Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome
Bibliographic record
Abstract
BACKGROUND: Copy number variation (CNV), an important source of diversity in genomic structure, is frequently found in clusters called CNV regions (CNVRs). CNVRs are strongly associated with segmental duplications (SDs), but the composition of these complex repetitive structures remains unclear. RESULTS: We conducted self-comparative-plot analysis of all mouse chromosomes using the high-speed and large-scale-homology search algorithm SHEAP. For eight chromosomes, we identified various types of large SD as tartan-checked patterns within the self-comparative plots. A complex arrangement of diagonal split lines in the self-comparative-plots indicated the presence of large homologous repetitive sequences. We focused on one SD on chromosome 13 (SD13M), and developed SHEPHERD, a stepwise ab initio method, to extract longer repetitive elements and to characterize repetitive structures in this region. Analysis using SHEPHERD showed the existence of 60 core elements, which were expected to be the basic units that form SDs within the repetitive structure of SD13M. The demonstration that sequences homologous to the core elements (>70% homology) covered approximately 90% of the SD13M region indicated that our method can characterize the repetitive structure of SD13M effectively. Core elements were composed largely of fragmented repeats of a previously identified type, such as long interspersed nuclear elements (LINEs), together with partial genic regions. Comparative genome hybridization array analysis showed that whereas 42 core elements were components of CNVR that varied among mouse strains, 8 did not vary among strains (constant type), and the status of the others could not be determined. The CNV-type core elements contained significantly larger proportions of long terminal repeat (LTR) types of retrotransposon than the constant-type core elements, which had no CNV. The higher divergence rates observed in the CNV-type core elements than in the constant type indicate that the CNV-type core elements have a longer evolutionary history than constant-type core elements in SD13M. CONCLUSIONS: Our methodology for the identification of repetitive core sequences simplifies characterization of the structures of large SDs and detailed analysis of CNV. The results of detailed structural and quantitative analyses in this study might help to elucidate the biological role of one of the SDs on chromosome 13.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".