Modeling gene networks and biomechanics in development and evolution
1.Basic job and project description:
4 year position to do a PhD in the Autonomous University of Barcelona (UAB).
Topic: Mathematical modeling of evolution in complex adaptive landscapes. This implies modeling of gene network dynamics, development and population genetics.
2. Introduction to the topic of research
How is it possible that complex structures like the human brain or the molecular machinery within cells have evolved? Current evolutionary theory provides the basic principles to understand such evolution but its theoretical core, population genetics, does not incorporate models of how genes interact or on how they interact with cell and tissue properties. This is a limitation since, clearly, complex phenotypes are build through complex networks of gene and cell interactions. Besides, although mutation is random, the structure and dynamics of these networks determine how phenotypes change by mutations. In other words, the phenotypic effect of mutations is not random but depends on these networks. This implies that the structure and dynamics of these networks at a given moment affects the likely directions of phenotypic variation and, thus, evolution.
-The research will be in any of these three related lines:
2.1. Models to predict evolution.
The networks determining possible phenotypic variation are complex. However, by understanding some of its dynamics, we can understand which phenotypic variation they can produce. For example, by computational models of gene networks during embryonic development we have obtained an understanding of the directions of variation most likely to occur in specific phenotypes (mammalian teeth, see Salazar-Ciudad and Jernvall, 2010). In a way these models describe the space of phenotypes within which a population would evolve over time. If information about natural selection is available, then these models can be used to predict how phenotypes evolve. Our research consist in building such prediction approach in general and applying it to specific cases of evolution.
2.2 Evolutionary theory under complex genotype-phenotype maps.
Most of evolutionary theory was developed at a time where not much was know about gene networks, development or the genotype-phenotype map. As a result, its main mathematical models and concepts are based on the assumption that this latter map is simple or by ignoring it all together. The aim in here is to build general models of development that realistically consider that these maps can be complex, the underlying gene networks and development. These models will then be used to explore how, or whether, many of the ideas and conclusion of
current evolutionary theory change. These models will also be used to address questions that current evolutionary theory cannot explain, does not aim to explain or that,
simply, could be explained better by considering gene networks and development, such as: the evolution of development and gene networks, the direction of evolution in the short and long term, how evolution in complex adaptive landscapes is possible, how complex phenotypes can evolve, etc.
2.3 Any other question of the applicants interest that is related to the previous questions.
3. Requirements:
- Candidates should have a University Degree and a Master’s Degree in biology or related
-Scientific programming skills or a willingness to acquire them.
-A strong interest and motivation on science and evolution. A capacity for creative and critical thinking.