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  • 09월 10일 16시 이후 : 초록수정 불가능, 일정확인 및 검색만 가능

제124회 대한화학회 학술발표회, 총회 및 기기전시회 안내 The Chemical Fluctuation Theorem governing gene expression

등록일
2019년 9월 16일 18시 03분 06초
접수번호
2050
발표코드
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발표시간
목 10시 : 09분
발표형식
구두발표
발표분야
KCS - Oral Presentation for 2019 DOW Korea Award
저자 및
공동저자
Seong-jun Park, Sanggeun Song1, Gil-Suk Yang2, Philip M. Kim3, Sangwoon Yoon4,*, Ji-Hyun Kim2,*, Jaeyoung Sung1,*
Creative Research Initiative Center for Chemical Dynamics in Living Cells, Chung-Ang University / National Institute of Innovative Functional Imaging, Chung-Ang University, Korea
1Creative Research Initiative Center for Chemical Dynamics in Living Cells, Chung-Ang University / Department of Chemistry, Chung-Ang University / National Institute of Innovative Functional Imaging, Chung-Ang University, Korea
2Creative Research Initiative Center for Chemical Dynamics in Living Cells, Chung-Ang University, Korea
3Terrence Donnelly Center for Cellular and Biomolecular Research, Department of Molecular Genetics and Department of Computer Science, University of Toronto, Toronto M5S 3E1 ON, Canada
4Department of Chemistry, Chung-Ang University, Korea
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승인 1건
Gene expression is a complex stochastic process composed of numerous enzymatic reactions with rates coupled to hidden cell-state variables. Despite advances in single-cell technologies, the lack of a theory accurately describing the gene expression process has restricted a robust, quantitative understanding of gene expression variability among cells. Here we present the Chemical Fluctuation Theorem (CFT), providing an accurate relationship between the environment-coupled chemical dynamics of gene expression and gene expression variability. Combined with a general, accurate model of environment-coupled transcription processes, the CFT provides a unified explanation of mRNA variability for various experimental systems. From this analysis, we construct a quantitative model of transcription dynamics enabling analytic predictions for the dependence of mRNA noise on the mRNA lifetime distribution, confirmed against stochastic simulation. This work suggests promising new directions for quantitative investigation into cellular control over biological functions by making complex dynamics of intracellular reactions accessible to rigorous mathematical deductions.

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