Improved detection of aberrant splicing with FRASER 2.0 and the intron Jaccard index

Translating Muscle RNAseq Into the Clinic for the Diagnosis of Muscle Diseases

OBJECTIVE

Approximately half of patients with hereditary myopathies remain without a definitive genetic diagnosis after DNA next-generation sequencing (NGS). Here, we implemented transcriptome analysis of muscle biopsies as a complementary diagnostic tool for patients with muscle disease but no definitive genetic diagnosis after exome sequencing.

METHODS

In total, 70 undiagnosed cases with suspected genetic muscular dystrophies or congenital myopathies were included in the study. Muscle RNAseq comprised the analysis of aberrant splicing, aberrant expression, and monoallelic expression. In addition, existing NGS data or variant calling from RNAseq were reanalyzed, and genome sequencing was performed in selected cases. Four aberrant splicing open-source tools were compared and assessed.

RESULTS

RNAseq established a diagnosis in 10/70 patients (14.3%) by identifying aberrant transcripts produced by single nucleotide variants (7/10) or copy number variants (3/10). Reanalysis of NGS data allowed the diagnosis in 9/70 individuals (12.9%). Based on this cohort, FRASER was the tool that reported more splicing outlier events per sample while showing the highest accuracy (81.26%).

CONCLUSIONS

We demonstrate the utility of RNAseq in identifying causative variants in muscle diseases. Evaluation of four aberrant splicing tools allowed efficient identification of most pathogenic splicing events, obtaining a manageable number of candidate events for manual inspection, demonstrating feasibility for translation into a clinical setting. We also show how the integration of omic technologies reduces the turnaround time to identify causative variants.

An outlier approach: advancing diagnosis of neurological diseases through integrating proteomics into multi-omics guided exome reanalysis

Neurodevelopmental disorders (NDDs) often have unknown genetic causes. Current efforts in identifying disease-related genetic variants using exome or genome sequencing still lead to an excessive number of variants of uncertain significance (VUS). There is an increasing interest in transcriptomics and, more recently, proteomics for variant detection and interpretation. In this study, we integrated quantitative liquid chromatography-mass spectrometry proteomics, RNA sequencing, and exome reanalysis to resolve VUS and detect novel causal variants in 34 patients with undiagnosed NDDs, using the software PROTRIDER and DROP to detect protein outliers and RNA outliers, respectively. We obtained a diagnosis in 11 cases (32%) resulting from the increased amount of information provided by the two additional levels of omics (n = 5) and the updated literature evidence (n = 6). Our experience suggests the potential of this outlier-detection multi-omics workflow for improving diagnostic yield in NDDs and other rare disorders.

Clinical validation of RNA sequencing for Mendelian disorder diagnostics

Despite rapid advancements in clinical sequencing, over half of diagnostic evaluations still lack definitive results. RNA sequencing (RNA-seq) has shown promise in research settings for bridging this gap by providing essential functional data for accurate interpretation of diagnostic sequencing results. However, despite advanced research pipelines, clinical translation of diagnostic RNA-seq has not yet been realized. We have developed and validated a clinical diagnostic RNA-seq test for individuals with suspected genetic disorders who have existing or concurrent comprehensive DNA diagnostic testing. This diagnostic RNA-seq test processes RNA samples from fibroblasts or blood and derives clinical interpretations based on the analytical detection of outliers in gene expressions and splicing patterns. The clinical validation involves 130 samples, including 90 negative and 40 positive samples. We developed provisional expression and splicing benchmarks using short-read and long-read RNA-seq data from the GM24385 lymphoblastoid sample produced by the Genome in a Bottle Consortium. For clinical validation, we first established reference ranges for each gene and junction based on expression distributions from our control data. We then evaluated the clinical performance of our outlier-based pipeline using 40 positive samples with previously identified diagnostic findings from the Undiagnosed Diseases Network project. Our study provides a paradigm and necessary resources for independent laboratories to validate a clinical RNA-seq test.

Phenotype-driven genomics enhance diagnosis in children with unresolved neuromuscular diseases

Establishing a molecular diagnosis remains challenging in half of individuals with childhood-onset neuromuscular diseases (NMDs) despite exome sequencing. This study evaluates the diagnostic utility of combining genomic approaches in undiagnosed NMD patients. We performed deep phenotyping of 58 individuals with unsolved childhood-onset NMDs that have previously undergone inconclusive exome studies. Genomic approaches included trio genome sequencing and RNASeq. Genetic diagnoses were reached in 23 out of 58 individuals (40%). Twenty-one individuals carried causal single nucleotide variants (SNVs) or small insertions and deletions, while 2 carried pathogenic structural variants (SVs). Genomic sequencing identified pathogenic variants in coding regions or at the splice site in 17 out of 21 resolved cases, while RNA sequencing was additionally required for the diagnosis of 4 cases. Reasons for previous diagnostic failures included low coverage in exonic regions harboring the second pathogenic variant and involvement of genes that were not yet linked to human diseases at the time of the first NGS analysis. In summary, our systematic genetic analysis, integrating deep phenotyping, trio genome sequencing and RNASeq, proved effective in diagnosing unsolved childhood-onset NMDs. This approach holds promise for similar cohorts, offering potential improvements in diagnostic rates and clinical management of individuals with NMDs.

Robust detection of pathogenic HYDIN variants that cause primary ciliary dyskinesia using RNA-seq of nasal mucosa

Primary ciliary dyskinesia (PCD, OMIM 244400) is a rare genetic disorder that affects motile cilia and is characterised by impaired mucociliary clearance of the airway epithelium, which results in chronic upper and lower airway infections. While short-read next-generation sequencing technology has been used for the genetic testing of PCD, its effectiveness is limited in identifying variants in the HYDIN gene because of the nearly identical pseudogene HYDIN2 As we confirmed that the HYDIN2 gene was not expressed in airway cells, we obtained nasal mucosa biopsy specimens for total RNA sequencing (RNA-seq) with library enrichment using exome oligos. Among the 34 nasal samples from patients suspected of having PCD, three aberrant splicing patterns in HYDIN were identified in two samples. Variant calls from RNA-seq combined with long-read amplicon sequencing of genomic DNA detected four pathogenic variants exclusively in the HYDIN gene. Therefore, RNA-seq in combination with long-read sequencing significantly facilitates the accurate genetic diagnosis of PCD caused by HYDIN variants.

Researcher views on returning results from multi-omics data to research participants: insights from The Molecular Transducers of Physical Activity Consortium (MoTrPAC) Study

BACKGROUND

There is growing consensus in favor of returning individual specific research results that are clinically actionable, valid, and reliable. However, deciding what and how research results should be returned remains a challenge. Researchers are key stakeholders in return of results decision-making and implementation. Multi-omics data contains medically relevant findings that could be considered for return. We sought to understand researchers' views regarding the potential for return of results for multi-omics data from a large, national consortium generating multi-omics data.

METHODS

Researchers from the Molecular Transducers of Physical Activity Consortium (MoTrPAC) were recruited for in-depth semi-structured interviews. To assess understanding of potential clinical utility for types of data collected and attitudes towards return of results in multi-omic clinical studies, we devised an interview guide focusing on types of results generated in the study for hypothetical return based on review of the literature and professional expertise of team members. The semi-structured interviews were recorded, transcribed verbatim and co-coded. Thematic trends were identified for reporting.

RESULTS

We interviewed a total of 16 individuals representative of 11 sites and 6 research roles across MoTrPAC. Many respondents expressed positive attitudes regarding hypothetical multi-omics results return, citing participant rights to their data and perception of minimal harm. Ethical and logistical concerns around the return of multi-omics results were raised, and they often mirrored those in the published literature for genomic return of results including: uncertain clinical validity, a lack of expertise to communicate results, and an unclear obligation regarding whether to return multi-omics results. With the exception of privacy concerns, respondents were able to give examples within multi-omics of how each point was relevant. Further, researchers called for more guidance from funding agencies and increased researcher education regarding return of results.

CONCLUSION

Overall, researchers expressed positive attitudes toward multi-omic return of results in principle, particularly if medically actionable. However, competing ethical considerations, logistical constraints, and need for more external guidance were raised as key implementation concerns. Future studies should consider views and experiences of other relevant stakeholders, specifically clinical genomics professionals and study participants, regarding the clinical utility of multi-omics information and multi-omics results return.

MAJIQ-CLIN: A novel tool for the identification of Mendelian disease-causing variants from RNA-Seq data

The current diagnostic rate for patients with suspected Mendelian genetic disorders is only 25 to 58%, even though whole exome sequencing (WES) is part of the standard of care. One reason for the low diagnostic rate is that traditional WES analysis methods struggle to detect RNA splicing aberrations. It is estimated that 15-50% of human pathogenic variants alter splicing, with numerous splice-altering variants being causal for known Mendelian disorders. Developing reliable diagnostic tools to detect, quantify, prioritize, and visualize RNA splicing aberrations from patient RNA sequencing is therefore crucial. We present MAJIQ-CLIN, a method to address this need to augment clinical diagnostic using RNA-Seq and compare it to existing tools. We include the first systematic evaluation of the accuracy of such tools using synthetic data across several aberration types and transcript inclusion levels; we also evaluate accuracy on several datasets of biologically validated solved test cases. We show that MAJIQ-CLIN compares favorably to existing tools in both accuracy and efficiency, then use MAJIQ-CLIN to investigate several unsolved patient cases from the Undiagnosed Diseases Network.

The Utility of Ultra-Deep RNA sequencing in Mendelian Disorder Diagnostics

Clinical RNA-seq has become an essential tool for resolving variants of uncertain significance (VUS), particularly those affecting gene expression and splicing. However, most reference data and diagnostic protocols employ relatively modest sequencing depths (∼50-150 million reads), which may fail to capture low-abundance transcripts and rare splicing events critical for accurate diagnoses. We evaluated the diagnostic and translational utility of ultra-high-depth (up to ∼one billion unique reads) RNA-seq in four clinically accessible tissues (blood, fibroblast, LCL, and iPSC) using Ultima sequencing platform. After validating the performance of Ultima RNA-seq, we investigated how increasing depth affects gene and isoform detection, splicing variant discovery, and clinical interpretation of VUS. Deep RNA-seq substantially improved sensitivity for detecting lowly-expressed genes and isoforms. At ∼1 billion reads, near-saturation was achieved for gene-level detection, although isoform-level coverage continued to benefit from even deeper sequencing. In two clinical cases with VUS, pathogenic splicing abnormalities were undetected at ∼50 million reads but emerged at 200 million reads, becoming even more pronounced at ∼one billion reads. Using deep RNA-seq data, we constructed a novel resource, MRSD-deep, to estimate the minimum required sequencing depth to achieve desired coverage thresholds. MRSD-deep provided gene- and junction-level guidelines, aiding labs in selecting suitable coverage targets for specific applications. Leveraging deep RNA-seq data on fibroblast, we also built an expanded splicing-variation reference that successfully identified rare splicing events missed by standard-depth data. Our findings underscore the diagnostic and research benefits of deep RNA-seq for Mendelian disease investigations. By capturing rare transcripts and splicing events, ultra-high-depth RNA-seq can facilitate more definitive variant interpretations and enrich splicing-reference databases. We anticipate that cost-effective deep sequencing technologies and robust reference cohorts will further advance RNA-based diagnostics in precision medicine.

TTN-Related Muscular Dystrophies, LGMD, and TMD, in an Estonian Family Caused by the Finnish Founder Variant

Background and Objectives

Tibial muscular dystrophy (TMD) is an autosomal dominant, slowly progressive late-onset distal myopathy. TMD was first described in 1991 by Udd et al. in Finnish patients, who were later found to harbor a heterozygous unique 11-bp insertion/deletion in the last exon of the TTN gene-the Finnish founder variant (FINmaj). In homozygous state or compound heterozygosity with a truncating variant, the FINmaj causes early-onset recessive titin-related limb-girdle muscular dystrophy type 10 (LGMD R10). So far, the FINmaj variant has not been detected outside the Finnish population.

Methods

We describe an Estonian family presenting both early-onset LGMD R10 and late-onset TMD. The index patient underwent trio exome sequencing (ES), muscle biopsy, and RNA sequencing. The detected variants were validated by Sanger sequencing. Muscle MRI was performed in all affected individuals.

Results

Trio ES revealed 2 heterozygous variants in the TTN gene: (NM_001267550.2):c.107780_107790delinsTGAAAGAAAAA, p.(Glu35927_Trp35930delinsValLysGluLys) (FINmaj variant, paternally inherited) and (NM_001267550.2):c.64672+2dup (maternally inherited) in trans in the proband. Familial segregation analysis revealed the same biallelic variants in the younger affected sister and heterozygous FINmaj in the father. We characterized the effect of the splice variant by RNA sequencing, proving that it causes an intronic retention resulting in a premature stop codon. Muscle histology of the proband showed myopathic changes. Muscle MRI of both individuals with LGMD R10 showed early degenerative changes in tibialis anterior and in hypotrophy of distal hamstrings. Muscle MRI of the father with TMD, at the age of 38 years, showed early minimal fatty degeneration in the peroneus longus and right tibialis anterior muscles.

Discussion

For the first time, we have detected the FINmaj variant in the Estonian population. We report an Estonian family without any known Finnish ancestry for many generations, with 2 siblings harboring FINmaj in a compound with a splice site variant and their father with heterozygous FINmaj. It is currently not known whether the FINmaj is originally Estonian or Finnish ancestry. Further population studies in Estonia to establish the frequency of FINmaj in the population are ongoing and will solve the quest.

saseR: Juggling offsets unlocks RNA-seq tools for fast and Scalable differential usage, Aberrant Splicing and Expression Retrieval

RNA-seq data analysis relies on many different tools, each tailored to specific applications and coming with unique assumptions and restrictions. Indeed, tools for differential transcript usage, or diagnosing patients with rare diseases through splicing and expression outliers, either lack in performance, discard information, or do not scale to massive data compendia. Here, we show that replacing the normalisation offsets unlocks bulk RNA-seq workflows for scalable differential usage, aberrant splicing and expression analyses. Our method, saseR, is much faster than state-of-the-art methods, dramatically outperforms these to detect aberrant splicing, and provides a single workflow for various short- and long-read RNA-seq applications.

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.

De novo variants in the RNU4-2 snRNA cause a frequent neurodevelopmental syndrome

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here we identify the non-coding RNA RNU4-2 as a syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 base pair region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 115 individuals with NDD. Most individuals (77.4%) have the same highly recurrent single base insertion (n.64_65insT). In 54 individuals in whom it could be determined, the de novo variants were all on the maternal allele. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to RNU4-1 and other U4 homologues. Using RNA sequencing, we show how 5' splice-site use is systematically disrupted in individuals with RNU4-2 variants, consistent with the known role of this region during spliceosome activation. Finally, we estimate that variants in this 18 base pair region explain 0.4% of individuals with NDD. This work underscores the importance of non-coding genes in rare disorders and will provide a diagnosis to thousands of individuals with NDD worldwide.

PSMF1 variants cause a phenotypic spectrum from early-onset Parkinson's disease to perinatal lethality by disrupting mitochondrial pathways

Dissecting biological pathways highlighted by Mendelian gene discovery has provided critical insights into the pathogenesis of Parkinson's disease (PD) and neurodegeneration. This approach ultimately catalyzes the identification of potential biomarkers and therapeutic targets. Here, we identify PSMF1 as a new gene implicated in PD and childhood neurodegeneration. We find that biallelic PSMF1 missense and loss-of-function variants co-segregate with phenotypes from early-onset PD and parkinsonism to perinatal lethality with neurological manifestations across 15 unrelated pedigrees with 22 affected subjects, showing clear genotype-phenotype correlation. PSMF1 encodes the proteasome regulator PSMF1/PI31, a highly conserved, ubiquitously expressed partner of the 20S proteasome and neurodegeneration-associated F-box-O 7 and valosin-containing proteins. We demonstrate that PSMF1 variants impair mitochondrial membrane potential, dynamics and mitophagy in patient-derived fibroblasts. Additionally, we develop models of psmf1 knockdown Drosophila and Psmf1 conditional knockout mouse exhibiting age-dependent motor impairment, with diffuse gliosis in mice. These findings unequivocally link defective PSMF1 to early-onset PD and neurodegeneration and suggest mitochondrial dysfunction as a mechanistic contributor.

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.

De novo variants in the non-coding spliceosomal snRNA gene RNU4-2 are a frequent cause of syndromic neurodevelopmental disorders

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Increasingly, large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here, we identify the non-coding RNA RNU4-2 as a novel syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 bp region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and Stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 119 individuals with NDD. The vast majority of individuals (77.3%) have the same highly recurrent single base-pair insertion (n.64_65insT). We estimate that variants in this region explain 0.41% of individuals with NDD. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to its contiguous counterpart RNU4-1 and other U4 homologs, supporting RNU4-2's role as the primary U4 transcript in the brain. Overall, this work underscores the importance of non-coding genes in rare disorders. It will provide a diagnosis to thousands of individuals with NDD worldwide and pave the way for the development of effective treatments for these individuals.