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全转录组异常值方法可识别患有轻微剪接变异疾病的个体。

Transcriptome-wide outlier approach identifies individuals with minor spliceopathies.

作者信息

Arriaga Maggie T, Mendez Rodrigo, Ungar Rachel A, Bonner Devon E, Matalon Dena R, Lemire Gabrielle, Goddard Pagé C, Padhi Evin M, Miller Alexander M, Nguyen Jonathon V, Ma Jialan, Smith Kevin S, Scott Stuart A, Liao Linda, Ng Zena, Marwaha Shruti, Bademci Guney, Bivona Stephanie A, Tekin Mustafa, Bernstein Jonathan A, Montgomery Stephen B, O'Donnell-Luria Anne, Wheeler Matthew T, Ganesh Vijay S

机构信息

Dept. of Genetics, Stanford Univ., Stanford, CA.

Department of Medicine, Stanford Univ., Stanford, CA.

出版信息

medRxiv. 2025 Jan 3:2025.01.02.24318941. doi: 10.1101/2025.01.02.24318941.

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 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 outliers in minor intron containing genes (MIGs). 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 individuals with excess intron retention outliers in MIGs, all of which were found to harbor rare, biallelic variants in minor spliceosome snRNAs. Four individuals had rare, compound heterozygous variants in , which aided the reclassification of four variants. Additionally, one individual had rare, highly conserved, compound heterozygous variants in that may disrupt the formation of the catalytic spliceosome, suggesting a novel gene-disease candidate. 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 novel disease gene associations.

摘要

RNA测序提高了罕见病患者的诊断率。目前的分析主要集中在识别单个基因中的异常值,这些异常值可归因于基因座内的顺式作用变异。这种方法忽略了对全转录组剪接具有反式作用的因果变异,例如影响剪接体功能的变异。我们提出了一种先进行转录组学分析的方法,通过检查全转录组范围的剪接异常值模式来诊断罕见病患者。使用剪接异常值检测方法(FRASER和FRASER2),我们对来自基因组学研究以阐明罕见病遗传学(GREGoR)和未确诊疾病网络(UDN)联盟的390名个体的全血中的剪接异常值进行了特征分析。我们检查了所有样本中含小内含子基因(MIG)的内含子保留异常值是否过多。小内含子约占人类基因组所有内含子的0.5%,由小核仁核糖核酸(snRNA)在小剪接体中去除。这种方法确定了5名MIG中内含子保留异常值过多的个体,所有这些个体都被发现小剪接体snRNA中存在罕见的双等位基因变异。4名个体在……中有罕见的复合杂合变异,这有助于对4个变异进行重新分类。此外,1名个体在……中有罕见的、高度保守的复合杂合变异,可能会破坏催化剪接体的形成,提示了一个新的疾病基因候选者。这些结果表明,检查RNA测序数据中的全转录组特征可以提高罕见病患者的诊断率,提供剪接病的变异到功能的解释,并发现新的疾病基因关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7669/11722475/4bba719a6aa1/nihpp-2025.01.02.24318941v1-f0001.jpg

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