The limitations of draft assemblies for understanding prokaryotic adaptation and evolution
Bibliographic record
Abstract
The de novo assembly of next generation sequencing data is a daunting task made more difficult by the presence of genomic repeats or transposable elements, resulting in an increasing number of genomes designated as completed draft assemblies. We created and assembled idealized sequence data sets for Cupriavidus metallidurans CH34, Caulobacter sp. K31, Gramella forsetii KT0803, Rhodobacter sphaeroides 2.4.1 and Bordetella bronchiseptica RB50. In addition to confirming the role of transposable elements in interrupting the assemblies, an association was found between the most fragmented regions and known or predicted genomic islands in these strains. Assembly quality was more strongly related to putative genomic island content than to any other factor examined. We believe this association indicates that draft assemblies are limiting our ability to understand the genomic context of important bacterial adaptations and that the increased effort required for finishing genomes can provide a wealth of information for future studies.
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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 | 0.037 | 0.238 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".