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dc.contributor.authorMarjomäki, Varpu
dc.date.accessioned2018-02-26T13:02:41Z
dc.date.available2018-02-26T13:02:41Z
dc.date.issued2012
dc.identifier.citationMarjomäki, V. (2012). Single-cell analysis of population context advances RNAi screening at multiple levels. <i>Molecular Systems Biology</i>, <i>24</i>(8), 579. <a href="https://doi.org/10.1038/msb.2012.9" target="_blank">https://doi.org/10.1038/msb.2012.9</a>
dc.identifier.otherCONVID_21743031
dc.identifier.otherTUTKAID_53077
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/57189
dc.description.abstractIsogenic cells in culture show strong variability, which arises from dynamic adaptations to the microenvironment of individual cells. Here we study the influence of the cell population context, which determines a single cell's microenvironment, in image‐based RNAi screens. We developed a comprehensive computational approach that employs Bayesian and multivariate methods at the single‐cell level. We applied these methods to 45 RNA interference screens of various sizes, including 7 druggable genome and 2 genome‐wide screens, analysing 17 different mammalian virus infections and four related cell physiological processes. Analysing cell‐based screens at this depth reveals widespread RNAi‐induced changes in the population context of individual cells leading to indirect RNAi effects, as well as perturbations of cell‐to‐cell variability regulators. We find that accounting for indirect effects improves the consistency between siRNAs targeted against the same gene, and between replicate RNAi screens performed in different cell lines, in different labs, and with different siRNA libraries. In an era where large‐scale RNAi screens are increasingly performed to reach a systems‐level understanding of cellular processes, we show that this is often improved by analyses that account for and incorporate the single‐cell microenvironment.
dc.language.isoeng
dc.publisherNature Publishing Group
dc.relation.ispartofseriesMolecular Systems Biology
dc.subject.othervirus
dc.subject.otherinfektio
dc.subject.otherinfection
dc.subject.othersystem biology
dc.titleSingle-cell analysis of population context advances RNAi screening at multiple levels
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201802231582
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.contributor.oppiaineSolu- ja molekyylibiologiafi
dc.contributor.oppiaineCell and Molecular Biologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2018-02-23T13:15:11Z
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange579
dc.relation.issn1744-4292
dc.relation.numberinseries8
dc.relation.volume24
dc.type.versionpublishedVersion
dc.rights.copyright© 2012 EMBO and Macmillan Publishers Limited. This is an open access article distributed under the terms of the Creative Commons License.
dc.rights.accesslevelopenAccessfi
dc.subject.ysosysteemibiologia
jyx.subject.urihttp://www.yso.fi/onto/yso/p18941
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1038/msb.2012.9
dc.type.okmA1


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© 2012 EMBO and Macmillan Publishers Limited. This is an open access article distributed under the terms of the Creative Commons License.
Except where otherwise noted, this item's license is described as © 2012 EMBO and Macmillan Publishers Limited. This is an open access article distributed under the terms of the Creative Commons License.