纳米孔测序
纳米孔
DNA测序
生物
计算生物学
深度测序
DNA
遗传学
基因组
分子生物学
基因
纳米技术
材料科学
作者
Stephanie C Y Yu,Jiaen Deng,Rong Qiao,Suk Hang Cheng,Wenlei Peng,So Ling Lau,L Y Lois Choy,Tak Yeung Leung,John Wong,Vincent Wai‐Sun Wong,Grace Lai‐Hung Wong,Peiyong Jiang,Rossa W. K. Chiu,K.C. Allen Chan,Y. M. Dennis Lo
出处
期刊:Clinical Chemistry
[American Association for Clinical Chemistry]
日期:2022-11-02
卷期号:69 (2): 168-179
被引量:36
标识
DOI:10.1093/clinchem/hvac180
摘要
Abstract Background Recent studies using single molecule, real-time (SMRT) sequencing revealed a substantial population of analyzable long cell-free DNA (cfDNA) in plasma. Potential clinical utilities of such long cfDNA in pregnancy and cancer have been demonstrated. However, the performance of different long-read sequencing platforms for the analysis of long cfDNA remains unknown. Methods Size biases of SMRT sequencing by Pacific Biosciences (PacBio) and nanopore sequencing by Oxford Nanopore Technologies (ONT) were evaluated using artificial mixtures of sonicated human and mouse DNA of different sizes. cfDNA from plasma samples of pregnant women at different trimesters, hepatitis B carriers, and patients with hepatocellular carcinoma were sequenced with the 2 platforms. Results Both platforms showed biases to sequence longer (1500 bp vs 200 bp) DNA fragments, with PacBio showing a stronger bias (5-fold overrepresentation of long fragments vs 2-fold in ONT). Percentages of cfDNA fragments 500 bp were around 6-fold higher in PacBio compared with ONT. End motif profiles of cfDNA from PacBio and ONT were similar, yet exhibited platform-dependent patterns. Tissue-of-origin analysis based on single-molecule methylation patterns showed comparable performance on both platforms. Conclusions SMRT sequencing generated data with higher percentages of long cfDNA compared with nanopore sequencing. Yet, a higher number of long cfDNA fragments eligible for the tissue-of-origin analysis could be obtained from nanopore sequencing due to its much higher throughput. When analyzing the size and end motif of cfDNA, one should be aware of the analytical characteristics and possible biases of the sequencing platforms being used.
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