Exploration into the MLL4/WRAD Enzyme-Substrate Network: Systematic Identification of CFP1 as a Non-Histone Substrate of the MLL4 Lysine Methyltransferase
Bibliographic record
Abstract
Histone lysine methyltransferases (KMTs) are key actors in the regulation of the cell's most critical functions, including but by no means limited to gene expression, DNA damage repair, and cell differentiation.Histone KMTs impart control over these processes by remodelling chromatin through the modification of histone N-tail lysine residues.While historically studied exclusively within the context of histones, emerging evidence points to a broader role for histone KMTs, specifically through the lysine methylation of non-histone proteins.In this thesis, I investigate nonhistone lysine methylation activity of the KMT2-class enzyme MLL4, characterized by its monomethylation activity on histone H3K4 at distal enhancer regions and devoid of other known substrates.Through tandem shotgun and systematic approaches, I identify the histone KMTassociated regulatory protein CXXC finger protein 1 as a novel substrate of MLL4, and conduct in vitro investigation of the potential functional consequences of this methylation event.iv Acknowledgments First and foremost, I would like to thank my advisor Dr. Kyle Biggar for providing me with constant support, guidance, and encouragement, without which I would not have been able to achieve this accomplishment.Thank you to the Couture lab at uOttawa for providing me with advice and plasmids used in these experiments.Thank you to Anand, Hemanta, Matt, and all of the other Biggar lab members.This work could not have been completed without their support in the conduct and troubleshooting of experiments, nor without the welcoming and fun working environment they helped create.I am grateful for the love
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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".