Logo: to the web site of Uppsala University

The key to the complexity of higher organisms lies not in the number of protein coding genes they carry, but rather in the intrinsic complexity of the gene regulatory networks. The major effectors of transcriptional regulation are proteins called transcription factors, and in this thesis four papers describing genome-wide studies of seven such factors are presented, together with studies on components of the chromatin and transcriptome.

In Paper I, we optimized a large-scale in vivo method, ChIP-chip, to study protein – DNA interactions using microarrays. The metabolic-disease related transcription factors USF1, HNF4a and FOXA2 were studied in 1 % of the genome, and a surprising number of binding sites were found, mostly far from annotated genes.

In Paper II, a novel sequencing based method, ChIP-seq, was applied to FOXA2, HNF4a and GABPa, allowing a true genome-wide view of binding sites. A large overlap between the datasets were seen, and molecular interactions were verified in vivo. Using a ChIP-seq specific motif discovery method, we identified both the expected motifs and several for co-localized transcription factors.

In Paper III, we identified and studied a novel transcription factor, ZBED6, using the ChIP-seq method. Here, we went from one known binding site to several hundred sites throughout the mouse genome. Finally, in Paper IV, we studied the chromatin landscape by deep sequencing of nucleosomal DNA, and further used RNA-sequencing to quantify expression levels, and extended the knowledge about the binding profiles for the transcription factors NFY and TCF7L2.

Transcriptional regulation largely determines which proteins and the protein levels that are found in a cell, and this is crucial in development, differentiation and responses to environmental stimuli. The major effectors of transcriptional regulation are a group of proteins known as transcription factors, which importance is supported by their frequent involvement in mendelian and complex diseases.

In paper I, we attempted to establish the importance of DNA sequence variation in transcriptional control, by analyzing the potential functionality of polymorphic short repetitive elements as cis-regulatory elements. However, the relevance of this study was constrained by the limited number of analyzed sequences and the in vitro nature of the experiments. To overcome these limitations, (paper II) we optimized an in vivo large-scale technology named ChIP-chip, which couples chromatin immunoprecipitation and microarray hybridization. We successfully identified the binding profiles of metabolic-disease associated transcription factors in 1% of the human genome, using a liver cellular model, and inferred the binding sites at base pair resolution.

Another important characteristic of transcriptional regulation is its plasticity, which allows adjusting the cellular transcriptome to cellular and environmental stimuli. In paper III, we investigated such plasticity by treating HepG2 cells with butyrate, a histone deacetylase inhibitor (HDACi) and interrogating the changes in histone H3 and H4 acetylation levels in 1% of the genome. Observation of frequent deacetylation around transcription start sites and hyperacetylation at the nuclear periphery challenges pre-assumed HDACi mechanisms of action.

Finally, in paper IV we extended the DNA binding profiles of the medically relevant transcription factors, USF1 and USF2, and H3 acetylation to the whole non-repetitive fraction of the human genome. Using motif finding tools and chromatin profiling, we uncovered the major determinants of USF-DNA interactions. Furthermore, USFs and H3ac were clearly localized around transcription start sites, frequently in the context of bidirectional promoters.

Regulation of transcription is a central mechanism in all living cells that now can be investigated with high-throughput technologies. Data produced from such experiments give new insights to how transcription factors (TFs) coordinate the gene transcription and thereby regulate the amounts of proteins produced. These studies are also important from a medical perspective since TF proteins are often involved in disease. To learn more about transcriptional regulation, we have developed strategies for analysis of data from microarray and massively parallel sequencing (MPS) experiments.

Our computational results consist of methods to handle the steadily increasing amount of data from high-throughput technologies. Microarray data analysis tools have been assembled in the LCB-Data Warehouse (LCB-DWH) (paper I), and other analysis strategies have been developed for MPS data (paper V). We have also developed a de novo motif search algorithm called BCRANK (paper IV).

The analysis has lead to interesting biological findings in human liver cells (papers II-V). The investigated TFs appeared to bind at several thousand sites in the genome, that we have identified at base pair resolution. The investigated histone modifications are mainly found downstream of transcription start sites, and correlated to transcriptional activity. These histone marks are frequently found for pairs of genes in a bidirectional conformation. Our results suggest that a TF can bind in the shared promoter of two genes and regulate both of them.

From a medical perspective, the genes bound by the investigated TFs are candidates to be involved in metabolic disorders. Moreover, we have developed a new strategy to detect single nucleotide polymorphisms (SNPs) that disrupt the binding of a TF (paper IV). We further demonstrated that SNPs can affect transcription in the immediate vicinity. Ultimately, our method may prove helpful to find disease-causing regulatory SNPs.