Defining the cistrome and quantitative transcriptome of virus-transformed cells using massively parallel sequencing

As in humans, many animals including chickens, develop cancer. However, unlike in humans, most of the cancers in chickens are caused by viruses. Marek's disease (MD) is a common disease of chickens involving paralysis and commonly death from the growth of highly malignant T lymphomas (cancers of white blood cells). MD is caused by a transmissible agent, Marek's disease virus (MDV). MDV is very contagious and is a major threat to the poultry industry worldwide. The estimated total loss from this disease worldwide is up to £ 2 billion. Presently, it is controlled by vaccination, and nearly 22 billion vaccine doses a year are used in an attempt to control the disease. Despite widespread vaccination, the threat from this disease is on the increase, and more fundamental studies to understand the mechanisms by which this virus cause cancer is needed to develop more effective control programmes. Another cancer inducing virus of chickens less common in the UK called Reticuloendotheliosis virus (REV) is a very good model for cancer. The advantage of using this virus for studying the mechanisms of cancer is that the experiments to induce cancer can be done on chicken cells collected from birds. We have used this model and examined the molecular changes to the cells while it is transformed into cancer cells. We have identified very important changes in the expression of genes and small 22-nucleotide microRNAs molecules between normal cancer cells, suggesting that these changes contribute to cancer. In this new grant proposal, to be carried out jointly between the Institute for Animal Health (Compton) and ARK-Genomics (Roslin Institute), we want to extend these studies to obtain detailed information on the changes in the expression of genes using the new RNA-Seq technology that will provide a much detailed comprehensive picture on the expression of genes during the transformation process. Similarly, we will also examine the sequences in the genomes where viral oncoproteins can directly bind to the DNA to change the gene expression to cause cancer. We aim to use this excellent model system and Marek's disease cancer model to obtain detailed gene expression data to understand and predict the molecular pathways to cancer. The study is very important to understand the mechanisms by which these viruses induce cancer, some of which are valuable in understanding cancer in other species including humans. Finally, the findings from the project will be very valuable in developing new approaches for the control of cancers caused by oncogenic viruses.

The objectives of this work are to define the interactions between virus-encoded transcription factors, the host genomic DNA, microRNAs and mRNA expression during transformation by two avian oncogenic viruses, Reticuloendotheliosis virus (REV) and Marek's disease virus (MDV). Our preliminary data show that both MDV and REV encode transcription factors that bind to host DNA and upregulate important mRNA and microRNA genes, and that the miR-155/miR-M4 pathway is incredibly important to both viruses. We will dissect the exact relationship between virus-encoded transcription factors, microRNAs and gene expression using the latest next-generation sequencing technologies. Specifically, in REV we will simultaneously measure the temporal expression of mRNAs and microRNAs using mRNA-Seq and miRNA-Seq. We will combine this data with ChIP-Seq data to define the binding sites of vRel (the oncogenic transcription factor of REV) within the host genome, both at infection and at full transformation. These data will be integrated within a statistical and bioinformatics framework to provide an incredibly rich dataset on how proteins, microRNAs and mRNAs interact in this system. We will repeat the above with Marek's disease virus (MDV); however, we can only assay MDV at uninfected and tumour cells due to a lack of models of in vitro transformation. Finally, we will define the differential targetome of miR-155 and miR-M4 using an RCAS vector system, providing us with fine-grained data on the effects of miR-155 and miR-M4 on gene expression, their similarities and differences. These data combined will allow us to build a model of virus-induced transformation, and to compare and contrast the pathways used by REV and MDV.

The beneficiaries of this research will include academic scientists, the poultry industry sector including the poultry breeding companies (e.g. Aviagen) and vaccine production companies (Pfizer Animal Health), farmers and the general public. Global demand for food is rising, both as a result of population growth and due to dietary changes in developing countries. A UN FAO report on this issue forecasts that food production will need to increase by over 40% by 2030 and by over 70% by 2050. With close to 55 billion chickens reared annually, poultry meat and eggs dominate animal protein products for human consumption world-wide. In the UK, the poultry sector is thought to contribute around £3.4 billion to the economy. Compared to the other livestock sectors, the modern poultry production methods have the most efficient feed-to-meat conversion ratios with lowest global warming potential. Because of these attributes, the poultry production sector is likely to expand significantly to meet the global demand for food in the coming years. Marek's disease (MD) is also one of the major diseases of poultry which causes serious economic losses and the global estimate of losses from Marek's disease is approximately $2,000 million annually. Detailed understanding of the molecular basis of tumours induced by these viruses, as the current proposal aims to achieve, will benefit development of new strategies for control. Rapid-onset lymphomas induced by MD and REV are also good models for studying virus-induced lymphomas in other species including humans. For example, the pathways of B-cell transformation occur through the CtBP interaction, both in MDV and Epstein-Barr virus (EBV)-induced tumours. Similarly, both MDV and the human pathogen KSHV encode functional miR-155 homologues, and since there are no human models of KSHV-induced tumours, MDV system will be valuable.