The study, published October 10 in the journal Nature Methods, potentially broadens the depth and scope of investigations possible on tissue samples, according to researchers from the Wyss Institute for Biologically Inspired Engineering at Harvard.

Researchers sometimes observe rare cell types. To delve deeper, they developed ways to access cells' gene expression patterns (transcriptomes) by analyzing the gene-derived RNA molecules present within them, which are then matched with cells' shapes, spatial positions, and molecular biomarkers.

However, this "spatial transcriptomics" approach only captures a fraction of a cell's total RNA molecules and lacks the analysis quality provided by costly single-cell sequencing methods --which prevent researchers from revisiting samples.

Harvard researchers overcame these limitations with Light-Seq, a DNA nanotechnology-driven method. Specifically, Light-Seq allows researchers to geotag RNA sequences with unique DNA barcodes exclusive to a few target cells of interest via a rapid photo‐crosslinking process.

Light-Seq enabled the isolation of the full transcriptome of "dopaminergic amacrine cell" (DAC), a rare cell type involved in regulating the eye's circadian rhythm, by retrieving only four to eight individually barcoded cells per cross-section. DACs are hard to isolate because of their intricate connections to other retina cells, which were differently barcoded using Light-Seq.

Following Light-Seq's success in cultured cells, the researchers applied Light-Seq to cross-sections of the mouse retina and profiled three major layers with different functions. They found thousands of enriched RNAs between the retina's three major layers. Following sequence extraction, the tissue samples remained intact for follow-up analysis.

"Going forward, we're very interested in using Light-Seq to better understand the interplay between the immune system, disease-propagating cells, and different therapeutic strategies such as gene and cell therapy," said co-first author Jocelyn Kishi, PhD, who is pursuing a path toward Light-Seq commercialization.

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