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dc.contributor.authorHughes, Travis K
dc.contributor.authorWadsworth, Marc H
dc.contributor.authorGierahn, Todd M
dc.contributor.authorDo, Tran
dc.contributor.authorWeiss, David
dc.contributor.authorAndrade, Priscila R
dc.contributor.authorMa, Feiyang
dc.contributor.authorde Andrade Silva, Bruno J
dc.contributor.authorShao, Shuai
dc.contributor.authorTsoi, Lam C
dc.contributor.authorOrdovas-Montanes, Jose
dc.contributor.authorGudjonsson, Johann E
dc.contributor.authorModlin, Robert L
dc.contributor.authorLove, J Christopher
dc.contributor.authorShalek, Alex K
dc.date.accessioned2021-10-27T20:22:49Z
dc.date.available2021-10-27T20:22:49Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/135291
dc.description.abstract© 2020 The Authors High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 (“Second-Strand Synthesis”), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.
dc.language.isoen
dc.publisherElsevier BV
dc.relation.isversionof10.1016/J.IMMUNI.2020.09.015
dc.rightsCreative Commons Attribution 4.0 International license
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceElsevier
dc.titleSecond-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies
dc.typeArticle
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Science
dc.contributor.departmentRagon Institute of MGH, MIT and Harvard
dc.contributor.departmentKoch Institute for Integrative Cancer Research at MIT
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistry
dc.relation.journalImmunity
dc.eprint.versionFinal published version
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2021-06-14T15:28:59Z
dspace.orderedauthorsHughes, TK; Wadsworth, MH; Gierahn, TM; Do, T; Weiss, D; Andrade, PR; Ma, F; de Andrade Silva, BJ; Shao, S; Tsoi, LC; Ordovas-Montanes, J; Gudjonsson, JE; Modlin, RL; Love, JC; Shalek, AK
dspace.date.submission2021-06-14T15:29:02Z
mit.journal.volume53
mit.journal.issue4
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Needed


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