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Assessment of REPLI-g Multiple Displacement Whole Genome Amplification (WGA) Techniques for Metagenomic Applications

机译:评估REPLI-g多置换全基因组扩增(WGA)技术在元基因组学中的应用

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摘要

Amplification of minute quantities of DNA is a fundamental challenge in low-biomass metagenomic and microbiome studies because of potential biases in coverage, guanine-cytosine (GC) content, and altered species abundances. Whole genome amplification (WGA), although widely used, is notorious for introducing artifact sequences, either by amplifying laboratory contaminants or by nonrandom amplification of a sample’s DNA. In this study, we investigate the effect of REPLI-g multiple displacement amplification (MDA; Qiagen, Valencia, CA, USA) on sequencing data quality and species abundance detection in 8 paired metagenomic samples and 1 titrated, mixed control sample. We extracted and sequenced genomic DNA (gDNA) from 8 environmental samples and compared the quality of the sequencing data for the MDA and their corresponding non-MDA samples. The degree of REPLI-g MDA bias was evaluated by sequence metrics, species composition, and cross-validating observed species abundance and species diversity estimates using the One Codex and MetaPhlAn taxonomic classification tools. Here, we provide evidence of the overall efficacy of REPLI-g MDA on retaining sequencing data quality and species abundance measurements while providing increased yields of high-fidelity DNA. We find that species abundance estimates are largely consistent across samples, even with REPLI-g amplification, as demonstrated by the Spearman’s rank order coefficient (R2 > 0.8). However, REPLI-g MDA often produced fewer classified reads at the species, genera, and family level, resulting in decreased species diversity. We also observed some areas with the PCR “jackpot effect,” with varying input DNA values for the Metagenomics Research Group (MGRG) controls at specific genomic loci. We visualize this effect in whole genome coverage plots and with sequence composition analyses and note these caveats of the MDA method. Despite overall concordance of species abundance between the amplified and unamplified samples, these results demonstrate that amplification of DNA using the REPLI-g method has some limitations. These concerns could be addressed by future improvements in the enzymes or methods for REPLI-g to be considered a >99% robust method for increasing the amount of high-fidelity DNA from low-biomass samples or at the very least, accounted for during computational analysis of MDA samples.
机译:在低生物量宏基因组学和微生物组研究中,微量DNA的扩增是一项基本挑战,因为其覆盖范围,鸟嘌呤-胞嘧啶(GC)含量和物种丰度的变化可能存在偏差。全基因组扩增(WGA)尽管已被广泛使用,但它通过引入实验室污染物或通过样品DNA的非随机扩增而引入人为序列而臭名昭著。在这项研究中,我们调查了REPLI-g多重置换扩增(MDA;美国加利福尼亚州巴伦西亚Qiagen市)对8对配对的宏基因组学样品和1个滴定的混合对照样品中测序数据质量和物种丰度检测的影响。我们从8个环境样品中提取了基因组DNA(gDNA)并对其进行了测序,并比较了MDA及其对应的非MDA样品的测序数据质量。 REPLI-g MDA偏倚的程度通过使用One Codex和MetaPhlAn分类学分类工具通过序列指标,物种组成和交叉验证观察到的物种丰度和物种多样性估计来评估。在这里,我们提供了REPLI-g MDA在保持测序数据质量和物种丰度测量的同时提供更高保真度DNA产量的总体功效的证据。我们发现,即使使用REPLI-g扩增,物种之间的物种丰度估计值也基本一致,如Spearman的秩序系数(R 2 99%稳健方法,或者至少是在计算过程中考虑的方法MDA样品分析。

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