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Record W2059478287 · doi:10.5339/qfarf.2012.bmp54

Identification of novel genes causing autosomal recessive disorders in Qatari population using whole exome sequencing

2012· article· en· W2059478287 on OpenAlexaff
Somayyeh Fahiminiya, Mariam Almuriekhi, Zafar Nawaz, Alfredo Staffa, Jacek Majewski, Tawfeg Ben‐Omran

Bibliographic record

VenueQatar Foundation Annual Research Forum Volume 2012 Issue 1 · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsMcGill University and Génome Québec Innovation Centre
Fundersnot available
KeywordsGeneticsExome sequencingBiologyConsanguinityExomePopulation1000 Genomes ProjectCandidate geneDisease gene identificationAllele frequencyGeneAlleleMutationMedicineGenotypeSingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

Background Consanguinity and endogamy are common in the Middle East, resulting in a higher frequency of autosomal recessive (AR) disorders. This consanguinity facilitates discovery of disease causative genes particularly after introduction of the new techniques such as Whole Exome Sequencing (WES). In order to reduce the overall socio-economic burden of such diseases, the development of diagnostic tools and prevention strategies must be a priority. To achieve these goals, the causal genes underlying human genetic diseases should be first discovered. The goal of this study is to identify novel genes causing AR diseases in Qatari population using WES. Methods Genomic DNAs were captured with the Illumina TruSeq library and sequenced with Illumina HiSeq2000. The reads were aligned to the reference genome using BWA. Variants calling and annotation were performed by SAMtools and ANNOVAR, respectively. Novel variants were defined as those having an allele frequency <0.05 in the 1000 Genomes database and predicted to be nonsynonymous substitutions. Results WES was applied on affected individuals of 3 consanguineous families with Mental Retardation (MR: 2 siblings), Peripheral Neuropathy (PN: 2 siblings) and Eye Anomaly (EA: 1 male). The mode of inheritance was assumed to be AR in MR and PN families. This led to identification of 3 and 4 homozygous candidate variants, shared by two siblings, respectively. The mode of inheritance in EA was considered to be AR and/or X-linked that led to the identification of 26 autosomal homozygous and 6 X-linked genes. The function of one of the genes on X-chromosome was related to the patient phenotype. Conclusions These preliminary interesting results highlight the power of WES, to identify potential candidate genes for AR disorders. The identified genes will be considered for functional follow-up investigation and further characterization. However, our results also highlight that the large number of population-specific variants - which may be common polymorphisms in Qatar but are so far absent from public databases - make diagnosis and discovery more difficult than in well-studied Caucasian populations. We urge genetics researchers in Qatar to actively participate in the creation of a local variant database, which will greatly facilitate such future studies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.654

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 head0.045
GPT teacher head0.367
Teacher spread0.322 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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