A Monte Carlo study of knots in long double-stranded DNA chains

dc.contributor.authorRieger, Florian C.
dc.contributor.authorVirnau, Peter
dc.date.accessioned2022-06-14T07:47:45Z
dc.date.available2022-06-14T07:47:45Z
dc.date.issued2016
dc.description.abstractWe develop a coarse-grained model of double-stranded DNA which is solely based on experimentally determined knotting probabilities of short DNA strands. Our analysis is motivated by the emergence of DNA nanopore sequencing technology. The main advantage of nanopore sequencing in comparison to next-generation devices is its capability to sequence rather long DNA strands in a single run, currently up to ≈10,000 base pairs. Unfortunately, long DNA strands easily self-entangle into knotted conformations, and sequencing knotted DNA with nanopores may be subject to error. In our manuscript, the typical extent and likelihood of DNA knots is computed for DNA chains of up to half a million base pairs, and we estimate the abundance of complex and composite knots in relation to DNA length. Our analysis indicates that DNA knots may be a formidable roadblock for the development of devices which support substantially longer read lengths. We also show that structural properties of DNA, like its resistance to bending, are intimately linked to the molecule's tendency to form knots. We demonstrate how this connection can be utilized to introduce mathematical models of DNA which account for the molecule's overall statistical properties.en_GB
dc.description.sponsorshipDFG, Open Access-Publizieren Universität Mainz / Universitätsmedizinde
dc.identifier.doihttp://doi.org/10.25358/openscience-7143
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/7157
dc.language.isoengde
dc.rightsCC-BY-4.0*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.ddc530 Physikde_DE
dc.subject.ddc530 Physicsen_GB
dc.titleA Monte Carlo study of knots in long double-stranded DNA chainsen_GB
dc.typeZeitschriftenaufsatzde
jgu.journal.issue9de
jgu.journal.titlePLoS Computational Biologyde
jgu.journal.volume12de
jgu.organisation.departmentFB 08 Physik, Mathematik u. Informatikde
jgu.organisation.nameJohannes Gutenberg-Universität Mainz
jgu.organisation.number7940
jgu.organisation.placeMainz
jgu.organisation.rorhttps://ror.org/023b0x485
jgu.pages.alternativee1005029de
jgu.publisher.doi10.1371/journal.pcbi.1005029de
jgu.publisher.issn1553-7358de
jgu.publisher.issn1553-734Xde
jgu.publisher.namePublic Library of Sciencede
jgu.publisher.placeSan Francisco, Calif.de
jgu.publisher.urihttp://dx.doi.org/10.1371/journal.pcbi.1005029de
jgu.publisher.year2016
jgu.rights.accessrightsopenAccess
jgu.subject.ddccode530de
jgu.type.dinitypeArticleen_GB
jgu.type.resourceTextde
jgu.type.versionPublished versionde
opus.affiliatedVirnau, Peter
opus.date.modified2018-08-22T10:10:26Z
opus.identifier.opusid55145
opus.institute.number0801
opus.metadataonlyfalse
opus.organisation.stringFB 08: Physik, Mathematik und Informatik: Institut für Physikde_DE
opus.subject.dfgcode00-000
opus.type.contenttypeKeinede_DE
opus.type.contenttypeNoneen_EN

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