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Ultra-precise detection of mutations by droplet-based amplification of circularized DNA

BACKGROUND: NGS (next generation sequencing) has been widely used in studies of biological processes, ranging from microbial evolution to cancer genomics. However, the error rate of NGS (0.1 % ~ 1 %) is still remaining a great challenge for comprehensively investigating the low frequency variations,...

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Autores principales: Wang, Kaile, Ma, Qin, Jiang, Lan, Lai, Shujuan, Lu, Xuemei, Hou, Yali, Wu, Chung-I, Ruan, Jue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4784281/
https://www.ncbi.nlm.nih.gov/pubmed/26960407
http://dx.doi.org/10.1186/s12864-016-2480-1
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author Wang, Kaile
Ma, Qin
Jiang, Lan
Lai, Shujuan
Lu, Xuemei
Hou, Yali
Wu, Chung-I
Ruan, Jue
author_facet Wang, Kaile
Ma, Qin
Jiang, Lan
Lai, Shujuan
Lu, Xuemei
Hou, Yali
Wu, Chung-I
Ruan, Jue
author_sort Wang, Kaile
collection PubMed
description BACKGROUND: NGS (next generation sequencing) has been widely used in studies of biological processes, ranging from microbial evolution to cancer genomics. However, the error rate of NGS (0.1 % ~ 1 %) is still remaining a great challenge for comprehensively investigating the low frequency variations, and the current solution methods have suffered severe amplification bias or low efficiency. RESULTS: We creatively developed Droplet-CirSeq for relatively efficient, low-bias and ultra-sensitive identification of variations by combining millions of picoliter uniform-sized droplets with Cir-seq. Droplet-CirSeq is entitled with an incredibly low error rate of 3 ~ 5 X 10(-6). To systematically evaluate the performances of amplification uniformity and capability of mutation identification for Droplet-CirSeq, we took the mixtures of two E. coli strains as specific instances to simulate the circumstances of mutations with different frequencies. Compared with Cir-seq, the coefficient of variance of read depth for Droplet-CirSeq was 10 times less (p = 2.6 X 10(-3)), and the identified allele frequency presented more concentrated to the authentic frequency of mixtures (p = 4.8 X 10(-3)), illustrating a significant improvement of amplification bias and accuracy in allele frequency determination. Additionally, Droplet-CirSeq detected 2.5 times genuine SNPs (p < 0.001), achieved a 2.8 times lower false positive rate (p < 0.05) and a 1.5 times lower false negative rate (p < 0.001), in the case of a 3 pg DNA input. Intriguingly, the false positive sites predominantly represented in two types of base substitutions (G- > A, C- > T). Our findings indicated that 30 pg DNA input accommodated in 5 ~ 10 million droplets resulted in maximal detection of authentic mutations compared to 3 pg (p = 1.2 X 10(-8)) and 300 pg input (p = 2.2 X 10(-3)). CONCLUSIONS: We developed a method namely Droplet-CirSeq to significantly improve the amplification bias, which presents obvious superiority over the currently prevalent methods in exploitation of ultra-low frequency mutations. Droplet-CirSeq would be promisingly used in the identification of low frequency mutations initiated from extremely low input DNA, such as DNA of uncultured microorganisms, captured DNA of target region, circulation DNA of plasma et al, and its creative conception of rolling circle amplification in droplets would also be used in other low input DNA amplification fields. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2480-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-47842812016-03-10 Ultra-precise detection of mutations by droplet-based amplification of circularized DNA Wang, Kaile Ma, Qin Jiang, Lan Lai, Shujuan Lu, Xuemei Hou, Yali Wu, Chung-I Ruan, Jue BMC Genomics Methodology Article BACKGROUND: NGS (next generation sequencing) has been widely used in studies of biological processes, ranging from microbial evolution to cancer genomics. However, the error rate of NGS (0.1 % ~ 1 %) is still remaining a great challenge for comprehensively investigating the low frequency variations, and the current solution methods have suffered severe amplification bias or low efficiency. RESULTS: We creatively developed Droplet-CirSeq for relatively efficient, low-bias and ultra-sensitive identification of variations by combining millions of picoliter uniform-sized droplets with Cir-seq. Droplet-CirSeq is entitled with an incredibly low error rate of 3 ~ 5 X 10(-6). To systematically evaluate the performances of amplification uniformity and capability of mutation identification for Droplet-CirSeq, we took the mixtures of two E. coli strains as specific instances to simulate the circumstances of mutations with different frequencies. Compared with Cir-seq, the coefficient of variance of read depth for Droplet-CirSeq was 10 times less (p = 2.6 X 10(-3)), and the identified allele frequency presented more concentrated to the authentic frequency of mixtures (p = 4.8 X 10(-3)), illustrating a significant improvement of amplification bias and accuracy in allele frequency determination. Additionally, Droplet-CirSeq detected 2.5 times genuine SNPs (p < 0.001), achieved a 2.8 times lower false positive rate (p < 0.05) and a 1.5 times lower false negative rate (p < 0.001), in the case of a 3 pg DNA input. Intriguingly, the false positive sites predominantly represented in two types of base substitutions (G- > A, C- > T). Our findings indicated that 30 pg DNA input accommodated in 5 ~ 10 million droplets resulted in maximal detection of authentic mutations compared to 3 pg (p = 1.2 X 10(-8)) and 300 pg input (p = 2.2 X 10(-3)). CONCLUSIONS: We developed a method namely Droplet-CirSeq to significantly improve the amplification bias, which presents obvious superiority over the currently prevalent methods in exploitation of ultra-low frequency mutations. Droplet-CirSeq would be promisingly used in the identification of low frequency mutations initiated from extremely low input DNA, such as DNA of uncultured microorganisms, captured DNA of target region, circulation DNA of plasma et al, and its creative conception of rolling circle amplification in droplets would also be used in other low input DNA amplification fields. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2480-1) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-09 /pmc/articles/PMC4784281/ /pubmed/26960407 http://dx.doi.org/10.1186/s12864-016-2480-1 Text en © Wang et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Wang, Kaile
Ma, Qin
Jiang, Lan
Lai, Shujuan
Lu, Xuemei
Hou, Yali
Wu, Chung-I
Ruan, Jue
Ultra-precise detection of mutations by droplet-based amplification of circularized DNA
title Ultra-precise detection of mutations by droplet-based amplification of circularized DNA
title_full Ultra-precise detection of mutations by droplet-based amplification of circularized DNA
title_fullStr Ultra-precise detection of mutations by droplet-based amplification of circularized DNA
title_full_unstemmed Ultra-precise detection of mutations by droplet-based amplification of circularized DNA
title_short Ultra-precise detection of mutations by droplet-based amplification of circularized DNA
title_sort ultra-precise detection of mutations by droplet-based amplification of circularized dna
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4784281/
https://www.ncbi.nlm.nih.gov/pubmed/26960407
http://dx.doi.org/10.1186/s12864-016-2480-1
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