Knapp David J H F, McGovern Rachel A, Poon Art F Y, Zhong Xiaoyin, Chan Dennison, Swenson Luke C, Dong Winnie, Harrigan P Richard
BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada.
BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada; Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
PLoS One. 2014 Jun 24;9(6):e99508. doi: 10.1371/journal.pone.0099508. eCollection 2014.
Next generation, "deep", sequencing has increasing applications both clinically and in disparate fields of research. This study investigates the accuracy and reproducibility of "deep" sequencing as applied to co-receptor prediction using the V3 loop of Human Immunodeficiency Virus-1. Despite increasing use in HIV co-receptor prediction, the accuracy and reproducibility of deep sequencing technology, and the factors which can affect it, have received only a limited level of investigation. To accomplish this, repeated deep sequencing results were generated using the Roche GS-FLX (454) from a number of sources including a non-homogeneous clinical sample (N = 47 replicates over 18 deep sequencing runs), and a large clinical cohort from the MOTIVATE and A400129 studies (N = 1521). For repeated measurements of a non-homogeneous clinical sample, increasing input copy number both decreased variance in the measured proportion of non-R5 using virus (p<<0.001 and 0.02 for single replicates and triplicates respectively) and increased measured viral diversity (p<0.001; multiple measures). Detection of sequences with a mean abundance less than 1% abundance showed a 2 fold increase in median coefficient of variation (CV) in repeated measurements of a non-homogeneous clinical sample, and a 2.7 fold increase in CV in the MOTIVATE/A400129 dataset compared to sequences with ≥1% abundance. An unexpected source of error included read position, with low accuracy reads occurring more frequently towards the edge of sequencing regions (p<<0.001). Overall, the primary source of variability was sampling error caused by low input copy number/minority species prevalence, though other sources of error including sequence intrinsic, temporal, and read-position related errors were detected.
新一代“深度”测序技术在临床和不同研究领域的应用日益广泛。本研究调查了应用于人类免疫缺陷病毒1型V3环共受体预测的“深度”测序的准确性和可重复性。尽管深度测序技术在HIV共受体预测中的应用越来越多，但其准确性、可重复性以及可能影响它们的因素仅得到了有限程度的研究。为了实现这一目标，使用罗氏GS-FLX（454）从多个来源生成了重复的深度测序结果，包括一个非均质临床样本（在18次深度测序运行中进行了47次重复），以及来自MOTIVATE和A400129研究的一个大型临床队列（N = 1521）。对于非均质临床样本的重复测量，增加输入拷贝数既降低了非R5型病毒测量比例的方差（单次重复和三次重复的p值分别<<0.001和0.02），又增加了测量的病毒多样性（p<0.001；多次测量）。在非均质临床样本的重复测量中，平均丰度低于1%的序列检测显示，中位数变异系数（CV）增加了2倍，而在MOTIVATE/A400129数据集中，与丰度≥1%的序列相比，CV增加了2.7倍。一个意外的误差来源包括读取位置，低准确性的读取在测序区域边缘更频繁出现（p<<0.001）。总体而言，变异的主要来源是低输入拷贝数/少数物种流行率导致的抽样误差，不过也检测到了其他误差来源，包括序列固有、时间和读取位置相关的误差。
