SYSTEMS BIOLOGY AND GENOMICS

Project details

The candidate would have the opportunity to be involved in establishment of this technology to identify enhancer-promoter interactions with a major focus on interactions involving regions associated with human genetic disease (e.g. autoimmunity, neurodevelopmental disorders, cancer predisposition). The candidate would be working closely with a molecular biology postdoc who is establishing the technology and a bioinformatics postdoc who is establishing the computational pipeline. The candidate would also be involved in CRISPR editing of candidate enhancer regions to confirm they affect expression of the predicted target gene.

Contact
Professor Alistair Forrest – [email protected]

There is some flexibility in the project in terms of biological question. Potential research applications of the technology include:

• Examining cellular heterogeneity in cancer samples
• Examining cell-to-cell communication in cancer samples (working with bioinformaticians in the team)
• Generating reference expression profiles of rare cell types. These have the potential to identify new genes and deepen our understanding of genetic disorders.
• Identification of new cell types based on their expression profiles (a fundamental question in human biology is; How many different cell types do we have in our bodies?)

The candidate would work with a molecular biology postdoctoral researcher on establishing single cell profiling methods and apply it to tumour samples or normal tissue from surgery waste. They would also work with bioinformaticians in the group and would have the opportunity to be trained in analysis of single cell RNA-seq data.

Contact
Professor Alistair Forrest – [email protected]

Defects in cell-type-specific genes can lead to cell-type-specific phenotypes. For example mutations in POU transcription factors that are expressed specifically in the inner ear hair cells can result in deafness (see Forest et al. 2014 Nature). Despite this there are also genes such as MECP2 which are ubiquitously expressed throughout all cell types and yet mutations result in neurological defects rather than a whole organism disease or embryonic lethality.

The project would predominantly be a bioinformatics one with mining of large expression and genotype/phenotype datasets from human and mouse to systematically examine the relationships between cell-type-specific expression and tissue-specific disorders.

Additionally we have recently published an active enhancer atlas (Andersson et al. 2014 Nature). Enhancers show highly specific activation in different cell types (more specific than ‘genes’). By integration of the enhancer activity data with Genome wide association studies (GWAS) we are beginning to dissect out regulatory SNPs in cell-type-specific enhancers.

The candidate would work closely with a bioinformatics postdoc and would learn (and need to become proficient in dry techniques)

1. Data curation and databasing
2. Mining expression datasets (microarrays, RNA-seq or CAGE)
3. Mining GWAS and eQTL datasets
4. Data integration and statistical testing
5. Sample ontology enrichment analysis
6. Variant calling in whole exome and whole genome sequence datasets

Suitable candidates from both biostatistics/bioinformatics, biological/medical/veterinary sciences and computer sciences will be considered.

Contact
Professor Alistair Forrest – [email protected]

We aim to set up an instance of ZENBU at the Perkin’s and would like to work collaboratively with the developer Jessica Severin in Yokohama to further develop the tool

• additional data visualizations
• region based statistics
• peer-to-peer (enterprise ZENBU)
• ZENBU cloud
• Data integration
• Interoperability with tools such as Galaxy

This would best suit computer science and information technology graduates. For this project there is potential for short visits to RIKEN Yokohama Japan to work with the developer/collaborator Jessica Severin.

Contact
Professor Alistair Forrest – [email protected]

General areas include –
Basic research:

• Transcript discovery
• Non-coding RNAs
• Primary cell biology
• Mammalian transcriptional networks and evolution of multicellularity
• Building transcriptional regulatory network models (bioinformatics and NGS data)

Applied:

• Comparing broken networks in cancer
• Cancer Biomarkers
• Tissue specificity of drug targets
• Disease gene prioritization

Contact
Professor Alistair Forrest – [email protected]