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Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics

Single-cell whole-genome sequencing (WGS) is critical for characterizing dynamic intercellular changes in DNA. Current sample preparation technologies for single-cell WGS are complex, expensive, and suffer from high amplification bias and errors. Here, we describe Digital-WGS, a sample preparation p...

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Detalles Bibliográficos
Autores principales: Ruan, Qingyu, Ruan, Weidong, Lin, Xiaoye, Wang, Yang, Zou, Fenxiang, Zhou, Leiji, Zhu, Zhi, Yang, Chaoyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725457/
https://www.ncbi.nlm.nih.gov/pubmed/33298451
http://dx.doi.org/10.1126/sciadv.abd6454
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author Ruan, Qingyu
Ruan, Weidong
Lin, Xiaoye
Wang, Yang
Zou, Fenxiang
Zhou, Leiji
Zhu, Zhi
Yang, Chaoyong
author_facet Ruan, Qingyu
Ruan, Weidong
Lin, Xiaoye
Wang, Yang
Zou, Fenxiang
Zhou, Leiji
Zhu, Zhi
Yang, Chaoyong
author_sort Ruan, Qingyu
collection PubMed
description Single-cell whole-genome sequencing (WGS) is critical for characterizing dynamic intercellular changes in DNA. Current sample preparation technologies for single-cell WGS are complex, expensive, and suffer from high amplification bias and errors. Here, we describe Digital-WGS, a sample preparation platform that streamlines high-performance single-cell WGS with automatic processing based on digital microfluidics. Using the method, we provide high single-cell capture efficiency for any amount and types of cells by a wetted hydrodynamic structure. The digital control of droplets in a closed hydrophobic interface enables the complete removal of exogenous DNA, sufficient cell lysis, and lossless amplicon recovery, achieving the low coefficient of variation and high coverage at multiple scales. The single-cell genomic variations profiling performs the excellent detection of copy number variants with the smallest bin of 150 kb and single-nucleotide variants with allele dropout rate of 5.2%, holding great promise for broader applications of single-cell genomics.
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spelling pubmed-77254572020-12-16 Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics Ruan, Qingyu Ruan, Weidong Lin, Xiaoye Wang, Yang Zou, Fenxiang Zhou, Leiji Zhu, Zhi Yang, Chaoyong Sci Adv Research Articles Single-cell whole-genome sequencing (WGS) is critical for characterizing dynamic intercellular changes in DNA. Current sample preparation technologies for single-cell WGS are complex, expensive, and suffer from high amplification bias and errors. Here, we describe Digital-WGS, a sample preparation platform that streamlines high-performance single-cell WGS with automatic processing based on digital microfluidics. Using the method, we provide high single-cell capture efficiency for any amount and types of cells by a wetted hydrodynamic structure. The digital control of droplets in a closed hydrophobic interface enables the complete removal of exogenous DNA, sufficient cell lysis, and lossless amplicon recovery, achieving the low coefficient of variation and high coverage at multiple scales. The single-cell genomic variations profiling performs the excellent detection of copy number variants with the smallest bin of 150 kb and single-nucleotide variants with allele dropout rate of 5.2%, holding great promise for broader applications of single-cell genomics. American Association for the Advancement of Science 2020-12-09 /pmc/articles/PMC7725457/ /pubmed/33298451 http://dx.doi.org/10.1126/sciadv.abd6454 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Research Articles
Ruan, Qingyu
Ruan, Weidong
Lin, Xiaoye
Wang, Yang
Zou, Fenxiang
Zhou, Leiji
Zhu, Zhi
Yang, Chaoyong
Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics
title Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics
title_full Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics
title_fullStr Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics
title_full_unstemmed Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics
title_short Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics
title_sort digital-wgs: automated, highly efficient whole-genome sequencing of single cells by digital microfluidics
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725457/
https://www.ncbi.nlm.nih.gov/pubmed/33298451
http://dx.doi.org/10.1126/sciadv.abd6454
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