Independent recruitment of PRC1 and PRC2 by human XIST
Bibliographic record
Abstract
Abstract XIST establishes inactivation across its chromosome of origin, even when expressed from autosomal transgenes. To identify the regions of human XIST essential for recruiting heterochromatic marks we generated a series of overlapping deletions in an autosomal inducible XIST transgene. We examined the ability of each construct to enrich its unified XIST territory with the histone marks established by PRC1 and PRC2 as well as the heterochromatin factors MacroH2A and SMCHD1. PRC1 recruitment required four distinct regions of XIST, and these were completely distinct from the two domains crucial for PRC2 recruitment. Both the domains required and the impact of inhibitors suggest that PRC1 is required for SMCHD1 while PRC2 function is necessary for MacroH2A recruitment, although incomplete overlap of regions implicates a role for additional factors. The independence of the PRC1/PRC2 pathways, yet important of all regions tested, demonstrate both modularity and cooperativity across the XIST lncRNA. Author Summary XIST functions as a long, non-protein coding, RNA to initiate various pathways for the silencing of one of the two X chromosomes in female placental mammals. CRISPR-directed mutations of an inducible human XIST construct in somatic cells allowed us to discover which regions of the RNA are required for chromatin modification and protein recruitment. This was the first large-scale dissection of human XIST domains, and every function assessed was dependent on multiple regions of XIST, suggesting considerable interactions between domains of XIST. We observed similarities, but also differences, with the domains previously identified in mouse Xist and demonstrated the presence of independent pathways for chromosome reorganization in humans as well as ascribing new functionality to regions of XIST. The ability of XIST to inactivate large sections of chromosomes from which it is expressed makes it both an exciting potential therapeutic for chromosome number abnormalities as well as a paradigm for how non-coding RNA genes are able to regulate cellular biology.
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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) | 0.002 | 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 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".