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) Deep phylogenies and phylogenetic profiling
The transfer of functional annotations between biological sequences is a multi-layered procedure of which the most basic step is typically the identification of orthologs to functionally annotated proteins from model organisms in non-model organisms. Unfortunately, evolutionary relationships between proteins alone are only a poor proxy for functional equivalence. To ameliorate this problem, we aim at including additional evidences to achieve a more reliable annotation transfer by that minimizing the requirement of human curation. We are currently integrating an automated scoring of functional domain architecture similarities with the search for homologs. Moreover, we take the phylogenetic profiles of the respective proteins together with those of proteins interacting in the same functional pathway into account.
3) Phylostratigraphy and evolution of gene interaction networks.
4) Source of genetic and functional innovation
5) Development of software and workflows for biological sequence analysis
Department for Applied Bioinformatics
Institute for Cell Biology and Neuroscience
Prof. Dr. Ingo Ebersberger
Max-von-Laue Str. 13
Phone +49 69 798 - 42112
Biologicum; Room 3.205
Phone +49 69 798-42110