QuantAS: a comprehensive pipeline to study alternative splicing by absolute quantification of splice isoforms

Abstract

Alternative splicing (AS) is a mechanism by which cells generate abundant protein diversity from a limited number of genes (Baralle & Giudice, 2017). AS plays a crucial role in regulating various life activities such as growth, development, and aging in plants (Zhu et al., 2017; Godoy Herz & Kornblihtt, 2019; Jabre et al., 2019; Chen et al., 2020; Reddy et al., 2020; Zhang et al., 2020), where it greatly influences plant growth, development, and response to biotic and abiotic stresses (Motion et al., 2015; Laloum et al., 2018; Chaudhary et al., 2019; Chen et al., 2021; Ganie & Reddy, 2021; Saini et al., 2021; Zhu et al., 2023; Supporting Information Fig. S1). The traditional method for the identification of AS is semi-quantitative RT-PCR, which is easy to perform (Palusa et al., 2007; Li et al., 2020; Riegler et al., 2021; Han et al., 2022). Quantitative PCR (qPCR) is also widely used in AS research, as it enables real-time monitoring of fluorescence signals and accurate quantification of isoform copy numbers through the use of specific primers (Hefti et al., 2018; Liu et al., 2018; Huang et al., 2021). With the emergence of digital PCR (dPCR), the identification methods of AS have become more diversified, which disperses each single target fragment into separate droplets as much as possible through the calculation of positive droplets (Fig. S2; Gao et al., 2021).

Based on the urgent need for the accurate quantification of various isoforms, an AS detection method called QuantAS was established (Fig. 1), which allows us to accurately quantify all isoforms of genes based on absolute quantification technology and specific primer design. The method utilizes isoform-specific primers to overcome the isoform identification difficulty caused by different AS events and is designed by using the functional coding region as the isoform structure classification unit to ensure isoform independence (Fig. 2a). RT-qPCR enables real-time monitoring of changes in the fluorescence signal, quantification of differences between expression levels, and simultaneous detection of multiple in a single reaction. According to the copy number of different isoforms, isoform expression patterns can be identified by combining with absolute quantitative techniques. This method greatly increases the accuracy of identification and reduces the cost of repeated experiments. Furthermore, the absolute quantification of AS isoforms employing the combination of qPCR and dPCR could provide their respective advantages, thus rapidly obtaining all isoform information of the potential functional genes to be investigated.

QuantAS consists of three stages: (1) gene structure assembly and specific primer design, including AS event analysis; (2) accurate quantitative analysis of the isoforms in the treated samples using qPCR and dPCR to obtain the copy number of each isoform; and (3) absolute quantification, which involves data analysis to explore the existence and levels of isoforms (the outline of the protocol for QuantAS is shown in detail in Figs 1, S3).

In conclusion, QuantAS offers a universal method for the detection and quantification of isoforms in plants, allowing isoforms to be reclassified for different functional protein-coding regions and for precise AS identification to determine AS event types. QuantAS is also able to detect multiple isoforms simultaneously in a single reaction, thus decreasing the redundant identification and calculating the copy number of the complicated isoform according to MLE. Coupled with qPCR and dPCR techniques, it will allow rapid and precise screening of isoform changes that participate in physiological responses. The straightforward experimental design and procedures make QuantAS a valuable addition to the current tool chest for the study of AS, especially in the validation of splicing events identified in large-scale omics data.

None declared.

Y-CS wrote the manuscript and performed the experiments. M-XC and K-LZ performed the data analysis. ASNR and F-LC provided a critical review of the manuscript. F-YZ generally supervised the research group and designed the research.