Profiling human genetic variation at scale via high-throughput genome editing

A Crick funded PhD position for the 2022 programme in the lab of Greg Findlay.

Applications are now closed

We are no longer accepting applications for the 2022 PhD student programme. If you submitted an application by the deadline, check our applicant information pages.

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A diverse group of cells, and a cartoon showing their genomic features below.

Project background and description

 

The wealth of information contained in each human’s genome includes the instructions for how the body forms and functions, as well as clues about what diseases one may develop. As sequencing costs continue to fall, it has become common to sequence vast amounts of DNA in hopes of uncovering the molecular origins of disease. For example, understanding the effects of DNA variants in genes linked to cancer has proven vital for determining both whether a person is genetically predisposed to cancer and which clinical interventions will optimise outcomes [2].

Despite the promise of genomic medicine, gains have been limited. This is largely due to the difficulty of interpreting rare genetic variants. Even in the most well-studied genes, it is challenging to predict which mutations have molecular consequences that ultimately impact our health. Outside of these genes, we lack a firm understanding of precisely which regions perform key functions, making the task of interpreting variants harder, still. However, we now have powerful experimental tools that allow us to edit the human genome as a means of better understanding how it functions.

Our lab leverages innovations in genome editing to ask which variants contribute to human disease and how. We use CRISPR-based tools to alter human cells grown in culture and next-generation sequencing to track effects of millions of mutations simultaneously. We compare our experimental results to databases of human phenotypes and computational models to infer which mutations cause disease and why they do on a mechanistic level.

The selected student will lead a project studying mutations in tumour suppressor genes, such as BRCA1/2, TP53, APC, and MSH2. The student will learn methods such as saturation genome editing and prime editing to identify mutations implicated in disease [3, 4] and CRISPR-based guide-RNA screening to characterise poorly understood regions of the genome [5]. Variants will be explored with a range of human cell-based functional assays, including single-cell transcriptomics. The student will be given the autonomy to research areas of particular interest, such as RNA splicing, gene regulation, and/or long non-coding RNAs. The student will be trained to analyse complex, sequencing-based datasets in conjunction with large-scale human genetics data and there will be ample opportunities to collaborate with clinicians. 

This project will ultimately advance our understanding of how mutations can alter the molecular processes necessary for our genomes to function properly. It also promises to have a direct clinical impact by improving our ability to interpret variants seen in cancer patients.

Candidate background

 

No specific experiences are required. Prior research in genetics, genomics, computational biology, molecular biology, biotechnology, bioengineering or a closely related field is highly desirable. Experience with coding and/or DNA sequencing data analysis is desirable. The chosen candidate will be motivated to learn, curious about genomics and how mutations cause disease, and excited to develop and optimise new methods.

The successful applicant will be prepared to train in both experimental work and computational analysis. Attention to detail, respect for colleagues, and strong communication skills are required.

References

 

1.         Findlay, G.M. (2021)

            Linking genome variants to disease: Scalable approaches to test the functional impact of human mutations.

            Human Molecular Genetics Epub ahead of print. PubMed abstract

2.         Shendure, J., Findlay, G.M. and Snyder, M.W. (2019)

            Genomic medicine–progress, pitfalls, and promise.

            Cell 177: 45-57. PubMed abstract

3.         Findlay, G.M., Boyle, E.A., Hause, R.J., Klein, J.C. and Shendure, J. (2014)

            Saturation editing of genomic regions by multiplex homology-directed repair.

            Nature 513: 120-123. PubMed abstract

4.         Findlay, G.M., Daza, R.M., Martin, B., Zhang, M.D., Leith, A.P., Gasperini, M., . . . Shendure, J. (2018)

            Accurate classification of BRCA1 variants with saturation genome editing.

            Nature 562: 217-222. PubMed abstract

5.         Gasperini, M., Findlay, G.M., McKenna, A., Milbank, J.H., Lee, C., Zhang, M.D., . . . Shendure, J. (2017)

            CRISPR/Cas9-mediated scanning for regulatory elements required for HPRT1 expression via thousands of large, programmed genomic deletions.

            American Journal of Human Genetics 101: 192-205. PubMed abstract