive evolution in a spatially structured asexual population.

We study the process of adaptation in a spatially structured asexual haploid population. The model assumes a local competition for replication, where each organism interacts only with its nearest neighbors. We observe that the substitution rate of beneficial mutations is smaller for a spatially structured population than that seen for populations without structure. The difference between structured and unstructured populations increases as the adaptive mutation rate increases. Furthermore, the substitution rate decreases as the number of neighbors for local competition is reduced. We have also studied the impact of structure on the distribution of adaptive mutations that fix during adaptation.

Adaptation, Biological↗

Scaling, genetic drift, and clonal interference in the extinction pattern of asexual population.

We investigate the dynamics of loss of favorable mutations in an asexual haploid population. In the current work, we consider homogeneous as well as spatially structured population models. We focus our analysis on statistical measurements of the probability distribution of the maximum population size N(sb) achieved by those mutations that have not reached fixation. Our results show a crossover behavior which demonstrates the occurrence of two evolutionary regimes. In the first regime, which takes place for small N(sb) , the probability distribution is described by a power law with characteristic exponent theta(d) =1.8 +/- 0.01. This power law is not influenced by the rate of beneficial mutations. The second regime, which occurs for intermediate to large values of N(sb), has a characteristic exponent theta(c) which increases as the rate of beneficial mutations grows. These results establish where genetic drift and clonal interference become the main underlying mechanism in the extinction of advantageous mutations.

Demography↗

Adaptive walk on complex networks.

We investigate the properties of adaptive walks on an uncorrelated fitness landscape which is established in sequence spaces of complex structure. In particular, we perform numerical simulations of adaptive walks on random graphs and scale-free networks. For the former, we also derive some analytical approximations for the density of local optima of the fitness landscape and the mean length walk. We compare our results with those obtained for regular lattices. We obtain that the density of local optima decreases as 1/z, where z is the mean connectivity, for all networks we have investigated. In random graphs, the mean length walk L reaches the asymptotic value e - 1 for large z, which corresponds to the result for regular networks. Although we could not find an exact estimate, we derive an underestimated value for L. Unlike random graphs, scale-free networks show an upper asymptotic value of L.

Adaptation, Physiological↗

Gene phylogenies and protein-protein interactions: possible artifacts resulting from shared protein interaction partners.

The study of gene families critically depends on the correct reconstruction of gene genealogies, as for instance in the case of transcription factor genes like Hox genes and Dlx gene families. Proteins belonging to the same family are likely to share some of the same protein interaction partners and may thus face a similar selective environment. This common selective environment can induce co-evolutionary pressures and thus can give rise to correlated rates and patterns of evolution among members of a gene family. In this study, we simulate the evolution of a family of sequences which share a set of interaction partners. Depending on the amount of sequence dedicated to protein-protein interaction and the relative rate parameters of sequence evolution three outcomes are possible: if the fraction of the sequence dedicated to interaction with common co-factors is low and the time since divergence is small, the trees based on sequence information tend to be correct. If the time since gene duplication is long two possible outcomes are observed in our simulations. If the rate of evolution of the interaction partner is small compared to the rate of evolution of the focal protein family, the reconstructed trees tend towards star phylogenies. As the rate of evolution of the interaction partner approaches that of the focal protein family the reconstructed phylogenies tend to be incorrectly resolved. We conclude that the genealogies of gene families can be hard to estimate, in particular if the proteins interact with a conserved set of binding partners, as is likely the case for transcription factors.

Animals↗

Emergence of prime numbers as the result of evolutionary strategy.

We investigate by means of a simple theoretical model the emergence of prime numbers as life cycles, as those seen for some species of cicadas. The cicadas, more precisely the Magicicadas, spend most of their lives below the ground and then emerge and die in a short period of time. The Magicicadas display an uncommon behavior: their emergence is synchronized and these periods are usually prime numbers. In the current work, we develop a spatially extended model at which preys and predators coexist and can change their evolutionary dynamics through the occurrence of mutations. We verified that prime numbers as life cycles emerge as a result of the evolution of the population. Our results seem to be a first step in order to prove that the development of such strategy is selectively advantageous, especially for those organisms that are highly vulnerable to attacks of predators.

Animals↗

Fixation of beneficial mutations in the presence of epistatic interactions.

We investigate the effect of deleterious mutations on the process of fixation of new advantageous mutants in an asexual population. In particular we wish to study the dependence of the process on the strength of the deleterious mutations. We suppose the existence of epistatic interaction between the genes. We study the model by means of branching process theory and also by numerical simulations. Our results show the occurrence of two distinct regimes of behavior for the probability of fixation of these variants. The occurrence of either regime depends on the ratio between the selective advantage of the beneficial mutation sb and on the selective parameter for deleterious mutations sd. In the former, which takes place for sb/sd< or =1, the probability of fixation increases with the epistasis parameter , whereas for sb/sd>>1 the probability of fixation is a complex function of and the mutation rate U. Surprisingly, we find that for the multiplicative landscape (alpha=1) the probability of fixation Pfix is given by Pfix= pib)e-U/sd where pi(sb) is the probability of fixation for the two-allele model in the absence of mutations as calculated by Haldane (1927, Proc. Camb. Phil. Soc., 26, 220-230) and Kimura (1962, Genetics, 47, 713-719).

Alleles↗

Mutational effects on the clonal interference phenomenon.

We study the process of fixation of beneficial mutations in an asexual population by means of a theoretical model. Particularly, we wish to investigate how the supply of deleterious and beneficial mutations influences the dynamics of the adaptive process of an evolving population. It is well known that the deleterious mutations drastically affect the fate of beneficial mutations. In addition, an increasing supply of favorable mutations, to compensate the decay of the fitness due to the accumulation of deleterious mutations, produces the clonal interference phenomenon where advantageous mutations in distinct lineages compete to reach fixation. This competition imposes a limit to the speed of adaptation of the population. Intuitively, we would expect that the interplay of the two mechanisms would conspire to ensure fixation of only large-effect beneficial mutations. Our results, however, show that beneficial mutations of small effect have an increased probability of fixation when both beneficial and deleterious mutations rates are increased.

Adaptation, Biological↗

Small-world effects in the majority-vote model.

We investigate the majority-vote model on small-world networks by rewiring the two-dimensional square lattice. We observe that the introduction of long-range interactions does not remove the critical character of the model, that is, the system still exhibits a well-defined phase transition. However, we find that now the critical point is a monotonically increasing function of the rewiring probability. Moreover, we find that small-world effects change the class of universality of the model.

Journal Article↗

Error threshold transition in the random-energy model.

We perform a statistical analysis of the error threshold transition in quasispecies evolution on a random-energy fitness landscape. We obtain a precise description of the genealogical properties of the population through extensive numerical simulations. We find a clear phase transition and can distinguish two regimes of evolution: The first, for low mutation rates, is characterized by strong selection, and the second, for high mutation rates, is characterized by quasineutral evolution.

Journal Article↗

Genealogical process on a correlated fitness landscape.

We study with extensive numerical simulation the genealogical process of 2N haploid genetic sequences. The sequences are under selective pressure, and fitness values are assigned at random, but with a tunable degree of correlation to the fitness values of closely related sequences. The genealogies that we observe can be classified into three different categories, corresponding to different regimes of the mutation rate. At low mutation rates, the sequences remain localized around a small number of central sequences, which leads to trees with short pairwise distances and slow turnover of the most recent common ancestor of the population. At high mutation rates, we observe trees similar (but not identical) to those of neutral evolution. In this regime, the population drifts rapidly, and selection does not influence the distribution of fitness values in the population. The third regime, for intermediate mutation rates, is only found in strongly correlated landscapes. It resembles the one for high mutation rates in that the population drifts rapidly, but nevertheless selection still shapes the distribution of fitness values.

Animals↗