Linking developmental, computational and evolutionary biology of mammalian teeth

Consortium leader: JUKKA JERNVALL,
Institute of Biotechnology, University of Helsinki

Other project leaders of the consortium: 
Irma Thesleff, professor, Institute of Biotechnology, University of Helsinki
Mikael Fortelius, Department of Geology, University of Helsinki

Doctoral students of the consortium: 
Aapo Kangas,
Jussi Eronen,
Johanna Pispa,
Johanna Laurikkala
Tuija Mustonen
Mark Tummer

Other researchers of the consortium: 
Alistair Evans
Isaac Salazar-Ciudad
Kathryn Kavanagh

Key words:  teeth, gene networks, development, evolution, computational modeling

Project desciption and main results:  
By bringing together our research programs, our objective is to acquire a "total system view" in order to identify the organizational principles of gene networks responsible for developmental control of complex phenotypes, specifically mammalian tooth shape.  A major challenge for research attempting to link the genotype to the phenotype is the requirement of sophisticated computational biology methods that can integrate the simulation of both molecular signaling and tissue growth. We will use computational biology to further develop mathematical gene network models simulating tooth development. First we will search for the simplest signaling network topology that is able to produce wild type and mutant mouse teeth. Second, our total system view of mammalian teeth allows us to perform the crucial test whether models built to explore mutations in the laboratory have explanatory power over the true diversity found in nature. The final goal is to link all the organizational levels by obtaining the simplest signaling network that accounts for the evolutionary, developmental, and molecular aspects of tooth development. This will be done by linking in silico experiments with in vitro experiments. The mammalian dentition is probably the only known organ system that offers this rich array of interrelated data on development, detailed evolutionary history, and robust functional information necessary for the total system view that we strive to attain. To our knowledge this would be the first time a signaling network topology linking cellular signaling, morphology, and evolution has been constructed.

Publications: