Department of Pediatrics (Genetic Medicine), Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.
Department of Epidemiology and Population Health, NYU School of Medicine, New York, NY, USA.
Cell Rep Methods. 2023 Jan 23;3(1):100391. doi: 10.1016/j.crmeth.2022.100391.
In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades.
在一项由 1772 名西班牙裔社区健康研究/拉丁裔研究参与者组成的大型队列中，这些参与者具有重叠的 16SV4 rRNA 基因（细菌扩增子）、ITS1（真菌扩增子）和鸟枪法测序数据，我们证明了 16SV4 扩增子测序和鸟枪法宏基因组测序在属水平上对细菌具有相同的分类准确性，即使在浅测序深度下也是如此。相比之下，对于真菌分类群，我们没有观察到鸟枪法和 ITS1 扩增子结果之间有意义的一致性。最后，我们表明，使用合并的扩增子/鸟枪法数据可以对扩增子和鸟枪法数据进行协调和合并，从而生成具有出色一致性（三个独立结果的效应大小方差<1%）的更大微生物组数据集，与纯鸟枪法宏基因组分析相比。因此，在流行病学研究中有多种方法可以研究微生物组，我们提供了一种强大的合并方法的演示，该方法将允许研究人员利用过去二十年中产生的大量扩增子测序数据。
