SpliceLauncher: a tool for detection, annotation and relative quantification of alternative junctions from RNAseq data.

SUMMARY: Alternative splicing is an important biological process widely analyzed in molecular diagnostic settings. Indeed, a variant can be pathogenic by splicing alteration and a suspected pathogenic variant (e.g. truncating variant) can be rescued by splicing. In this context, detecting and quantifying alternative splicing is challenging. We developed SpliceLauncher, a fast and easy to use open source tool that aims at detecting, annotating and quantifying alternative splice junctions at high resolution. AVAILABILITY AND IMPLEMENTATION: SpliceLauncher is available at https://github.com/raphaelleman/SpliceLauncher. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.

Variant interpretation is the key issue in molecular diagnosis. Spliceogenic variants exemplify this issue as each nucleotide variant can be deleterious via disruption or creation of splice site consensus sequences. Consequently, reliable in silico prediction of variant spliceogenicity would be a major improvement. Thanks to an international effort, a set of 395 variants studied at the mRNA level and occurring in 5' and 3' consensus regions (defined as the 11 and 14 bases surrounding the exon/intron junction, respectively) was collected for 11 different genes, including BRCA1, BRCA2, CFTR and RHD, and used to train and validate a new prediction protocol named Splicing Prediction in Consensus Elements (SPiCE). SPiCE combines in silico predictions from SpliceSiteFinder-like and MaxEntScan and uses logistic regression to define optimal decision thresholds. It revealed an unprecedented sensitivity and specificity of 99.5 and 95.2%, respectively, and the impact on splicing was correctly predicted for 98.8% of variants. We therefore propose SPiCE as the new tool for predicting variant spliceogenicity. It could be easily implemented in any diagnostic laboratory as a routine decision making tool to help geneticists to face the deluge of variants in the next-generation sequencing era. SPiCE is accessible at (https://sourceforge.net/projects/spicev2-1/).

Landscape of pathogenic variations in a panel of 34 genes and cancer risk estimation from 5131 HBOC families.

PURPOSE: Integration of gene panels in the diagnosis of hereditary breast and ovarian cancer (HBOC) requires a careful evaluation of the risk associated with pathogenic or likely pathogenic variants (PVs) detected in each gene. Here we analyzed 34 genes in 5131 suspected HBOC index cases by next-generation sequencing. METHODS: Using the Exome Aggregation Consortium data sets plus 571 individuals from the French Exome Project, we simulated the probability that an individual from the Exome Aggregation Consortium carries a PV and compared it to the estimated frequency within the HBOC population. RESULTS: Odds ratio conferred by PVs within BRCA1, BRCA2, PALB2, RAD51C, RAD51D, ATM, BRIP1, CHEK2, and MSH6 were estimated at 13.22 [10.01-17.22], 8.61 [6.78-10.82], 8.22 [4.91-13.05], 4.54 [2.55-7.48], 5.23 [1.46-13.17], 3.20 [2.14-4.53], 2.49 [1.42-3.97], 1.67 [1.18-2.27], and 2.50 [1.12-4.67], respectively. PVs within RAD51C, RAD51D, and BRIP1 were associated with ovarian cancer family history (OR = 11.36 [5.78-19.59], 12.44 [2.94-33.30] and 3.82 [1.66-7.11]). PALB2 PVs were associated with bilateral breast cancer (OR = 16.17 [5.48-34.10]) and BARD1 PVs with triple-negative breast cancer (OR = 11.27 [3.37-25.01]). Burden tests performed in both patients and the French Exome Project population confirmed the association of PVs of BRCA1, BRCA2, PALB2, and RAD51C with HBOC. CONCLUSION: Our results validate the integration of PALB2, RAD51C, and RAD51D in the diagnosis of HBOC and suggest that the other genes are involved in an oligogenic determinism.

The BRCA1 c.5434C->G (p.Pro1812Ala) variant induces a deleterious exon 23 skipping by affecting exonic splicing regulatory elements.

BACKGROUND A large fraction of the sequence variants of unknown significance or unclassified variants (UVs) could be pathogenic by affecting mRNA splicing. The breast and ovarian cancer susceptibility gene BRCA1 exhibits a large spectrum of sequence variation but only two variants, both located in exon 18, have been shown experimentally to affect splicing regulatory elements. The present study investigated the impact on splicing of the variant BRCA1 c.5434C-->G (p.Pro1812Ala), identified in an ovarian cancer patient. This variant has previously been studied at the protein level with inconclusive results concerning its pathogenic role. METHODS Analysis of RNA from patient peripheral blood was performed by RT-PCR. The effect of the variant was tested by using splicing reporter hybrid minigene assays. RESULTS Using patient RNA analyses and hybrid minigene assays, we showed that this variant induces a major splicing defect, with skipping of exon 23, resulting in frameshift and predicted protein termination within the second BRCT domain. Moreover, we showed that the segment c.5420-5449 of BRCA1, in the centre of exon 23, exhibits splicing enhancer properties. This enhancement is abolished by the c.5434C-->G mutation, indicating that the nucleotide change, in this highly conserved region, affects a splicing regulatory element. Bioinformatics analyses predict that the mutation c.5434C-->G creates an hnRNPA1 dependent splicing silencer. CONCLUSION These data, together with segregation data, argue for the classification of BRCA1 c.5434C-->G as a pathogenic splicing mutation. These results also suggest that UVs in highly conserved nucleotide sequences of short exons may be good candidates for detecting functionally relevant splicing regulatory elements.

Detecting splicing patterns in genes involved in hereditary breast and ovarian cancer.

Interpretation of variants of unknown significance (VUS) is a major challenge for laboratories performing molecular diagnosis of hereditary breast and ovarian cancer (HBOC), especially considering that many genes are now known to be involved in this syndrome. One important way these VUS can have a functional impact is through their effects on RNA splicing. Here we present a custom RNA-Seq assay plus bioinformatics and biostatistics pipeline to analyse specifically alternative and abnormal splicing junctions in 11 targeted HBOC genes. Our pipeline identified 14 new alternative splices in BRCA1 and BRCA2 in addition to detecting the majority of known alternative spliced transcripts therein. We provide here the first global splicing pattern analysis for the other nine genes, which will enable a comprehensive interpretation of splicing defects caused by VUS in HBOC. Previously known splicing alterations were consistently detected, occasionally with a more complex splicing pattern than expected. We also found that splicing in the 11 genes is similar in blood and breast tissue, supporting the utility and simplicity of blood splicing assays. Our pipeline is ready to be integrated into standard molecular diagnosis for HBOC, but it could equally be adapted for an integrative analysis of any multigene disorder.

OutLyzer: software for extracting low-allele-frequency tumor mutations from sequencing background noise in clinical practice.

Highlighting tumoral mutations is a key step in oncology for personalizing care. Considering the genetic heterogeneity in a tumor, software used for detecting mutations should clearly distinguish real tumor events of interest that could be predictive markers for personalized medicine from false positives. OutLyzer is a new variant-caller designed for the specific and sensitive detection of mutations for research and diagnostic purposes. It is based on statistic and local evaluation of sequencing background noise to highlight potential true positive variants. 130 previously genotyped patients were sequenced after enrichment by capturing the exons of 22 genes. Sequencing data were analyzed by HaplotypeCaller, LofreqStar, Varscan2 and OutLyzer. OutLyzer had the best sensitivity and specificity with a fixed limit of detection for all tools of 1% for SNVs and 2% for Indels. OutLyzer is a useful tool for detecting mutations of interest in tumors including low allele-frequency mutations, and could be adopted in standard practice for delivering targeted therapies in cancer treatment.

Genetic profiles of cervical tumors by high-throughput sequencing for personalized medical care.

Cancer treatment is facing major evolution since the advent of targeted therapies. Building genetic profiles could predict sensitivity or resistance to these therapies and highlight disease-specific abnormalities, supporting personalized patient care. In the context of biomedical research and clinical diagnosis, our laboratory has developed an oncogenic panel comprised of 226 genes and a dedicated bioinformatic pipeline to explore somatic mutations in cervical carcinomas, using high-throughput sequencing. Twenty-nine tumors were sequenced for exons within 226 genes. The automated pipeline used includes a database and a filtration system dedicated to identifying mutations of interest and excluding false positive and germline mutations. One-hundred and seventy-six total mutational events were found among the 29 tumors. Our cervical tumor mutational landscape shows that most mutations are found in PIK3CA (E545K, E542K) and KRAS (G12D, G13D) and others in FBXW7 (R465C, R505G, R479Q). Mutations have also been found in ALK (V1149L, A1266T) and EGFR (T259M). These results showed that 48% of patients display at least one deleterious mutation in genes that have been already targeted by the Food and Drug Administration approved therapies. Considering deleterious mutations, 59% of patients could be eligible for clinical trials. Sequencing hundreds of genes in a clinical context has become feasible, in terms of time and cost. In the near future, such an analysis could be a part of a battery of examinations along the diagnosis and treatment of cancer, helping to detect sensitivity or resistance to targeted therapies and allow advancements towards personalized oncology.

Next-generation sequencing for the diagnosis of hereditary breast and ovarian cancer using genomic capture targeting multiple candidate genes.

To optimize the molecular diagnosis of hereditary breast and ovarian cancer (HBOC), we developed a next-generation sequencing (NGS)-based screening based on the capture of a panel of genes involved, or suspected to be involved in HBOC, on pooling of indexed DNA and on paired-end sequencing in an Illumina GAIIx platform, followed by confirmation by Sanger sequencing or MLPA/QMPSF. The bioinformatic pipeline included CASAVA, NextGENe, CNVseq and Alamut-HT. We validated this procedure by the analysis of 59 patients' DNAs harbouring SNVs, indels or large genomic rearrangements of BRCA1 or BRCA2. We also conducted a blind study in 168 patients comparing NGS versus Sanger sequencing or MLPA analyses of BRCA1 and BRCA2. All mutations detected by conventional procedures were detected by NGS. We then screened, using three different versions of the capture set, a large series of 708 consecutive patients. We detected in these patients 69 germline deleterious alterations within BRCA1 and BRCA2, and 4 TP53 mutations in 468 patients also tested for this gene. We also found 36 variations inducing either a premature codon stop or a splicing defect among other genes: 5/708 in CHEK2, 3/708 in RAD51C, 1/708 in RAD50, 7/708 in PALB2, 3/708 in MRE11A, 5/708 in ATM, 3/708 in NBS1, 1/708 in CDH1, 3/468 in MSH2, 2/468 in PMS2, 1/708 in BARD1, 1/468 in PMS1 and 1/468 in MLH3. These results demonstrate the efficiency of NGS in performing molecular diagnosis of HBOC. Detection of mutations within other genes than BRCA1 and BRCA2 highlights the genetic heterogeneity of HBOC.

Contribution of bioinformatics predictions and functional splicing assays to the interpretation of unclassified variants of the BRCA genes.

A large fraction of sequence variants of unknown significance (VUS) of the breast and ovarian cancer susceptibility genes BRCA1 and BRCA2 may induce splicing defects. We analyzed 53 VUSs of BRCA1 or BRCA2, detected in consecutive molecular screenings, by using five splicing prediction programs, and we classified them into two groups according to the strength of the predictions. In parallel, we tested them by using functional splicing assays. A total of 10 VUSs were predicted by two or more programs to induce a significant reduction of splice site strength or activation of cryptic splice sites or generation of new splice sites. Minigene-based splicing assays confirmed four of these predictions. Five additional VUSs, all at internal exon positions, were not predicted to induce alterations of splice sites, but revealed variable levels of exon skipping, most likely induced by the modification of exonic splicing regulatory elements. We provide new data in favor of the pathogenic nature of the variants BRCA1 c.212+3A>G and BRCA1 c.5194-12G>A, which induced aberrant out-of-frame mRNA forms. Moreover, the novel variant BRCA2 c.7977-7C>G induced in frame inclusion of 6 nt from the 3' end of intron 17. The novel variants BRCA2 c.520C>T and BRCA2 c.7992T>A induced incomplete skipping of exons 7 and 18, respectively. This work highlights the contribution of splicing minigene assays to the assessment of pathogenicity, not only when patient RNA is not available, but also as a tool to improve the accuracy of bioinformatics predictions.