Single-cell Resolution View of the Transcriptional Landscape of Developing Drosophila Eye

Faithful and reliable quantification of gene expression at a single-cell level is an outstanding challenge in developmental biology. Most existing approaches face a trade-off between the signal to noise ratio, resolution, and sensitivity. Here, we present a novel approach for in situ quantification of gene expression in a developing tissue. Our pipeline combines computational prediction of transcription factor targets, gene tagging, fluorescent reporter imaging, state-of-the-art image analysis, and automated cell-type identification. By applying this approach to identify the sequence of quantitative changes in gene expression which govern the development of the Drosophila neural retina, we demonstrate the feasibility of our method. We analyze the targets of Atonal (Ato), a transcription factor that controls the transition from eye disc progenitor cell to photoreceptor neurons. We utilized recombineering and genomic engineering to tag all predicted Ato targets with novel transcriptional reporters. These reporters enable following the expression of both regulator and regulated genes to accurately quantify their expression levels in individual cells. Our complete computational pipeline identifies nuclei in the eye discs and detects different states of cells as they progress through differentiation. Based on detailed gene expression analysis, our technique revealed genes likely to be direct Ato targets and provided insight into how gene expression changes drive the specification of photoreceptors.