Bitbow Enables Highly Efficient Neuronal Lineage Tracing and Morphology Reconstruction in Single Drosophila Brains.

Identifying the cellular origins and mapping the dendritic and axonal arbors of neurons have been century old quests to understand the heterogeneity among these brain cells. Current Brainbow based transgenic animals take the advantage of multispectral labeling to differentiate neighboring cells or lineages, however, their applications are limited by the color capacity. To improve the analysis throughput, we designed Bitbow, a digital format of Brainbow which exponentially expands the color palette to provide tens of thousands of spectrally resolved unique labels. We generated transgenic Bitbow Drosophila lines, established statistical tools, and streamlined sample preparation, image processing, and data analysis pipelines to conveniently mapping neural lineages, studying neuronal morphology and revealing neural network patterns with unprecedented speed, scale, and resolution.

Identification of Neuronal Lineages in the Drosophila Peripheral Nervous System with a "Digital" Multi-spectral Lineage Tracing System.

Elucidating cell lineages provides crucial understanding of development. Recently developed sequencing-based techniques enhance the scale of lineage tracing but eliminate the spatial information offered by conventional approaches. Multi-spectral labeling techniques, such as Brainbow, have the potential to identify lineage-related cells in situ. Here, we report nuclear Bitbow (nBitbow), a "digital" version of Brainbow that greatly expands the color diversity for scoring cells, and a suite of statistical methods for quantifying the lineage relationship of any two cells. Applying these tools to the Drosophila peripheral nervous system (PNS), we determined lineage relationship between all neuronal pairs. This study demonstrates nBitbow as an efficient tool for in situ lineage mapping, and the complete lineage relationship among larval PNS neurons opens new possibilities for studying how neurons gain specific features and circuit connectivity.