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

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.

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.

What genes are differentially expressed in individuals with schizophrenia? A systematic review

Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.

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).

Limited allele-specific gene expression in highly polyploid sugarcane

Polyploidy is widespread in plants, allowing the different copies of genes to be expressed differently in a tissue-specific or developmentally specific way. This allele-specific expression (ASE) has been widely reported, but the proportion and nature of genes showing this characteristic have not been well defined. We now report an analysis of the frequency and patterns of ASE at the whole-genome level in the highly polyploid sugarcane genome. Very high depth whole-genome sequencing and RNA sequencing revealed strong correlations between allelic proportions in the genome and in expressed sequences. This level of sequencing allowed discrimination of each of the possible allele doses in this 12-ploid genome. Most genes were expressed in direct proportion to the frequency of the allele in the genome with examples of polymorphisms being found with every possible discrete level of dose from 1:11 for single-copy alleles to 12:0 for monomorphic sites. The rarer cases of ASE were more frequent in the expression of defense-response genes, as well as in some processes related to the biosynthesis of cell walls. ASE was more common in genes with variants that resulted in significant disruption of function. The low level of ASE may reflect the recent origin of polyploid hybrid sugarcane. Much of the ASE present can be attributed to strong selection for resistance to diseases in both nature and domestication.

Research on the Computational Prediction of Essential Genes

Genes, the nucleotide sequences that encode a polypeptide chain or functional RNA, are the basic genetic unit controlling biological traits. They are the guarantee of the basic structures and functions in organisms, and they store information related to biological factors and processes such as blood type, gestation, growth, and apoptosis. The environment and genetics jointly affect important physiological processes such as reproduction, cell division, and protein synthesis. Genes are related to a wide range of phenomena including growth, decline, illness, aging, and death. During the evolution of organisms, there is a class of genes that exist in a conserved form in multiple species. These genes are often located on the dominant strand of DNA and tend to have higher expression levels. The protein encoded by it usually either performs very important functions or is responsible for maintaining and repairing these essential functions. Such genes are called persistent genes. Among them, the irreplaceable part of the body’s life activities is the essential gene. For example, when starch is the only source of energy, the genes related to starch digestion are essential genes. Without them, the organism will die because it cannot obtain enough energy to maintain basic functions. The function of the proteins encoded by these genes is thought to be fundamental to life. Nowadays, DNA can be extracted from blood, saliva, or tissue cells for genetic testing, and detailed genetic information can be obtained using the most advanced scientific instruments and technologies. The information gained from genetic testing is useful to assess the potential risks of disease, and to help determine the prognosis and development of diseases. Such information is also useful for developing personalized medication and providing targeted health guidance to improve the quality of life. Therefore, it is of great theoretical and practical significance to identify important and essential genes. In this paper, the research status of essential genes and the essential genome database of bacteria are reviewed, the computational prediction method of essential genes based on communication coding theory is expounded, and the significance and practical application value of essential genes are discussed.

Cellular variability of nonsense-mediated mRNA decay

Nonsense-mediated mRNA decay (NMD) is an mRNA degradation pathway that eliminates transcripts containing premature termination codons (PTCs). Half-lives of the mRNAs containing PTCs demonstrate that a small percent escape surveillance and do not degrade. It is not known whether this escape represents variable mRNA degradation within cells or, alternatively cells within the population are resistant. Here we demonstrate a single-cell approach with a bi-directional reporter, which expresses two β-globin genes with or without a PTC in the same cell, to characterize the efficiency of NMD in individual cells. We found a broad range of NMD efficiency in the population; some cells degraded essentially all of the mRNAs, while others escaped NMD almost completely. Characterization of NMD efficiency together with NMD regulators in single cells showed cell-to-cell variability of NMD reflects the differential level of surveillance factors, SMG1 and phosphorylated UPF1. A single-cell fluorescent reporter system that enabled detection of NMD using flow cytometry revealed that this escape occurred either by translational readthrough at the PTC or by a failure of mRNA degradation after successful translation termination at the PTC.

Bayesian model comparison for rare-variant association studies

Whole-genome sequencing studies applied to large populations or biobanks with extensive phenotyping raise new analytic challenges. The need to consider many variants at a locus or group of genes simultaneously and the potential to study many correlated phenotypes with shared genetic architecture provide opportunities for discovery not addressed by the traditional one variant, one phenotype association study. Here, we introduce a Bayesian model comparison approach called MRP (multiple rare variants and phenotypes) for rare-variant association studies that considers correlation, scale, and direction of genetic effects across a group of genetic variants, phenotypes, and studies, requiring only summary statistic data. We apply our method to exome sequencing data (n = 184,698) across 2,019 traits from the UK Biobank, aggregating signals in genes. MRP demonstrates an ability to recover signals such as associations between PCSK9 and LDL cholesterol levels. We additionally find MRP effective in conducting meta-analyses in exome data. Non-biomarker findings include associations between MC1R and red hair color and skin color, IL17RA and monocyte count, and IQGAP2 and mean platelet volume. Finally, we apply MRP in a multi-phenotype setting; after clustering the 35 biomarker phenotypes based on genetic correlation estimates, we find that joint analysis of these phenotypes results in substantial power gains for gene-trait associations, such as in TNFRSF13B in one of the clusters containing diabetes- and lipid-related traits. Overall, we show that the MRP model comparison approach improves upon useful features from widely used meta-analysis approaches for rare-variant association analyses and prioritizes protective modifiers of disease risk.

Power calculator for detecting allelic imbalance using hierarchical Bayesian model

OBJECTIVE

Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Methods for testing AI exist, but methods are needed to estimate type I error and power for detecting AI and difference of AI between conditions. As the costs of the technology plummet, what is more important: reads or replicates?

RESULTS

We find that a minimum of 2400, 480, and 240 allele specific reads divided equally among 12, 5, and 3 replicates is needed to detect a 10, 20, and 30%, respectively, deviation from allelic balance in a condition with power > 80%. A minimum of 960 and 240 allele specific reads divided equally among 8 replicates is needed to detect a 20 or 30% difference in AI between conditions with comparable power. Higher numbers of replicates increase power more than adding coverage without affecting type I error. We provide a Python package that enables simulation of AI scenarios and enables individuals to estimate type I error and power in detecting AI and differences in AI between conditions.

Endoplasmic stress-inducing variants in CPB1 and CPA1 and risk of pancreatic cancer: A case-control study and meta-analysis

Gene variants that encode pancreatic enzymes with impaired secretion can induce pancreatic acinar endoplasmic reticulum (ER) stress, cellular injury and pancreatitis. The role of such variants in pancreatic cancer risk has received little attention. We compared the prevalence of ER stress-inducing variants in CPA1 and CPB1 in patients with pancreatic ductal adenocarcinoma (PDAC cases), enrolled in the National Familial Pancreas Tumor Registry, to their prevalence in noncancer controls in the Genome Aggregation Database (gnomAD). Variants of unknown significance were expressed and variants with reduced secretion assessed for ER stress induction. In vitro assessments were compared with software predictions of variant function. Protein variant software was used to assess variants found in only one gnomAD control ("n-of-one" variants). A meta-analysis of prior PDAC case/control studies was also performed. Of the 1385 patients with PDAC, 0.65% were found to harbor an ER stress-inducing variant in CPA1 or CPB1, compared to 0.17% of the 64 026 controls (odds ratio [OR]: 3.80 [1.92-7.51], P = .0001). ER stress-inducing variants in the CPA1 gene were identified in 4 of 1385 PDAC cases vs 77 of 64 026 gnomAD controls (OR: 2.4 [0.88-6.58], P = .087), and variants in CPB1 were detected in 5 of 1385 cases vs 33 of 64 026 controls (OR: 7.02 [2.74-18.01], P = .0001). Meta-analysis demonstrated strong associations for pancreatic cancer and ER-stress inducing variants for both CPA1 (OR: 3.65 [1.58-8.39], P < .023) and CPB1 (OR: 9.51 [3.46-26.15], P < .001). Rare variants in CPB1 and CPA1 that induce ER stress are associated with increased odds of developing pancreatic cancer.

Evaluation of the MGISEQ-2000 Sequencing Platform for Illumina Target Capture Sequencing Libraries

Illumina is the leading sequencing platform in the next-generation sequencing (NGS) market globally. In recent years, MGI Tech has presented a series of new sequencers, including DNBSEQ-T7, MGISEQ-2000 and MGISEQ-200. As a complex application of NGS, cancer-detecting panels pose increasing demands for the high accuracy and sensitivity of sequencing and data analysis. In this study, we used the same capture DNA libraries constructed based on the Illumina protocol to evaluate the performance of the Illumina Nextseq500 and MGISEQ-2000 sequencing platforms. We found that the two platforms had high consistency in the results of hotspot mutation analysis; more importantly, we found that there was a significant loss of fragments in the 101-133 bp size range on the MGISEQ-2000 sequencing platform for Illumina libraries, but not for the capture DNA libraries prepared based on the MGISEQ protocol. This phenomenon may indicate fragment selection or low fragment ligation efficiency during the DNA circularization step, which is a unique step of the MGISEQ-2000 sequence platform. In conclusion, these different sequencing libraries and corresponding sequencing platforms are compatible with each other, but protocol and platform selection need to be carefully evaluated in combination with research purpose.

Global mapping of cancers: The Cancer Genome Atlas and beyond

Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.

Clinical and molecular characterization of five Chinese patients with autosomal recessive osteopetrosis

Background

Osteopetrosis is characterized by increased bone density and bone marrow cavity stenosis due to a decrease in the number of osteoclasts or the dysfunction of their differentiation and absorption properties usually caused by biallelic variants of the TCIRG1 and CLCN7 genes.

Methods

In this study, we describe five Chinese children who presented with anemia, thrombocytopenia, hepatosplenomegaly, repeated infections, and increased bone density. Whole‐exome sequencing identified five compound heterozygous variants of the CLCN7 and TCIRG1 genes in these patients.

Results

Patient 1 had a novel variant c.1555C>T (p.L519F) and a previously reported pathogenic variant c.2299C>T (p.R767W) in CLCN7. Patient 2 harbored a novel missense variant (c.1025T>C; p.L342P) and a novel splicing variant (c.286‐9G>A) in CLCN7. Patients 3A and 3B from one family displayed the same compound heterozygous TCIRG1 variant, including a novel frameshift variant (c.1370del; p.T457Tfs*71) and a novel splicing variant (c.1554+2T>C). In Patient 4, two novel variants were identified in the TCIRG1 gene: c.676G>T; p.E226* and c.1191del; p.P398Sfs*5. Patient 5 harbored two known pathogenic variants, c.909C>A (p.Y303*) and c.2008C>T (p.R670*), in TCIRG1. Analysis of the products obtained from the reverse transcription‐polymerase chain reaction revealed that the c.286‐9G>A variant in CLCN7 of patient 2 leads to intron 3 retention, resulting in the formation of a premature termination codon (p.E95Vfs*8). These five patients were eventually diagnosed with autosomal recessive osteopetrosis, and the three children with TCIRG1 variants received hematopoietic stem cell transplantation.

Conclusions

Our results expand the spectrum of variation of genes related to osteopetrosis and deepen the understanding of the relationship between the genotype and clinical characteristics of osteopetrosis.

Pan-Cancer Analysis of Immune Complement Signature C3/C5/C3AR1/C5AR1 in Association with Tumor Immune Evasion and Therapy Resistance

Despite the advances in our understanding of the genetic and immunological basis of cancer, cancer remains a major public health burden with an ever-increasing incidence rate globally. Nevertheless, increasing evidence suggests that the components of the complement system could regulate the tumor microenvironment (TME) to promote cancer progression, recurrence, and metastasis. In the present study, we used an integrative multi-omics analysis of clinical data to explore the relationships between the expression levels of and genetic and epigenetic alterations in C3, C5, C3AR1, and C5AR1 and tumor immune evasion, therapy response, and patient prognosis in various cancer types. We found that the complements C3, C5, C3AR1, and C5AR1 have deregulated expression in human malignancies and are associated with activation of immune-related oncogenic processes and poor prognosis of cancer patients. Furthermore, we found that the increased expression levels of C3, C5, C3AR1, and C5AR1 were primarily predicted by copy number variation and gene methylation and were associated with dysfunctional T-cell phenotypes. Single nucleotide variation in the gene signature co-occurred with multiple oncogenic mutations and is associated with the progression of onco-immune-related diseases. Further correlation analysis revealed that C3, C5, C3AR1, and C5AR1 were associated with tumor immune evasion via dysfunctional T-cell phenotypes with a lesser contribution of T-cell exclusion. Lastly, we also demonstrated that the expression levels of C3, C5, C3AR1, and C5AR1 were associated with context-dependent chemotherapy, lymphocyte-mediated tumor killing, and immunotherapy outcomes in different cancer types. In conclusion, the complement components C3, C5, C3AR1, and C5AR1 serve as attractive targets for strategizing cancer immunotherapy and response follow-up.

Nanopore sequencing reveals endogenous NMD-targeted isoforms in human cells

BACKGROUND

Nonsense-mediated mRNA decay (NMD) is a eukaryotic, translation-dependent degradation pathway that targets mRNAs with premature termination codons and also regulates the expression of some mRNAs that encode full-length proteins. Although many genes express NMD-sensitive transcripts, identifying them based on short-read sequencing data remains a challenge.

RESULTS

To identify and analyze endogenous targets of NMD, we apply cDNA Nanopore sequencing and short-read sequencing to human cells with varying expression levels of NMD factors. Our approach detects full-length NMD substrates that are highly unstable and increase in levels or even only appear when NMD is inhibited. Among the many new NMD-targeted isoforms that our analysis identifies, most derive from alternative exon usage. The isoform-aware analysis reveals many genes with significant changes in splicing but no significant changes in overall expression levels upon NMD knockdown. NMD-sensitive mRNAs have more exons in the 3΄UTR and, for those mRNAs with a termination codon in the last exon, the length of the 3΄UTR per se does not correlate with NMD sensitivity. Analysis of splicing signals reveals isoforms where NMD has been co-opted in the regulation of gene expression, though the main function of NMD seems to be ridding the transcriptome of isoforms resulting from spurious splicing events.

CONCLUSIONS

Long-read sequencing enables the identification of many novel NMD-sensitive mRNAs and reveals both known and unexpected features concerning their biogenesis and their biological role. Our data provide a highly valuable resource of human NMD transcript targets for future genomic and transcriptomic applications.

Nonsense-mediated decay is highly stable across individuals and tissues

Precise interpretation of the effects of rare protein-truncating variants (PTVs) is important for accurate determination of variant impact. Current methods for assessing the ability of PTVs to induce nonsense-mediated decay (NMD) focus primarily on the position of the variant in the transcript. We used RNA sequencing of the Genotype Tissue Expression v.8 cohort to compute the efficiency of NMD using allelic imbalance for 2,320 rare (genome aggregation database minor allele frequency ≤ 1%) PTVs across 809 individuals in 49 tissues. We created an interpretable predictive model using penalized logistic regression in order to evaluate the comprehensive influence of variant annotation, tissue, and inter-individual variation on NMD. We found that variant position, allele frequency, the inclusion of ultra-rare and singleton variants, and conservation were predictive of allelic imbalance. Furthermore, we found that NMD effects were highly concordant across tissues and individuals. Due to this high consistency, we demonstrate in silico that utilizing peripheral tissues or cell lines provides accurate prediction of NMD for PTVs.

Deep sequencing of 1320 genes reveals the landscape of protein-truncating variants and their contribution to psoriasis in 19,973 Chinese individuals

Protein-truncating variants (PTVs) have important impacts on phenotype diversity and disease. However, their population genetics characteristics in more globally diverse populations are not well defined. Here, we describe patterns of PTVs in 1320 genes sequenced in 10,539 healthy controls and 9434 patients with psoriasis, all of Han Chinese ancestry. We identify 8720 PTVs, of which 77% are novel, and estimate 88% of all PTVs are deleterious and subject to purifying selection. Furthermore, we show that individuals with psoriasis have a significantly higher burden of PTVs compared to controls (P = 0.02). Finally, we identified 18 PTVs in 14 genes with unusually high levels of population differentiation, consistent with the action of local adaptation. Our study provides insights into patterns and consequences of PTVs.

How Machine Learning and Statistical Models Advance Molecular Diagnostics of Rare Disorders Via Analysis of RNA Sequencing Data

Rare diseases, although individually rare, collectively affect approximately 350 million people worldwide. Currently, nearly 6,000 distinct rare disorders with a known molecular basis have been described, yet establishing a specific diagnosis based on the clinical phenotype is challenging. Increasing integration of whole exome sequencing into routine diagnostics of rare diseases is improving diagnostic rates. Nevertheless, about half of the patients do not receive a genetic diagnosis due to the challenges of variant detection and interpretation. During the last years, RNA sequencing is increasingly used as a complementary diagnostic tool providing functional data. Initially, arbitrary thresholds have been applied to call aberrant expression, aberrant splicing, and mono-allelic expression. With the application of RNA sequencing to search for the molecular diagnosis, the implementation of robust statistical models on normalized read counts allowed for the detection of significant outliers corrected for multiple testing. More recently, machine learning methods have been developed to improve the normalization of RNA sequencing read count data by taking confounders into account. Together the methods have increased the power and sensitivity of detection and interpretation of pathogenic variants, leading to diagnostic rates of 10-35% in rare diseases. In this review, we provide an overview of the methods used for RNA sequencing and illustrate how these can improve the diagnostic yield of rare diseases.

Variable Expressivity of the Beckwith-Wiedemann Syndrome in Four Pedigrees Segregating Loss-of-Function Variants of CDKN1C

Beckwith-Wiedemann syndrome (BWS) is an imprinting disorder characterized by prenatal and/or postnatal overgrowth, organomegaly, abdominal wall defects and tumor predisposition. CDKN1C is a maternally expressed gene of the 11p15.5 chromosomal region and is regulated by the imprinting control region IC2. It negatively controls cellular proliferation, and its expression or activity are frequently reduced in BWS. In particular, loss of IC2 methylation is associated with CDKN1C silencing in the majority of sporadic BWS cases, and maternally inherited loss-of-function variants of CDKN1C are the most frequent molecular defects of familial BWS. We have identified, using Sanger sequencing, novel CDKN1C variants in three families with recurrent cases of BWS, and a previously reported variant in a woman with recurrent miscarriages with exomphalos. Clinical evaluation of the patients showed variable manifestation of the disease. The frameshift and nonsense variants were consistently associated with exomphalos, while the missense variant caused a less severe phenotype. Pregnancy loss and perinatal lethality were found in the families segregating nonsense mutations. Intrafamilial variability of the clinical BWS features was observed, even between siblings. Our data are indicative of severe BWS phenotypes that, with variable expressivity, may be associated with both frameshift and nonsense variants of CDKN1C.

Exons as units of phenotypic impact for truncating mutations in autism

Autism spectrum disorders (ASD) are a group of related neurodevelopmental diseases displaying significant genetic and phenotypic heterogeneity. Despite recent progress in understanding ASD genetics, the nature of phenotypic heterogeneity across probands remains unclear. Notably, likely gene-disrupting (LGD) de novo mutations affecting the same gene often result in substantially different ASD phenotypes. Nevertheless, we find that truncating mutations affecting the same exon frequently lead to strikingly similar intellectual phenotypes in unrelated ASD probands. Analogous patterns are observed for two independent proband cohorts and several other important ASD-associated phenotypes. We find that exons biased toward prenatal and postnatal expression preferentially contribute to ASD cases with lower and higher IQ phenotypes, respectively. These results suggest that exons, rather than genes, often represent a unit of effective phenotypic impact for truncating mutations in autism. The observed phenotypic patterns are likely mediated by nonsense-mediated decay (NMD) of splicing isoforms, with autism phenotypes usually triggered by relatively mild (15-30%) decreases in overall gene dosage. We find that each ASD gene with recurrent mutations can be characterized by a parameter, phenotype dosage sensitivity (PDS), which quantifies the relationship between changes in a gene's dosage and changes in a given disease phenotype. We further demonstrate analogous relationships between exon LGDs and gene expression changes in multiple human tissues. Therefore, similar phenotypic patterns may be also observed in other human genetic disorders.

Loss of MANF Causes Childhood-Onset Syndromic Diabetes Due to Increased Endoplasmic Reticulum Stress

Mesencephalic astrocyte-derived neurotrophic factor (MANF) is an endoplasmic reticulum (ER)-resident protein that plays a crucial role in attenuating ER stress responses. Although MANF is indispensable for the survival and function of mouse β-cells, its precise role in human β-cell development and function is unknown. In this study, we show that lack of MANF in humans results in diabetes due to increased ER stress, leading to impaired β-cell function. We identified two patients from different families with childhood diabetes and a neurodevelopmental disorder associated with homozygous loss-of-function mutations in the MANF gene. To study the role of MANF in human β-cell development and function, we knocked out the MANF gene in human embryonic stem cells and differentiated them into pancreatic endocrine cells. Loss of MANF induced mild ER stress and impaired insulin-processing capacity of β-cells in vitro. Upon implantation to immunocompromised mice, the MANF knockout grafts presented elevated ER stress and functional failure, particularly in recipients with diabetes. By describing a new form of monogenic neurodevelopmental diabetes syndrome caused by disturbed ER function, we highlight the importance of adequate ER stress regulation for proper human β-cell function and demonstrate the crucial role of MANF in this process.

Survival Analysis on Rare Events Using Group-Regularized Multi-Response Cox Regression

MOTIVATION

The prediction performance of Cox proportional hazard model suffers when there are only few uncensored events in the training data.

RESULTS

We propose a Sparse-Group regularized Cox regression method to improve the prediction performance of large-scale and high-dimensional survival data with few observed events. Our approach is applicable when there is one or more other survival responses that 1. has a large number of observed events; 2. share a common set of associated predictors with the rare event response. This scenario is common in the UK Biobank (Sudlow et al., 2015) dataset where records for a large number of common and less prevalent diseases of the same set of individuals are available. By analyzing these responses together, we hope to achieve higher prediction performance than when they are analyzed individually. To make this approach practical for large-scale data, we developed an accelerated proximal gradient optimization algorithm as well as a screening procedure inspired by Qian et al. (2020).

AVAILABILITY

https://github.com/rivas-lab/multisnpnet-Cox.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Whole exome sequencing analyses reveal gene-microbiota interactions in the context of IBD

OBJECTIVE

Both the gut microbiome and host genetics are known to play significant roles in the pathogenesis of IBD. However, the interaction between these two factors and its implications in the aetiology of IBD remain underexplored. Here, we report on the influence of host genetics on the gut microbiome in IBD.

DESIGN

To evaluate the impact of host genetics on the gut microbiota of patients with IBD, we combined whole exome sequencing of the host genome and whole genome shotgun sequencing of 1464 faecal samples from 525 patients with IBD and 939 population-based controls. We followed a four-step analysis: (1) exome-wide microbial quantitative trait loci (mbQTL) analyses, (2) a targeted approach focusing on IBD-associated genomic regions and protein truncating variants (PTVs, minor allele frequency (MAF) >5%), (3) gene-based burden tests on PTVs with MAF <5% and exome copy number variations (CNVs) with site frequency <1%, (4) joint analysis of both cohorts to identify the interactions between disease and host genetics.

RESULTS

We identified 12 mbQTLs, including variants in the IBD-associated genes IL17REL, MYRF, SEC16A and WDR78. For example, the decrease of the pathway acetyl-coenzyme A biosynthesis, which is involved in short chain fatty acids production, was associated with variants in the gene MYRF (false discovery rate <0.05). Changes in functional pathways involved in the metabolic potential were also observed in participants carrying rare PTVs or CNVs in CYP2D6, GPR151 and CD160 genes. These genes are known for their function in the immune system. Moreover, interaction analyses confirmed previously known IBD disease-specific mbQTLs in TNFSF15.

CONCLUSION

This study highlights that both common and rare genetic variants affecting the immune system are key factors in shaping the gut microbiota in the context of IBD and pinpoints towards potential mechanisms for disease treatment.

Pathogenic Variants in the Myosin Chaperone UNC-45B Cause Progressive Myopathy with Eccentric Cores

The myosin-directed chaperone UNC-45B is essential for sarcomeric organization and muscle function from Caenorhabditis elegans to humans. The pathological impact of UNC-45B in muscle disease remained elusive. We report ten individuals with bi-allelic variants in UNC45B who exhibit childhood-onset progressive muscle weakness. We identified a common UNC45B variant that acts as a complex hypomorph splice variant. Purified UNC-45B mutants showed changes in folding and solubility. In situ localization studies further demonstrated reduced expression of mutant UNC-45B in muscle combined with abnormal localization away from the A-band towards the Z-disk of the sarcomere. The physiological relevance of these observations was investigated in C. elegans by transgenic expression of conserved UNC-45 missense variants, which showed impaired myosin binding for one and defective muscle function for three. Together, our results demonstrate that UNC-45B impairment manifests as a chaperonopathy with progressive muscle pathology, which discovers the previously unknown conserved role of UNC-45B in myofibrillar organization.

Mutations primarily alter the inclusion of alternatively spliced exons

Genetic analyses and systematic mutagenesis have revealed that synonymous, non-synonymous and intronic mutations frequently alter the inclusion levels of alternatively spliced exons, consistent with the concept that altered splicing might be a common mechanism by which mutations cause disease. However, most exons expressed in any cell are highly-included in mature mRNAs. Here, by performing deep mutagenesis of highly-included exons and by analysing the association between genome sequence variation and exon inclusion across the transcriptome, we report that mutations only very rarely alter the inclusion of highly-included exons. This is true for both exonic and intronic mutations as well as for perturbations in trans. Therefore, mutations that affect splicing are not evenly distributed across primary transcripts but are focussed in and around alternatively spliced exons with intermediate inclusion levels. These results provide a resource for prioritising synonymous and other variants as disease-causing mutations.

Evaluation of both exonic and intronic variants for effects on RNA splicing allows for accurate assessment of the effectiveness of precision therapies

Elucidating the functional consequence of molecular defects underlying genetic diseases enables appropriate design of therapeutic options. Treatment of cystic fibrosis (CF) is an exemplar of this paradigm as the development of CFTR modulator therapies has allowed for targeted and effective treatment of individuals harboring specific genetic variants. However, the mechanism of these drugs limits effectiveness to particular classes of variants that allow production of CFTR protein. Thus, assessment of the molecular mechanism of individual variants is imperative for proper assignment of these precision therapies. This is particularly important when considering variants that affect pre-mRNA splicing, thus limiting success of the existing protein-targeted therapies. Variants affecting splicing can occur throughout exons and introns and the complexity of the process of splicing lends itself to a variety of outcomes, both at the RNA and protein levels, further complicating assessment of disease liability and modulator response. To investigate the scope of this challenge, we evaluated splicing and downstream effects of 52 naturally occurring CFTR variants (exonic = 15, intronic = 37). Expression of constructs containing select CFTR intronic sequences and complete CFTR exonic sequences in cell line models allowed for assessment of RNA and protein-level effects on an allele by allele basis. Characterization of primary nasal epithelial cells obtained from individuals harboring splice variants corroborated in vitro data. Notably, we identified exonic variants that result in complete missplicing and thus a lack of modulator response (e.g. c.2908G>A, c.523A>G), as well as intronic variants that respond to modulators due to the presence of residual normally spliced transcript (e.g. c.4242+2T>C, c.3717+40A>G). Overall, our data reveals diverse molecular outcomes amongst both exonic and intronic variants emphasizing the need to delineate RNA, protein, and functional effects of each variant in order to accurately assign precision therapies.

Genetic variants that impact pre-mRNA splicing are a common cause of genetic disease and have varying downstream molecular consequences. As a result, precision therapies that function at the protein level are not always effective for these variants and thus careful assessment is necessary. Here we evaluate RNA-level effects of 52 variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene and show that study of splicing and its consequences allows for more accurate assignment of precision therapies.

Tolerance to Selenoprotein Loss Differs between Human and Mouse

Mouse has emerged as the most common model organism in biomedicine. Here, we analyzed the tolerance to the loss-of-function (LoF) of selenoprotein genes, estimated from mouse knockouts and the frequency of LoF variants in humans. We found not only a general correspondence in tolerance (e.g., GPX1, GPX2) and intolerance (TXNRD1, SELENOT) to gene LoF between humans and mice but also important differences. Notably, humans are intolerant to the loss of iodothyronine deiodinases, whereas their deletion in mice leads to mild phenotypes, and this is consistent with phenotype differences in selenocysteine machinery loss between these species. In contrast, loss of TXNRD2 and GPX4 is lethal in mice but may be tolerated in humans. We further identified the first human SELENOP variants coding for proteins varying in selenocysteine content. Finally, our analyses suggested that premature termination codons in selenoprotein genes trigger nonsense-mediated decay, but do this inefficiently when UGA codon is gained. Overall, our study highlights differences in the physiological importance of selenoproteins between human and mouse.

A polyclonal allelic expression assay for detecting regulatory effects of transcript variants

We present an assay to experimentally test the regulatory effects of genetic variants within transcripts using CRISPR/Cas9 followed by targeted sequencing. We applied the assay to 32 premature stop-gained variants across the genome and in two Mendelian disease genes, 33 putative causal variants of eQTLs, and 62 control variants in HEK293T cells, replicating a subset of variants in HeLa cells. We detected significant effects in the expected direction (in 60% of variants), demonstrating the ability of the assay to capture regulatory effects of eQTL variants and nonsense-mediated decay triggered by premature stop-gained variants. The results suggest a utility for validating transcript-level effects of genetic variants.

A vast resource of allelic expression data spanning human tissues

Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

The NEMP family supports metazoan fertility and nuclear envelope stiffness

Human genome-wide association studies have linked single-nucleotide polymorphisms (SNPs) in NEMP1 (nuclear envelope membrane protein 1) with early menopause; however, it is unclear whether NEMP1 has any role in fertility. We show that whole-animal loss of NEMP1 homologs in Drosophila, Caenorhabditis elegans, zebrafish, and mice leads to sterility or early loss of fertility. Loss of Nemp leads to nuclear shaping defects, most prominently in the germ line. Biochemical, biophysical, and genetic studies reveal that NEMP proteins support the mechanical stiffness of the germline nuclear envelope via formation of a NEMP-EMERIN complex. These data indicate that the germline nuclear envelope has specialized mechanical properties and that NEMP proteins play essential and conserved roles in fertility.

Functional annotation of rare structural variation in the human brain

Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge. Here, we integrate SVs with RNA-sequencing from human post-mortem brains to quantify their dosage and regulatory effects. We show that genic and regulatory SVs exist at significantly lower frequencies than intergenic SVs. Functional impact of copy number variants (CNVs) stems from both the proportion of genic and regulatory content altered and loss-of-function intolerance of the gene. We train a linear model to predict expression effects of rare CNVs and use it to annotate regulatory disruption of CNVs from 14,891 independent genome-sequenced individuals. Pathogenic deletions implicated in neurodevelopmental disorders show significantly more extreme regulatory disruption scores and if rank ordered would be prioritized higher than using frequency or length alone. This work shows the deleteriousness of regulatory SVs, particularly those altering CTCF sites and provides a simple approach for functionally annotating the regulatory consequences of CNVs.