EFTUD2 missense variants disrupt protein function and splicing in mandibulofacial dysostosis Guion‐Almeida type

Human MutationVolume 41, Issue 8 p. 1372-1382 RESEARCH ARTICLEOpen Access EFTUD2 missense variants disrupt protein function and splicing in mandibulofacial dysostosis Guion-Almeida type Huw B. Thomas, orcid.org/0000-0001-9626-9706 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorKatherine A. Wood, orcid.org/0000-0002-6459-2127 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorWeronika A. Buczek, orcid.org/0000-0003-1131-8009 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorChristopher T. Gordon, orcid.org/0000-0002-9300-8399 Laboratory of Embryology and Genetics of Human Malformation, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163, Institut Imagine, Paris, France Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, FranceSearch for more papers by this authorVéronique Pingault, orcid.org/0000-0001-7064-0765 Laboratory of Embryology and Genetics of Human Malformation, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163, Institut Imagine, Paris, France Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, France Département de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris, FranceSearch for more papers by this authorTania Attié-Bitach, orcid.org/0000-0002-1155-3626 Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, France Département de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris, France INSERM UMR 1163, Institut Imagine, Paris, FranceSearch for more papers by this authorKathryn E. Hentges, orcid.org/0000-0001-8917-3765 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorVinod C. Varghese, orcid.org/0000-0002-6512-6064 All Wales Medical Genomics Service, Cardiff, UKSearch for more papers by this authorJeanne Amiel, orcid.org/0000-0001-5973-4728 Laboratory of Embryology and Genetics of Human Malformation, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163, Institut Imagine, Paris, France Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, France Département de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris, FranceSearch for more papers by this authorWilliam G. Newman, orcid.org/0000-0002-6382-4678 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Center for Genomic Medicine, St. Mary's Hospital, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorRaymond T. O'Keefe, Corresponding Author rokeefe@manchester.ac.uk orcid.org/0000-0001-8764-1289 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK Correspondence Raymond T. O'Keefe, Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9PT, UK. Email: rokeefe@manchester.ac.ukSearch for more papers by this author Huw B. Thomas, orcid.org/0000-0001-9626-9706 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorKatherine A. Wood, orcid.org/0000-0002-6459-2127 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorWeronika A. Buczek, orcid.org/0000-0003-1131-8009 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorChristopher T. Gordon, orcid.org/0000-0002-9300-8399 Laboratory of Embryology and Genetics of Human Malformation, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163, Institut Imagine, Paris, France Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, FranceSearch for more papers by this authorVéronique Pingault, orcid.org/0000-0001-7064-0765 Laboratory of Embryology and Genetics of Human Malformation, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163, Institut Imagine, Paris, France Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, France Département de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris, FranceSearch for more papers by this authorTania Attié-Bitach, orcid.org/0000-0002-1155-3626 Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, France Département de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris, France INSERM UMR 1163, Institut Imagine, Paris, FranceSearch for more papers by this authorKathryn E. Hentges, orcid.org/0000-0001-8917-3765 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorVinod C. Varghese, orcid.org/0000-0002-6512-6064 All Wales Medical Genomics Service, Cardiff, UKSearch for more papers by this authorJeanne Amiel, orcid.org/0000-0001-5973-4728 Laboratory of Embryology and Genetics of Human Malformation, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163, Institut Imagine, Paris, France Paris Descartes-Sorbonne Paris Cité University, Institut Imagine, Paris, France Département de Génétique, Hôpital Necker-Enfants Malades, AP-HP, Paris, FranceSearch for more papers by this authorWilliam G. Newman, orcid.org/0000-0002-6382-4678 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Center for Genomic Medicine, St. Mary's Hospital, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UKSearch for more papers by this authorRaymond T. O'Keefe, Corresponding Author rokeefe@manchester.ac.uk orcid.org/0000-0001-8764-1289 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK Correspondence Raymond T. O'Keefe, Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9PT, UK. Email: rokeefe@manchester.ac.ukSearch for more papers by this author First published: 25 April 2020 https://doi.org/10.1002/humu.24027Citations: 4AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Abstract Pathogenic variants in the core spliceosome U5 small nuclear ribonucleoprotein gene EFTUD2/SNU114 cause the craniofacial disorder mandibulofacial dysostosis Guion-Almeida type (MFDGA). MFDGA-associated variants in EFTUD2 comprise large deletions encompassing EFTUD2, intragenic deletions and single nucleotide truncating or missense variants. These variants are predicted to result in haploinsufficiency by loss-of-function of the variant allele. While the contribution of deletions within EFTUD2 to allele loss-of-function are self-evident, the mechanisms by which missense variants are disease-causing have not been characterized functionally. Combining bioinformatics software prediction, yeast functional growth assays, and a minigene (MG) splicing assay, we have characterized how MFDGA missense variants result in EFTUD2 loss-of-function. Only four of 19 assessed missense variants cause EFTUD2 loss-of-function through altered protein function when modeled in yeast. Of the remaining 15 missense variants, five altered the normal splicing pattern of EFTUD2 pre-messenger RNA predominantly through exon skipping or cryptic splice site activation, leading to the introduction of a premature termination codon. Comparison of bioinformatic predictors for each missense variant revealed a disparity amongst different software packages and, in many cases, an inability to correctly predict changes in splicing subsequently determined by MG interrogation. This study highlights the need for laboratory-based validation of bioinformatic predictions for EFTUD2 missense variants. 1 INTRODUCTION The spliceosome is a large RNA/protein complex that is required for removal of intron regions from pre-messenger RNA (pre-mRNA; Wahl, Will, & Lührmann, 2009). The spliceosome is composed of five small nuclear ribonucleoproteins (snRNPs) that associate with the pre-mRNA and are dynamically remodeled to allow the two transesterification reactions required for intron removal from pre-mRNA (Will & Lührmann, 2011). Genetic variants in spliceosome-associated genes cause a number of human craniofacial disorders. Variants in the human spliceosome-associated genes TXNL4A, EFTUD2, SF3B4, SNRPB, and EIF4A3 cause craniofacial disorders: Burn-McKeown syndrome, mandibulofacial dysostosis Guion-Almeida type (MFDGA), Nager syndrome/Rodriguez syndrome, cerebrocostomandibular syndrome, and Richieri-Costa–Pereira syndrome, respectively (Lehalle et al., 2015). In most of these craniofacial disorders, the disease variants inactivate one allele and are proposed to cause disease through haploinsufficiency. Patients with MFDGA possess a wide variety of variants within EFTUD2 that potentially inactivate one EFTUD2 allele (Gordon et al., 2012; Huang et al., 2016; Lacour et al., 2019; Lehalle et al., 2014; Lines et al., 2012; Luquetti et al., 2013; Matsuo et al., 2017; Sarkar et al., 2015; Smigiel et al., 2015; Vincent et al., 2016; Voigt et al., 2013). EFTUD2/Snu114 is a GTPase, and a core U5 snRNP protein that is present throughout the splicing cycle and regulates spliceosome remodeling (Frazer, Nancollis, & O'Keefe, 2008). The MFDGA disease-associated variants comprise small and large deletions, splice site variants, and nonsense and missense variants. These MFDGA variants are present in a single allele in trans with a wild type, functional allele, consistent with haploinsufficiency. It is not entirely clear why a reduction in the amount of a core pre-mRNA splicing protein, required for the splicing of all pre-mRNAs, results in such a specific disease phenotype. However, recent cell and animal models of MFDGA have begun to analyze the consequences of reduced EFTUD2 expression (Beauchamp et al., 2019; Deml, Reis, Muheisen, Bick, & Semina, 2015; Lei et al., 2017; Wood et al., 2019). Of all the variants in EFTUD2, the missense variants are of particular interest as several of these variants have been suggested to disrupt EFTUD2 protein function (Huang et al., 2016), but have not been tested for their function experimentally. We took advantage of the high conservation between EFTUD2 and its orthologue in yeast, SNU114, to test the function in vivo of 19 EFTUD2 missense variants associated with MFDGA. Functional assays in yeast revealed that only four missense variants in SNU114, modeling EFTUD2 missense variants in MFDGA, disrupted protein function. The viability of many MFDGA related SNU114 missense variants in the yeast functional assay suggested that EFTUD2 missense variants influenced EFTUD2 function in a different way. In fact, by subsequently using a minigene (MG) splicing assay, we determined that five EFTUD2 missense variants influenced the splicing of the EFTUD2 pre-mRNA to inactivate one allele in MFDGA. Thus, we have defined how missense variants in EFTUD2 can influence both EFTUD2 protein function and pre-mRNA splicing to cause MFDGA and provide support for the growing evidence that missense variants can influence splicing and should be routinely tested for splicing defects. 2 MATERIAL AND METHODS 2.1 Yeast SNU114 mutagenesis and functional analysis Mutagenic primers were designed to introduce missense variants that corresponded to orthologous MFDGA-associated missense mutations in EFTUD2 following pairwise alignment of protein sequences (EFTUD2 NP_001245282, Snu114 AJS56599.1) by EMBOSS Needle (Figure S1). Where necessary, optimal yeast codon usage was used. Mutagenesis of the SNU114 gene in the plasmid pRS413-SNU114 was carried out using the Kunkel method (Kunkel, 1985) and mutagenic primers (Table S1), followed by sequencing to confirm the mutation. The mutant or wild type plasmids were transformed into the haploid SNU114 deletion strain (YSNU114KO1 MATa; his3Δ1; leu2Δ0; lys2Δ0; ura3Δ0; YKL173w::kanMX4; pRS416-Snu114) then grown on 5-fluoroorotic acid (5-FOA) to assay for function as previously described (Frazer, Lovell, & O'Keefe, 2009). 2.2 Splicing minigene construction A 3.8 kb fragment (“Fragment 3”) of the pSpliceExpress MG splicing reporter vector (a gift from Stefan Stamm, Addgene 32485) (Kishore, Khanna, & Stamm, 2008) was amplified by polymerase chain reaction (PCR) using Phusion High-Fidelity DNA Polymerase (Thermo Fisher Scientific), or isolated by restriction enzyme digestion with NheI and BamHI. Similarly, EFTUD2 exons and at least 100 bp of flanking 5′ and 3′ intronic sequence were PCR-amplified from control genomic DNA also using Phusion High-Fidelity DNA Polymerase employing two pairs of primers to produce two overlapping (10–20 bp) fragments (“Fragment 1” and “Fragment 2”) each with a single portion of overlap (6–10 bp) with the vector fragment (“Fragment 3”) on one end. Where necessary, overlapping primer sequences for Fragments 1 and 2 were altered to introduce single-nucleotide variations into the exons corresponding to MFDGA-associated EFTUD2 missense variants (see Table 1 for full list of variants). Fragments 1, 2, and 3 were assembled using the Gibson method (Gibson, 2011) and transformed into competent bacteria. Successfully assembled vectors were isolated from candidate colonies and their sequence-verified by direct Sanger sequencing performed by Eurofins Genomics. Sequences of primers used for Gibson assembly of MG splicing constructs can be found in Table S1. Table 1. Yeast growth assay and minigene (MG) splicing assay results for MFDGA-associated missense variants Snu114 EFTUD2 Amino acid change Yeast growth assay results Amino acid change Exon No. cDNA coordinates Mutation name Minigene results References Thr147Ile Lethal Thr143Ile 5 c.428C>T T143I No effect See supporting notes Gly217Glu Lethal Gly207Glu 9 c.620G>zA G207E No effect See supporting notes His218Arg Slow-growing His208Arg c.623A>G H208R No effect Gordon et al. (2012) Leu234Arg Viable Gly224Arg c.670G>A G224R No effect Gordon et al. (2012) c.670G>C G224R-synth No effect n/a Arg272Trp Viable Arg262Trp 10 c.784C>T R262W No effect Lines et al. (2012), Smigiel et al. (2015), Huang et al. (2016) Asn296Ser Viable Asn286Ser c.857A>G N286S Cryptic splice site See supporting notes Tyr387His Viable Gln383His 13 c.1149G>C Q383H Exon skipped/3′ Intron retained See supporting notes Gln444Glu Viable Gln436Glu 15 c.1306C>G Q436E No effect Luquetti et al. (2013) Ala470Arg Lethal Cys476Arg 16 c.1426T>C C476R No effect Lines et al. (2012) Gly491Asp Viable Gly499Asp c.1496G>A G499D No effect Huang et al. (2016) Lys593* Lethal (control) Arg578* 18 c.1732C>T R578* No effect (Control) Sarkar et al. (2015), Huang et al. (2016) Lys635Asn Viable Lys620Asn c.1860G>C K620N Spliced out (majority) Lehalle et al. (2014) c.1860G>T K620N-synth Spliced out (majority) n/a Met652Arg Viable Leu637Arg 19 c.1910T>G L637R No effect Lines et al. (2012) Ile689Lys Viable Thr678Lys 20 c.2033C>A T678K No effect Huang et al. (2016) Gly798Arg Viable Gly769Arg 23 c.2305G>C G769R No effect Huang et al. (2016) Pro807Ser Viable Pro778Ser c.2332C>T P778S No effect See supporting notes Ala853Thr Viable Ala823Thr 25 c.2467G>A A823T Spliced out (majority) Vincent et al (2016) Glu859Lys Viable Glu829Lys c.2485G>A E829K Spliced in (majority) Luquetti et al. (2013) Arg887Tyr Viable His856Tyr 26 c.2566C>T H856Y No effect Lehalle et al. (2014) Arg971His Viable Arg938His 27 c.2813G>A R938H No effect Huang et al. (2016) Snu114 L589-K635del (ΔEx18) Lethal For the MG splicing assay, HEK293 cells were grown overnight to 40–60% confluency in 3 ml of Dulbecco's modified Eagle's medium high-glucose, DMEM (Sigma-Aldrich), supplemented with 10% fetal bovine serum (Sigma-Aldrich) in tissue-culture treated six-well plates at 37°C and with 5% CO2. Cells were transiently transfected with at least 0.2 μg of MG vector (either wild type or mutant) using Lipofectamine (Thermo Fisher Scientific) and the manufacturer's standard protocol. Following 48 hr incubation at 37°C with 5% CO2, RNA was extracted using TRI Reagent® according to the manufacturer's instructions (Sigma-Aldrich). Extracted RNA was purified further using the RNeasy column clean-up kit (Qiagen), which included a DNase digestion step. cDNA was synthesized from up to 4 μg RNA (using an equal amount of RNA for each sample set) using Superscript Reverse Transcriptase (Thermo Fisher Scientific). Resulting cDNA was amplified by Phusion High-Fidelity DNA Polymerase (Thermo Fisher Scientific) using “Minigene RT PCR-for” and “Minigene RT PCR-rev” primers (Table S1). Finally, PCR products were run on an agarose gel (1–3%) supplemented with SafeView nucleic acid stain (NBS Biologicals). Gels were visualized under a blue-light transilluminator and, where appropriate, bands of interest were extracted and purified using QIAquick gel extraction kit (Qiagen) followed by direct Sanger sequencing performed by Eurofins Genomics, to confirm splicing products. 2.3 Ethical compliance Institutional ethical review and approval was granted, and informed consent was provided, for all data obtained from patients. 3 RESULTS 3.1 Functional analysis of disease-associated EFTUD2 missense variants in yeast There are currently over 100 different characterized genetic variants in EFTUD2 (https://databases.lovd.nl/shared/variants/EFTUD2/unique), the majority of which are linked to craniofacial anomalies consistent with a diagnosis of MFDGA (Gordon et al., 2012; Huang et al., 2016; Lehalle et al., 2014; Lines et al., 2012; Luquetti et al., 2013; Sarkar et al., 2015; Smigiel et al., 2015; Vincent et al., 2016). Here, we present five new missense variants in EFTUD2 (see Supporting Information Notes). It is now well established that haploinsufficiency of EFTUD2 is the primary cause of craniofacial phenotypes in patients with MFDGA (Lines et al., 2012). However, it is less clear how each individual pathogenic variant leads to a loss-of-function in that allele and, as such, haploinsufficiency. While many of the known variants in EFTUD2 are large enough to be clearly deleterious (e.g., multiexon deletion or whole gene deletion), approximately 15–20% of MFDGA patients present with only a single allele missense variant. The effect of these missense variants on EFTUD2 function has not been characterized. Several of the EFTUD2 missense variants are located close to, or within the EFTUD2 protein G-domain or one of five G-box motifs thought to be important for GTP-binding (Bartels, Urlaub, Lührmann, & Fabrizio, 2003) (Figure S1). However, several other missense variants are distal to any clearly functional EFTUD2 protein domain and may not influence EFTUD2 function. Alignment of the yeast Snu114 and human EFTUD2 amino acid sequences reveals that 13 of 20 amino acids where missense variants occur in EFTUD2 are identical in yeast Snu114 (Figure S1). To investigate the effect of EFTUD2 missense variants on EFTUD2 protein function, comparable variants were made in the orthologous yeast gene SNU114 by in vitro mutagenesis of the HIS3 plasmid pRS413-SNU114. SNU114 missense containing plasmids were transformed into a SNU114 haploid deletion strain where SNU114 function was complemented with the URA3 plasmid pRS416-SNU114. Transformed strains were grown on plates containing 5-FOA to remove the pRS416-SNU114 plasmid, leaving only the missense variant form of yeast Snu114 as a single allele. Missense variants that caused a loss-of-function change in the yeast Snu114 protein would be lethal after growth in the presence of 5-FOA. Nineteen different EFTUD2 missense variants, plus one nonsense variant used as a lethal control, were tested for function in yeast SNU114. In addition to the nonsense variant control, three variants (Gly217Glu, Ala470Arg, Thr147Ile) were lethal and one variant (His218Arg) displayed slow growth (Table 1). None of the missense variants exhibited any temperature sensitivity difference compared to control samples and all variants exhibited a similar growth pattern when grown in liquid culture or on solid media (data not shown). The lack of a functional defect in yeast Snu114, containing orthologous EFTUD2-associated missense variants, suggests that some variants do not influence EFTUD2 protein function and might be disrupting another process, potentially the splicing of the EFTUD2 pre-mRNA. 3.2 EFTUD2 missense variants disrupt splicing of the EFTUD2 pre-mRNA Since a number of EFTUD2 missense variants were found to be viable in yeast SNU114, these missense variants were assayed to determine if they resulted in loss of function by influencing the splicing of EFTUD2 pre-mRNA. An important difference between EFTUD2 and SNU114 is that EFTUD2 is a multiexon gene, whereas yeast SNU114 is a single exon gene. Therefore, any missense variants which alter a splice site or splicing enhancer/silencer motif in EFTUD2 would not have been deleterious in the processing of the yeast SNU114 mRNA. Initial characterization of EFTUD2 missense mutations involved the use of multiple bioinformatics tools to predict the influence on splicing of each variant (Desmet et al., 2009; Fairbrother, Yeh, Sharp, & Burge, 2002; Lim & Fairbrother, 2012; Mort et al., 2014; Reese, Eeckman, Kulp, & Haussler, 1997; Schwarz, Cooper, Schuelke, & Seelow, 2014; Shapiro & Senapathy, 1987; Xiong et al., 2015; Yeo & Burge, 2004). Bioinformatic tools with disparate predictive algorithms were employed to provide a broad range of possible outcomes. Outputs from the in silico tools varied from quantitative scores in the case of “MutPred Splice” and “Spliceman” to more qualitative splice predictions of donor/acceptor site gain or loss or the introduction of exonic splicing enhancers (ESEs). All EFTUD2 variants that we tested were predicted to have some altered splicing characteristics from at least one of the nine software tools used (Tables 2 and S2). However, there was considerable discordance between the in silico predictors. For example, the variants Arg262Trp and Pro778Ser both had very low splicing score from MutPred Splice suggesting both were likely to be splice neutral variants and there were also no alterations to potential splice donor or acceptor sites predicted for these variants from five other tools. However, both Arg262Trp and Pro778Ser achieved a high ranking score from the Spliceman software suggesting these particular missense variants may alter or disrupt the normal splicing pattern. Conversely, there was good agreement from all software packages on the variant Asn286Ser and the likelihood of this variant altering the splicing of EFTUD2 exon 10. Table 2. Predictive analysis of MFDGA-associated EFTUD2 missense mutations using nine different analysis programs and summarized results of MG splicing assay EFTUD2 variant Genomic change MutPred splice score/prediction SPANR SR (%) R-ESE MT SSF MES NNSplice HSF MG assay results NP_004238.3:p.(T143I) NC_000017.10:g.42960525G>A 0.86, SAV 43 Loss of ESE, gain of ESE Acceptor loss Acceptor increase Acceptor increase Acceptor increase No effect NP_004238.3:p.(G207E) NC_000017.10:g.42957006C>T 0.8, SAV Decreased exon 9 inclusion 57 Gain of 3 ESEs Acceptor loss Acceptor decrease Acceptor decrease Acceptor decrease Acceptor decrease No effect NP_004238.3:p.(H208R) NC_000017.10:g.42957003T>C 0.4, SNV 62 Loss of ESE Donor gain Donor loss Acceptor increase Donor gain No effect NP_004238.3:p.(G224R) NC_000017.10:g.42956956C>T 0.57, SNV Decreased exon 9 inclusion 57 Loss of ESE Donor gain Acceptor decrease Acceptor increase Acceptor gain No effect NP_004238.3:p.(R262W) NC_000017.10:g.42953387G>A 0.17, SNV 72 Gain of ESE No effect NP_004238.3:p.(N286S) NC_000017.10:g.42953314T>C 0.82, SAV 66 Loss of two ESEs Donor gain Donor increase Donor increase Donor gain Donor increase, acceptor gain Cryptic splice site NP_004238.3:p.(Q383H) NC_000 017.10:g.42945175C>G 0.82, SAV 82 Donor loss, acceptor gain Donor decrease Donor decrease, acceptor loss, acceptor gain Donor decrease Donor decrease Exon skipped/3’ Intron retained NP_004238.3:p.(Q436E) NC_000017.10:g.42941130G>C 0.22, SNV 53 Gain of ESE Donor increase, acceptor increase Acceptor loss Acceptor loss Acceptor decrease Acceptor decrease No effect NP_004238.3:p.(C476R) NC_000017.10:g.42940262A>G 0.12, SNV 68 Donor gain Acceptor decrease Acceptor increase No effect NP_004238.3:p.(G499D) NC_000017.10:g.42940192C>T 0.21, SNV 41 Gain of ESE Donor gain Acceptor increase No effect NP_004238.3:p.(R578*) NC_000017.10:g.42937401G>A 0.31, SNV Decreased exon 18 inclusion 87 Acceptor increase Acceptor gain Acceptor increase Acceptor increase Acceptor increase No effect (control) NP_004238.3:p.(K620N) NC_000017.10:g.42937273C>G 0.8, SAV Decreased exon 18 inclusion 73 Gain of ESE Donor loss, acceptor gain Donor decrease Donor decrease, acceptor loss Donor decrease Donor decrease, acceptor loss Spliced out (majority) NP_004238.3:p.(L637R) NC_000017.10:g.42936500A>C 0.24, SNV 69 Donor gain No effect NP_004238.3:p.(T678K) NC_000017.10:g.42934455G>T 0.26, SNV 70 Loss of ESE, gain of ESE Donor increase Acceptor gain Acceptor gain No effect NP_004238.3:p.(G769R) NC_000017.10:g.42931679C>G 0.27, SNV 64 Gain of ESE Donor increase, acceptor increase Acceptor gain Acceptor gain Donor loss, acceptor loss No effect NP_004238.3:p.(P778S) NC_000017.10:g.42931652G>A 0.15, SNV 68 No effect NP_004238.3:p.(A823T) NC_000017.10:g.42930758C>T 0.8, SAV 44 Donor gain, acceptor loss Donor loss, acceptor decrease Acceptor decrease Acceptor decrease Acceptor decrease Spliced out (majority) NP_004238.3:p.(E829K) NC_000017.10:g.42930740C>T 0.32, SNV 55 Gain of 3 ESEs Donor increase Acceptor gain Acceptor increase Acceptor increase Spliced in (majority) NP_004238.3:p.(H856Y) NC_000017.10:g.42929926G>A 0.92, SAV 65 Donor increase Donor gain Donor gain, acceptor decrease Donor gain, acceptor increase No effect NP_004238.3:p.(R938H) NC_000017.10:g.42929088C>T 0.2, SNV 64 Donor gain Donor increase, acceptor increase Donor increase, acceptor increase No effect NP_004238.3:p.(G224R) (synth) NC_000017.10:g.42956956C>T 0.35, SNV Increased exon 9 inclusion 67 Loss of ESE, gain of ESE Donor increase Acceptor increase Acceptor increase Acceptor increase No effect NP_004238.3:p.(K620N) (synth) NC_000017.10:g.42937273C>G 0.81, SAV Decreased exon 18 inclusion 60 Donor loss, acceptor gain Donor decrease Donor decrease, acceptor loss Donor decrease Donor decrease, acceptor loss Spliced out (majority) Note: Programs include SPANR (Xiong et al., 2015), MutPred Splice (Mort et al., 2014), SR (Lim & Fairbrother, 2012), R-ESE (Fairbrother et al., 2002), MT (Schwarz et al., 2014), SSF (Shapiro & Senapathy, 1987), MES (Yeo & Burge, 2004), NNSplice (Reese et al., 1997), and HSF (Desmet et al., 2009). Empty cells represent no result for that particular program. Refer to individual programs for details of predictive algorithms employed. Abbreviations: HSF, Human Splicing Finder; MES, MaxEntScan; MFDGA, mandibulofacial dysostosis Guion-Almeida type; MG, minigene; MT, Mutation Taster; R-ESE, Rescue-ESE; SAV, splice-altering variant; SNV, splice-neutral variant; SR, Spliceman ranking; SSF, SpliceSiteFinder. In total, 19 EFTUD2 missense variants and one nonsense variant (negative control) covering 13 exons