Metabarcoding with Illumina and Oxford Nanopore Technologies Provides Unique Insight into the Mycobiota of Tree Seeds
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB81281 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR13848523_1.fastq.gz | Fastqsanger.gz | |||
| ERR13848523_2.fastq.gz | Fastqsanger.gz | |||
| ERR13848524_1.fastq.gz | Fastqsanger.gz | |||
| ERR13848524_2.fastq.gz | Fastqsanger.gz | |||
| ERR13848525_1.fastq.gz | Fastqsanger.gz |
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Project description:Metabarcoding for Tree Seeds - ONT data
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Project description:Illumina MiSeq is the current standard for characterizing microbial communities in soil. The newer alternative, Oxford Nanopore Technologies MinION sequencer, is quickly gaining popularity because of the low initial cost and longer sequence reads. However, the accuracy of MinION, per base, is much lower than MiSeq (95% versus 99.9%). The effects of this difference in base-calling accuracy on taxonomic and diversity estimates remains unclear. We compared the effects of platform, primers, and bioinformatics on mock community and agricultural soil samples using short MiSeq, and short and full-length MinION 16S rRNA amplicon sequencing. For all three methods, we found that taxonomic assignments of the mock community at both the genus and species level matched expectations with minimal deviation (genus: 80.9-90.5%; species: 70.9-85.2% Bray-Curtis similarity); however, the short MiSeq with error correction (DADA2) resulted in the correct estimate of mock community species richness and much lower alpha diversity for soils. Several filtering strategies were tested to improve these estimates with varying results. The sequencing platform also had a significant influence on the relative abundances of taxa with MiSeq resulting in significantly higher abundances Actinobacteria, Chloroflexi, and Gemmatimonadetes and lower abundances of Acidobacteria, Bacteroides, Firmicutes, Proteobacteria, and Verrucomicrobia compared to the MinION platform. When comparing agricultural soils from two different sites (Fort Collins, CO and Pendleton, OR), methods varied in the taxa identified as significantly different between sites. At all taxonomic levels, the full-length MinION method had the highest similarity to the short MiSeq method with DADA2 correction with 73.2%, 69.3%, 74.1%, 79.3%, 79.4%, and 82.28% of the taxa at the phyla, class, order, family, genus, and species levels, respectively, showing similar patterns in differences between the sites. In summary, although both platforms appear suitable for 16S rRNA microbial community composition, biases for different taxa may make the comparison between studies problematic; and even with a single study (i.e., comparing sites or treatments), the sequencing platform can influence the differentially abundant taxa identified.
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Project description:Rapid, accurate bacterial identification in biological samples is an important task for microbiology laboratories, for which 16S~rRNA gene Sanger sequencing of cultured isolates is frequently used. In contrast, next-generation sequencing does not require intermediate culturing steps and can be directly applied on communities, but its performance has not been extensively evaluated. We present a comparative evaluation of second (Illumina) and third (Oxford Nanopore Technologies (ONT)) generation sequencing technologies for 16S targeted genomics using a well-characterized reference sample. Different 16S gene regions were amplified and sequenced using the Illumina MiSeq, and analyzed with Mothur. Correct classification was variable, depending on the region amplified. Using a majority vote over all regions, most false positives could be eliminated at the genus level but not the species level. Alternatively, the entire 16S gene was amplified and sequenced using the ONT MinION, and analyzed with Mothur, EPI2ME, and GraphMap. Although >99\% of reads were correctly classified at the genus level, up to $\approx$40\% were misclassified at the species level. Both~technologies, therefore, allow reliable identification of bacterial genera, but can potentially misguide identification of bacterial species, and constitute viable alternatives to Sanger sequencing for rapid analysis of mixed samples without requiring any culturing steps.
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