Chromosome-wide assessment of replication timing for human chromosomes 11q and 21q: disease-related genes in timing-switch regions
Bibliographic record
Abstract
The completion of the human genome sequence will greatly accelerate development of a new branch of bioscience and provide fundamental knowledge to biomedical research. We used the sequence information to measure replication timing of the entire lengths of human chromosomes 11q and 21q. Megabase-sized zones that replicate early or late in S phase (thus early/late transition) were defined at the sequence level. Early zones were more GC-rich and gene-rich than were late zones, and early/late transitions occurred primarily at positions identical to or near GC% transitions. We also found the single nucleotide polymorphism (SNP) frequency was high in the late-replicating and replication-transition regions. In the early/late transition regions, concentrated occurrence of cancer-related genes that include CCND1 encoding cyclin D1 (BCL1), FGF4 (KFGF), TIAM1 and FLI1, was observed. The transition regions contained other disease-related genes including APP associated with familial Alzheimer's disease (AD1), SOD1 associated with familial amyotrophic lateral sclerosis (ALS1) and PTS associated with phenylketonuria. These findings are discussed with respect to the prediction that increased DNA damage occurs in replication-transition regions. We propose that genome-wide assessment of replication timing serves as an efficient strategy for identifying disease-related genes.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".