Thomas Down PhD
Thomas is a Wellcome Trust Career Development Fellow, and member of the Genetics Department
Epigenomics and transcription informatics
Co-workers: Paulina Chilasrska • Kenneth Evans
Plain English: Genome sequences are available for many organisms, but tools for finding and interpreting the sequences which regulate gene activity remain very limited. My group is developing new computational techniques for analysing gene regulators. Gene regulators consist principally of clusters of short DNA words (motifs), each of which enables the regulation of a gene by one of several hundred transcription factors. Therefore, we are creating comprehensive catalogs or dictionaries of regulatory motifs found in the human genome, and in several key model organisms. We then use them to annotate complete genome sequences and understand which genes are controlled by which transcription factors.
Understanding gene regulation will help to answer many fundamental biological questions, especially in developmental biology where little is known about how the many cell types found in complex organisms differentiate from stem cells. It has been shown that some genetic diseases, including one form of the blood disease thalassemia are caused by defects in regulators rather than protein-coding genes. Accurate and comprehensive identification of gene regulators is essential to fully understand genetic disease and variation between individuals.
We study the mechanisms by which programs of gene expression are selected and perpetuated during the development of multicellular organisms. Regulatory sequence elements contain clusters of binding sites for transcription factors, most of which interact with some specific DNA sequence motif. By discovering the repertoire of transcription factor binding sites, we can uncover an important part of the cell’s regulatory network. We are addressing this question using a new computational motif discovery tool, NestedMICA, to find DNA sequence motifs that are over-represented in larger sets of regulatory sequences from across the genomes of a panel of multicellular organisms. It has become increasingly clear that the function of regulatory elements depends on their context in terms of nuclear location and chromatin structre. To this end, we are keen to understand the landscape and functions of stable epigenetic modifications - particularly DNA cytosine methylation. High-throughput sequencing technologies allow epigenetic marks to be studied on a genome-wide basis, and we have used a combination of deep sequencing and a new analytical technique to generate the first map of DNA methylation across a complete vertebrate genome. We are now combining this technology with other analysis and data visualisation methods in order to study how DNA methylation interacts with other regulatory and epigenetic mechanisms. We are also investigating how human DNA methylation changes are associated with ageing and complex diseases.
• Rakyan VK, Down TA, Maslau S, Andrew T,Yang T-P, Beyan H,Whittaker P, McCann OT, Finer S,Valdes AM, Leslie RD, Deloukas P, and Spector TD (2010) Human aging- associated DNA hypermethylation occurs preferentially at bivalent chromatin domains. Genome Res 20:434-439
• Kolasinska-Zwierz P, Down T, Latorre I, Liu T, Liu XS and Ahringer J (2009) Differential chromatin marking of introns and expressed exons by H3K36me3. Nature Genetics 41:376-381
• Down TA, Rakyan VK,Turner DJ, Flicek P, Li J, Kulesha E, Graf S, Johnson N, Herrero J,Tomazou EM,Thorne NP, Backdahl L, Herberth M, Howe KL, Jackson DK, Miretti MM, Marioni JC, Birney E, Hubbard TJP, Durbin R,Tavare S and Beck S (2008) A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis. Nature Biotech 26:779-785
• Down TA, Bergman CM, Su J and Hubbard TJP (2007) Large scale discovery of promoter motifs in Drosophila melanogaster. PLoS Comput Biol 3:e7
• Down TA and Hubbard TJP (2005) NestedMICA: sensitive inference of over-represented motifs in nucleic acid sequences. Nucleic Acids Res 33, 1445-1453