Analysis of gene functional coupling and the meaning of gene positional information in eukaryotic genomes

The location of a gene within a genome affects its functionality via the cis-effects of regulatory elements, neighboring genes and regional topology related to chromosome packaging and nuclear positioning. There is a certain degree of a shared synteny - phylogenetic conservation of gene order- between genomes, the conservation of which is in part associated with functional coupling of genes. In prokaryotes shared synteny usually reflects operon structure; co-regulated and co-expressed strings of genes jointly participating in a biological function or process. Generally operons do not occur in eukaryotes, however synteny may reflect the functional synergism, even where genes are not co-expressed. Co-localization dictates a high degree of gene linkage during recombination and a coordinated gain or loss of genes. We hypothesise that conserved gene neighborhoods represent regulatory modules that contribute to cell differentiation and adaptation. Such structural domains may be especially significant during malignant cell transformation.

This project aims to evaluate the functional significance of gene positional information in eukaryotic genomes. Using a number of bioinformatics methods we will retrieve sets of genes from syntenic regions across metazoan genomes, grouped at different phylogenetic levels. We will project these gene sets on to regulatory and protein-protein interaction networks and analyze connectivity and topology within the defined network domains. We will also compare these genomic loci to known haplotype patterns and to regions of gain/loss typical for different human malignancies. We expect to demonstrate that highly syntenic regions bare functionally distinct and potentially important regulatory gene modules and have relatively low levels of recombination or chromosomal aberration (deletion, translocation). This project will be largely supported by an Algorithm development group (Computer Sciences Dept) and is expected to lead to novel methods for the prediction of functional links between genes with network visualization and analysis of established syntenic groups.


Training:
This project provides a thorough training in bioinformatics technique, including gene discovery and comparative genomics, collation and analysis of large-scale datasets, patterns-searching and statistical data processing techniques, visualisation techniques and creation of network descriptions, interactomes and reactomes with introduction to a software development. If appropriate student training in writing code will be given. Dr Olga Vasieva who is Senior Bioinformatician, together with Prof Gasieniec who is a head of the Computer Sciences department and an expert in algorithm development, will supervise this project. The student will work within a large and active bioinformatics group incorporated into the MRC/NERC-supported Centre for Genome Research, alongside a large number of postgrads and postdocs and Prof Gasieniec’s group of software developers. He/she will benefit from frequent journal clubs and there are opportunities to join local and national courses in bioinformatics technique, and to join elements of the bioinformatics Masters program. The project is integrated into the ERASYSBIO+ project “GRAPPLE” which involves developing new methods for data interrogation and network analysis with partners in Cambridge and Barcelona. This project would suit a student with a degree in Computer Science, Maths, Physics or Theoretical Physics, or Biologists with an interest and competence in informatics and computer studies.