Complete Reference Genome and Pangenome Expand Biologically Relevant Information for Genome-Wide DNA Methylation Analysis Using Short-Read Sequencing and Array Data
Bibliographic record
Abstract
Abstract Background The new complete telomere-to-telomere human genome assembly, T2T-CHM13, and the first draft of the human pangenome reference provide unique opportunities to update the reference genome for epigenetics investigations and clinical research. However, it is largely unclear how these reference genome updates may impact DNA methylation (DNAm) analysis. Results Compared to the previous GRCh38 assembly, we found an average increase of 7.4% (range 5.4%–9.9% across samples and sequencing methods) in the number of CpGs genome-wide using T2T-CHM13 with data from four commonly used short-read sequencing DNAm profiling methods. The increase in number of CpGs facilitated discovery of 88 new differentially methylated CpGs within cancer driver genes in an epigenome-wide association study (EWAS) of colon cancer. Further, by aligning probe sequences from the commonly used and recently released Illumina DNAm arrays to T2T-CHM13 and GRCh38, we showed the enhanced utility of T2T-CHM13 for evaluation of potential probe cross-reactivity (i.e., where probes match multiple regions) and mismatch (i.e., where probes do not perfectly match the target region), resulting in the identification of new and more reproducible sets of unambiguous probes (i.e., probes uniquely mapping to the target region) (HM450K, n = 430,719; EPIC, n = 777,491; EPICv2, n = 859,216). In EWASs of 24 cancer types, an average of 945 additional differentially methylated CpG sites were identified in the new unambiguous probe set rather than in the GRCh38-based unambiguous probe set, with enrichments in cancer driver genes and cancer signaling pathways. Moreover, the pangenome called 4.5% more CpGs on average in short-read sequencing data than T2T-CHM13 and identified cross-population and population-specific unambiguous probes in DNAm arrays, owing to its improved representation of genetic diversity. These additional CpGs were overlapped with the promoters and gene bodies of various biologically and medically relevant genes and pangenome-based unambiguous probes can potentially facilitate the discovery of DNAm alterations in more than 200 cancer driver genes in each cancer type. Conclusions Use of T2T-CHM13 and pangenome references can benefit epigenome-wide association studies by including CpGs previously unobserved in short-read sequencing data and by improving the identification of unambiguous probes for DNAm arrays, thus expanding biologically relevant information. This study highlights the practical applications of T2T-CHM13 and pangenome for genome biology and provides a basis for expansion of epigenetics investigations.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".