Highly comparable metabarcoding results from MGI-Tech and Illumina sequencing platforms
Research output: Contribution to journal › Journal article › Research › peer-review
Final published version, 1.83 MB, PDF document
With the developments in DNA nanoball sequencing technologies and the emergence of new platforms, there is an increasing interest in their performance in comparison with the widely used sequencing-by-synthesis methods. Here, we test the consistency of metabarcoding results from DNBSEQ-G400RS (DNA nanoball sequencing platform by MGI-Tech) and NovaSeq 6000 (sequencing-by-synthesis platform by Illumina) platforms using technical replicates of DNA libraries that consist of COI gene amplicons from 120 soil DNA samples. By subjecting raw sequencing data from both platforms to a uniform bioinformatics processing, we found that the proportion of high-quality reads passing through the filtering steps was similar in both datasets. Per-sample operational taxonomic unit (OTU) and amplicon sequence variant (ASV) richness patterns were highly correlated, but sequencing data from DNBSEQ-G400RS harbored a higher number of OTUs. This may be related to the lower dominance of most common OTUs in DNBSEQ data set (thus revealing higher richness by detecting rare taxa) and/or to a lower effective read quality leading to generation of spurious OTUs. However, there was no statistical difference in the ASV and post-clustered ASV richness between platforms, suggesting that additional denoising step in the ASV workflow had effectively removed the ‘noisy’ reads. Both OTU-based and ASV-based composition were strongly correlated between the sequencing platforms, with essentially interchangeable results. Therefore, we conclude that DNBSEQ-G400RS and NovaSeq 6000 are both equally efficient high-throughput sequencing platforms to be utilized in studies aiming to apply the metabarcoding approach, but the main benefit of the former is related to lower sequencing cost.
|Number of pages||21|
|Publication status||Published - Sep 2021|
We thank the service providers for providing excellent-quality data. We have no conflicting interests with the service providers. We thank Vasco Elbrecht, Mathilde Borg Dahl and an anonymous reviewer for their constructive comments. Funding for this study was provided by the Novo Nordisk Fonden (Silva Nova), Norway-Baltic financial mechanism (EMP632) and the Estonian Research Council (Mobilitas Pluss grant MOBTP198). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Funding for this study was provided by the Novo Nordisk Fonden (Silva Nova), Norway-Baltic financial mechanism (EMP632) and the Estonian Research Council (Mobilitas Pluss grant MOBTP198). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright 2021 Anslan et al.
- COI, DNBSEQ, Illumina, Metabarcoding, MGI-Tech, NovaSeq
Number of downloads are based on statistics from Google Scholar and www.ku.dk