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Record W2468890608 · doi:10.1186/s12864-016-2854-4

Extent of pre-translational regulation for the control of nucleocytoplasmic protein localization

2016· article· en· W2468890608 on OpenAlexafffund
Mikael-Jonathan Luce, Anna Akpawu, Daniel C. Tucunduva, Spencer Mason, Michelle S. Scott

Bibliographic record

VenueBMC Genomics · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversité de Sherbrooke
FundersFaculty of Medicine and Health, University of SydneyNatural Sciences and Engineering Research Council of CanadaUniversité de Sherbrooke
KeywordsBiologyNLSNuclear localization sequenceAlternative splicingExonComputational biologyRNA splicingSubcellular localizationGeneticsFrameshift mutationTranslation (biology)Cell biologyGeneMessenger RNARNA

Abstract

fetched live from OpenAlex

BACKGROUND: Appropriate protein subcellular localization is essential for proper cellular function. Central to the regulation of protein localization are protein targeting motifs, stretches of amino acids serving as guides for protein entry in a specific cellular compartment. While the use of protein targeting motifs is modulated in a post-translational manner, mainly by protein conformational changes and post-translational modifications, the presence of these motifs in proteins can also be regulated in a pre-translational manner. Here, we investigate the extent of pre-translational regulation of the main signals controlling nucleo-cytoplasmic traffic: the nuclear localization signal (NLS) and the nuclear export signal (NES). RESULTS: Motif databases and manual curation of the literature allowed the identification of 175 experimentally validated NLSs and 120 experimentally validated NESs in human. Following mapping onto annotated transcripts, these motifs were found to be modular, most (73 % for NLS and 88 % for NES) being encoded entirely in only one exon. The presence of a majority of these motifs is regulated in an alternative manner at the transcript level (61 % for NLS and 72 % for NES) while the remaining motifs are present in all coding isoforms of their encoding gene. NLSs and NESs are pre-translationally regulated using four main mechanisms: alternative transcription/translation initiation, alternative translation termination, alternative splicing of the exon encoding the motif and frameshift, the first two being by far the most prevalent mechanisms. Quantitative analysis of the presence of these motifs using RNA-seq data indicates that inclusion of these motifs can be regulated in a tissue-specific and a combinatorial manner, can be altered in disease states in a directed way and that alternative inclusion of these motifs is often used by proteins with diverse interactors and roles in diverse pathways, such as kinases. CONCLUSIONS: The pre-translational regulation of the inclusion of protein targeting motifs is a prominent and tightly-regulated mechanism that adds another layer in the control of protein subcellular localization.

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: none
Teacher disagreement score0.605
Threshold uncertainty score0.119

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 head0.008
GPT teacher head0.212
Teacher spread0.205 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

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