Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues

Abstract Background 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. Results Here, we present a highly sensitive library construction protocol for ultralow input R...

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Autores principales:	Erteng Jia, Huajuan Shi, Ying Wang, Ying Zhou, Zhiyu Liu, Min Pan, Yunfei Bai, Xiangwei Zhao, Qinyu Ge
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	scRNA-seq Sensitivity Template-switching oligos terminal modification Low abundance gene detection Subcellular Biotechnology TP248.13-248.65 Genetics QH426-470
Acceso en línea:	https://doaj.org/article/b0be696efd3f4fac88cee77b65386bc1
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spelling	oai:doaj.org-article:b0be696efd3f4fac88cee77b65386bc12021-11-14T12:26:48ZOptimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues10.1186/s12864-021-08132-w1471-2164https://doaj.org/article/b0be696efd3f4fac88cee77b65386bc12021-11-01T00:00:00Zhttps://doi.org/10.1186/s12864-021-08132-whttps://doaj.org/toc/1471-2164Abstract Background 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. Results 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. Conclusions 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.Erteng JiaHuajuan ShiYing WangYing ZhouZhiyu LiuMin PanYunfei BaiXiangwei ZhaoQinyu GeBMCarticlescRNA-seqSensitivityTemplate-switching oligos terminal modificationLow abundance gene detectionSubcellularBiotechnologyTP248.13-248.65GeneticsQH426-470ENBMC Genomics, Vol 22, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	scRNA-seq Sensitivity Template-switching oligos terminal modification Low abundance gene detection Subcellular Biotechnology TP248.13-248.65 Genetics QH426-470
spellingShingle	scRNA-seq Sensitivity Template-switching oligos terminal modification Low abundance gene detection Subcellular Biotechnology TP248.13-248.65 Genetics QH426-470 Erteng Jia Huajuan Shi Ying Wang Ying Zhou Zhiyu Liu Min Pan Yunfei Bai Xiangwei Zhao Qinyu Ge Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues
description	Abstract Background 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. Results 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. Conclusions 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.
format	article
author	Erteng Jia Huajuan Shi Ying Wang Ying Zhou Zhiyu Liu Min Pan Yunfei Bai Xiangwei Zhao Qinyu Ge
author_facet	Erteng Jia Huajuan Shi Ying Wang Ying Zhou Zhiyu Liu Min Pan Yunfei Bai Xiangwei Zhao Qinyu Ge
author_sort	Erteng Jia
title	Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues
title_short	Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues
title_full	Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues
title_fullStr	Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues
title_full_unstemmed	Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues
title_sort	optimization of library preparation based on smart for ultralow rna-seq in mice brain tissues
publisher	BMC
publishDate	2021
url	https://doaj.org/article/b0be696efd3f4fac88cee77b65386bc1
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Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues

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