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Record W1985768944 · doi:10.1101/gr.4456006

Identification by full-coverage array CGH of human DNA copy number increases relative to chimpanzee and gorilla

2005· article· en· W1985768944 on OpenAlexafffund
Gary M. Wilson, Stéphane Flibotte, Perseus I. Missirlis, Marco A. Marra, Steven J.M. Jones, Kevin Thornton, Andrew G. Clark, Robert A. Holt

Bibliographic record

VenueGenome Research · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsCanada's Michael Smith Genome Sciences Centre
FundersNational Human Genome Research InstituteBC Cancer AgencyCanadian Institutes of Health ResearchNational Institutes of HealthMichael Smith Health Research BC
KeywordsBiologyGorillaIdentification (biology)GeneticsDNACopy-number variationLow copy numberComputational biologyEvolutionary biologyGeneGenomePaleontology

Abstract

fetched live from OpenAlex

Duplication of chromosomal segments and associated genes is thought to be a primary mechanism for generating evolutionary novelty. By comparative genome hybridization using a full-coverage (tiling) human BAC array with 79-kb resolution, we have identified 63 chromosomal segments, ranging in size from 0.65 to 1.3 Mb, that have inferred copy number increases in human relative to chimpanzee. These segments span 192 Ensembl genes, including 82 gene duplicates (41 reciprocal best BLAST matches). Synonymous and nonsynonymous substitution rates across these pairs provide evidence for general conservation of the amino acid sequence, consistent with the maintenance of function of both copies, and one case of putative positive selection for an uncharacterized gene. Surprisingly, the core histone genes H2A, H2B, H3, and H4 have been duplicated in the human lineage since our split with chimpanzee. The observation of increased copy number of a human cluster of core histone genes suggests that altered dosage, even of highly constrained genes, may be an important evolutionary mechanism.

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 score0.066
Threshold uncertainty score0.405

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 head0.018
GPT teacher head0.320
Teacher spread0.302 · 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
Published2005
Admission routes2
Has abstractyes

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