Please use this identifier to cite or link to this item: https://doi.org/10.1093/gigascience/giz077
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dc.titleA collection of yeast cellular electron cryotomography data
dc.contributor.authorGan, L.
dc.contributor.authorNg, C.T.
dc.contributor.authorChen, C.
dc.contributor.authorCai, S.
dc.date.accessioned2021-12-29T04:35:06Z
dc.date.available2021-12-29T04:35:06Z
dc.date.issued2019
dc.identifier.citationGan, L., Ng, C.T., Chen, C., Cai, S. (2019). A collection of yeast cellular electron cryotomography data. GigaScience 8 (6) : giz077. ScholarBank@NUS Repository. https://doi.org/10.1093/gigascience/giz077
dc.identifier.issn2047217X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/212298
dc.description.abstractCells are powered by a large set of macromolecular complexes, which work together in a crowded environment. The in situ mechanisms of these complexes are unclear because their 3D distribution, organization, and interactions are largely unknown. Electron cryotomography (cryo-ET) can address these knowledge gaps because it produces cryotomograms - 3D images that reveal biological structure at ?4-nm resolution. Cryo-ET uses no fixation, dehydration, staining, or plastic embedment, so cellular features are visualized in a life-like, frozen-hydrated state. To study chromatin and mitotic machinery in situ, we subjected yeast cells to genetic and chemical perturbations, cryosectioned them, and then imaged the cells by cryo-ET. Findings: Here we share >1,000 cryo-ET raw datasets of cryosectioned budding yeast Saccharomyces cerevisiaecollected as part of previously published studies. These data will be valuable to cell biologists who are interested in the nanoscale organization of yeasts and of eukaryotic cells in general. All the unpublished tilt series and a subset of corresponding cryotomograms have been deposited in the EMPIAR resource for the community to use freely. To improve tilt series discoverability, we have uploaded metadata and preliminary notes to publicly accessible Google Sheets, EMPIAR, and GigaDB. Conclusions: Cellular cryo-ET data can be mined to obtain new cell-biological, structural, and 3D statistical insights in situ. These data contain structures not visible in traditional electron-microscopy data. Template matching and subtomogram averaging of known macromolecular complexes can reveal their 3D distributions and low-resolution structures. Furthermore, these data can serve as testbeds for high-throughput image-analysis pipelines, as training sets for feature-recognition software, for feasibility analysis when planning new structural-cell-biology projects, and as practice data for students. © 2019 The Author(s) 2019. Published by Oxford University Press.
dc.publisherOxford University Press
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2019
dc.subjectchromatin
dc.subjectcryo-EM
dc.subjectcryo-ET
dc.subjectmining
dc.subjectnucleus
dc.subjecttemplate matching
dc.subjectyeast
dc.typeArticle
dc.contributor.departmentDEPT OF BIOLOGICAL SCIENCES
dc.description.doi10.1093/gigascience/giz077
dc.description.sourcetitleGigaScience
dc.description.volume8
dc.description.issue6
dc.description.pagegiz077
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