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EASI-PASS: An accessible pipeline for linking functional imaging and mRNA profiling

Created on 27 Aug 2026

Authors

Singh Alvarado, J., Massengill, C. I., Stern, J., Amsalem, O., Ventura, B. F., Jang, A., Cook, S., Veliche, A., Sunkavalli, P., Patel, D., Colaccino, J., Evans, K. E., Wang, Y., Andermann, M. L.

Abstract

We developed EASI-PASS, a reliable, high-throughput method for estimating the molecular identity of functionally characterized cells by merging live imaging with subsequent fixed-tissue imaging using conventional microscopes. Our method matches the shapes and locations of thousands of densely imaged cells between large (>1 mm2) functional images and a thick, expanded, and cleared EASI-FISH tissue volume to assess gene expression. This approach is more efficient than alignment to thin sections and recovers the molecular identity of ~78% of cells. In acute brain slice imaging from the mouse parabrachial nucleus during optogenetic stimulation of long-range spinal inputs, we observed fine-scale specificity in the molecular identity of spinorecipient neurons. In the awake mouse visual cortex, we observed distinct arousal modulation and spatial falloff in correlations within and across interneuron classes. Thus, EASI-PASS provides reliable and efficient alignment of cellular activity with molecular identity.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 27 Aug 2026.

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