1. NanoAmpli-Seq: A workflow for amplicon sequencing for mixed microbial communities on the nanopore sequencing platform
- Author
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Szymon T. Calus, Umer Zeeshan Ijaz, and Ameet J. Pinto
- Subjects
0301 basic medicine ,Listeria ,Computer science ,030106 microbiology ,genetic processes ,Health Informatics ,Computational biology ,DNA sequencing ,Deep sequencing ,Nanopores ,03 medical and health sciences ,RNA, Ribosomal, 16S ,natural sciences ,Cluster analysis ,Gene ,de novo analyses ,Illumina dye sequencing ,030304 developmental biology ,Ssu rrna gene ,Sequence (medicine) ,sequencing accuracy ,0303 health sciences ,Bacteria ,amplicon sequencing ,030306 microbiology ,Microbiota ,Research ,High-Throughput Nucleotide Sequencing ,Reproducibility of Results ,Sequence Analysis, DNA ,Ribosomal RNA ,16S ribosomal RNA ,Computer Science Applications ,Nanopore ,030104 developmental biology ,Workflow ,nanopore sequencing ,Amplicon sequencing ,Base calling ,Nanopore sequencing - Abstract
BackgroundAmplicon sequencing on Illumina sequencing platforms leverages their deep sequencing and multiplexing capacity, but is limited in genetic resolution due to short read lengths. While Oxford Nanopore or Pacific Biosciences platforms overcome this limitation, their application has been limited due to higher error rates or smaller data output.ResultsIn this study, we introduce an amplicon sequencing workflow, i.e., NanoAmpli-Seq, that builds on Intramolecular-ligated Nanopore Consensus Sequencing (INC-Seq) approach and demonstrate its application for full-length 16S rRNA gene sequencing. NanoAmpli-Seq includes vital improvements to the aforementioned protocol that reduces sample-processing time while significantly improving sequence accuracy. The developed protocol includes chopSeq software for fragmentation and read orientation correction of INC-Seq consensus reads while nanoClust algorithm was designed for read partitioning-based de novo clustering and within cluster consensus calling to obtain full-length 16S rRNA gene sequences.ConclusionsNanoAmpli-Seq accurately estimates the diversity of tested mock communities with average sequence accuracy of 99.5% for 2D and 1D2 sequencing on the nanopore sequencing platform. Nearly all residual errors in NanoAmpli-Seq sequences originate from deletions in homopolymer regions, indicating that homopolymer aware basecalling or error correction may allow for sequencing accuracy comparable to short-read sequencing platforms.
- Published
- 2018
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