ulRNA-seq – a library construction scheme for high sensitivity and low abundance gene detection in subcellular or ultralow RNA sequencing

Single-cell RNA sequencing (scRNA-seq) provides new insights to address biological and medical questions, and it will benefit more from the ultralow input RNA or subcellular sequencing.

Researchers at Southeast University, Nanjing have developed a highly sensitive library construction protocol for ultralow input RNA sequencing (ulRNA-seq). The researchers systematically evaluate experimental conditions of this protocol, such as reverse transcriptase, template-switching oligos (TSO), and template RNA structure. It was found that Maxima H Minus reverse transcriptase and rN modified TSO, as well as all RNA templates capped with m7G improved the sequencing sensitivity and low abundance gene detection ability. RNA-seq libraries were successfully prepared from total RNA samples as low as 0.5 pg, and more than 2000 genes have been identified.

Validation of ulRNA-seq protocol using single-cell micro-region

Fig. 8

A The number of genes detected Smart-seq2 and ulRNA-seq protocol. B The number of genes detected in different expression levels binned by standardized expression FPKM in single-cell. C The ratio of the detected genes in the cell marker gene database of mice. D Sensitivity for detecting genes in single-cell. E Precision for detecting genes in single-cell. F Heatmap showing person correlation between the five replicates

The ability of low abundance gene detection and sensitivity were largely enhanced with this optimized protocol. It was also confirmed in single-cell sequencing, that more genes and cell markers were identified compared to conventional sequencing method. The researchers expect that ulRNA-seq will sequence and transcriptome characterization for the subcellular of disease tissue, to find the corresponding treatment plan.

Jia E, Shi H, Wang Y, Zhou Y, Liu Z, Pan M, Bai Y, Zhao X, Ge Q. (2021) Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues. BMC Genomics 22(1):809. [article]

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