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Record W2522920940 · doi:10.1016/j.celrep.2016.08.050

Multivalent Chromatin Engagement and Inter-domain Crosstalk Regulate MORC3 ATPase

2016· article· en· W2522920940 on OpenAlexfundno aff
Forest H. Andrews, Qiong Tong, Kelly D. Sullivan, Evan M. Cornett, Yi Zhang, Muzaffar Ali, Jae‐Woo Ahn, Ahway Pandey, Angela H. Guo, Brian D. Strahl, James C. Costello, Joaquı́n M. Espinosa, Scott B. Rothbart, Tatiana G. Kutateladze

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of General Medical SciencesUniversity of Colorado DenverNational Institute on Alcohol Abuse and AlcoholismRyerson UniversityNational Cancer InstituteNational Institutes of HealthUniversity of Chicago
KeywordsChromatinHistoneCrosstalkCell biologyATPaseBiologyDNAChemistryEnzymeGeneticsBiochemistryPhysics

Abstract

fetched live from OpenAlex

MORC3 is linked to inflammatory myopathies and cancer; however, the precise role of MORC3 in normal cell physiology and disease remains poorly understood. Here, we present detailed genetic, biochemical, and structural analyses of MORC3. We demonstrate that MORC3 is significantly upregulated in Down syndrome and that genetic abnormalities in MORC3 are associated with cancer. The CW domain of MORC3 binds to the methylated histone H3K4 tail, and this interaction is essential for recruitment of MORC3 to chromatin and accumulation in nuclear bodies. We show that MORC3 possesses intrinsic ATPase activity that requires DNA, but it is negatively regulated by the CW domain, which interacts with the ATPase domain. Natively linked CW impedes binding of the ATPase domain to DNA, resulting in a decrease in the DNA-stimulated enzymatic activity. Collectively, our studies provide a molecular framework detailing MORC3 functions and suggest that its modulation may contribute to human disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.241
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations53
Published2016
Admission routes1
Has abstractyes

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