Trace-n-Seq combines retrograde fluorescent tracing with sorting and single-cell sequencing of innervating peripheral neurons.

Authors

Vera Thiel, Manuel Mastel, Simon Renders, Jasper Panten, Katharina Bauer, Rene Jackstadt, Martin R Sprick, Andreas Trumpp

Published in

Nature protocols. Sep 21, 2026. Epub Sep 21, 2026.

Abstract

Neuronal innervation plays a pivotal role in controlling tissue function during homeostasis and regeneration, as well as in pathological contexts such as inflammation, autoimmune disorders, fibrosis and cancer. A major obstacle in understanding neuron-tissue interactions at the molecular level is that neuronal cell bodies reside in peripheral ganglia often far outside the organ of interest and are therefore typically excluded in common single-cell datasets of tissues. Here we developed Trace-n-Seq to address this issue-a method that combines retrograde tracing with fluorescence-activated cell sorting and single-cell sequencing to molecularly profile individual neurons innervating healthy or diseased tissues. Trace-n-Seq can be used to explore the specific gene expression signatures of peripheral neurons at single-cell resolution. The method utilizes retrograde axonal tracing using Fast Blue, ganglia dissociation and fluorescence-activated cell sorting followed by single-cell RNA sequencing to enable the isolation and transcriptomic analysis of ganglia. Unlike bulk or whole-ganglia single-cell RNA sequencing without retrograde labeling, Trace-n-Seq allows the characterization of organ-specific neurons with single-cell resolution, eliminating background from uninvolved neurons and unrelated cell types located in the same ganglion. The procedure allows researchers to obtain molecular transcriptomes of tissue-innervating neurons and to study their plasticity, subtype identity and potential interactions with the tissue microenvironment. The complete Trace-n-Seq workflow can be performed in 2 weeks and is suitable for researchers with experience in molecular biology, neuronal tissue handling, sequencing techniques and bioinformatic analysis.

PMID:
42768210
Bibliographic data and abstract were imported from PubMed on 22 Sep 2026.

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