Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability
In recent years the analysis of noise in gene expression has widely attracted the attention of experimentalists and theoreticians. Experimentally, the approaches based on in vivo fluorescent reporters in single cells appear to be straightforward and effective tools for bacteria and yeast. However, t...
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Veröffentlicht in: | Procedia computer science 2012, Vol.9, p.373-382 |
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description | In recent years the analysis of noise in gene expression has widely attracted the attention of experimentalists and theoreticians. Experimentally, the approaches based on in vivo fluorescent reporters in single cells appear to be straightforward and effective tools for bacteria and yeast. However, transferring these approaches to multicellular organisms presents many methodological problems. Here we describe our approach to measure between-nucleus variability (noise) in the primary morphogenetic gradient of Bicoid (Bcd) in the precellular blastoderm stage of fruit fly (Drosophila) embryos. The approach is based on the comparison of results for fixed immunostained embryos with observations of live embryos carrying fluorescent Bcd (Bcd-GFP). We measure the noise using two-dimensional Singular Spectrum Analysis (2D SSA). We have found that the nucleus-to-nucleus noise in Bcd intensity, both for live (Bcd-GFP) and for fixed immunstained embryos, tends to be signal-independent. In addition, the character of the noise is sensitive to the nuclear masking technique used to extract quantitative intensities. Further, the method of decomposing the raw quantitative expression data into a signal (expression surface) and residual noise affects the character of the residual noise. We find that careful masking of confocal images and use of appropriate computational tools to decompose raw expression data into trend and noise makes it possible to extract and study the biological noise of gene expression. |
doi_str_mv | 10.1016/j.procs.2012.04.040 |
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Experimentally, the approaches based on in vivo fluorescent reporters in single cells appear to be straightforward and effective tools for bacteria and yeast. However, transferring these approaches to multicellular organisms presents many methodological problems. Here we describe our approach to measure between-nucleus variability (noise) in the primary morphogenetic gradient of Bicoid (Bcd) in the precellular blastoderm stage of fruit fly (Drosophila) embryos. The approach is based on the comparison of results for fixed immunostained embryos with observations of live embryos carrying fluorescent Bcd (Bcd-GFP). We measure the noise using two-dimensional Singular Spectrum Analysis (2D SSA). We have found that the nucleus-to-nucleus noise in Bcd intensity, both for live (Bcd-GFP) and for fixed immunstained embryos, tends to be signal-independent. In addition, the character of the noise is sensitive to the nuclear masking technique used to extract quantitative intensities. Further, the method of decomposing the raw quantitative expression data into a signal (expression surface) and residual noise affects the character of the residual noise. 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Experimentally, the approaches based on in vivo fluorescent reporters in single cells appear to be straightforward and effective tools for bacteria and yeast. However, transferring these approaches to multicellular organisms presents many methodological problems. Here we describe our approach to measure between-nucleus variability (noise) in the primary morphogenetic gradient of Bicoid (Bcd) in the precellular blastoderm stage of fruit fly (Drosophila) embryos. The approach is based on the comparison of results for fixed immunostained embryos with observations of live embryos carrying fluorescent Bcd (Bcd-GFP). We measure the noise using two-dimensional Singular Spectrum Analysis (2D SSA). We have found that the nucleus-to-nucleus noise in Bcd intensity, both for live (Bcd-GFP) and for fixed immunstained embryos, tends to be signal-independent. In addition, the character of the noise is sensitive to the nuclear masking technique used to extract quantitative intensities. Further, the method of decomposing the raw quantitative expression data into a signal (expression surface) and residual noise affects the character of the residual noise. We find that careful masking of confocal images and use of appropriate computational tools to decompose raw expression data into trend and noise makes it possible to extract and study the biological noise of gene expression.</description><subject>2D SSA</subject><subject>fluorescence imaging</subject><subject>gene expression noise</subject><subject>image segmentation</subject><subject>measuring gene expression</subject><subject>noise analysis</subject><subject>noise filtration</subject><subject>Singular Spectrum Analysis (SSA)</subject><issn>1877-0509</issn><issn>1877-0509</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp9UU1rGzEQFSWhMWl-QaHomMs6-lhZ2kIKIXWcgOteQi89CK12NpZZS1tpN9T_PnKchvSSYWAG5s2bxzyEPlMypYTOLjbTPgabpoxQNiVlTvIBTaiSsiCCVEdv-hN0ltKG5OBKVVR-RCeMScYVpRP0-weYNEbnH_ACPOD53z5CSi54vAouAXYez03sdvh7DCn0a9cZPN_WcRfSV7wabQdjKoZQ-EOLf5noTO06N-w-oePWdAnOXuopur-Z31_fFsufi7vrq2VhS1ENBZWtFbXiQhCZZTWVaioKrQRDmLVGCs4axmlVGdZwymujwJZtxW0jFK0JP0XfDrT9WG-hseCHaDrdR7c1caeDcfr_iXdr_RAeNedScSoywfkLQQx_RkiD3rpkoeuMhzAmTRWbCaGUKDOUH6A2fyNFaF_PUKL3xuiNfjZG743RpMy5V_jlrcLXnX82ZMDlAQD5TY8Ook7WgbfQuAh20E1w7x54AiebodM</recordid><startdate>2012</startdate><enddate>2012</enddate><creator>Golyandina, Nina E.</creator><creator>Holloway, David M.</creator><creator>Lopes, Francisco J.P.</creator><creator>Spirov, Alexander V.</creator><creator>Spirova, Ekaterina N.</creator><creator>Usevich, Konstantin D.</creator><general>Elsevier B.V</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>2012</creationdate><title>Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability</title><author>Golyandina, Nina E. ; Holloway, David M. ; Lopes, Francisco J.P. ; Spirov, Alexander V. ; Spirova, Ekaterina N. ; Usevich, Konstantin D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c459t-17fc5b835507723d98d91ef7ea02cca7532d23199a2d313ba8ec4f93cd581b03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>2D SSA</topic><topic>fluorescence imaging</topic><topic>gene expression noise</topic><topic>image segmentation</topic><topic>measuring gene expression</topic><topic>noise analysis</topic><topic>noise filtration</topic><topic>Singular Spectrum Analysis (SSA)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Golyandina, Nina E.</creatorcontrib><creatorcontrib>Holloway, David M.</creatorcontrib><creatorcontrib>Lopes, Francisco J.P.</creatorcontrib><creatorcontrib>Spirov, Alexander V.</creatorcontrib><creatorcontrib>Spirova, Ekaterina N.</creatorcontrib><creatorcontrib>Usevich, Konstantin D.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Procedia computer science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Golyandina, Nina E.</au><au>Holloway, David M.</au><au>Lopes, Francisco J.P.</au><au>Spirov, Alexander V.</au><au>Spirova, Ekaterina N.</au><au>Usevich, Konstantin D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability</atitle><jtitle>Procedia computer science</jtitle><addtitle>Procedia Comput Sci</addtitle><date>2012</date><risdate>2012</risdate><volume>9</volume><spage>373</spage><epage>382</epage><pages>373-382</pages><issn>1877-0509</issn><eissn>1877-0509</eissn><abstract>In recent years the analysis of noise in gene expression has widely attracted the attention of experimentalists and theoreticians. 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Further, the method of decomposing the raw quantitative expression data into a signal (expression surface) and residual noise affects the character of the residual noise. We find that careful masking of confocal images and use of appropriate computational tools to decompose raw expression data into trend and noise makes it possible to extract and study the biological noise of gene expression.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>22723811</pmid><doi>10.1016/j.procs.2012.04.040</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 2D SSA fluorescence imaging gene expression noise image segmentation measuring gene expression noise analysis noise filtration Singular Spectrum Analysis (SSA) |
title | Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability |
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