Theoretical Evolution group
Biological networks contain multiple components that interact with each other in many different ways. Often the functionality of these networks depends on the ability of molecules to interact specifically with certain targets, while simultaneously avoiding interaction with many other potential targets. Given the low interaction energies and large number of molecular species, this raises fundamental theoretical questions concerning the evolution of such networks.
We are a theoretical-computational group. We use a variety of physical and mathematical approaches, in particular population genetics models, stochastic simulations and genomic data analysis.
Current projects in the lab are:
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Evolution of “self-incompatibility” proteins: “Self-incompatibility” is a general name for molecular mechanisms, plants have developed to avoid self-fertilization, which might lead to the spread of deleterious mutations. As a medium-sized network with strong selection on the interactions, self-incompatibility is an excellent model system for network evolution. Self-incompatibility forms barriers to reproduction of many agricultural crops. A better understanding of this mechanism is an essential step in designing efficient breeding strategies. To read more…
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Transitions between mating modes in plants: plants employ diverse mating strategies, where in some cases different populations of the same species vary in their mode of mating, yet what drives transitions between mating modes remain elusive. For example, the wild tomato Solanum habrochaites is equipped with a self-incompatibility mechanism, but only some of its wild populations are self-incompatible (employing outcrossing), whereas others are self-compatible (capable of self-fertilization) or mixed (employing both self-fertilization and outcrossing). In a joint project with Menachem Moshelion's lab, we are growing both self-compatible and self-incompatible S. habrochaites plants and will study the relation between stress and the plant mating mode.
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ABA signal processing in plants: abscisic acid (ABA) is a plant hormone that triggers drought responses in plants. ABA binds dedicated receptors that mediate various downstream responses. These receptors have evolved starting from ABA-insensitive ancestral receptors in algae to various forms of ABA-sensitive receptors in mosses and angiosperms. In this project we use mathematical modeling to study the functional role of the different receptor forms in ABA signal processing. This project is in collaboration with Assaf Mosquna's lab.
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Flowering dependence on temperature in olive trees (collaboration with the lab of Alon Samach): plants flower in response to environmental cues such as day length and temperature. Many fruit trees flower in spring and the exact timing and extent of flowering depend on temperatures during winter. In collaboration with Alon Samach's lab we have analyzed olive tree flowering data and detailed temperature data from the relevant sites and years. We have constructed a phenomenological model predicting the tree flowering level depending on the past winter temperatures. To read more...
We are also interested in general evolutionary theory questions. For more details on current and previous projects check out our research page.
The lab is part of the CAFE initiative - Computational Agriculture Food and Environment.