Abstract
Presentation Description :
Noncoding variants in the gene body often cause diseases by altering splicing sites to include intronic sequences or exclude exonic sequences in the mature mRNA, leading to mainly loss of normal protein function. These disease-associated splicing variants are typically identified by in silico prediction tools and verified by RNA analyses or minigene assays after showing alternative splicing sites were used. We found that some disease-associated candidate splicing variants do not alter mRNA splicing sites in minigene assays. We deployed a quantitative minigene (qMini) assay and discovered that these variants caused diminished mature mRNA levels. We further showed that the precursor mRNA levels were not altered by these variants, suggesting that they represent a novel class of previously overlooked splicing variants that decrease the splicing machinery efficiency. Further identification and characterization of these variants may lead to novel insights into the splicing mechanisms. These variants are often not predicted to cause splicing defects by the existing in silico prediction tools. Thus, we designed a new efficient platform to perform high-throughput minigene assays followed by both sequence analyses and quantification. Creating a larger catalog of this class of variants would allow the development of new in silico tools that may facilitate genetic diagnosis and research.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.