SiNG-PCRseq: Accurate inter-sequence quantification achieved by spiking-in a neighbor genome for competitive PCR amplicon sequencingopen access
- Authors
- Oh, Soo A.; Yang, Inchul; Hahn, Yoon Soo; Kang, Yong-Kook; Chung, Sun-Ku; Jeong, Sangkyun
- Issue Date
- Jul-2015
- Publisher
- NATURE PUBLISHING GROUP
- Citation
- SCIENTIFIC REPORTS, v.5
- Journal Title
- SCIENTIFIC REPORTS
- Volume
- 5
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/9350
- DOI
- 10.1038/srep11879
- ISSN
- 2045-2322
- Abstract
- Despite the recent technological advances in DNA quantitation by sequencing, accurate delineation of the quantitative relationship among different DNA sequences is yet to be elaborated due to difficulties in correcting the sequence-specific quantitation biases. We here developed a novel DNA quantitation method via spiking-in a neighbor genome for competitive PCR amplicon sequencing (SiNG-PCRseq). This method utilizes genome-wide chemically equivalent but easily discriminable homologous sequences with a known copy arrangement in the neighbor genome. By comparing the amounts of selected human DNA sequences simultaneously to those of matched sequences in the orangutan genome, we could accurately draw the quantitative relationships for those sequences in the human genome (root-mean-square deviations <0.05). Technical replications of cDNA quantitation performed using different reagents at different time points also resulted in excellent correlations (R-2 > 0.95). The cDNA quantitation using SiNG-PCRseq was highly concordant with the RNA-seq-derived version in inter-sample comparisons (R-2 = 0.88), but relatively discordant in inter-sequence quantitation (R-2 < 0.44), indicating considerable level of sequence-dependent quantitative biases in RNA-seq. Considering the measurement structure explicitly relating the amount of different sequences within a sample, SiNG-PCRseq will facilitate sharing and comparing the quantitation data generated under different spatio-temporal settings.
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Collections - College of Natural Sciences > Department of Life Science > 1. Journal Articles
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