Gene expression profiling identifies eleven DNA repair genes down-regulated during mouse neural crest cell migration
Bibliographic record
Abstract
Neural Crest Cells (NCCs) are transient multipotent migratory cells that derive from the embryonic neural crest which is itself derived from the margin of the neural tube. DNA repair genes are expressed in the early stages of mammalian development to reduce possible replication errors and genotoxic damage. Some birth defects and cancers are due to inappropriate or defective DNA repair machinery, indicating that the proper functioning of DNA repair genes in the early stages of fetal development is essential for maintaining DNA integrity. We performed a genome-wide expression analysis combining laser capture microdissection (LCM) and high-density oligo-microarray of murine NCCs at pre-migratory embryonic days 8.5 (E8.5), and at E13.5, as well as on neural crest-derived cells from the adrenal medulla at postnatal day 90. We found 11 genes involved in DNA repair activity (response to DNA damage stimulus, DNA damage checkpoint, base-excision repair, mismatch repair), over-expressed in the early stages of mouse embryo development. Expression of these 11 genes was very low or undetectable in the differentiated adrenal medulla of the adult mouse. Amongst the 11 genes, 6 had not been previously reported as being over-expressed during mouse embryonic development. High expression of DNA repair genes in enriched NCCs during early embryonic development may contribute to maintaining DNA integrity whilst failure of some of these genes may be associated with the onset of genetic disease and cancer. Our model of enriched murine NCCs and neural crest-derived cells can be used to elucidate the key roles of genes during normal embryonic development and in cancer pathogenesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".