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Rodrigo, G.

Publications and source records attributed to Rodrigo, G..

2 recordsLinked to original sources

Viral fitness predicts the magnitude and direction of perturbations in the infected host transcriptome

Determining the fitness of viral genotypes has become a standard practice in virology as it is essential to evaluate their evolutionary potential. Darwinian fitness, defined as the advantage of a given genotype with respect to a reference one, is a mesoscopic property that captures into a single figure differences in performance at every stage of viral infection. But to which extent viral fitness results from particular molecular interactions with host factors and regulatory networks during infection? Can we identify host genes, and then functional classes, whose expression depends on viral fitness? Here, we compared the transcriptomes of tobacco plants infected with seven genotypes of tobacco etch potyvirus (TEV) that differ in fitness. We found that the larger the fitness differences among genotypes, the more dissimilar the transcriptomic profiles are. Consistently, two different mutations, one in the viral RNA polymerase and another in the viral suppressor of RNA silencing, that led to close fitness values, also resulted in significantly similar gene expression profiles. Moreover, we identified host genes whose expression showed a significant correlation, positive or negative, with TEV fitness. Over-expression of genes with positive correlation activates hormone-and RNA silencing-mediated pathways of plant defense. By contrast, under-expression of genes negatively correlated reduces metabolism, growth, and development. Overall, these results reveal the high information content of viral fitness, and suggest its potential use to predict differences in genomic profiles of infected hosts.

evolutionary biology

Intrinsic adaptive value and early fate of gene duplication revealed by a bottom-up approach

Gene duplication is a major source of functional innovations and genome complexity, albeit this evolutionary process requires the preservation of duplicates in the genomes for long time. However, the population genetic mechanisms governing this preservation, especially in the critical very initial phase, have remained largely unknown. Here, we demonstrate that gene duplication confers per se a weak selective advantage in scenarios of fitness trade-offs. Through a precise quantitative description of a model system, we show that a second gene copy enhances the information transfer from the environmental signal to the phenotypic response by reducing gene expression inaccuracies derived from pervasive molecular noise and suboptimal gene regulation. We then reveal that such a phenotypic accuracy yields a selective advantage in the order of 0.1% on average, which would allow the positive selection of gene duplication in populations with moderate or large sizes. This advantage is greater at higher noise levels and intermediate concentrations of the environmental molecule, when fitness trade-offs become more evident. Moreover, we show that the genome rearrangement rates greatly condition the eventual fixation of duplicated genes, either by natural selection or by random genetic drift. Overall, our theoretical results highlight an original adaptive value for cells carrying new-born duplicates, broadly analyze the selective conditions that determine their early fates in different organisms, and reconcile population genetics with evolution by gene duplication.\n\nSIGNIFICANCEGene duplication is considered a major driver for the evolution of biological complexity. However, it is still enigmatic to what extent natural selection and genetic drift have governed this evolutionary process. This work uncovers a selective advantage for genotypes carrying duplicates, called phenotypic accuracy, widely characterized thanks to a multi-scale mathematical model coupling gene regulation with population genetics. Importantly, the integrative results presented here provide a detailed mechanistic description for the fixation of duplicates, which allows making predictions about the genome architectures, and which is relevant to understand the origins of complexity.

evolutionary biology