Sample Submission Guidelines
Why Nanopore Amplicon Sequencing Matters
Short-read methods, such as Illumina panels targeting V3–V4 regions, often fail to distinguish closely related species. This can limit downstream research in microbiome analysis, pathogen detection, and clonal validation.
Nanopore sequencing addresses these gaps by producing long reads across the full gene length, such as V1–V9 of 16S or the entire ITS region. These reads provide higher taxonomic resolution, reduce errors in community analysis, and enable confident species- or strain-level identification.
For researchers needing broader context, Nanopore Ultra-Long Sequencing supports telomere-to-telomere genome assemblies, while Nanopore Direct RNA Sequencing links structure with expression.
Technical Specifications
CD Genomics provides a reliable, end-to-end workflow for Nanopore Amplicon Sequencing, optimised for both clonal and community-based projects. Our laboratory protocols, sequencing platforms, and bioinformatics pipelines are designed to maximise read accuracy and ensure species- or strain-level resolution.
| Parameter | Specification |
|---|---|
| Amplicon size range | 0.5–25 kb (extended support available upon request) |
| Platforms | Oxford Nanopore PromethION / GridION |
| Chemistry | Kit 14 with R10.4.1 flow cells for improved accuracy |
| Read depth | ≥50,000 reads per sample recommended for community profiling |
| Turnaround time | 1–3 business days (clonal projects); ~14 days (community profiling) |
| Data accuracy | Standard polishing pipelines; optional barcode-based consensus workflow for higher fidelity |
| Deliverables | FASTQ/FASTA files, quality control reports, taxonomy/variant tables, interactive HTML and PDF reports |
Quality assurance: All sequencing projects undergo strict QC, including DNA integrity checks, read-length distribution analysis, and error-rate monitoring.
Applications
Nanopore Amplicon Sequencing is widely applied in microbial research, gene validation, and comparative genomics. By providing long reads that span entire amplicons, it enables confident interpretation of complex datasets and reduces the ambiguity often found in short-read methods.
Microbial Community Profiling
- Full-length 16S rRNA (V1–V9) and ITS regions deliver species-level identification.
- Suitable for environmental samples, human microbiomes, and industrial microbiology projects.
- Supports diversity analysis, population structure evaluation, and comparative studies.
Pathogen Surveillance and Risk Assessment
- Detect potential pathogens in water, soil, food, and indoor environments.
- Enables tracking of microbial shifts in response to seasonal or environmental changes.
- Enhances biosafety monitoring in clinical and agricultural research.
Food Safety and Agriculture
- Identify spoilage organisms and beneficial strains in food production chains.
- Support breeding programs by profiling microbial communities linked to crop resilience.
- Facilitate agricultural biotechnology studies by resolving strain-level diversity.
Clonal Verification and Variant Detection
- Confirm single-gene amplicons, edited constructs, or plasmid inserts.
- Generate high-fidelity consensus for clonal samples using barcode-based strategies.
- Rapid turnaround enables iterative design and testing cycles.
Comparative and Evolutionary Genomics
- Resolve closely related species and strain-level variants.
- Support population genetics and microbial evolution studies with full-length coverage.
- Combine with Nanopore Target Sequencing for focused analysis of specific loci.
Workflow: End-to-End Service
Primer strategy: select target regions (16S, ITS, custom genes)
High-fidelity PCR: with optional barcode tagging for error correction
Library preparation: ONT Kit 14, minimal fragmentation
Sequencing: PromethION/GridION with R10.4.1 flow cells
Data processing: basecalling, consensus generation, chimera filtering
Bioinformatics: taxonomic assignment, variant analysis, diversity statistics
Delivery: FASTQ/FASTA files, QC reports, HTML/PDF outputs
Bioinformatics & Reporting
CD Genomics provides a complete bioinformatics pipeline for Nanopore Amplicon Sequencing, ensuring high-confidence results and publication-ready outputs. Our analysis covers quality control, taxonomic classification, variant detection, and customised reporting.
Standard Analysis
Basecalling & demultiplexing: conversion of raw signals to FASTQ with sample separation.
Quality control: read length distribution, coverage depth, and accuracy statistics.
Taxonomic assignment: species-level classification for 16S and ITS datasets using curated reference databases.
Diversity analysis: alpha- and beta-diversity indices with visualisations such as PCoA or NMDS plots.
Advanced Analysis (Optional)
Differential abundance: comparative statistics across experimental groups.
Variant detection: identify sequence variants within clonal amplicons.
Barcode-consensus workflow: enhanced accuracy with error suppression and chimera filtering.
Strain-level resolution: clustering and fine-scale variant calling.
Proven Case Applications
Our Nanopore Amplicon Sequencing service has been successfully applied across diverse research fields. Below are selected examples that demonstrate practical outcomes.
| Project | Research Goal | Key Results |
|---|---|---|
| Urban Water Microbiome | Assess seasonal changes and pollution impact on river communities | Species-level resolution of Arcobacter and Aeromonas; revealed source-specific contributions in wet vs. dry seasons |
| Indoor Environment Study | Characterise microbial populations linked to human occupancy | Identified 21 key species, including 11 potential pathogens; higher abundance of beneficial bacteria indoors |
| Clonal Gene Verification | Confirm engineered constructs and plasmid sequences | High-fidelity consensus achieved; reduced false positives using barcode-based strategy |
| Agricultural Microbiome | Investigate crop-associated microbial diversity in soil samples | Improved strain-level profiling; supported resilience analysis in breeding research |
Note: These applications are for research use only and are not intended for diagnostic procedures.
Choosing the Right Sequencing Platform
While Nanopore Amplicon Sequencing offers unique strengths, PacBio SMRT and Illumina sequencing also serve important roles. The table below provides a simple comparison to guide your project planning.
Deliverables
- Raw sequencing data: FASTQ and optional FASTA files.
- QC reports: yield, read length distribution, and accuracy metrics.
- Taxonomy/variant tables with abundance profiles.
- Interactive HTML and PDF reports with publication-ready figures (SVG/PNG).
- Methods text and pipeline parameters to support reproducibility.
Choosing the Right Sequencing Platform
CD Genomics supports multiple long- and short-read technologies, ensuring that each project receives the most suitable approach. Whether your goal is high-accuracy variant detection, full-length amplicon analysis, or population-scale studies, we can recommend the right platform.
| Feature | PacBio SMRT | Oxford Nanopore | Illumina |
|---|---|---|---|
| Read length | Long (10–25 kb; HiFi ~15–20 kb) | Ultra-long (kb to Mb range) | Short (100–500 bp) |
| Accuracy | Very high (HiFi >99.9%) | High with consensus/error-suppression | Very high (>99.9%) |
| Turnaround | Moderate | Flexible, portable, real-time | High-throughput, batch-based |
| Strengths | Low error, ideal for repeat regions | Longest reads, species-level amplicons, direct RNA/DNA | Cost-effective for large cohorts |
| Limitations | Higher cost, DNA quality critical | Raw error rate higher without correction | Limited resolution for long repeats |
| Best suited for | De novo assemblies, repeat regions | Amplicons, microbiomes, rapid analysis | SNP detection, large sample studies |
Our commitment:
We provide sequencing services on all three platforms—PacBio, Oxford Nanopore, and Illumina—so you don't need to worry about choosing the wrong method. Our experts evaluate your samples and research goals, then recommend the platform that maximises data quality, efficiency, and cost-effectiveness.
Sample Requirements
| Sample Type | Requirement |
|---|---|
| Genomic DNA | - Recommended: ≥500 ng total DNA - Concentration: ≥10 ng/µL - Purity: OD260/280 ≈1.8–2.0; OD260/230 >2.0 - Buffer: DNase-free water or EB |
| Amplicon DNA | - Recommended: ≥1 µg DNA - Minimum total: ≥500 ng - Concentration: ≥20 ng/µL - Requirement: single, specific PCR product (visible clean band, no non-specific products) |
General Notes
- DNA must be RNase-treated and free of proteins, polysaccharides, and phenolic contaminants.
- Avoid repeated freeze–thaw cycles to preserve integrity.
- Ship on dry ice; use DNA LoBind tubes (1.5 mL or 2 mL).
- Label tubes clearly with ≤4 alphanumeric characters consistent with the submission form.
Demo Results Showcase
Nanopore reads span the full 16S/ITS regions, while short-read platforms are limited to partial segments.
Taxonomic Resolution Improvement
Nanopore amplicon sequencing significantly improves species-level assignment compared with short-read methods.
Consensus Accuracy with Error Suppression
Advanced error-correction workflows reduce false positives and chimera formation, ensuring high-fidelity consensus.
Community Diversity Analysis
Beta-diversity analysis enables clear separation of microbial communities across sample groups.
FAQ
Q1. What distinguishes Nanopore amplicon sequencing from Illumina short-read methods?
Nanopore delivers full-length reads (e.g. full 16S V1–V9 or ITS), allowing species- or strain-level resolution. Illumina reads are shorter (e.g. V3–V4) and may misclassify species or lose strain-level detail.
Q2. When is barcode-based error correction (unique tagging) needed?
Use it when:
- you require very high accuracy (e.g. variant detection in clonal or mixed samples),
- targeting long amplicons prone to sequencing or PCR errors,
- investigating rare taxa.
Q3. How many reads per sample are recommended?
- For community profiling: ≥ 50,000 reads/sample to saturate diversity in moderate-complexity samples.
- For clonal amplicons: fewer reads are needed, since focus is consensus accuracy rather than richness.
Q4. What factors most affect data quality?
- DNA input: quantity, purity (OD ratios), integrity (fragment size).
- PCR specificity: clean single-band amplifications.
- Sample handling: avoid freeze-thaws, contamination, inhibitors.
Q5. How fast will I receive results?
Turnaround time depends on project type and sample quality. Clonal projects are typically faster, while community studies may take longer due to additional analysis steps.
Q6. Are results suitable for publication or regulatory use?
Yes, for research use only. We supply publication-quality reports, methods details, versioned taxonomy databases. However, this service is not certified for diagnostics.
Q7. Which internal reference databases are used for taxonomic assignment?
We use curated, regularly updated 16S/ITS full-length reference databases to ensure improved species-level assignment and minimal misclassification.
Q8. Can I sequence multiple gene targets or loci in a single sample?
Yes, provided PCR amplifications are specific (single distinct product per target). Mixed or non-specific amplicons reduce accuracy and may require separate runs or custom workflows.
Case Study: Complete Genome Sequencing of Streptomyces albus CAS922
Client Background
Researchers from TU Dortmund University (Germany) and Universidad Nacional del Sur (Argentina) investigated the actinomycete Streptomyces albus CAS922. This strain was isolated from sunflower seed hulls and exhibited strong potential for lignocellulose degradation and secondary metabolite biosynthesis. To explore its metabolic capacity and industrial relevance, the team required a high-quality complete genome sequence.
Challenge
- Actinomycetes typically contain large, GC-rich genomes (>70%), which complicates sequencing and assembly.
- Short-read technologies often produce fragmented assemblies with unresolved repeats, limiting downstream analysis of biosynthetic gene clusters (BGCs) and carbohydrate-active enzymes (CAZymes).
- The client needed an approach that could generate long, contiguous reads and support accurate annotation for functional genomics research.
Our Solution
- CD Genomics performed Oxford Nanopore long-read sequencing using the SQK-LSK109 ligation kit.
- Data generation: Over 1.5 Gb of clean data from >260,000 reads, with an N50 read length of ~8 kb.
- Assembly strategy: De novo assembly with Canu, followed by polishing with Pilon to enhance accuracy.
- Annotation tools: NCBI Prokaryotic Genome Annotation Pipeline (PGAP) for gene calling; RepeatMasker for repetitive elements; CAZy/dbCAN2 for carbohydrate-active enzyme prediction; antiSMASH for biosynthetic cluster detection.
Results
- A complete linear chromosome of 8.06 Mb was assembled, achieving ~191× coverage and a GC content of 72.6%.
- 6,776 protein-coding genes and 80 RNAs were identified.
- 232 carbohydrate-active enzymes were predicted, including three copper-dependent enzymes implicated in cellulose and xylan degradation.
- 27 biosynthetic gene clusters were revealed, encoding metabolites such as siderophores (desferrioxamine E), terpenes (cyslabdan, geosmin), and antibiotics (xantholipin, pseudouridimycin).
Impact
- The high-quality genome enabled strain-level functional insights into lignocellulose degradation, supporting the development of renewable biomass applications.
- Discovery of diverse biosynthetic clusters highlighted the biotechnological potential of S. albus CAS922 for producing novel antibiotics and bioactive compounds.
- The project demonstrated how CD Genomics' Nanopore sequencing service can resolve complex, high-GC genomes and deliver actionable biological insights.
References:
- Tippelt A, Nett M, Vela Gurovic MS. Complete Genome Sequence of the Lignocellulose-Degrading Actinomycete Streptomyces albus CAS922. Microbiol Resour Announc. 2020 May 21;9(21):e00227-20. doi: 10.1128/MRA.00227-20. PMID: 32439662; PMCID: PMC7242664.
- Sun B, Bhati KK, Song P, Edwards A, Petri L, Kruusvee V, Blaakmeer A, Dolde U, Rodrigues V, Straub D, Yang J, Jia G, Wenkel S. FIONA1-mediated methylation of the 3'UTR of FLC affects FLC transcript levels and flowering in Arabidopsis. PLoS Genet. 2022 Sep 27;18(9):e1010386. doi: 10.1371/journal.pgen.1010386. PMID: 36166469; PMCID: PMC9543952.
