Researchers at CENTOGENE GmbH aimed to assess the clinical relevance of splicing variants by analyzing the gene expression of blood samples using RNA sequencing (RNA-seq). These variants, which are mutations that affect how genes are spliced during the process of protein production, are important because they can alter normal cellular functions and contribute to various diseases.

To begin, the researchers selected 108 individuals, each of whom had 113 splicing variants previously identified in their genetic analysis. The key idea behind this study was to use the same blood samples (specifically dried blood spots or DBS) that were originally collected for DNA testing, and then perform RNA-sequencing on them. This multiomic approach, combining both genetic and transcriptomic (RNA) information, helps scientists gain a more complete picture of how specific gene variants may impact cellular functions.

The results revealed that 64 of the variants (57%) led to abnormal splicing, a process where the gene is incorrectly “cut” or altered. The most common type of abnormal splicing observed was exon skipping, where parts of the gene are skipped over during splicing, accounting for 48% of the cases. Other types of splicing errors included the use of incorrect splice sites (39%) and intron retention, where non-coding regions of genes remain included in the final RNA product (6%). Some variants could not be fully analyzed due to insufficient sample quality or a low number of sequencing reads.

Schematics showing examples of splicing effects detected

(1) Exon exclusion, (2) Pseudo exon, (3) Cryptic donor splice site with intron retention, (4) Cryptic acceptor splice site with intron retention. Left: The solid line shows the regular splicing pattern, and the dashed lines show the observed abnormal splicing. Right: Resulting transcripts with a red cross indicating a premature stop codon. The red dot indicates the location of the noncoding variant. 

Interestingly, in three patients, the abnormal splicing was linked to reduced enzyme activity, providing further confirmation that these splicing changes were indeed affecting the individuals’ health. The enzymes affected were linked to genes involved in conditions like Tay-Sachs disease (HEXA gene), Pompe disease (GAA gene), and Fabry disease (GLA gene).

This study shows the importance of combining DNA analysis with RNA sequencing to more accurately understand the effects of genetic variants. By using the same sample for both DNA and RNA testing, scientists can obtain a clearer picture of how certain gene changes might impact health. Ultimately, this multiomic approach provides a more thorough method for diagnosing genetic conditions and understanding how specific mutations might contribute to disease.