Human genomics. Effect of predicted protein-truncating genetic variants on the human transcriptome

Whole-genome sequencing identifies variants in ANK1, LRRN1, HAS1, and other genes and regulatory regions for stroke in type 1 diabetes

Individuals with type 1 diabetes (T1D) carry a markedly increased risk of stroke, with distinct clinical and neuroimaging characteristics as compared to those without diabetes. Using whole-exome or whole-genome sequencing of 1,051 individuals with T1D, we aimed to find rare and low-frequency genomic variants associated with stroke in T1D. We analysed the genome comprehensively with single-variant analyses, gene aggregate analyses, and aggregate analyses on genomic windows, enhancers and promoters. In addition, we attempted replication in T1D using a genome-wide association study (N = 3,945) and direct genotyping (N = 3,263), and in the general population from the large-scale population-wide FinnGen project and UK Biobank summary statistics. We identified a rare missense variant on SREBF1 exome-wide significantly associated with stroke (rs114001633, p.Pro227Leu, p-value = 7.30 × 10-8), which replicated for hemorrhagic stroke in T1D. Using gene aggregate analysis, we identified exome-wide significant genes: ANK1 and LRRN1 displayed replication evidence in T1D, and LRRN1, HAS1 and UACA in the general population (UK Biobank). Furthermore, we performed sliding-window analyses and identified 14 genome-wide significant windows for stroke on 4q33-34.1, of which two replicated in T1D, and a suggestive genomic window on LINC01500, which replicated in T1D. Finally, we identified a suggestively stroke-associated TRPM2-AS promoter (p-value = 5.78 × 10-6) with borderline significant replication in T1D, which we validated with an in vitro cell-based assay. Due to the rarity of the identified genetic variants, future replication of the genomic regions represented here is required with sequencing of individuals with T1D. Nevertheless, we here report the first genome-wide analysis on stroke in individuals with diabetes.

X-chromosome inactivation in human iPSCs provides insight into X-regulated gene expression in autosomes

BACKGROUND

Variation in X chromosome inactivation (XCI) in human-induced pluripotent stem cells (hiPSCs) can impact their ability to model biological sex biases. The gene-wise landscape of X chromosome gene dosage remains unresolved in female hiPSCs. To characterize patterns of de-repression and escape from inactivation, we performed a systematic survey of allele specific expression in 165 female hiPSC lines.

RESULTS

XCI erosion is non-random and primarily affects genes that escape XCI in human tissues. Individual genes and cell lines vary in the frequency and degree of de-repression. Bi-allelic expression increases gradually after modest decrease of XIST in cultures, whose loss is commonly used to mark lines with eroded XCI. We identify three clusters of female lines at different stages of XCI. Increased XCI erosion amplifies female-biased expression at hypomethylated sites and regions normally occupied by repressive histone marks, lowering male-biased differences in the X chromosome. In autosomes, erosion modifies sex differences in a dose-dependent way. Male-biased genes are enriched for hypermethylated regions, and de-repression of XIST-bound autosomal genes in female lines attenuates normal male-biased gene expression in eroded lines. XCI erosion can compensate for a dominant loss of function effect in several disease genes.

CONCLUSIONS

We present a comprehensive view of X chromosome gene dosage in hiPSCs and implicate a direct mechanism for XCI erosion in regulating autosomal gene expression in trans. The uncommon and variable reactivation of X chromosome genes in female hiPSCs can provide insight into X chromosome's role in regulating gene expression and sex differences in humans.

Mutations causing premature termination codons discriminate and generate cellular and clinical variability in HHT

ABSTRACT

For monogenic diseases caused by pathogenic loss-of-function DNA variants, attention focuses on dysregulated gene-specific pathways, usually considering molecular subtypes together within causal genes. To better understand phenotypic variability in hereditary hemorrhagic telangiectasia (HHT), we subcategorized pathogenic DNA variants in ENG/endoglin, ACVRL1/ALK1, and SMAD4 if they generated premature termination codons (PTCs) subject to nonsense-mediated decay. In 3 patient cohorts, a PTC-based classification system explained some previously puzzling hemorrhage variability. In blood outgrowth endothelial cells (BOECs) derived from patients with ACVRL1+/PTC, ENG+/PTC, and SMAD4+/PTC genotypes, PTC-containing RNA transcripts persisted at low levels (8%-23% expected, varying between replicate cultures); genes differentially expressed to Bonferroni P < .05 in HHT+/PTC BOECs clustered significantly only to generic protein terms (isopeptide-bond/ubiquitin-like conjugation) and pulse-chase experiments detected subtle protein maturation differences but no evidence for PTC-truncated protein. BOECs displaying highest PTC persistence were discriminated in unsupervised hierarchical clustering of near-invariant housekeeper genes, with patterns compatible with higher cellular stress in BOECs with >11% PTC persistence. To test directionality, we used a HeLa reporter system to detect induction of activating transcription factor 4 (ATF4), which controls expression of stress-adaptive genes, and showed that ENG Q436X but not ENG R93X directly induced ATF4. AlphaFold accurately modeled relevant ENG domains, with AlphaMissense suggesting that readthrough substitutions would be benign for ENG R93X and other less rare ENG nonsense variants but more damaging for Q436X. We conclude that PTCs should be distinguished from other loss-of-function variants, PTC transcript levels increase in stressed cells, and readthrough proteins and mechanisms provide promising research avenues.

A systematic assessment of the impact of rare canonical splice site variants on splicing using functional and in silico methods

Canonical splice site variants (CSSVs) are often presumed to cause loss-of-function (LoF) and are assigned very strong evidence of pathogenicity (according to American College of Medical Genetics/Association for Molecular Pathology criterion PVS1). The exact nature and predictability of splicing effects of unselected rare CSSVs in blood-expressed genes are poorly understood. We identified 168 rare CSSVs in blood-expressed genes in 112 individuals using genome sequencing, and studied their impact on splicing using RNA sequencing (RNA-seq). There was no evidence of a frameshift, nor of reduced expression consistent with nonsense-mediated decay, for 25.6% of CSSVs: 17.9% had wildtype splicing only and normal junction depths, 3.6% resulted in cryptic splice site usage and in-frame insertions or deletions, 3.6% resulted in full exon skipping (in frame), and 0.6% resulted in full intron inclusion (in frame). Blind to these RNA-seq data, we attempted to predict the precise impact of CSSVs by applying in silico tools and the ClinGen Sequence Variant Interpretation Working Group 2018 guidelines for applying PVS1 criterion. The predicted impact on splicing using (1) SpliceAI, (2) MaxEntScan, and (3) AutoPVS1, an automatic classification tool for PVS1 interpretation of null variants that utilizes Ensembl Variant Effect Predictor and MaxEntScan, was concordant with RNA-seq analyses for 65%, 63%, and 61% of CSSVs, respectively. In summary, approximately one in four rare CSSVs did not show evidence for LoF based on analysis of RNA-seq data. Predictions from in silico methods were often discordant with findings from RNA-seq. More caution may be warranted in applying PVS1-level evidence to CSSVs in the absence of functional data.

Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity

Long-read RNA sequencing has shed light on transcriptomic complexity, but questions remain about the functionality of downstream protein products. We introduce Biosurfer, a computational approach for comparing protein isoforms, while systematically tracking the transcriptional, splicing, and translational variations that underlie differences in the sequences of the protein products. Using Biosurfer, we analyzed the differences in 32,799 pairs of GENCODE annotated protein isoforms, finding a majority (70%) of variable N-termini are due to the alternative transcription start sites, while only 9% arise from 5' UTR alternative splicing. Biosurfer's detailed tracking of nucleotide-to-residue relationships helped reveal an uncommonly tracked source of single amino acid residue changes arising from the codon splits at junctions. For 17% of internal sequence changes, such split codon patterns lead to single residue differences, termed "ragged codons". Of variable C-termini, 72% involve splice- or intron retention-induced reading frameshifts. We found an unusual pattern of reading frame changes, in which the first frameshift is closely followed by a distinct second frameshift that restores the original frame, which we term a "snapback" frameshift. We analyzed long read RNA-seq-predicted proteome of a human cell line and found similar trends as compared to our GENCODE analysis, with the exception of a higher proportion of isoforms predicted to undergo nonsense-mediated decay. Biosurfer's comprehensive characterization of long-read RNA-seq datasets should accelerate insights of the functional role of protein isoforms, providing mechanistic explanation of the origins of the proteomic diversity driven by the alternative splicing. Biosurfer is available as a Python package at https://github.com/sheynkman-lab/biosurfer.

Differential functional consequences of GRIN2A mutations associated with schizophrenia and neurodevelopmental disorders

Human genetic studies have revealed rare missense and protein-truncating variants in GRIN2A, encoding for the GluN2A subunit of the NMDA receptors, that confer significant risk for schizophrenia (SCZ). Mutations in GRIN2A are also associated with epilepsy and developmental delay/intellectual disability (DD/ID). However, it remains enigmatic how alterations to the same protein can result in diverse clinical phenotypes. Here, we performed functional characterization of human GluN1/GluN2A heteromeric NMDA receptors that contain SCZ-linked GluN2A variants, and compared them to NMDA receptors with GluN2A variants associated with epilepsy or DD/ID. Our findings demonstrate that SCZ-associated GRIN2A variants were predominantly loss-of-function (LoF), whereas epilepsy and DD/ID-associated variants resulted in both gain- and loss-of-function phenotypes. We additionally show that M653I and S809R, LoF GRIN2A variants associated with DD/ID, exert a dominant-negative effect when co-expressed with a wild-type GluN2A, whereas E58Ter and Y698C, SCZ-linked LoF variants, and A727T, an epilepsy-linked LoF variant, do not. These data offer a potential mechanism by which SCZ/epilepsy and DD/ID-linked variants can cause different effects on receptor function and therefore result in divergent pathological outcomes.

Systematic analysis of variants escaping nonsense-mediated decay uncovers candidate Mendelian diseases

Protein-truncating variants (PTVs) near the 3' end of genes may escape nonsense-mediated decay (NMD). PTVs in the NMD-escape region (PTVescs) can cause Mendelian disease but are difficult to interpret given their varying impact on protein function. Previously, PTVesc burden was assessed in an epilepsy cohort, but no large-scale analysis has systematically evaluated these variants in rare disease. We performed a retrospective analysis of 29,031 neurodevelopmental disorder (NDD) parent-offspring trios referred for clinical exome sequencing to identify PTVesc de novo mutations (DNMs). We identified 1,376 PTVesc DNMs and 133 genes that were significantly enriched (binomial p < 0.001). The PTVesc-enriched genes included those with PTVescs previously described to cause dominant Mendelian disease (e.g., SEMA6B, PPM1D, and DAGLA). We annotated ClinVar variants for PTVescs and identified 948 genes with at least one high-confidence pathogenic variant. Twenty-two known Mendelian PTVesc-enriched genes had no prior evidence of PTVesc-associated disease. We found 22 additional PTVesc-enriched genes that are not well established to be associated with Mendelian disease, several of which showed phenotypic similarity between individuals harboring PTVesc variants in the same gene. Four individuals with PTVesc mutations in RAB1A had similar phenotypes including NDD and spasticity. PTVesc mutations in IRF2BP1 were found in two individuals who each had severe immunodeficiency manifesting in NDD. Three individuals with PTVesc mutations in LDB1 all had NDD and multiple congenital anomalies. Using a large-scale, systematic analysis of DNMs, we extend the mutation spectrum for known Mendelian disease-associated genes and identify potentially novel disease-associated genes.

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

Detection of aberrantly spliced genes is an important step in RNA-seq-based rare-disease diagnostics. We recently developed FRASER, a denoising autoencoder-based method that outperformed alternative methods of detecting aberrant splicing. However, because FRASER's three splice metrics are partially redundant and tend to be sensitive to sequencing depth, we introduce here a more robust intron-excision metric, the intron Jaccard index, that combines the alternative donor, alternative acceptor, and intron-retention signal into a single value. Moreover, we optimized model parameters and filter cutoffs by using candidate rare-splice-disrupting variants as independent evidence. On 16,213 GTEx samples, our improved algorithm, FRASER 2.0, called typically 10 times fewer splicing outliers while increasing the proportion of candidate rare-splice-disrupting variants by 10-fold and substantially decreasing the effect of sequencing depth on the number of reported outliers. To lower the multiple-testing correction burden, we introduce an option to select the genes to be tested for each sample instead of a transcriptome-wide approach. This option can be particularly useful when prior information, such as candidate variants or genes, is available. Application on 303 rare-disease samples confirmed the relative reduction in the number of outlier calls for a slight loss of sensitivity; FRASER 2.0 recovered 22 out of 26 previously identified pathogenic splicing cases with default cutoffs and 24 when multiple-testing correction was limited to OMIM genes containing rare variants. Altogether, these methodological improvements contribute to more effective RNA-seq-based rare diagnostics by drastically reducing the amount of splicing outlier calls per sample at minimal loss of sensitivity.

Early-onset schizophrenia is associated with immune-related rare variants in a Chinese sample

Background

Rare variants are likely to contribute to schizophrenia (SCZ), given the large discrepancy between the heritability estimated from twin and GWAS studies. Furthermore, the nature of the rare-variant contribution to SCZ may vary with the "age-at-onset" (AAO), since early-onset has been suggested as being indicative of neurodevelopment deviance.

Objective

To examine the association of rare deleterious coding variants in early- and adult-onset SCZ in a Chinese sample.

Method

Exome sequencing was performed on DNA from 197 patients with SCZ spectrum disorder and 82 healthy controls (HC) of Chinese ancestry recruited in Hong Kong. We also gathered AAO information in the majority of SCZ samples. Patients were classified into early-onset (EOS, AAO<18) and adult-onset (AOS, AAO>18). We collapsed the rare variants to improve statistical power and examined the overall association of rare variants in SCZ versus HC, EOS versus HC, and AOS versus HC at the gene and gene-set levels by Sequence Kernel Association Test. The quantitative rare-variant association test of AAO was also conducted. We focused on variants which were predicted to have a medium or high impact on the protein-encoding process as defined by Ensembl. We applied a 100000-time permutation test to obtain empirical p-values, with significance threshold set at p < 1e -3 to control family-wise error rates. Moreover, we compared the burden of targeted rare variants in significant risk genes and gene sets in cases and controls.

Results

Based on several binary-trait association tests (i.e., SCZ vs HC, EOS vs HC and AOS vs HC), we identified 7 candidate risk genes and 20 gene ontology biological processes (GOBP) terms, which exhibited higher burdens in SCZ than in controls. Based on quantitative rare-variant association tests, we found that alterations in 5 candidate risk genes and 7 GOBP pathways were significantly correlated with AAO. Based on biological and functional profiles of the candidate risk genes and gene sets, our findings suggested that, in addition to the involvement of perturbations in neural systems in SCZ in general, altered immune responses may be specifically implicated in EOS.

Conclusion

Disrupted immune responses may exacerbate abnormal perturbations during neurodevelopment and trigger the early onset of SCZ. We provided evidence of rare variants increasing SCZ risk in the Chinese population.

Brain-region-specific changes in neurons and glia and dysregulation of dopamine signaling in Grin2a mutant mice

A genetically valid animal model could transform our understanding of schizophrenia (SCZ) disease mechanisms. Rare heterozygous loss-of-function (LoF) mutations in GRIN2A, encoding a subunit of the NMDA receptor, greatly increase the risk of SCZ. By transcriptomic, proteomic, and behavioral analyses, we report that heterozygous Grin2a mutant mice show (1) large-scale gene expression changes across multiple brain regions and in neuronal (excitatory and inhibitory) and non-neuronal cells (astrocytes and oligodendrocytes), (2) evidence of hypoactivity in the prefrontal cortex (PFC) and hyperactivity in the hippocampus and striatum, (3) an elevated dopamine signaling in the striatum and hypersensitivity to amphetamine-induced hyperlocomotion (AIH), (4) altered cholesterol biosynthesis in astrocytes, (5) a reduction in glutamatergic receptor signaling proteins in the synapse, and (6) an aberrant locomotor pattern opposite of that induced by antipsychotic drugs. These findings reveal potential pathophysiologic mechanisms, provide support for both the "hypo-glutamate" and "hyper-dopamine" hypotheses of SCZ, and underscore the utility of Grin2a-deficient mice as a genetic model of SCZ.

Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

BACKGROUND

Breast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.

METHODS

Tumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman's rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan-Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.

RESULTS

Herein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.

CONCLUSIONS

We conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

Translation-coupled mRNA quality control mechanisms

mRNA surveillance pathways are essential for accurate gene expression and to maintain translation homeostasis, ensuring the production of fully functional proteins. Future insights into mRNA quality control pathways will enable us to understand how cellular mRNA levels are controlled, how defective or unwanted mRNAs can be eliminated, and how dysregulation of these can contribute to human disease. Here we review translation-coupled mRNA quality control mechanisms, including the non-stop and no-go mRNA decay pathways, describing their mechanisms, shared trans-acting factors, and differences. We also describe advances in our understanding of the nonsense-mediated mRNA decay (NMD) pathway, highlighting recent mechanistic findings, the discovery of novel factors, as well as the role of NMD in cellular physiology and its impact on human disease.

PTCH/SMO gene mutations in odontogenic keratocysts and drug interventions

BACKGROUND

Odontogenic keratocysts (OKCs) are odontogenic jaw lesions that cause destruction and dysfunction of the jawbone. OKCs can be sporadic or associated with nevoid basic cell carcinoma syndrome (NBCCS). However, the factors that initiate OKCs and the mechanism of cyst formation remain unclear. Here, we investigated the impact of PTCH1 and SMO mutations on disease progression, as well as the effects of sonic hedgehog (SHH) signaling pathway inhibitors GDC-0449 and GANT61 on OKC fibroblasts.

METHODS

Eight sporadic OKC fibroblasts without gene mutations were used as the control, and six NBCCS-related fibroblasts were cultured in vitro. The effect of PTCH1 non-truncated mutation 3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutation on OKC fibroblast proliferation was examined by EdU assay. CCK8 and wound-healing assays detected the effects of OKC fibroblasts carrying PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutations on the proliferation and migration of HaCaT cells after co-culture. Quantitative real-time PCR detected the effects of GDC-0449 or GANT61 on the SHH signaling pathway in NBCCS-related OKCs with PTCH1 truncated mutations and PTCH1 c.3499G>A (p.G1167R) and/or SMO c.2081C>G (p.P694R) mutations.

RESULTS

PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) promoted the proliferation of OKC fibroblasts. The proliferation and migration of HaCaT cells were affected by NBCCS-related OKC fibroblasts carrying PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutations. GDC-0449 significantly inhibited the SHH signaling pathway in NBCCS-related OKC fibroblasts with PTCH1 truncated mutations. An NBCCS-related OKC carrying PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutations were resistant to GDC-0449 but inhibited by GANT61.

CONCLUSIONS

Genetic mutations in OKC fibroblasts may affect the biological behavior of epithelial and stromal cells and cause disease. GDC-0449 could be used to treat OKCs, especially NBCCS-related OKCs with PTCH1 truncated mutations. SMO c.2081C>G (p.P694R) may lead to resistance to GDC-0449; however, GANT61 may be used as an alternative inhibitor.

Advanced variant classification framework reduces the false positive rate of predicted loss-of-function variants in population sequencing data

Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines' PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 genes associated with autosomal-recessive disease from the Genome Aggregation Database (gnomAD v.2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in a low proportion expressed across transcripts (pext) scored region, or the presence of cryptic in-frame splice rescues. Variants predicted to evade LoF or to be potential artifacts were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of pLoF variants predicted as likely not LoF/not LoF, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

aenmd: annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants

SUMMARY

DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce transcript degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these variants that could exert DN/GOF effects via NMD escape.

AVAILABILITY AND IMPLEMENTATION

aenmd is implemented in the R programming language. Code is available on GitHub as an R-package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).

GRIN2A (NR2A): a gene contributing to glutamatergic involvement in schizophrenia

Involvement of the glutamate system, particularly N-methyl-D-aspartate (NMDA) receptor hypofunction, has long been postulated to be part of the pathophysiology of schizophrenia. An important development is provided by recent data that strongly implicate GRIN2A, the gene encoding the NR2A (GluN2A) NMDA receptor subunit, in the aetiology of the disorder. Rare variants and common variants are both robustly associated with genetic risk for schizophrenia. Some of the rare variants are point mutations likely affecting channel function, but most are predicted to cause protein truncation and thence result, like the common variants, in reduced gene expression. We review the genomic evidence, and the findings from Grin2a mutant mice and other models which give clues as to the likely phenotypic impacts of GRIN2A genetic variation. We suggest that one consequence of NR2A dysfunction is impairment in a form of hippocampal synaptic plasticity, producing deficits in short-term habituation and thence elevated and dysregulated levels of attention, a phenotype of relevance to schizophrenia and its cognitive aspects.

TEQUILA-seq: a versatile and low-cost method for targeted long-read RNA sequencing

Long-read RNA sequencing (RNA-seq) is a powerful technology for transcriptome analysis, but the relatively low throughput of current long-read sequencing platforms limits transcript coverage. One strategy for overcoming this bottleneck is targeted long-read RNA-seq for preselected gene panels. We present TEQUILA-seq, a versatile, easy-to-implement, and low-cost method for targeted long-read RNA-seq utilizing isothermally linear-amplified capture probes. When performed on the Oxford nanopore platform with multiple gene panels of varying sizes, TEQUILA-seq consistently and substantially enriches transcript coverage while preserving transcript quantification. We profile full-length transcript isoforms of 468 actionable cancer genes across 40 representative breast cancer cell lines. We identify transcript isoforms enriched in specific subtypes and discover novel transcript isoforms in extensively studied cancer genes such as TP53. Among cancer genes, tumor suppressor genes (TSGs) are significantly enriched for aberrant transcript isoforms targeted for degradation via mRNA nonsense-mediated decay, revealing a common RNA-associated mechanism for TSG inactivation. TEQUILA-seq reduces the per-reaction cost of targeted capture by 2-3 orders of magnitude, as compared to a standard commercial solution. TEQUILA-seq can be broadly used for targeted sequencing of full-length transcripts in diverse biomedical research settings.

Mapping genetic variants for nonsense-mediated mRNA decay regulation across human tissues

BACKGROUND

Nonsense-mediated mRNA decay (NMD) was originally conceived as an mRNA surveillance mechanism to prevent the production of potentially deleterious truncated proteins. Research also shows NMD is an important post-transcriptional gene regulation mechanism selectively targeting many non-aberrant mRNAs. However, how natural genetic variants affect NMD and modulate gene expression remains elusive.

RESULTS

Here we elucidate NMD regulation of individual genes across human tissues through genetical genomics. Genetic variants corresponding to NMD regulation are identified based on GTEx data through unique and robust transcript expression modeling. We identify genetic variants that influence the percentage of NMD-targeted transcripts (pNMD-QTLs), as well as genetic variants regulating the decay efficiency of NMD-targeted transcripts (dNMD-QTLs). Many such variants are missed in traditional expression quantitative trait locus (eQTL) mapping. NMD-QTLs show strong tissue specificity especially in the brain. They are more likely to overlap with disease single-nucleotide polymorphisms (SNPs). Compared to eQTLs, NMD-QTLs are more likely to be located within gene bodies and exons, especially the penultimate exons from the 3' end. Furthermore, NMD-QTLs are more likely to be found in the binding sites of miRNAs and RNA binding proteins.

CONCLUSIONS

We reveal the genome-wide landscape of genetic variants associated with NMD regulation across human tissues. Our analysis results indicate important roles of NMD in the brain. The preferential genomic positions of NMD-QTLs suggest key attributes for NMD regulation. Furthermore, the overlap with disease-associated SNPs and post-transcriptional regulatory elements implicates regulatory roles of NMD-QTLs in disease manifestation and their interactions with other post-transcriptional regulators.

An Update on MYBPC3 Gene Mutation in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is the most prevalent genetically inherited cardiomyopathy that follows an autosomal dominant inheritance pattern. The majority of HCM cases can be attributed to mutation of the MYBPC3 gene, which encodes cMyBP-C, a crucial structural protein of the cardiac muscle. The manifestation of HCM's morphological, histological, and clinical symptoms is subject to the complex interplay of various determinants, including genetic mutation and environmental factors. Approximately half of MYBPC3 mutations give rise to truncated protein products, while the remaining mutations cause insertion/deletion, frameshift, or missense mutations of single amino acids. In addition, the onset of HCM may be attributed to disturbances in the protein and transcript quality control systems, namely, the ubiquitin-proteasome system and nonsense-mediated RNA dysfunctions. The aforementioned genetic modifications, which appear to be associated with unfavorable lifelong outcomes and are largely influenced by the type of mutation, exhibit a unique array of clinical manifestations ranging from asymptomatic to arrhythmic syncope and even sudden cardiac death. Although the current understanding of the MYBPC3 mutation does not comprehensively explain the varied phenotypic manifestations witnessed in patients with HCM, patients with pathogenic MYBPC3 mutations can exhibit an array of clinical manifestations ranging from asymptomatic to advanced heart failure and sudden cardiac death, leading to a higher rate of adverse clinical outcomes. This review focuses on MYBPC3 mutation and its characteristics as a prognostic determinant for disease onset and related clinical consequences in HCM.

Evidence-Based Guide to Using Artificial Introns for Tissue-Specific Knockout in Mice

Up until recently, methods for generating floxed mice either conventionally or by CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas9 (CRISPR-associated protein 9) editing have been technically challenging, expensive and error-prone, or time-consuming. To circumvent these issues, several labs have started successfully using a small artificial intron to conditionally knockout (KO) a gene of interest in mice. However, many other labs are having difficulty getting the technique to work. The key problem appears to be either a failure in achieving correct splicing after the introduction of the artificial intron into the gene or, just as crucial, insufficient functional KO of the gene's protein after Cre-induced removal of the intron's branchpoint. Presented here is a guide on how to choose an appropriate exon and where to place the recombinase-regulated artificial intron (rAI) in that exon to prevent disrupting normal gene splicing while maximizing mRNA degradation after recombinase treatment. The reasoning behind each step in the guide is also discussed. Following these recommendations should increase the success rate of this easy, new, and alternative technique for producing tissue-specific KO mice.

MTAP-ANRIL gene fusion promotes melanoma epithelial-mesenchymal transition-like process by activating the JNK and p38 signaling pathways

Gene fusions caused by cytogenetic aberrations play important roles in the initiation and progression of cancers. The recurrent MTAP-ANRIL fusion gene was reported to have a frequency of greater than 7% in melanoma in our previous study. However, its functions remain unclear. Truncated MTAP proteins resulting from point mutations in the last three exons of MTAP can physically interact with the wild-type MTAP protein, a tumor suppressor in several human cancers. Similarly, MTAP-ANRIL, which is translated into a truncated MTAP protein, would influence wild-type MTAP to act as an oncogene. Here, we found that MTAP-ANRIL gene fusion downregulated the expression of wild-type MTAP and promoted epithelial-mesenchymal transition-like process through the activation of JNK and p38 MAPKs in vitro and in vivo. Our results suggest that MTAP-ANRIL is a potential molecular prognostic biomarker and therapeutic target for melanoma.

Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data

Long-read RNA sequencing (lrRNA-seq) produces detailed information about full-length transcripts, including novel and sample-specific isoforms. Furthermore, there is an opportunity to call variants directly from lrRNA-seq data. However, most state-of-the-art variant callers have been developed for genomic DNA. Here, there are two objectives: first, we perform a mini-benchmark on GATK, DeepVariant, Clair3, and NanoCaller primarily on PacBio Iso-Seq, data, but also on Nanopore and Illumina RNA-seq data; second, we propose a pipeline to process spliced-alignment files, making them suitable for variant calling with DNA-based callers. With such manipulations, high calling performance can be achieved using DeepVariant on Iso-seq data.

The origins and functional effects of postzygotic mutations throughout the human life span

Postzygotic mutations (PZMs) begin to accrue in the human genome immediately after fertilization, but how and when PZMs affect development and lifetime health remain unclear. To study the origins and functional consequences of PZMs, we generated a multitissue atlas of PZMs spanning 54 tissue and cell types from 948 donors. Nearly half the variation in mutation burden among tissue samples can be explained by measured technical and biological effects, and 9% can be attributed to donor-specific effects. Through phylogenetic reconstruction of PZMs, we found that their type and predicted functional impact vary during prenatal development, across tissues, and through the germ cell life cycle. Thus, methods for interpreting effects across the body and the life span are needed to fully understand the consequences of genetic variants.

Improved detection of aberrant splicing using the Intron Jaccard Index

Detection of aberrantly spliced genes is an important step in RNA-seq-based rare disease diagnostics. We recently developed FRASER, a denoising autoencoder-based method for aberrant splicing detection that outperformed alternative approaches. However, as FRASER's three splice metrics are partially redundant and tend to be sensitive to sequencing depth, we introduce here a more robust intron excision metric, the Intron Jaccard Index, that combines alternative donor, alternative acceptor, and intron retention signal into a single value. Moreover, we optimized model parameters and filter cutoffs using candidate rare splice-disrupting variants as independent evidence. On 16,213 GTEx samples, our improved algorithm called typically 10 times fewer splicing outliers while increasing the proportion of candidate rare splice-disrupting variants by 10 fold and substantially decreasing the effect of sequencing depth on the number of reported outliers. Application on 303 rare disease samples confirmed the reduction fold-change of the number of outlier calls for a slight loss of sensitivity (only 2 out of 22 previously identified pathogenic splicing cases not recovered). Altogether, these methodological improvements contribute to more effective RNA-seq-based rare diagnostics by a drastic reduction of the amount of splicing outlier calls per sample at minimal loss of sensitivity.

A complementary approach for genetic diagnosis of inborn errors of immunity using proteogenomic analysis

Advances in next-generation sequencing technology have identified many genes responsible for inborn errors of immunity (IEI). However, there is still room for improvement in the efficiency of genetic diagnosis. Recently, RNA sequencing and proteomics using peripheral blood mononuclear cells (PBMCs) have gained attention, but only some studies have integrated these analyses in IEI. Moreover, previous proteomic studies for PBMCs have achieved limited coverage (approximately 3000 proteins). More comprehensive data are needed to gain valuable insights into the molecular mechanisms underlying IEI. Here, we propose a state-of-the-art method for diagnosing IEI using PBMCs proteomics integrated with targeted RNA sequencing (T-RNA-seq), providing unique insights into the pathogenesis of IEI. This study analyzed 70 IEI patients whose genetic etiology had not been identified by genetic analysis. In-depth proteomics identified 6498 proteins, which covered 63% of 527 genes identified in T-RNA-seq, allowing us to examine the molecular cause of IEI and immune cell defects. This integrated analysis identified the disease-causing genes in four cases undiagnosed in previous genetic studies. Three of them could be diagnosed by T-RNA-seq, while the other could only be diagnosed by proteomics. Moreover, this integrated analysis showed high protein-mRNA correlations in B- and T-cell-specific genes, and their expression profiles identified patients with immune cell dysfunction. These results indicate that integrated analysis improves the efficiency of genetic diagnosis and provides a deep understanding of the immune cell dysfunction underlying the etiology of IEI. Our novel approach demonstrates the complementary role of proteogenomic analysis in the genetic diagnosis and characterization of IEI.

Improving Hereditary Hemorrhagic Telangiectasia Molecular Diagnosis: A Referral Center Experience

BACKGROUND

Hereditary hemorrhagic telangiectasia (HHT) is a rare vascular disease inherited in an autosomal dominant manner. Disease-causing variants in endoglin (ENG) and activin A receptor type II-like 1 (ACVRL1) genes are detected in more than 90% of the patients undergoing molecular testing. The identification of variants of unknown significance is often seen as a challenge in clinical practice that makes family screening and genetic counseling difficult. Here, we show that the implementation of cDNA analysis to assess the effect of splice site variants on mRNA splicing is a powerful tool.

METHODS

Gene panel sequencing of genes associated with HHT and other arteriovenous malformation-related syndromes was performed. To evaluate the effect of the splice site variants, cDNA analysis of ENG and ACVRL1 genes was carried out.

RESULTS

three novel splice site variants were identified in ENG (c.68-2A > T and c.1311+4_1311+8del) and ACVLR1 (c.526-6C > G) genes correspondingly in three individuals with HHT that met ≥ 3 Curaçao criteria. All three variants led to an aberrant splicing inducing exon skipping (ENG:c.68-2A > T and ACVRL1:c.526-6C > G) or intron retention (ENG:c.1311+4_1311+8del) allowing the confirmation of the predicted effect on splicing and the reclassification from unknown significance to pathogenic/likely pathogenic of two of them.

CONCLUSIONS

RNA analysis should be performed to assess and/or confirm the impact of variants on splicing. The molecular diagnosis of HHT patients is crucial to allow family screening and accurate genetic counseling. A multidisciplinary approach including clinicians and geneticists is crucial when dealing with patients with rare diseases.

aenmd: Annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants

DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce a transcript's degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these that could exert DN/GOF effects via NMD escape. Availability and implementation: aenmd is implemented in the R programming language. Code is available on GitHub as an R package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).

Mouse mutants in schizophrenia risk genes GRIN2A and AKAP11 show EEG abnormalities in common with schizophrenia patients

Schizophrenia is a heterogeneous psychiatric disorder with a strong genetic basis, whose etiology and pathophysiology remain poorly understood. Exome sequencing studies have uncovered rare, loss-of-function variants that greatly increase risk of schizophrenia [1], including loss-of-function mutations in GRIN2A (aka GluN2A or NR2A, encoding the NMDA receptor subunit 2A) and AKAP11 (A-Kinase Anchoring Protein 11). AKAP11 and GRIN2A mutations are also associated with bipolar disorder [2], and epilepsy and developmental delay/intellectual disability [1, 3, 4], respectively. Accessible in both humans and rodents, electroencephalogram (EEG) recordings offer a window into brain activity and display abnormal features in schizophrenia patients. Does loss of Grin2a or Akap11 in mice also result in EEG abnormalities? We monitored EEG in heterozygous and homozygous knockout Grin2a and Akap11 mutant mice compared with their wild-type littermates, at 3- and 6-months of age, across the sleep/wake cycle and during auditory stimulation protocols. Grin2a and Akap11 mutants exhibited increased resting gamma power, attenuated auditory steady-state responses (ASSR) at gamma frequencies, and reduced responses to unexpected auditory stimuli during mismatch negativity (MMN) tests. Sleep spindle density was reduced in a gene dose-dependent manner in Akap11 mutants, whereas Grin2a mutants showed increased sleep spindle density. The EEG phenotypes of Grin2a and Akap11 mutant mice show a variety of abnormal features that overlap considerably with human schizophrenia patients, reflecting systems-level changes caused by Grin2a and Akap11 deficiency. These neurophysiologic findings further substantiate Grin2a and Akap11 mutants as genetic models of schizophrenia and identify potential biomarkers for stratification of schizophrenia patients.

Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data

Predicted loss of function (pLoF) variants are highly deleterious and play an important role in disease biology, but many of these variants may not actually result in loss-of-function. Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines's PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 autosomal recessive disease-genes from the Genome Aggregation Database (gnomAD, v2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in low per-base expression (pext) score regions, or the presence of cryptic splice rescues. Variants predicted to be potential artifacts or to evade LoF were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of LoF evading variants assessed, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines, and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Genome-wide association study reveals BET1L associated with survival time in the 137,693 Japanese individuals

Human lifespan is reported to be heritable. Although previous genome-wide association studies (GWASs) have identified several loci, a limited number of studies have assessed the genetic associations with the real survival information on the participants. We conducted a GWAS to identify loci associated with survival time in the Japanese individuals participated in the BioBank Japan Project by carrying out sex-stratified GWASs involving 78,029 males and 59,664 females. Of them, 31,324 (22.7%) died during the mean follow-up period of 7.44 years. We found a novel locus associated with survival (BET1L; P = 5.89 × 10^-9). By integrating with eQTL data, we detected a significant overlap with eQTL of BET1L in skeletal muscle. A gene-set enrichment analysis showed that genes related to the BCAR1 protein-protein interaction subnetwork influence survival time (P = 1.54 × 10^-7). These findings offer the candidate genes and biological mechanisms associated with human lifespan.

PGAGP: Predicting pathogenic genes based on adaptive network embedding algorithm

The study of disease-gene associations is an important topic in the field of computational biology. The accumulation of massive amounts of biomedical data provides new possibilities for exploring potential relations between diseases and genes through computational strategy, but how to extract valuable information from the data to predict pathogenic genes accurately and rapidly is currently a challenging and meaningful task. Therefore, we present a novel computational method called PGAGP for inferring potential pathogenic genes based on an adaptive network embedding algorithm. The PGAGP algorithm is to first extract initial features of nodes from a heterogeneous network of diseases and genes efficiently and effectively by Gaussian random projection and then optimize the features of nodes by an adaptive refining process. These low-dimensional features are used to improve the disease-gene heterogenous network, and we apply network propagation to the improved heterogenous network to predict pathogenic genes more effectively. By a series of experiments, we study the effect of PGAGP's parameters and integrated strategies on predictive performance and confirm that PGAGP is better than the state-of-the-art algorithms. Case studies show that many of the predicted candidate genes for specific diseases have been implied to be related to these diseases by literature verification and enrichment analysis, which further verifies the effectiveness of PGAGP. Overall, this work provides a useful solution for mining disease-gene heterogeneous network to predict pathogenic genes more effectively.

Impact of pathogenic FBN1 variant types on the development of severe scoliosis in patients with Marfan syndrome

BACKGROUND

Among the several musculoskeletal manifestations in patients with Marfan syndrome, spinal deformity causes pain and respiratory impairment and is a great hindrance to patients' daily activities. The present study elucidates the genetic risk factors for the development of severe scoliosis in patients with Marfan syndrome.

METHODS

We retrospectively evaluated 278 patients with pathogenic or likely pathogenic FBN1 variants. The patients were divided into those with (n=57) or without (n=221) severe scoliosis. Severe scoliosis was defined as (1) patients undergoing surgery before 50 years of age or (2) patients with a Cobb angle exceeding 50° before 50 years of age. The variants were classified as protein-truncating variants (PTVs), which included variants creating premature termination codons and inframe exon-skipping, or non-PTVs, based on their location and predicted amino acid alterations, and the effect of the FBN1 genotype on the development of severe scoliosis was examined. The impact of location of FBN1 variants on the development of severe scoliosis was also investigated.

RESULTS

Univariate and multivariate analyses revealed that female sex, PTVs of FBN1 and variants in the neonatal region (exons 25-33) were all independent significant predictive factors for the development of severe scoliosis. Furthermore, these factors were identified as predictors of progression of existing scoliosis into severe state.

CONCLUSIONS

We elucidated the genetic risk factors for the development of severe scoliosis in patients with Marfan syndrome. Patients harbouring pathogenic FBN1 variants with these genetic risk factors should be monitored carefully for scoliosis progression.

Integrated top-down and bottom-up proteomics mass spectrometry for the characterization of endogenous ribosomal protein heterogeneity

Ribosomes are abundant, large RNA-protein complexes that are the sites of all protein synthesis in cells. Defects in ribosomal proteins (RPs), including proteoforms arising from genetic variations, alternative splicing of RNA transcripts, post-translational modifications and alterations of protein expression level, have been linked to a diverse range of diseases, including cancer and aging. Comprehensive characterization of ribosomal proteoforms is challenging but important for the discovery of potential disease biomarkers or protein targets. In the present work, using E. coli 70S RPs as an example, we first developed a top-down proteomics approach on a Waters Synapt G2 Si mass spectrometry (MS) system, and then applied it to the HeLa 80S ribosome. The results were complemented by a bottom-up approach. In total, 50 out of 55 RPs were identified using the top-down approach. Among these, more than 30 RPs were found to have their N-terminal methionine removed. Additional modifications such as methylation, acetylation, and hydroxylation were also observed, and the modification sites were identified by bottom-up MS. In a HeLa 80S ribosomal sample, we identified 98 ribosomal proteoforms, among which multiple truncated 80S ribosomal proteoforms were observed, the type of information which is often overlooked by bottom-up experiments. Although their relevance to diseases is not yet known, the integration of top-down and bottom-up proteomics approaches paves the way for the discovery of proteoform-specific disease biomarkers or targets.

Genetic Mimicry Analysis Reveals the Specific Lipases Targeted by the ANGPTL3-ANGPTL8 Complex and ANGPTL4

Angiopoietin-like proteins, ANGPTL3, ANGPTL4, and ANGPTL8, are involved in regulating plasma lipids. In vitro and animal-based studies point to LPL and endothelial lipase (EL, LIPG) as key targets of ANGPTLs. To examine the ANGPTL mechanisms for plasma lipid modulation in humans, we pursued a genetic mimicry analysis of enhancing or suppressing variants in the LPL, LIPG, lipase C hepatic type (LIPC), ANGPTL3, ANGPTL4, and ANGPTL8 genes using data on 248 metabolic parameters derived from over 110,000 nonfasted individuals in the UK Biobank and validated in over 13,000 overnight fasted individuals from 11 other European populations. ANGPTL4 suppression was highly concordant with LPL enhancement but not HL or EL, suggesting ANGPTL4 impacts plasma metabolic parameters exclusively via LPL. The LPL-independent effects of ANGPTL3 suppression on plasma metabolic parameters showed a striking inverse resemblance with EL suppression, suggesting ANGPTL3 not only targets LPL but also targets EL. Investigation of the impact of the ANGPTL3-ANGPTL8 complex on plasma metabolite traits via the ANGPTL8 R59W substitution as an instrumental variable showed a much higher concordance between R59W and EL activity than between R59W and LPL activity, suggesting the R59W substitution more strongly affects EL inhibition than LPL inhibition. Meanwhile, when using a rare and deleterious protein-truncating ANGPTL8 variant as an instrumental variable, the ANGPTL3-ANGPTL8 complex was very LPL specific. In conclusion, our analysis provides strong human genetic evidence that the ANGPTL3-ANGPTL8 complex regulates plasma metabolic parameters, which is achieved by impacting LPL and EL. By contrast, ANGPTL4 influences plasma metabolic parameters exclusively via LPL.

Whole-Genome Profile of Greek Patients with Teratozοοspermia: Identification of Candidate Variants and Genes

Male infertility is a global health problem that affects a large number of couples worldwide. It can be categorized into specific subtypes, including teratozoospermia. The present study aimed to identify new variants associated with teratozoospermia in the Greek population and to explore the role of genes on which these were identified. For this reason, whole-genome sequencing (WGS) was performed on normozoospermic and teratozoospermic individuals, and after selecting only variants found in teratozoospermic men, these were further prioritized using a wide range of tools, functional and predictive algorithms, etc. An average of 600,000 variants were identified, and of them, 61 were characterized as high impact and 153 as moderate impact. Many of these are mapped in genes previously associated with male infertility, yet others are related for the first time to teratozoospermia. Furthermore, pathway enrichment analysis and Gene ontology (GO) analyses revealed the important role of the extracellular matrix in teratozoospermia. Therefore, the present study confirms the contribution of genes studied in the past to male infertility and sheds light on new molecular mechanisms by providing a list of variants and candidate genes associated with teratozoospermia in the Greek population.

A resource for integrated genomic analysis of the human liver

In this study, we generated whole-transcriptome RNA-Seq from n = 192 genotyped liver samples and used these data with existing data from the GTEx Project (RNA-Seq) and previous liver eQTL (microarray) studies to create an enhanced transcriptomic sequence resource in the human liver. Analyses of genotype-expression associations show pronounced enrichment of associations with genes of drug response. The associations are primarily consistent across the two RNA-Seq datasets, with some modest variation, indicating the importance of obtaining multiple datasets to produce a robust resource. We further used an empirical Bayesian model to compare eQTL patterns in liver and an additional 20 GTEx tissues, finding that MHC genes, and especially class II genes, are enriched for liver-specific eQTL patterns. To illustrate the utility of the resource to augment GWAS analysis with small sample sizes, we developed a novel meta-analysis technique to combine several liver eQTL data sources. We also illustrate its application using a transcriptome-enhanced re-analysis of a study of neutropenia in pancreatic cancer patients. The associations of genotype with liver expression, including splice variation and its genetic associations, are made available in a searchable genome browser.

Transcriptome variation in human tissues revealed by long-read sequencing

Regulation of transcript structure generates transcript diversity and plays an important role in human disease1-7. The advent of long-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure8-16. In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.

Nonsense-mediated RNA decay: an emerging modulator of malignancy

Nonsense-mediated RNA decay (NMD) is a highly conserved RNA turnover pathway that selectively degrades RNAs harbouring truncating mutations that prematurely terminate translation, including nonsense, frameshift and some splice-site mutations. Recent studies show that NMD shapes the mutational landscape of tumours by selecting for mutations that tend to downregulate the expression of tumour suppressor genes but not oncogenes. This suggests that NMD can benefit tumours, a notion further supported by the finding that mRNAs encoding immunogenic neoantigen peptides are typically targeted for decay by NMD. Together, this raises the possibility that NMD-inhibitory therapy could be of therapeutic benefit against many tumour types, including those with a high load of neoantigen-generating mutations. Complicating this scenario is the evidence that NMD can also be detrimental for many tumour types, and consequently tumours often have perturbed NMD. NMD may suppress tumour generation and progression by degrading subsets of specific normal mRNAs, including those encoding stress-response proteins, signalling factors and other proteins beneficial for tumours, as well as pro-tumour non-coding RNAs. Together, these findings suggest that NMD-modulatory therapy has the potential to provide widespread therapeutic benefit against diverse tumour types. However, whether NMD should be stimulated or repressed requires careful analysis of the tumour to be treated.

A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project

Background

Genomic variants which disrupt splicing are a major cause of rare genetic diseases. However, variants which lie outside of the canonical splice sites are difficult to interpret clinically. Improving the clinical interpretation of non-canonical splicing variants offers a major opportunity to uplift diagnostic yields from whole genome sequencing data.

Methods

Here, we examine the landscape of splicing variants in whole-genome sequencing data from 38,688 individuals in the 100,000 Genomes Project and assess the contribution of non-canonical splicing variants to rare genetic diseases. We use a variant-level constraint metric (the mutability-adjusted proportion of singletons) to identify constrained functional variant classes near exon–intron junctions and at putative splicing branchpoints. To identify new diagnoses for individuals with unsolved rare diseases in the 100,000 Genomes Project, we identified individuals with de novo single-nucleotide variants near exon–intron boundaries and at putative splicing branchpoints in known disease genes. We identified candidate diagnostic variants through manual phenotype matching and confirmed new molecular diagnoses through clinical variant interpretation and functional RNA studies.

Results

We show that near-splice positions and splicing branchpoints are highly constrained by purifying selection and harbour potentially damaging non-coding variants which are amenable to systematic analysis in sequencing data. From 258 de novo splicing variants in known rare disease genes, we identify 35 new likely diagnoses in probands with an unsolved rare disease. To date, we have confirmed a new diagnosis for six individuals, including four in whom RNA studies were performed.

Conclusions

Overall, we demonstrate the clinical value of examining non-canonical splicing variants in individuals with unsolved rare diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01087-x.

Alternative splicing as a source of phenotypic diversity

A major goal of evolutionary genetics is to understand the genetic processes that give rise to phenotypic diversity in multicellular organisms. Alternative splicing generates multiple transcripts from a single gene, enriching the diversity of proteins and phenotypic traits. It is well established that alternative splicing contributes to key innovations over long evolutionary timescales, such as brain development in bilaterians. However, recent developments in long-read sequencing and the generation of high-quality genome assemblies for diverse organisms has facilitated comparisons of splicing profiles between closely related species, providing insights into how alternative splicing evolves over shorter timescales. Although most splicing variants are probably non-functional, alternative splicing is nonetheless emerging as a dynamic, evolutionarily labile process that can facilitate adaptation and contribute to species divergence.

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.

The broader sense of nonsense

The term 'nonsense-mediated mRNA decay' (NMD) was initially coined to describe the translation-dependent degradation of mRNAs harboring premature termination codons (PTCs), but it is meanwhile known that NMD also targets many canonical mRNAs with numerous biological implications. The molecular mechanisms determining on which RNAs NMD ensues are only partially understood. Considering the broad range of NMD-sensitive RNAs and the variable degrees of their degradation, we highlight here the hallmarks of mammalian NMD and point out open questions. We review the links between NMD and disease by summarizing the role of NMD in cancer, neurodegeneration, and viral infections. Finally, we describe strategies to modulate NMD activity and specificity as potential therapeutic approaches for various diseases.

Population Prevalence of Premature Truncating Variants in Plakophilin-2 and Association With Arrhythmogenic Right Ventricular Cardiomyopathy: A UK Biobank Analysis

BACKGROUND

Truncating variants in the desmosomal gene PKP2 (PKP2tv) cause arrhythmogenic right ventricular cardiomyopathy (ARVC) yet display varied penetrance and expressivity.

METHODS

We identified individuals with PKP2tv from the UK Biobank (UKB) and determined the prevalence of an ARVC phenotype and other cardiovascular traits based on clinical and procedural data. The PKP2tv minor allelic frequency in the UKB was compared with a second cohort of probands with a clinical diagnosis of ARVC (ARVC cohort), with a figure of 1:5000 assumed for disease prevalence. In silico predictors of variant pathogenicity (combined annotation-dependent depletion and Splice AI [Illumina, Inc.]) were assessed.

RESULTS

PKP2tv were identified in 193/200 643 (0.10%) UKB participants, with 47 unique PKP2tv. Features consistent with ARVC were present in 3 (1.6%), leaving 190 with PKP2tv without manifest disease (UKB cohort; minor allelic frequency 4.73×10-4). The ARVC cohort included 487 ARVC probands with 144 distinct PKP2tv, with 25 PKP2tv common to both cohorts. The odds ratio for ARVC for the 25 common PKP2tv was 0.047 (95% CI, 0.001-0.268; P=2.43×10-6), and only favored ARVC (odds ratio >1) for a single variant, p.Arg79*. In silico variant analysis did not differentiate PKP2tv between the 2 cohorts. Atrial fibrillation was over-represented in the UKB cohort in those with PKP2tv (7.9% versus 4.3%; odds ratio, 2.11; P=0.005).

CONCLUSIONS

PKP2tv are prevalent in the population and associated with ARVC in only a small minority, necessitating a more detailed understanding of how PKP2tv cause ARVC in combination with associated genetic and environmental risk factors.

Genetic, epigenetic, and environmental mechanisms govern allele-specific gene expression

Allele-specific expression (ASE) is a phenomenon in which one allele is preferentially expressed over the other. Genetic and epigenetic factors cause ASE by altering the final composition of a gene's product, leading to expression imbalances that can have functional consequences on phenotypes. Environmental signals also impact allele-specific expression, but how they contribute to this cross talk remains understudied. Here, we explored how genotype, parent-of-origin, tissue, sex, and dietary fat simultaneously influence ASE biases. Male and female mice from a F₁ reciprocal cross of the LG/J and SM/J strains were fed a high or low fat diet. We harnessed strain-specific variants to distinguish between two ASE classes: parent-of-origin-dependent (unequal expression based on parental origin) and sequence-dependent (unequal expression based on nucleotide identity). We present a comprehensive map of ASE patterns in 2853 genes across three tissues and nine environmental contexts. We found that both ASE classes are highly dependent on tissue and environmental context. They vary across metabolically relevant tissues, between males and females, and in response to dietary fat. We also found 45 genes with inconsistent ASE biases that switched direction across tissues and/or environments. Finally, we integrated ASE and QTL data from published intercrosses of the LG/J and SM/J strains. Our ASE genes are often enriched in QTLs for metabolic and musculoskeletal traits, highlighting how this orthogonal approach can prioritize candidate genes. Together, our results provide novel insights into how genetic, epigenetic, and environmental mechanisms govern allele-specific expression, which is an essential step toward deciphering the genotype-to-phenotype map.

Pathophysiological Heterogeneity of the BBSOA Neurodevelopmental Syndrome

The formation and maturation of the human brain is regulated by highly coordinated developmental events, such as neural cell proliferation, migration and differentiation. Any impairment of these interconnected multi-factorial processes can affect brain structure and function and lead to distinctive neurodevelopmental disorders. Here, we review the pathophysiology of the Bosch–Boonstra–Schaaf Optic Atrophy Syndrome (BBSOAS; OMIM 615722; ORPHA 401777), a recently described monogenic neurodevelopmental syndrome caused by the haploinsufficiency of NR2F1 gene, a key transcriptional regulator of brain development. Although intellectual disability, developmental delay and visual impairment are arguably the most common symptoms affecting BBSOAS patients, multiple additional features are often reported, including epilepsy, autistic traits and hypotonia. The presence of specific symptoms and their variable level of severity might depend on still poorly characterized genotype–phenotype correlations. We begin with an overview of the several mutations of NR2F1 identified to date, then further focuses on the main pathological features of BBSOAS patients, providing evidence—whenever possible—for the existing genotype–phenotype correlations. On the clinical side, we lay out an up-to-date list of clinical examinations and therapeutic interventions recommended for children with BBSOAS. On the experimental side, we describe state-of-the-art in vivo and in vitro studies aiming at deciphering the role of mouse Nr2f1, in physiological conditions and in pathological contexts, underlying the BBSOAS features. Furthermore, by modeling distinct NR2F1 genetic alterations in terms of dimer formation and nuclear receptor binding efficiencies, we attempt to estimate the total amounts of functional NR2F1 acting in developing brain cells in normal and pathological conditions. Finally, using the NR2F1 gene and BBSOAS as a paradigm of monogenic rare neurodevelopmental disorder, we aim to set the path for future explorations of causative links between impaired brain development and the appearance of symptoms in human neurological syndromes.

Clinical implementation of RNA sequencing for Mendelian disease diagnostics

BACKGROUND

Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics.

METHODS

We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease that previously underwent WES. We also assessed through simulations how aberrant expression and mono-allelic expression tests depend on RNA-seq coverage.

RESULTS

We detected on average 12,500 genes per sample including around 60% of all disease genes-a coverage substantially higher than with whole blood, supporting the use of skin biopsies. We prioritized genes demonstrating aberrant expression, aberrant splicing, or mono-allelic expression. The pipeline required less than 1 week from sample preparation to result reporting and provided a median of eight disease-associated genes per patient for inspection. A genetic diagnosis was established for 16% of the 205 WES-inconclusive cases. Detection of aberrant expression was a major contributor to diagnosis including instances of 50% reduction, which, together with mono-allelic expression, allowed for the diagnosis of dominant disorders caused by haploinsufficiency. Moreover, calling aberrant splicing and variants from RNA-seq data enabled detecting and validating splice-disrupting variants, of which the majority fell outside WES-covered regions.

CONCLUSION

Together, these results show that streamlined experimental and computational processes can accelerate the implementation of RNA-seq in routine diagnostics.

Rare coding variants in ten genes confer substantial risk for schizophrenia

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

Significant sparse polygenic risk scores across 813 traits in UK Biobank

We present a systematic assessment of polygenic risk score (PRS) prediction across more than 1,500 traits using genetic and phenotype data in the UK Biobank. We report 813 sparse PRS models with significant (p < 2.5 x 10-5) incremental predictive performance when compared against the covariate-only model that considers age, sex, types of genotyping arrays, and the principal component loadings of genotypes. We report a significant correlation between the number of genetic variants selected in the sparse PRS model and the incremental predictive performance (Spearman's ⍴ = 0.61, p = 2.2 x 10-59 for quantitative traits, ⍴ = 0.21, p = 9.6 x 10-4 for binary traits). The sparse PRS model trained on European individuals showed limited transferability when evaluated on non-European individuals in the UK Biobank. We provide the PRS model weights on the Global Biobank Engine (https://biobankengine.stanford.edu/prs).