High resolution profiling of neuronal lineages by functional characterisation and sequencing of barcoded RNA

Lineage tracing is the fundamental aspect of biological research that examines how dividing cells can give rise to many different types of mature cell. This is crucial for understanding how biological tissue develops and functions. It is also crucial for understanding disease processes, because many diseases involve the abnormal production of cells or the loss of a particular cell type. Lineage tracing provides the information that explains where each of the different cell types are born, how these cells move to their final position and how they interact with one another to produce a functional piece of tissue. In the nervous system for example, scientists use lineage tracing to understand how dividing 'progenitor' cells give rise to the many different types of nerve cells found in the adult brain. We are also just beginning to understand how much influence a progenitor can have upon the nerve cells that it produces. For example, recent work has suggested that even the way that a nerve cell forms its particular connections with other nerve cells can be linked to the progenitor from which it was born.

Despite its importance for understanding biological processes, scientists have had limited tools for working out which cells come from a dividing progenitor cell. The most conclusive method has involved labelling members of the same lineage with a unique tag made from a string of genetic material in which the sequence of nucleotide 'letters' are unique. This has been referred to as 'DNA barcoding', as it uses unique labels, similar to the way that barcodes are used to identify different products in the supermarket. However, a series of issues have limited the application of this method. First, recovering the DNA barcode has proved to be very inefficient. Second, DNA barcoding has been performed on fixed tissue, which has meant that it has not been possible to study important properties of the cells whilst they are alive.

To address this problem we have developed a new approach that works with a different type of genetic material, called RNA. In our preliminary experiments we have designed an RNA barcoding approach that produces many copies of the same barcode in each cell and have shown that this increases the success of reading the barcode sequence to practically 100%. Furthermore, since RNA barcoding can be performed in live cells, this approach offers exciting new opportunities to combine our method with techniques for studying live nerve cells. For example, we can combine our method with techniques for recording the electrical activity and detailed three-dimensional shape of the nerve cell. Perhaps most importantly, our approach allows us to use powerful new genetic methods to measure the levels of thousands of different genes in each cell that we study. This provides a very rich way of classifying the exact type of nerve cell, as well as offering an insight into how a progenitor cell can influence very specific aspects of the cells it produces.

In this project we will investigate the potential of our new approach by assessing its utility for lineage tracing mouse cortical cells and also human cortical cells derived from pluripotent stem cells. Demonstrating that our method works in such different systems will show that it is an important method and can make new contributions to multiple areas of science. We will also use our method to address important biological questions, including what genes might cause related nerve cells to be more similar to one another. Finally, we are proposing to make new versions of our barcoding tool that will further increase the range of applications and we have specific plans about how we can make our tools available to the scientific community. The work will therefore have dual impact in the sense that it will advance our biological understanding of the brain, whilst also providing new technologies for scientists in many fields, including stem cell biology and cancer biology.

An appreciation of cell lineages is crucial for understanding tissue development, organisation and function. This is exemplified in the nervous system, where a diversity of progenitor cell types is believed to give rise to many different lineages. Furthermore, recent work has revealed that the precise properties of a neuron are intimately linked to the particular progenitor from which it originated. To fully understand the structural and functional organisation of the nervous system therefore, we must understand both the diversity of cell types produced by progenitor cells and how progenitors impart properties upon their progeny.

The most definitive methods for tracking cell lineages have used distinct labels that are unique to each clone of cells in the tissue. In an advanced form, this has used retroviruses to deliver unique DNA 'barcodes' to neuronal progenitors, which integrate into the genome and are passed onto the progeny. However, the impact of this approach has been limited by the low success rates in recovering the DNA barcode and its application in fixed tissue.

We believe we have solved this problem by developing a method that is based upon RNA barcoding. Our pilot work has demonstrated that this results in almost perfect recovery rates. Furthermore, our method integrates patch clamp electrophysiology and morphological assessment of live cells and is compatible with powerful single-cell transcriptomic techniques for interrogating cell type and cellular properties. We have named this approach Lineage-Seq. This project will assess the utility of this approach for lineage tracing of mouse cortical cells in vivo and human cortical cells derived from pluripotent stem cells in vitro. We will use our methodology to investigate what aspects of the transcriptome underlie morphological and functional similarities between clonally-related cortical neurons. Finally, we will extend and make available the tools for conducting Lineage-Seq in different cell types.

In addition to the academic community (see Academic Beneficiaries), the other potential beneficiaries of our work will be the private sector in the form of the pharmaceutical and life science industries, clinicians and ultimately patient populations, public service organisations in the form of local primary schools and the general public. The economical and societal impact of the proposal will be felt in the following ways:

First, the project will make a significant contribution to the computational genomics environment at the University of Oxford. This has been the intellectual foundation for spin-out companies such as Genomics plc (http://www.genomicsplc.com/), which was founded by Oxford academics and has developed analytical platforms to extract information from human genome sequences. Current members of the Sims lab are based part-time within Genomics plc, which means there will be a continuous, bi-directional exchange of ideas and approaches between the academic and commercial sector. This is an excellent example of a commercial-academic partnership.

Second, both of the contributing labs have a track record in training scientists that have transferred their skills to the commercial sector. In the case of Akerman, a previous postdoctoral scientist and PhD student both moved to DeepMind Technologies Ltd - a British artificial intelligence company that has recruited neuroscientists to work on problems in artificial intelligence and machine learning. In the case of Sims, a postdoctoral scientist has taken up the position as Senior Scientist at Genomics plc, where he works on algorithm development for the interpretation of human computational genomics data. These examples illustrate how the members of the current project can expect to acquire skill sets that are in high-demand and will strengthen the non-academic sector.

Third, the project will benefit the pharmaceutical industry because the work will involve an investigation of human induced pluripotent stem cells (iPSCs). This is a technology that is receiving major investment from pharmaceutical companies, as they look to human cellular models of disease to improve and speed up the drug discovery and development process. Indeed, over the last five years, Akerman has been an active member of the StemBANCC Innovative Medicines Initiative project, which is a European Union public-private partnership focused on the characterisation of induced pluripotent stem cell models. As well as continuing to generate experimental data that is pertinent to the iPSC system, the current project contribute to the iPSC skill-base in the UK.

Fourth, although the research is fundamental in nature, it aims to contribute to a knowledge base that will be used for training clinicians, with the ultimate goal of influencing our understanding and treatment of patient populations. As explained in other parts of the application, these fundamental studies are crucial for understanding how biological tissue develops and functions, but they also provide our framework for understanding disease processes. Many diseases involve the loss of specific cell types and understanding the developmental origin of cells, and the genes that regulate their generation, has the potential to inform intervention strategies such as stem cell therapies or drug treatments.

The fifth contribution will be felt as a social impact, by supporting public service organisations in the form of local primary schools, and benefitting the general public by increasing public engagement with research. Both contributing labs have a strong track record in public engagement and outreach and plan to maintain this during the proposed project. For example, the labs have established links to two local state primary schools, where lab members have worked with teachers to design lessons and activities around the topic of 'How we learn' and 'Our changing brains', with a particular emphasis on the neuroscience around a 'Growth Mindset'.