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Record W1898015186 · doi:10.1093/genetics/157.4.1543

Novel Role for a <i>Saccharomyces cerevisiae</i> Nucleoporin, Nup170p, in Chromosome Segregation

2001· article· en· W1898015186 on OpenAlexaff
Oliver Kerscher, Philip Hieter, Mark Winey, Munira A. Basrai

Bibliographic record

VenueGenetics · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of British Columbia
FundersNational Institute of General Medical SciencesNational Cancer Institute
KeywordsKinetochoreBiologyGeneticsNucleoporinSaccharomyces cerevisiaeChromosome segregationMutantSynthetic lethalityGeneChromosomeNuclear proteinTranscription factor

Abstract

fetched live from OpenAlex

We determined that a mutation in the nucleoporin gene NUP170 leads to defects in chromosome transmission fidelity (ctf) and kinetochore integrity in Saccharomyces cerevisiae. A ctf mutant strain, termed s141, shows a transcription readthrough phenotype and stabilizes a dicentric chromosome fragment in two assays for kinetochore integrity. Previously, these assays led to the identification of two essential kinetochore components, Ctf13p and Ctf14p. Thus, s141 represents another ctf mutant involved in the maintenance of kinetochore integrity. We cloned and mapped the gene complementing the ctf mutation of s141 and showed that it is identical to the S. cerevisiae NUP170 gene. A deletion strain of NUP170 (nup170 Delta::HIS3) has a Ctf(-) phenotype similar to the s141 mutant (nup170-141) and also exhibits a kinetochore integrity defect. We identified a second nucleoporin, NUP157, a homologue of NUP170, as a suppressor of the Ctf(-) phenotype of nup170-141 and nup170 Delta::HIS3 strains. However, a deletion of NUP157 or several other nucleoporins did not affect chromosome segregation. Our data suggest that NUP170 encodes a specialized nucleoporin with a unique role in chromosome segregation and possibly kinetochore function.

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 score0.285
Threshold uncertainty score0.523

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 head0.016
GPT teacher head0.275
Teacher spread0.259 · 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

Citations50
Published2001
Admission routes1
Has abstractyes

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