HUMANMUTATION 28(6), 599^612,2007

RESEARCH ARTICLE

Extensive In Silico Analysis of NF1 SplicingDefects Uncovers Determinants for SplicingOutcome Upon 50 Splice-Site Disruption

K. Wimmer,1� X. Roca,2 H. Beiglbock,1 T. Callens,3 J. Etzler,1 A.R. Rao,2,4 A.R. Krainer,2 C. Fonatsch,1

and L. Messiaen3

1Department of Medical Genetics, Medical University of Vienna, Vienna, Austria; 2Cold Spring Harbor Laboratory, Cold Spring Harbor, NewYork; 3Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama; 4Biometric Division, Indian Agricultural StatisticsResearch Institute, New Delhi, India

Communicated by Jean-Louis Mandel

We describe 94 pathogenic NF1 gene alterations in a cohort of 97 Austrian neurofibromatosis type 1 patientsmeeting the NIH criteria. All mutations were fully characterized at the genomic and mRNA levels. Over half ofthe patients carried novel mutations, and only a quarter carried recurrent minor-lesion mutations at 16mutational warm spots. The remaining patients carried NF1 microdeletions (7%) and rare recurring mutations.Thirty-six of the mutations (38%) altered pre-mRNA splicing, and fall into five groups: exon skipping resultingfrom mutations at authentic splice sites (type I), cryptic exon inclusion caused by deep intronic mutations (typeII), creation of de novo splice sites causing loss of exonic sequences (type III), activation of cryptic splice sitesupon authentic splice-site disruption (type IV), and exonic sequence alterations causing exon skipping (type V).Extensive in silico analyses of 37 NF1 exons and surrounding intronic sequences suggested that the availabilityof a cryptic splice site combined with a strong natural upstream 30 splice site (30ss)is the main determinant ofcryptic splice-site activation upon 50 splice-site disruption. Furthermore, the exonic sequences downstream ofexonic cryptic 50 splice sites (50ss) resemble intronic more than exonic sequences with respect to exonic splicingenhancer and silencer density, helping to distinguish between exonic cryptic and pseudo 50ss. This studyprovides valuable predictors for the splicing pathway used upon 50ss mutation, and underscores the importanceof using RNA-based techniques, together with methods to identify microdeletions and intragenic copy-numberchanges, for effective and reliable NF1 mutation detection. Hum Mutat 28(6), 599–612, 2007. Published2007 Wiley-Liss, Inc.y

KEY WORDS: neurofibromatosis type 1; NF1; splicing; cryptic splice site; pseudo splice site; splicing enhancer; splicingsilencer

INTRODUCTION

Neurofibromatosis type (NF1; MIM] 162200) is one of the mostcommon autosomal dominant disorders, affecting approximately 1out of 3,500 individuals worldwide. A hallmark of the disease isthe extreme heterogeneity in clinical expression [Easton et al.,1993; Huson, 1994]. The classical diagnostic signs of NF1, such ascafe-au-lait spots (CLSs), iris Lisch nodules, and dermalneurofibromas, appear in an age-dependent order. Therefore, onlyabout half of the patients with sporadic NF1 fulfill the diagnosticcriteria by 1 year of age, and�5% will still not fulfill these criteriaby the age of 8 years [DeBella et al., 2000]. Further, there arespecific forms of neurofibromatosis, such as familial spinalneurofibromatosis, with an unusually mild dermal presentation ofthe disease even in adults [Ars et al., 1998; Kaufmann et al., 2001;Kluwe et al., 2003; Korf et al., 2005; Messiaen et al., 2003], andoligosymptomatic mosaic cases [Tinschert et al., 2000]. Signs ofNF1 may also be found in children with malignancies usually notassociated with NF1 that carry biallelic mutations in one of themismatch-repair genes [De Vos et al., 2005; Ostergaard et al.,2005]. Taken together, there is a need for a reliable and sensitivegenetic NF1 testing to help resolve diagnostic dilemmas in

patients not fulfilling the NIH diagnostic criteria [Gutmann et al.,1997; Stumpf et al., 1988], especially in young children andatypical patients, to determine the affected status of familymembers, and to carry out prenatal or preimplantation diagnosis[Spits et al., 2005], if desired.

Published online 20 February 2007 in Wiley InterScience (www.interscience.wiley.com).yThis article is a US Government work and, as such, is in the publicdomain in the United States of America.

DOI10.1002/humu.20493

The Supplementary Material referred to in this article can beaccessed at http://www.interscience.wiley.com/jpages/1059-7794/suppmat.

Received 14 September 2006; accepted revised manuscript 10January 2007.

Grant sponsor: NIH; Grant number: CA13106; Grant sponsor:Department of Biotechnology, Government of India; BiotechnologyOverseas Associateship; Grant number: BT/IN/BTOA/03/2005.

�Correspondence to: Katharina Wimmer, PhD, Department ofMedical Genetics, Medical UniversityVienna,Waehringerstr.10,1090Vienna, Austria. E-mail: katharina.wimmer@meduniwien.ac.at

PUBLISHED 2007 WILEY-LISS, INC.

The NF1 gene, located in 17q11.2, was cloned in 1990[Cawthon et al., 1990; Viskochil et al., 1990; Wallace et al., 1990].However, mutation detection in the NF1 gene is still a difficulttask, in part due to the complex organization of the gene, whichcomprises 57 constitutive and at least three alternative exons[Danglot et al., 1995; Li et al., 1995; Marchuk et al., 1991],and due to the fact that large parts of the 280-kb gene (see latestentry MapViewer, build 36.1: November 1, 2005 at the NCBI) areduplicated as pseudogenes in other regions of the genome.Moreover, there are no clear mutational hotspots in the gene,and the spectrum of mutations is very diverse, ranging frommicrodeletions affecting the entire NF1 and several additionalgenes [De Raedt et al., 2004; Jenne et al., 2003], to minor-lesionmutations that include a high proportion of splicing mutations[Ars et al., 2000]. Thus, the mutation-detection rates of mostlaboratories, some relying on a single technique, do not exceed50 to 80% [Ars et al., 2003; De Luca et al., 2003; Fahsold et al.,2000; Griffiths et al., in press; Han et al., 2001]. So far onlyone study has identified a clearly pathogenic lesion in 95% ofthe patients fulfilling the NIH criteria [Messiaen et al., 2000].The efficiency and reliability of this study is explained by theapplication of a set of complementary techniques that allow thedetection of the different mutation types, as well as by the use ofan mRNA-based core assay that can also uncover unusual splicingdefects which are due to mutations outside the canonical GT-AGsplice-site sequences in the NF1 gene. Splicing mutations mayescape identification or correct interpretation by genomic DNA-based assays, such as high-throughput sequencing or screeningapproaches, essentially because: 1) the underlying alteration islocated outside the analyzed sequence; and 2) it is detected butcannot be unequivocally classified as pathogenic based on thegenomic sequence alone [Messiaen and Wimmer, 2005]. Examplesof the former are deep intronic single-nucleotide changes thatcreate novel splice sites, and thus lead to inclusion of a crypticexon into the processed mRNA transcript (see, e.g., Perrin et al.[1996]). Examples of the latter are silent or conservative missensemutations that either create novel splice sites that are used insteadof the natural splice sites [Messiaen et al., 1999], or disruptsplicing signals, resulting in exon skipping [Zatkova et al., 2004].Furthermore, the classification of intronic changes affecting the50 or 30 splice sites (50ss and 30ss), but outside the highly conservedAG/GT dinucleotides is difficult.

Reliable in silico prediction of the splicing outcome resultingfrom mutations would increase the efficiency of genomic DNA-based mutation-detection assays. However, the difficulty inpredicting in silico the in vivo splicing outcome of a sequencealteration reflects the complex interplay of sequence elements thatdefine the splice sites and the exons. The splicing specificity isdefined partly by the 50ss and 30ss and thousands of splice-sitesequences have been used to define these two consensus elements.However, the great majority of natural splice sites do not perfectlyconform to the consensus, and pseudo 50ss and 30ss sequences thatmatch the consensus motifs as well as or even better than naturalsplice sites, but are never selected for splicing, outnumber thegenuine splice sites [Sun and Chasin, 2000]. Additional informa-tion required for the recognition of splice sites is provided byauxiliary cis-acting regulatory sequences. Exonic splicing enhan-cers (ESEs) are typically bound by members of the SR proteinfamily [Blencowe, 2000; Graveley, 2000], which help to defineexons, either by recruiting components of the splicing machinery[Graveley et al., 2001; Zuo and Maniatis, 1996] and/or byantagonizing the action of nearby splicing silencer elements [Kanand Green, 1999]. Exonic and intronic splicing silencers (ESSs

and ISSs) seem to work by interaction with negative regulators,which often belong to the heterogeneous nuclear ribonucleoprotein(hnRNP) superfamily [Dreyfuss et al., 1993; Lopez, 1998; Wagnerand Garcia-Blanco, 2001]. Their mechanism of action may involveantagonizing splicing enhancers, but other mechanisms, such as‘‘looping-out’’ of exons have also been proposed [Blanchette andChabot, 1999; Wagner and Garcia-Blanco, 2001].

We have performed NF1 mutation analysis in 97 Austrianpatients fulfilling the NIH criteria. We applied a multistepapproach to analyze the complete coding region, using an RNA-based core assay complemented with methods to identifymicrodeletions and intragenic copy-number changes. Here wepresent the results and discuss the effectiveness of the approach, aswell as the spectrum and recurrence rate of the mutationsidentified in this patient cohort. The full characterization ofall mutations at the genomic and the mRNA level allowed us tocorrelate the observed splicing effects with the predicted strengthof the characterized mutant, de novo, and cryptic NF1 splice sitesas well as the corresponding wild-type sites and with the predictedESE/ESS densities of the affected exons. By these means weidentified important predictors for the splicing pathway used upon50ss disruption, as well as parameters that help distinguishingexonic cryptic from pseudo 50ss.

MATERIALSANDMETHODSPatient Samples

Over the past 7 years, 123 unrelated index persons were sent formolecular genetic NF1 testing to our laboratory at the Departmentof Human Genetics at the Medical University Vienna. Clinicalfeatures were recorded for all patients, and for those that fulfilledthe diagnostic criteria according to the NIH consensus conference[Gutmann et al., 1997; Stumpf et al., 1988], comprehensive RNA-and DNA-based testing was performed. Informed consent wasobtained from all patients.

Comprehensive NF1Mutation Analysis

For all patients, two blood samples, EDTA- and heparin-blood,were received. Heparin-blood was used for cytogenetic analysis.The EDTA-blood sample was split and DNA was extracted bystandard salt precipitations from one aliquot. Lymphocytes werepurified from the remaining blood sample by erythrocyte lysis andwere used to setup short-term phytohaemagglutinine-(PHA)-stimulated lymphocyte cultures to circumvent illegitimate splicing,a phenomenon that occurs mainly in ‘‘aged’’ blood samples whoseRNA cannot be extracted directly after blood drawing, leadingto multiple aberrant splice variants that are not caused by theunderlying pathogenic mutations [Wimmer et al., 2000a]. Thesecultures were treated for 6 hours with puromycin (200 mg/ml),prior to cell harvest and RNA extraction, to inhibit nonsense-mediated decay [Messiaen et al., 2000]. RNA was extracted withTRIzol (Gibco BRL, Gaithersburg, MD) and 2.5 mg of total RNAwas reverse-transcribed using random hexamers and a SuperScriptFirst-Strand Synthesis System for RT-PCR (Invitrogen, Carlsbad,CA). For protein truncation testing (PTT) and direct cDNAsequencing, the entire cDNA was amplified by PCR in fiveoverlapping segments using primer pairs as described [Heim et al.,1995].

PTT performed as described in Wimmer et al. [2002] was theprimary assay performed for all patients received prior to June2005. For patients received after May 2005, as well as forall patients that were negative by PTT, direct sequencing of allfive segments was performed using SequiThermExcel II DNA-

600 HUMANMUTATION 28(6), 599^612,2007

Human Mutation DOI 10.1002/humu

Sequencing Kit-LC (Epicenter, Madison, WI). The reactionswere run on a LiCor automated sequencer (MWG, Ebersberg,Germany). Any sequence alteration identified by PTT and/ordirect cDNA sequencing was further confirmed by genomicsequencing of the exon involved. Primers used for PCRamplification of the affected exons are available upon request.

For all patients in whom RNA-based mutation analysis wasnegative, fluorescence in situ hybridization (FISH) analysis wasperformed using NF1 intragenic cosmid probes C01919 (contain-ing the NF1 promoter region), G02121 (encompassing intron 28to exon 45), and H0410 (located in the NF1 30UTR). The threeprobes were pooled and labeled with digoxygenin [Fonatsch andStreubel, 1998], and hybridized together with a commercial biotin-labeled alpha-satellite DNA probe for Chromosome 17 (Vysis/Abbott, Abbott Park, IL). At least 15 metaphases were inspectedper sample.

Patients who were negative for any other type of mutation weretested for intragenic copy-number changes by multiplex ligation-dependent probe amplification (MLPA) analysis [Wimmer et al.,2006]. The flow of the analysis program is depicted in Figure 1.The nomenclature of the mutations is based on NF1 mRNAsequence NM_000267.1. Nucleotide positions of given NF1mutations are calculated from nucleotide 212 where the ATGstart codon is located. Note that according to the most widely usednomenclature that is best known to researchers in the field, NF1exons are not named with strictly consecutively numbers.

Splice-Site Strength Prediction

We applied several methods to estimate the strength of all wild-type, mutated, de novo, and cryptic splice sites that are destroyedby, or used in the context of, mutations identified in our patient

cohort. The position-weight matrices developed by Shapiro andSenapathy (S&S) [Senapathy et al., 1990; Shapiro and Senapathy,1987] evaluate concordance of a sequence to the splice-siteconsensus motifs. We also calculated the strength by algorithmsdeveloped by Burge and colleagues, including maximum entropy(MAXENT), multiple dependence decomposition (MDD), firstorder Markov model (MM), and a weight matrix model (WMM)using their web-based tool MaxEntScan (http://genes.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html) [Burge, 1998; Rocaet al., 2003; Roca et al., 2005; Yeo and Burge, 2004]. Since Watson-Crick base-pairing of the 50ss consensus sequence to the U1 snRNA50 terminus plays a critical role in 50ss selection [Horowitz andKrainer, 1994; Seraphin et al., 1988; Siliciano and Guthrie, 1988],the predicted energetic stability of this RNA duplex has also beenused as a method to estimate the strength of a 50ss [Lear et al.,1990; Mayeda and Ohshima, 1988; Sorek et al., 2004]. The free-energy (DG) for the stability of the 50ss/U1 RNA duplex waspredicted using the nearest-neighbor RNA base-pairing parametersreported by the Turner laboratory (also known as the ‘‘Turnerrules’’) [Roca et al., 2003; Serra and Turner, 1995]. The neuralnetwork method is a machine-learning approach that recognizessequence patterns once it is trained with a set of DNA sequencesencompassing authentic splice sites [Reese et al., 1997]. Splice SitePrediction by Neural Network (SSPNN) allows searching forpotential splice sites in long sequence stretches (www.fruitfly.org/seq_tools/splice.html), whereas the other methods score only shortinput sequences containing single splice sites. Therefore, SSPNNwas the only program we used to search for and score potentialcryptic 50ss. The entire exonic sequences, extending to 5(nucleotides) of the downstream intron, were analyzed with SSPNNto calculate the density of exonic cryptic 50ss. The densityis given as the number of 50ss per 100 nt that scored above a

FIGURE 1. Mutation analysis scheme.The blood sample is split after collection, and two short-term cultures for cytogenetic analysisand RNA-extraction are started. DNA is extracted from a third aliquot.The primary mutation-detection assay, PTT, and/or directcDNA sequencing, identi¢ed a pathogenic lesion in 84% of the patients ful¢lling theNIH criteria. All minor-lesionmutations identi-¢edby thesemeans are con¢rmed at the genomic level byexon sequencing. Patients negative forPTTand/ordirect cDNA sequencingare subjected toFISHanalysis. Eight patientswithNF1microdeletionswere identi¢ed. Finally, in twopatients negative forPTT,directcDNA sequencing and FISHMLPA identi¢ed large intragenic deletions.The overall mutation detection rate is 94%.

HUMAN MUTATION 28(6), 599^612,2007 601

Human Mutation DOI 10.1002/humu

threshold level of 0.2. The first 180 nt of the downstream intronwere similarly analyzed to calculate the density of potential introniccryptic 50ss. Potential cryptic 50ss that are never used in the contextof a mutant splice site are referred to as pseudo 50ss.

Estimation of ESE and ESSDensity

Several web-based programs have been developed to predictESEs and to assess the effect of sequence alterations on theirfunction. We used ESEfinder (http://exon.cshl.org/ESE), RES-CUE-ESE (http://genes.mit.edu/burgelab/rescue-ese), and Puta-tive Exonic Splicing Enhancers/Silencers (PESX; http://cubweb.biology.columbia.edu/pesx/). ESEfinder [Cartegni et al.,2003] employs position-weight matrices for scoring a subset ofcandidate ESE motifs, corresponding to the functional consensusmotifs of several SR proteins [Liu et al., 1998, 2000]. RESCUE-ESE was developed to predict sequences with ESE activity basedon the statistical analysis of differences in hexamer frequenciesbetween exons and introns, and between exons with weak andstrong splice sites [Fairbrother et al., 2002]. ESE prediction byPESX is based on the statistical analysis of differences in RNAoctamer frequencies between noncoding exons and pseudoexonsplus the 50UTRs of intronless genes [Zhang and Chasin, 2004].The PESX program also allows the prediction of putative ESSs.

The ESE and ESS densities of the exons affected by 50ssmutations and of the 180 nt of the downstream introns wereobtained by counting each individual ESE/ESS site (regardless ofwhether it overlaps other ESE/ESS sites) that falls entirely ormostly, i.e., 4 out of 7, 3 out of 6, or 4 out of 8 nts, in these exonicand intronic wild-type sequences. The density is given as thenumber of ESEs/ESSs per 100 nt.

The ESE/ESS densities surrounding the identified cryptic andpseudo 50ss were similarly obtained, but from the pre-mRNAtranscripts expressed from the mutant alleles. Note that: 1) the50ss at position138 in intron 22 is classified as a cryptic 50ss intranscripts from the c.387011G4A mutated allele, but as apseudo 50ss in transcripts harboring the c.387011G4C or c.387011G4T mutations. The latter two mutations lead to the use ofanother weak (SSPNN score o0.1) cryptic 50ss 26 nt upstreamof the natural 50ss. 2) The cryptic 50ss at position139 in intron 43is used in the majority of the transcripts from the c.767511G4Amutated allele. However, in a small proportion (�20%) of thetranscripts, exon 43 is skipped. Therefore, this 50ss is classifiedboth as cryptic and pseudo 50ss, and the ESE/ESS densities of themutant pre-mRNA are counted in both groups.

Statistical Analysis

We used the nonparametric Mann-Whitney-Wilcoxon rank testto assess whether the analyzed parameters differ significantlybetween type I and type IV exons, and between cryptic and pseudo

50ss, respectively. We used the exact method of PROC NPAR1-WAY of the SAS system [SAS Institute, 1990] to compute theMann-Whitney-Wilcoxon rank test scores and exact P-values. Theexact method has an advantage over asymptotic methods, such asnormal and t-tests, because it remains valid for very small samplesizes, as well as for data that are sparse, skewed, or heavily tied. Weused the exact one-sided P-values to test the null hypothesis of nodifference between the analyzed parameters from the two groups.For tests 30, 39–44, and 51, exact P-values were estimated usingthe Monte Carlo simulation, as exact computations required a lotof time and memory, and also asymptotic approximations were notsufficient. To detect putative false positives due to multiple testing,the false discovery rate (FDR) controlling procedure [Benjaminiand Hochberg, 1995] was applied on the P-values obtained fromthree test groups, separately. This procedure was applied to controlFDR at 0.05 ( 5f), and the null hypothesis was rejected when theP-values are rP(j), where j is the largest index for which P(j)rfj/n(j 5 1, 2,y, n), and n is the number of comparisons.

RESULTSMutation-Detection Rate

We identified pathogenic NF1 gene alterations in 94 out of 123unrelated index individuals referred to our laboratory for moleculargenetic testing. Sixty-one of the patients were sporadic patientsand 19 familial cases. In the remaining 14 cases clinical reports didnot mention the familial status. Six of the 29 individuals in whomno mutation was found probably carry NF1 mutations that weremissed by the comprehensive testing. Three of these six patientsare adults who fulfilled the NIH criteria for NF1, according to theclinicians’ reports. Furthermore, we did not find pathogenic NF1alterations in three children with six or more CLSs but no othersigns of NF1. If we presume that these six patients do carry NF1mutations, we achieved a mutation detection rate of 94% (Fig. 1).

None of the remaining 23 individuals for whom comprehensivetesting failed to uncover a pathogenic NF1 lesion is likely toharbor such a mutation in the majority of their cells (Table 1).Three of the 23 patients were sent for molecular genetic testingwith the suspicion of segmental or mosaic NF1: an adult patienthaving an isolated intraorbital plexiform neurofibroma, anotheradult patient with a large hyperpigmented region in the lowerabdomen with a number of small neurofibromas but no CLSs orneurofibromas outside this region, and a boy with multiple (46)CLSs on the trunk, inguinal freckling, and very mild scoliosis, butwith a completely unaffected monozygotic twin brother.

Two other index individuals without pathogenic NF1 mutationsfulfilled the NIH criteria. However, both patients were alsosuffering from malignancies usually not associated with NF1, i.e.,acute lymphatic leukemia and colon carcinoma in one case, anda glioblastoma in the other case. Both parents of these patients

TABLE 1. Description of 29 Patients inWhomNoPathogenicNF1LesionWas Identi¢ed

No. of patients Description

Patients likely to harbor an undetected constitutiveNF1mutation3 Adult patient presenting at least two clinical features ofNF13 Children presenting six andmoreCLSs but no other features ofNF1

Patients unlikely to harbor aNF1mutation in themajority of his/her body cells3 Patients with suspected segmental ormosaicNF12 Patients with suspected homozygous or compound heterozygousmismatch-repair gene defects2 Patient with suspected spinal neuro¢bromatosis8 Patients with less than ¢veCLSs and no other clearlyNF1-associated feature8 Childrenwith optic pathway gliomas or astroctomas of a di¡erent location but without CLSs

602 HUMANMUTATION 28(6), 599^612,2007

Human Mutation DOI 10.1002/humu

were unaffected, but both patients had a sibling who also died ofa malignancy and at least in one case also showed signs of NF1.One of these families was from a consanguineous marriage.We suspect that these two patients may carry biallelic mutations inone of the MMR genes, rather than a mutation in the NF1 gene.

Two patients without pathogenic NF1 alterations were referredwith the suspicion of spinal neurofibromatosis. Both were adultsporadic patients with neuropathies and MRI results indicativeof multiple spinal neurofibromas, but no other feature of NF1.

Furthermore, five children and two adults without NF1mutation presented with one to four CLSs. Two of these childrenalso showed mild to severe mental retardation, whereas the otherfive patients showed no other NF1-associated signs. An additionaleight children presenting with optic-pathway gliomas or astro-cytomas at a different location, but no other NF1 features, testednegative for a pathogenic NF1 lesion. Finally, one child withoutmutation showed occipital and electroencephalogram alterationsof unknown etiology, but no clearly NF1-associated features.

NF1Mutation Spectrum

Supplementary Table S1 (available online at http://www.interscience.wiley.com/jpages/1059-7794/suppmat) describes all 94pathogenic NF1 gene alterations identified in our diagnosticlaboratory. Eight patients harbored submicroscopic NF1 micro-deletions identified by FISH analysis. Five patients carriedintragenic deletions described in detail in a previous report onintragenic copy-number changes in the NF1 gene [Wimmer et al.,2006]. In one patient we discovered a de novo Alu-insertion,c.650_651insAluYa5, with the Alu-sequence most closely relatedto the AluYa5 family. The approximately 350-nt insertion 4 ntupstream of the 30 end of exon 4c led to skipping of this exon inthe mRNA transcripts of the patient. This effect is most likely dueto the dramatic (approximately six-fold) increase of the exon sizeby the insertion. The remaining 80 patients carried 77 differentminor-lesion mutations.

Minor-lesion mutations affecting NF1 splicing represented thelargest group of pathogenic alterations, with 31 different sequencealterations identified in 32 patients. This group includes threenonsense mutations that result in exon skipping: c.5719G4T,c.6792C4A, and c.6792C4G. Exon skipping was also found in aminor proportion of the transcripts from three other mutated allelescarrying nonsense mutations in NF1 exon 7 [Wimmer et al., 2000b].Taken together, a total of 36 out of 94 (38%) identified NF1alterations had an effect on pre-mRNA splicing, including the exonskipping caused by the Alu-insertion. The second largest groupwithin the minor-lesion mutations comprised 23 different frameshiftmutations found in 25 index patients. A total of 19 differentnonsense mutations were identified in our patient cohort, includingthe three nonsense mutations in exon 7 leading to exon skippingonly in a minority of the transcripts in the patients’ samples.

The smallest group of pathogenic alterations consisted ofmissense mutations found in only four patients. Two of thesewere located within the GAP-related domain (GRD) of neurofi-bromin. The recurrent mutation p.Arg1276Gln affects the‘‘arginine finger’’ of the GRD and, therefore, compromises thecatalytic GTPase-activating function of neurofibromin [Ahmadianet al., 1997; Klose et al., 1998]. An unreported missense mutation,p.Ser1399P, was found as a de novo alteration. The mutationaffects the evolutionarily conserved Ser1399. According to thealgorithms developed by Miller and Kumar [2001] Ser to Pro isslightly overrepresented in pathogenic alterations. Taking theseindicators for pathogenicity together, this mutation is considered

as disease-causing. Two other missense mutations affect the highlyconserved Trp1931. Mutation p.Trp1931Arg has been reported ina NF1 patient [Hudson et al., 1997], but p.Trp1931Cys is novel.Both alterations cause a dramatic change from an aromatichydrophobic to a positively charged or sulfur-containing aminoacid, respectively, which are found more frequently as pathogenicalterations than as interspecies variations [Miller and Kumar,2001]. Both sequence alterations are considered pathogenicbecause of their dramatic change of a highly conserved aminoacid, although we were unable to confirm the de novo appearanceof these two changes in these sporadic patients.

Sequence Context of RecurrentNF1Mutations

Only two minor-lesion mutations (c.1466A4G andc.1756_1759delACTA) were found more than once in our patientcohort, underscoring the overall low recurrence rate of NF1mutations. Therefore, we compared the list of all minor-lesionmutations and intragenic copy-number changes found in ourpatient cohort with mutations found in over 1,000 NF1 patientsthat have been published in 65 different reports (SupplementaryTable S2). We found 36 out of 86 (40%) of our nonmicrodeletionpatients to carry 33 different recurrent NF1 alterations (Table 2).Of these 33 recurrent mutations, 13 were previously reported onlytwice (12) or three times (1) and the remaining 20 were foundmore than three times in NF1 patients.

Ten of the latter mutations are explained by spontaneousmethyl-cytosine deamination-mediated C4T/G4A transitionsat nine of the 120 CpG dinucleotides of the NF1 coding sequence[Girodon-Boulandet et al., 2000]. Two mutations are tandem-duplication-mediated deletions (c.499_502delTGTT andc.1756_1759delACTA) and one, c.2033dupC, is an insertion ofa C at a mononucleotide tract of seven Cs. Further, four mutationsare located in a hypermutable region in exon 37, containing a‘‘quasisymmetric’’ element [Robinson et al., 1995] and includes anAC-dinucleotide repeat. Mutation c.1541_1542delAG in exon10c may be explained by excision of two mispaired nucleotidesin an inverted repeat that can form a hairpin-loop structure[Ball et al., 2005] and mutations 1466A4G and 57491332A4G,found so far 11 and five times, respectively, may result fromspontaneous adenine deamination [Lindahl, 1993] that leadsto the formation of hypoxanthine, which mispairs with cytosine,and hence represents a premutagenic lesion for A4G/T4Ctransitions.

Among the 13 mutations with a low recurrence rate, only fourcan be explained by the aforementioned mechanisms. Mutationsc.152714_152717delAGTA and c.2033delC may be explainedby DNA-polymerase slippage, as they are located within atrinucleotide tandem repeat and a homonucleotide tract, respec-tively. The mutations c.4268A4G and c.5791T4C may beexplained by spontaneous adenine deamination at the sense andanti-sense strand, respectively. One recurrent mutation was anAlu-mediated deletion including the entire exon 2 and adjacentsequences [Wimmer et al., 2006]. The reason for recurrence of theremaining eight mutations remains unexplained.

Analysis of the Splice-Site Strengths A¡ected byNF1Splicing Mutations

We identified 35 different mutations that affect splicing. Thesesplicing mutations can be divided into five categories: classicalsplice-site mutations leading to exon skipping (type I); single-nucleotide changes within introns, creating de novo splice sitesleading to inclusion of a cryptic exon (type II); single-nucleotide

HUMANMUTATION 28(6), 599^612,2007 603

Human Mutation DOI 10.1002/humu

TABLE

2.Rec

urrenc

eRates

of3

3NF1

Mutations�

No.

Exo

n/

Intron

Mutation

Des

criptionof

mutationmec

han

ism

explaining

recu

rren

ce(seq

uenc

eco

ntext)

No.

ofpatients

inthisreport

No.

ofpatients

inother

reportsa

Totaln

o.of

patients

1IV

S1-IVS2

c.61

^519

0_2

04115

99de

l693

3Alu-m

ediatedde

letion

1xWi1

x2x

2IV

S2

c.20

411G

4T

Mec

han

ism

unkn

own(TAACAATA

TGg(4

t)tgag

tatttg)

1xFa

1x2x

3E4a

c.31

1T4A

Mec

han

ism

unkn

own(A

CAATGAGATT(4

A)A

GATGAAACG)

1xMa1x

2x

4E4B

c.49

9_5

02de

lTGTT

Slip

pedmispairingat

tetran

ucleotide

tand

emrepe

at(A

TTA

ACTGTT(T

GTT)C

AGAAGACAA)

1xAr3x,

Fa6x,

Ha3x,

Lu04

4x,

Lu05

1x,M

a1x

,Os1x

,Sa1x

21x

5E4b

c.57

4C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xFa

2x,

Me1x

,Lu04

2x

6x

6E7

c.91

0C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xAr7x,

Fa2x,

Kl03b1x

,Lu

041x

Me2x,

Or1

x,15

x

7E7

c.10

07G4A

Mec

han

ism

unkn

own(TACATCAATTG(4

A)G

GAAGATA

AC)

1xLu

041x

2x

8IV

S8

c.11

8511G

4A

Mec

han

ism

unkn

own(A

CACTTTA

AGg(4

a)tgag

agca

tt)

1xAr1

x,Fa

1x3x

9E1

0a

c.13

18C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xFa

3x,

He1x

,Kr2x,

Kl03a1x

,Ma3x,

Os1x

12x

10E1

0b

c.14

66A4G

Spontane

ousde

aminationof

aden

ine

(ACAAGAAGCTA(4

G)TAAGTA

TCTT)

2x

Ar4x,

Fa1x

,Ha1x

,Ma3x,

Me2x,

Os1x

,14

x

11IV

S10b

c.15

2714

_152

717de

lAGTA

Slip

pedmispairingat

trinuc

leotide

repe

at(G

CTTTGTg

ta(a

gta

)tttttttatg)

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x2x

12E1

0c

c.15

41_1

542

delAG

Mismatch

excision

ofinve

rted

repe

at(C

CAAGAAAAC(A

G)G

GGCCCGAAA)

1xAr4x,

Fa3x,

Os1x

,9x

13E1

2a

c.17

56

_175

9de

lACTA

Slip

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dinu

cleo

tide

repe

at(C

AAGAAATTA

(ACTA)G

TCATCAAAT)

3x

Ar1

x,Fa

1x,M

a1x

,Pa1x

,Lu05

1x8x

14E1

2a

c.17

97G4A

Mec

han

ism

unkn

own(T

TCTCAAGTGG(4

A)T

TGCGGGAAA)

1xAr1

x2x

15E1

3c.20

33de

lCSlip

pedmispairingat

hom

onu

cleo

tide

trac

t(G

GAACCCCCC(C

)GATTTGCCGA)

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33du

pC

Slip

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hom

onu

cleo

tide

trac

t(G

AACCCCCCC(1

C)G

ATTTGCCGA)

1xFa

2x,

He2x,

Kl021x

,Ma1x

,Me2x,

Or2x

11x

17E1

3c.20

41C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xAr3x,

Fa4x,

Or1

x,9x

18E1

6c.24

46C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xFa

3x,

Ma1x

,Ba1x

6x

19IV

S17

c.29

91^1

G4C

Mec

han

ism

unkn

own(TGTCTA

TATA

G(4

C)gtatgttcg

t)1x

Fa1x

,2x

20IV

S19b

c.33

15^3

C4G

Mec

han

ism

unkn

own(ttttatttctc(4

g)agA

TACTTCA)

1xMe1x

2x

21E22

c.38

26C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xFa

3x,

He1x

,Kl021x

,Me1x

,Os1x

,Up97

1x9x

22E22

c.38

27G4A

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xFa

2x,

Ma2x

5x

23E22

c.38

31C4T

Mec

han

ism

unkn

own(TCTTCCGAGGC(4

T)A

ACAGCTTGG)

1xFa

1x(m

isclas

si¢ed

assilent)

2x

24E24

c.42

68A4G

Mec

han

ism

unkn

own(T

TAATGTCAAA(4

G)G

gtga

attat)

1xHa1x

(misclas

si¢ed

asmisse

nse

)2x

25E27

ac.45

37C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xAr1

x,Fa

7x,

Kl03a1x

,Lu04

1x,

Ma2x,

Me2x,

Or1

x16

x

26IV

S30

c.57

49133

2A4G

Spontane

ousde

aminationof

aden

ine

(AAAAGTCCACa(4

g)taa

gtatcc

a)1x

Ar3x,

Pe1x

,5x

27E31

c.57

91T4C

Mec

han

ism

unko

wn

(CATGACTCCAT( 4

C)G

GCTGTCAAA)

1xHu1x

2x

28

E31

c.583

9C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xAr4x,

Ab1x

,Ai1

x,Ca1x

,Du1x

,Es1x

,Fa3xH

o2x,

Hu1x

,Kr2x,

Lu04

1x,M

e1x

,Or1

x,Va,

22x

29E37

c.67

89_6

792de

lTTA

CMismatch

excision

atsy

mmetricelem

ent

(GACCTGACAC(T

TAC)A

ACAGTCAAG)o

rslip

ped

1xFa

5x,

Lu04

1x,M

e1x

,Or1

x,9x

604 HUMAN MUTATION 28(6), 599^612,2007

Human Mutation DOI 10.1002/humu

changes within exons, creating de novo splice sites whose useresults in the loss of a part of the exon (type III); mutationsdisrupting use of the splice site and resulting in activation ofcryptic exonic or intronic splice sites (type IV); and exonicsequence alterations causing exon skipping (type V).

In a previous study we showed that the primary effect of thesix type V splicing mutations in our cohort is the disruption ofESEs, which consequently compromises exon recognition [Zatkovaet al., 2004]. These six type V splicing mutations as well as the denovo Alu-insertion that causes skipping of exon 4c, are notincluded in our present splice-site analysis.

The remaining 28 type I to type IV splicing mutations are listedin Supplementary Table S3. The splice-site strengths of all wild-type, mutated, de novo, and cryptic splice sites that are destroyedby, or used in the context of, mutations identified in our patients’cohort were estimated using four different computational methods.From this analysis, the following conclusions can be drawn.

We identified 12 type I splicing mutations, nine affecting a50ss and three a 30ss. In contrast to the common notion that mostdisease-causing splice-site mutations affect the terminal GT-AGdinucleotides [Krawczak et al., 1992; Roca et al., 2003], only fiveof the 12 mutations were single-nucleotide changes at thesepositions. Nevertheless, all the sequence alterations substantiallydecrease the predicted strengths of the splice-site sequencescompared to their wild-type counterparts, consistent with theaberrant splicing observed with these mutant NF1 pre-mRNAs.

The type II group includes two deep intronic mutations: thenovel mutation c.152711159C4T in IVS10b, and the recurrentmutation c.57491332A4G in IVS30. Both mutations createstrong de novo 50ss and lead to the insertion of cryptic exons intothe mRNA. All splice-site scoring methods predict that the 30ss forthe cryptic exon created by c.152711159C4T is strong. However,the 30ss of the cryptic exon created by c.57491332A4G at positionc.57491154 is predicted to be extremely weak by all methodssuggesting that factors other than the splice sites helpto define this cryptic exon. The latter mutation was originallyidentified by Perrin et al. [1996], who described not only theinsertion of 177 nt using the weak cryptic 30ss at position c.57491

154, but also inclusion of 208 nt using a noncanonical cryptic 30ss atposition c.57491124, not seen by us and others [Ars et al., 2000].

Five type III splicing mutations, which appear at the genomiclevel as missense (3) or silent (2) sequence alterations, create denovo 50ss that are used instead of the authentic 50ss. For all fivemutations, the four computational methods concordantly pre-dicted an increase of the splice-site strength at the de novo splicesites. Moreover, the de novo 50ss tend to be stronger than theauthentic 50ss they out-compete, as evidenced by a higher meanof their estimated strengths (Supplementary Table S3). However,this difference was not statistically significant, and the authentic50ss are in most cases predicted to be only marginally weaker, andin some instances even stronger, than the de novo 50ss.

The list of type IV splicing mutations in our cohort includesthree 50ss and six 30ss mutations. With one exception, all themutations result in only one mRNA species in the patient samples.Mutation c.767511G4A leads to the use of a cryptic 50ss 39 ntdownstream of the authentic 50ss, as well as to exon skipping.As activation of the cryptic 50ss is the major splicing event causedby this mutation, it is cataloged as a type IV mutation.

Two of the type IV 30ss mutations may be considered as asubtype of type IV splice-site mutations. Mutation c.3198–2A4Tdisrupts the proximal of two tandem AG dinucleotides at theauthentic 30ss of exon 19b, resulting in activation of the distal AGdinucleotide. Mutation c.7000–4A4G creates a NAGNAG-

Mispairingat

dinu

cleo

tide

repe

at(G

ACCTGACAC(T

TAC)A

ACAGTCAAG)

30E37

c.67

91du

pASeq

uenc

edu

plic

ationat

symmetricelem

ent

(CTGACACTTA

(1A)C

AACAGTCAA)

1xAb1x

,Ar2x,

Co1x

,Fa1

x,Kl021x

,Lu

042x,

Os1x

,Up961x

11x

31E37

c.67

92C4A

Unkn

ownmec

han

ism

athyp

ermutab

leregion

(CTGACACTTA

C(4

A)A

ACAGTCAA)

1xAr6x,

Fa3x,

Kl03a1x

,Lu04

1x,

Ma1x

,Me1x

,Or1

x,Up962x

17x

32E37

c.67

92C4G

Unkn

ownmec

han

ism

athyp

ermutab

leregion

(CTGACACTTA

C(4

G)A

ACAGTCAAG)

1xFa

1x,M

a1x

,Me1x

,4x

33E42

c.74

86C4T

Spontane

ousde

aminationof

methy

lcytos

ine;

hypermutab

leCpG

dinu

cleo

tide

1xFa

2x,

Kl021x

,Ma1x

,Me1x

,Pa1x

,Pu1x

,8x

� Exo

nic

sequ

ence

inca

pital

letters,

intronic

sequ

ence

inlower

case

letters;

a¡ec

ted

nucleo

tide

sin

bold;de

leted/

inserted

and

chan

ged

sequ

ence

sin

paren

thes

is;inse

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are

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ted

by1

and

sequ

ence

chan

gesby

4;

aAbbreviationsformutationreportsaregive

nin

Sup

plemen

taryTa

ble

S2.

HUMAN MUTATION 28(6), 599^612,2007 605

Human Mutation DOI 10.1002/humu

tandem motif [Chua and Reed, 2001; Hiller et al., 2004] at the30ss of exon 39, resulting in activation of the newly-createdproximal AG dinucleotide. In both instances, the authenticpolypyrimidine tract and branch site can be used.

Consistent with previous studies on cryptic splice-site activation[Kralovicova et al., 2004; Roca et al., 2003], the predictedstrengths of the cryptic splice sites are generally lower thanthose of the corresponding authentic splice sites (SupplementaryTable S3 and Table 3). Indeed, some of the cryptic splice siteswe detected were extremely weak. For instance, mutationc.5943G4A affecting the last base of exon 31 sharply reducesthe estimated strength of the authentic 50ss and at the same timeslightly increases the predicted strength of a cryptic 50ss located4 nt upstream of the authentic 50ss. The use of this, as well as ofother weak cryptic 50ss, was unexpected in the light of other exons,such as exon 38, which is skipped upon mutation of its natural 50ssalthough it harbors a potential cryptic 50ss with a much higherestimated strength (SSPNN 0.82; see Supplementary Table S4)than those of the authentic cryptic 50ss utilized in the mutantexons 31 and 2 (SSPNN o0.01 and 0.48, respectively).

Di¡erences Between ExonsThat Are Skipped or ThatUndergo Cryptic 50ss Activation Upon 50ss Mutation

50ss mutations usually result in either skipping of the affectedexon, or activation of cryptic 50ss. To investigate the determinantsof these two aberrant splicing pathways, we extended the in silicoanalyses of 50ss mutations found in our patient cohort to otherpublished NF1 mutations [Ars et al., 2003; Messiaen et al., 2000]and to unpublished NF1 mutations identified at the MedicalGenomics Laboratory of the University of Alabama at Birmingham(UAB). We obtained a list of 28 type I and nine type IV NF1 exonsthat are affected by 67 and 17 50ss mutations, respectively (seeSupplementary Table S4). Many of the splicing effects wereobserved in several patients carrying the same or different 50ssmutations, suggesting that quantitative differences in theabundance of splicing factors among individuals have no or onlya minor influence on the splicing effect of 50ss disruption. Hence,the splicing outcome upon 50ss mutation appears to be dictatedmainly by cis-acting elements in the pre-mRNA.

To uncover cis-acting elements that influence the splicing effectof 50ss disruption, we compared the following parameters betweenthe two groups: first, the strength of the natural 50ss and 30ss ofthe affected exons, as well as the exon size; second, the densitiesof splicing enhancers and silencers in the affected exons and thefirst 180 nt of the adjacent introns, as predicted by three web-based programs; third, the average density and strength of putativecryptic 50ss identified by SSPNN using a threshold of 0.2 in the

affected exon and within the first 180 nt of the following intron(Supplementary Table S4). Means and standard deviations forthese parameters and the statistical comparisons between thetwo groups using the Mann-Whitney-Wilcoxon nonparametric testare summarized in Table 4.

All scoring tools consistently showed that the 30ss of type IVexons are stronger than the 30ss of type I exons (see tests 8–12;Table 4). Neither the strength of the natural 50ss, nor the exonsize, nor the ESE/ESS density showed significant differencesbetween both groups (see tests 1–7, 13, and 22–25; Table 4).Further, type IV exons have, on average, more putative crypticsplice sites in the exonic and adjacent intronic sequence than typeI exons (test 18). We found a higher density of exonic putativecryptic 50ss in type IV than in type I exons (test 14) and thestrength of exonic putative cryptic 50ss was higher (test 15) in thetype IV than in the type-I exons. However, the significance ofthese tests is lost after FDR correction for multiple testing.Nevertheless, the observation that all 30ss scoring methods showthe same trend, and that the comparisons of the density andstrength of putative cryptic 30ss are consistent with each other,suggests that these two parameters might be valuable predictorsfor the outcome of 50ss mutations. Even though a larger datasetis needed to confirm these findings, they suggest that the presenceof a strong putative cryptic 50ss in the exon, combined with astrong authentic 30ss, might be the main determinants of cryptic50ss activation vs. exon skipping (Fig. 2A).

Di¡erences Between Cryptic and Pseudo 50ss

The putative cryptic 50ss identified by SSPNN using a thresholdof 0.2, but that are not used upon 50ss mutation, are henceforthreferred to as pseudo 50ss [Roca et al., 2003]. A total of 44 pseudo50ss within the affected exons (16) and within the 180-nt intronicsequences downstream of the affected exons (28) were detected inour type IV (15) and type I (29) exons (see Supplementary TableS4). Three of the nine type IV splicing NF1 exons show activation,upon 50ss mutation, of four cryptic 50ss with SSPNN strengthsr0.1 (Supplementary Table S4; exons 22, 27b, and 31) and theaverage strength of the cryptic 50ss (0.53 using SSPNN) is weakerthan that of the pseudo 50ss (0.67), suggesting that the intrinsicstrength of the 50ss does not play a major role in discriminatingbetween cryptic and pseudo 50ss [Roca et al., 2003].

In an attempt to understand how cryptic and pseudo 50ss arediscriminated, we sought to identify differences in the cis-actingelements between the 11 cryptic 50ss in type IV exons and the 44pseudo 50ss identified in both type I and type IV exons. Bycomparing the predicted ESE and ESS densities surrounding thecryptic and pseudo 50ss, we noticed that the 50ss mutations

TABLE 3. Comparison of 50ss Strength BetweenWild-TypeAuthentic andCryptic 50ss�

Wild-type authentic 50ss Cryptic 50ssWilcoxon-Mann-Whitney

Test ] Mean SD Mean SD test (one sided exact) FDR 50.05 Result

56 Strength (SSPNN) 0.90 0.14 0.52 0.44 0.0260 0.0500 auth 4 crypt57 Strength (MAXENT) 8.99 1.43 3.08 6.85 8.63E^04 7.10E^03 auth 4 crypt58 Strength (MDD) 13.32 1.62 8.17 4.84 0.0015 0.0214 auth 4 crypt59 Strength (MM) 8.20 1.54 3.66 4.55 2.60E^03 2.86E^02 auth 4 crypt60 Strength (WMM) 8.28 2.40 4.76 3.43 0.0075 0.0429 auth 4 crypt61 Strength (S&S) 86.01 5.33 72.25 10.92 0.0014 0.0143 auth 4 crypt62 Strength (DG) �10.92 1.47 �7.72 3.29 0.0074 0.0357 auth 4 crypt

�Signi¢cant results are in bold.crypt, cryptic; auth, authentic.

606 HUMANMUTATION 28(6), 599^612,2007

Human Mutation DOI 10.1002/humu

TABLE

4.Com

parisonof

Param

etersBetwee

nTy

peIa

ndTy

peIV

Splic

ingExo

ns

TypeIs

plic

ingex

ons

TypeIV

splic

ingex

ons

Wilc

oxo

n-Man

n-Whitne

yTe

st]

Descriptionofp

aram

eter

Mea

nSD

Mea

nSD

test

(one

-sided

exac

t)FD

R50.05

Result

1Stren

gthof

auth

5’ss(S

SPNN)

0.89

0.16

0.90

0.14

0.377

80.041

4I5

IV2

Stren

gthof

auth

5’ss(M

AXENT)

8.62

1.52

8.99

1.43

0.334

90.037

9I5

IV3

Stren

gthof

auth

5’ss(M

DD)

12.98

1.86

13.32

1.62

0.223

90.027

6I5

IV4

Stren

gthof

auth

5’ss(M

M)

8.15

1.96

8.20

1.54

0.482

60.0500

I5IV

5Stren

gthof

auth

5’ss(W

MM)

8.54

2.22

8.28

2.40

0.475

70.0483

I5IV

6Stren

gthof

auth

5’ss(S

&S)

84.81

7.66

86.01

5.33

0.414

00.0448

I5IV

7Stren

gthof

auth

5’ss(D

G)

^11.43

2.32

^10.92

1.47

0.314

80.036

2I5

IV8

Stren

gthof

auth

3’ss(S

SPNN)

0.79

0.27

0.88

0.22

0.016

40.0069

IoIV��

9Stren

gthof

auth

3’ss(M

AXENT)

7.71

2.24

9.71

1.89

0.005

30.001

7Io

IV��

10Stren

gthof

auth

3’ss(M

M)

8.35

2.59

10.53

2.68

0.031

80.012

1Io

IV��

11Stren

gthof

auth

3’ss(W

MM)

8.61

2.86

11.54

4.92

0.018

40.008

6Io

IV��

12Stren

gthof

auth

3’ss(S

&S)

86.06

5.76

90.64

6.49

0.030

50.010

3Io

IV��

13Exo

nsize

(nts)

141.68

61.94

204.56

136.03

0.120

10.020

7I5

IV14

Noof

exonic(put)c

rypt5

’ss/10

0nts

0.18

0.31

0.55

0.46

0.015

50.005

2Io

IV��

15Stren

gthof

exonic(put)c

rypt5

’ss

0.46

0.25

0.70

0.22

0.037

60.013

8Io

IV��

16Noof

intronic(put)c

rypt5

’ss/10

0nts

0.39

0.45

0.74

0.68

0.134

30.024

1I5

IV17

Stren

gthof

intronic(put)c

rypt5

’ssintronic

0.68

0.27

0.78

0.21

0.121

30.022

4I5

IV18

Noof

exonic&

intronic(put)c

rypt5

’ss/10

0nts

0.31

0.25

0.64

0.39

0.012

40.003

4Io

IV��

19Stren

gthof

exonic&

intronic(put)c

rypt5

’ss/10

0nts

0.61

0.28

0.75

0.21

0.059

20.017

2I5

IV20

Noof

(put)c

rypt5

’ssresu

ltingin

pute

xons

withop

timal

size

(50^2

50nts)/ex

on

0.54

0.74

1.00

0.71

0.050

30.015

5I5

IV21

Stren

gthof

(put)c

rypt5

’ssresu

ltingin

(put)e

xons

withoptimal

size

(50^2

50nts)

0.56

0.28

0.75

0.28

0.059

40.019

0I5

IV22

ESEde

nsityin

exon(E

SE¢nd

er)

12.06

2.85

11.77

2.26

0.282

80.034

5I5

IV23

ESEde

nsityin

exon(R

escu

eESE)

12.10

5.05

12.09

5.03

0.465

40.0465

I5IV

24ESEde

nsityin

exon(P

ESX)

5.43

2.78

4.36

2.71

0.203

50.025

9I5

IV25

ESSde

nsityin

exon(P

ESX)

2.90

2.68

3.96

4.65

0.393

50.043

1I5

IV26

ESEde

nsityin

intron(E

SE¢nd

er)

9.39

2.42

8.89

3.38

0.227

60.029

3I5

IV27

ESEde

nsityin

intron(R

escu

eESE)

7.88

4.31

6.48

2.45

0.3605

0.039

7I5

IV28

ESEde

nsityin

intron(P

ESX)

2.68

1.96

2.04

1.36

0.2609

0.032

8I5

IV29

ESSde

nsityin

intron(P

ESX)

9.39

5.41

7.90

4.48

0.239

80.031

0I5

IV

put,putative;

cryp

t,cryp

tic;

nts,n

ucleotide

s;no

,num

ber.

��P-value

so0.05

that

beco

menons

igni¢ca

ntu

nder

FDR.

HUMAN MUTATION 28(6), 599^612,2007 607

Human Mutation DOI 10.1002/humu

frequently create or destroy predicted ESE/ESS sites. Therefore,we analyzed the ESE/ESS densities not in the wild type, but ratherin the pre-mRNA transcripts that result from 59 different mutantalleles associated with 55 different pseudo (44) and cryptic (11)50ss. However, the ESE/ESS densities were not significantlydifferent between exons resulting from the use of cryptic 50ssand exons that would be generated by the use of pseudo 50ss (tests39–46; Table 5).

Finally, we asked whether the calculated ESS density is higherin exonic sequences downstream of cryptic 50ss than in thosedownstream of pseudo 50ss. Indeed, the divergence for thisparameter between the two groups turned out to be highlysignificant after FDR correction (test 54; Table 5). Likewise, theESE density (PESX and RescueESE) was severely reduced in theexonic sequences that become intronic sequences upon use ofa cryptic 50ss, compared to the exonic sequences downstreamof pseudo 50ss (tests 52 and 53; Table 5).

We also compared the ESE/ESS densities between authenticand potential novel exonic sequences resulting from the use ofeither intronic cryptic or intronic pseudo 50ss. No significantdifferences were found by this comparison (tests 47–50; Table 5),possibly because the number of mutated pre-mRNA transcriptsthat lead to use of intronic cryptic 50ss is very small (four cases).

In summary, this study revealed that the main discriminatorbetween exonic cryptic and pseudo 50ss is not their intrinsicstrength, but rather the sequence between the cryptic/pseudo 50ssand the authentic 50ss. This sequence is 1) rich in ESSs for cryptic50ss, but poor in ESSs for pseudo 50ss; and 2) poor in ESEs forcryptic 50ss, but rich for pseudo 50ss (Fig. 2B).

DISCUSSION

In this report we show that the most reliable and effectiveapproach to identify pathogenic NF1 mutations is currently amultistep mutation-analysis program with an RNA-based coreassay supplemented with methods to identify NF1 microdeletions,as well as smaller intragenic copy-number changes, consistent witha previous study [Messiaen et al., 2000]. The advantage of RNA-based methods is largely explained by the frequent ‘‘unusual’’splicing defects in the NF1 gene. In our cohort, two deep intronicmutations that activate a pseudo-exon would have been missedby inspection of the genomic DNA alone. Furthermore, fivemutations that create de novo splice sites within exons may easilyhave been misclassified as silent (2) or innocuous missense (3)alterations (see Supplementary Table S1).

In our patient cohort we achieved a mutation detection rateof 97% (94/97) for NF1 patients fulfilling the NIH criteria.Also taking into account young children with more than six CLS,we conservatively estimate that we have missed pathogenicalterations in approximately 6% of NF1 patients. The failure toidentify mutations in these patients most likely has multipleexplanations. First, the promoter and the 30UTR have not beenentirely sequenced and tested for copy-number changes. Second,it is clear that no molecular genetic method is 100% effective.The low percentage of missense mutations (4/97) in comparison toother highly effective studies (9% in Messiaen et al. [2000])suggests that some missense mutations in our cohort may havebeen missed. However, we cannot rule out a selection bias thatcould have arisen by prescreening of a proportion of the patientswith genomic DNA-based methods prior to submission to ourlaboratory. This possibility is supported by the relatively highnumber of splicing mutations not affecting the consensus splice

FIGURE 2. Schematic representation of the parameters that in£uence the splicing outcome upon 50ssmutation. A: A high density ofpotential cryptic 50ss combinedwith a strong natural 30ss directs the splicing pathway toward the use of a cryptic 50ss.The thunder-bolts indicate 50ss disruptingmutations.Up anddownarrows indicatehigh and low values for the correspondingparameters, respec-tively.B:Themaindiscriminator betweenexoniccryptic andpseudo 50ss is the sequencecontext between thecryptic/pseudo 50ssandthe authentic 50ss.The exonic sequence that turns into intronic sequence upon use of the cryptic 50ss resembles intronic rather thanexonic sequences with respect to ESE/ESS density.This sequence is enriched in ESSs and depleted of ESEs when compared to theexonic sequence downstreamof pseudo 50ss. [Color ¢gure can be viewed in the online issue,which is available at www.interscience.wiley.com.]

608 HUMANMUTATION 28(6), 599^612,2007

Human Mutation DOI 10.1002/humu

sites in our patient cohort. Third, the exact extent of mosaicismamong the NF1 patients is currently unknown. It is striking thattwo of the sporadic patients without mutations, although fulfillingthe NIH criteria, were mildly affected to borderline cases. One wasof African descent and reported with cutaneous neurofibromasonly, but had a likewise-affected sister. The second was aborderline-affected woman in her 30s, with multiple CLSs notrestricted to a body part, and a histologically confirmed sacralplexiform neurofibroma, but no other reported NF1 features.Hence, it is possible that a larger proportion of patients thancurrently expected correspond to mosaic cases. Finally, it ispossible that biallelic mismatch-repair (MMR) gene alterationsare the underlying cause in a small proportion of young sporadicNF1-like cases without pathogenic NF1 lesions. So far, all reportedcases with biallelic MMR-gene alterations and signs of NF1 alsopresented in childhood and/or early adulthood malignanciestypically not associated with NF1 [Bandipalliam, 2005; De Voset al., 2005; Ostergaard et al., 2005]. Detailed clinical as well asfamilial anamnesis including cancer history and consanguinity mayhelp to identify possible candidates of this genetic mechanism,even among the young sporadic NF1-like patients that do not yetpresent any malignancies.

The mutational spectrum identified in our NF1 patients showedthe following distribution: 80% minor lesion mutations, 8%NF1 microdeletions, 5% intragenic deletions, and 1% de novoAlu insertions. Among the minor-lesion mutations, the splicingmutations (32–36%) represent the largest group, followed byframeshift (25%) and nonsense (16–19%) mutations, whereasmissense mutations represent the smallest group (4%). By andlarge this representation fits into the mutational spectrum reportedby others [Ars et al., 2000; Messiaen et al., 2000]. However, wenoticed that our cohort contained slightly more NF1 microdele-tions [Kluwe et al., 2004] and intragenic deletions [Wimmer et al.,2006] compared to other cohorts, and fewer missense mutations[Messiaen et al., 2000]. Hence, the mutational spectrum in ourcohort may be influenced by the relatively small sample size and/ora possible patient-selection bias.

We found that 36 of our patients carry recurrent mutationsand roughly a quarter (23) of our patients carried mutationsat mutational warm spots including nine CpG nucleotides in exons4b, 7, 10a, 13, 16, 22, 27a, 31, and 42, two duplications in exons4b and 12a, a seven-cytosine mononucleotide tract in exon 13, aninverted repeat in exon 10c, and a hypermutable region in exon37 containing a quasisymmetric element and a dinucleotiderepeat. Interestingly, two mutational warm spots were adeninesmutated into guanines in exons 10b and intron 30. A possibleexplanation for the recurrence of these two A4G mutations isa high susceptibility to spontaneous adenosine deamination[Lindahl, 1993]. Taken together, our study shows that only aminority of NF1 mutations are located in mutational warm spots.

Splicing mutations represent the largest group (32–36%) of NF1gene alterations found in our cohort of patients. The fullcharacterization of all mutations at the genomic and mRNA levelallowed us to correlate predictions made on splice-site strength andESE/ESS densities by in silico analysis tools with the observedsplicing outcome of the mutation. By these means, we made thefollowing observations relevant to mechanisms of splice-siteselection.

First, in contrast to the common notion that most splice-sitemutations are single-nucleotide substitutions at the highly con-served GT-AG dinucleotides, only 5 out of 12 and 5 out of 9 50ssand 30ss mutations, respectively, were of this type. Nevertheless, alltested splice-site scoring programs readily predicted a substantial

TABLE

5.Com

parisonof

Param

etersBetwee

nPotential

andAuthe

nticCryptic5’ss

Pseud

o50 ss

Cryptic50 ss

Wilc

oxo

n-Man

n-Whitne

yTe

st]

Des

criptionof

param

eter

Mea

nSD

Mea

nSD

test

one

-sided

exac

tFD

R50.05

Result

39ESEde

nsityin

theex

onicse

quen

cethat

resu

ltsfrom

theus

eof5

’ss(E

SE¢nd

er)

12.15

3.47

13.25

3.42

0.149

5�

0.037

5pseud

o5cryp

t40

ESEde

nsityin

theex

onicse

quen

cethat

resu

ltsfrom

theus

eof5

’ss(R

escu

eESE)

10.74

6.06

13.73

7.07

0.025

7�

0.015

6pseud

oocryp

t��

41ESEde

nsityin

theex

onicse

quen

cethat

resu

ltsfrom

theus

eof5

’ss(P

ESX)

4.26

2.54

6.16

4.67

0.0995�

0.025

0pseud

o5cryp

t42

ESSde

nsityin

theex

onicse

quen

cethat

resu

ltsfrom

theus

eof

5’ss(P

ESX)

4.07

3.59

3.32

3.48

0.133

5�

0.031

3pseud

o5cryp

t43

ESEde

nsitybe

twee

nau

th3’ssan

dex

onic5’ss(E

SE¢nd

er)

12.89

4.81

14.07

3.39

0.1097�

0.028

1pseud

o5cryp

t44

ESEde

nsitybe

twee

nau

th3’ssan

dex

onic5’ss(R

escu

eESE)

11.77

8.45

13.88

7.06

0.052

9�

0.021

9pseud

o5cryp

t45

ESEde

nsitybe

twee

nau

th3’ssan

dex

onic5’ss(P

ESX)

3.58

3.65

7.23

4.76

0.0

060

0.012

5pse

udoocr

ypt

46

ESSde

nsitybe

twee

nau

th3’ssan

dex

onic5’ss(P

ESX)

3.51

4.32

3.59

3.89

0.331

00.0469

pseud

o5cryp

t47

ESEde

nsitybe

twee

nau

th5’ssan

dintronic5’ss(E

SE¢nd

er)

9.84

4.29

11.18

7.13

0.226

90.040

6pseud

o5cryp

t48

ESEde

nsitybe

twee

nau

th5’ssan

dintronic5’ss(R

escu

eESE)

9.72

8.40

10.61

9.62

0.357

50.0500

pseud

o5cryp

t49

ESEde

nsitybe

twee

nau

th5’ssan

dintronic5’ss(P

ESX)

2.53

2.82

1.47

1.73

0.300

50.043

8pseud

o5cryp

t50

ESSde

nsitybe

twee

nau

th5’ssan

dintronic5’ss(P

ESX)

7.73

5.62

4.71

5.52

0.137

60.034

4pseud

o5cryp

t51

ESEde

nsitybe

twee

nex

onic5’ssan

dau

th5’ss(E

SE¢nd

er)

13.04

4.09

10.31

4.80

0.052

8�

0.018

8pseud

o5cryp

t52

ESEde

nsitybe

twee

nex

onic5’ssan

dau

th5’ss(R

escu

eESE)

11.37

4.11

8.29

5.85

0.0

023

0.0

063

pse

udo4

cryp

t53

ESEde

nsitybe

twee

nex

onic5’ssan

dau

th5’ss(P

ESX)

5.17

3.67

2.60

2.88

0.0

042

0.0

094

pse

udo4

cryp

t54

ESSde

nsitybe

twee

nex

onic5’ssan

dau

th5’ss(P

ESX)

1.97

2.78

7.48

6.34

6.41E-0

43.10E-0

2pse

udoocr

ypt

� Monte

Carlo

approximation;

sign

i¢ca

ntresultsin

bold.p

ut,pu

tative;c

rypt,cryp

tic;

auth,a

uthen

tic.

��P-value

so0.05

that

bec

omenonsign

i¢ca

ntu

nder

FDR.

HUMANMUTATION 28(6), 599^612,2007 609

Human Mutation DOI 10.1002/humu

loss of the strength of the authentic splice site upon mutation,consistent with the disruption of the use of the affected splice site.

Second, we have identified five silent and missense mutationsthat create de novo 50ss (type III mutations). In each case, thepredicted splice-site strength was higher for the mutant than forthe wild-type sequence at that site. We also observed a trendtoward higher splice-site scores of the de novo 50ss than of thenatural ones with which they compete, but this tendency did notreach statistical significance, possibly due to the small number oftype III mutations. Furthermore, it is possible that these mutationsnot only create a de novo 50ss but simultaneously affect exoniccis-elements that help to define the natural 50ss. There is anexample in which a pathogenic mutation affects auxiliary cis-actingelements that dictate the splicing outcome of the competing 50ss[Mine et al., 2003]. Thus, it will be important to study a largernumber of de novo 50ss, to determine whether they indeed havehigher strengths than the authentic 50ss, and how the sequencecontext of the de novo 50ss influences their use.

Third, our systematic analysis of type I and type IV splicingmutations addressed the question of the determinants of thesplicing pathway activated upon mutation of the natural 50ss;i.e., skipping of the affected exon or activation of a cryptic 50ss.Identification of factors that influence the splicing effect of50ss mutations is important for a better understanding of thedefinition of cryptic 50ss, but also has diagnostic implications, sincethe splicing outcome in most cases severely influences the activityof the protein. Here, we undertook extensive statistical analyses touncover parameters that influence the splicing pathway activatedupon 50ss mutation. Our results suggest that upon 50ss mutation,the presence of a good potential cryptic 50ss combined with astrong 30ss may direct the splicing pathway towards the use ofa cryptic 50ss. This notion is supported by a study performed inparallel to our investigations that came to the same conclusion[Krawczak et al., 2007].

Fourth and last, we also confirmed previous studies showing thatin general, cryptic 50ss are weaker than authentic 50ss [Ars et al.,2000; Lear et al., 1990; Roca et al., 2003], explaining in most casesthe competitive advantage of the authentic 50ss vs. the cryptic 50ss.Our study also confirms that pseudo 50ss found in the vicinity ofauthentic 50ss do not differ in splice-site strength from cryptic 50ss,nor are they located farther from the authentic 50ss [Roca et al.,2003]. Hence, cis-acting elements, such as ESEs and ESSs, mayexplain the differential 50ss selection in these cases. Here wepresent strong evidence for the notion that the sequence contextdownstream of exonic cryptic 50ss plays an important role as adiscriminator between cryptic and pseudo 50ss. The ESS density(PESX) is substantially higher in exonic sequences that turn intointronic sequences upon use of cryptic 50ss than the correspondingsequences that would result from the use of pseudo 50ss. Likewise,the ESE densities (PESX and RescueESE) are severely reduced inthe exonic sequences downstream of a cryptic 50ss when comparedto those downstream of a pseudo 50ss.

RescueESE was developed to predict ESE activity based on thestatistical analysis of differences in hexamer frequencies betweenexons and introns, and between exons with weak and strong splicesites. PESX computation is based on the statistical analysis ofdifferences in RNA octamer frequencies between noncoding exonsand pseudo exons plus 50UTRs of intronless genes. Therefore, ourresults indicate that, in general, the nucleotide composition ofexonic sequences that become intronic sequences by utilization ofa cryptic 50ss resembles intronic more than exonic sequences withrespect to ESE/ESS densities. The comparison of the ESE/ESSdensities in the exonic and intronic sequences (Table 4) with those

in the exonic regions downstream of cryptic and pseudo 50ss(Table 5) strongly supports this notion.

Zhang and Chasin [2004] showed that the PESS frequencyraises above the characteristic ratio for deep intronic sequences inthe first 50 nt downstream of internal coding exons, whereas theopposite can be observed in the first 50 nt downstream of the 50ssof pseudo exons. The authors concluded that the peak in negativesignals downstream of real exons might contribute to a lockingin on the positive signals flanked by the real splice sites. Consistentwith this idea, ISSs that are bound by proteins of the hnRNPfamily can help define the exon–intron borders [Blanchette andChabot, 1999; Martinez-Contreras et al., 2006; Nasim et al.,2002]. These findings may relate also to our observation that ESSdensities, particularly those in exonic sequences downstream ofthe weak cryptic 50ss in exons 2, 22, and 27b, compare favorablywith, or are higher than, the mean ESS density (9.02) calculatedfor the first 180 nt of the introns in our dataset. Thus, it isconceivable that a high ESS density (as defined by PESX) betweencryptic and authentic 50ss corresponds to an enrichment ofintronic elements important for the definition of suboptimalexonic cryptic 50ss.

In summary, we show here that RNA-based mutation detectiontechniques are still the most reliable and effective methods toidentify splicing mutations in disease genes, and we advocate theimplementation of these methods for NF1 diagnosis, because ofthe high prevalence of such mutations specifically in this gene.In addition, we have uncovered important clues for the splicingpathway used upon 50ss mutation, as well as parameters that helpdistinguish cryptic from pseudo 50ss. These data are not onlyrelevant to a better understanding of the mechanisms of splice-siteselection, but also constitute a step towards developing toolsto predict the outcome of splice-site mutations associated withdisease.

ACKNOWLEDGMENTS

We thank all patients and family members who participated inthis study, and all the clinicians for providing patient clinical data.We are also indebted to Dr. A. Zatkova for critical reading of themanuscript and Dr. C. Lazaro for sharing updated splicing analysesof mutations published by Ars et al. [2003] (PMID] 12807981).X.R. and A.R.K. acknowledge support from NIH grant CA13106.A.R.R. was supported by a Biotechnology Overseas Associateship(BT/IN/BTOA/03/2005) from the Department of Biotechnology,Government of India.

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612 HUMANMUTATION 28(6), 599^612,2007

Human Mutation DOI 10.1002/humu