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.
Keywords
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References
Elowitz, M.B., Levine, A.J., Siggia, E.D., Swain, P.S.: Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002)
Ozbudak, E.M., Thattai, M., Kurtser, I., Grossman, A.D., van Oudenaarden, A.: Regulation of noise in the expression of a single gene. Nature Genetics 31(1), 69 (2002)
Raser, J.M., O’Shea, E.K.: Control of stochasticity in eukaryotic gene expression. Science 304, 1811–1814 (2004)
Bar-Even, A., Paulsson, J., Maheshri, N., Carmi, M., O’Shea, E., Pilpel, Y., Barkai, N.: Noise in protein expression scales with natural protein abundance. Nat. Genet. 38, 636–643 (2006)
Longo, D., Hasty, J.: Dynamics of single-cell gene expression. Mol. Syst. Biol. 2, 64 (2006)
Newman, J.R., Ghaemmaghami, S., Ihmels, J., Breslow, D.K., Noble, M., Derisi, J.L., Weissman, J.S.: Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441, 840–846 (2006)
Fedoroff, N., Fontana, W.: Small Numbers of Big Molecules. Science, New Series 297(5584), 1129–1131 (2002)
Wu, Y., Myasnikova, E., Reinitz, J.: Master equation simulation analysis of immunostained Bicoid morphogen gradient. BMC Syst. Biol. 1, 52 (2007)
Tkacik, G., Gregor, T., Bialek, W.: The Role of Input Noise in Transcriptional Regulation. PLoS ONE 3(7), e2774 (2008)
He, F., Wen, Y., Deng, J., Lin, X., Lu, L.J., Jiao, R., Ma, J.: Probing intrinsic properties of a robust morphogen gradient in Drosophila. Dev. Cell 15(4), 558–567 (2008)
He, F., Saunders, T.E., Wen, Y., Cheung, D., Jiao, R., ten Wolde, P.R., Howard, M., Ma, J.: Shaping a morphogen gradient for positional precision. Biophys. J. 99(3), 697–707 (2010)
Zamparo, L., Perkins, T.J.: Statistical lower bounds on protein copy number from fluorescence expression images. Bioinformatics 25, 2670–2676 (2009)
Myasnikova, E., Surkova, S., Panok, L., Samsonova, M., Reinitz, J.: Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in Drosophila. Bioinformatics 25, 346–352 (2009)
Myasnikova, E., Surkova, S., Stein, G., Pisarev, A., Samsonova, M.: A regression system for estimation of errors introduced by confocal imaging into gene expression data in situ. BMC Bioinformatics 12, 320 (2011)
Holloway, D.M., Lopes, F.J.P., da Fontoura Costa, L., Travençolo, B.A.N., Golyandina, N., Usevich, K., Spirov, A.V.: Gene expression noise in spatial patterning: hunchback promoter structure affects noise amplitude and distribution in Drosophila segmentation. PLoS Comput. Biol. 7(2), e1001069 (2011)
Lucchetta, E.M., Vincent, M.E., Ismagilov, R.F.: A Precise Bicoid Gradient Is Nonessential during Cycles 11–13 for Precise Patterning in the Drosophila Blastoderm. PLoS ONE 3(11), e3651 (2008)
Lécuyer, E., Yoshida, H., Parthasarathy, N., Alm, C., Babak, T., Cerovina, T., Hughes, T.R., Tomancak, P., Krause, H.M.: Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function. Cell 131, 174–187 (2007)
Golyandina, N., Nekrutkin, V., Zhigljavsky, A.: Analysis of Time Series Structure: SSA and Related Techniques. Chapman & Hall/CRC, Boca Raton (2001)
Alexandrov, T., Golyandina, N., Spirov, A.V.: Singular spectrum analysis of gene expression profiles of early Drosophila embryo: exponential-in-distance patterns. Res. Lett. Signal Processing 2008, 825758 (2008)
Lebrecht, D., Foehr, M., Smith, E., Lopes, F.J.P., Vanario-Alonso, C.E., et al.: Bicoid cooperative DNA binding is critical for embryonic patterning in Drosophila. Proc. Natl. Acad. Sci. USA 102, 13176–13181 (2005)
Holloway, D.M., Harrison, L.G., Kosman, D., Vanario-Alonso, C.E., Spirov, A.V.: Analysis of pattern precision shows that Drosophila segmentation develops substantial independence from gradients of maternal gene products. Dev. Dyn. 235, 2949–2960 (2006)
Lopes, F.J.P., Vieira, F.M.C., Holloway, D.M., Bisch, P.M., Spirov, A.V.: Spatial Bistability Generates hunchback Expression Sharpness in the Drosophila Embryo. PLoS Comput. Biol. 4(9), e1000184 (2008)
Pisarev, A., Poustelnikova, E., Samsonova, M., Reinitz, J.: FlyEx, the quantitative atlas on segmentation gene expression at cellular resolution. Nucl. Acids Res. 37, D560–D566 (2009)
Surkova, S., Kosman, D., Kozlov, K., Manu Myasnikova, E., Samsonova, A.A., Spirov, A.: Characterization of the Drosophila segment determination morphome. Dev. Biol. 313(2), 844–862 (2008)
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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
Publisher Name: Springer, Berlin, Heidelberg
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