Single-cell protein-mRNA correlation analysis enabled by multiplexed dual-analyte co-detection

Haibiao Gong,Aik Ooi,Gang Sun,Chad Sanada,Ramesh Ramakrishnan,Gajalakshmi Dakshinamoorthy,Xiaohui Wang,Ilona Holcomb,Stephane Boutet,Benjamin Liu

doi:10.1038/s41598-017-03057-5

Haibiao Gong, Aik Ooi + Show 8 more

Open Access

https://doi.org/10.1038/s41598-017-03057-5

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Journal: Scientific Reports	Publication Date: Jun 5, 2017
Citations: 24	License type: open-access

Affiliation: Fluidigm (United States)

Abstract

We have investigated the correlation between proteins and mRNAs in single cells employing an integrated workflow for dual-analyte co-detection. This is achieved by combining the oligo extension reaction (OER), which converts protein levels to DNA levels, with reverse transcription for mRNA detection. Unsupervised gene expression profiling analysis, including principal component analysis and hierarchical clustering, revealed different aspects of the protein-mRNA relationship. Violin plot analysis showed that some genes exhibited similar distribution patterns for proteins and mRNAs. We also demonstrate that cells can be separated into subpopulations based on their protein-mRNA expression profiles, and that different subpopulations have distinct correlation coefficient values. Our results demonstrated that integrated investigations of mRNA and protein levels in single cells allows comprehensive analysis not attainable at bulk levels.

Highlights

The ability to measure gene expression at single-cell resolution is of increasing importance, in particular for cancer genomics, where cell-to-cell heterogeneity is an intrinsic feature[1]
Protein and mRNA levels are converted to DNA levels by oligo extension reaction (OER) and reverse transcription, respectively
Gene expression analysis at the protein and mRNA levels has been an essential tool for investigating intrinsic genomic programs and cellular responses to stimuli, leading to the construction of complex signaling pathways

Summary

Introduction

The ability to measure gene expression at single-cell resolution is of increasing importance, in particular for cancer genomics, where cell-to-cell heterogeneity is an intrinsic feature[1]. Integrated co-detection of proteins and mRNAs from the same cell has the potential to reveal the correlation between these two classes of biologically important molecules, but to help understand the mechanisms of gene regulation, at both the transcriptional and translational levels. To simplify workflow and reduce variability, a method that combines the protein and mRNA detection in a single reaction has been reported[16], a systematic analysis of the interrelationship between protein and RNA expression remains unexplored.

Results

Conclusion