Transgenerational Epigenetic Inheritance Is Negatively Regulated by the HERI-1 Chromodomain Protein
Bibliographic record
Abstract
Abstract Transgenerational epigenetic inheritance (TEI) is the inheritance of epigenetic information for two or more generations. In most cases, TEI is limited to a small number of generations (two to three). The short-term nature of TEI could be set by innate biochemical limitations to TEI or by genetically encoded systems that actively limit TEI. In Caenorhabditis elegans, double-stranded RNA (dsRNA)-mediated gene silencing [RNAi (RNA interference)] can be inherited (termed RNAi inheritance or RNA-directed TEI). To identify systems that might actively limit RNA-directed TEI, we conducted a forward genetic screen for factors whose mutation enhanced RNAi inheritance. This screen identified the gene heritable enhancer of RNAi (heri-1), whose mutation causes RNAi inheritance to last longer (> 20 generations) than normal. heri-1 encodes a protein with a chromodomain, and a kinase homology domain that is expressed in germ cells and localizes to nuclei. In C. elegans, a nuclear branch of the RNAi pathway [termed the nuclear RNAi or NRDE (nuclear RNA defective) pathway] promotes RNAi inheritance. We find that heri-1(−) animals have defects in spermatogenesis that are suppressible by mutations in the nuclear RNAi Argonaute (Ago) HRDE-1, suggesting that HERI-1 might normally act in sperm progenitor cells to limit nuclear RNAi and/or RNAi inheritance. Consistent with this idea, we find that the NRDE nuclear RNAi pathway is hyperresponsive to experimental RNAi treatments in heri-1 mutant animals. Interestingly, HERI-1 binds to genes targeted by RNAi, suggesting that HERI-1 may have a direct role in limiting nuclear RNAi and, therefore, RNAi inheritance. Finally, the recruitment of HERI-1 to chromatin depends upon the same factors that drive cotranscriptional gene silencing, suggesting that the generational perdurance of RNAi inheritance in C. elegans may be set by competing pro- and antisilencing outputs of the nuclear RNAi machinery.
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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".