Short Reads, Circular Genome: Skimming SOLiD Sequence to Construct the Bighorn Sheep Mitochondrial Genome
Bibliographic record
Abstract
As sequencing technology improves, an increasing number of projects aim to generate full genome sequence, even for nonmodel taxa. These projects may be feasibly conducted at lower read depths if the alignment can be aided by previously developed genomic resources from a closely related species. We investigated the feasibility of constructing a complete mitochondrial (mt) genome without preamplification or other targeting of the sequence. Here we present a full mt genome sequence (16,463 nucleotides) for the bighorn sheep (Ovis canadensis) generated though alignment of SOLiD short-read sequences to a reference genome. Average read depth was 1240, and each base was covered by at least 36 reads. We then conducted a phylogenomic analysis with 27 other bovid mitogenomes, which placed bighorn sheep firmly in the Ovis clade. These results show that it is possible to generate a complete mitogenome by skimming a low-coverage genomic sequencing library. This technique will become increasingly applicable as the number of taxa with some level of genome sequence rises.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".