uu.seUppsala universitets publikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Maps of context-dependent putative regulatory regions and genomic signal interactions
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräkningsbiologi och bioinformatik.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräkningsbiologi och bioinformatik.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräkningsbiologi och bioinformatik.
Polish Acad Sci, Inst Comp Sci, PL-01248 Warsaw, Poland..
Visa övriga samt affilieringar
2016 (Engelska)Ingår i: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 44, nr 19, s. 9110-9120Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
2016. Vol. 44, nr 19, s. 9110-9120
Nationell ämneskategori
Biokemi och molekylärbiologi
Identifikatorer
URN: urn:nbn:se:uu:diva-310761DOI: 10.1093/nar/gkw800ISI: 000388016900012PubMedID: 27625394OAI: oai:DiVA.org:uu-310761DiVA, id: diva2:1057942
Forskningsfinansiär
AstraZenecaVetenskapsrådetDiabetesförbundeteSSENCE - An eScience Collaboration
Anmärkning

De två första författarna delar förstaförfattarskapet.

Tillgänglig från: 2016-12-19 Skapad: 2016-12-19 Senast uppdaterad: 2019-09-22Bibliografiskt granskad
Ingår i avhandling
1. Computational Modelling of Gene Regulation in Cancer: Coding the noncoding genome
Öppna denna publikation i ny flik eller fönster >>Computational Modelling of Gene Regulation in Cancer: Coding the noncoding genome
2018 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Uppsala: Acta Universitatis Upsaliensis, 2018. s. 54
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1627
Nyckelord
Regulatory elements, gene regulation, cancer, motif, integrative database, software solutions for cancer data
Nationell ämneskategori
Bioinformatik (beräkningsbiologi)
Forskningsämne
Bioinformatik
Identifikatorer
urn:nbn:se:uu:diva-339937 (URN)978-91-513-0220-1 (ISBN)
Disputation
2018-03-14, A1:111a, BMC, Husargatan 3, 09:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2018-02-21 Skapad: 2018-01-24 Senast uppdaterad: 2018-03-07
2. Integrating multi-omics for type 2 diabetes: Data science and big data towards personalized medicine
Öppna denna publikation i ny flik eller fönster >>Integrating multi-omics for type 2 diabetes: Data science and big data towards personalized medicine
2019 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Type 2 diabetes (T2D) is a complex metabolic disease characterized by multi-tissue insulin resistance and failure of the pancreatic β-cells to secrete sufficient amounts of insulin. Cells recruit transcription factors (TF) to specific genomic loci to regulate gene expression that consequently affects the protein and metabolite abundancies. Here we investigated the interplay of transcriptional and translational regulation, and its impact on metabolome and phenome for several insulin-resistant tissues from T2D donors. We implemented computational tools and multi-omics integrative approaches that can facilitate the selection of candidate combinatorial markers for T2D.

We developed a data-driven approach to identify putative regulatory regions and TF-interaction complexes. The cell-specific sets of regulatory regions were enriched for disease-related single nucleotide polymorphisms (SNPs), highlighting the importance of such loci towards the genomic stability and the regulation of gene expression. We employed a similar principle in a second study where we integrated single nucleus ribonucleic acid sequencing (snRNA-seq) with bulk targeted chromosome-conformation-capture (HiCap) and mass spectrometry (MS) proteomics from liver. We identified a putatively polymorphic site that may contribute to variation in the pharmacogenetics of fluoropyrimidines toxicity for the DPYD gene. Additionally, we found a complex regulatory network between a group of 16 enhancers and the SLC2A2 gene that has been linked to increased risk for hepatocellular carcinoma (HCC). Moreover, three enhancers harbored motif-breaking mutations located in regulatory regions of a cohort of 314 HCC cases, and were candidate contributors to malignancy.

In a cohort of 43 multi-organ donors we explored the alternating pattern of metabolites among visceral adipose tissue (VAT), pancreatic islets, skeletal muscle, liver and blood serum samples. A large fraction of lysophosphatidylcholines (LPC) decreased in muscle and serum of T2D donors, while a large number of carnitines increased in liver and blood of T2D donors, confirming that changes in metabolites occur in primary tissues, while their alterations in serum consist a secondary event. Next, we associated metabolite abundancies from 42 subjects to glucose uptake, fat content and volume of various organs measured by positron emission tomography/magnetic resonance imaging (PET/MRI). The fat content of the liver was positively associated with the amino acid tyrosine, and negatively associated with LPC(P-16:0). The insulin sensitivity of VAT and subcutaneous adipose tissue was positively associated with several LPCs, while the opposite applied to branch-chained amino acids. Finally, we presented the network visualization of a rule-based machine learning model that predicted non-diabetes and T2D in an “unseen” dataset with 78% accuracy.

Ort, förlag, år, upplaga, sidor
Uppsala: Acta Universitatis Upsaliensis, 2019. s. 65
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1860
Nyckelord
type 2 diabetes, multi-omics, genomics, metabolomics, data science, machine learning, personalized medicine
Nationell ämneskategori
Bioinformatik (beräkningsbiologi) Endokrinologi och diabetes
Forskningsämne
Bioinformatik
Identifikatorer
urn:nbn:se:uu:diva-393440 (URN)978-91-513-0758-9 (ISBN)
Disputation
2019-11-11, C2:305, Biomedical Centrum (BMC), Husargatan 3, Uppsala, 09:00 (Engelska)
Opponent
Handledare
Forskningsfinansiär
AstraZeneca
Tillgänglig från: 2019-10-18 Skapad: 2019-09-22 Senast uppdaterad: 2019-11-12

Open Access i DiVA

fulltext(2153 kB)295 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 2153 kBChecksumma SHA-512
4ca11f743c741f82d60a79a11ad584f3d2449b68ca596ae2307e1df6056a494e6cf5a02b1cc7283f27f6f75c2b1039a1dcd7c52cfa3314392311aaea82d542d2
Typ fulltextMimetyp application/pdf

Övriga länkar

Förlagets fulltextPubMed

Personposter BETA

Diamanti, KlevUmer, Husen M.Kruczyk, MarcinCavalli, MarcoWadelius, ClaesKomorowski, Jan

Sök vidare i DiVA

Av författaren/redaktören
Diamanti, KlevUmer, Husen M.Kruczyk, MarcinCavalli, MarcoWadelius, ClaesKomorowski, Jan
Av organisationen
Beräkningsbiologi och bioinformatikMedicinsk genetik och genomikScience for Life Laboratory, SciLifeLab
I samma tidskrift
Nucleic Acids Research
Biokemi och molekylärbiologi

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 295 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

doi
pubmed
urn-nbn

Altmetricpoäng

doi
pubmed
urn-nbn
Totalt: 878 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf