Nuclease deficiencies alter plasma cell-free DNA methylation profiles
Bibliographic record
Abstract
The effects of DNASE1L3 or DNASE1 deficiency on cell-free DNA (cfDNA) methylation were explored in plasma of mice deficient in these nucleases and in DNASE1L3-deficient humans. Compared to wild-type cfDNA, cfDNA in DNASE1L3-deficient mice was significantly hypomethylated, while cfDNA in DNASE1-deficient mice was hypermethylated. The cfDNA hypomethylation in DNASE1L3-deficient mice was due to increased fragmentation and representation from open chromatin regions (OCRs) and CpG islands (CGIs). These findings were absent in DNASE1-deficient mice, demonstrating the preference of DNASE1 to cleave in hypomethylated OCRs and CGIs. We also observed a substantial decrease of fragment ends at methylated CpGs in the absence of DNASE1L3, thereby demonstrating that DNASE1L3 prefers to cleave at methylated CpGs. Furthermore, we found that methylation levels of cfDNA varied by fragment size in a periodic pattern, with cfDNA of specific sizes being more hypomethylated and enriched for OCRs and CGIs. These findings were confirmed in DNASE1L3-deficient human cfDNA. Thus, we have found that nuclease-mediated cfDNA fragmentation markedly affects cfDNA methylation level on a genome-wide scale. This work provides a foundational understanding of the relationship between methylation, nuclease biology, and cfDNA fragmentation.
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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 | 0.000 | 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) | 0.001 | 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".