Systems developmental biology, mutation and the unsolved problem of evolution
Van Leeuwenhoek Lecture on BioScience.
Jonathan Bard is a recently retired biologist with interests in developmental biology (both experimental and theoretical), bioinformatics (particularly the production and use of ontologies of development) and the history of developmental and evolutionary biology.
In 1965 he did his M.A. in Physics (Cambridge), in 1968 his PhD in Biophysics (Manchester). In 1969 he moved to the Human Genetics Department in Edinburgh. In 1973 he was a research fellow at Harvard, in 1980 a visiting professor of Applied Mathematics in Israel (Weizmann Institute).
In 2002 he obtained a personal chair in Development and Bioinformatics. From 2007-2009 he was a honorary member of the Computational Biology Group (Oxford University) and from 2009 until now he is a visiting member of the Department of Physiology, Abnatomy & Genetics at Oxford University.
In the 200 years since Lamarck and the 150 years since Darwin, we have learnt a great deal about the historyof life and the mechanisms of evolutionary change, with recent progress almost entirely deriving from the efforts of computational biologists. There are however still gaps to fill in our understanding of evolution, and an apparently simple example is how a mutation in a DNA sequence leads to an anatomical variant that my have a selective advantage. We have known since at least the time of Thomas Huxley that such variants usually reflect abnormal development, but it is hard to think of an environment in which any of the host of developmental mutants that we study today will flourish. Light on this and related problems is shone by systems developmental biology, a subject that focuses on the roles of protein networks, complexity and hierarchies in understanding how embryos develop normally and how mutation affects that normal developmental trajectory. The implications of this perspective are not however as immediately helpful for computational evolutionary biologists as one might wish.
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