UC Irvine UC Irvine Previously

Background: To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. Results: Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. Conclusion: The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks. Published: 21 December 2006 Genome Biology 2006, 7:R123 (doi:10.1186/gb-2006-7-12-r123) Received: 1 August 2006 Revised: 17 November 2006 Accepted: 21 December 2006 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2006/7/12/R123 Genome Biology 2006, 7:R123 R123.2 Genome Biology 2006, Volume 7, Issue 12, Article R123 Luengo Hendriks et al. http://genomebiology.com/2006/7/12/R123 Background Animal embryos can be thought of as dynamic three-dimensional arrays of cells expressing gene products in intricate spatial and temporal patterns that determine cellular differentiation and morphogenesis. Although developmental biologists most commonly analyze gene expression and morphology by visual inspection of photographic images, it has been increasingly recognized that a rigorous understanding of developmental processes requires automated methods that quantitatively record and analyze these phenomenally complex spatio-temporal patterns at cellular resolution. Different imaging and image analysis methods have been used to provide one-, two-, or three-dimensional descriptions of parts or all of a developing animal at various levels of detail (for example, [1-9]). Yet, none of these experiments have described the morphology and gene expression of a complete embryo at cellular resolution. The Berkeley Drosophila Transcription Network Project (BDTNP) [10] has initiated an interdisciplinary analysis of the transcription network in the early Drosophila embryo [11,12]. The project's goals are to develop techniques for deciphering the transcriptional regulatory information encoded in the genome and quantitatively model how regulatory interactions within the network generate spatial and temporal patterns of gene expression. Multiple system-wide datasets are being generated, including information on the in vivo and in vitro DNA binding specificities of the trans-acting factors that control the network. In this paper, we introduce a complementary dataset that describes the expression patterns of key transcription factors and a subset of their target genes in three dimensions for the whole embryo at cellular resolution, together with the methods we have developed to generate and analyze these data. By comparing the patterns of expression of the trans-regulators to those of their presumptive targets, we hope to provide evidence for the regulatory relationships within the network and allow modeling of how gene expression patterns develop. The Drosophila blastoderm was chosen as the model to study as it is one of the best characterized animal regulatory networks [13-16]. Two and a half hours after fertilization, the embryo is a syncytium of around 6,000 nuclei, which then become cellularized by an enveloping membrane during developmental stage 5 [17]. By the end of cellularization, the basic body plan is determined and the complex cell movements of gastrulation begin. A handful of maternal gene products are spatially patterned in the unfertilized egg in broad gradients along the dorsal/ventral (d/v) and the anterior/ posterior (a/p) axes. Zygotic transcription begins at around two hours after fertilization, with the maternal products initiating a hierarchical cascade of transcription factors that drive expression of increasing numbers of genes in more and more intricate patterns. The relatively small number of primary transcriptional regulators that initiate pattern formation (around 40) and the morphological simplicity of the early embryo make the blastoderm a particularly tractable system for modeling animal transcription networks, while capturing the complexities present in all animals. In this paper, we describe an integrated pipeline of methods for studying gene expression in the Drosophila melanogaster blastoderm and release our first set of spatial gene expression patterns digitized from 1,282 embryos. We show that our methods can detect many previously uncharacterized features of morphology and gene expression at a high level of accuracy. An accompanying paper describes further strategies necessary to study temporal changes in gene expression in the presence of dynamic morphology. Results and discussion A three-dimensional analysis pipeline To be able to analyze morphology and gene expression in three dimensions we developed an integrated suite of methods as follows (Figure 1; see Materials and methods). First, embryos were fixed and fluorescently stained to label the mRNA expression patterns of two genes and nuclear DNA, mounted on microscope slides, and visually examined to determine their developmental age. Second, labeled and staged embryos were imaged in whatever orientation they lay on the microscope slide using a two photon laser-scanning microscope to produce three-dimensional images. Third, raw three-dimensional images were converted by image analysis methods into text files, which we call 'PointClouds'. Each PointCloud describes the center of mass coordinates of all nuclei on the embryo surface and the mRNA or protein expression levels of two genes in and around each nucleus. These methods run unattended on large batches of images, processing three to four images per hour, per processor. Fourth, PointClouds were analyzed in three dimensions using a number of automatic and semi-automatic feature extraction methods to determine the orientation of the a/p and d/v axes, record morphological features, measure the locations of gene expression domains, and quantify relative levels of expression. Fifth, a BioImaging database (BID) was employed to track and manage the raw images and PointCloud data files and extensive metadata for each step of the pipeline. Sixth, two visualization tools were used to validate the image analysis methods (Segmentation Volume Renderer) [18], and to analyze the resulting PointClouds (PointCloudXplore) [10,19]. A critical feature of our strategy is that the large 0.3 to 0.5 Gb raw three-dimensional images for each embryo, such as that shown in Figure 2a-c, are reduced via image analysis to 1 Mb PointCloud files. The resulting PointClouds provide a compact representation of the image data and are readily amenable to computational analysis while maintaining the richness of the blastoderm's morphology and gene expression patterns. Figure 2 provides a qualitative illustration of this, comparing renderings of a part of a three-dimesnional raw image Genome Biology 2006, 7:R123 http://genomebiology.com/2006/7/12/R123 Genome Biology 2006, Volume 7, Issue 12, Article R123 Luengo Hendriks et al. R123.3