Completion of draft bacterial genomes by long-read sequencing of synthetic genomic pools
Bibliographic record
Abstract
BACKGROUND: Illumina technology currently dominates bacterial genomics due to its high read accuracy and low sequencing cost. However, the incompleteness of draft genomes generated by Illumina reads limits their application in comprehensive genomics analyses. Alternatively, hybrid assembly using both Illumina short reads and long reads generated by single molecule sequencing technologies can enable assembly of complete bacterial genomes, yet the high per-genome cost of long-read sequencing limits the widespread use of this approach in bacterial genomics. Here we developed a protocol for hybrid assembly of complete bacterial genomes using miniaturized multiplexed Illumina sequencing and non-barcoded PacBio sequencing of a synthetic genomic pool (SGP), thus significantly decreasing the overall per-genome cost of sequencing. RESULTS: We evaluated the performance of SGP hybrid assembly on the genomes of 20 bacterial isolates with different genome sizes, a wide range of GC contents, and varying levels of phylogenetic relatedness. By improving the contiguity of Illumina assemblies, SGP hybrid assembly generated 17 complete and 3 nearly complete bacterial genomes. Increased contiguity of SGP hybrid assemblies resulted in considerable improvement in gene prediction and annotation. In addition, SGP hybrid assembly was able to resolve repeat elements and identify intragenomic heterogeneities, e.g. different copies of 16S rRNA genes, that would otherwise go undetected by short-read-only assembly. Comprehensive comparison of SGP hybrid assemblies with those generated using multiplexed PacBio long reads (long-read-only assembly) also revealed the relative advantage of SGP hybrid assembly in terms of assembly quality. In particular, we observed that SGP hybrid assemblies were completely devoid of both small (i.e. single base substitutions) and large assembly errors. Finally, we show the ability of SGP hybrid assembly to differentiate genomes of closely related bacterial isolates, suggesting its potential application in comparative genomics and pangenome analysis. CONCLUSION: Our results indicate the superiority of SGP hybrid assembly over both short-read and long-read assemblies with respect to completeness, contiguity, accuracy, and recovery of small replicons. By lowering the per-genome cost of sequencing, our parallel sequencing and hybrid assembly pipeline could serve as a cost effective and high throughput approach for completing high-quality bacterial genomes.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".