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Maps of context-dependent putative regulatory regions and genomic signal interactions
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
Polish Acad Sci, Inst Comp Sci, PL-01248 Warsaw, Poland..
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2016 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 44, no 19, p. 9110-9120Article in journal (Refereed) Published
Abstract [en]

Gene transcription is regulated mainly by transcription factors (TFs). ENCODE and Roadmap Epigenomics provide global binding profiles of TFs, which can be used to identify regulatory regions. To this end we implemented a method to systematically construct cell-type and species-specific maps of regulatory regions and TF-TF interactions. We illustrated the approach by developing maps for five human cell-lines and two other species. We detected similar to 144k putative regulatory regions among the human cell-lines, with the majority of them being similar to 300 bp. We found similar to 20k putative regulatory elements in the ENCODE heterochromatic domains suggesting a large regulatory potential in the regions presumed transcriptionally silent. Among the most significant TF interactions identified in the heterochromatic regions were CTCF and the cohesin complex, which is in agreement with previous reports. Finally, we investigated the enrichment of the obtained putative regulatory regions in the 3D chromatin domains. More than 90% of the regions were discovered in the 3D contacting domains. We found a significant enrichment of GWAS SNPs in the putative regulatory regions. These significant enrichments provide evidence that the regulatory regions play a crucial role in the genomic structural stability. Additionally, we generated maps of putative regulatory regions for prostate and colorectal cancer human cell-lines.

Place, publisher, year, edition, pages
2016. Vol. 44, no 19, p. 9110-9120
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:uu:diva-310761DOI: 10.1093/nar/gkw800ISI: 000388016900012PubMedID: 27625394OAI: oai:DiVA.org:uu-310761DiVA, id: diva2:1057942
Funder
AstraZenecaSwedish Research CouncilSwedish Diabetes AssociationeSSENCE - An eScience Collaboration
Note

De två första författarna delar förstaförfattarskapet.

Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2018-01-25Bibliographically approved
In thesis
1. Computational Modelling of Gene Regulation in Cancer: Coding the noncoding genome
Open this publication in new window or tab >>Computational Modelling of Gene Regulation in Cancer: Coding the noncoding genome
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Technological advancements have enabled quantification of processes within and around us. The information stored within our body converts into petabytes of data. Processing and learning from such data requires comprehensive computational programs and software systems. We developed software programs to systematically investigate the process of gene regulation in the human genome. Gene regulation is a complex process where several genomic elements control expression of a gene through recruiting many transcription factor (TF) proteins. The TFs recognize specific DNA sequences known as motifs. DNA mutations in regulatory elements and particularly in TF motifs may cause gene deregulation. Therefore, defining the landscape of regulatory elements and their roles in cancer and complex diseases is of major importance.

We developed an algorithm (tfNet) to identify regulatory elements based on transcription factor binding sites. tfNet identified nearly 144,000 regulatory elements in five human cell lines. Investigating the elements we identified TF interaction networks and enrichment of many GWAS SNPs. We also defined the regulatory landscape for other conditions and species. Next, we investigated the role of regulatory elements in cancer. Cancer is initiated and developed by genetic aberrations in the genome. Genetic changes that are present in a cancer genome are obtained through whole genome sequencing technologies. We analyzed somatic mutations that had been detected in 326 whole genomes of liver cancer patients. Our results indicated 907 candidate mutations affecting TF motifs. Genome wide alignment of the mutated motifs revealed a significant enrichment of mutations in a highly conserved position of the CTCF motif. Gene expression analysis exhibited disruption of topologically associated domains in the mutated samples. We also confirmed the mutational pattern in pancreatic, gastric and esophagus cancers. Finally, enrichment of cancer associated gene sets and pathways suggested great role of noncoding mutations in cancer.

To systematically analyze DNA mutations in TF motifs, we developed an online database system (funMotifs). Publicly available datasets were collected for thousands experiments. The datasets were integrated using a logistic regression model. Functionality annotations and scores for motifs of 519 TFs were derived. The database allows for identification of variants affecting functional motifs in a selected tissue type. Finally, a comprehensive analysis was performed to identify mutations overlapping functional TF motifs in 37 cancer types. Somatic mutations from a pan-cancer cohort of 2,515 cancer whole genomes were investigated. A significant enrichment of mutations in the CpG site of the CEBPB motif was identified. Overall, 10,806 mutated regulatory elements were identified including 406 highly recurrent ones. Genes associated to the mutated elements were highly enriched for cancer-related pathways. Our analyses provide further insights onto the role of regulatory elements and their impacts on cancer development.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 54
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1627
Keywords
Regulatory elements, gene regulation, cancer, motif, integrative database, software solutions for cancer data
National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics
Identifiers
urn:nbn:se:uu:diva-339937 (URN)978-91-513-0220-1 (ISBN)
Public defence
2018-03-14, A1:111a, BMC, Husargatan 3, 09:00 (English)
Opponent
Supervisors
Available from: 2018-02-21 Created: 2018-01-24 Last updated: 2018-03-07

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