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Seminar series on Mathematical Evolutionary Biology - Michael Lynch: Mutation, Drift and the Origin of Subcellular features

  • Date: Jul 2, 2018
  • Time: 15:00 - 16:00
  • Speaker: Michael Lynch from the Biodesign Institute at Arizona State University, USA
  • For more information on Michael Lynch, please check: https://biodesign.asu.edu/michael-lynch
  • Location: MPI Plön
  • Room: Lecture hall
  • Host: Linda Odenthal-Hesse & Chaitanya S. Gokhale

Abstract:

Although natural selection may be the most powerful force in the biological world, it is not all powerful. As a consequence, many aspects of evolution at the genomic level can only be explained by the inability of natural selection to operate. This general principle also appears to extend to numerous higher-level features of cells: the evolution of the ~1000-fold range in mutation rates that exists among species; greatly elevated rates of transcription error; the divergence of the multimeric states of proteins; the phylogenetic drift of gene-regulatory vocabulary; the stream-lined genomes of microbes vs. bloated genomes of multicellular eukaryotes; and the scaling of growth rate with organismal size.
An attempt will be made to describe how these diverse observations can be explained at the theoretical level, in some cases using methods derived from statistical mechanics. A fundamental principle is that although natural selection relentlessly pushes traits to the highest possible level of refinement, the limits to perfection are dictated by the power of random genetic drift rather than by intrinsic molecular limitations / cellular constraints. The drift-barrier hypothesis broadly implies that the population-genetic environment imposes a fundamental constraint on the paths that are open vs. closed for evolutionary exploration in different phylogenetic lineages, hence defining the patterns of adaptation seen at the molecular and cellular level. Additional examples may be drawn from recent observations on the bioenergetic costs of maintaining and
expressing genes.

 
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