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Transcriptome-wide outlier approach identifies individuals with minor spliceopathies

剪接体 内含子 小剪接体 RNA剪接 生物 遗传学 转录组 基因 选择性拼接 计算生物学 基因组学 从头转录组组装 基因组 核糖核酸 外显子 基因表达
作者
Taylor Maurer,Rodrigo Mendez,Rachel A. Ungar,Devon Bonner,Dena R. Matalon,Gabrielle Lemire,Pagé C. Goddard,Evin M. Padhi,Alexander M Miller,J. Nguyen,Jialan Ma,Kevin S. Smith,Stuart A. Scott,Linda M. Liao,Zena Ng,Shruti Marwaha,Güney Bademci,Stephanie Bivona,Mustafa Tekin,Jonathan A. Bernstein
出处
期刊:Cold Spring Harbor Laboratory - medRxiv 被引量:1
标识
DOI:10.1101/2025.01.02.24318941
摘要

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 or near that gene. 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 identified splicing outliers from whole blood for 390 individuals from the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) and Undiagnosed Diseases Network (UDN) consortia. We examined all samples for excess intron retention events in minor intron containing genes. Minor introns, which make up about 0.5% of all introns in the human genome, are removed by small nuclear RNAs (snRNAs) in the minor spliceosome. This approach identified five cases with excess intron retention events in minor intron containing genes, all of which were found to harbor rare, biallelic variants in the minor spliceosome snRNAs. Four had rare, compound heterozygous variants in RNU4ATAC. These results led to the reclassification of four variants. Additionally, one case had rare, highly conserved, compound heterozygous variants in RNU6ATAC that may disrupt the formation of the catalytic spliceosome, suggesting a novel disease-gene candidate. These results demonstrate that examining RNA-sequencing data for known transcriptome-wide signatures can increase the diagnostic yield of individuals with rare diseases, provide variant-to-functional interpretation of spliceopathies, and potentially uncover novel disease genes.

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