A high quality, high molecular weight DNA extraction method for PacBio HiFi genome sequencing of recalcitrant plants
Bibliographic record
Abstract
BACKGROUND: PacBio HiFi sequencing provides highly accurate long-read sequencing datasets which are of great advantage for whole genome sequencing projects. One limitation of the method is the requirement for high quality, high molecular weight input DNA. This can be particularly challenging for plants that frequently contain common and species-specific secondary metabolites, which often interfere with downstream processes. Cape Primroses (genus Streptocarpus), are some of these recalcitrant plants and are selected here as material to develop a high quality, high molecular weight DNA extraction protocol for long read genome sequencing. RESULTS: We developed a DNA extraction method for PacBio HiFi sequencing for Streptocarpus grandis and Streptocarpus kentaniensis. A CTAB lysis buffer was employed to avoid guanidine, and the traditional chloroform and phenol purification steps were replaced with pre-lysis sample washes. Best cells/nucleus lysis was achieved with 4 h at 58 °C. The obtained high quality and high molecular weight DNAs were tested in PacBio SMRTBell™ library preparations, which resulted in circular consensus sequencing (CCS) reads from 17 to 27 Gb per cell, and a read length N50 from 14 to 17 kbp. To evaluate the quality of the reads for whole genome sequencing, they were assembled with HiFiasm into draft genomes, with N50 = 49 Mb and 23 Mb, and L50 = 10 and 11. The longest contigs were 95 Mb and 57 Mb respectively, showing good contiguity as these are longer than the theoretical chromosome length (genome size/chromosome number) of 78 Mb and 55 Mb, for S. grandis and S. kentaniensis respectively. CONCLUSIONS: DNA extraction is a critical step towards obtaining a complete genome assembly. Our DNA extraction method here provided the required high quality, high molecular weight DNA for successful standard-input PacBio HiFi library preparation. The contigs from those reads showed a high contiguity, providing a good starting draft assembly towards obtaining a complete genome. The results obtained here were highly promising, and demonstrated that the DNA extraction method developed here is compatible with PacBio HiFi sequencing and suitable for de novo whole genome sequencing projects of plants.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".