Rapid High Resolution Single Nucleotide Polymorphism–Comparative Genome Hybridization Mapping in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
We have developed a significantly improved and simplified method for high-resolution mapping of phenotypic traits in Caenorhabditis elegans using a combination of single nucleotide polymorphisms (SNPs) and oligo array comparative genome hybridization (array CGH). We designed a custom oligonucleotide array using a subset of confirmed SNPs between the canonical wild-type Bristol strain N2 and the Hawaiian isolate CB4856, populated with densely overlapping 50-mer probes corresponding to both N2 and CB4856 SNP sequences. Using this method a mutation can be mapped to a resolution of approximately 200 kb in a single genetic cross. Six mutations representing each of the C. elegans chromosomes were detected unambiguously and at high resolution using genomic DNA from populations derived from as few as 100 homozygous mutant segregants of mutant N2/CB4856 heterozygotes. Our method completely dispenses with the PCR, restriction digest, and gel analysis of standard SNP mapping and should be easy to extend to any organism with interbreeding strains. This method will be particularly powerful when applied to difficult or hard-to-map low-penetrance phenotypes. It should also be possible to map polygenic traits using this method.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".