Nicholas Luscombe

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Computational approaches to analyze genomic function

We are a computational biology laboratory with a particular interest in the genome-scale analysis of gene regulation and evolution, in other words, how information encoded in genomes are used and preserved.

Our goal is to use genomic data to understand:

  • How is gene expression regulated?
  • How do these mechanisms control interesting biological behaviours?
  • How does gene regulation affect evolution?

We are looking for a PhD candidate with a computational background interested in projects pertaining to aims 1 and 3. This projects involves extensive interactions with wet-lab scientists.

Aim 1: We have an excellent track-record in developing methods to understand gene regulation at a genomic scale. Previously we have built statistical models that accurately predict gene expression outcomes based on the activities of transcription factors (eg, Ilsley et al, 2013). We are now applying deep-learning methods to integrate transcriptomic, proteomic and DNA-binding data to understand the contribution of regulatory sequences and the impact of genomic variation.

Aim 3: Together with collaborators in the Crick, we have recently developed approaches to measure levels of DNA damage on a genomic scale. The genome is subject to constant chemical modification and damage, which gives rise to variable mutation rates throughout the genome. Although the mechanisms of DNA repair are reasonably well understood, how repair is executed across the genome remains poorly defined. Our new approaches and data types bridge the gap between our understanding of DNA repair mechanisms and mutation distributions by directly addressing oxidative DNA damage.

1. Martincorena, I., Seshasayee, A. S. N. and Luscombe, N. M. (2012)
Evidence of non-random mutation rates suggests an evolutionary risk management strategy.
Nature 485: 95-98. PubMed abstract

2. Martincorena, I. and Luscombe, N. M. (2013)
Non-random mutation: the evolution of targeted hypermutation and hypomutation.
Bioessays 35: 123-130. PubMed abstract

3. Mifsud, B., Tavares-Cadete, F., Young, A. N., Sugar, R., Schoenfelder, S., Ferreira, L., Wingett, S. W., Andrews, S., Grey, W., Ewels, P. A., Herman, B., Happe, S., Higgs, A., LeProust, E., Follows, G. A., Fraser, P., Luscombe, N. M. and Osborne, C. S. (2015)
Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C.
Nature Genetics 47: 598-606. PubMed abstract

4. Ilsley, G. R., Fisher, J., Apweiler, R., De Pace, A. H. and Luscombe, N. M. (2013)
Cellular resolution models for even skipped regulation in the entire Drosophila embryo.
eLife 2: e00522. PubMed abstract

5. Zarnack, K., König, J., Tajnik, M., Martincorena, I., Eustermann, S., Stévant, I., Reyes, A., Anders, S., Luscombe, N. M. and Ule, J. (2013)
Direct competition between hnRNP C and U2AF65 protects the transcriptome from the exonization of Alu elements.
Cell 152: 453-466. PubMed abstract