Genomic scaling of transcriptional noise

Many diseases are caused by the faulty function of various different cell types. In order to understand what can go wrong and how it can be fixed, it is important to know as well as possible how a cell works.
The fundamental problem is to understand how the 20- to 30,000 genes in a mammalian cell regulate each other. Depending on how 'active' a gene is, RNA is produced at a certain rate and will eventually be translated into proteins. Protein products of some genes can bind to DNA and regulate activity of other genes (sometimes their own), thus forming an extremely complex gene regulatory network. The interactions within this network are constantly fluctuating strongly. It is thus particularly puzzling how a cell manages to keep control in spite of this background noise.
This high complexity posed an insurmountable obstacle until very recently. New developments in experimental technologies are currently revolutionizing research in biology and provide a means to address this problem. These novel technologies are largely based on remarkable advances in sequencing DNA and allow probing in parallel many factors important for gene regulation. A tremendous amount of data is produced by such experiments. This requires extensive computational analyses but makes it possible for the first time to study such a complicated regulatory network and its background noise.
A better understanding of this network will provide fascinating new insights into the general molecular mechanisms that control cell function and will open up clinical perspectives for the cases where this function is defective.

Expression levels of the same mRNA or protein vary strongly among the cells of an otherwise identical population. Such biological noise has great functional implications and is largely due to transcriptional bursting. This process refers to the episodic production of mRNAs in short, intense bursts, interspersed by periods of transcriptional inactivity. The parameters and properties of bursting, such as the frequency and size of bursts can be inferred from single cell mRNA distributions. The values of these parameters are highly informative of transcriptional mechanisms.
It is the aim of this project to study transcriptional noise from a genome-wide, multi-factorial perspective. To this end, we will establish the experimental technique of single cell RNA-sequencing (scRNA-seq) and measure with it absolute mRNA expression levels in ~300 individual cells. In parallel, we will use conventional RNA-seq to determine the numbers of active alleles for each gene based on SNPs in heterozygous cells. We will further measure average transcription and mRNA degradation rates by combining metabolic labelling with RNA-seq. Each of these techniques will be applied to murine CD4+ T cells of different differentiation stages, which will serve as our model system.
Upon completion of the datasets, we will integrate these with additional genomic information such as gene structures, epigenetic marks and promoter architectures. This will allow us to generate models for how the studied factors interact to control transcription and to differentially express genes.

-Are there any beneficiaries within the commercial private sector who will benefit from the research?

The project will be based on the CD4+ T cell model system. T cells are involved in numerous diseases such as allergy and autoimmunity, provide hosts for HIV, and can give rise to leukemia upon uncontrolled cell division. A better understanding of the molecular mechanisms controlling T cell function, differentiation and proliferation are therefore essential from a clinical perspective. This would be of interest to pharmaceutical companies that are trying to develop commercially exploitable strategies for clinical intervention.

-Is there anyone, including policy-makers, within international, national, local or devolved government and government agencies or regulators who would benefit from this research?

Not to my knowledge.

-Are there any beneficiaries within the public sector, third sector or any others who might use the results to their advantage?

The public sector might profit from my research in the long-term due to possible clinical developments resulting from basic findings obtained from my work. This could lead to reductions in healthcare costs. It is difficult, though, to make predictions about this at this point.

-Are there any beneficiaries within the wider public?

The wider public will probably profit from commercially exploitable findings that result from my work. The innovative nature of my work also will contribute to a degree towards the development of molecular biology into a more quantitative science. This in turn would improve the UK's positioning in the international research environment and thus will benefit the wider public.

-How will they benefit from this research? Explain how the research has the potential to contribute to the nation's health, wealth or culture.

In the long-term, patients suffering from diseases such as allergy or autoimmunity will benefit from clinical strategies based on findings from my research. Commercially exploitable strategies will positively affect the economy.
In the intermediate-term, from one to a few years, my interdisciplinary work will gain visibility through presentations and publications. This will attract researchers to my group who will profit from training in new methods that span fields such as physics and biology. In addition to this, my scientific approaches will contribute to a strengthening of the perception of the UK and, in particular, the University of Warwick, as places where state-of-the-art scientific approaches are employed. This will further attract highly qualified researchers and position the UK well in the international research environment.
I am further planning to make my research become known outside of academia by collaborating with the science communication office of the University of Warwick. Initiatives such as the Schools and Community program will help to advertise my interdisciplinary scientific approach among the public and among young people. This will provide the future generation of scientists with new perspectives on how biology is becoming an exact science and will contribute to inspire mathematically oriented minds to pursue biological questions. Since biology is developing towards a quantitative science, it will greatly benefit from people with training, interests and talents in mathematics and physics.
In addition to this, I will further increase the public visibility of my research by taking part in workshops tailored for this purpose. This will increase the general awareness of current molecular biological research topics, will lead to more public interest in it, and will help to make society more scientifically knowledgeable.