Goodwin, Daniel R, Vaughan, Alex, Leible, Daniel, Alon, Shahar, Henry, Gilbert L, Cheng, Anne, Chen, Xiaoyin, Zhang, Ruihan, Xue, Andrew G, Wassie, Asmamaw T, Sinha, Anubhav, Bando, Yosuke, Kajita, Atsushi, Marblestone, Adam H, Zador, Anthony M, Boyden, Edward S, Church, George M, Kohman, Richie E (July 2022) Expansion Sequencing of RNA Barcoded Neurons in the Mammalian Brain: Progress and Implications for Molecularly Annotated Connectomics. bioRxiv. (Submitted)
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Abstract
Mapping and molecularly annotating mammalian neural circuits is challenging due to the inability to uniquely label cells while also resolving subcellular features such as synaptic proteins or fine cellular processes. We argue that an ideal technology for connectomics would have the following characteristics: the capacity for robust distance-independent labeling, synaptic resolution, molecular interrogation, and scalable computational methods. The recent development of high-diversity cellular barcoding with RNA has provided a way to overcome the labeling limitations associated with spectral dyes, however performing all-optical circuit mapping has not been demonstrated because no method exists to image barcodes throughout cells at synaptic-resolution. Here we show ExBarSeq, an integrated method combining in situ sequencing of RNA barcodes, immunostaining, and Expansion Microscopy coupled with an end-to-end software pipeline that automatically extracts barcode identities from large imaging datasets without data processing bottlenecks. As a proof of concept, we applied ExBarSeq to thick tissue sections from mice virally infected with MAPseq viral vectors and demonstrated the extraction of 50 barcoded cells in the visual cortex as well as cell morphologies uncovered via immunostaining. The current work demonstrates high resolution multiplexing of exogenous barcodes and endogenous synaptic proteins and outlines a roadmap for molecularly annotated connectomics at a brain-wide scale.
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