Preparation of Drosophila embryos for quantitative imaging of gene expression.

Quantitative measurements derived using sophisticated microscopy techniques are essential for understanding the basic principles that control the behavior of biological systems. We have developed a five-step data pipeline to extract quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. This protocol describes the preparation of Drosophila embryos for imaging by confocal microscopy. Embryos are collected at the appropriate developmental stage and fixed. They are then stained with both primary antibodies and secondary antibodies conjugated with fluorophores to reveal the segmentation gene expression patterns.

Quantitative imaging of gene expression in Drosophila embryos.

Quantitative measurements derived using sophisticated microscopy techniques are essential for understanding the basic principles that control the behavior of biological systems. Here we describe a data pipeline developed to extract quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. The pipeline consists of image segmentation, background removal, temporal characterization of an embryo, data registration, and data averaging. This pipeline has been successfully applied to obtain quantitative gene expression data at cellular resolution in space and at 6.5-min resolution in time. It has also enabled the construction of a spatiotemporal atlas of segmentation gene expression. We describe the software used to construct a workflow for extracting quantitative data on segmentation gene expression and the BREReA package, which implements the methods for background removal and registration of segmentation gene expression patterns.

A regression system for estimation of errors introduced by confocal imaging into gene expression data in situ.

BACKGROUND: Accuracy of the data extracted from two-dimensional confocal images is limited due to experimental errors that arise in course of confocal scanning. The common way to reduce the noise in images is sequential scanning of the same specimen several times with the subsequent averaging of multiple frames. Attempts to increase the dynamical range of an image by setting too high values of microscope PMT parameters may cause clipping of single frames and introduce errors into the data extracted from the averaged images. For the estimation and correction of this kind of errors a method based on censoring technique (Myasnikova et al., 2009) is used. However, the method requires the availability of all the confocal scans along with the averaged image, which is normally not provided by the standard scanning procedure. RESULTS: To predict error size in the data extracted from the averaged image we developed a regression system. The system is trained on the learning sample composed of images obtained from three different microscopes at different combinations of PMT parameters, and for each image all the scans are saved. The system demonstrates high prediction accuracy and was applied for correction of errors in the data on segmentation gene expression in Drosophila blastoderm stored in the FlyEx database (http://urchin.spbcas.ru/flyex/, http://flyex.uchicago.edu/flyex/). The prediction method is realized as a software tool CorrectPattern freely available at http://urchin.spbcas.ru/asp/2011/emm/. CONCLUSIONS: We created a regression system and software to predict the magnitude of errors in the data obtained from a confocal image based on information about microscope parameters used for the image acquisition. An important advantage of the developed prediction system is the possibility to accurately correct the errors in data obtained from strongly clipped images, thereby allowing to obtain images of the higher dynamical range and thus to extract more detailed quantitative information from them.

FlyEx, the quantitative atlas on segmentation gene expression at cellular resolution.

The datasets on gene expression are the valuable source of information about the functional state of an organism. Recently, we have acquired the large dataset on expression of segmentation genes in the Drosophila blastoderm. To provide efficient access to the data, we have developed the FlyEx database (http://urchin.spbcas.ru/flyex). FlyEx contains 4716 images of 14 segmentation gene expression patterns obtained from 1579 embryos and 9,500,000 quantitative data records. Reference data are available for all segmentation genes in cycles 11-13 and all temporal classes of cycle 14A. FlyEx supports operations on images of gene expression patterns. The database can be used to examine the quality of data, analyze the dynamics of formation of segmentation gene expression domains, as well as to estimate the variability of gene expression patterns. Currently, a user is able to monitor and analyze the dynamics of formation of segmentation gene expression domains over the whole period of segment determination, that amounts to 1.5 h of development. FlyEx supports the data downloads and construction of personal reference datasets, that makes it possible to more effectively use and analyze data.

A database for management of gene expression data in situ.

MOTIVATION: To create a spatiotemporal atlas of Drosophila segmentation gene expression at cellular resolution. RESULTS: The expression of segmentation genes plays a crucial role in the establishment of the Drosophila body plan. Using the IBM DB2 Relational Database Management System we have designed and implemented the FlyEx database. FlyEx contains 2832 images of 14 segmentation gene expression patterns obtained from 954 embryos and 2,073,662 quantitative data records. The averaged data is available for most of segmentation genes at eight time points. FlyEx supports operations on images of gene expression patterns. The database can be used to examine the quality of data, analyze the dynamics of formation of segmentation gene expression domains, as well as estimate the variability of gene expression patterns. We also provide the capability to download data of interest. AVAILABILITY: http://urchin.spbcas.ru/flyex, http://flyex.ams.sunysb.edu/flyex

A method for two-dimensional registration and construction of the two-dimensional atlas of gene expression patterns in situ.

We apply the fast redundant dyadic wavelet transform to the spatial registration of two-dimensional gene expression patterns of 736 Drosophila melanogaster embryos. This method is superior to the Fourier transform or windowed Fourier transform because of its ability to reduce noise and is of high resolution. In registration of the dataset we use two cost functions based on computing the Euclidean or Mahalanobis distance. The algorithm shows a high level of accuracy. For early temporal classes the cost function based on Mahalanobis distance gives better results. We have reported a method for construction of an integrated dataset elsewhere. In this paper the method is extended to the two-dimensional case. The procedure for data assembly provides for the preservation of some aspects of the nuclear structure of a two-dimensional gene expression pattern. It is based on creating an averaged model that reproduces the spatial distribution of nuclei over the embryo image. The average concentrations of each protein in each averaged nucleus are computed from the series of embryos of the same age.