Genetic diagnosis of Mendelian disorders via RNA sequencing

Abstract

44Across a large variety of Mendelian disorders, ~50-75% of patients do not receive a 45 genetic diagnosis by whole exome sequencing indicative of underlying disease-causing 46 variants in non-coding regions. In contrast, whole genome sequencing facilitates the 47 discovery of all genetic variants, but their sizeable number, coupled with a poor 48 understanding of the non-coding genome, makes their prioritization challenging. Here, we 49 demonstrate the power of transcriptome sequencing to provide a confirmed genetic 50 diagnosis for 10% (5 of 48) of undiagnosed mitochondrial disease patients and identify 51 strong candidate genes for patients remaining without diagnosis. We found a median of 1 52 aberrantly expressed gene, 5 aberrant splicing events, and 6 mono-allelically expressed 53 rare variants in patient-derived fibroblasts and established disease-causing roles for each 54 kind. Private exons often arose from sites that are weakly spliced in other individuals, 55providing an important clue for future variant prioritization. One such intronic exon-56 creating variant was found in three unrelated families in the complex I assembly factor 57 TIMMDC1, which we consequently established as a novel disease-associated gene. In 58 conclusion, our study expands the diagnostic tools for detecting non-exonic variants of 59Mendelian disorders and provides examples of intronic loss-of-function variants with 60 pathological relevance. 61Despite the revolutionizing impact of whole exome sequencing (WES) on the molecular 62 genetics of Mendelian disorders, ~50-75% of the patients do not receive a genetic diagnosis after 63 WES [1][2][3][4][5][6] . The disease-causing variants might be detected by WES but remain as variants of 64 unknown significance (VUS, Methods) or they are missed due to the inability to prioritize them. 65Many of these VUS are synonymous or non-coding variants that may affect RNA abundance or 66 isoform but cannot be prioritized due to the poor understanding of regulatory sequence to date 67 compared to coding sequence. Furthermore, WES covers only the 2% exonic regions of the 68 genome. Accordingly, it is mostly blind to regulatory variants in non-coding regions that could 69 affect RNA sequence and abundance. While the limitation of genome coverage is overcome by 70 whole genome sequencing (WGS), prioritization and interpretation of variants identified by 71 WGS is in turn limited by their amount [7][8][9] . 72With RNA sequencing (RNA-seq), limitations of the sole genetic information can be 73 complemented by directly probing variations in RNA abundance and in RNA sequence, 74 including allele-specific expression and splice isoforms. At least three extreme situations can be 75 directly interpreted to prioritize candidate disease-causing genes for a rare disorder. First, the 76 expression level of a gene can lie outside its physiological range. Genes with expression outside 77 their physical range can be identified as expression outliers, often using a stringent cutoff on 78 expression variat...

A diagnostic ceiling for exome sequencing in cerebellar ataxia and related neurological disorders

“…Furthermore, variants whose effect is determined in combination with additional genes (digenic, polygenic), epigenetic, or environmental factors, or causal mutations in the noncoding genome that affect gene regulation would be difficult to detect by current DNA‐only methods. The application of “multi‐omic” strategies is increasingly being applied to facilitate variant interpretation by assessing their effects on the transcriptome, including alteration in messenger RNA splicing (Cummings et al, ; Elsaid et al, ; Kremer et al, ). Coupling next‐generation sequencing methods with transcriptome analysis has already shown diagnostic utility in other rare diseases (Lee et al, ).…”

Bi-allelic mutations in TRAPPC2L result in a neurodevelopmental disorder and have an impact on RAB11 in fibroblasts

“…Next-generation whole exome sequencing (WES)5 was performed on DNA extracted from peripheral blood from probands and their parents. In brief, coding regions were enriched using a SureSelect Human All Exon V5 kit (Agilent) or TruSeq (Illumina) followed by sequencing as 100 bp paired-end runs on an Illumina HiSeq4000.…”

Genomic testing in myeloid malignancy

“…For example, the LSC17 gene expression signature can identify patients with higher and lower risk in AML. In Mendelian disorders, RNA‐seq has proved a useful method to identify novel disease‐associated genes, through the use of outlier expression, monoallelic expression, and splicing analyses . Translation of RNA‐seq into the clinic is challenging due to both inter‐ and intralaboratory technical variation in establishing appropriate thresholds …”