TY - JOUR
T1 - Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing
AU - Hou, Yong
AU - Wu, Kui
AU - Shi, Xulian
AU - Li, Fuqiang
AU - Song, Luting
AU - Wu, Hanjie
AU - Dean, Michael
AU - Li, Guibo
AU - Tsang, Shirley
AU - Jiang, Runze
AU - Zhang, Xiaolong
AU - Li, Bo
AU - Liu, Geng
AU - Bedekar, Niharika
AU - Lu, Na
AU - Xie, Guoyun
AU - Liang, Han
AU - Chang, Liao
AU - Wang, Ting
AU - Chen, Jianghao
AU - Li, Yingrui
AU - Zhang, Xiuqing
AU - Yang, Huanming
AU - Xu, Xun
AU - Wang, Ling
AU - Wang, Jun
N1 - Funding Information:
We thank L Goodman for revising the manuscript and Youyong Lv for providing the BGC823 gastric cancer cell line. This work was supported by the National High Technology Research and Development Program of China -863 Program (NO.2012AA02A201), the Guangdong Innovative Research Team Program (2009010016), the Guangdong Enterprise Key Laboratory of Human Disease Genomics (No. 2011A060906007), National Basic Research Program of China (973 program No. 2011CB809202 and 2011CB809203), the Major Industrial Technology Research Program of Shenzhen (program number BGI20100001), the Key Laboratory Project Supported by Shenzhen City (grants CXB201108250096A and ZDSYS20140509153457495) and the Shenzhen Key Laboratory of China National GeneBank-Shenzhen. This project was also supported by the National Natural Science Fund (81272899 and 81172510) and Discipline booster plan of Xi Jing Hospital (XJZT12Z07). We also acknowledge the Ole Rømer grant from the Danish Natural Science Research Council, the Danish National Research Foundation, National Natural Science Foundation of China, and funds from the Shenzhen Municipal Government and the Local Government of Yantian District of Shenzhen.
Funding Information:
We thank L Goodman for revising the manuscript and Youyong Lv for providing the BGC823 gastric cancer cell line. This work was supported by the National High Technology Research and Development Program of China-863 Program (NO.2012AA02A201), the Guangdong Innovative Research Team Program (2009010016), the Guangdong Enterprise Key Laboratory of Human Disease Genomics (No. 2011A060906007), National Basic Research Program of China (973 program No. 2011CB809202 and 2011CB809203), the Major Industrial Technology Research Program of Shenzhen (program number BGI20100001), the Key Laboratory Project Supported by Shenzhen City (grants CXB201108250096A and ZDSYS20140509153457495) and the Shenzhen Key Laboratory of China National GeneBank-Shenzhen. This project was also supported by the National Natural Science Fund (81272899 and 81172510) and Discipline booster plan of Xi Jing Hospital (XJZT12Z07). We also acknowledge the Ole R?mer grant from the Danish Natural Science Research Council, the Danish National Research Foundation, National Natural Science Foundation of China, and funds from the Shenzhen Municipal Government and the Local Government of Yantian District of Shenzhen.
PY - 2015
Y1 - 2015
N2 - Background: Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed. Results: We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2). Conclusions: Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.
AB - Background: Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed. Results: We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2). Conclusions: Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.
KW - DOP-PCR
KW - MALBAC
KW - MDA
KW - Next-generation sequencing
KW - Single-cell resequencing
KW - Variations detection
KW - Whole genome amplification
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U2 - 10.1186/s13742-015-0068-3
DO - 10.1186/s13742-015-0068-3
M3 - Article
C2 - 26251698
AN - SCOPUS:84979520403
SN - 2047-217X
VL - 4
JO - GigaScience
JF - GigaScience
IS - 1
M1 - 37
ER -