bioRxivBioengineering
Linked optical and gene expression profiling of single cells at high throughput
J. Q. Zhang, C. A. Siltanen, L. Liu, K.-C. Chang, Z. J. Gartner, A. R. Abate
Abstract
Single cell RNA sequencing has emerged as a powerful tool for characterizing cells, but not all phenotypes of interest can be observed through gene expression alone. Linking sequencing with optical analysis has provided insight into the molecular basis behind cellular function, but current approaches have limited throughput. Here, we present a high throughput platform for linked optical and gene expression profiling of single cells. We demonstrate accurate fluorescence and gene expression measurements from thousands of cells in a single experiment and use the platform to characterize DNA and RNA changes in Jurkat cells through the cell cycle. In addition to its scalability, our integration of microfluidics and array-based molecular biology holds promise for comprehensive multi-omics profiling of single cells.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- μCB-seq: Microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells
T. N. Chen, A. N. Gupta, … A. Streets·bioRxiv·Feb 18, 2020
- Linking single-cell measurements of mass, growth rate, and gene expression
R. J. Kimmerling, S. M. Prakadan, … S. R. Manalis·bioRxiv·Jun 7, 2018
- Single-cell phenomics through integrated imaging and molecular profiling
Johannes Bues, Joern Pezoldt, … Bart Deplancke·bioRxiv·Nov 28, 2025
- Integrating single-cell RNA-seq and imaging with SCOPE-seq2
Zhouzerui Liu, Jinzhou Yuan, … Peter A. Sims·Scientific ReportsPeer-reviewed·Nov 10, 2020
- Ultra-high throughput single-cell RNA sequencing by combinatorial fluidic indexing
Paul Datlinger, André F. Rendeiro, … Christoph Bock·Nature MethodsPeer-reviewed·May 31, 2021
- High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution
Dennis J. Eastburn, Kevin S. White, … Bruce E. Seligmann·Scientific ReportsPeer-reviewed·Dec 28, 2024