Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

Data formats for modelling the spatial structure of chromatin based on experimental positions of nucleosomes

Competence Center Bioinformatics, Institute for Applied Computer Science, University of Applied Sciences Stralsund, Zur Schwedenschanze 15, 18435 Stralsund, Germany

Topical Section: Chromatin and Gene Regulation

In the nucleus of eukaryotic cells, DNA is wrapped around histone proteins, forming units termed nucleosomes. Nucleosome chains fold into chromatin. Despite extensive experimental advancement, many fundamental features of chromatin remain uncertain. Since all cell types and states cannot be profiled experimentally, especially in solution and in vivo, computer simulations are valuable tools for research. Most computer simulation models of chromatin are coarse-grained and describe the main characteristics of 3D chromatin packing. Newer models include experimentally derived positions of nucleosomes. While it is common practice in other disciplines, such as systems biology, to make experimental data publicly available, data from computer simulations of chromatin models are not usually published. Thus, data standard exchange formats are lacking, and we address this issue in the present work. We analysed the workflow, from experimental determination of the positions of nucleosomes through to analysis of outputs from simulated computer models. We defined standardized formats based on Extensible Markup Language (XML) for artefacts generated by steps in this workflow. We found that XML is useful since it is easy to transform XML-based-files by applying Extensible Stylesheet Language Transformations (XSLT) to other formats. We demonstrate the viability of this approach and the associated file formats using a complete example of computer simulation of chromatin domains based on experimentally determined nucleosome positions. The XML schemas and examples are published in an open source repository.
  Figure/Table
  Supplementary
  Article Metrics

References

1. Lanctôt C, Cheutin T, Cremer M, et al. (2007) Dynamic genome architecture in the nuclear space: regulation of gene expression in three dimensions. Nat Rev Genet 8: 104–115.    

2. Diermeier S, Kolovos P, Heizinger L, et al. (2014) TNFα signalling primes chromatin for NF-κB binding and induces rapid and widespread nucleosome repositioning. Genome Biol 15: 536.    

3. Müller O, Kepper N, Schöpflin R, et al. (2014) Changing chromatin fiber conformation by nucleosome repositioning. Biophys J 107: 2141–2150.    

4. Bajpai G, Padinhateeri R (2018) Irregular chromatin: packing density, fiber width and occurrence of heterogeneous clusters. bioRxiv: 453126.

5. Busch N, Wedemann G (2009) Modeling genomic data with type attributes, balancing stability and maintainability. BMC Bioinf 10: 97.    

6. Teif VB (2015) Nucleosome positioning: resources and tools online. Briefings Bioinf 17: 745–757.

7. Bowtie: Bowtie 2: fast and sensitive read alignment. Available from: http://bowtie-bio.sourceforge.net/bowtie2/index.shtml.

8. BWA-Mapping: BWA Mapper. Available from: https://www.ridom.de/u/BWA_Mapper.html.

9. Zhao Y, Wang J, Liang F, et al. (2019) NucMap: a database of genome-wide nucleosome positioning map across species. Nucleic Acids Res 47: D163–D169.    

10. Marti-Renom MA, Almouzni G, Bickmore WA, et al. (2018) Challenges and guidelines toward 4D nucleome data and model standards. Nat Genet 50: 1352.    

11. Schöpflin R, Teif VB, Müller O, et al. (2013) Modeling nucleosome position distributions from experimental nucleosome positioning maps. Bioinformatics 29: 2380–2386.    

12. Rippe K, Stehr R, Wedemann G (2012) Monte Carlo Simulations of nucleosome chains to identify factors that control DNA compaction and access. In: Schlick T, editor, Innovations in Biomolecular Modeling and Simulations. Cambridge: Royal Society of Chemistry, 198–235.

13. Nordenskiold L (2017) Coarse-Grained Modeling of Biomolecules. In: Papoian GA, editor, Coarse-Grained Modeling of Biomolecules, CRC Press, 297–340.

14. Jung J, Nishima W, Daniels M, et al. (2019) Scaling molecular dynamics beyond 100,000 processor cores for large-scale biophysical simulations. J Comput Chem 40: 1919–1930.

15. Perišić O, Portillo-Ledesma S, Schlick T (2019) Sensitive effect of linker histone binding mode and subtype on chromatin condensation. Nucleic Acids Res 47: 4948–4957.    

16. Nordenskiöld L, Soman A, Korolev N, et al. (2019) Structure and Dynamics of the Telomeric Nucleosome and Chromatin. Biophys J 116: 71a.

17. W3C: XML Technology. Available from: https://www.w3.org/standards/xml/.

18. W3C: The Extensible Stylesheet Language Family (XSL). Available from: https://www.w3.org/Style/XSL/.

19. W3C: World Wide Web Consortium (W3C). Available from: https://www.w3.org/.

20. Group OM: About the Unified Modeling Language Specification Version 2.5.1. Available from: https://www.omg.org/spec/UML/About-UML/.

21. Kepper N, Foethke D, Stehr R, et al. (2008) Nucleosome geometry and internucleosomal interactions control the chromatin fiber conformation. Biophys J 95: 3692–3705.    

22. Stehr R, Kepper N, Rippe K, et al. (2008) The effect of internucleosomal interaction on folding of the chromatin fiber. Biophys J 95: 3677–3691.    

23. Lenz O (2018) The VTF Plugin is a plugin for the VMD software that reads the VTF format. Available from: https://github.com/olenz/vtfplugin/wiki.

24. Lenz O: VMD-Visual Molecular Dynamics. Available from: http://www.ks.uiuc.edu/Research/vmd/.

25. Information NCfB: Data Series GSE40896. Available from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40896.

26. Teif VB, Vainshtein Y, Caudron-Herger M, et al. (2012) Genome-wide nucleosome positioning during embryonic stem cell development. Nat struct mol biol 19: 1185–1192.    

27. POV-Ray: POV-Ray-The Persistence of Vision Raytracer. Available from: http://www.povray.org/.

28. Wedemann G, Langowski J (2002) Computer simulation of the 30-nanometer chromatin fiber. Biophy J 82: 2847–2859.    

29. ECMA-404: ECMA-404 The JSON Data Interchange Standard. Available from: https://www.json.org/.

30. Hucka M, Finney A, Sauro HM, et al. (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19: 524–531.    

31. Bascom GD, Schlick T (2018) 5-Mesoscale Modeling of Chromatin Fibers. In: Lavelle C, Victor J-M, editors. Nuclear Architecture and Dynamics. Boston: Academic Press, 123–147.

32. Bascom GD, Sanbonmatsu KY, Schlick T (2016) Mesoscale modeling reveals hierarchical looping of chromatin fibers near gene regulatory elements. J Phys Chem B 120: 8642–8653.    

33. Ehrlich L, Münckel C, Chirico G, et al. (1997) A Brownian dynamics model for the chromatin fiber. Comput Appl Biosci 13: 271–279.

© 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Article outline

Show full outline
Copyright © AIMS Press All Rights Reserved