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Record W7161976999 · doi:10.82308/48898

Quantitative changes in gene expression caused by missense variants in deoxyribonucleic acid repair genes

2014· dissertation· en· W7161976999 on OpenAlexaboutno aff
Lili Li

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsRNA splicingExonMissense mutationGenePMS2PhenotypeExonic splicing enhancerAlternative splicingPopulation

Abstract

fetched live from OpenAlex

Inherited mutations in DNA repair genes are major contributors to familial cancer syndromes. Most pathogenic mutations introduce premature stop codons resulting in the loss of protein function. Missense variants of uncertain pathogenic significance are also often observed. In an attempt to understand the physiological attributes of this category of variants, this thesis analysed two recurrent coding variants using a multi-disciplinary approach. The first variant, PMS2 c.2002A>G, was identified in the Inuit population of Quebec and early onset cancers co-segregate with homozygous status. The second, BRCA2 c.6853A>G, appears to be restricted to the Ashkenazi Jewish population and is frequently recorded in the database of Breast Cancer Information Core (BIC, http://research.nhgri.nih.gov/bic/). Both variants not only cause the substitution of an isoleucine to a valine in the proteins, but also interfere with RNA splicing. The variant PMS2 c.2002 A>G creates a novel 5' splicing site which competes with the authentic one, resulting in biased gene expression. The majority of the transcripts are aberrant ones with a five-base pair deletion and a minority of intact transcripts are still produced. The intact transcripts are translated into a full-length proteins which contribute to the milder phenotype associated with this variant, when compared to phenotypes caused by homozygous truncating PMS2 mutations. The variant BRCA2 c.6853A>G disrupts a splicing enhancer promoting the skipping of exon 12, an in-frame exon that does not code for any known functional domains. No detectable phenotype is caused by this variant.The work described in this thesis generated significant medical insights into hereditary syndrome. First, we demonstrated that the inclusion of expression analysis in gene test can improve the accuracy of predicting the functional significance of a candidate variant. Second, manipulating gene expression may be a potential avenue of preventing recessive diseases. Finally, phenotypic variation may be caused by multiple factors, so predicting disease risk solely based on DNA sequence should be practised cautiously with full awareness of the limitation.

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 score0.004

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)0.0010.000

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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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