Back

A Massively Parallel Screen of 5'UTR Mutations Identifies Variants Impacting Translation and Protein Production in Neurodevelopmental Disorder Genes

Plassmeyer, S. P.; Florian, C. P.; Kasper, M. J.; Chase, R.; Mueller, S.; Liu, Y.; McFarland White, K.; Jungers, C. F.; Pavlovic Djuranovic, S.; Djuranovic, S.; Dougherty, J. D.

2023-11-03 genetic and genomic medicine
10.1101/2023.11.02.23297961 medRxiv
Show abstract

De novo mutations cause a variety of neurodevelopmental disorders including autism. Recent whole genome sequencing from individuals with autism has shown that many de novo mutations also occur in untranslated regions (UTRs) of genes, but it is difficult to predict from sequence alone which mutations are functional, let alone causal. Therefore, we developed a high throughput assay to screen the transcriptional and translational effects of 997 variants from 5'UTR patient mutations. This assay successfully enriched for elements that alter reporter translation, identifying over 100 potentially functional mutations from probands. Studies in patient-derived cell lines further confirmed that these mutations can alter protein production in individuals with autism, and some variants fall in genes known to cause syndromic forms of autism, suggesting a diagnosis for these individual patients. Since UTR function varies by cell type, we further optimized this high throughput assay to enable assessment of mutations in neurons in vivo. First, comparing in cellulo to in vivo results, we demonstrate neurons have different principles of regulation by 5'UTRs, consistent with a more robust mechanism for reducing the impact of RNA secondary structure. Finally, we discovered patient mutations specifically altering the translational activity of additional known syndromic genes LRRC4 and ZNF644 in neurons of the brain. Overall our results highlight a new approach for assessing the impact of 5'UTR mutations across cell types and suggest that some cases of neurodevelopmental disorder may be caused by such variants.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.