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A Bioinformatics Study of Human Transcriptional Regulation
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis , 2008. , p. 52
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 566
Keywords [en]
bioinformatics, microarray, ChIP-chip, ChIP-seq, transcription factor, histone modification, motif search
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-9346ISBN: 978-91-554-7324-2 (print)OAI: oai:DiVA.org:uu-9346DiVA, id: diva2:172750
Public defence
2008-11-28, C8:305, BMC, Husargatan 3, Uppsala, 09:00
Opponent
Supervisors
Available from: 2008-11-06 Created: 2008-11-06 Last updated: 2018-01-13Bibliographically approved
List of papers
1. The LCB Data Warehouse
Open this publication in new window or tab >>The LCB Data Warehouse
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2006 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 22, no 8, p. 1024-1026Article in journal (Refereed) Published
Abstract [en]

The Linnaeus Centre for Bioinformatics Data Warehouse (LCB-DWH) is a web-based infrastructure for reliable and secure microarray gene expression data management and analysis that provides an online service for the scientific community. The LCB-DWH is an effort towards a complete system for storage (using the BASE system), analysis and publication of microarray data. Important features of the system include: access to established methods within R/Bioconductor for data analysis, built-in connection to the Gene Ontology database and a scripting facility for automatic recording and re-play of all the steps of the analysis. The service is up and running on a high performance server. At present there are more than 150 registered users.

National Category
Natural Sciences
Identifiers
urn:nbn:se:uu:diva-97704 (URN)10.1093/bioinformatics/btl036 (DOI)16455749 (PubMedID)
Available from: 2008-11-06 Created: 2008-11-06 Last updated: 2017-12-14Bibliographically approved
2. Binding sites for metabolic disease related transcription factors inferred at base pair resolution by chromatin immunoprecipitation and genomic microarrays
Open this publication in new window or tab >>Binding sites for metabolic disease related transcription factors inferred at base pair resolution by chromatin immunoprecipitation and genomic microarrays
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2005 (English)In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 14, no 22, p. 3435-3447Article in journal (Refereed) Published
Abstract [en]

We present a detailed in vivo characterization of hepatocyte transcriptional regulation in HepG2 cells, using chromatin immunoprecipitation and detection on PCR fragment-based genomic tiling path arrays covering the encyclopedia of DNA element (ENCODE) regions. Our data suggest that HNF-4α and HNF-3β, which were commonly bound to distal regulatory elements, may cooperate in the regulation of a large fraction of the liver transcriptome and that both HNF-4α and USF1 may promote H3 acetylation to many of their targets. Importantly, bioinformatic analysis of the sequences bound by each transcription factor (TF) shows an over-representation of motifs highly similar to the in vitro established consensus sequences. On the basis of these data, we have inferred tentative binding sites at base pair resolution. Some of these sites have been previously found by in vitro analysis and some were verified in vitro in this study. Our data suggests that a similar approach could be used for the in vivo characterization of all predicted/uncharacterized TF and that the analysis could be scaled to the whole genome.

Keywords
Base Pairing/*genetics, Binding Sites/genetics, Cell Line; Tumor, Chromatin/*metabolism, Chromatin Immunoprecipitation/methods, Consensus Sequence, Genome; Human, Hepatocyte Nuclear Factor 3-beta/physiology, Hepatocyte Nuclear Factor 4/physiology, Hepatocytes/metabolism, Histones/metabolism, Humans, Metabolic Diseases/*metabolism, Oligonucleotide Array Sequence Analysis/methods, Promoter Regions (Genetics), Research Support; N.I.H.; Extramural, Research Support; Non-U.S. Gov't, Sequence Analysis; DNA, Transcription Factors/genetics/*metabolism, Upstream Stimulatory Factors/metabolism
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-80603 (URN)10.1093/hmg/ddi378 (DOI)16221759 (PubMedID)
Available from: 2006-05-19 Created: 2006-05-19 Last updated: 2017-12-14Bibliographically approved
3. Whole-genome maps of USF1 and USF2 binding and histone H3 acetylation reveal new aspects of promoter structure and candidate genes for common human disorders
Open this publication in new window or tab >>Whole-genome maps of USF1 and USF2 binding and histone H3 acetylation reveal new aspects of promoter structure and candidate genes for common human disorders
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2008 (English)In: Genome Research, ISSN 1088-9051, E-ISSN 1549-5469, Vol. 18, no 3, p. 380-392Article in journal (Refereed) Published
Abstract [en]

Transcription factors and histone modifications are crucial regulators of gene expression that mutually influence each other. We present the DNA binding profiles of upstream stimulatory factors 1 and 2 (USF1, USF2) and acetylated histone H3 (H3ac) in a liver cell line for the whole human genome using ChIP-chip at a resolution of 35 base pairs. We determined that these three proteins bind mostly in proximity of protein coding genes transcription start sites (TSSs), and their bindings are positively correlated with gene expression levels. Based on the spatial and functional relationship between USFs and H3ac at protein coding gene promoters, we found similar promoter architecture for known genes and the novel and less-characterized transcripts human mRNAs and spliced ESTs. Furthermore, our analysis revealed a previously underestimated abundance of genes in a bidirectional conformation, where USFs are bound in between TSSs. After taking into account this promoter conformation, the results indicate that H3ac is mainly located downstream of TSS, and it is at this genomic location where it positively correlates with gene expression. Finally, USF1, which is associated to familial combined hyperlipidemia, was found to bind and potentially regulate nuclear mitochondrial genes as well as genes for lipid and cholesterol metabolism, frequently in collaboration with GA binding protein transcription factor alpha (GABPA, nuclear respiratory factor 2 [NRF-2]). This expands our understanding about the transcriptional control of metabolic processes and its alteration in metabolic disorders.

National Category
Bioinformatics and Systems Biology
Identifiers
urn:nbn:se:uu:diva-97706 (URN)10.1101/gr.6880908 (DOI)000253766700004 ()18230803 (PubMedID)
Available from: 2008-11-06 Created: 2008-11-06 Last updated: 2017-12-14Bibliographically approved
4. New algorithm and ChIP-analysis identifies candidate functional SNPs
Open this publication in new window or tab >>New algorithm and ChIP-analysis identifies candidate functional SNPs
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In: PNASArticle in journal (Refereed) Submitted
Identifiers
urn:nbn:se:uu:diva-97707 (URN)
Available from: 2008-11-06 Created: 2008-11-06Bibliographically approved
5. Differential binding and co-binding pattern of FOXA1 and FOXA3 and their relation to H3K4me3 in HepG2 cells revealed by ChIP-seq
Open this publication in new window or tab >>Differential binding and co-binding pattern of FOXA1 and FOXA3 and their relation to H3K4me3 in HepG2 cells revealed by ChIP-seq
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2009 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 10, no 11, p. R129-Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: The forkhead box/winged helix family members FOXA1, FOXA2, and FOXA3 are of high importance in development and specification of the hepatic linage and the continued expression of liver-specific genes. RESULTS: Here, we present a genome-wide location analysis of FOXA1 and FOXA3 binding sites in HepG2 cells through chromatin immunoprecipitation with detection by sequencing (ChIP-seq) studies and compare these with our previous results on FOXA2. We found that these factors often bind close to each other in different combinations and consecutive immunoprecipitation of chromatin for one and then a second factor (ChIP-reChIP) shows that this occurs in the same cell and on the same DNA molecule, suggestive of molecular interactions. Using co-immunoprecipitation, we further show that FOXA2 interacts with both FOXA1 and FOXA3 in vivo, while FOXA1 and FOXA3 do not appear to interact. Additionally, we detected diverse patterns of trimethylation of lysine 4 on histone H3 (H3K4me3) at transcriptional start sites and directionality of this modification at FOXA binding sites. Using the sequence reads at polymorphic positions, we were able to predict allele specific binding for FOXA1, FOXA3, and H3K4me3. Finally, several SNPs associated with diseases and quantitative traits were located in the enriched regions. CONCLUSIONS: We find that ChIP-seq can be used not only to create gene regulatory maps but also to predict molecular interactions and to inform on the mechanisms for common quantitative variation.

National Category
Medical and Health Sciences Biological Sciences
Identifiers
urn:nbn:se:uu:diva-119751 (URN)10.1186/gb-2009-10-11-r129 (DOI)000273344600016 ()19919681 (PubMedID)
Note

De två (2) första författarna delar förstaförfattarskapet.

Available from: 2010-03-01 Created: 2010-03-01 Last updated: 2017-12-12Bibliographically approved

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