Issue 14, 2023

Specific multiplexed detection of mRNA splice variants based on size-coding DNA probes and universal PCR amplification

Abstract

Alternative messenger RNA (mRNA) splicing is a vital regulatory process during the gene expression of higher eukaryotes. The specific and sensitive quantification of disease-related mRNA splice variants in biological and clinical samples is becoming particularly important. Reverse transcription polymerase chain reaction (RT-PCR), the most classical strategy for the assay of mRNA splice variants, cannot avoid false positive signals, which poses a challenge to the specificity of mRNA splice variant detection. In this paper, by rationally designing two DNA probes with double recognition at the splice site and different lengths, different mRNA splice variants could generate amplification products of unique lengths. Combined with capillary electrophoresis (CE) separation, the product peak of the corresponding mRNA splice variant can be specifically detected, which can avoid false-positive signals caused by non-specific amplification of PCR, greatly improving the specificity of the mRNA splice variant assay. In addition, universal PCR amplification eliminates amplification bias caused by different primer sequences and improves quantitative accuracy. Furthermore, the proposed method can simultaneously detect multiple mRNA splice variants as low as 100 aM in a one-tube reaction and has been successfully applied to the assay of variants in cell samples, which will provide a new strategy for mRNA splice variant-based clinical diagnosis and research.

Graphical abstract: Specific multiplexed detection of mRNA splice variants based on size-coding DNA probes and universal PCR amplification

Supplementary files

Article information

Article type
Paper
Submitted
17 Apr 2023
Accepted
05 Jun 2023
First published
06 Jun 2023

Analyst, 2023,148, 3341-3346

Specific multiplexed detection of mRNA splice variants based on size-coding DNA probes and universal PCR amplification

Y. Jia, H. Wang, H. Wang, F. Wang, K. Gao and Z. Li, Analyst, 2023, 148, 3341 DOI: 10.1039/D3AN00597F

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