Ivar Grytten

• Pavlović, Milena; Scheffer, Lonneke; Motwani, Keshav; Kanduri, Chakravarthi; Kompova, Radmila & Vazov, Nikolay Aleksandrov [Show all 41 contributors for this article] (2021). The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nature Machine Intelligence. 3(11), p. 936–944. doi: 10.1038/s42256-021-00413-z.
• Grytten, Ivar; Rand, Knut Dagestad; Nederbragt, Alexander Johan & Sandve, Geir Kjetil (2020). Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methods. BMC Genomics. ISSN 1471-2164. 21. doi: 10.1186/s12864-020-6685-y. Full text in Research Archive
• Fan, Qiong; Nørgaard, Rikke Christine; Grytten, Ivar; Ness, Cecilie; Lucas, Christin & Vekterud, Kristin [Show all 15 contributors for this article] (2020). LXRα Regulates ChREBPα Transactivity in a Target Gene-Specific Manner through an Agonist-Modulated LBD-LID Interaction. Cells. ISSN 2073-4409. 9(5), p. 1–26. doi: 10.3390/cells9051214. Full text in Research Archive Show summary

  The cholesterol-sensing nuclear receptor liver X receptor (LXR) and the glucose-sensing transcription factor carbohydrate responsive element-binding protein (ChREBP) are central players in regulating glucose and lipid metabolism in the liver. More knowledge of their mechanistic interplay is needed to understand their role in pathological conditions like fatty liver disease and insulin resistance. In the current study, LXR and ChREBP co-occupancy was examined by analyzing ChIP-seq datasets from mice livers. LXR and ChREBP interaction was determined by Co-immunoprecipitation (CoIP) and their transactivity was assessed by real-time quantitative polymerase chain reaction (qPCR) of target genes and gene reporter assays. Chromatin binding capacity was determined by ChIP-qPCR assays. Our data show that LXRα and ChREBPα interact physically and show a high co-occupancy at regulatory regions in the mouse genome. LXRα co-activates ChREBPα and regulates ChREBP-specific target genes in vitro and in vivo. This co-activation is dependent on functional recognition elements for ChREBP but not for LXR, indicating that ChREBPα recruits LXRα to chromatin in trans. The two factors interact via their key activation domains; the low glucose inhibitory domain (LID) of ChREBPα and the ligand-binding domain (LBD) of LXRα. While unliganded LXRα co-activates ChREBPα, ligand-bound LXRα surprisingly represses ChREBPα activity on ChREBP-specific target genes. Mechanistically, this is due to a destabilized LXRα:ChREBPα interaction, leading to reduced ChREBP-binding to chromatin and restricted activation of glycolytic and lipogenic target genes. This ligand-driven molecular switch highlights an unappreciated role of LXRα in responding to nutritional cues that was overlooked due to LXR lipogenesis-promoting function.

• Fan, Qiong; Nørgaard, Rikke Christine; Grytten, Ivar; Ness, Cecilie Maria; Lucas, Christin & Vekterud, Kristin [Show all 15 contributors for this article] (2019). Open the LID: LXRα regulates ChREBPα transactivity in a target gene-specific manner through an agonist-modulated LBD-LID interaction. BioRxiv. ISSN 0362-4331. doi: 10.1101/2019.12.20.869974. Show summary

  The cholesterol-sensing nuclear receptor liver X receptor (LXR) and the glucose-sensing transcription factor carbohydrate responsive element-binding protein (ChREBP) are central players in regulating glucose and lipid metabolism in liver. We have previously shown that LXR regulates ChREBP transcription and activity; however, the underlying mechanisms are unclear. In the current study, we demonstrate that LXRα and ChREBPα interact physically, and show a high co-occupancy at regulatory regions in the mouse genome. LXRα co-activates ChREBPα, and regulates ChREBP-specific target genes in vitro and in vivo. This co-activation is dependent on functional recognition elements for ChREBP, but not for LXR, indicating that ChREBPα recruits LXRα to chromatin in trans. The two factors interact via their key activation domains; ChREBPα’s low glucose inhibitory domain (LID) and the ligand-binding domain (LBD) of LXRα. While unliganded LXRα co-activates ChREBPα, ligand-bound LXRα surprisingly represses ChREBPα activity on ChREBP-specific target genes. Mechanistically, this is due to a destabilized LXRα:ChREBPα interaction, leading to reduced ChREBP-binding to chromatin and restricted activation of glycolytic and lipogenic target genes. This ligand-driven molecular switch highlights an unappreciated role of LXRα that was overlooked due to LXR lipogenesis-promoting function.

• Salvatore, Stefania; Rand, Knut Dagestad; Grytten, Ivar; Ferkingstad, Egil; Domanska, Diana & Holden, Lars [Show all 10 contributors for this article] (2019). Beware the Jaccard: the choice of similarity measure is important and non-trivial in genomic colocalisation analysis. Briefings in Bioinformatics. ISSN 1467-5463. p. 1–8. doi: 10.1093/bib/bbz083.
• Grytten, Ivar; Rand, Knut Dagestad; Nederbragt, Alexander Johan; Storvik, Geir Olve; Glad, Ingrid Kristine & Sandve, Geir Kjetil (2019). Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes. PLoS Computational Biology. ISSN 1553-734X. 15(2), p. 1–13. doi: 10.1371/journal.pcbi.1006731. Full text in Research Archive
• Rand, Knut Dagestad; Grytten, Ivar; Nederbragt, Alexander Johan; Storvik, Geir Olve; Glad, Ingrid Kristine & Sandve, Geir Kjetil (2017). Coordinates and intervals in graph-based reference genomes. BMC Bioinformatics. ISSN 1471-2105. 18:263, p. 1–8. doi: 10.1186/s12859-017-1678-9. Full text in Research Archive
• Simovski, Boris; Vodak, Daniel; Gundersen, Sveinung; Domanska, Diana Ewa; Azab, Abdulrahman & Holden, Lars [Show all 25 contributors for this article] (2017). GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome. GigaScience. ISSN 2047-217X. 6(7), p. 1–12. doi: 10.1093/gigascience/gix032. Full text in Research Archive Show summary

  Background: Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. Findings: We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Conclusions: Through a combination of streamlined data acquisition, interoperable representation of dataset collections and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no

• 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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• Balaban, Gabriel; Grytten, Ivar; Rand, Knut Dagestad; Scheffer, Lonneke & Sandve, Geir Kjetil (2021). Ten simple rules for quick and dirty scientific programming. PLoS Computational Biology. ISSN 1553-734X. 17:e1008549(3), p. 1–15. doi: 10.1371/journal.pcbi.1008549.
• Fan, Qiong; Nørgaard, Rikke Christine; Grytten, Ivar; Ness, Cecilie Maria; Lucas, Christin & Vekterud, Kristin [Show all 15 contributors for this article] (2019). LXRα interacts with the glucose-sensing transcription factor ChREBPα to regulate its transcriptional activity.
• Fan, Qiong; Nørgaard, Rikke Christine; Grytten, Ivar; Ulven, Stine Marie; Lucas, Christin & Bindesbøll, Christian [Show all 11 contributors for this article] (2018). LXRα interacts with the glucose-sensing transcription factor ChREBPα and increases its transcriptional activity.

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