title: Ultra-precise detection of mutations by droplet-based amplification of circularized DNA.
abstract: 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.
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.|University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Kaile
authors.initials: K
authors.lastname: Wang
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.|University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Qin
authors.initials: Q
authors.lastname: Ma
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
authors.forename: Lan
authors.initials: L
authors.lastname: Jiang
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
authors.forename: Shujuan
authors.initials: S
authors.lastname: Lai
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
authors.forename: Xuemei
authors.initials: X
authors.lastname: Lu
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. houyl@big.ac.cn.
authors.forename: Yali
authors.initials: Y
authors.lastname: Hou
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. cw16@uchicago.edu.|State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China. cw16@uchicago.edu.|Department of Ecology and Evolution, University of Chicago, Illinois, USA. cw16@uchicago.edu.
authors.forename: Chung-I
authors.initials: CI
authors.lastname: Wu
authors.affiliation: Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. ruanjue@gmail.com.|Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China. ruanjue@gmail.com.
authors.forename: Jue
authors.initials: J
authors.lastname: Ruan
mesh_terms: D004252:DNA Mutational Analysis / Q000379:methods*; D004269:DNA, Bacterial / Q000235:genetics; D004270:DNA, Circular / Q000235:genetics*; D004926:Escherichia coli; D005787:Gene Frequency; D021141:Nucleic Acid Amplification Techniques / Q000379:methods*; D020641:Polymorphism, Single Nucleotide
chemical_list: D004269:DNA, Bacterial; D004270:DNA, Circular