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Record W2142896923 · doi:10.1083/jcb.201210019

Global analysis of SUMO chain function reveals multiple roles in chromatin regulation

2013· article· en· W2142896923 on OpenAlexafffund
Tharan Srikumar, Megan Lewicki, Michael Costanzo, Johnny M. Tkach, Harm van Bakel, Kyle Tsui, Erica S. Johnson, Grant W. Brown, Brenda Andrews, Charles Boone, Guri Giaever, Corey Nislow, Brian Raught

Bibliographic record

VenueThe Journal of Cell Biology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer Research
FundersNational Human Genome Research InstituteCanadian Institutes of Health Research
KeywordsBiologyChromatinMutantUbiquitinSaccharomyces cerevisiaeSUMO proteinGeneGeneticsCell biologyPsychological repressionChIA-PETFunction (biology)YeastGene expressionComputational biologyChromatin remodeling

Abstract

fetched live from OpenAlex

Like ubiquitin, the small ubiquitin-related modifier (SUMO) proteins can form oligomeric "chains," but the biological functions of these superstructures are not well understood. Here, we created mutant yeast strains unable to synthesize SUMO chains (smt3(allR)) and subjected them to high-content microscopic screening, synthetic genetic array (SGA) analysis, and high-density transcript profiling to perform the first global analysis of SUMO chain function. This comprehensive assessment identified 144 proteins with altered localization or intensity in smt3(allR) cells, 149 synthetic genetic interactions, and 225 mRNA transcripts (primarily consisting of stress- and nutrient-response genes) that displayed a >1.5-fold increase in expression levels. This information-rich resource strongly implicates SUMO chains in the regulation of chromatin. Indeed, using several different approaches, we demonstrate that SUMO chains are required for the maintenance of normal higher-order chromatin structure and transcriptional repression of environmental stress response genes in budding yeast.

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)0.001
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 score0.333
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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

Citations72
Published2013
Admission routes2
Has abstractyes

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