Abstract
Fluorescence imaging has become a widely used technique for quantitatively measuring mRNA or protein expression. The first measurements were on gene expression noise in bacteria and yeast. The relative biological and physicochemical simplicity of these single cells encouraged a number of groups to try similar approaches in multicellular organisms. Such work has been primarily on whole Drosophila embryos, where the genes forming the body plan are very well understood. The numerous sources of noise in complex embryonic tissues are a major challenge for characterizing gene expression noise. Here, we present our approach for first separating experimental from biological noise, followed by distinguishing sources of biological noise. We decompose raw signal into trend and residual noise using Singular Spectrum Analysis. We demonstrate our statistical techniques on the Drosophila Hunchback protein pattern. We show that the ‘texture noise’, arising from the pre-cellular compartmentalization of the embryo surface, which is highly dynamic in time, is a major component of total biological noise, and can exceed gene transcription/translation noise.
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Spirov, A.V., Golyandina, N.E., Holloway, D.M., Alexandrov, T., Spirova, E.N., Lopes, F.J.P. (2012). Measuring Gene Expression Noise in Early Drosophila Embryos: The Highly Dynamic Compartmentalized Micro-environment of the Blastoderm Is One of the Main Sources of Noise. In: Giacobini, M., Vanneschi, L., Bush, W.S. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2012. Lecture Notes in Computer Science, vol 7246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29066-4_16
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DOI: https://doi.org/10.1007/978-3-642-29066-4_16
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