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首页> 外文期刊>Procedia Computer Science >Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability
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Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability

机译:测量早期果蝇胚胎中的基因表达噪声:核对核的变异性

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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.
机译:近年来,对基因表达中的噪声的分析已引起了实验学家和理论家的广泛关注。实验上,基于体内单细胞荧光报告基因的方法似乎是细菌和酵母的直接有效工具。然而,将这些方法转移到多细胞生物上存在许多方法学问题。在这里,我们描述了在果蝇(Drosophila)胚胎的细胞前胚盘期中,在Bicoid(Bcd)的主要形态发生梯度中测量核间变异性(噪声)的方法。该方法基于固定免疫染色胚胎的结果与携带荧光Bcd(Bcd-GFP)的活胚胎的观察结果的比较。我们使用二维奇异频谱分析(2D SSA)测量噪声。我们已经发现,对于活的(Bcd-GFP)和固定的免疫染色胚胎,Bcd强度的核对核噪声都趋于独立于信号。另外,噪声的特征对用于提取定量强度的核掩蔽技术很敏感。此外,将原始定量表达数据分解为信号(表达表面)和残留噪声的方法影响残留噪声的特性。我们发现,对共聚焦图像进行仔细的掩盖并使用适当的计算工具将原始表达数据分解为趋势和噪声,可以提取和研究基因表达的生物学噪声。

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