Deciphering exome sequencing data: Bringing mitochondrial DNA variants to light

The expanding use of exome sequencing (ES) in diagnosis generates a huge amount of data, including untargeted mitochondrial DNA (mtDNA) sequences. We developed a strategy to deeply study ES data, focusing on the mtDNA genome on a large unspecific cohort to increase diagnostic yield. A targeted bioinformatics pipeline assembled mitochondrial genome from ES data to detect pathogenic mtDNA variants in parallel with the "in-house" nuclear exome pipeline. mtDNA data coming from off-target sequences (indirect sequencing) were extracted from the BAM files in 928 individuals with developmental and/or neurological anomalies. The mtDNA variants were filtered out based on database information, cohort frequencies, haplogroups and protein consequences. Two homoplasmic pathogenic variants (m.9035T>C and m.11778G>A) were identified in 2 out of 928 unrelated individuals (0.2%): the m.9035T>C (MT-ATP6) variant in a female with ataxia and the m.11778G>A (MT-ND4) variant in a male with a complex mosaic disorder and a severe ophthalmological phenotype, uncovering undiagnosed Leber\u27s hereditary optic neuropathy (LHON). Seven secondary findings were also found, predisposing to deafness or LHON, in 7 out of 928 individuals (0.75%). This study demonstrates the usefulness of including a targeted strategy in ES pipeline to detect mtDNA variants, improving results in diagnosis and research, without resampling patients and performing targeted mtDNA strategies

Recommendations for accurate genotyping of SARS-CoV-2 using amplicon-based sequencing of clinical samples.

Genotyping of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been instrumental in monitoring viral evolution and transmission during the pandemic. The quality of the sequence data obtained from these genotyping efforts depends on several factors, including the quantity/integrity of the input material, the technology, and laboratory-specific implementation. The current lack of guidelines for SARS-CoV-2 genotyping leads to inclusion of error-containing genome sequences in genomic epidemiology studies. We aimed to establish clear and broadly applicable recommendations for reliable virus genotyping. We established and used a sequencing data analysis workflow that reliably identifies and removes technical artefacts; such artefacts can result in miscalls when using alternative pipelines to process clinical samples and synthetic viral genomes with an amplicon-based genotyping approach. We evaluated the impact of experimental factors, including viral load and sequencing depth, on correct sequence determination. We found that at least 1000 viral genomes are necessary to confidently detect variants in the SARS-CoV-2 genome at frequencies of ≥10%. The broad applicability of our recommendations was validated in over 200 clinical samples from six independent laboratories. The genotypes we determined for clinical isolates with sufficient quality cluster by sampling location and period. Our analysis also supports the rise in frequencies of 20A.EU1 and 20A.EU2, two recently reported European strains whose dissemination was facilitated by travel during the summer of 2020. We present much-needed recommendations for the reliable determination of SARS-CoV-2 genome sequences and demonstrate their broad applicability in a large cohort of clinical samples

Integration of Hi-C with short and long-read genome sequencing reveals the structure of germline rearranged genomes

Structural variants are a common cause of disease and contribute to a large extent to inter-individual variability, but their detection and interpretation remain a challenge. Here, we investigate 11 individuals with complex genomic rearrangements including germline chromothripsis by combining short- and long-read genome sequencing (GS) with Hi-C. Large-scale genomic rearrangements are identified in Hi-C interaction maps, allowing for an independent assessment of breakpoint calls derived from the GS methods, resulting in >300 genomic junctions. Based on a comprehensive breakpoint detection and Hi-C, we achieve a reconstruction of whole rearranged chromosomes. Integrating information on the three-dimensional organization of chromatin, we observe that breakpoints occur more frequently than expected in lamina-associated domains (LADs) and that a majority reshuffle topologically associating domains (TADs). By applying phased RNA-seq, we observe an enrichment of genes showing allelic imbalanced expression (AIG) within 100 kb around the breakpoints. Interestingly, the AIGs hit by a breakpoint (19/22) display both up- and downregulation, thereby suggesting different mechanisms at play, such as gene disruption and rearrangements of regulatory information. However, the majority of interpretable genes located 200 kb around a breakpoint do not show significant expression changes. Thus, there is an overall robustness in the genome towards large-scale chromosome rearrangements

Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples

Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES

Integration of Hi-C with short and long-read genome sequencing reveals the structure of germline rearranged genomes

Here the authors characterize structural variations (SVs) in a cohort of individuals with complex genomic rearrangements, identifying breakpoints by employing short- and long-read genome sequencing and investigate their impact on gene expression and the three-dimensional chromatin architecture. They find breakpoints are enriched in inactive regions and can result in chromatin domain fusions.Structural variants are a common cause of disease and contribute to a large extent to inter-individual variability, but their detection and interpretation remain a challenge. Here, we investigate 11 individuals with complex genomic rearrangements including germline chromothripsis by combining short- and long-read genome sequencing (GS) with Hi-C. Large-scale genomic rearrangements are identified in Hi-C interaction maps, allowing for an independent assessment of breakpoint calls derived from the GS methods, resulting in >300 genomic junctions. Based on a comprehensive breakpoint detection and Hi-C, we achieve a reconstruction of whole rearranged chromosomes. Integrating information on the three-dimensional organization of chromatin, we observe that breakpoints occur more frequently than expected in lamina-associated domains (LADs) and that a majority reshuffle topologically associating domains (TADs). By applying phased RNA-seq, we observe an enrichment of genes showing allelic imbalanced expression (AIG) within 100 kb around the breakpoints. Interestingly, the AIGs hit by a breakpoint (19/22) display both up- and downregulation, thereby suggesting different mechanisms at play, such as gene disruption and rearrangements of regulatory information. However, the majority of interpretable genes located 200 kb around a breakpoint do not show significant expression changes. Thus, there is an overall robustness in the genome towards large-scale chromosome rearrangements

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

PURPOSE: Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. METHODS: Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. RESULTS: We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). CONCLUSION: The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Clinical spectrum of MTOR-related hypomelanosis of Ito with neurodevelopmental abnormalities

PURPOSE: Hypomelanosis of Ito (HI) is a skin marker of somatic mosaicism. Mosaic MTOR pathogenic variants have been reported in HI with brain overgrowth. We sought to delineate further the pigmentary skin phenotype and clinical spectrum of neurodevelopmental manifestations of MTOR-related HI. METHODS: From two cohorts totaling 71 patients with pigmentary mosaicism, we identified 14 patients with Blaschko-linear and one with flag-like pigmentation abnormalities, psychomotor impairment or seizures, and a postzygotic MTOR variant in skin. Patient records, including brain magnetic resonance image (MRI) were reviewed. Immunostaining (n = 3) for melanocyte markers and ultrastructural studies (n = 2) were performed on skin biopsies. RESULTS: MTOR variants were present in skin, but absent from blood in half of cases. In a patient (p.[Glu2419Lys] variant), phosphorylation of p70S6K was constitutively increased. In hypopigmented skin of two patients, we found a decrease in stage 4 melanosomes in melanocytes and keratinocytes. Most patients (80%) had macrocephaly or (hemi)megalencephaly on MRI. CONCLUSION: MTOR-related HI is a recognizable neurocutaneous phenotype of patterned dyspigmentation, epilepsy, intellectual deficiency, and brain overgrowth, and a distinct subtype of hypomelanosis related to somatic mosaicism. Hypopigmentation may be due to a defect in melanogenesis, through mTORC1 activation, similar to hypochromic patches in tuberous sclerosis complex

Exome reanalysis and proteomic profiling identified TRIP4 as a novel cause of cerebellar hypoplasia and spinal muscular atrophy (PCH1)

TRIP4 is one of the subunits of the transcriptional coregulator ASC-1, a ribonucleoprotein complex that participates in transcriptional coactivation and RNA processing events. Recessive variants in the TRIP4 gene have been associated with spinal muscular atrophy with bone fractures as well as a severe form of congenital muscular dystrophy. Here we present the diagnostic journey of a patient with cerebellar hypoplasia and spinal muscular atrophy (PCH1) and congenital bone fractures. Initial exome sequencing analysis revealed no candidate variants. Reanalysis of the exome data by inclusion in the Solve-RD project resulted in the identification of a homozygous stop-gain variant in the TRIP4 gene, previously reported as disease-causing. This highlights the importance of analysis reiteration and improved and updated bioinformatic pipelines. Proteomic profile of the patient’s fibroblasts showed altered RNA-processing and impaired exosome activity supporting the pathogenicity of the detected variant. In addition, we identified a novel genetic form of PCH1, further strengthening the link of this characteristic phenotype with altered RNA metabolism

Mechanism of KMT5B haploinsufficiency in neurodevelopment in humans and mice.

Pathogenic variants in KMT5B, a lysine methyltransferase, are associated with global developmental delay, macrocephaly, autism, and congenital anomalies (OMIM# 617788). Given the relatively recent discovery of this disorder, it has not been fully characterized. Deep phenotyping of the largest (n = 43) patient cohort to date identified that hypotonia and congenital heart defects are prominent features that were previously not associated with this syndrome. Both missense variants and putative loss-of-function variants resulted in slow growth in patient-derived cell lines. KMT5B homozygous knockout mice were smaller in size than their wild-type littermates but did not have significantly smaller brains, suggesting relative macrocephaly, also noted as a prominent clinical feature. RNA sequencing of patient lymphoblasts and Kmt5b haploinsufficient mouse brains identified differentially expressed pathways associated with nervous system development and function including axon guidance signaling. Overall, we identified additional pathogenic variants and clinical features in KMT5B-related neurodevelopmental disorder and provide insights into the molecular mechanisms of the disorder using multiple model systems