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dc.contributor.authorChristopher, Josie
dc.contributor.authorGeladaki, Aikaterini
dc.contributor.authorDawson, Charlotte S
dc.contributor.authorVennard, Owen L
dc.contributor.authorLilley, Kathryn
dc.date.accessioned2022-01-13T00:30:04Z
dc.date.available2022-01-13T00:30:04Z
dc.date.issued2022-02
dc.identifier.issn1535-9476
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/332656
dc.description.abstractThe internal environment of cells is molecularly crowded, which requires spatial organization via subcellular compartmentalization. These compartments harbor specific conditions for molecules to perform their biological functions, such as coordination of the cell cycle, cell survival, and growth. This compartmentalization is also not static, with molecules trafficking between these subcellular neighborhoods to carry out their functions. For example, some biomolecules are multifunctional, requiring an environment with differing conditions or interacting partners, and others traffic to export such molecules. Aberrant localization of proteins or RNA species has been linked to many pathological conditions, such as neurological, cancer, and pulmonary diseases. Differential expression studies in transcriptomics and proteomics are relatively common, but the majority have overlooked the importance of subcellular information. In addition, subcellular transcriptomics and proteomics data do not always colocate because of the biochemical processes that occur during and after translation, highlighting the complementary nature of these fields. In this review, we discuss and directly compare the current methods in spatial proteomics and transcriptomics, which include sequencing- and imaging-based strategies, to give the reader an overview of the current tools available. We also discuss current limitations of these strategies as well as future developments in the field of spatial -omics.
dc.publisherElsevier BV
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleSubcellular Transcriptomics and Proteomics: A Comparative Methods Review.
dc.typeArticle
dc.publisher.departmentDepartment of Biochemistry Student
dc.publisher.departmentDepartment of Biochemistry
dc.date.updated2021-12-22T17:01:21Z
prism.endingPage100186
prism.number100186
prism.publicationDate2021
prism.publicationNameMol Cell Proteomics
prism.startingPage100186
dc.identifier.doi10.17863/CAM.80101
dcterms.dateAccepted2021-12-13
rioxxterms.versionofrecord10.1016/j.mcpro.2021.100186
rioxxterms.versionAM
dc.contributor.orcidChristopher, Josie [0000-0001-7077-4894]
dc.contributor.orcidLilley, Kathryn [0000-0003-0594-6543]
dc.identifier.eissn1535-9484
rioxxterms.typeJournal Article/Review
pubs.funder-project-idBiotechnology and Biological Sciences Research Council (BB/R505365/1)
pubs.funder-project-idBiotechnology and Biological Sciences Research Council (BB/R505304/1)
pubs.funder-project-idWellcome Trust (110071/Z/15/Z)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Research Infrastructures (RI) (823839)
pubs.funder-project-idBBSRC (1947751)
cam.issuedOnline2021-12-16
cam.orpheus.success2022-01-12 - Embargo set during processing via Fast-track
cam.depositDate2021-12-22
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
rioxxterms.freetoread.startdate2021-12-15


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International