Effectiveness of integrated interpretation of exome and corresponding transcriptome data for detecting splicing variants of genes associated with autosomal recessive disorders

Truncating variants of the sterol recognition region of SHH cause hypertelorism phenotype rather than hypotelorism-holoprosencephaly

Sonic hedgehog signaling molecule (SHH) is a key molecule in the cilia-mediated signaling pathway and a critical morphogen in embryogenesis. The association between loss-of-function variants of SHH and holoprosencephaly is well established. In mice experiments, reduced or increased signaling of SHH have been shown to be associated with narrowing or excessive expansion of the facial midline, respectively. Herein, we report two unrelated patients with de novo truncating variants of SHH presenting with hypertelorism rather than hypotelorism. The first patient was a 13-year-old girl. Her facial features included hypertelorism, strabismus, telecanthus, malocclusion, frontal bossing, and wide widow's peak. She had borderline developmental delay and agenesis of the corpus callosum. She had a nonsense variant of SHH: Chr7(GRCh38):g.155802987C > T, NM_000193.4:c.1302G > A, p.(Trp434*). The second patient was a 25-year-old girl. Her facial features included hypertelorism and wide widow's peak. She had developmental delay and agenesis of the corpus callosum. She had a frameshift variant of SHH: Chr7(GRCh38):g.155803072_155803074delCGGinsT, NM_000193.4:c.1215_1217delCCGinsA, p.(Asp405Glufs*92). The hypertelorism phenotype contrasts sharply with the prototypical hypotelorism-holoprosencephaly phenotype associated with loss-of-function of SHH. We concluded that a subset of truncating variants of SHH could be associated with hypertelorism rather than hypotelorism.

Integration of exome-seq and mRNA-seq using DawnRank, identified genes involved in innate immunity as drivers of breast cancer in the Indian cohort

Genetic heterogeneity influences the prognosis and therapy of breast cancer. The cause of disease progression varies and can be addressed individually. To identify the mutations and their impact on disease progression at an individual level, we sequenced exome and transcriptome from matched normal-tumor samples. We utilised DawnRank to prioritise driver genes and identify specific mutations in Indian patients. Mutations in the C3 and HLA genes were identified as drivers of disease progression, indicating the involvement of the innate immune system. We performed immune profiling on 16 matched normal/tumor samples using CIBERSORTx. We identified CD8+ve T cells, M2 macrophages, and neutrophils to be enriched in luminal A and T cells CD4+naïve, natural killer (NK) cells activated, T follicular helper (Tfh) cells, dendritic cells activated, and neutrophils in triple-negative breast cancer (TNBC) subtypes. Weighted gene co-expression network analysis (WGCNA) revealed activation of T cell-mediated response in ER positive samples and Interleukin and Interferons in ER negative samples. WGCNA analysis also identified unique pathways for each individual, suggesting that rare mutations/expression signatures can be used to design personalised treatment.

Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes

Pathogenic/likely pathogenic variants in susceptibility genes that interrupt RNA splicing are a well-documented mechanism of hereditary cancer syndromes development. However, if RNA studies are not performed, most of the variants beyond the canonical GT-AG splice site are characterized as variants of uncertain significance (VUS). To decrease the VUS burden, we have bioinformatically evaluated all novel VUS detected in 732 consecutive patients tested in the routine genetic counseling process. Twelve VUS that were predicted to cause splicing defects were selected for mRNA analysis. Here, we report a functional characterization of 12 variants located beyond the first two intronic nucleotides using RNAseq in APC, ATM, FH, LZTR1, MSH6, PALB2, RAD51C, and TP53 genes. Based on the analysis of mRNA, we have successfully reclassified 50% of investigated variants. 25% of variants were downgraded to likely benign, whereas 25% were upgraded to likely pathogenic leading to improved clinical management of the patient and the family members.

Novel alterations in IFT172 and KIFAP3 may induce basal cell carcinoma

Background

Basal cell carcinoma (BCC) is the most commonly occurring neoplasm in patients with Gorlin syndrome. It is widely accepted that multiple basal cell carcinomas simultaneously develop in middle-aged patients with this syndrome. However, the presence of driver genes other than the PTCH1 in Gorlin syndrome has not been explored. This study aimed to identify common gene mutations other than PTCH1 in simultaneously occurring basal cell carcinomas in patients with Gorlin syndrome via exome sequencing analysis.

Methods

Next-generation sequencing analysis was performed using four basal cell carcinoma samples, one dental keratinocyte sample, and two epidermoid cyst samples, which were surgically resected from one patient with Gorlin syndrome on the same day.

Results

Overall, 282 somatic mutations were identified in the neoplasms. No additional somatic mutations in PTCH1, PTCH2, TP53, and SMO were identified. However, enrichment analysis showed that multiple genes, such as IFT172 and KIFAP3, could regulate ciliary functions important for Hedgehog signaling.

Conclusion

The development of BCCs in patients with Gorlin syndrome may be triggered by mutations that cause substantial dysfunction of cilia.

New Approach for Detection of Normal Alternative Splicing Events and Aberrant Spliceogenic Transcripts with Long-Range PCR and Deep RNA Sequencing

RNA sequencing is a promising technique for detecting normal and aberrant RNA isoforms. Here, we present a new single-gene, straightforward 1-day hands-on protocol for detection of splicing alterations with deep RNA sequencing from blood. We have validated our method’s accuracy by detecting previously published normal splicing isoforms of STK11 gene. Additionally, the same technique was used to provide the first comprehensive catalogue of naturally occurring alternative splicing events of the NBN gene in blood. Furthermore, we demonstrate that our approach can be used for detection of splicing impairment caused by genetic variants. Therefore, we were able to reclassify three variants of uncertain significance: NBN:c.584G>A, STK11:c.863-5_863-3delCTC and STK11:c.615G>A. Due to the simplicity of our approach, it can be incorporated into any molecular diagnostics laboratory for determination of variant’s impact on splicing.

Role of chimeric transcript formation in the pathogenesis of birth defects

Chimeric transcripts are formed by chromosomal aberrations. Little is known about the role of chimeric transcripts in the pathogenesis of birth defects. We reanalyzed RNA-seq data in alignment map files from the peripheral blood of 56 patients in whom the diagnoses could not be confirmed by standard exome analysis and transcriptome analysis to screen for chimeric transcripts using a dedicated software, ChimPipe. Chimeric analysis led to a diagnosis in two of the 56 patients: (a) the first patient had a chimeric transcript spanning the causative gene ZEB2 and the GTDC1 gene in its neighboring locus. RNA-seq revealed reads spanning exon 5 of ZEB2 and exon 7 of GTDC1. Whole genome sequencing revealed a 436-kb deletion spanning intron 4 of ZEB2 and intron 7 of GTDC1 and the diagnosis of Mowat-Wilson syndrome was made. (b) The second patient had a chimeric transcript spanning the causative gene KCNK9 and the TRAPPC9 gene in its neighboring locus. RNA-seq revealed reads spanning exon 21 of TRAPPC9 and exon 1 of KCNK9. Whole genome sequencing revealed a 186-kb deletion spanning intron 20 of TRAPPC9 and intron 1 of KCNK9 in this patient. KCNK9 gene is a maternally expressed imprinted gene. The diagnosis of Birk-Barel syndrome was made. Thus, both patients had chimeric transcripts that were directly involved in the pathogenesis of the birth defects. The approach reported herein, of detecting chimeric transcripts from RNA-seq data, is unique in that the approach does not rely on any prior information on the presence of genomic deletion.

Multi-Omics Approaches to Improve Mitochondrial Disease Diagnosis: Challenges, Advances, and Perspectives

Mitochondrial diseases (MD) are rare disorders caused by deficiency of the mitochondrial respiratory chain, which provides energy in each cell. They are characterized by a high clinical and genetic heterogeneity and in most patients, the responsible gene is unknown. Diagnosis is based on the identification of the causative gene that allows genetic counseling, prenatal diagnosis, understanding of pathological mechanisms, and personalized therapeutic approaches. Despite the emergence of Next Generation Sequencing (NGS), to date, more than one out of two patients has no diagnosis in the absence of identification of the responsible gene. Technologies currently used for detecting causal variants (genetic alterations) is far from complete, leading many variants of unknown significance (VUS) and mainly based on the use of whole exome sequencing thus neglecting the identification of non-coding variants. The complexity of human genome and its regulation at multiple levels has led biologists to develop several assays to interrogate the different aspects of biological processes. While one-dimension single omics investigation offers a peek of this complex system, the combination of different omics data allows the discovery of coherent signatures. The community of computational biologists and bioinformaticians, in order to integrate data from different omics, has developed several approaches and tools. However, it is difficult to understand which suits the best to predict diverse phenotypic outcome. First attempts to use multi-omics approaches showed an improvement of the diagnostic power. However, we are far from a complete understanding of MD and their diagnosis. After reviewing multi-omics algorithms developed in the latest years, we are proposing here a novel data-driven classification and we will discuss how multi-omics will change and improve the diagnosis of MD. Due to the growing use of multi-omics approaches in MD, we foresee that this work will contribute to set up good practices to perform multi-omics data integration to improve the prediction of phenotypic outcomes and the diagnostic power of MD.

Diagnostic utility of integrated analysis of exome and transcriptome: Successful diagnosis of Au-Kline syndrome in a patient with submucous cleft palate, scaphocephaly, and intellectual disabilities

Background

A weakness of exome analysis lies in inability to characterize aberrant splicing other than those involving consensus donor‐acceptor sequence. To overcome this limitation, we developed a novel analytic method SAVNet that combines transcriptome and exome analysis which enabled the successful detection of carriers of splicing variants in the disease‐causing genes of autosomal recessive disorders within a normal cohort. However, the clinical utility of the SAVNet analysis in delineating splicing defects in patients without a diagnosis has yet to be documented.

Method

We performed SAVNet analysis using the integrated analysis of exome and transcriptome analysis from the peripheral blood of the patient. The patient is an undiagnosed Japanese female patient with submucous cleft palate, scaphocephaly and intellectual disability with no words at 8 years of age. Dysmorphic features included a long face, a short palpebral fissure, thick lips with an open month, premaxillary hypoplasia, a depressed nasal bridge, and satyr ears.

Result

A SAVNet analysis showed that a heterozygous intronic variant located at the −10 position of exon 5 of the HNRNPK gene on chromosome 9 created a new splice acceptor sequence “ag” and led to the incorporation of 9 intronic nucleotides into the coding sequence. The mutant protein would have three extra amino acid residues, Leu‐Leu‐Gln, inserted within the critical KH domain. The patient was diagnosed as having recently delineated Au–Kline syndrome, which is characterized by cleft palate, craniosynostosis, and intellectual disability.

Conclusion

The successful molecular diagnosis of the presently reported patient illustrates the diagnostic utility of the SAVNet analysis as an innovative way of implementing an integrated exome‐transcriptome analysis in clinical settings.

Shortfall of exome analysis for diagnosis of Shwachman-Diamond syndrome: Mismapping due to the pseudogene SBDSP1

Shwachman-Diamond syndrome characterized by metaphyseal dysplasia, pancreatic insufficiency, and pancytopenia is caused by biallelic mutations in SBDS. Gene conversion between SBDS and its pseudogene SBDSP1 is the major cause. Here, we report two unrelated patients with Shwachman-Diamond syndrome who were shown to be compound heterozygotes for relatively frequent pathogenic alleles (the 258+2T>C allele and another allele composed of 183-184TA>CT and 201A>G) using an established polymerase chain reaction sequencing assay with SBDS-specific primers. Exome analysis of the patients showed discrepant results: 258+2T>C with variant allele frequency around 0.85, and no variants detected for the 183-184TA>CT allele. Parental exome analysis of the two families further supported this notion. Confronted with two patients with an unexpected segregation pattern, we performed a transcriptome analysis of peripheral blood-derived mRNA to demonstrate that the results were compatible with those obtained using SBDS-specific PCR primers. Both alleles could be accounted for by gene conversion events. The diagnostic discrepancy can be accounted for by a decreased efficiency in the computational mapping of the reads with 183-184TA>CT and 201A>G to the reference sequence of the SBDS locus during exome analysis. This report highlights the pitfall of exome analysis for genes with pseudogenes, such as SBDS and the alternative use of RNA-seq is recommended to circumvent this problem.