Our view on organismal evolution is intimately connected to our understanding of how genomes and the encoded information change over time, and how this translates to the phenotypic and functional characteristics of contemporary species. The sequencing of entire genomes and transcriptomes from species covering all major groups in the tree of life has lifted the data basis for evolutionary research with a functional perspective to an unprecedented level. In its combination, this data facilitates access to the full repertoire of information stored in a species' genome and allows unraveling individual cellular programs translating genetic information into a diverse set of functions. However, the effort connected to the experimental functional characterization of even considerably few proteins in the lab is still enormous. It is for this reason that exhaustive functional studies are limited to few and well established model organisms, many of which are of economical or medical relevance. More often only individual pathways are studied in niche model organisms featuring a particular trait of interest. However, for the vast majority of species only a draft genome assembly or transcript data is available without further experimental support. In these instances the in silico prediction of genes together with a subsequent tentative transfer of functional annotation from corresponding sequences in experimentally characterized model organisms provides the only source of functional information. Integrating all available information into a comprehensive picture of organismal and functional evolution is the common denominator of the individual projects in our group.
More specifically, we concentrate on the following main topics: Expand all...
1) Reconstructing the evolutionary histories of species and of their genes
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2) Functional annotation transfer between homologous proteins
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3) From phylogenetic profiles to the evolution of gene interaction networks
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4) Evolution of species-specific phenotypes
We integrate phylogenomics tree reconstruction, feature architecture-aware phylogenetic profiling and functional inference to study how human pathogens emerge from their largely a-pathogenic ancestors. This sheds light on the molecular mechanisms of host-pathogen interaction and forms the basis of novel routes of treatment.
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5) Tools for for managing, exploring and analysing genome-scale data in a functional and evolutionary context
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