Web-accessible application for identifying pathogenic transcripts with RNA-seq: Increased sensitivity in diagnosis of neurodevelopmental disorders

Beyond genomics: using RNA-seq from dried blood spots to unlock the clinical relevance of splicing variation in a diagnostic setting

We aimed to assess the impact of splicing variants reported in our laboratory to gain insight into their clinical relevance. A total of 108 consecutive individuals, for whom 113 splicing variants had been reported, were selected for RNA-sequencing (RNA-seq), considering the gene expression in blood. A protocol was developed to perform RNA extraction and sequencing using the same sample (dried blood spots, DBS) provided for the DNA analysis, including library preparation and bioinformatic pipeline analysis. Splicing in genes of interest was inspected using IGV, with at least three unaffected individuals as controls. From the 113 variants, we confirmed an abnormal splicing in 64 variants (57%). In 15 variants (13%), we did not observe a splicing alteration. In the remaining 34 variants, no decision could be made on the splicing effect due to insufficient sample quality (21%) or a low number of reads (9%). The most common event leading to aberrant splicing was exon skipping, identified in 31 variants (48%). Other events included cryptic donor/acceptor site usage (n = 25; 39%), intron retention (n = 4; 6%), and other complex events (n = 4; 6%). In three patients, pathologically reduced enzymatic activity (measured using the same DBS) served as additional confirmation of the abnormal splicing caused by variants in HEXA, GAA, and GLA. We implemented an RNA-seq pipeline using the same sample provided for genomic testing. This multiomic approach, as implemented in our routine diagnostic processes, clarifies the clinical relevance of most of the analyzed variants and delivers more comprehensive genetic testing.

The improvement in diagnostic yield of developmental and epileptic encephalopathy by the multi-omics sequential testing method

Despite traditional panel and Whole Exome Sequencing (WES) assays, the causative factors for 60 % of epilepsy cases remain elusive, mainly due to incomplete detection of variant spectrums, and limited ability to interpret variants. Our research developed the multi-omics method of a comprehensive sequential testing methodology, to enhance the diagnostic yield for the etiology. In this study, we performed sequential multi-omics analyses on a cohort of 236 Chinese patients exhibiting recurrent seizures along with developmental delay or intellectual disability. Our study had devised a comprehensive multi-omics variant analysis methodology in a sequential mode. The initial analytical strategy included WES, CNV-seq and in-house cases evidence. If no pathogenic cause was identified, the subsequent analytical approach in the sequential mode included the analysis of WGS SVs, mitochondrial variations, dynamic mutations, and abnormalities in RNA-seq. Our results revealed that the initial step achieved a diagnostic detection rate of 44.1 % (104 cases). Subsequently, WGS and RNA-seq testing were performed, with 33 familial diagnoses tested positive, representing a 14 % increase. Meanwhile our pipeline has elucidated the pathogenicity classification of 72 variants which are either not yet recorded in the ClinVar database or are classified as VUS. Our study achieved an overall positive diagnostic rate of 58.1 % (137/236). In summary, our pipeline can detect comprehensive variant spectrums and provide a clear interpretation of variations with unclear clinical significance, the multi-omics sequential testing approach significantly improves the rate of genetic diagnosis for epileptic disorders.

Aberrant gene expression prediction across human tissues

Despite the frequent implication of aberrant gene expression in diseases, algorithms predicting aberrantly expressed genes of an individual are lacking. To address this need, we compile an aberrant expression prediction benchmark covering 8.2 million rare variants from 633 individuals across 49 tissues. While not geared toward aberrant expression, the deleteriousness score CADD and the loss-of-function predictor LOFTEE show mild predictive ability (1-1.6% average precision). Leveraging these and further variant annotations, we next train AbExp, a model that yields 12% average precision by combining in a tissue-specific fashion expression variability with variant effects on isoforms and on aberrant splicing. Integrating expression measurements from clinically accessible tissues leads to another two-fold improvement. Furthermore, we show on UK Biobank blood traits that performing rare variant association testing using the continuous and tissue-specific AbExp variant scores instead of LOFTEE variant burden increases gene discovery sensitivity and enables improved phenotype predictions.

BRCC3 -Associated Syndromic Moyamoya Angiopathy Diagnosed Through Clinical RNA Sequencing

Moyamoya angiopathy is a cerebral vasculopathy causing progressive stenosis of the internal carotid arteries and the compensatory development of collateral blood vessels, leading to brain ischemia and an increased risk of cerebral haemorrhage. Although multiple non-genetic causes have been associated with moyamoya syndrome, it can also be associated with rare genetic syndromes. Moyamoya Disease 4, characterised by a short stature, hypergonadotropic hypogonadism and facial dysmorphism (MYMY4, OMIM #300845), also referred to as BRCC3-associated moyamoya syndrome, has so far been described in 11 individuals. Here, we describe a 23-year-old male presenting with moyamoya syndrome, global developmental delay and intellectual disability, epilepsy, short stature and dysmorphic features, who after > 17 years of uninformative diagnostics was diagnosed with BRCC3-associated moyamoya syndrome after clinical RNA-seq. Transcriptome analysis showed reduced expression of the likely disease-causing gene BRCC3 in patient-derived fibroblasts, which was subsequently found to be caused by a ~ 26 kb Xq28 deletion. We furthermore review all reported cases of BRCC3-associated moyamoya syndrome, further delineating this clinical entity.

Fibroblast transcriptomics uncovers pathogenic genomic variants in individuals with exome-negative childhood onset epilepsy

OBJECTIVE

This study aims to improve genetic diagnosis in childhood onset epilepsy with neurodevelopmental problems by utilizing RNA sequencing of fibroblasts to identify pathogenic variants that may be missed by exome sequencing and copy number variation analysis.

METHODS

We enrolled 41 individuals with childhood onset epilepsy and neurodevelopmental problems who previously had inconclusive genetic testing. Fibroblast samples were cultured and analyzed using RNA sequencing to detect aberrant expression, aberrant splicing, and monoallelic expression using the Detection of RNA Outlier Pipeline (DROP) pipeline. Detected events were correlated with phenotypes, and long-read genome sequencing was performed on individuals with strong candidate events to identify the causal genomic variant. A systematic literature review on RNA sequencing in rare disorders was conducted to contextualize our findings.

RESULTS

RNA sequencing identified five strong candidate events in four individuals, affecting the genes QRICH1, TSC1, SMARCA1, GNAI1, and PTEN. (Likely) pathogenic genomic variants affecting expression of QRICH1, TSC1, and SMARCA1 were detected, resulting in a diagnostic yield of 7% (3/41). Two variants were not covered in the initial exome sequencing data but were revealed through long-read sequencing. The identification of a pathogenic TSC1 variant led to a previously unrecognized diagnosis of tuberous sclerosis complex. This prompted guideline-based screening, which revealed tuberous sclerosis lesions in the brain and lung, directly impacting clinical care. Notably, two of the three pathogenic events would not have been detected using whole blood due to the lack of expression of the involved genes. The lower yield of this study compared to studies in other rare disorders reflects the genetic heterogeneity of epilepsy and neurodevelopmental disorders, and the inaccessibility of affected tissue.

SIGNIFICANCE

This research underscores RNA sequencing of cultured fibroblasts as a valuable tool in genetic diagnostics for childhood onset epilepsy, particularly when conventional methods fail. Expanding the control dataset with age-matched samples and incorporating RNA sequencing with nonsense-mediated decay inhibition could further enhance diagnostic yield.

Human ITGAV variants are associated with immune dysregulation, brain abnormalities, and colitis

Integrin heterodimers containing an Integrin alpha V subunit are essential for development and play critical roles in cell adhesion and signaling. We identified biallelic variants in the gene coding for Integrin alpha V (ITGAV) in three independent families (two patients and four fetuses) that either caused abnormal mRNA and the loss of functional protein or caused mistargeting of the integrin. This led to eye and brain abnormalities, inflammatory bowel disease, immune dysregulation, and other developmental issues. Mechanistically, the reduction of functional Integrin αV resulted in the dysregulation of several pathways including TGF-β-dependent signaling and αVβ3-regulated immune signaling. These effects were confirmed using immunostaining, RNA sequencing, and functional studies in patient-derived cells. The genetic deletion of itgav in zebrafish recapitulated patient phenotypes including retinal and brain defects and the loss of microglia in early development as well as colitis in juvenile zebrafish with reduced SMAD3 expression and transcriptional regulation. Taken together, the ITGAV variants identified in this report caused a previously unknown human disease characterized by brain and developmental defects in the case of complete loss-of-function and atopy, neurodevelopmental defects, and colitis in cases of incomplete loss-of-function.

Biallelic and monoallelic variants in EFEMP1 can cause a severe and distinct subtype of heritable connective tissue disorder

Variants in EFEMP1, encoding Fibulin-3, were previously reported as a rare cause of heritable connective tissue disorder (HCTD) with recurrent hernias and joint hypermobility. We report three new cases with biallelic or monoallelic EFEMP1 variants and severe hernia phenotypes. Two male siblings of 10 and 13 years old presented with marfanoid habitus, recurrent inguinal and umbilical hernias, generalized joint hypermobility, and scoliosis. Parents and halfsiblings reported joint hypermobility and umbilical hernias. The eldest boy died at age 16 from incarcerated gastrointestinal herniation complicated by gastric and bowel necrosis with perforation. Autopsy revealed widespread intestinal diverticula. Immunohistochemistry of skin and fascia tissue did not reveal any abnormalities, including normal staining of elastic fibers. Both siblings harbored compound heterozygous likely pathogenic EFEMP1 variants (c.1320 + 2T > A, p.? and c.698G > A, p.Gly233Asp). An unrelated 58-year-old male had marfanoid features, high myopia, recurrent diaphragmatic and inguinal hernias, and chronic gastrointestinal dilatation with severe malabsorption. Both his dizygotic twin-brother and mother had recurrent hernias and high myopia. This man died at 59 years of age, and autopsy showed extensive diaphragmatic herniation, bowel diverticula, and pulmonary emphysema. A heterozygous EFEMP1 splice-variant (c.81 + 1G > A, p.?) was identified, causing exon skipping leading to a start-loss. Targeted genome reanalysis nor RNA-sequencing revealed a second variant at the other allele. The reported individuals expand the clinical and pathological phenotypes of EFEMP1-related disease, a distinct entity within the spectrum of HCTD. The severe and recurrent hernias, gastrointestinal dilatation, and diverticulosis result in an increased risk for life-threatening complications, demanding early recognition and close monitoring.

Biallelic NDC1 variants that interfere with ALADIN binding are associated with neuropathy and triple A-like syndrome

Nuclear pore complexes (NPCs) regulate nucleocytoplasmic transport and are anchored in the nuclear envelope by the transmembrane nucleoporin NDC1. NDC1 is essential for post-mitotic NPC assembly and the recruitment of ALADIN to the nuclear envelope. While no human disorder has been associated to one of the three transmembrane nucleoporins, biallelic variants in AAAS, encoding ALADIN, cause triple A syndrome (Allgrove syndrome). Triple A syndrome, characterized by alacrima, achalasia, and adrenal insufficiency, often includes progressive demyelinating polyneuropathy and other neurological complaints. In this report, diagnostic exome and/or RNA sequencing was performed in seven individuals from four unrelated consanguineous families with AAAS-negative triple A syndrome. Molecular and clinical studies followed to elucidate the pathogenic mechanism. The affected individuals presented with intellectual disability, motor impairment, severe demyelinating with secondary axonal polyneuropathy, alacrima, and achalasia. None of the affected individuals has adrenal insufficiency. All individuals presented with biallelic NDC1 in-frame deletions or missense variants that affect amino acids and protein domains required for ALADIN binding. No other significant variants associated with the phenotypic features were reported. Skin fibroblasts derived from affected individuals show decreased recruitment of ALADIN to the NE and decreased post-mitotic NPC insertion, confirming pathogenicity of the variants. Taken together, our results implicate biallelic NDC1 variants in the pathogenesis of polyneuropathy and a triple A-like disorder without adrenal insufficiency, by interfering with physiological NDC1 functions, including the recruitment of ALADIN to the NPC.

Re-analysis of whole genome sequencing ends a diagnostic odyssey: Case report of an RNU4-2 related neurodevelopmental disorder

Despite increasing knowledge of disease-causing genes in human genetics, approximately half of the individuals affected by neurodevelopmental disorders remain genetically undiagnosed. Part of this missing heritability might be caused by genetic variants outside of protein-coding genes, which are not routinely diagnostically investigated. A recent preprint identified de novo variants in the non-coding spliceosomal snRNA gene RNU4-2 as a cause of a frequent novel syndromic neurodevelopmental disorder. Here we mined 164 whole genome sequencing (WGS) trios from individuals with neurodevelopmental or multiple congenital anomaly disorders that received diagnostic genomic investigations at our clinic. We identify a recurrent de novo RNU4-2 variant (NR_003137.2(RNU4-2):n.64_65insT) in a 5-year-old girl with severe global developmental delay, hypotonia, microcephaly, and seizures that likely explains her phenotype, given that extensive previous genetic investigations failed to identify an alternative cause. We present detailed phenotyping of the individual obtained during a 5-year follow-up. This includes photographs showing recognizable facial features for this novel disorder, which might allow prioritizing other currently unexplained affected individuals sharing similar facial features for targeted investigations of RNU4-2. This case illustrates the power of re-analysis to solve previously unexplained cases even when a diagnostic genome remains negative.

Combining optical genome mapping and RNA-seq for structural variants detection and interpretation in unsolved neurodevelopmental disorders

BACKGROUND

Structural variations (SVs) are key genetic contributors to neurodevelopmental disorders (NDDs). Exome sequencing (ES), the current first-line tool for genetic testing of NDDs, falls short in SVs detection. This diagnostic gap is being actively addressed by new methods such as optical genome mapping (OGM).

METHODS

This study evaluated the utility of combining OGM and RNA-seq in the detection and interpretation of SVs in ES-negative NDDs. OGM was performed in 43 patients with NDDs with inconclusive ES results. Candidate SVs were selected based on disease association and pathogenicity evaluation, and further validated or reconstructed by alternative methods, including long-read sequencing for a complex rearrangement event. RNA-Seq was performed on blood samples from patients with candidate SVs to facilitate interpretation of pathogenicity.

RESULTS

OGM detected four candidate SVs, and RNA-seq confirmed the pathogenicity of three SVs in the patient cohort. This combined approach solved three cases-two cases with de novo SVs in genes associated with autosomal dominant NDDs, including a deletion encompassing the promoter and 5'UTR of MBD5 and an intragenic duplication of PAFAH1B1, and a third case possessing an intragenic duplication in trans with a pathogenic single-nucleotide variant of PLA2G6, associated with autosomal recessive NDDs. The expression alteration of the affected genes and the tandem positioning of two intragenic duplications were confirmed by RNA-seq. In the fourth case, OGM detected a complex rearrangement involving chromosomes 2 and 6, much more complex than the de novo t(2:6)(q13;q15) indicated by conventional cytogenetic analysis. Reconstruction showed that 17 segments of 6q15 spanning 9.3 Mb were disarranged and joined 2q11.2, with four breakpoints detected in the 5' and 3' non-coding region of the NDD-associated gene SYNCRIP. RNA-seq revealed largely preserved SYNCRIP expression, leaving the pathogenicity of this complex rearrangement event uncertain.

CONCLUSIONS

SVs in ES-negative NDDs can be identified by OGM, which is particularly useful for SVs in non-coding regions not covered by ES. OGM helps to construct complex SVs and provides information on the location and orientation of duplications, which is crucial for pathogenicity interpretation. The integration of RNA-seq facilitates the interpretation of the functional consequences of SVs at the transcriptional level. These findings demonstrate the utility and feasibility of combining OGM and RNA-seq in ES-negative cases with NDDs.

Identification of diagnostic candidates in Mendelian disorders using an RNA sequencing-centric approach

BACKGROUND

RNA sequencing (RNA-seq) is increasingly being used as a complementary tool to DNA sequencing in diagnostics where DNA analysis has been uninformative. RNA-seq enables the identification of aberrant splicing and aberrant gene expression, improving the interpretation of variants of unknown significance (VUSs), and provides the opportunity to scan the transcriptome for aberrant splicing and expression in relevant genes that may be the cause of a patient's phenotype. This work aims to investigate the feasibility of generating new diagnostic candidates in patients without a previously reported VUS using an RNA-seq-centric approach.

METHODS

We systematically assessed the transcriptomic profiles of 86 patients with suspected Mendelian disorders, 38 of whom had no candidate sequence variant, using RNA from blood samples. Each VUS was visually inspected to search for splicing abnormalities. Once aberrant splicing was identified in cases with VUS, multiple open-source alternative splicing tools were used to investigate if they would identify what was observed in IGV. Expression outliers were detected using OUTRIDER. Diagnoses in cases without a VUS were explored using two separate strategies.

RESULTS

RNA-seq allowed us to assess 71% of VUSs, detecting aberrant splicing in 14/48 patients with a VUS. We identified four new diagnoses by detecting novel aberrant splicing events in patients with no candidate sequence variants from prior DNA testing (n = 32) or where the candidate VUS did not affect splicing (n = 23). An additional diagnosis was made through the detection of skewed X-inactivation.

CONCLUSION

This work demonstrates the utility of an RNA-centric approach in identifying novel diagnoses in patients without candidate VUSs. It underscores the utility of blood-based RNA analysis in improving diagnostic yields and highlights optimal approaches for such analyses.

Impact of genome build on RNA-seq interpretation and diagnostics

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network and Genomics Research to Elucidate the Genetics of Rare Disease Consortium. Across six routinely collected biospecimens, 61% of quantified genes were not influenced by genome build. However, we identified 1,492 genes with build-dependent quantification, 3,377 genes with build-exclusive expression, and 9,077 genes with annotation-specific expression across six routinely collected biospecimens, including 566 clinically relevant and 512 known OMIM genes. Further, we demonstrate that between builds for a given gene, a larger difference in quantification is well correlated with a larger change in expression outlier calling. Combined, we provide a database of genes impacted by build choice and recommend that transcriptomics-guided analyses and diagnoses are cross referenced with these data for robustness.

Genome and RNA sequencing were essential to reveal cryptic intronic variants associated to defective ATP6AP1 mRNA processing

The diagnosis of Mendelian disorders has notably advanced with integration of whole exome and genome sequencing (WES and WGS) in clinical practice. However, challenges in variant interpretation and uncovered variants by WES still leave a substantial percentage of patients undiagnosed. In this context, integrating RNA sequencing (RNA-seq) improves diagnostic workflows, particularly for WES inconclusive cases. Additionally, functional studies are often necessary to elucidate the impact of prioritized variants on gene expression and protein function. Our study focused on three unrelated male patients (P1-P3) with ATP6AP1-CDG (congenital disorder of glycosylation), presenting with intellectual disability and varying degrees of hepatopathy, glycosylation defects, and an initially inconclusive diagnosis through WES. Subsequent RNA-seq was pivotal in identifying the underlying genetic causes in P1 and P2, detecting ATP6AP1 underexpression and aberrant splicing. Molecular studies in fibroblasts confirmed these findings and identified the rare intronic variants c.289-233C > T and c.289-289G > A in P1 and P2, respectively. Trio-WGS also revealed the variant c.289-289G > A in P3, which was a de novo change in both patients. Functional assays expressing the mutant alleles in HAP1 cells demonstrated the pathogenic impact of these variants by reproducing the splicing alterations observed in patients. Our study underscores the role of RNA-seq and WGS in enhancing diagnostic rates for genetic diseases such as CDG, providing new insights into ATP6AP1-CDG molecular bases by identifying the first two deep intronic variants in this X-linked gene. Additionally, our study highlights the need to integrate RNA-seq and WGS, followed by functional validation, in routine diagnostics for a comprehensive evaluation of patients with an unidentified molecular etiology.

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

BACKGROUND

Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging.

METHODS

To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes.

RESULTS

We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities.

CONCLUSIONS

Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.

The clinical utility and diagnostic implementation of human subject cell transdifferentiation followed by RNA sequencing

RNA sequencing (RNA-seq) has recently been used in translational research settings to facilitate diagnoses of Mendelian disorders. A significant obstacle for clinical laboratories in adopting RNA-seq is the low or absent expression of a significant number of disease-associated genes/transcripts in clinically accessible samples. As this is especially problematic in neurological diseases, we developed a clinical diagnostic approach that enhanced the detection and evaluation of tissue-specific genes/transcripts through fibroblast-to-neuron cell transdifferentiation. The approach is designed specifically to suit clinical implementation, emphasizing simplicity, cost effectiveness, turnaround time, and reproducibility. For clinical validation, we generated induced neurons (iNeurons) from 71 individuals with primary neurological phenotypes recruited to the Undiagnosed Diseases Network. The overall diagnostic yield was 25.4%. Over a quarter of the diagnostic findings benefited from transdifferentiation and could not be achieved by fibroblast RNA-seq alone. This iNeuron transcriptomic approach can be effectively integrated into diagnostic whole-transcriptome evaluation of individuals with genetic disorders.

Practical Recommendations for the Selection of Patients for Individualized Splice-Switching ASO-Based Treatments

Although around 6% of the world's population is affected by rare diseases, only a small number of disease-modifying therapies are available. In recent years, antisense oligonucleotides (ASOs) have emerged as one option for the development of therapeutics for orphan diseases. In particular, ASOs can be utilized for individualized genetic treatments, addressing patients with a known disease-causing genetic variant, who would otherwise not be able to receive therapy. Careful prioritization of genetic variants amenable to an ASO approach is crucial to increase chances for successful treatments and reduce costs and time for drug development. At present, there is no consensus on how to systematically approach this selection procedure. Here, we present practical guidelines to evaluate disease-causing variants and standardize the process of selecting n-of-1 cases. We focus on variants leading to a loss of function in monogenic disorders and consider which splice-switching ASO-mediated treatments are applicable in each case. To ease the understanding and application of our guidelines, we created a hypothetical transcript covering different pathogenic variants and explained their evaluation in detail. We support our recommendations with real-life examples and add further considerations to be applied to specific cases to provide a comprehensive framework for selecting eligible variants.

Genomes in clinical care

In the era of precision medicine, genome sequencing (GS) has become more affordable and the importance of genomics and multi-omics in clinical care is increasingly being recognized. However, how to scale and effectively implement GS on an institutional level remains a challenge for many. Here, we present Genome First and Ge-Med, two clinical implementation studies focused on identifying the key pillars and processes that are required to make routine GS and predictive genomics a reality in the clinical setting. We describe our experience and lessons learned for a variety of topics including test logistics, patient care processes, data reporting, and infrastructure. Our model of providing clinical care and comprehensive genomic analysis from a single source may be used by other centers with a similar structure to facilitate the implementation of omics-based personalized health concepts in medicine.

Diagnostic genome sequencing improves diagnostic yield: a prospective single-centre study in 1000 patients with inherited eye diseases

PURPOSE

Genome sequencing (GS) is expected to reduce the diagnostic gap in rare disease genetics. We aimed to evaluate a scalable framework for genome-based analyses 'beyond the exome' in regular care of patients with inherited retinal degeneration (IRD) or inherited optic neuropathy (ION).

METHODS

PCR-free short-read GS was performed on 1000 consecutive probands with IRD/ION in routine diagnostics. Complementary whole-blood RNA-sequencing (RNA-seq) was done in a subset of 74 patients. An open-source bioinformatics analysis pipeline was optimised for structural variant (SV) calling and combined RNA/DNA variation interpretation.

RESULTS

A definite genetic diagnosis was established in 57.4% of cases. For another 16.7%, variants of uncertain significance were identified in known IRD/ION genes, while the underlying genetic cause remained unresolved in 25.9%. SVs or alterations in non-coding genomic regions made up for 12.7% of the observed variants. The RNA-seq studies supported the classification of two unclear variants.

CONCLUSION

GS is feasible in clinical practice and reliably identifies causal variants in a substantial proportion of individuals. GS extends the diagnostic yield to rare non-coding variants and enables precise determination of SVs. The added diagnostic value of RNA-seq is limited by low expression levels of the major IRD disease genes in blood.

Impact of genome build on RNA-seq interpretation and diagnostics

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network (UDN) and Genomics Research to Elucidate the Genetics of Rare Disease (GREGoR) Consortium. We identified 2,800 genes with build-dependent quantification across six routinely-collected biospecimens, including 1,391 protein-coding genes and 341 known rare disease genes. We further observed multiple genes that only have detectable expression in a subset of genome builds. Finally, we characterized how genome build impacts the detection of outlier transcriptomic events. Combined, we provide a database of genes impacted by build choice, and recommend that transcriptomics-guided analyses and diagnoses are cross-referenced with these data for robustness.

Integrating RNA-Seq into genome sequencing workflow enhances the analysis of structural variants causing neurodevelopmental disorders

BACKGROUND

Molecular diagnosis of neurodevelopmental disorders (NDDs) is mainly based on exome sequencing (ES), with a diagnostic yield of 31% for isolated and 53% for syndromic NDD. As sequencing costs decrease, genome sequencing (GS) is gradually replacing ES for genome-wide molecular testing. As many variants detected by GS only are in deep intronic or non-coding regions, the interpretation of their impact may be difficult. Here, we showed that integrating RNA-Seq into the GS workflow can enhance the analysis of the molecular causes of NDD, especially structural variants (SVs), by providing valuable complementary information such as aberrant splicing, aberrant expression and monoallelic expression.

METHODS

We performed trio-GS on a cohort of 33 individuals with NDD for whom ES was inconclusive. RNA-Seq on skin fibroblasts was then performed in nine individuals for whom GS was inconclusive and optical genome mapping (OGM) was performed in two individuals with an SV of unknown significance.

RESULTS

We identified pathogenic or likely pathogenic variants in 16 individuals (48%) and six variants of uncertain significance. RNA-Seq contributed to the interpretation in three individuals, and OGM helped to characterise two SVs.

CONCLUSION

Our study confirmed that GS significantly improves the diagnostic performance of NDDs. However, most variants detectable by GS alone are structural or located in non-coding regions, which can pose challenges for interpretation. Integration of RNA-Seq data overcame this limitation by confirming the impact of variants at the transcriptional or regulatory level. This result paves the way for new routinely applicable diagnostic protocols.

Solving the unsolved genetic epilepsies: Current and future perspectives

Many patients with epilepsy undergo exome or genome sequencing as part of a diagnostic workup; however, many remain genetically unsolved. There are various factors that account for negative results in exome/genome sequencing for patients with epilepsy: (1) the underlying cause is not genetic; (2) there is a complex polygenic explanation; (3) the illness is monogenic but the causative gene remains to be linked to a human disorder; (4) family segregation with reduced penetrance; (5) somatic mosaicism or the complexity of, for example, a structural rearrangement; or (6) limited knowledge or diagnostic tools that hinder the proper classification of a variant, resulting in its designation as a variant of unknown significance. The objective of this review is to outline some of the diagnostic options that lie beyond the exome/genome, and that might become clinically relevant within the foreseeable future. These options include: (1) re-analysis of older exome/genome data as knowledge increases or symptoms change; (2) looking for somatic mosaicism or long-read sequencing to detect low-complexity repeat variants or specific structural variants missed by traditional exome/genome sequencing; (3) exploration of the non-coding genome including disruption of topologically associated domains, long range non-coding RNA, or other regulatory elements; and finally (4) transcriptomics, DNA methylation signatures, and metabolomics as complementary diagnostic methods that may be used in the assessment of variants of unknown significance. Some of these tools are currently not integrated into standard diagnostic workup. However, it is reasonable to expect that they will become increasingly available and improve current diagnostic capabilities, thereby enabling precision diagnosis in patients who are currently undiagnosed.

Integrative omics approaches to advance rare disease diagnostics

Over the past decade high-throughput DNA sequencing approaches, namely whole exome and whole genome sequencing became a standard procedure in Mendelian disease diagnostics. Implementation of these technologies greatly facilitated diagnostics and shifted the analysis paradigm from variant identification to prioritisation and evaluation. The diagnostic rates vary widely depending on the cohort size, heterogeneity and disease and range from around 30% to 50% leaving the majority of patients undiagnosed. Advances in omics technologies and computational analysis provide an opportunity to increase these unfavourable rates by providing evidence for disease-causing variant validation and prioritisation. This review aims to provide an overview of the current application of several omics technologies including RNA-sequencing, proteomics, metabolomics and DNA-methylation profiling for diagnostics of rare genetic diseases in general and inborn errors of metabolism in particular.