Population-wide DNA methylation polymorphisms at single-nucleotide resolution in 207 cotton accessions reveal epigenomic contributions to complex traits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
DNA methylation plays multiple regulatory roles in crop development. However, the relationships of methylation polymorphisms with genetic polymorphisms, gene expression, and phenotypic variation in natural crop populations remain largely unknown. Here, we surveyed high-quality methylomes, transcriptomes, and genomes obtained from the 20-days-post-anthesis (DPA) cotton fibers of 207 accessions and extended the classical framework of population genetics to epigenetics. Over 287 million single methylation polymorphisms (SMPs) were identified, 100 times more than the number of single nucleotide polymorphisms (SNPs). These SMPs were significantly enriched in intragenic regions while depleted in transposable elements. Association analysis further identified a total of 5,426,782 cis-methylation quantitative trait loci (cis-meQTLs), 5078 cis-expression quantitative trait methylation (cis-eQTMs), and 9157 expression quantitative trait loci (eQTLs). Notably, 36.39% of cis-eQTM genes were not associated with genetic variation, indicating that a large number of SMPs associated with gene expression variation are independent of SNPs. In addition, out of the 1715 epigenetic loci associated with yield and fiber quality traits, only 36 (2.10%) were shared with genome-wide association study (GWAS) loci. The construction of multi-omics regulatory networks revealed 43 cis-eQTM genes potentially involved in fiber development, which cannot be identified by GWAS alone. Among these genes, the role of one encoding CBL-interacting protein kinase 10 in fiber length regulation was successfully validated through gene editing. Taken together, our findings prove that DNA methylation data can serve as an additional resource for breeding purposes and can offer opportunities to enhance and expedite the crop improvement process.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it