Heritability of alternative splicing in the human genome
Bibliographic record
Abstract
Alternative pre-mRNA splicing increases proteomic diversity and provides a potential mechanism underlying both phenotypic diversity and susceptibility to genetic disorders in human populations. To investigate the variation in splicing among humans on a genome-wide scale, we use a comprehensive exon-targeted microarray to examine alternative splicing in lymphoblastoid cell lines (LCLs) derived from the CEPH HapMap population. We show the identification of transcripts containing sequence verified exon skipping, intron retention, and cryptic splice site usage that are specific between individuals. A number of novel alternative splicing events with no previous annotations in either the RefSeq and EST databases were identified, indicating that we are able to discover de novo splicing events. Using family-based linkage analysis, we demonstrate Mendelian inheritance and segregation of specific splice isoforms with regulatory haplotypes for three genes: OAS1, CAST, and CRTAP. Allelic association was further used to identify individual SNPs or regulatory haplotype blocks linked to the alternative splicing event, taking advantage of the high-resolution genotype information from the CEPH HapMap population. In one candidate, we identified a regulatory polymorphism that disrupts a 5' splice site of an exon in the CAST gene, resulting in its exclusion in the mutant allele. This report illustrates that our approach can detect both annotated and novel alternatively spliced variants, and that such variation among individuals is heritable and genetically controlled.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".