Regulatory Genomics in Evolution
and Disease

 

Summary

Our group undertakes computational analyses of large-scale genomic, transcriptomic and genotyping datasets to investigate human disease and molecular evolution in mammals. Highlights have included exploratory, genome-wide studies of regulatory sequence evolution (Taylor et al, 2006) and of human chromosome structure and mutation rates (Prendergast et al, 2007). At the same time we have been active in studies of medical relevance, such as the reconstruction of regulatory networks in cancer (FANTOM Consortium, 2009).

 

 

Key Publications

1. Semple, C.A. and Taylor, M.S. Molecular biology: The structure of change.
   Science 323:347-348, 2009
   PubMed Abstract
2. FANTOM Consortium: Suzuki, H.; Forrest, A.R.; ..... Semple, C.A.;....and Hayashizaki, Y. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nat Genet 41(5):553-562, 2009 PubMed Abstract
3. Tenesa, A.; Farrington, S.M.; Prendergast, J.G.; Porteous, M.E.; Walker, M.; Haq, N.; Barnetson, R.A.; Theodoratou, E.; Cetnarskyj, R.; Cartwright, N.;
   Semple, C.; ....... Campbell, H., and Dunlop, M.G. Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat Genet 40(5): 631-637, 2008
   PubMed Abstract
   
4. Prendergast, J.G.; Campbell, H.; Gilbert, N.; Dunlop, M.G.; Bickmore, W.A. and
   Semple, C.A. Chromatin structure and evolution in the human genome.
   BMC Evol Biol 7:72, 2007
   PubMed Abstract
5. Carninci, P.; Sandelin, A.; Lenhard, B.; Katayama, S.; Shimokawa, K.; Ponjavic, J. Semple, C.A.; Taylor, M.S.; Engstrom, P.G.; Frith, M.C. et al. Genome-wide analysis of mammalian promoter architecture and evolution.
   Nat Genet 38:626-635, 2006
   PubMed Abstract
   
6. Taylor, M.S.; Kai, C.; Kawai, J.; Carninci, P.; Hayashizaki, Y. and Semple C.A. Heterotachy in mammalian promoter evolution. PLOS Genetics 2(4):e30, 2006 PubMed Abstract
7. Turner, F.S.; Clutterbuck, D.R.; and
   Semple, C.A.M. POCUS: mining genomic sequence annotation to predict disease genes. Genome Biology 4:R75, 2003
   PubMed Abstract
   

 

Collaborations

• Professor Wendy Bickmore MRC Human Genetics Unit, Edinburgh, UK.
• Professor Malcolm Dunlop MRC Human Genetics Unit, Edinburgh, UK.
• Professor Yoshihide Hayashizaki Genome Science Centre, RIKEN, Yokohama, Japan.
• Professor Chris Haley, Roslin Institute and MRC Human Genetics Unit, Edinburgh, UK.
• Dr Martin Taylor MRC Human Genetics Unit, Edinburgh, UK
  
  

 

Lab Members

Current lab members involved in this work are:

• Dr Colin Semple Head of Bioinformatics

• Dr Philippe Gautier MRC staff Bioinformatician

• Mr Graeme Grimes MRC staff Bioinformatician

• Dr James Prendergast MRC staff Bioinformatician

• Ms Emily Chambers MRC Computational Biology PhD student Ms

• Ms Alida Kindt MRC Computational Biology PhD student
  

 

We have also been active in more focused work, examining the regulation and evolution of genes studied by human disease geneticists. These results have guided the subsequent work of experimental biologists.

 

1. Computational Genomics Laboratory

 

Purpose

We exploit large-scale datasets to study mammalian genome function and evolution.

 

Approach, Progress and Future Work

We aim to build on our past work and existing collaborations to examine regulatory genomics in evolution and disease at various levels:

 

(i) Chromatin structure in development and disease

We have examined the correlation between chromatin fiber structure and various evolutionary parameters such as mutation and selection across the human genome (Prendergast et al, 2007). We intend to extend this work to generate new insights into development and disease states with an epigenetic component, such as cancers.

 

(ii) Comparative epigenomics

Developments in high throughput sequencing have provided the first glimpses of conservation and divergence of the epigenomic landscape between species (Semple and Taylor, 2009), we are currently studying the dynamics of chromatin structure over evolutionary time.

 

(iii) Transcriptional regulation and molecular evolution

Our studies of the dynamics of mammalian promoter evolution concluded that primate regulatory sequences appeared to have suffered an unusual mutational spectrum (Carninci et al, 2006; Taylor et al, 2006). This work has generated new questions that we aim to address by studying patterns of mutation and selective constraint at higher resolution. In addition we are undertaking novel analyses of new datasets made available through our participation in an ongoing international consortium: the FANTOM Consortium (The FANTOM Consortium, 2009).

 

(iv) Prediction of causal variants in human disease

We have had a long-standing interest in prioritising genetic variants for meta-analyses of human disease (Turner et al, 2003) and in genome-wide association studies (Tenesa et al, 2008). Recent work has suggested several strategies to increase the success of such analyses.