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A computational model for functional mapping of genes that regulate intra-cellular circadian rhythms.

Liu T, Liu X, Chen Y, Wu R - Theor Biol Med Model (2007)

Bottom Line: This model integrates a system of differential equations into the framework for functional mapping, allowing hypotheses about the interplay between genetic actions and periodic rhythms to be tested.A simulation approach based on sustained circadian oscillations of the clock proteins and their mRNAs has been designed to test the statistical properties of the model.The model has significant implications for probing the molecular genetic mechanism of rhythmic oscillations through the detection of the clock QTL throughout the genome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Statistics, University of Florida, Gainesville, FL 32611, USA. tianliu@stat.ufl.edu

ABSTRACT

Background: Genes that control circadian rhythms in organisms have been recognized, but have been difficult to detect because circadian behavior comprises periodically dynamic traits and is sensitive to environmental changes.

Method: We present a statistical model for mapping and characterizing specific genes or quantitative trait loci (QTL) that affect variations in rhythmic responses. This model integrates a system of differential equations into the framework for functional mapping, allowing hypotheses about the interplay between genetic actions and periodic rhythms to be tested. A simulation approach based on sustained circadian oscillations of the clock proteins and their mRNAs has been designed to test the statistical properties of the model.

Conclusion: The model has significant implications for probing the molecular genetic mechanism of rhythmic oscillations through the detection of the clock QTL throughout the genome.

Show MeSH
(A) Diagram of the biological elements of the protein synthesis cascade for a circadian rhythm generator. (B) Model interpretation of A showing the delay (τ) and nonlinearity in the protein production cascade, the nonlinear negative feedback, and mRNA and protein production (rM, rP) and degradation (qM, qP). Adapted from ref. [10].
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Figure 1: (A) Diagram of the biological elements of the protein synthesis cascade for a circadian rhythm generator. (B) Model interpretation of A showing the delay (τ) and nonlinearity in the protein production cascade, the nonlinear negative feedback, and mRNA and protein production (rM, rP) and degradation (qM, qP). Adapted from ref. [10].

Mentions: In all organisms studied so far, circadian rhythms that allow adaptation to a periodically changing environment originate from negative autoregulation of gene expression. Scheper et al. [10] illustrated and analyzed the generation of a circadian rhythm as a process involving a reaction cascade containing a loop, as depicted in Fig. 1A. The reaction loop consists in the production of the effective protein from its mRNA and negative feedback from the effective protein on mRNA production. The protein production process involves translation and subsequent processing steps such as phosphorylation, dimerization, transport and nuclear entry. It is assumed that the protein production cascade and the negative feedback are nonlinear processes in the reaction loop (Fig. 1B), with a time delay between protein production and subsequent processing. These nonlinearities and the delay critically determine the free-running periodicity in the feedback loop.


A computational model for functional mapping of genes that regulate intra-cellular circadian rhythms.

Liu T, Liu X, Chen Y, Wu R - Theor Biol Med Model (2007)

(A) Diagram of the biological elements of the protein synthesis cascade for a circadian rhythm generator. (B) Model interpretation of A showing the delay (τ) and nonlinearity in the protein production cascade, the nonlinear negative feedback, and mRNA and protein production (rM, rP) and degradation (qM, qP). Adapted from ref. [10].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1803780&req=5

Figure 1: (A) Diagram of the biological elements of the protein synthesis cascade for a circadian rhythm generator. (B) Model interpretation of A showing the delay (τ) and nonlinearity in the protein production cascade, the nonlinear negative feedback, and mRNA and protein production (rM, rP) and degradation (qM, qP). Adapted from ref. [10].
Mentions: In all organisms studied so far, circadian rhythms that allow adaptation to a periodically changing environment originate from negative autoregulation of gene expression. Scheper et al. [10] illustrated and analyzed the generation of a circadian rhythm as a process involving a reaction cascade containing a loop, as depicted in Fig. 1A. The reaction loop consists in the production of the effective protein from its mRNA and negative feedback from the effective protein on mRNA production. The protein production process involves translation and subsequent processing steps such as phosphorylation, dimerization, transport and nuclear entry. It is assumed that the protein production cascade and the negative feedback are nonlinear processes in the reaction loop (Fig. 1B), with a time delay between protein production and subsequent processing. These nonlinearities and the delay critically determine the free-running periodicity in the feedback loop.

Bottom Line: This model integrates a system of differential equations into the framework for functional mapping, allowing hypotheses about the interplay between genetic actions and periodic rhythms to be tested.A simulation approach based on sustained circadian oscillations of the clock proteins and their mRNAs has been designed to test the statistical properties of the model.The model has significant implications for probing the molecular genetic mechanism of rhythmic oscillations through the detection of the clock QTL throughout the genome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Statistics, University of Florida, Gainesville, FL 32611, USA. tianliu@stat.ufl.edu

ABSTRACT

Background: Genes that control circadian rhythms in organisms have been recognized, but have been difficult to detect because circadian behavior comprises periodically dynamic traits and is sensitive to environmental changes.

Method: We present a statistical model for mapping and characterizing specific genes or quantitative trait loci (QTL) that affect variations in rhythmic responses. This model integrates a system of differential equations into the framework for functional mapping, allowing hypotheses about the interplay between genetic actions and periodic rhythms to be tested. A simulation approach based on sustained circadian oscillations of the clock proteins and their mRNAs has been designed to test the statistical properties of the model.

Conclusion: The model has significant implications for probing the molecular genetic mechanism of rhythmic oscillations through the detection of the clock QTL throughout the genome.

Show MeSH