Evaluation in Monogenic Diabetes of the Impact of GCK, HNF1A, and HNF4A Variants on Splicing through the Combined Use of In Silico Tools and Minigene Assays

Abstract

Variants in GCK, HNF1A, and HNF4A genes are the three main causes of monogenic diabetes. Determining the molecular etiology is essential for patients with monogenic diabetes to benefit from the most appropriate treatment. The increasing number of variants of unknown significance (VUS) is a major issue in genetic diagnosis, and assessing the impact of variants on RNA splicing is challenging, particularly for genes expressed in tissues not easily accessible as in monogenic diabetes. The in vitro functional splicing assay based on a minigene construct is an appropriate approach. Here, we performed in silico analysis using SpliceAI and SPiP and prioritized 36 spliceogenic variants in GCK, HNF1A, and HNF4A. Predictions were secondarily compared with Pangolin and AbSplice-DNA bioinformatics tools which include tissue-specific annotations. We assessed the effect of selected variants on RNA splicing using minigene assays. These assays validated splicing defects for 33 out of 36 spliceogenic variants consisting of exon skipping (15%), exonic deletions (18%), intronic retentions (24%), and complex splicing patterns (42%). This provided additional evidence to reclassify 23 out of 31 (74%) VUS including missense, synonymous, and intronic noncanonical splice site variants as likely pathogenic variants. Comparison of in silico analysis with minigene results showed the robustness of bioinformatics tools to prioritize spliceogenic variants, but revealed inconsistencies in the location of cryptic splice sites underlying the importance of confirming predicted splicing alterations with functional splicing assays. Our study underlines the feasibility and the benefits of implementing minigene-splicing assays in the genetic testing of monogenic diabetes after a prior in-depth in silico analysis.

Figure 1

Variant selection for minigene assays. This flowchart shows the sequential steps of variant selection. ^∗Exclusion of canonic splice sites (-1 and -2; +1 and +2), nonsense, and frameshift variants. ^∗∗Four variants located in the exon 1 requiring specific plasmid construction were excluded. In our series, no variant was located in the last exons. VUS: variant of unknown significance; LP: likely pathogenic; P: pathogenic.

Figure 2

Overview of the 36 spliceogenic variants tested by minigene assays. (a) Location of the variants on GCK (N = 25), HNF1A (N = 8), and HNF4A (N = 3). The figure shows the schematic representation of the three genes. Exons indicated in black are exons whose splicing is in-frame. (b) Position of the tested spliceogenic variants relative to the acceptor and donor splice sites. Black bar: variants inducing splicing alterations; white bar: variants maintaining normal splicing in the minigene assay.

Figure 3

Illustration of each type of splicing effect based on minigene-splicing assay. The pictures show RT-PCR products visualized on agarose gels and annotated as described in Materials and Methods. v: empty pCAS2 vector; WT: wild type; MT: mutant. △: nucleotide deletion; ▼: nucleotide insertion.

Figure 4

Characterization of splicing alterations, accuracy of in silico predictions, and impact on variant classification. (a) Distribution of splicing alterations. (b) Accuracy of in silico splicing predictions. (c) Impact of splicing defects on protein reading frame. (d) Accuracy of in silico tools to detect cryptic splice sites. An “incomplete prediction” was applied to variants for which a splicing alteration was predicted but the corresponding algorithm has not provided the position of the alternative splice site. Positions of cryptic splice sites were unavailable for AbSplice-DNA. Variant classification before (e) and after (f) minigene-splicing assays.