Full-Length 16S · PacBio & Oxford Nanopore

Species-level microbiome resolution. The whole 16S gene, end to end.

Short-read amplicon sequencing reads only one or two hypervariable regions (typically V3–V4, ~460 bp). Full-length 16S sequencing captures all nine hypervariable regions in one continuous read, giving you the taxonomic resolution and phylogenetic depth that short amplicons cannot deliver.

Plan Your Project → Learn the Basics
~1,500 bp
full gene, single read
Species-level
resolution in many taxa
PacBio HiFi + ONT Q20+
platforms
SILVA 138.1 / GTDB / Greengenes2
databases
About the Service

Full-Length 16S rRNA Sequencing at Nucleome Informatics

The bacterial 16S rRNA gene contains nine hypervariable regions (V1–V9) flanked by highly conserved stretches. Because no primer pair amplifies every region universally, short-read workflows must choose a subset — most commonly V3–V4 — and accept that many taxa cannot be distinguished beyond genus with a ~460 bp window. Full-length 16S sequencing removes this compromise: primers flanking the conserved regions at the ends of the gene (e.g. 27F/1492R) amplify the complete gene, and long reads sequence the amplicon end to end without assembly.

Nucleome Informatics offers full-length 16S amplicon sequencing on both major long-read platforms:

  • Demultiplexed, quality-filtered full-length 16S reads (FASTQ) with QC report
  • ASV/OTU feature table and representative sequences (QIIME 2 / DADA2 full-length workflow)
  • Taxonomic classification against SILVA 138.1, GTDB, or Greengenes2
  • Alpha- and beta-diversity analyses, differential abundance testing, and visualisations
  • A written analysis report with methods, parameters, and interpretation notes

Why full length matters

  • Resolution: full-length reads separate species that share identical V3–V4 regions — a well-documented limitation of short amplicons.
  • Phylogeny: the complete gene supports robust phylogenetic placement (e.g. with GTDB or full-length reference trees), improving diversity metrics such as UniFrac.
  • Primer-bias transparency: every workflow has primer bias; with full-length data you can also quantify how many reads are lost to primer mismatches and choose region subsets in silico for cross-study comparison.
Learning Path

From first principles to expert-level analysis

New here? Start with Foundations. Planning a study or reviewing results? Jump to Practitioner or Expert. Each level builds on the one before it, so you can read this page as a short course or dip in where you need to.

Start here if you are new to this service — six ideas that explain what it is and why it matters.

LEVEL 1

What is the 16S rRNA gene?

A component of the bacterial ribosome present in essentially all bacteria and archaea. It contains conserved regions (good primer sites) and nine hypervariable regions (V1–V9) that act as a barcode distinguishing taxa.

LEVEL 1

What does "full length" mean?

Sequencing the entire ~1,450–1,500 bp gene in one continuous read, instead of a 250–460 bp slice. Long reads make this possible because they comfortably exceed the amplicon length.

LEVEL 1

What is an ASV?

An amplicon sequence variant — an exact sequence inferred after modelling sequencing errors. ASVs are comparable across studies, unlike older 97%-similarity OTUs.

LEVEL 1

Why is V3–V4 so common if full length is better?

V3–V4 works on short-read instruments at low cost per sample and has a huge body of comparable literature. Full length trades some throughput and cost for resolution. Both remain valid; the choice depends on the question.

LEVEL 1

What can I expect to resolve?

Genera are resolved essentially universally; species-level calls are achievable for many taxa but not all — some species are genuinely identical across the 16S gene. We state this honestly in every report.

LEVEL 1

What samples can I send?

Faeces, soil, water, swabs, tissue biopsies, food, and environmental extracts. DNA extraction quality and consistency matter more than any downstream step — we can advise on extraction protocols or accept extracted DNA.

For scientists planning a project or reading a report: how each step works and how it can mislead.

LEVEL 2

Library design and barcoding

Samples are PCR-amplified with full-length primers carrying sample barcodes and platform adapters. We follow current PacBio and ONT amplicon recommendations, including unique dual indexing where appropriate, to minimise index hopping and barcode bleed-through.

LEVEL 2

Error correction: CCS vs consensus denoising

PacBio CCS builds a consensus per molecule from multiple polymerase passes. ONT workflows combine high-accuracy basecalling with per-ASV denoising (e.g. DADA2's long-read settings or clustering-based correction). Both routes aim for the same outcome: reliable exact sequences.

LEVEL 2

Chimera and length filtering

Full-length workflows screen for chimeras and off-size amplicons. Expect a small fraction of reads from mitochondria, chloroplasts, or eukaryotes depending on sample type; these are filtered and reported.

LEVEL 2

Taxonomic assignment choices

Naive-Bayes classifiers (QIIME 2), GTDB-Tk-style placement, or k-mer classifiers each have trade-offs. We default to SILVA 138.1 with QIIME 2 and can add GTDB or Greengenes2 on request.

LEVEL 2

Copy-number caveat

Bacteria carry variable 16S copy numbers (roughly 1–15+ per genome). Amplicon data measures gene abundance, not cell abundance. We flag this in interpretation and can support complementary approaches where cell-level quantification matters.

LEVEL 2

Contamination and controls

Negative extraction controls and mock communities are strongly recommended. We can process controls alongside your samples and report contaminant signals (e.g. decontam-style prevalence/frequency screening).

For study design: the decisions that determine whether the data answers your question.

LEVEL 3

Power and replication

Amplicon studies are sensitive to between-sample variance. Plan biological replicates and block for batch; as a rule of thumb, within-group replication matters more than raw read depth once ~10,000–20,000 full-length reads per sample are reached.

LEVEL 3

Cross-study comparability

Full-length ASVs can be region-trimmed in silico to match V3–V4 studies, enabling integration with legacy datasets — a major advantage when building on published cohorts.

LEVEL 3

Longitudinal and intervention design

For time-course or pre/post studies, pre-register the primary contrast, randomise extraction order, and sequence all time points in one batch to avoid batch-driven beta-diversity artefacts.

LEVEL 3

Combining with shotgun metagenomics

Full-length 16S is an excellent, economical screen; shotgun metagenomics (see our Shotgun Metagenomics page) adds strain-level resolution, functional potential, and MAG recovery. Many projects run 16S on all samples and shotgun on a subset.

LEVEL 3

Absolute quantification

Relative abundance is compositional. If you need absolute shifts, consider spike-in standards or qPCR/dPCR for total bacterial load alongside sequencing.

LEVEL 3

Reporting standards

We follow MIxS/STORMS-style reporting norms: primers, chemistry versions, reference database versions, and pipeline parameters are all documented in your report for reproducibility.

ASV
amplicon sequence variant; an inferred exact biological sequence.
CCS
circular consensus sequence; PacBio's per-molecule consensus read.
Hypervariable region (V1–V9)
segments of 16S whose sequence varies between taxa.
UniFrac
a beta-diversity metric weighting branch lengths of a phylogenetic tree by sample-specific abundance.
Copy-number bias
the distortion of relative abundance caused by variable 16S copy numbers per genome.
Mock community
a defined mixture of known microbes used as a positive control.
The Science

How it works, in two figures

Full-length 16S on PacBio HiFi and ONT platforms has been benchmarked against short-read amplicons and isolate genomes in multiple studies; species-level resolution gains are largest in genera with conserved V3–V4 regions (e.g. Lactobacillus, Streptococcus, Bacteroides). See references below.

Figure 1 Resolution comparison. schematic
V3–V4 short amplicon (~460 bp) Full-length 16S (~1,500 bp) One or two hypervariable regions Genus-level resolution for many taxa Huge body of comparable literature All nine hypervariable regions in one read Species-level resolution for many taxa Robust phylogenetic placement
Figure 1 | Resolution comparison. (Illustrative schematic, not sample data.)
Figure 2 Pipeline schematic. schematic
HMW DNA Full-length PCR (27F/1492R) PacBio CCS / ONT Q20+ ASV inference (QIIME 2 / DADA2) Taxonomy (SILVA / GTDB) Diversity & abundance report
Figure 2 | Pipeline schematic. (Illustrative schematic, not sample data.)
Technology Highlights

Built for the questions you are asking

The platforms, pipelines and standards behind this service.

PacBio HiFi circular consensus sequencing

Each full-length amplicon molecule is read multiple times in a single ZMW, and the consensus (CCS) reaches ≥99.9% accuracy — sufficient for single-nucleotide-level ASV inference across ~1,500 bp.

Oxford Nanopore Q20+ chemistry

Native amplification-free-compatible library options and Q20+ chemistry deliver full-length reads in real time; Dorado super-accuracy basecalling plus denoising supports species-level calls for many taxa.

Universal full-gene primers

27F/1492R-flanked amplification captures V1–V9 in one amplicon; we can advise on domain-specific primer sets (e.g. archaea, or taxa-biased panels) during project design.

QIIME 2 + DADA2 full-length pipelines

Amplicon sequence variant (ASV) inference with error models tuned for long reads; exact-sequence variants rather than 97% OTUs, enabling reproducible cross-study comparison.

Curated reference databases

Classification against SILVA 138.1 (full-length aligned), GTDB (genome-informed taxonomy), or Greengenes2 (full-length 16S integrated with metagenomic species) — we help you pick the database that matches your question.

Full statistical reporting

Alpha diversity (Shannon, Faith's PD), beta diversity (Bray–Curtis, weighted/unweighted UniFrac), PERMANOVA, differential abundance (ANCOM-BC2, DESeq2-style models), and publication-ready figures. ---

Scope Note

What this service does and does not cover

Scope note. Full-length 16S sequencing measures the composition of bacterial (and, with appropriate primers, archaeal) communities. It does not provide strain-level resolution, functional gene content, or antimicrobial resistance profiles — for those, see our Shotgun Metagenomics service. Species-level classification is not guaranteed for all taxa; where 16S cannot discriminate, we say so and suggest alternatives.---
Why Nucleome

Service highlights

What you can expect from our team in Hyderabad.

Both platforms, one lab

PacBio Revio/Sequel IIe and Oxford Nanopore PromethION under one roof — choose by budget, throughput, or turnaround needs.

Analysis included

Every project ships with a full QIIME 2-based analysis, not just FASTQ files.

India-relevant expertise

Experience with gut, soil, water, food, and livestock microbiomes relevant to Indian research programmes.

Flexible sample formats

From extracted DNA to raw swabs and stool kits; extraction services available.

Publication-ready outputs

Figures, tables, and methods text formatted for journals.

Consultative project design

Free project-design consultation before you commit samples. ---

Questions

Frequently asked, in plain language

From the basics to the finer points of design and interpretation.

basicHow is this different from the 16S V3–V4 sequencing I've used before?
V3–V4 reads a ~460 bp window on a short-read instrument. Full-length sequencing reads the entire ~1,500 bp gene on PacBio or ONT, which resolves many taxa to species level and supports better phylogenetic analyses.
basicHow many samples do I need?
It depends on your design. For simple group comparisons, plan for adequate biological replication within each group (typically ≥5–10 per group for exploratory work); we can advise during project design.
basicWhat sample types do you accept?
Stool, soil, water, swabs, tissues, food, and extracted DNA. Contact us for sample collection and shipping guidance.
intermediateWhich platform should I choose — PacBio or ONT?
PacBio HiFi offers the highest per-read accuracy after CCS; ONT offers rapid turnaround and scalable throughput on PromethION. For most microbiome profiling projects both deliver comparable biological conclusions; we will recommend based on your sample number and timeline.
intermediateWhich reference database will you use?
SILVA 138.1 by default, with GTDB or Greengenes2 available. Database choice affects taxonomy names; we document the version in every report.
intermediateWill I get species-level identifications?
For many taxa, yes. Some species are indistinguishable by 16S alone; in those cases we report the highest resolvable level honestly.
advancedCan I compare my full-length data with published V3–V4 datasets?
Yes — full-length ASVs can be trimmed in silico to the V3–V4 region for cross-study integration, one of the practical advantages of full-length data.
advancedHow do you handle 16S copy-number variation?
We report gene-relative abundances and flag the caveat. For cell-level quantification, pair amplicon data with qPCR/dPCR or spike-in standards.
advancedCan you add archaea or eukaryotes?
Archaea are covered with appropriate primers (e.g. archaeal 16S panels). For eukaryotes and fungi, see our ITS amplicon and 18S services.
advancedDo you provide raw data?
Yes — demultiplexed FASTQ plus all intermediate artefacts (feature tables, taxonomy assignments, QC reports) are delivered.
References

Key literature & resources

Selected sources behind the methods and reference values on this page. Figures labelled "schematic" or "illustrative" are generated for this page, not client data.

  1. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nature Methods. 2016;13(7):581–583.
  2. Bolyen E, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology. 2019;37(8):852–857.
  3. Quast C, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research. 2013;41(D1):D590–D596. (SILVA 138.1 release, 2020–2024 updates.)
  4. Parks DH, et al. GTDB: an ongoing census of genome and taxonomic innovation. Nucleic Acids Research. 2022;50(D1):D785–D794.
  5. McDonald D, et al. Greengenes2 unifies microbial data in a single reference space. Nature Biotechnology. 2024;42(7):1099–1104.
  6. Johnson JS, et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nature Communications. 2019;10(1):5029.
  7. Klindworth A, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Research. 2013;41(1):e1.