Background: The most diverse marine ecosystems, coral reefs, depend upon a functional symbiosis between cnidarian hosts and unicellular dinoflagellate algae. The molecular mechanisms underlying the establishment, maintenance, and breakdown of the symbiotic partnership are, however, not well understood. Efforts to dissect these questions have been slow, as corals are notoriously difficult to work with. In order to expedite this field of research, we generated and analyzed a collection of expressed sequence tags (ESTs) from the sea anemone Aiptasia pallida and its dinoflagellate symbiont (Symbiodinium sp.), a system that is gaining popularity as a model to study cellular, molecular, and genomic questions related to cnidarian-dinoflagellate symbioses.

The Genomics Education Partnership offers an inclusive model for undergraduate research experiences incorporated into the academic year science curriculum, with students pooling their work to contribute to international data bases.

No abstract

No abstract

Although recent work has demonstrated that modularity can increase evolvability in non-embodied systems, it remains to be seen how the morphologies of embodied agents influences the ability of an evolutionary algorithm to find useful and modular controllers for them. We hypothesize that a modular control system may enable different parts of a robot's body to sense and react to stimuli independently, enabling it to correctly recognize a seemingly novel environment as, in fact, a composition of familiar percepts and thus respond appropriately without need of further evolution. Here we provide evidence that supports this hypothesis: We found that such robots can indeed be evolved if (1) the robot's morphology is evolved along with its controller, (2) the fitness function selects for the desired behavior and (3) also selects for conservative and robust behavior. In addition, we show that if constraints (1) and (3) are relaxed, or structural modularity is selected for directly, the robots have too little or too much modularity and lower evolvability. Thus, we demonstrate a previously unknown relationship between modularity and embodied cognition: evolving morphology and control such that robots exhibit conservative behavior indirectly selects for appropriate modularity and, thus, increased evolvability.