Academic interests
My research focuses on how the three-dimensional (3D) organization of DNA inside the nucleus relates to critical functions in the eukaryotic cell, including epigenetic gene expression regulation. I develop computational tools and bioinformatics software to explore the comparative genomics of the 3D genome across cell-types, tissues and species. Read more about research group here.
Courses taught
Former courses taught
Publications
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Raffo, Andrea & Paulsen, Jonas
(2023).
The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data.
Briefings in Bioinformatics.
ISSN 1467-5463.
24(5),
p. 1–14.
doi:
10.1093/bib/bbad302.
Full text in Research Archive
Show summary
The three-dimensional organization of chromatin plays a crucial role in gene regulation and cellular processes like deoxyribonucleic acid (DNA) transcription, replication and repair. Hi-C and related techniques provide detailed views of spatial proximities within the nucleus. However, data analysis is challenging partially due to a lack of well-defined, underpinning mathematical frameworks. Recently, recognizing and analyzing geometric patterns in Hi-C data has emerged as a powerful approach. This review provides a summary of algorithms for automatic recognition and analysis of geometric patterns in Hi-C data and their correspondence with chromatin structure. We classify existing algorithms on the basis of the data representation and pattern recognition paradigm they make use of. Finally, we outline some of the challenges ahead and promising future directions.
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Rossini, Roberto; Kumar, Vipin; Mathelier, Anthony; Rognes, Torbjørn & Paulsen, Jonas
(2022).
MoDLE: high-performance stochastic modeling of DNA loop extrusion interactions.
Genome Biology.
ISSN 1465-6906.
23(1).
doi:
10.1186/s13059-022-02815-7.
Full text in Research Archive
Show summary
DNA loop extrusion emerges as a key process establishing genome structure and function. We introduce MoDLE, a computational tool for fast, stochastic modeling of molecular contacts from DNA loop extrusion capable of simulating realistic contact patterns genome wide in a few minutes. MoDLE accurately simulates contact maps in concordance with existing molecular dynamics approaches and with Micro-C data and does so orders of magnitude faster than existing approaches. MoDLE runs efficiently on machines ranging from laptops to high performance computing clusters and opens up for exploratory and predictive modeling of 3D genome structure in a wide range of settings.
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Paulsen, Jonas; Liyakat Ali, Tharvesh Moideen; Nekrasov, Maxim; Delbarre, Erwan; Baudement, Marie-Odile & Kurscheid, Sebastian
[Show all 8 contributors for this article]
(2019).
Long-range interactions between topologically associating domains shape the four-dimensional genome during differentiation.
Nature Genetics.
ISSN 1061-4036.
51(5),
p. 835–843.
doi:
10.1038/s41588-019-0392-0.
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Paulsen, Jonas; Liyakat Ali, Tharvesh Moideen & Collas, Philippe
(2018).
Computational 3D genome modeling using Chrom3D.
Nature Protocols.
ISSN 1754-2189.
13(5),
p. 1137–1152.
doi:
10.1038/nprot.2018.009.
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Di Stefano, Marco; Paulsen, Jonas; Lien, Tonje Gulbrandsen; Hovig, Johannes Eivind & Micheletti, Cristian
(2016).
Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization.
Scientific Reports.
ISSN 2045-2322.
6.
doi:
10.1038/srep35985.
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Sekelja, Monika; Paulsen, Jonas & Collas, Philippe
(2016).
4D nucleomes in single cells: What can computational modeling reveal about spatial chromatin conformation?
Genome Biology.
ISSN 1465-6906.
17:54.
doi:
10.1186/s13059-016-0923-2.
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Børnich, Claus; Grytten, Ivar; Hovig, Johannes Eivind; Paulsen, Jonas; Cech, Martin & Sandve, Geir Kjetil
(2016).
Galaxy Portal: Interacting with the galaxy platform through mobile devices.
Bioinformatics.
ISSN 1367-4803.
32(11),
p. 1743–1745.
doi:
10.1093/bioinformatics/btw042.
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Håkelien, Anne-Mari; Bryne, Jan Christian; Harstad, Kristine Gjul; Lorenz, Susanne; Paulsen, Jonas & Sun, Jinchang
[Show all 9 contributors for this article]
(2014).
The regulatory landscape of osteogenic differentiation.
Stem Cells.
ISSN 1066-5099.
32(10),
p. 2780–2793.
doi:
10.1002/stem.1759.
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Paulsen, Jonas; Rødland, Einar Andreas; Holden, Lars; Holden, Marit & Hovig, Johannes Eivind
(2014).
A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions.
Nucleic Acids Research (NAR).
ISSN 0305-1048.
42(18).
doi:
10.1093/nar/gku738.
Show summary
Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.
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Sandve, Geir Kjetil; Gundersen, Sveinung; Johansen, Morten; Glad, Ingrid Kristine; Gunathasan, Krishanthi & Holden, Lars
[Show all 21 contributors for this article]
(2013).
The Genomic HyperBrowser: an analysis web server for genome-scale data.
Nucleic Acids Research (NAR).
ISSN 0305-1048.
41(W1),
p. W133–W141.
doi:
10.1093/nar/gkt342.
Full text in Research Archive
Show summary
The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome.
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Paulsen, Jonas; Lien, Tonje Gulbrandsen; Sandve, Geir Kjetil; Holden, Lars; Borgan, Ørnulf & Glad, Ingrid Kristine
[Show all 7 contributors for this article]
(2013).
Handling realistic assumptions in hypothesis testing of 3D co-localization of genomic elements.
Nucleic Acids Research (NAR).
ISSN 0305-1048.
41(10),
p. 5164–5174.
doi:
10.1093/nar/gkt227.
Show summary
The study of chromatin 3D structure has recently gained much focus owing to novel techniques for detecting genome-wide chromatin contacts using next-generation sequencing. A deeper understanding of the architecture of the DNA inside the nucleus is crucial for gaining insight into fundamental processes such as transcriptional regulation, genome dynamics and genome stability. Chromatin conformation capture-based methods, such as Hi-C and ChIA-PET, are now paving the way for routine genome-wide studies of chromatin 3D structure in a range of organisms and tissues. However, appropriate methods for analyzing such data are lacking. Here, we propose a hypothesis test and an enrichment score of 3D co-localization of genomic elements that handles intra- or interchromosomal interactions, both separately and jointly, and that adjusts for biases caused by structural dependencies in the 3D data. We show that maintaining structural properties during resampling is essential to obtain valid estimation of P-values. We apply the method on chromatin states and a set of mutated regions in leukemia cells, and find significant co-localization of these elements, with varying enrichment scores, supporting the role of chromatin 3D structure in shaping the landscape of somatic mutations in cancer.
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View all works in Cristin
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Paulsen, Jonas & Collas, Philippe
(2022).
Modeling the 3D Genome Using Hi-C and Nuclear
Lamin-Genome Contacts.
In Bicciato, Silvio & Ferrari, Francesco (Ed.),
Hi-C Data Analysis
Methods and Protocols.
Humana Press.
ISSN 978-1-0716-1390-0.
p. 337–352.
doi:
10.1007/978-1-0716-1390-0_18.
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Star, Bastiaan; Nederbragt, Alexander Johan; Jentoft, Sissel; Grimholt, Unni; Malmstrøm, Martin & Gregers, Tone Fredsvik
[Show all 18 contributors for this article]
(2011).
The genome of Atlantic cod reveals a unique immune system.
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Paulsen, Jonas
(2014).
Inferential analysis of genomic 3D organization.
Akademika forlag.
ISSN 978-82-8264-950-6.
View all works in Cristin
Published
Jan. 3, 2020 2:07 PM
- Last modified
Jan. 29, 2021 1:21 PM
