Transcriptome-wide outlier approach identifies individuals with minor spliceopathies.

Abstract

RNA sequencing has improved the diagnostic yield of individuals with rare diseases. Current analyses predominantly focus on identifying outliers in single genes that can be attributed to cis-acting variants within the gene locus. This approach overlooks causal variants with trans-acting effects on splicing transcriptome wide, such as variants impacting spliceosome function. We present a transcriptomics-first method to diagnose individuals with rare diseases by examining transcriptome-wide patterns of splicing outliers. Using splicing outlier detection methods (FRASER and FRASER2), we characterized splicing outliers from whole blood for 385 individuals from the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) and Undiagnosed Diseases Network (UDN) consortia. We examined all individuals for excess intron retention outliers in minor intron-containing genes (MIGs). Minor introns, which account for 0.5% of all introns in the human genome, are removed by small nuclear RNAs (snRNAs) in the minor spliceosome. This approach identified five individuals with excess intron retention outliers in MIGs, all of whom were found to harbor rare, bi-allelic variants in minor spliceosome snRNAs. Four individuals had rare, compound heterozygous variants in RNU4ATAC, which aided the reclassification of four variants. Additionally, one individual had rare, highly conserved, compound heterozygous variants in RNU6ATAC that may disrupt the formation of the catalytic spliceosome, suggesting it is a gene associated with Mendelian disease. These results demonstrate that examining RNA-sequencing data for transcriptome-wide signatures can increase the diagnostic yield of individuals with rare diseases, provide variant-to-function interpretation of spliceopathies, and uncover gene-disease associations.