Statistical models of TF/DNA interaction

• Main Author: Fouquier d'Herouel, Aymeric
• Format: Others
• Language: English
• Published: KTH, Beräkningsbiologi, CB 2008
• Subjects: gene expression; regulation; transcription factor; binding motif; matrix representations; gibbs sampling; binding affinity; non-specific binding; Biological physics; Biologisk fysik
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4633; http://nbn-resolving.de/urn:isbn:978-91-7178-874-0

Gene expression is regulated in response to metabolic necessities and environmental changes throughout the life of a cell. A major part of this regulation is governed at the level of transcription, deciding whether messengers to specific genes are produced or not. This decision is triggered by the action of transcription factors, proteins which interact with specific sites on DNA and thus influence the rate of transcription of proximal genes. Mapping the organisation of these transcription factor binding sites sheds light on potential causal relations between genes and is the key to establishing networks of genetic interactions, which determine how the cell adapts to external changes. In this work I review briefly the basics of genetics and summarise popular approaches to describe transcription factor binding sites, from the most straight forward to finally discuss a biophysically motivated representation based on the estimation of free energies of molecular interactions. Two articles on transcription factors are contained in this thesis, one published (Aurell, Fouquier d'Hérouël, Malmnäs and Vergassola, 2007) and one submitted (Fouquier d'Hérouël, 2008). Both rely strongly on the representation of binding sites by matrices accounting for the affinity of the proteins to specific nucleotides at the different positions of the binding sites. The importance of non-specific binding of transcription factors to DNA is briefly addressed in the text and extensively discussed in the first appended article: In a study on the affinity of yeast transcription factors for their binding sites, we conclude that measured in vivo protein concentrations are marginally sufficient to guarantee the occupation of functional sites, as opposed to unspecific emplacements on the genomic sequence. A common task being the inference of binding site motifs, the most common statistical method is reviewed in detail, upon which I constructed an alternative biophysically motivated approach, exemplified in the second appended article. === QC 20101110