Back to Search Start Over

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells

Authors :
Hyo-Jeong Jeon
Hye Hyeon Eum
Dae-Soon Son
Yeon Jeong Kim
Woosung Chung
Kyu-Tae Kim
Myung-Ju Ahn
Sangmin Kim
Woong-Yang Park
Kyung Yeon Han
Hong Kwan Kim
Hae-Ock Lee
Je-Gun Joung
Jeong Eon Lee
Areum Jo
Donghyun Park
Chang Eun Yoo
Hui-Sung Moon
Publication Year :
2018
Publisher :
Cold Spring Harbor Laboratory Press, 2018.

Abstract

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....84521d2636422c4c36ae6b4a9f1125d8