RESEARCH ARTICLE Open Access Copy number variation in the genomes of twelve
Bibliographic record
Abstract
Background: Copy number variation is an important component of genetic variation in higher eukaryotes. The extent of natural copy number variation in C. elegans is unknown outside of 2 highly divergent wild isolates and the canonical N2 Bristol strain. Results: We have used array comparative genomic hybridization (aCGH) to detect copy number variation in the genomes of 12 natural isolates of Caenorhabditis elegans. Deletions relative to the canonical N2 strain are more common in these isolates than duplications, and indels are enriched in multigene families on the autosome arms. Among the strains in our study, the Hawaiian and Madeiran strains (CB4856 and JU258) carry the largest number of deletions, followed by the Vancouver strain (KR314). Overall we detected 510 different deletions affecting 1136 genes, or over 5 % of the genes in the canonical N2 genome. The indels we identified had a median length of 2.7 kb. Since many deletions are found in multiple isolates, deletion loci were used as markers to derive an unrooted tree to estimate genetic relatedness among the strains. Conclusion: Copy number variation is extensive in C. elegans, affecting over 5 % of the genes in the genome. The deletions we have detected in natural isolates of C. elegans contribute significantly to the number of deletion alleles available to researchers. The relationships between strains are complex and different regions of the genome possess different genealogies due to recombination throughout the natural history of the species, which may not be apparent in studies utilizing smaller numbers of genetic markers. Background Copy number variation is an important component of genetic diversity in both Caenorhabditis elegans [1] and humans [2-4] and has been associated with complex traits including autism spectrum disorder [5], mental retardation [6,7], and schizophrenia [8]. Genes involved in sensory perception, innate immunity and cell adhesion are overrepresented in copy number variants (CNVs) [1,2].
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Insufficient payload (model declined to judge) Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".