Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues.
IF: 4.547
Cited by: 1


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. Here, we present a highly sensitive library construction protocol for ultralow input RNA sequencing (ulRNA-seq). We 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. 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. We expect that ulRNA-seq will sequence and transcriptome characterization for the subcellular of disease tissue, to find the corresponding treatment plan.


Gene Expression
Spatial Transcriptomics
Low abundance gene detection
Template-switching oligos terminal modification

MeSH terms

Gene Expression Profiling
Gene Library
High-Throughput Nucleotide Sequencing
Sequence Analysis, RNA
Single-Cell Analysis


Jia, Erteng
Shi, Huajuan
Wang, Ying
Zhou, Ying
Liu, Zhiyu
Pan, Min
Bai, Yunfei
Zhao, Xiangwei
Ge, Qinyu

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