title: Single-cell analysis of transcription kinetics across the cell cycle.
abstract: Transcription is a highly stochastic process. To infer transcription kinetics for a gene-of-interest, researchers commonly compare the distribution of mRNA copy-number to the prediction of a theoretical model. However, the reliability of this procedure is limited because the measured mRNA numbers represent integration over the mRNA lifetime, contribution from multiple gene copies, and mixing of cells from different cell-cycle phases. We address these limitations by simultaneously quantifying nascent and mature mRNA in individual cells, and incorporating cell-cycle effects in the analysis of mRNA statistics. We demonstrate our approach on Oct4 and Nanog in mouse embryonic stem cells. Both genes follow similar two-state kinetics. However, Nanog exhibits slower ON/OFF switching, resulting in increased cell-to-cell variability in mRNA levels. Early in the cell cycle, the two copies of each gene exhibit independent activity. After gene replication, the probability of each gene copy to be active diminishes, resulting in dosage compensation.
authors.affiliation: Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States.|Center for Theoretical Biological Physics, Rice University, Houston, United States.|Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States.
authors.forename: Samuel O
authors.initials: SO
authors.lastname: Skinner
authors.affiliation: Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States.|Center for Theoretical Biological Physics, Rice University, Houston, United States.|Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, United States.
authors.forename: Heng
authors.initials: H
authors.lastname: Xu
authors.affiliation: Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, United States.
authors.forename: Sonal
authors.initials: S
authors.lastname: Nagarkar-Jaiswal
authors.affiliation: Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, United States.
authors.forename: Pablo R
authors.initials: PR
authors.lastname: Freire
authors.affiliation: Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, United States.|Department for Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, United States.
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Zwaka
authors.affiliation: Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States.|Center for Theoretical Biological Physics, Rice University, Houston, United States.|Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States.|Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, United States.
authors.forename: Ido
authors.identifier: http://orcid.org/0000-0002-4308-4959
authors.initials: I
authors.lastname: Golding
mesh_terms: D000818:Animals; D002453:Cell Cycle; D053595:Embryonic Stem Cells; D020869:Gene Expression Profiling; D051379:Mice; D000071317:Nanog Homeobox Protein / Q000096:biosynthesis / Q000235:genetics; D050814:Octamer Transcription Factor-3 / Q000096:biosynthesis / Q000235:genetics; D012333:RNA, Messenger / Q000032:analysis; D059010:Single-Cell Analysis; D014158:Transcription, Genetic
chemical_list: D000071317:Nanog Homeobox Protein; C475540:Nanog protein, mouse; D050814:Octamer Transcription Factor-3; C494174:Pou5f1 protein, mouse; D012333:RNA, Messenger
keywords: chromosomes; computational biology; fluorescence in situ; genes; mathematical modeling; mouse; single cell; single molecule; stochastic gene expression; systems biology; theory
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