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Efficient Gene Expression Profiling Approach Developed for Transcriptomics

Oct 26, 2021

Scientists at the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences 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 on Sept. 12.
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.
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. 
Comparison of SiPAS with TruSeq. (Image by IGDB)
 
The performance of SiPAS on degrading RNA library. (Image by IGDB)
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LU Fei

Institute of Genetics and Developmental Biology

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Boosting the power of transcriptomics by developing an efficient gene expression profiling approach

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