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Opto-combinatorial indexing enables high-content transcriptomics by linking cell images and transcriptome

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP465912
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We introduce a simple integrated analysis method that links cellular phenotypic behaviour with single-cell RNA sequencing (scRNA-seq) by utilizing a combination of optical indices from cells and hydrogel beads. Our method achieves the link reading-out of the combinations, referred to as joint colour codes via matching the optical combinations measured by the conventional epi-fluorescence microscopy with the concatenated DNA molecular barcodes created by the cell-hydrogel bead pairs and sequenced by next-generation sequencing. We validated our approach by demonstrating an accurate link between the cell image and scRNA-seq with mixed species experiments, the longitudinal cell tagging by electroporation and lipofection, and gene expression analysis. Furthermore, we extended our approach to multiplexed chemical transcriptomics, which enables us to identify distinct phenotypic behaviours in HeLa cells under various paclitaxel burdens, and uncover corresponding gene regulations associated with the formation of a multipolar spindle.
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2023-10-12
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