Unexpected allelic heterogeneity and spectrum of mutations in Fowler syndrome revealed by next-generation exome sequencing
Why this work is in the frame
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Bibliographic record
Abstract
Protein coding genes constitute approximately 1% of the human genome but harbor 85% of the mutations with large effects on disease-related traits. Therefore, efficient strategies for selectively sequencing complete coding regions (i.e., "whole exome") have the potential to contribute our understanding of human diseases. We used a method for whole-exome sequencing coupling Agilent whole-exome capture to the Illumina DNA-sequencing platform, and investigated two unrelated fetuses from nonconsanguineous families with Fowler Syndrome (FS), a stereotyped phenotype lethal disease. We report novel germline mutations in feline leukemia virus subgroup C cellular-receptor-family member 2, FLVCR2, which has recently been shown to cause FS. Using this technology, we identified three types of genetic abnormalities: point-mutations, insertions-deletions, and intronic splice-site changes (first pathogenic report using this technology), in the fetuses who both were compound heterozygotes for the disease. Although revealing a high level of allelic heterogeneity and mutational spectrum in FS, this study further illustrates the successful application of whole-exome sequencing to uncover genetic defects in rare Mendelian disorders. Of importance, we show that we can identify genes underlying rare, monogenic and recessive diseases using a limited number of patients (n=2), in the absence of shared genetic heritage and in the presence of allelic heterogeneity.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it