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Massively parallel reporter assays discover de novo exonic splicing mutants in paralogs of Autism genes.

ABSTRACT: To determine the contribution of defective splicing in Autism Spectrum Disorders (ASD), the most common neurodevelopmental disorder, a high throughput Massively Parallel Splicing Assay (MaPSY) was employed and identified 42 exonic splicing mutants out of 725 coding de novo variants discovered in the sequencing of ASD families. A redesign of the minigene constructs in MaPSY revealed that upstream exons with strong 5' splice sites increase the magnitude of skipping phenotypes observed in downstream exons. Select hits were validated by RT-PCR and amplicon sequencing in patient cell lines. Exonic splicing mutants were enriched in probands relative to unaffected siblings -especially synonymous variants (7.5% vs 3.5%, respectively). Of the 26 genes disrupted by exonic splicing mutations, 6 were in known ASD genes and 3 were in paralogs of known ASD genes. Of particular interest was a synonymous variant in TNRC6C - an ASD gene paralog with interactions with other ASD genes. Clinical records of 3 ASD patients with TNRC6C variant revealed respiratory issues consistent with phenotypes observed in TNRC6 depleted mice. Overall, this study highlights the need for splicing analysis in determining variant pathogenicity, especially as it relates to ASD.

SUBMITTER: Rhine CL

PROVIDER: S-EPMC8775188 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Motivation:The majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRAs), have been used to functionally validate non-coding variants. However, we are still missing high-quality and robust data analysis tools for these datasets. Results:We have further developed our method for allele-specific analysis QuASAR (quantitative allele-specific analysis of reads) to analyze allele-specific signals in barcoded read counts data from MPRA. Using this approach, we can take into account the uncertainty on the original plasmid proportions, over-dispersion, and sequencing errors. The provided allelic skew estimate and its standard error also simplifies meta-analysis of replicate experiments. Additionally, we show that a beta-binomial distribution better models the variability present in the allelic imbalance of these synthetic reporters and results in a test that is statistically well calibrated under the null. Applying this approach to the MPRA data, we found 602 SNPs with significant (false discovery rate 10%) allele-specific regulatory function in LCLs. We also show that we can combine MPRA with QuASAR estimates to validate existing experimental and computational annotations of regulatory variants. Our study shows that with appropriate data analysis tools, we can improve the power to detect allelic effects in high-throughput reporter assays. Availability and implementation:http://github.com/piquelab/QuASAR/tree/master/mpra. Contact:fluca@wayne.edu or rpique@wayne.edu. Supplementary information:Supplementary data are available online at Bioinformatics.

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Massively parallel reporter assays discover de novo exonic splicing mutants in paralogs of Autism genes.

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