The primary aim of this project is to understand how gene regulation generates precise spatial patterns in embryonic development. Biochemical reactions frequently operate at concentrations of hundreds to thousands of molecules in a nucleus or cell. Statistical expectation is that such low numbers should display relatively high variability. Yet gene expression patterns display high-precision boundaries, necessary for proper embryogenesis. This study will extend current understanding of noise control in temporal gene expression to the case of spatial patterning in complex eukaryotic development: in particular, anteroposterior body segmentation in the fruit fly Drosophila melanogaster. Using this genetically very well characterized system will contribute to understanding and controlling noise robustness in human development. Noise in segmentation is not well characterized: experimental evidence to quantify expression variability has not been gathered for statistical numbers of embryos; and mathematical models have been descriptive or deterministic, lacking noise terms. This project focuses directly on filling in these experimental and theoretical gaps. In preliminary work, expression variability has been measured both within single embryos and between embryos (work is needed to quantify the specific contributions from molecular noise and from other factors, e.g. embryo size or shape). The proposed work introduces a method for extracting quantitative gene kinetics from measured variability, i.e. using noise as a probe into the underlying biochemistry. Putative kinetic mechanisms will be tested, via stochastic simulation, for the ability to reproduce experimental variability. Parameters will be estimated by reverse-fit optimizations to data (mean and variance of expression levels). Such a mechanism can be used to determine relative contributions to patterning by different types of molecular transport (active vs. diffusive), and for studying the kinetic basis of noise suppression in developmental genetics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM072022-05
Application #
7405321
Study Section
Special Emphasis Panel (ZGM1-CMB-0 (MB))
Program Officer
Lyster, Peter
Project Start
2004-04-01
Project End
2009-06-30
Budget Start
2008-04-01
Budget End
2009-06-30
Support Year
5
Fiscal Year
2008
Total Cost
$292,914
Indirect Cost
Name
State University New York Stony Brook
Department
Biostatistics & Other Math Sci
Type
Schools of Engineering
DUNS #
804878247
City
Stony Brook
State
NY
Country
United States
Zip Code
11794
Spirov, Alexander V; Myasnikova, Ekaterina M; Holloway, David M (2016) Sequential construction of a model for modular gene expression control, applied to spatial patterning of the Drosophila gene hunchback. J Bioinform Comput Biol 14:1641005
Shlemov, Alex; Golyandina, Nina; Holloway, David et al. (2015) Shaped 3D singular spectrum analysis for quantifying gene expression, with application to the early zebrafish embryo. Biomed Res Int 2015:986436
Zamdborg, Leonid; Holloway, David M; Merelo, Juan J et al. (2015) Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem. Inf Sci (N Y) 306:88-110
Shlemov, Alex; Golyandina, Nina; Holloway, David et al. (2015) Shaped singular spectrum analysis for quantifying gene expression, with application to the early Drosophila embryo. Biomed Res Int 2015:689745
Holloway, David M; Spirov, Alexander V (2015) Mid-embryo patterning and precision in Drosophila segmentation: Krüppel dual regulation of hunchback. PLoS One 10:e0118450
Spirov, A V; Zagriychuk, E A; Holloway, D M (2014) Evolutionary Design of Gene Networks: Forced Evolution by Genomic Parasites. Parallel Process Lett 24:
Zagrijchuk, Elizaveta A; Sabirov, Marat A; Holloway, David M et al. (2014) In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression. J Bioinform Comput Biol 12:1441009
Spirov, Alexander; Holloway, David (2013) Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks. Methods 62:39-55
Spirov, Alexander V; Holloway, David M (2013) Modeling the evolution of gene regulatory networks for spatial patterning in embryo development. Procedia Comput Sci 18:
Lopes, Francisco J P; Spirov, Alexander V; Bisch, Paulo M (2012) The role of Bicoid cooperative binding in the patterning of sharp borders in Drosophila melanogaster. Dev Biol 370:165-72

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