A Quantitative Spatiotemporal Atlas of Gene Expression in the Drosophila Blastoderm

Abstract

To fully understand animal transcription networks, it is essential to accurately measure the spatial and temporal expression patterns of transcription factors and their targets. We describe a registration technique that takes image-based data from hundreds of Drosophila blastoderm embryos, each costained for a reference gene and one of a set of genes of interest, and builds a model VirtualEmbryo. This model captures in a common framework the average expression patterns for many genes in spite of significant variation in morphology and expression between individual embryos. We establish the method's accuracy by showing that relationships between a pair of genes' expression inferred from the model are nearly identical to those measured in embryos costained for the pair. We present a VirtualEmbryo containing data for 95 genes at six time cohorts. We show that known gene-regulatory interactions can be automatically recovered from this data set and predict hundreds of new interactions.

Assembling models of embryo development: Image analysis and the construction of digital atlases

“…The fruit fly Drosophila melanogaster has been extensively studied in the field of genetics and developmental biology (Fowlkes et al, 2008;Frise et al, 2010;Peng et al, 2011). Sixty percent of so called genetic diseases in humans have their counterpart in the Drosophila genome.…”

“…At early developmental stages, the whole organism is more easily amenable to in toto imaging with resolution at the single cell level, Figure 2D, E (Fowlkes et al, 2008;Castro et al, 2009;Long etal., 2009).…”

“…The use of an average template (Fig. 2G) is widely spread (Rex et al, 2003;Fowlkes et al, 2008;Peng et al, 2011). Ma et al (2005) constructed a "minimal deformation average template" as an idealized specimen minimizing the deformation required to fit any specimen of the cohort.…”

“…Although the three different methods yielded correlated measurements across different individuals, the relevance of the obtained quantitative measurements to compare different specimens is questionable and this issue remains a challenge. Current efforts to achieve the quantitative comparison of gene expression levels in different individuals include the minimization of variability within a population (Fowlkes et al, 2008) and the conversion of fluorescence signal into fluorescent proteins number in transgenic specimens (Damle etal.,2006).…”

“…These transformations are local and nonlinear and typically produce an alteration of the data shapes and volumes. Peng et al (2011) developed an automatic pattern recognition system to identify and match visual anatomic references with certain geometric properties such as high local curvature, and Fowlkes et al (2008) ereated a method to unequivocally identify the cell to cell correspondence in C. elegans embryos.…”