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Our research group is based at the Institute of Physics, UASLP (Instituto de Física, Universidad Autónoma de San Luis Potosí). We have a keen interest in evolutionary biology. Specifically, we focus on using modeling approaches to study the interplay between developmental and evolutionary processes, as we explain briefly below.


Developmental processes rely on interactions among multiple elements, be them genes, proteins, metabolites or cells, to produce phenotypic traits. Because the consequences of a gene's activity depend on its interactants, the same mutation may produce very different phenotypic alterations in two distinct genotypes. Therefore, distinct genotypes may differ in how easily mutations can change the phenotype along one specific direction. We may say that such genotypes differ in their developmental biases: random mutations upon their different developmental mechanisms produce different distributions of phenotypic effects. Genotypes may even differ in how easily random mutation creates new phenotypic variation. In that case, differences in developmental biases translate into differences in evolvability. 


That developmental bias exists and that this bias can create differences in evolvability has certainly been acknowledged for a long time. Moreover, work on simple population genetics models has already demonstrated that this bias can set the course for evolutionary trajectories under realistic, frequently encountered, conditions. However, there is a significant gap in evolutionary biology as we do not understand neither how developmental bias evolves nor what factors determine its direction and strength. We attempt to accomplish significant advances in filling this gap. How developmental mechanisms evolve is specially important since their modification leads the evolution of innovations across the entire tree of life. We expect to contribute to the understanding of how the organization, structure and dynamics of developmental mechanisms affect the direction and speed of the evolution of new traits. To that end, we perform computational simulations of developmental dynamics and evolutionary processes. 


Using computer simulations to study how the potential to evolve itself evolves is a largely unoccupied scientific niche. We are confident that its colonization will open novel and fruitful perspectives in evolutionary biology that will be required to complement the high-throughput and data-driven approaches that abound nowadays.


Feel free to contact us if you want to know more about us.



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Abstract A new phenotypic variant may appear first in organisms through plasticity, that is, as a response to an environmental signal or other non-genetic perturbation. If such trait is beneficial, selection may increase the frequency ofalleles that enable and facilitate its development. Thus, genes may take control of such traits, decreasing dependence on non-genetic disturbances, in a process called genetic assimilation. Despite an increasing amount of empirical studies supporting genetic assimilation, its significance is still controversial. Whether genetic assimilation is widespread depends, to a great extent, on how easily mutation and recombination reduce the trait's dependence on non-genetic perturbations. Previous research suggests that this is the case for mutations.Here we use simulations of gene regulatory network dynamics to address this issue with respect to recombination. We find that recombinant offspring of parents that produce a new phenotype through plasticity are more likely to produce the same phenotype without requiring any perturbation. They are also prone to preserve the ability to produce that phenotype after genetic and non-genetic perturbations. Our work also suggests that ancestral plasticity can play an important role for setting the course that evolution takes. In sum, our results indicate that the manner in which phenotypic variation maps unto genetic variation facilitates evolution through genetic assimilation in gene regulatory networks. Thus, we contend that the importance of this evolutionary mechanism should not be easily neglected.

Carlos Espinosa‐Soto  |  Ulises Hernández  |  Yuridia S. Posadas‐García

Instituto de Física, Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico. 2021.

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