SUsPECT: a pipeline for variant effect prediction based on custom long-read transcriptomes for improved clinical variant annotation

Abstract

Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular if they affect transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are not predicted to be pathogenic using the reference transcript annotation. In further support of SUsPECT's utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

Keywords: Computational pipeline; Immune response; Medical diagnostics; Primary immunodeficiencies; Rare diseases; Variant effect prediction.

Fig. 1

Premise for the creation of SUsPECT. (A) Some pathogenic variants may be missed without actual information about all alternative transcripts expressed in a relevant sample. A variant in a particular genomic position may be incorrectly predicted to be non-deleterious. (B) A variant at the same genomic position may cause a different missense variant in different transcript structures due to varying open reading frames per transcript

Fig. 2

Reannotation with SUsPECT. (A) Defining “more severe”. The five categories of severity are modifier, low, moderate, damaging missense and high. We consider levels 3 and 4 to be deleterious, and thus potentially pathogenic. (B) The schematic of the pipeline

Fig. 3

Two examples of ClinVar pathogenic variants being reannotated. Both variants were considered low severity variants when using hg38 reference transcriptome to annotate. (A) IFNGR1 whole view and close-up of region around the variant. Variant causes a stop-gain effect (K>*) in the custom transcript novelT001005410. (B) STAT1 whole view and close-up of region around variant. Variant causes a start loss (M > T) in the custom transcript novelT001115628