Novel MYO1D Missense Variant Identified Through Whole Exome Sequencing and Computational Biology Analysis Expands the Spectrum of Causal Genes of Laterality Defects
Bibliographic record
Abstract
Laterality defects (LDs) or asymmetrically positioned organs are a group of rare developmental disorders caused by environmental and/or genetic factors. However, the exact molecular pathophysiology of LD is not yet fully characterised. In this context, studying Arab population presents an ideal opportunity to discover the novel molecular basis of diseases owing to the high rate of consanguinity and genetic disorders. Therefore, in the present study, we studied the molecular basis of LD in Arab patients, using next-generation sequencing method. We discovered an extremely rare novel missense variant in MYO1D gene (Pro765Ser) presenting with visceral heterotaxy and left isomerism with polysplenia syndrome. The proband in this index family has inherited this homozygous variant from her heterozygous parents following the autosomal recessive pattern. This is the first report to show MYO1D genetic variant causing left–right axis defects in humans, besides previous known evidence from zebrafish, frog and Drosophila models. Moreover, our multilevel bioinformatics-based structural (protein variant structural modelling, divergence, and stability) analysis has suggested that Ser765 causes minor structural drifts and stability changes, potentially affecting the biophysical and functional properties of MYO1D protein like calmodulin binding and microfilament motor activities. Functional bioinformatics analysis has shown that MYO1D is ubiquitously expressed across several human tissues and is reported to induce severe phenotypes in knockout mouse models. In conclusion, our findings show the expanded genetic spectrum of LD, which could potentially pave way for the novel drug target identification and development of personalised medicine for high-risk families.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".