SiPAS – boosting the power of transcriptomics

Scientists at the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences have developed a simplified and highly efficient 3’RNA-seq method, called Simplified Poly(A) Anchored Sequencing (SiPAS), to boost population transcriptomics in plants. The study was recently published in Plant Biotechnology Journal.

RNA sequencing (RNA-seq) is a keystone technology for modern biological research, shifting many genomic studies from a solely genomic level to a multi-omic level and thus effectively improving our understanding of genome biology. Over the last a few years, vast amounts of genomic data have been generated in many plant species. The gigantic size of genomic data is creating a vacuum where a large quantity of transcriptomic data needs to be filled to help decode the function of the genome. Highly efficient RNA-seq technologies are increasingly demanded in biological research.

The emergence of 3’RNA-seq is a giant leap of RNA-seq technologies. Active methodological development has been made to the 3’RNA-seq technology. However, these 3’RNA-seq methods usually use custom sequencing format and have not been sufficiently optimized for the standard paired-end 150/250 bp (PE150 or PE250) sequencing. This hinders their application in large-scale population transcriptomic study.

In this study, WANG Jing, XU Jun and YANG Xiaohan et al. in LU Fei’s research group developed an efficient gene expression profiling approach, SiPAS, by combining the advantages of reported 3’RNA-seq methods and optimizing the use of standard PE150 sequencing format.

The design of SiPAS

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(a) Framework workflow of SiPAS. For step 1, cell lysis in single tube is performed to break down the cell wall completely. For steps of 2 and 3, lysate is transferred into 96-well plates, followed by total RNA extraction, as well as barcoding and reverse transcription of total RNA using designed primers. For steps of 4–8, samples in one plate are pooled for second-strand synthesis, purifying cDNA, size selection, and PCR amplification for sequencing. (b) Optimization design of SiPAS. Four protocol tests (T1, T2, T3 and T4) were designed to assess the effect of switching adapters and using UMIs. In T1, barcodes are ligated to P5 adapter and UMIs are not used. In T2, barcodes are ligated to P7 adapter and UMIs are not used. In T3, barcodes are ligated to P5 adapter and UMIs are used. The optimal design of SiPAS can be obtained through the comparison of the four tests. In Illumina paired-end sequencing, R1 are reads with P5 adapter and R2 are reads with P7 adapter.

Through testing SiPAS for its performance in bread wheat, they presented evidence showing that SiPAS achieves a high level of sensitivity, accuracy, and reproducibility.

According to the researchers, the improved 3’RNA-seq method SiPAS provides multiple strengths to advance population transcriptomic studies in plants. It is effortless and cost-effective with the simplified workflow. In addition, it is highly effective in quantifying gene expression and it is robust to RNA degradation.

Overall, with the strengths of being cost-effective and laborsaving, and equivalent performance with TruSeq, SiPAS promises the ease of use of this method in large-scale population transcriptomic studies. It is anticipated that SiPAS will be used in many species and contribute to an in-depth understanding of plant genomes.

The performance of SiPAS on degrading RNA library. (Image by IGDB)

SourceThe Chinese Academy of Sciences

Wang J, Xu J, Yang X, Xu S, Zhang M, Lu F. (2021) Boosting the power of transcriptomics by developing an efficient gene expression profiling approach. Plant Biotechnol J [Epub ahead of print]. [article]

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