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A reassessment of DNA-immunoprecipitation-based genomic profiling
Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.ORCID iD: 0000-0003-1239-5495
Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Department of Medical and Health Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences. Natl Board Forens Med, Dept Forens Genet and Forens Toxicol, Linkoping, Sweden.ORCID iD: 0000-0001-5977-3049
Univ Edinburgh, Scotland.
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2018 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 15, no 7, p. 499-+Article in journal (Refereed) Published
Abstract [en]

DNA immunoprecipitation followed by sequencing (DIP-seq) is a common enrichment method for profiling DNA modifications in mammalian genomes. However, the results of independent DIP-seq studies often show considerable variation between profiles of the same genome and between profiles obtained by alternative methods. Here we show that these differences are primarily due to the intrinsic affinity of IgG for short unmodified DNA repeats. This pervasive experimental error accounts for 50-99% of regions identified as enriched for DNA modifications in DIP-seq data. Correction of this error profoundly altered DNA-modification profiles for numerous cell types, including mouse embryonic stem cells, and subsequently revealed novel associations among DNA modifications, chromatin modifications and biological processes. We conclude that both matched input and IgG controls are essential in order for the results of DIP-based assays to be interpreted correctly, and that complementary, non-antibody-based techniques should be used to validate DIP-based findings to avoid further misinterpretation of genome-wide profiling data.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP , 2018. Vol. 15, no 7, p. 499-+
National Category
Bioinformatics and Computational Biology
Identifiers
URN: urn:nbn:se:liu:diva-149867DOI: 10.1038/s41592-018-0038-7ISI: 000437934800012PubMedID: 29941872OAI: oai:DiVA.org:liu-149867DiVA, id: diva2:1236427
Note

Funding Agencies|Swedish Research Council [2015-03495, 2015-02575]; LiU-Cancer [2016-007]; Swedish Cancer Society [CAN 2017/625, CAN 2016/602]; Medical Research Council, UK [MC_PC_U127574433]

Available from: 2018-08-02 Created: 2018-08-02 Last updated: 2025-02-07
In thesis
1. Dynamic regulation of DNA methylation in human T-cell biology
Open this publication in new window or tab >>Dynamic regulation of DNA methylation in human T-cell biology
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

T helper cells play a central role in orchestrating immune responses in humans. Upon encountering a foreign antigen, T helper cells are activated followed by a differentiation process where the cells are specialised to help combating the infection. Dysregulation of T helper cell activation, differentiation and function has been implicated in numerous diseases, including autoimmunity and cancer. Whereas gene-regulatory networks help drive T-cell differentiation, acquisition of stable cell states require heritable epigenetic signals, such as DNA methylation. Indeed, the establishment of DNA methylation patterns is a key part of appropriate T-cell differentiation but how this is regulated over time remains unknown. Methylation can be directly attached to cytosine residues in DNA to form 5-methylcytosine (5mC) but the removal of DNA methylation requires multiple enzymatic reactions, commonly initiated by the conversion into 5-hydroxymethylcytosine (5hmC), thus creating a highly complex regulatory system. This thesis aimed to investigate how DNA methylation is dynamically regulated during T-cell differentiation.

To this end, we employed large-scale profiling techniques combining gene expression as well as genome-wide 5mC and 5hmC measurements to construct a time-series model of epigenetic regulation of differentiation. This revealed that early T-cell activation was accompanied by extensive genome-wide deposition of 5hmC which resulted in demethylation upon proliferation. Early DNA methylation remodelling through 5hmC was not only indicative of demethylation events during T-cell differentiation but also marked changes persisting longterm in memory T-cell subsets. These results suggest that priming of epigenetic landscapes in T-cells is initiated during early activation events, preceding any establishment of a stable lineage, which are then maintained throughout the cells lifespan. The regions undergoing remodelling were also highly enriched for genetic variants in autoimmune diseases which we show to be functional through disruption of protein binding. These variants could potentially disrupt gene-regulatory networks and the establishment of epigenetic priming, highlighting the complex interplay between genetic and epigenetic layers. In the course of this work, we discovered that a commonly used technique to study genome-wide DNA modifications, DNA immunoprecipitation (DIP)-seq, had a false discovery rate between 50-99% depending on the modification and cell type being assayed. This represented inherent technical errors related to the use of antibodies resulting in off-target binding of repetitive sequences lacking any DNA modifications. These sequences are common in mammalian genomes making robust detection of rare DNA modifications very difficult due to the high background signals. However, offtarget binding could easily be controlled for using a non-specific antibody control which greatly improved data quality and biological insight of the data. Although future studies are advised to use alternative methods where available, error correction is an acceptable alternative which will help fuel new discoveries through the removal of extensive background signals.

Taken together, this thesis shows how integrative use of high-resolution epigenomic data can be used to study complex biological systems over time as well as how these techniques can be systematically characterised to identify and correct errors resulting in improved detection.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 56
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1671
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:liu:diva-155116 (URN)10.3384/diss.diva-155116 (DOI)9789176851074 (ISBN)
Public defence
2019-03-29, Granitsalen, Campus US, Linköping, 09:00 (English)
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Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2019-03-19Bibliographically approved

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