David

David Liberles

group leader (CBU)

  • Ph.D from California Institute of Technology (USA), 1997
  • Postdoctoral Researcher, University of Florida (USA), 1997-1999
  • Assistant Professor, Stockholm University (Sweden), 2000-2003
  • affiliated with CBU since 2002

Group members:

  • Matthew Betts (postdoc)
  • Christian Roth (postdoc)
  • Marie Skovgaard (postdoc)
  • Himanshu Ardawatia (Ph.D. student)
  • Tim Hughes (Ph.D. student)
  • Shruti Rastogi (Ph.D. student)
  • Åsa Tellgren (Ph.D. student)

Liberles group

Evolutionary and phylogenetic approaches to comparative genomics

As species diverge, specific molecular changes drive phenotypic changes and ultimately adaptation.Understanding the mechanism of the evolution of new functionality in genomes and how this correlates with the phenotypic divergence of species is the central theme of my research group.

Important genomic events include horizontal transfer, gene duplication, sequence divergence, gene expression divergence, mRNA splicing pattern divergence, and a host of other mechanisms. Detecting and collating these different events in a phylogenetic perspective is an ongoing process. This involves methods development, both at the DNA and protein sequence levels using parsimony and maximum likelihood methodologies, at protein structural levels, and at systems network levels.

One example of the application of these methods is the development of The Adaptive Evolution Database (TAED). This database includes information on protein coding sequences that appear to be undergoing adaptive evolution or changes of function along specific branches of the tree of life and has been established in a phylogenetic context. This database is a resource for asking the question, what are the genes or molecular events that diverged as different species separated from a common ancestor. It is also useful in combination with the Protein Data Bank (PDB) for analyzing the effect of protein structure and folding on the fixation of mutations during evolution. At the same time, we are also modeling the evolution of proteins to see how well our models explain observed genomic data.To do this, we use genomics to build a bridge between the physical chemistry of protein structure and molecular evolution.

Specific examples of proteins are also of interest. These are studied computationally by examining mutational patterns in a phylogenetic perspective and comparing that with three dimensional protein structures and published mutagenesis studies to develop models for the roles of specific mutations in functional adaptation. Other proteins of interest are studied further through experimental analysis coupled to phylogenetic analysis.

This research paradigm fits together at the interface of several fields, enabling us to address basic questions in biology and evolution. An understanding of the role of specific mutations underlying phenotypic effects allows us to better understand the evolution of species. Future projects and goals:

Future projects and goals:

  • Continuously improve both TAED and the methods used to generate it
  • Study specific case studies of proteins under positive selective pressure in more detail using both computational and experimental methods
  • Develop a better understanding of the roles of gene duplication, biological network structure, and other mechanistic constraints on the process of genome evolution
  • Continue the development of a synthesis combining the physical chemistry of protein structure with phylogenetics and molecular evolution

Selected publications:

  • Braun, F.N. and Liberles D.A. 2003. Retention of enzyme gene duplicates by subfunctionalization. International Journal of Biological Macromolecules, 33:19-22.
  • Davids, W., Gamieldien, J., Liberles, D.A., and Hide, W. 2002. Positive selection scanning reveals decoupling of enzymatic activities of carbamoyl phosphate synthetase in H. pylori. Journal of Molecular Evolution, 54:458-464.
  • Siltberg, J. and Liberles, D.A. 2002. A simple covarion-based approach to analyse nucleotide substitution rates. Journal of Evolutionary Biology, 15:588-594.
  • Liberles, D.A. 2001. Evaluation of Methods for Determination of a Reconstructed History of Gene Sequence Evolution. Molecular Biology and Evolution, 18:2040-2047.
  • Liberles, D.A., Schreiber, D.R., Govindarajan, S., Chamberlin, S.G., and Benner, S.A. 2001. The Adaptive Evolution Database (TAED). Genome Biology, 2: research0028.1-0028.6.