Full-length transcript amplification and sequencing as universal method to test mRNA integrity and biallelic expression in mismatch repair genes.
Monika MorakKerstin SchaeferVerena Steinke-LangeUdo KoehlerSusanne KeinathTrisari MassdorfBrigitte MauracherNils RahnerJessica BaileyChristiane KlingTanja HaeusserAndreas LanerElke Holinski-FederPublished in: European journal of human genetics : EJHG (2019)
In pathogenicity assessment, RNA-based analyses are important for the correct classification of variants, and require gene-specific cut-offs for allelic representation and alternative/aberrant splicing. Beside this, the diagnostic yield of RNA-based techniques capable to detect aberrant splicing or allelic loss due to intronic/regulatory variants has to be elaborated. We established a cDNA analysis for full-length transcripts (FLT) of the four DNA mismatch repair (MMR) genes to investigate the splicing pattern and transcript integrity with active/inhibited nonsense-mediated mRNA-decay (NMD). Validation was based on results from normal controls, samples with premature termination codons (PTC), samples with splice-site defects (SSD), and samples with pathogenic putative missense variants. The method was applied to patients with variants of uncertain significance (VUS) or unexplained immunohistochemical MMR deficiency. We categorized the allelic representation into biallelic (50 ± 10%) or allelic loss (≤10%), and >10% and <40% as unclear. We defined isoforms up to 10% and exon-specific exceptions as alternative splicing, set the cut-off for SSD in cDNA + P to 30-50%, and regard >10% and <30% as unclear. FLT cDNA analyses designated 16% of all putative missense variants and 12% of VUS as SSD, detected MMR-defects in 19% of the unsolved patients, and re-classified >30% of VUS. Our method allows a standardized, systematic cDNA analysis of the MMR FLTs to assess the pathogenicity mechanism of VUS on RNA level, which will gain relevance for precision medicine and gene therapy. Diagnostic accuracy will be enhanced by detecting MMR defects in hitherto unsolved patients. The data generated will help to calibrate a high-throughput NGS-based mRNA-analysis and optimize prediction programs.
Keyphrases
- copy number
- end stage renal disease
- intellectual disability
- high throughput
- ejection fraction
- newly diagnosed
- acute myeloid leukemia
- genome wide
- chronic kidney disease
- peritoneal dialysis
- machine learning
- public health
- nucleic acid
- gene therapy
- tyrosine kinase
- binding protein
- patient reported outcomes
- dna methylation
- single cell
- artificial intelligence
- rna seq
- escherichia coli
- deep learning
- biofilm formation
- genome wide identification
- neural network
- big data
- circulating tumor cells
- long non coding rna