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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7725457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
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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