We report 281 individuals carrying a pathogenic recurrent NF1 missense variants at p.Met1149, p.Arg1276 or p.Lys1423, representing three non‐truncating NF1 hotspots in the University of Alabama at Birmingham (UAB) cohort, together identified in 1.8% of unrelated NF1 individuals. About 25% (95% CI, 20.5%‐31.2%) of individuals heterozygous for a pathogenic NF1 p.Met1149, p.Arg1276 or p.Lys1423 missense variant had a Noonan‐like phenotype, which is significantly more compared to the “classic” NF1‐affected cohorts (all P<0.0001). Furthermore, p.Arg1276 and p.Lys1423 pathogenic missense variants were associated with a high prevalence of cardiovascular abnormalities, including pulmonic stenosis (all P<0.0001), while p.Arg1276 variants had a high prevalence of symptomatic spinal neurofibromas (P<0.0001) compared with “classic” NF1‐affected cohorts. However, p.Met1149‐positive individuals had a mild phenotype, characterized mainly by pigmentary manifestations without externally visible plexiform neurofibromas, symptomatic spinal neurofibromas or symptomatic optic pathway gliomas. As up to 0.4% of unrelated individuals in the UAB cohort carries a p.Met1149 missense variant, this finding will contribute to more accurate stratification of a significant number of NF1 individuals. Although clinically relevant genotype‐phenotype correlations are rare in NF1, each affecting only a small percentage of individuals, together they impact counseling and management of a significant number of the NF1 population.

Long interspersed (L1) and Alu elements are actively amplified in the human genome through retrotransposition of their RNA intermediates by the ∼100 still retrotranspositionally fully competent L1 elements. Retrotransposition can cause inherited disease if such an element is inserted near or within a functional gene. Using direct cDNA sequencing as the primary assay for comprehensive NF1 mutation analysis, we uncovered in 18 unrelated index patients splicing alterations not readily explained at the genomic level by an underlying point-mutation or deletion. Improved PCR protocols avoiding allelic drop-out of the mutant alleles uncovered insertions of fourteen Alu elements, three L1 elements, and one poly(T) stretch to cause these splicing defects. Taken together, the 18 pathogenic L1 endonuclease-mediated de novo insertions represent the largest number of this type of mutations characterized in a single human gene. Our findings show that retrotransposon insertions account for as many as ∼0.4% of all NF1 mutations. Since altered splicing was the main effect of the inserted elements, the current finding was facilitated by the use of RNA–based mutation analysis protocols, resulting in improved detection compared to gDNA–based approaches. Six different insertions clustered in a relatively small 1.5-kb region (NF1 exons 21(16)–23(18)) within the 280-kb NF1 gene. Furthermore, three different specific integration sites, one of them located in this cluster region, were each used twice, i.e. NM_000267.3(NF1):c.1642-1_1642 in intron 14(10c), NM_000267.3(NF1):c.2835_2836 in exon 21(16), and NM_000267.3(NF1):c.4319_4320 in exon 33(25). Identification of three loci that each served twice as integration site for independent retrotransposition events as well as 1.5-kb cluster region harboring six independent insertions supports the notion of non-random insertion of retrotransposons in the human genome. Currently, little is known about which features make sites particularly vulnerable to L1 EN-mediated insertions. The here identified integration sites may serve to elucidate these features in future studies. Repetitive retrotransposable elements, including LINE1 and Alu elements accounting for more than one fourth of the human genome, are still actively amplifying. It is widely believed that retroelements insert randomly in the genome. Retroelements newly inserted in the germ line may cause genetic disease, if a functional gene is disrupted. Up to now, only ∼65 well-characterized pathogenic retroelement insertions in 31 different human genes have been reported. Therefore, retrotransposition is suspected to be underdiagnosed as disease-causing mutation mechanism. Reporting 18 novel insertions in the NF1 gene, all identified by a comprehensive RNA–based mutation analysis protocol, we show that L1 and Alu insertions represent 0.4% of all NF1 mutations. Strikingly, we found three integration sites within this 280-kb gene that were used twice independently to insert a retroelement. One of these sites was located in a 1.5-kb “hotspot” region where four additional integration sites clustered. These findings, together with three additional integration sites used multiple times independently to insert retroelements in other genes, indicate that some genomic sites may be especially prone to host newly retrotransposed elements. As some of these sites are embedded in “hotspot” regions, larger flanking sequences may play a role in making these sites particularly vulnerable.

Background: Genomic disorders are caused by copy number changes that may exhibit recurrent breakpoints processed by nonallelic homologous recombination. However, region-specific disease-associated copy number changes have also been observed which exhibit non-recurrent breakpoints. The mechanisms underlying these non-recurrent copy number changes have not yet been fully elucidated. Results: We analyze large NF1 deletions with non-recurrent breakpoints as a model to investigate the full spectrum of causative mechanisms, and observe that they are mediated by various DNA double strand break repair mechanisms, as well as aberrant replication. Further, two of the 17 NF1 deletions with non-recurrent breakpoints, identified in unrelated patients, occur in association with the concomitant insertion of SINE/variable number of tandem repeats/Alu (SVA) retrotransposons at the deletion breakpoints. The respective breakpoints are refractory to analysis by standard breakpoint-spanning PCRs and are only identified by means of optimized PCR protocols designed to amplify across GC-rich sequences. The SVA elements are integrated within SUZ12P intron 8 in both patients, and were mediated by target-primed reverse transcription of SVA mRNA intermediates derived from retrotranspositionally active source elements. Both SVA insertions occurred during early postzygotic development and are uniquely associated with large deletions of 1 Mb and 867 kb, respectively, at the insertion sites. Conclusions: Since active SVA elements are abundant in the human genome and the retrotranspositional activity of many SVA source elements is high, SVA insertion-associated large genomic deletions encompassing many hundreds of kilobases could constitute a novel and as yet under-appreciated mechanism underlying large-scale copy number changes in the human genome.

Targeted next-generation-sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy-number variations (CNVs) in addition to single-nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user-friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state-of-the-art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user-selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user-friendliness rendering it highly suitable for routine clinical diagnostics.