This project is no longer listed in the FindAPhD database
and may not be available.
In recent years a range of different fish species have become promising vertebrate models in biology. supported by the sequencing and assembly and annotation of several fish genomes. Since Y2000 scientists at the University of Liverpool have pioneered the creation of genomic resources for various Euteleostean species (trout, carp, flounder, zebrafish, eel) including customised microarrays which generated unique data sets relating to abiotic stress responses, ecotoxicity, hydrostatic pressure, and disease tolerance. These datasets contains dimensions that have not been fully explored. Thus, gene co-expression between different experimental conditions indicates a functional coupling and functional links in functional connectivity matrices. However, there is currently no generate a taxon-wide integration of gene lists along with functional attributes, that might provide insights into genome evolution, and physiological adaptation. Also, there is no reliable fish-specific ‘reactome’ available to the fish community.
This bioinformatics project will focus first on a thorough cross-species gene mapping of data from array repositories, and establishing homologies and paralogies across the wide taxonomic range of fishes. Second, it will seek to identify patterns of co-expression that are conserved across species. Using new methods of organism-specific functional networks and of network alignment we will reconstruct a weighted fish-specific ‘reactome’ using the existing resources (BioGrid, INtAct, BioMart, FunCoup, InParanoid etc). We will also seek to identify gene neighbourhoods in Danio rerio and Tetrodion genomes and use the conserved links as an additional indication of functional coupling between pairs of genes. This and expression meta-analysis data will help us to refine the reconstructed network and to weight probabilities of predicted interactions. The project should lead to the development of the valuable resource for the systemic analysis of fish ‘Omics’ datasets.
Training:
This project provides a thorough training in bioinformatics technique, including gene discovery and annotation, collation and analysis of large-scale datasets, patterns-searching and statistical data processing techniques, visualisation techniques and creation of network descriptions, interactomes and reactomes. For suitable student training in writing code will be given. A major focus is on identifying questions that can be addressed through grand data collations. Supervision by Dr Olga Vasieva who is Senior Bioinformatician, together with Prof Cossins, who has led fish genomics work for >10 years. The student will work within a vigorous bioinformatics group incorporated into the MRC/NERC-supported Centre for Genome Research, alongside a large number of postgrads and postdocs. S/he 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 students from any biological discipline able to provide evidence of interest and competence in informatics and computer studies.
References:
Gracey, A.Y., Fraser, E.J., Li, W., Fang, Y., Brass, A., Rogers, J. And A.R. Cossins (2004) Coping with cold: an integrative, multi-tissue analysis of transcript expression profiles in a poikilothermic vertebrate. Proc. Nat. Acad. Sci. USA 101: 16970-16975.
Li, W., L, Hughes, M.A., Rogers, J., et al.. (2009) ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles. BMC Genomics 560; 10: 560
Mirsa, N., Vasieva, O. et al. (2011) Exploring the Genetic Basis of Pharmacoresistance in Epilepsy: An Integrative Analysis of Large-Scale Gene Expression Profiling Studies on Brain Tissue from Epilepsy Surgery. Human Genetics Vol pages
Research Assessment Exercise (RAE) 2008 Results