An extended single‐index multiplexed 16S rRNA sequencing for microbial community analysis on MiSeq illumina platforms
Bibliographic record
Abstract
The primary 16S rRNA sequencing protocol for microbial community analysis using Illumina platforms includes a single-indexing approach that allows pooling of hundreds of samples in each sequencing run. The protocol targets the V4 hypervariable region (HVR) of 16S rRNA using 150 bp paired-end (PE) sequencing. However, the latest improvement in Illumina chemistry has increased the read length up to 600 bp using 300 bp PE sequencing. To take advantage of the longer read length, a dual-indexing approach was previously developed for targeting different HVRs. However, due to simple working protocols, the single-index 150 bp PE approach still continues to be attractive to many researchers. Here, we described an extended single-indexing protocol for 300 bp PE illumina sequencing that targets the V3-V4 HVRs of 16S rRNA. The new primer set led to increased read length and alignment resolution, as well as increased richness and diversity of resulting microbial profile compared to that obtained from150 bp PE protocol for V4 sequencing. The β-diversity profile also differed qualitatively and quantitatively between the two approaches. Both primer sets had high coverage rates and specificity to detect dominant phyla; however, their coverage rate with regards to the rare biosphere varied. Our data further confirms that the choice of primer is the most deterministic factor in sequencing coverage and specificity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".