Title Evaluating the Drosophila Bicoid morphogen gradient system through dissecting the noise in transcriptional bursts
Authors He, Feng
Ren, Jie
Wang, Wei
Ma, Jun
Affiliation Cincinnati Childrens Res Fdn, Div Biomed Informat, Cincinnati, OH 45229 USA.
Cincinnati Childrens Res Fdn, Div Dev Biol, Cincinnati, OH 45229 USA.
Peking Univ, Key Lab Cell Proliferat & Differentiat, Ctr Dev Biol & Genet, Coll Life Sci, Beijing 100871, Peoples R China.
Cincinnati Childrens Res Fdn, Div Biomed Informat, 3333 Burnet Ave, Cincinnati, OH 45229 USA.
Keywords GENE-EXPRESSION
POSITIONAL INFORMATION
PROTEIN
EMBRYOS
STOCHASTICITY
DEGRADATION
ACTIVATION
MECHANISMS
PRECISION
LIMITS
Issue Date 2012
Publisher bioinformatics
Citation BIOINFORMATICS.2012,28,(7),970-975.
Abstract Motivation: We describe a statistical model to dissect the noise in transcriptional bursts in a developmental system. Results: We assume that, at any given moment of time, each copy of a native gene inside a cell can exist in either a bursting (active) or non-bursting (inactive) state. The experimentally measured total noise in the transcriptional states of a gene in a population of cells can be mathematically dissected into two contributing components: internal and external. While internal noise quantifies the stochastic nature of transcriptional bursts, external noise is caused by cell-to-cell differences including fluctuations in activator concentration. We use our developed methods to analyze the Drosophila Bicoid (Bcd) morphogen gradient system. For its target gene hunchback (hb), the noise properties can be recapitulated by a simplified gene regulatory model in which Bcd acts as the only input, suggesting that the external noise in hb transcription is primarily derived from fluctuations in the Bcd activator input. However, such a simplified gene regulatory model is insufficient to predict the noise properties of another Bcd target gene, orthodenticle (otd), suggesting that otd transcription is sensitive to additional external fluctuations beyond those in Bcd. Our results show that analysis of the relationship between input and output noise can reveal important insights into how a morphogen gradient system works. Our study also advances the knowledge about transcription at a fundamental level.
URI http://hdl.handle.net/20.500.11897/393528
ISSN 1367-4803
DOI 10.1093/bioinformatics/bts068
Indexed SCI(E)
Appears in Collections: 生命科学学院
细胞增殖分化调控机理研究教育部重点实验室

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