Researchers have found a simple way to remove nearly all sequencing errors produced by a widely used portable DNA sequencer.
High-throughput amplicon sequencing is a ubiquitous method for studying genetic populations with low-abundance variants or high heterogeneity. Illumina short-read sequencing has dominated amplicon-related research. This is due to its unprecedented throughput and low native error-rate of ~0.1%. However, its maximum amplicon size limits important long-range information and assay resolution. Experts have applied unique molecular identifiers (UMIs) to enable sequencing of longer amplicons with short-reads via assembly of synthetic long-reads. This approach, however, cannot resolve amplicons with repeats longer than the short-read length. Additionally, the high native error rates of Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) have also made it difficult to confidently identify true UMI tag sequences necessary to accurately assign raw reads to their template molecules.
Improving portable DNA sequencer accuracy
In this paper, published in Nature Methods, researchers presented a simple workflow that combines UMIs with sequencing of long amplicons on the ONT and PacBio platforms to produce highly accurate single-molecule consensus sequences. They designed UMIs to contain recognisable internal patterns that avoid error-prone homopolymer stretches.
Applying their approach to sequence ribosomal RNA operon amplicons and genomics sequences of reference microbial communities, the team observed a chimera rate <0.02%. The team were able to reduce the 5-25% error rate of ONT MinION to 0.0042%. Moreover, they reduced the error rate of PacBio from ~13% to ~0.0007%.
Ryan Ziels, co-lead author of the study, stated:
“A beautiful thing about this method is that it is applicable to any gene of interest that can be amplified.
This means that it can be very useful in any field where the combination of high-accuracy and long-range genomic information is valuable, such as cancer research, plant research, human genetics and microbiome science.”
The team are now working to expand the method to permit near-real-time detection of microorganisms in water and wastewater. This may help improve public health strategies and treatment technologies, and also better control the spread of harmful microorganisms like SARS-CoV-2.
Image credit: By Bill Oxford – canva.com