Critical Evaluation of Imprinted Gene Expression by RNA–Seq: A New Perspective
Bibliographic record
Abstract
In contrast to existing estimates of approximately 200 murine imprinted genes, recent work based on transcriptome sequencing uncovered parent-of-origin allelic effects at more than 1,300 loci in the developing brain and two adult brain regions, including hundreds present in only males or females. Our independent replication of the embryonic brain stage, where the majority of novel imprinted genes were discovered and the majority of previously known imprinted genes confirmed, resulted in only 12.9% concordance among the novel imprinted loci. Further analysis and pyrosequencing-based validation revealed that the vast majority of the novel reported imprinted loci are false-positives explained by technical and biological variation of the experimental approach. We show that allele-specific expression (ASE) measured with RNA-Seq is not accurately modeled with statistical methods that assume random independent sampling and that systematic error must be accounted for to enable accurate identification of imprinted expression. Application of a robust approach that accounts for these effects revealed 50 candidate genes where allelic bias was predicted to be parent-of-origin-dependent. However, 11 independent validation attempts through a range of allelic expression biases confirmed only 6 of these novel cases. The results emphasize the importance of independent validation and suggest that the number of imprinted genes is much closer to the initial estimates.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".