SiNG-PCRseq: Accurate inter-sequence quantification achieved by spiking-in a
neighbor genome for competitive PCR amplicon sequencing
Soo A Oh1, Inchul Yang2, Yoonsoo Hahn3, Yong-Kook Kang4, Sun-Ku Chung1
and Sangkyun Jeong1,*
1. Medical Research Division, KIOM, Daejon 305-811, Koera
2. Center for Bioanalysis, KRISS, Daejon 305-340, Korea
3. Department of Life Science, Chung-Ang University, Seoul 156-756, Korea
4. Development and Differentiation Research Center, KRIBB, Daejon 305-806, Korea
Accurate delineation of the quantitative relationships among different DNA sequences is yet
to be a routine task due to a limited availability of means to normalize the sequence-specific
quantitation biases. To address this, we developed a novel DNA quantitation method via
spiking-in a neighbor genome for competitive PCR amplicon sequencing (SiNG-PCRseq),
which in principle compares the amounts of selected DNA sequences simultaneously to those
of matched sequences in a neighbor genome and reveals an unbiased inter-sequence
quantitative landscape. This method took advantage of genome-wide chemically equivalent,
but discriminable homologous sequences with a known copy arrangement in the neighbor
genome. As a proof of concept, we conducted a set of experiments using human samples with
a spike-in of orangutan genome. It drew unbiased quantitative relationships of many
sequences in the human genome, demonstrating it being highly accurate (root mean square
deviations < 5%). Technical replications for cDNA quantitation also resulted in excellent
correlations (R2 > 0.92), supporting its reproducibility. The SiNG-PCRseq-yielded
quantitative landscape for cDNA sequences appeared highly concordant to RNA-seq-derived
version in inter-sample comparisons (R2 = 0.88) but relatively discordant in inter-sequence
quantitation (R2 < 0.47), providing an insight into the sequence-dependent quantitative biases
in RNA-seq. Given the results insofar as being obtained and the measurement structure
explicitly relating the quantities of different sequences, SiNG-PCRseq substantiates its utility
in a range of applications such as determining copy number differences, relative quantitating
the transcript variants and inter-species quantitative comparison of gene expressions.