Department of Genome Dynamics, Berkeley Drosophila Genome Project, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
Mol Syst Biol. 2010;6:345. doi: 10.1038/msb.2009.102. Epub 2010 Jan 19.
Discovery of temporal and spatial patterns of gene expression is essential for understanding the regulatory networks and development in multicellular organisms. We analyzed the images from our large-scale spatial expression data set of early Drosophila embryonic development and present a comprehensive computational image analysis of the expression landscape. For this study, we created an innovative virtual representation of embryonic expression patterns using an elliptically shaped mesh grid that allows us to make quantitative comparisons of gene expression using a common frame of reference. Demonstrating the power of our approach, we used gene co-expression to identify distinct expression domains in the early embryo; the result is surprisingly similar to the fate map determined using laser ablation. We also used a clustering strategy to find genes with similar patterns and developed new analysis tools to detect variation within consensus patterns, adjacent non-overlapping patterns, and anti-correlated patterns. Of the 1800 genes investigated, only half had previously assigned functions. The known genes suggest developmental roles for the clusters, and identification of related patterns predicts requirements for co-occurring biological functions.
发现基因表达的时空模式对于理解多细胞生物的调控网络和发育至关重要。我们分析了来自早期果蝇胚胎发育的大规模空间表达数据集的图像，并对表达图谱进行了全面的计算图像分析。在这项研究中，我们使用椭圆形状的网格创建了胚胎表达模式的创新虚拟表示形式，这使我们能够使用共同的参考框架对基因表达进行定量比较。通过基因共表达，我们展示了该方法的强大功能，以确定早期胚胎中的不同表达域；结果与使用激光消融确定的命运图谱惊人地相似。我们还使用聚类策略来寻找具有相似模式的基因，并开发了新的分析工具来检测共识模式、相邻非重叠模式和负相关模式内的变化。在研究的 1800 个基因中，只有一半具有先前分配的功能。已知基因提示了簇的发育作用，并且相关模式的识别预测了共同发生的生物功能的要求。
