Reconstruction of the dynamics of drosophila genes expression from sets of images sharing a common pattern

• Authors: Alexander V. Spirov;Alexander B. Kazansky;Dmitry L. Timakin;John Reinitz
• Venue: Real-Time Imaging - Special issue: Imaging in bioinformatics part II
• Year: 2002

Like all other insects, the body of the fruit fly Drosophila melanogaster is made up of repeated units called segments. At the early developmental stages prior to morphological differentiation, the segments are marked out by a chemical blueprint at cellular resolution. This blueprint is formed by the early patterns of segmentation gene expression, which become more spatially resolved over time. The precise characterization of this pattern and its temporal changes is of considerable biological significance. Such characterization faces a twofold technical barrier. First, although we are interested in the time course of expression, segmentation gene expression can only be visualized in fixed tissue and so the time course must be reconstructed from many embryos, each at a slightly different point in development. Second, available confocal microscopes can image only three gene products at once. We overcome this barrier by using data retrieved from a large number of scanned embryos which have been placed in temporal equivalence classes. Each embryo was scanned for the expression patterns of three genes. These three patterns vary from embryo to embryo because of individual differences and cannot be directly superimposed. However, if each embryo is stained for one common gene product and for two others, which vary among the dataset, it is possible to make some coordinate transformations of every embryo image so that the expression domains of the common gene will maximally coincide. To find these coordinate transformations is to solve the registration problem.We present a set of methods to reconstruct the dynamics of gene expression patterns from sets of images sharing a common pattern. For this purpose, we applied modern heuristic methods of optimization to find the elastic deformation necessary for image registration. We used the standard Genetic Algorithms technique by itself and in combination with the simplex method. By this approach, it is possible to retrace the detailed dynamics of developmental gene activity at the resolution on the level of individual nuclei for each of 4-6 thousand cells composing early fly embryo. The final result of this analysis will be the quantitative atlas of Drosophila genes expression (http://www.iephb.nw.ru/~spirov/atlas).