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Record W4384008411 · doi:10.15252/embr.202256512

MOV10 recruits DCP2 to decap human LINE‐1 RNA by forming large cytoplasmic granules with phase separation properties

2023· article· en· W4384008411 on OpenAlexaff
Qian Liu, Dongrong Yi, Jiwei Ding, Yang Mao, Shujie Wang, Ling Ma, Quanjie Li, Jing Wang, Yongxin Zhang, Jianyuan Zhao, Saisai Guo, Zhenlong Liu, Fei Guo, Dongbing Zhao, Liang Chen, Xiaoyu Li, Xiaozhong Peng, Shan Cen

Bibliographic record

VenueEMBO Reports · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill UniversityJewish General Hospital
FundersChinese Academy of Medical Sciences Initiative for Innovative MedicineNational Natural Science Foundation of ChinaMassachusetts Department of Agricultural Resources
KeywordsRNACell biologyRNA interferenceBiologyCytoplasmEffectorChemistryGeneticsGene

Abstract

fetched live from OpenAlex

Long interspersed element 1 (LINE-1) is the only active autonomous mobile element in the human genome. Its transposition can exert deleterious effects on the structure and function of the host genome and cause sporadic genetic diseases. Tight control of LINE-1 mobilization by the host is crucial for genetic stability. In this study, we report that MOV10 recruits the main decapping enzyme DCP2 to LINE-1 RNA and forms a complex of MOV10, DCP2, and LINE-1 RNP, exhibiting liquid-liquid phase separation (LLPS) properties. DCP2 cooperates with MOV10 to decap LINE-1 RNA, which causes degradation of LINE-1 RNA and thus reduces LINE-1 retrotransposition. We here identify DCP2 as one of the key effector proteins determining LINE-1 replication, and elucidate an LLPS mechanism that facilitates the anti-LINE-1 action of MOV10 and DCP2.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.001

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.

Opus teacher head0.030
GPT teacher head0.343
Teacher spread0.313 · 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 source (direct Gemma or distilled Codex), 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

Citations17
Published2023
Admission routes1
Has abstractyes

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