Slippage of degenerate primers can cause variation in amplicon length
Bibliographic record
Abstract
It is well understood that homopolymer regions should be avoided for primer binding to prevent off-target amplification. However, in metabarcoding, it is often difficult to avoid primer degeneracy in order to maximize taxa detection. We here investigate primer binding specificity using different primer sets from several invertebrate metabarcoding studies. Our results indicate that primers frequently bound 1-2 bp upstream in taxa where a homopolymer region was present in the amplification direction. Primer binding 1 bp downstream was observed less frequently. This primer slippage leads to taxon-specific length variation in amplicons and subsequent length variation in recovered sequences. Some widely used primer sets were severely affected by this bias, while others were not. While this variation will only have small impacts on the designation of Operational Taxonomic Units (OTUs) by clustering algorithms that ignore terminal gaps, primer sets employed in metabarcoding projects should be evaluated for their sensitivity to slippage. Moreover, steps should be taken to reduce slippage by improving protocols for primer design. For example, the flanking region adjacent to the 3' end of the primer is not considered by current primer development software although GC clamps in this position could mitigate slippage.
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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 | 0.023 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".