A systematic survey of loss-of-function variants in human protein-coding genes

Evaluating variant pathogenicity prediction tools to establish African inclusive guidelines for germline genetic testing

BACKGROUND

Genetic germline testing is restricted for African patients. Lack of ancestrally relevant genomic data perpetuated by African diversity has resulted in European-biased curated clinical variant databases and pathogenic prediction guidelines. While numerous variant pathogenicity prediction tools (VPPTs) exist, their performance has yet to be established within the context of African diversity.

METHODS

To address this limitation, we assessed 54 VPPTs for predictive performance (sensitivity, specificity, false positive and negative rates) across 145,291 known pathogenic or benign variants derived from 50 Southern African and 50 European men matched for advanced prostate cancer. Prioritising VPPTs for optimal ancestral performance, we screened 5.3 million variants of unknown significance for predicted functional and oncogenic potential.

RESULTS

We observe a 2.1- and 4.1-fold increase in the number of known and predicted rare pathogenic or benign variants, respectively, against a 1.6-fold decrease in the number of available interrogated variants in our European over African data. Although sensitivity was significantly lower for our African data overall (0.66 vs 0.71, p = 9.86E-06), MetaSVM, CADD, Eigen-raw, BayesDel-noAF, phyloP100way-vertebrate and MVP outperformed irrespective of ancestry. Conversely, MutationTaster, DANN, LRT and GERP-RS were African-specific top performers, while MutationAssessor, PROVEAN, LIST-S2 and REVEL are European-specific. Using these pathogenic prediction workflows, we narrow the ancestral gap for potentially deleterious and oncogenic variant prediction in favour of our African data by 1.15- and 1.1-fold, respectively.

CONCLUSION

Although VPPT sensitivity favours European data, our findings provide guidelines for VPPT selection to maximise rare pathogenic variant prediction for African disease studies.

Analysis of canine gene constraint identifies new variants for orofacial clefts and stature

Dog breeding promotes within-group homogeneity through conformation to strict breed standards, while simultaneously driving between-group heterogeneity. There are over 350 recognized dog breeds that provide the foundation for investigating the genetic basis of phenotypic diversity. Typically, breed standard phenotypes such as stature, pelage, and craniofacial structure are analyzed through genetic association studies. However, such analyses are limited to assayed phenotypes only, leaving difficult-to-measure phenotypic subtleties easily overlooked. We investigated coding variation from over 2000 dogs, leading to discoveries of variants related to craniofacial morphology and stature. Breed-enriched variants were prioritized according to gene constraint, which was calculated using a mutation model derived from trinucleotide substitution probabilities. Among the newly found variants is a splice-acceptor variant in PDGFRA associated with bifid nose, a characteristic trait of Çatalburun dogs, implicating the gene's role in midline closure. Two additional LCORL variants, both associated with canine body size are also discovered: a frameshift that causes a premature stop in large breeds (>25 kg) and an intronic substitution found in small breeds (<10 kg), thus highlighting the importance of allelic heterogeneity in selection for breed traits. Most variants prioritized in this analysis are not associated with genomic signatures for breed differentiation, as these regions are enriched for constrained genes intolerant to nonsynonymous variation. This indicates trait selection in dogs is likely a balancing act between preserving essential gene functions and maximizing regulatory variation to drive phenotypic extremes.

Unraveling the hidden complexity of cancer through long-read sequencing

Cancer is fundamentally a disease of the genome, characterized by extensive genomic, transcriptomic, and epigenomic alterations. Most current studies predominantly use short-read sequencing, gene panels, or microarrays to explore these alterations; however, these technologies can systematically miss or misrepresent certain types of alterations, especially structural variants, complex rearrangements, and alterations within repetitive regions. Long-read sequencing is rapidly emerging as a transformative technology for cancer research by providing a comprehensive view across the genome, transcriptome, and epigenome, including the ability to detect alterations that previous technologies have overlooked. In this Perspective, we explore the current applications of long-read sequencing for both germline and somatic cancer analysis. We provide an overview of the computational methodologies tailored to long-read data and highlight key discoveries and resources within cancer genomics that were previously inaccessible with prior technologies. We also address future opportunities and persistent challenges, including the experimental and computational requirements needed to scale to larger sample sizes, the hurdles in sequencing and analyzing complex cancer genomes, and opportunities for leveraging machine learning and artificial intelligence technologies for cancer informatics. We further discuss how the telomere-to-telomere genome and the emerging human pangenome could enhance the resolution of cancer genome analysis, potentially revolutionizing early detection and disease monitoring in patients. Finally, we outline strategies for transitioning long-read sequencing from research applications to routine clinical practice.

Benchmark of computational methods to detect digenism in sequencing data

Digenic inheritance is characterized by the combined alteration of two different genes leading to a disease. It could explain the etiology of many currently undiagnosed rare diseases. With the advent of next-generation sequencing technologies, the identification of digenic inheritance patterns has become more technically feasible, yet still poses significant challenges without any gold standard method. Here, we present a comprehensive overview of the existing methods developed to detect digenic inheritance in sequencing data and provide a classification in cohort-based and individual-based methods. The latter category of methods appeared the most applicable to rare diseases, especially the ones not needing patient phenotypic description as input. We discuss the availability of the different methods, their output and scalability to inform potential users. Focusing on methods to detect digenic inheritance in the case of very rare or heterogeneous diseases, we propose a benchmark using different real-life scenarios involving known digenic and putative neutral pairs of genes. Among these different methods, DiGePred stood out as the one giving the least number of false positives, ARBOCK as giving the greatest number of true positives, and DIEP as having the best balance between both. By synthesizing the state-of-the-art techniques and providing insights into their practical utility, this benchmark serves as a valuable resource for researchers and clinicians in selecting suitable methodologies for detecting digenic inheritance in a wide range of disorders using sequencing data.

Decoding Immunobiology Through Genetic Errors of Immunity

Throughout biology, the pursuit of genotype-phenotype relationships has provided foundational knowledge upon which new concepts and hypotheses are built. Genetic perturbation, whether occurring naturally or in experimental settings, is the mainstay of mechanistic dissection in biological systems. The unbiased discovery of causal genetic lesions via forward genetics in patients who have a rare disease elucidates a particularly impactful set of genotype-phenotype relationships. Here, we review the field of genetic errors of immunity, often termed inborn errors of immunity (IEIs), in a framework aimed at highlighting the powerful real-world immunology insights provided collectively and individually by these (approximately) 500 disorders. By conceptualizing essential immune functions in a model of the adaptive arsenal of rapid defenses, we organize IEIs based on immune circuits in which sensors, relays, and executioners cooperate to carry out pathogen clearance functions in an effective yet regulated manner. We review and discuss findings from IEIs that not only reinforce known immunology concepts but also offer surprising phenotypes, prompting an opportunity to refine our understanding of immune system function.

Reduced Penetrance is Common Among Predicted Loss-of-Function Variants and is Likely Driven by Residual Allelic Activity

Loss-of-function genetic variants (LoFs) often result in severe phenotypes, including autosomal dominant diseases driven by haploinsufficiency. Due to low carrier frequencies, their penetrance is generally unknown but typically variable. Here, we investigate the penetrance of >6,000 predicted LoFs (pLoFs) linked to 91 haploinsufficient diseases using a cohort of ≈24,000 carriers with linked electronic health record data. We find evidence for widespread reduced penetrance, which persisted after accounting for variant annotation artifacts, missed diagnoses, and incomplete clinical data. We thus hypothesized that many pLoFs have incomplete penetrance, which may be driven by residual allelic activity. To test this, we trained machine learning models to predict pLoF penetrance using variant-specific genomic features that may correlate with incomplete loss-of-function. The models were predictive of pLoF penetrance across a range of diseases and variant types, including those with prior clinical evidence for pathogenicity. This suggests that many pLoFs have incomplete penetrance due to residual allelic activity, complicating disease prognostication in asymptomatic carriers.

Functionally constrained human proteins are less prone to mutational instability from single amino acid substitutions

Missense mutations that disrupt protein structural stability are a common pathogenic mechanism in human genetic disease. Here, we quantify potential disruption of protein stability due to amino acid substitution and show that functionally constrained proteins are less susceptible to large mutational changes in stability. Mechanistically, this relates to greater intrinsic disorder among constrained proteins and to increased B-factors in the ordered regions of constrained proteins. This phenomenon means that constrained proteins exhibit smaller stability effects due to missense mutations, and partly explains why overtransmission of pathogenic missense variation is less prevalent in genetic disorders characterised by protein truncations. We show that the most functionally constrained proteins are depleted of both destabilising and overly-stabilising amino acid variation in disease-free populations. Despite this, amino acid substitutions with large stability effects in functionally constrained proteins are still highly prevalent among pathogenic human genetic variation. Importantly, we observe that there are approximately five times more missense variants with large stability effects than there are unambiguous loss-of-function mutations. Missense variants with disruption of stability effects recapitulate the per-gene patterns of functional constraint observed with protein truncating loss-of-function variation, yet their relative abundance abrogates difficulties encountered when estimating functional constraint for the shortest human genes.

Identification of nonsense-mediated decay inhibitors that alter the tumor immune landscape

Despite exciting developments in cancer immunotherapy, its broad application is limited by the paucity of targetable antigens on the tumor cell surface. As an intrinsic cellular pathway, nonsense-mediated decay (NMD) conceals neoantigens through the destruction of the RNA products from genes harboring truncating mutations. We developed and conducted a high-throughput screen, based on the ratiometric analysis of transcripts, to identify critical mediators of NMD in human cells. This screen implicated disruption of kinase SMG1's phosphorylation of UPF1 as a potential disruptor of NMD. This led us to design a novel SMG1 inhibitor, KVS0001, that elevates the expression of transcripts and proteins resulting from human and murine truncating mutations in vitro and murine cells in vivo. Most importantly, KVS0001 concomitantly increased the presentation of immune-targetable human leukocyte antigens (HLA) class I-associated peptides from NMD-downregulated proteins on the surface of human cancer cells. KVS0001 provides new opportunities for studying NMD and the diseases in which NMD plays a role, including cancer and inherited diseases.

Population Genomics of Premature Termination Codons in Cavefish With Substantial Trait Loss

Loss-of-function alleles are a pertinent source of genetic variation with the potential to contribute to adaptation. Cave-adapted organisms exhibit striking loss of ancestral traits such as eyes and pigment, suggesting that loss-of-function alleles may play an outsized role in these systems. Here, we leverage 141 whole genome sequences to evaluate the evolutionary history and adaptive potential of single nucleotide premature termination codons (PTCs) in Mexican tetra. We find that cave populations contain significantly more PTCs at high frequency than surface populations. We also find that PTCs occur more frequently in genes with inherent relaxed evolutionary constraint relative to the rest of the genome. Using SLiM to simulate PTC evolution in a cavefish population, we show that the smaller population size and increased genetic drift is sufficient to account for the observed increase in PTC frequency in cave populations without positive selection. Using CRISPR-Cas9, we show that mutation of one of these genes, pde6c, produces phenotypes in surface Mexican tetra that mimic cave-derived traits. Finally, we identify a small subset of candidate genes that contain high-frequency PTCs in cave populations, occur within selective sweeps, and may contribute to beneficial traits such as reduced energy expenditure, suggesting that a handful of PTCs may be adaptive. Overall, our work provides a rare characterization of PTCs across wild populations and finds that they may have an important role in loss-of-function phenotypes, contributing to a growing body of literature showing genome evolution through relaxed constraint in subterranean organisms.

Insights into eye genetics and recent advances in ocular gene therapy

The rapid advancements in the field of genetics have significantly propelled the development of gene therapies, paving the way for innovative treatments of various hereditary disorders. This review focuses on the genetics of ophthalmologic conditions, highlighting the currently approved ophthalmic gene therapy and exploring emerging therapeutic strategies under development. Inherited retinal dystrophies represent a heterogeneous group of genetic disorders that manifest across a broad spectrum from infancy to late middle age. Key clinical features include nyctalopia (night blindness), constriction of the visual field, impairments in color perception, reduced central visual acuity, and rapid eye movements. Recent technological advancements, such as multimodal imaging, psychophysical assessments, and electrophysiological testing, have greatly enhanced our ability to understand disease progression and establish genotype-phenotype correlations. Additionally, the integration of molecular diagnostics into clinical practice is revolutionizing patient stratification and the design of targeted interventions, underscoring the transformative potential of personalized medicine in ophthalmology. The review also covers the challenges and opportunities in developing gene therapies for other ophthalmic conditions, such as age-related macular degeneration and optic neuropathies. We discuss the viral and non-viral vector systems used in ocular gene therapy, highlighting their advantages and limitations. Additionally, we explore the potential of emerging technologies like CRISPR/Cas9 in treating genetic eye diseases. We briefly address the regulatory landscape, concerns, challenges, and future directions of gene therapy in ophthalmology. We emphasize the need for long-term safety and efficacy data as these innovative treatments move from bench to bedside.

Exome sequencing of UK birth cohorts

Birth cohort studies involve repeated surveys of large numbers of individuals from birth and throughout their lives. They collect information useful for a wide range of life course research domains, and biological samples which can be used to derive data from an increasing collection of omic technologies. This rich source of longitudinal data, when combined with genomic data, offers the scientific community valuable insights ranging from population genetics to applications across the social sciences. Here we present quality-controlled whole exome sequencing data from three UK birth cohorts: the Avon Longitudinal Study of Parents and Children (8,436 children and 3,215 parents), the Millenium Cohort Study (7,667 children and 6,925 parents) and Born in Bradford (8,784 children and 2,875 parents). The overall objective of this coordinated effort is to make the resulting high-quality data widely accessible to the global research community in a timely manner. We describe how the datasets were generated and subjected to quality control at the sample, variant and genotype level. We then present some preliminary analyses to illustrate the quality of the datasets and probe potential sources of bias. We introduce measures of ultra-rare variant burden to the variables available for researchers working on these cohorts, and show that the exome-wide burden of deleterious protein-truncating variants, S het burden, is associated with educational attainment and cognitive test scores. The whole exome sequence data from these birth cohorts (CRAM & VCF files) are available through the European Genome-Phenome Archive, and here we provide guidance for their use.

Biochemistry and genetics are coming together to improve our understanding of genotype to phenotype relationships

Since genome sequencing became accessible, determining how specific differences in genotypes lead to complex phenotypes such as disease has become one of the key goals in biomedicine. Predicting effects of sequence variants on cellular or organismal phenotype faces several challenges. First, variants simultaneously affect multiple protein properties and predicting their combined effect is complex. Second, effects of changes in a single protein propagate through the cellular network, which we only partially understand. In this review, we emphasize the importance of both biochemistry and genetics in addressing these challenges. Moreover, we highlight work that blurs the distinction between biochemistry and genetics fields to provide new insights into the genotype-to-phenotype relationships.

Research participants' perspectives regarding the feedback of secondary findings-A cohort from the DDD-Africa study, South Africa

Genomic researchers face an ethical dilemma regarding feedback of individual results generated from genomic studies. In the African setting, genomic research is still not widely implemented and, coupled with this, the limited African-specific guidelines on how to feedback on individual research findings. A qualitative study was performed to assess participants' expectations and preferences regarding the feedback of secondary findings from genomic research. Participants were parents of children with a developmental disorder, enrolled in the Deciphering Developmental Disorders in Africa (DDD-Africa) research project, and were purposefully selected. Three deliberative focus group discussions were conducted with 14 participants. Each deliberative focus group consisted of two separate audio-recorded interviews and presented different case scenarios for different types of secondary findings that could be theoretically detected during genomic research. We aimed to explore participants' preferences for the extent, nature, timing, and methods for receiving individual study results, specifically pertaining to secondary findings. Thematic content analysis was done, with a deductive approach to coding. Four themes emerged which included participants' perception of readiness to receive secondary findings, queries raised around who has access to research findings and feedback of findings consent, responsibilities of the researcher, and reasons for not wanting/wanting secondary findings. Overall, participants expressed that they want to receive feedback on secondary findings irrespective of disease severity and treatment availability. Lifestyle changes, early prevention or treatment, impact on future generations, and preparedness were strong motivations for wanting feedback on results. Participants felt that when the research involved minors, it was the parents' right to receive results on behalf of their children. This study provides new insights into participants' preferences around feedback on genomic research results and could serve as an important basis for creating guidelines and recommendations for feedback on genomic results in the African context.

High-coverage nanopore sequencing of samples from the 1000 Genomes Project to build a comprehensive catalog of human genetic variation

Fewer than half of individuals with a suspected Mendelian or monogenic condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control data sets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project (1KGP) Oxford Nanopore Technologies Sequencing Consortium aims to generate LRS data from at least 800 of the 1KGP samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37× and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.

Systematic analysis of nonsense variants uncovers peptide release rate as a novel modifier of nonsense-mediated mRNA decay

Nonsense variants underlie many genetic diseases. The phenotypic impact of nonsense variants is determined by nonsense-mediated mRNA decay (NMD), which degrades transcripts with premature termination codons (PTCs). Despite its clinical importance, the factors controlling transcript-specific and context-dependent variation in NMD activity remain poorly understood. Through analysis of human genetic datasets, we discovered that the amino acid preceding the PTC strongly influences NMD activity. Notably, glycine codons promote robust NMD efficiency and show striking enrichment before PTCs but depletion before normal termination codons (NTCs). This glycine-PTC enrichment is particularly pronounced in genes tolerant to loss-of-function variants, suggesting evolutionary selection or neutrality conferred by efficient elimination of truncated proteins from non-essential genes. Using biochemical assays and massively parallel reporter analysis, we demonstrated that the peptide release rate during translation termination varies substantially with the identity of the preceding amino acid and serves as the primary determinant of NMD activity. We propose a "window of opportunity" model where translation termination kinetics modulate NMD efficiency. By revealing how sequence context shapes NMD activity through translation termination dynamics, our findings provide a mechanistic framework for improved clinical interpretation of nonsense variants.

A spectrum of nonsense-mediated mRNA decay efficiency along the degree of mutational constraint

Despite its importance for regulating gene expression, nonsense-mediated mRNA decay (NMD) remains poorly understood. Here, we extend the findings of a previous landmark study that proposed several factors associated with NMD efficiency using matched genome and transcriptome data from The Cancer Genome Atlas Program (TCGA) by incorporating additional data including Genotype-Tissue Expression (GTEx), gnomAD, and metrics for mutational constraints. Factors affecting NMD efficiency are analyzed using an allele-specific expression (ASE)-based measure to reduce noise caused by random variations. Additionally, by combining our data with the updated allele frequency database of gnomAD, we demonstrate the spectrum of NMD efficiency according to the degree of gene-level mutational constraints (degree of a gene-tolerating loss-of-function variants). The NMD prediction model, trained on TCGA data, shows that gene-level mutational constraint is an important predictor of NMD efficiency. Findings of this study suggest the potential role of NMD on shaping the landscape of mutational constraints.

Loss of heterozygosity of CYP2D6 enhances the sensitivity of hepatocellular carcinomas to talazoparib

BACKGROUND

Loss of heterozygosity (LOH) diminishes genetic diversity within cancer genomes. A tumour arising in an individual heterozygous for a functional and a loss-of-function (LoF) allele of a gene occasionally retain only the LoF allele. This can result in deficiency of specific protein activities in cancer cells, creating unique differences between tumour cells and normal cells of the individual. Such differences may constitute vulnerabilities that can be exploited through allele-specific therapies.

METHODS

To discover frequently lost genes with prevalent LoF alleles, we mined the 1000 Genomes dataset for SNVs causing protein truncation through base substitution, indels or splice site disruptions, resulting in 60 LoF variants in 60 genes. From these, the variant rs3892097 in the liver enzyme CYP2D6 was selected because it is located within a genomic region that frequently undergoes LOH in several tumor types including hepatocellular cancers. To evaluate the relationship between CYP2D6 activity and the toxicities of anticancer agents, we screened 525 compounds currently in clinical use or undergoing clinical trials using cell model systems with or without CYP2D6 activity.

FINDINGS

We identified 12 compounds, AZD-3463, CYC-116, etoposide, everolimus, GDC-0349, lenvatinib, MK-8776, PHA-680632, talazoparib, tyrphostin 9, VX-702, and WZ-3146, using an engineered HEK293T cell model. Of these, talazoparib and MK-8776 demonstrated consistently heightened cytotoxic effects against cells with compromised CYP2D6 activity in engineered hepatocellular cancer cell models. Moreover, talazoparib displayed CYP2D6 genotype dependent effects on primary hepatocellular carcinoma organoids.

INTERPRETATION

Exploiting the loss of drug-metabolizing enzyme gene activity in tumor cells following loss of heterozygosity could present a promising therapeutic strategy for targeted cancer treatment.

FUNDING

This work was funded by Barncancerfonden (T.S, PR2022-0099 and PR2020-0171, X.Z, TJ2021-0111), Cancerfonden (T.S, 211719Pj and D.G, 222449Pj), Vetenskapsrådet (T.S, 2020-02371 and D.G, 2020-04707), and the Erling Persson Foundation (T.S, 2020-0037 and T.S, 2023-0113).

Extreme positive epistasis for fitness in monosomic yeast strains

The loss of a single chromosome in a diploid organism halves the dosage of many genes and is usually accompanied by a substantial decrease in fitness. We asked whether this decrease simply reflects the joint damage caused by individual gene dosage deficiencies. We measured the fitness effects of single heterozygous gene deletions in yeast and combined them for each chromosome. This predicted a negative growth rate, that is, lethality, for multiple monosomies. However, monosomic strains remained alive and grew as if much (often most) of the damage caused by single mutations had disappeared, revealing an exceptionally large and positive epistatic component of fitness. We looked for functional explanations by analyzing the transcriptomes. There was no evidence of increased (compensatory) gene expression on the monosomic chromosomes. Nor were there signs of the cellular stress response that would be expected if monosomy led to protein destabilization and thus cytotoxicity. Instead, all monosomic strains showed extensive upregulation of genes encoding ribosomal proteins, but in an indiscriminate manner that did not correspond to their altered dosage. This response did not restore the stoichiometry required for efficient biosynthesis, which probably became growth limiting, making all other mutation-induced metabolic defects much less important. In general, the modular structure of the cell leads to an effective fragmentation of the total mutational load. Defects outside the module(s) currently defining fitness lose at least some of their relevance, producing the epiphenomenon of positive interactions between individually negative effects.

The performance of AlphaMissense to identify genes influencing disease

A novel algorithm, AlphaMissense, has been shown to have an improved ability to predict the pathogenicity of rare missense genetic variants. However, it is not known whether AlphaMissense improves the ability of gene-based testing to identify disease-influencing genes. Using whole-exome sequencing data from the UK Biobank, we compared gene-based association analysis strategies including sets of deleterious variants: predicted loss-of-function (pLoF) variants only, pLoF plus AlphaMissense pathogenic variants, pLoF with missense variants predicted to be deleterious by any of five commonly utilized annotation methods (Missense (1/5)) or only variants predicted to be deleterious by all five methods (Missense (5/5)). We measured performance to identify 519 previously identified positive control genes, which can lead to Mendelian diseases, or are the targets of successfully developed medicines. These strategies identified 0.85 million pLoF variants and 5 million deleterious missense variants, including 22,131 likely pathogenic missense variants identified exclusively by AlphaMissense. The gene-based association tests found 608 significant gene associations (at p < 1.25 × 10-7) across 24 common traits and diseases. Compared with pLoFs plus Missense (5/5), tests using pLoFs and AlphaMissense variants found slightly more significant gene-disease and gene-trait associations, albeit with a marginally lower proportion of positive control genes. Nevertheless, their overall performance was similar. Merging AlphaMissense with Missense (5/5), whether through their intersection or union, did not yield any further enhancement in performance. In summary, employing AlphaMissense to select deleterious variants for gene-based testing did not improve the ability to identify genes that are known to influence disease.

MDVarP: modifier ~ disease-causing variant pairs predictor

BACKGROUND

Modifiers significantly impact disease phenotypes by modulating the effects of disease-causing variants, resulting in varying disease manifestations among individuals. However, identifying genetic interactions between modifier and disease-causing variants is challenging.

RESULTS

We developed MDVarP, an ensemble model comprising 1000 random forest predictors, to identify modifier ~ disease-causing variant combinations. MDVarP achieves high accuracy and precision, as verified using an independent dataset with published evidence of genetic interactions. We identified 25 novel modifier ~ disease-causing variant combinations and obtained supporting evidence for these associations. MDVarP outputs a class label ("Associated-pair" or "Nonrelevant-pair") and two prediction scores indicating the probability of a true association.

CONCLUSIONS

MDVarP prioritizes variant pairs associated with phenotypic modulations, enabling more effective mapping of functional contributions from disease-causing and modifier variants. This framework interprets genetic interactions underlying phenotypic variations in human diseases, with potential applications in personalized medicine and disease prevention.

Improving long-term kidney allograft survival by rethinking HLA compatibility: from molecular matching to non-HLA genes

Optimizing immunologic compatibility in organ transplantation extends beyond the conventional approach of Human Leukocyte Antigen (HLA) antigen matching, which exhibits significant limitations. A broader comprehension of the roles of classical and non-classical HLA genes in transplantation is imperative for enhancing long-term graft survival. High-resolution molecular HLA genotyping, despite its inherent challenges, has emerged as the cornerstone for precise patient-donor compatibility assessment. Leveraging understanding of eplet biology and indirect immune activation, eplet mismatch calculators and the PIRCHE-II algorithm surpass traditional methods in predicting allograft rejection. Understanding minor histocompatibility antigens may also present an opportunity to personalize the compatibility process. While the application of molecular matching in deceased donor organ allocation presents multiple technical, logistical, and conceptual barriers, rendering it premature for mainstream use, several other areas of donor-recipient matching and post-transplant management are ready to incorporate molecular matching. Provision of molecular mismatch scores to physicians during potential organ offer evaluations could potentially amplify long-term outcomes. The implementation of molecular matching in living organ donation and kidney paired exchange programs is similarly viable. This article will explore the current understanding of immunologic matching in transplantation and the potential applications of epitope and non-epitope molecular biology and genetics in clinical transplantation.

Genetics and Traumatic Brain Injury: Findings from an Exome-Based Study of a 50-Patient Case Series

Traumatic brain injury (TBI) is the leading cause of global mortality and morbidity. Because TBI is accident-related, the role of genetics in predisposing to TBI has been largely unexplored. However, the likelihood of injury may not be entirely random and may be associated with certain physical and mental characteristics. In this study, we analyzed the exomes of 50 patients undergoing rehabilitation after TBI. Patients were divided into three groups according to rehabilitation outcome: improvement, no change, and deterioration/death. We focused on rare, potentially functional missense and high-impact variants in genes intolerant to these variants. The concordant results from the three independent groups of patients allowed for the suggestion of the existence of a genetic predisposition to TBI, associated with rare functional variations in intolerant genes, with a prevalent dominant mode of inheritance and neurological manifestations in the genetic phenotypes according to the OMIM database. Forty-four of the 50 patients had one or more rare, potentially deleterious variants in one or more neurological genes. Comparison of these results with those of a 50-sampled matched non-TBI cohort revealed significant differences: P = 2.6 × 10-3, OR = 4.89 (1.77-13.47). There were no differences in the distribution of the genes of interest between the TBI patient groups. Our exploratory study provides new insights into the impact of genetics on TBI risk and is the first to address potential genetic susceptibility to TBI.

Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts

Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.

Identification of nonsense variants in the genomes of 15 Murciano-Granadina bucks and analysis of their segregation in parent-offspring trios

Nonsense variants can inactivate gene function by causing the synthesis of truncated proteins or by inducing nonsense mediated decay of messenger RNAs. The occurrence of such variants in the genomes of livestock species is modulated by multiple demographic and selective factors. Even though nonsense variants can have causal effects on embryo lethality, abortions, and disease, their genomic distribution and segregation in domestic goats have not been characterized in depth yet. In this work, we have sequenced the genomes of 15 Murciano-Granadina bucks with an average coverage of 32.92 × ± 1.45 × . Bioinformatic analysis revealed 947 nonsense variants consistently detected with SnpEff and Ensembl-VEP. These variants were especially abundant in the 3'end of the protein-coding regions. Genes related to olfactory perception, ATPase activity coupled to transmembrane movement of substances, defense to virus, hormonal response, and sensory perception of taste were particularly enriched in nonsense variants. Seventeen nonsense variants expected to have harmful effects on fitness were genotyped in parent-offspring trios. We observed that several nonsense variants predicted to be lethal based on mouse knockout data did not have such effect, a finding that could be explained by the existence of multiple mechanisms counteracting lethality. These findings demonstrate that predicting the effects of putative nonsense variants on fitness is extremely challenging. As a matter of fact, such a goal could only be achieved by generating a high quality telomere-to-telomere goat reference genome combined with carefully curated annotation and functional testing of promising candidate variants.

RNA variant assessment using transactivation and transdifferentiation

Understanding the impact of splicing and nonsense variants on RNA is crucial for the resolution of variant classification as well as their suitability for precision medicine interventions. This is primarily enabled through RNA studies involving transcriptomics followed by targeted assays using RNA isolated from clinically accessible tissues (CATs) such as blood or skin of affected individuals. Insufficient disease gene expression in CATs does however pose a major barrier to RNA based investigations, which we show is relevant to 1,436 Mendelian disease genes. We term these "silent" Mendelian genes (SMGs), the largest portion (36%) of which are associated with neurological disorders. We developed two approaches to induce SMG expression in human dermal fibroblasts (HDFs) to overcome this limitation, including CRISPR-activation-based gene transactivation and fibroblast-to-neuron transdifferentiation. Initial transactivation screens involving 40 SMGs stimulated our development of a highly multiplexed transactivation system culminating in the 6- to 90,000-fold induction of expression of 20/20 (100%) SMGs tested in HDFs. Transdifferentiation of HDFs directly to neurons led to expression of 193/516 (37.4%) of SMGs implicated in neurological disease. The magnitude and isoform diversity of SMG expression following either transactivation or transdifferentiation was comparable to clinically relevant tissues. We apply transdifferentiation and/or gene transactivation combined with short- and long-read RNA sequencing to investigate the impact that variants in USH2A, SCN1A, DMD, and PAK3 have on RNA using HDFs derived from affected individuals. Transactivation and transdifferentiation represent rapid, scalable functional genomic solutions to investigate variants impacting SMGs in the patient cell and genomic context.

Spatial enrichment and genomic analyses reveal the link of NOMO1 with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a severe motor neuron disease with uncertain genetic predisposition in most sporadic cases. The spatial architecture of cell types and gene expression are the basis of cell-cell interactions, biological function and disease pathology, but are not well investigated in the human motor cortex, a key ALS-relevant brain region. Recent studies indicated single nucleus transcriptomic features of motor neuron vulnerability in ALS motor cortex. However, the brain regional vulnerability of ALS-associated genes and the genetic link between region-specific genes and ALS risk remain largely unclear. Here, we developed an entropy-weighted differential gene expression matrix-based tool (SpatialE) to identify the spatial enrichment of gene sets in spatial transcriptomics. We benchmarked SpatialE against another enrichment tool (multimodal intersection analysis) using spatial transcriptomics data from both human and mouse brain tissues. To investigate regional vulnerability, we analysed three human motor cortex and two dorsolateral prefrontal cortex tissues for spatial enrichment of ALS-associated genes. We also used Cell2location to estimate the abundance of cell types in ALS-related cortex layers. To dissect the link of regionally expressed genes and ALS risk, we performed burden analyses of rare loss-of-function variants detected by whole-genome sequencing in ALS patients and controls, then analysed differential gene expression in the TargetALS RNA-sequencing dataset. SpatialE showed more accurate and specific spatial enrichment of regional cell type markers than multimodal intersection analysis in both mouse brain and human dorsolateral prefrontal cortex. Spatial transcriptomic analyses of human motor cortex showed heterogeneous cell types and spatial gene expression profiles. We found that 260 manually curated ALS-associated genes are significantly enriched in layer 5 of the motor cortex, with abundant expression of upper motor neurons and layer 5 excitatory neurons. Burden analyses of rare loss-of-function variants in Layer 5-associated genes nominated NOMO1 as a novel ALS-associated gene in a combined sample set of 6814 ALS patients and 3324 controls (P = 0.029). Gene expression analyses in CNS tissues revealed downregulation of NOMO1 in ALS, which is consistent with a loss-of-function disease mechanism. In conclusion, our integrated spatial transcriptomics and genomic analyses identified regional brain vulnerability in ALS and the association of a layer 5 gene (NOMO1) with ALS risk.

A single base pair duplication in the SLC33A1 gene is associated with fetal losses and neonatal lethality in Manech Tête Rousse dairy sheep

We recently discovered that the Manech Tête Rousse (MTR) deficient homozygous haplotype 2 (MTRDHH2) probably carries a recessive lethal mutation in sheep. In this study, we fine-mapped this region through whole-genome sequencing of five MTRDHH2 heterozygous carriers and 95 non-carriers from various ovine breeds. We identified a single base pair duplication within the SLC33A1 gene, leading to a frameshift mutation and a premature stop codon (p.Arg246Alafs*3). SLC33A1 encodes a transmembrane transporter of acetyl-coenzyme A that is crucial for cellular metabolism. To investigate the lethality of this mutation in homozygous MTR sheep, we performed at-risk matings using artificial insemination (AI) between heterozygous SLC33A1 variant carriers (SLC33A1_dupG). Pregnancy was confirmed 15 days post-AI using a blood test measuring interferon Tau-stimulated MX1 gene expression. Ultrasonography between 45 and 60 days post-AI revealed a 12% reduction in AI success compared with safe matings, indicating embryonic/fetal loss. This was supported by the MX1 differential expression test suggesting fetal losses between 15 and 60 days of gestation. We also observed a 34.7% pre-weaning mortality rate in 49 lambs born from at-risk matings. Homozygous SLC33A1_dupG lambs accounted for 47% of this mortality, with deaths occurring mostly within the first 5 days without visible clinical signs. Therefore, appropriate management of SLC33A1_dupG with an allele frequency of 0.04 in the MTR selection scheme would help increase overall fertility and lamb survival.

Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults

The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves' disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.

A Pilot Detection and Associate Study of Gene Presence-Absence Variation in Holstein Cattle

Presence-absence variations (PAVs) are important structural variations, wherein a genomic segment containing one or more genes is present in some individuals but absent in others. While PAVs have been extensively studied in plants, research in cattle remains limited. This study identified PAVs in 173 Holstein bulls using whole-genome sequencing data and assessed their associations with 46 economically important traits. Out of 28,772 cattle genes (from the longest transcripts), a total of 26,979 (93.77%) core genes were identified (present in all individuals), while variable genes included 928 softcore (present in 95-99% of individuals), 494 shell (present in 5-94%), and 371 cloud genes (present in <5%). Cloud genes were enriched in functions associated with hormonal and antimicrobial activities, while shell genes were enriched in immune functions. PAV-based genome-wide association studies identified associations between gene PAVs and 16 traits including milk, fat, and protein yields, as well as traits related to health and reproduction. Associations were found on multiple chromosomes, illustrating important associations on cattle chromosomes 7 and 15, involving olfactory receptor and immune-related genes, respectively. By examining the PAVs at the population level, the results of this research provided crucial insights into the genetic structures underlying the complex traits of Holstein cattle.

Identification of nonsense-mediated decay inhibitors that alter the tumor immune landscape

Despite exciting developments in cancer immunotherapy, its broad application is limited by the paucity of targetable antigens on the tumor cell surface. As an intrinsic cellular pathway, nonsense-mediated decay (NMD) conceals neoantigens through the destruction of the RNA products from genes harboring truncating mutations. We developed and conducted a high throughput screen, based on the ratiometric analysis of transcripts, to identify critical mediators of NMD. This screen implicated disruption of kinase SMG1's phosphorylation of UPF1 as a potential disruptor of NMD. This led us to design a novel SMG1 inhibitor, KVS0001, that elevates the expression of transcripts and proteins resulting from truncating mutations in vivo and in vitro . Most importantly, KVS0001 concomitantly increased the presentation of immune-targetable HLA class I-associated peptides from NMD-downregulated proteins on the surface of cancer cells. KVS0001 provides new opportunities for studying NMD and the diseases in which NMD plays a role, including cancer and inherited diseases.

One Sentence Summary

Disruption of the nonsense-mediated decay pathway with a newly developed SMG1 inhibitor with in-vivo activity increases the expression of T-cell targetable cancer neoantigens resulting from truncating mutations.

Genetic/epigenetic effects in NF1 microdeletion syndrome: beyond the haploinsufficiency, looking at the contribution of not deleted genes

NF1 microdeletion syndrome, accounting for 5-11% of NF1 patients, is caused by a deletion in the NF1 region and it is generally characterized by a severe phenotype. Although 70% of NF1 microdeletion patients presents the same 1.4 Mb type-I deletion, some patients may show additional clinical features. Therefore, the contribution of several pathogenic mechanisms, besides haploinsufficiency of some genes within the deletion interval, is expected and needs to be defined. We investigated an altered expression of deletion flanking genes by qPCR in patients with type-1 NF1 deletion, compared to healthy donors, possibly contributing to the clinical traits of NF1 microdeletion syndrome. In addition, the 1.4-Mb deletion leads to changes in the 3D chromatin structure in the 17q11.2 region. Specifically, this deletion alters DNA-DNA interactions in the regions flanking the breakpoints, as demonstrated by our 4C-seq analysis. This alteration likely causes position effect on the expression of deletion flanking genes.Interestingly, 4C-seq analysis revealed that in microdeletion patients, an interaction was established between the RHOT1 promoter and the SLC6A4 gene, which showed increased expression. We performed NGS on putative modifier genes, and identified two "likely pathogenic" rare variants in RAS pathway, possibly contributing to incidental phenotypic features.This study provides new insights into understanding the pathogenesis of NF1 microdeletion syndrome and suggests a novel pathomechanism that contributes to the expression phenotype in addition to haploinsufficiency of genes located within the deletion.This is a pivotal approach that can be applied to unravel microdeletion syndromes, improving precision medicine, prognosis and patients' follow-up.

Nonlethal deleterious mutation-induced stress accelerates bacterial aging

Random mutagenesis, including when it leads to loss of gene function, is a key mechanism enabling microorganisms' long-term adaptation to new environments. However, loss-of-function mutations are often deleterious, triggering, in turn, cellular stress and complex homeostatic stress responses, called "allostasis," to promote cell survival. Here, we characterize the differential impacts of 65 nonlethal, deleterious single-gene deletions on Escherichia coli growth in three different growth environments. Further assessments of select mutants, namely, those bearing single adenosine triphosphate (ATP) synthase subunit deletions, reveal that mutants display reorganized transcriptome profiles that reflect both the environment and the specific gene deletion. We also find that ATP synthase α-subunit deleted (ΔatpA) cells exhibit elevated metabolic rates while having slower growth compared to wild-type (wt) E. coli cells. At the single-cell level, compared to wt cells, individual ΔatpA cells display near normal proliferation profiles but enter a postreplicative state earlier and exhibit a distinct senescence phenotype. These results highlight the complex interplay between genomic diversity, adaptation, and stress response and uncover an "aging cost" to individual bacterial cells for maintaining population-level resilience to environmental and genetic stress; they also suggest potential bacteriostatic antibiotic targets and -as select human genetic diseases display highly similar phenotypes, - a bacterial origin of some human diseases.

Clustering of predicted loss-of-function variants in genes linked with monogenic disease can explain incomplete penetrance

BACKGROUND

Genetic variants that severely alter protein products (e.g. nonsense, frameshift) are often associated with disease. For some genes, these predicted loss-of-function variants (pLoFs) are observed throughout the gene, whilst in others, they occur only at specific locations. We hypothesised that, for genes linked with monogenic diseases that display incomplete penetrance, pLoF variants present in apparently unaffected individuals may be limited to regions where pLoFs are tolerated. To test this, we investigated whether pLoF location could explain instances of incomplete penetrance of variants expected to be pathogenic for Mendelian conditions.

METHODS

We used exome sequence data in 454,773 individuals in the UK Biobank (UKB) to investigate the locations of pLoFs in a population cohort. We counted numbers of unique pLoF, missense, and synonymous variants in UKB in each quintile of the coding sequence (CDS) of all protein-coding genes and clustered the variants using Gaussian mixture models. We limited the analyses to genes with ≥ 5 variants of each type (16,473 genes). We compared the locations of pLoFs in UKB with all theoretically possible pLoFs in a transcript, and pathogenic pLoFs from ClinVar, and performed simulations to estimate the false-positive rate of non-uniformly distributed variants.

RESULTS

For most genes, all variant classes fell into clusters representing broadly uniform variant distributions, but genes in which haploinsufficiency causes developmental disorders were less likely to have uniform pLoF distribution than other genes (P < 2.2 × 10-6). We identified a number of genes, including ARID1B and GATA6, where pLoF variants in the first quarter of the CDS were rescued by the presence of an alternative translation start site and should not be reported as pathogenic. For other genes, such as ODC1, pLoFs were located approximately uniformly across the gene, but pathogenic pLoFs were clustered only at the end, consistent with a gain-of-function disease mechanism.

CONCLUSIONS

Our results suggest the potential benefits of localised constraint metrics and that the location of pLoF variants should be considered when interpreting variants.

Putative protective genomic variation in the Lithuanian population

Genomic effect variants associated with survival and protection against complex diseases vary between populations due to microevolutionary processes. The aim of this study was to analyse diversity and distribution of effect variants in a context of potential positive selection. In total, 475 individuals of Lithuanian origin were genotyped using high-throughput scanning and/or sequencing technologies. Allele frequency analysis for the pre-selected effect variants was performed using the catalogue of single nucleotide polymorphisms. Comparison of the pre-selected effect variants with variants in primate species was carried out to ascertain which allele was derived and potentially of protective nature. Recent positive selection analysis was performed to verify this protective effect. Four variants having significantly different frequencies compared to European populations were identified while two other variants reached borderline significance. Effect variant in SLC30A8 gene may potentially protect against type 2 diabetes. The existing paradox of high rates of type 2 diabetes in the Lithuanian population and the relatively high frequencies of potentially protective genome variants against it indicate a lack of knowledge about the interactions between environmental factors, regulatory regions, and other genome variation. Identification of effect variants is a step towards better understanding of the microevolutionary processes, etiopathogenetic mechanisms, and personalised medicine.

A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites

Protein evolution is constrained by structure and function, creating patterns in residue conservation that are routinely exploited to predict structure and other features. Similar constraints should affect variation across individuals, but it is only with the growth of human population sequencing that this has been tested at scale. Now, human population constraint has established applications in pathogenicity prediction, but it has not yet been explored for structural inference. Here, we map 2.4 million population variants to 5885 protein families and quantify residue-level constraint with a new Missense Enrichment Score (MES). Analysis of 61,214 structures from the PDB spanning 3661 families shows that missense depleted sites are enriched in buried residues or those involved in small-molecule or protein binding. MES is complementary to evolutionary conservation and a combined analysis allows a new classification of residues according to a conservation plane. This approach finds functional residues that are evolutionarily diverse, which can be related to specificity, as well as family-wide conserved sites that are critical for folding or function. We also find a possible contrast between lethal and non-lethal pathogenic sites, and a surprising clinical variant hot spot at a subset of missense enriched positions.

Predicted genetic burden and frequency of phenotype-associated variants in the horse

Disease-causing variants have been identified for less than 20% of suspected equine genetic diseases. Whole genome sequencing (WGS) allows rapid identification of rare disease causal variants. However, interpreting the clinical variant consequence is confounded by the number of predicted deleterious variants that healthy individuals carry (predicted genetic burden). Estimation of the predicted genetic burden and baseline frequencies of known deleterious or phenotype associated variants within and across the major horse breeds have not been performed. We used WGS of 605 horses across 48 breeds to identify 32,818,945 variants, demonstrate a high predicted genetic burden (median 730 variants/horse, interquartile range: 613-829), show breed differences in predicted genetic burden across 12 target breeds, and estimate the high frequencies of some previously reported disease variants. This large-scale variant catalog for a major and highly athletic domestic animal species will enhance its ability to serve as a model for human phenotypes and improves our ability to discover the bases for important equine phenotypes.

Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

Dysregulation of mTOR signaling mediates common neurite and migration defects in both idiopathic and 16p11.2 deletion autism neural precursor cells

Autism spectrum disorder (ASD) is defined by common behavioral characteristics, raising the possibility of shared pathogenic mechanisms. Yet, vast clinical and etiological heterogeneity suggests personalized phenotypes. Surprisingly, our iPSC studies find that six individuals from two distinct ASD subtypes, idiopathic and 16p11.2 deletion, have common reductions in neural precursor cell (NPC) neurite outgrowth and migration even though whole genome sequencing demonstrates no genetic overlap between the datasets. To identify signaling differences that may contribute to these developmental defects, an unbiased phospho-(p)-proteome screen was performed. Surprisingly despite the genetic heterogeneity, hundreds of shared p-peptides were identified between autism subtypes including the mTOR pathway. mTOR signaling alterations were confirmed in all NPCs across both ASD subtypes, and mTOR modulation rescued ASD phenotypes and reproduced autism NPC-associated phenotypes in control NPCs. Thus, our studies demonstrate that genetically distinct ASD subtypes have common defects in neurite outgrowth and migration which are driven by the shared pathogenic mechanism of mTOR signaling dysregulation.

Emerging significance of butyrylcholinesterase

Butyrylcholinesterase (BChE; EC 3.1.1.8), an enzyme structurally related to acetylcholinesterase, is widely distributed in the human body. It plays a role in the detoxification of chemicals such as succinylcholine, a muscle relaxant used in anesthetic practice. BChE is well-known due to variant forms of the enzyme with little or no hydrolytic activity which exist in some endogamous communities and result in prolonged apnea following the administration of succinylcholine. Its other functions include the ability to hydrolyze acetylcholine, the cholinergic neurotransmitter in the brain, when its primary hydrolytic enzyme, acetylcholinesterase, is absent. To assess its potential roles, BChE was studied in relation to insulin resistance, type 2 diabetes mellitus, cognition, hepatic disorders, cardiovascular and cerebrovascular diseases, and inflammatory conditions. Individuals who lack the enzyme activity of BChE are otherwise healthy, until they are given drugs hydrolyzed by this enzyme. Therefore, BChE is a candidate for the study of loss-of-function mutations in humans. Studying individuals with variant forms of BChE can provide insights into whether they are protected against metabolic diseases. The potential utility of the enzyme as a biomarker for Alzheimer's disease and the response to its drug treatment can also be assessed.

Nanopore sequencing of 1000 Genomes Project samples to build a comprehensive catalog of human genetic variation

Less than half of individuals with a suspected Mendelian condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control datasets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project ONT Sequencing Consortium aims to generate LRS data from at least 800 of the 1000 Genomes Project samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37x and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.

Inherited non-FGF23-mediated phosphaturic disorders: A kidney-centric review

Phosphate is freely filtered by the glomerulus and reabsorbed exclusively in the proximal tubule by two key transporters, NaPiIIA and NaPiIIC, encoded by SLC34A1 and SLC34A3, respectively. Regulation of these transporters occurs primarily through the hormone FGF23 and, to a lesser degree, PTH. Consequently, inherited non-FGF23 mediated phosphaturic disorders are due to generalised proximal tubular dysfunction, loss-of-function variants in SLC34A1 or SLC34A3 or excess PTH signalling. The corresponding disorders are Renal Fanconi Syndrome, Infantile Hypercalcaemia type 2, Hereditary Hypophosphataemic Rickets with Hypercalciuria and Familial Hyperparathyroidism. Several inherited forms of Fanconi renotubular syndrome (FRTS) have also been described with the underlying genes encoding for GATM, EHHADH, HNF4A and NDUFAF6. Here, we will review their pathophysiology, clinical manifestations and the implications for treatment from a kidney-centric perspective, focussing on those disorders caused by dysfunction of renal phosphate transporters. Moreover, we will highlight specific genetic aspects, as the availability of large population genetic databases has raised doubts about some of the originally proposed gene-disease associations concerning phosphate transporters or their associated proteins.

Prioritising genetic findings for drug target identification and validation

The decreasing costs of high-throughput genetic sequencing and increasing abundance of sequenced genome data have paved the way for the use of genetic data in identifying and validating potential drug targets. However, the number of identified potential drug targets is often prohibitively large to experimentally evaluate in wet lab experiments, highlighting the need for systematic approaches for target prioritisation. In this review, we discuss principles of genetically guided drug development, specifically addressing loss-of-function analysis, colocalization and Mendelian randomisation (MR), and the contexts in which each may be most suitable. We subsequently present a range of biomedical resources which can be used to annotate and prioritise disease-associated proteins identified by these studies including 1) ontologies to map genes, proteins, and disease, 2) resources for determining the druggability of a potential target, 3) tissue and cell expression of the gene encoding the potential target, and 4) key biological pathways involving the potential target. We illustrate these concepts through a worked example, identifying a prioritised set of plasma proteins associated with non-alcoholic fatty liver disease (NAFLD). We identified five proteins with strong genetic support for involvement with NAFLD: CYB5A, NT5C, NCAN, TGFBI and DAPK2. All of the identified proteins were expressed in both liver and adipose tissues, with TGFBI and DAPK2 being potentially druggable. In conclusion, the current review provides an overview of genetic evidence for drug target identification, and how biomedical databases can be used to provide actionable prioritisation, fully informing downstream experimental validation.

Copy-number analysis from genome sequencing data of 11,754 rare-disease parent-child trios: A model for identifying autosomal recessive human gene knockouts including a novel gene for autosomal recessive retinopathy

Purpose

In parent-child trios with genome sequencing data, we investigated inherited biallelic deletions to identify known and novel genetic disorders.

Methods

We developed a copy-number variations analysis pipeline based on autosomal genome sequencing read depth of Genomics England 100,000 Genomes Project data from 11,754 parent-child trios and additional 18,875 non-trios. A control cohort of 15,440 cancer patients provided independent deletion frequencies.

Results

Autosomal recessive (AR) modeling detected 34 distinct rare deletions that were homozygous in the proband and heterozygous in both parents. These inherited biallelic deletions were only detected in 52 trios. These "knockout" regions included 37 genes, having among them 8 with an Online Mendelian Inheritance in Man AR annotation. Deletions of NPHP1, followed by OTOA, both within segmental duplications, were the only recurrent findings explaining phenotypes in a total of 10 and 3 patients, respectively. Recurrent heterozygous NPHP1 deletions were detected in 0.3%-0.5% of controls. We reviewed "knockout" patients for the remaining 29 genes without disease associations and identified SLC66A1 as a likely novel cause for AR rod-cone dystrophy in 4 families.

Conclusion

A tailored copy-number variations analysis of genome sequencing trio data shows that biallelic inherited gene deletions are rare, with NPHP1 biallelic deletions causing nephronophthisis the leading finding. We propose SLC66A1 as a novel cause for AR retinopathy.

50,000 years of Evolutionary History of India: Insights from ~2,700 Whole Genome Sequences

India has been underrepresented in whole genome sequencing studies. We generated 2,762 high coverage genomes from India-including individuals from most geographic regions, speakers of all major languages, and tribal and caste groups-providing a comprehensive survey of genetic variation in India. With these data, we reconstruct the evolutionary history of India through space and time at fine scales. We show that most Indians derive ancestry from three ancestral groups related to ancient Iranian farmers, Eurasian Steppe pastoralists and South Asian hunter-gatherers. We uncover a common source of Iranian-related ancestry from early Neolithic cultures of Central Asia into the ancestors of Ancestral South Indians (ASI), Ancestral North Indians (ANI), Austro-asiatic-related and East Asian-related groups in India. Following these admixtures, India experienced a major demographic shift towards endogamy, resulting in extensive homozygosity and identity-by-descent sharing among individuals. At deep time scales, Indians derive around 1-2% of their ancestry from gene flow from archaic hominins, Neanderthals and Denisovans. By assembling the surviving fragments of archaic ancestry in modern Indians, we recover ~1.5 Gb (or 50%) of the introgressing Neanderthal and ~0.6 Gb (or 20%) of the introgressing Denisovan genomes, more than any other previous archaic ancestry study. Moreover, Indians have the largest variation in Neanderthal ancestry, as well as the highest amount of population-specific Neanderthal segments among worldwide groups. Finally, we demonstrate that most of the genetic variation in Indians stems from a single major migration out of Africa that occurred around 50,000 years ago, with minimal contribution from earlier migration waves. Together, these analyses provide a detailed view of the population history of India and underscore the value of expanding genomic surveys to diverse groups outside Europe.

A Comprehensive Analysis of 3 Moroccan Genomes Revealed Contributions From Both African and European Ancestries

Genetic variations in the human genome represent the differences in DNA sequence within individuals. This highlights the important role of whole human genome sequencing which has become the keystone for precision medicine and disease prediction. Morocco is an important hub for studying human population migration and mixing history. This study presents the analysis of 3 Moroccan genomes; the variant analysis revealed 6 379 606 single nucleotide variants (SNVs) and 1 050 577 small InDels. Of those identified SNVs, 219 152 were novel, with 1233 occurring in coding regions, and 5580 non-synonymous single nucleotide variants (nsSNP) variants were predicted to affect protein functions. The InDels produced 1055 coding variants and 454 non-3n length variants, and their size ranged from -49 and 49 bp. We further analysed the gene pathways of 8 novel coding variants found in the 3 genomes and revealed 5 genes involved in various diseases and biological pathways. We found that the Moroccan genomes share 92.78% of African ancestry, and 92.86% of Non-Finnish European ancestry, according to the gnomAD database. Then, population structure inference, by admixture analysis and network-based approach, revealed that the studied genomes form a mixed population structure, highlighting the increased genetic diversity in Morocco.

STIGMA: Single-cell tissue-specific gene prioritization using machine learning

Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.

Phenome- and genome-wide analyses of retinal optical coherence tomography images identify links between ocular and systemic health

The human retina is a multilayered tissue that offers a unique window into systemic health. Optical coherence tomography (OCT) is widely used in eye care and allows the noninvasive, rapid capture of retinal anatomy in exquisite detail. We conducted genotypic and phenotypic analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed OCT layer cross-phenotype association analyses (OCT-XWAS), associating retinal thicknesses with 1866 incident conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association studies (GWASs), identifying inherited genetic markers that influence retinal layer thicknesses and replicated our associations among the LIFE-Adult Study (N = 6313). Last, we performed a comparative analysis of phenome- and genome-wide associations to identify putative causal links between retinal layer thicknesses and both ocular and systemic conditions. Independent associations with incident mortality were detected for thinner photoreceptor segments (PSs) and, separately, ganglion cell complex layers. Phenotypic associations were detected between thinner retinal layers and ocular, neuropsychiatric, cardiometabolic, and pulmonary conditions. A GWAS of retinal layer thicknesses yielded 259 unique loci. Consistency between epidemiologic and genetic associations suggested links between a thinner retinal nerve fiber layer with glaucoma, thinner PS with age-related macular degeneration, and poor cardiometabolic and pulmonary function with a thinner PS. In conclusion, we identified multiple inherited genetic loci and acquired systemic cardio-metabolic-pulmonary conditions associated with thinner retinal layers and identify retinal layers wherein thinning is predictive of future ocular and systemic conditions.

Genome-wide assessment of genetic diversity and transcript variations in 17 accessions of the model diatom Phaeodactylum tricornutum

Diatoms, a prominent group of phytoplankton, have a significant impact on both the oceanic food chain and carbon sequestration, thereby playing a crucial role in regulating the climate. These highly diverse organisms show a wide geographic distribution across various latitudes. In addition to their ecological significance, diatoms represent a vital source of bioactive compounds that are widely used in biotechnology applications. In the present study, we investigated the genetic and transcriptomic diversity of 17 accessions of the model diatom Phaeodactylum tricornutum including those sampled a century ago as well as more recently collected accessions. The analysis of the data reveals a higher genetic diversity and the emergence of novel clades, indicating an increasing diversity within the P. tricornutum population structure, compared to the previous study and a persistent long-term balancing selection of genes in old and newly sampled accessions. However, the study did not establish a clear link between the year of sampling and genetic diversity, thereby, rejecting the hypothesis of loss of heterozygoty in cultured strains. Transcript analysis identified novel transcript including noncoding RNA and other categories of small RNA such as PiwiRNAs. Additionally, transcripts analysis using differential expression as well as Weighted Gene Correlation Network Analysis has provided evidence that the suppression or downregulation of genes cannot be solely attributed to loss-of-function mutations. This implies that other contributing factors, such as epigenetic modifications, may play a crucial role in regulating gene expression. Our study provides novel genetic resources, which are now accessible through the platform PhaeoEpiview (https://PhaeoEpiView.univ-nantes.fr), that offer both ease of use and advanced tools to further investigate microalgae biology and ecology, consequently enriching our current understanding of these organisms.

Dissecting the Immune System through Gene Regulation

The immune system plays a dual role in human health, functioning both as a protector against pathogens and, at times, as a contributor to disease. This feature emphasizes the importance to uncover the underlying causes of its malfunctions, necessitating an in-depth analysis in both pathological and physiological conditions to better understand the immune system and immune disorders. Recent advances in scientific technology have enabled extensive investigations into gene regulation, a crucial mechanism governing cellular functionality. Studying gene regulatory mechanisms within the immune system is a promising avenue for enhancing our understanding of immune cells and the immune system as a whole. The gene regulatory mechanisms, revealed through various methodologies, and their implications in the field of immunology are discussed in this chapter.

Novel compound heterozygous pathogenic variants in the SLC3A1 gene in a Chinese family with cystinuria

BACKGROUND

Cystinuria is an autosomal recessive disorder characterized by a cystine transport deficiency in the renal tubules due to mutations in two genes: SLC3A1 and SLC7A9. Cystinuria can be classified into three forms based on the genotype: type A, due to mutations in the SLC3A1 gene; type B, due to mutations in the SLC7A9 gene; and type AB, due to mutations in both genes.

METHODS

We report a 12-year-old boy from central China with cystine stones. He was from a non-consanguineous family that had no known history of genetic disease. A physical examination showed normal development and neurological behaviors. Whole-exome and Sanger sequencing were used to identify and verify the suspected pathogenic variants.

RESULTS

The compound heterozygous variants c.898_905del (p.Arg301AlafsTer6) is located in exon5 and c.1898_1899insAT (p.Asp634LeufsTer46) is located in exon10 of SLC3A1 (NM_000341.4) were deemed responsible for type A cystinuria family. The variant c.898_905del was reported in a Japanese patient in 2000, and the variant c.1898_1899insAT is novel.

CONCLUSION

A novel pathogenic heterozygous variant pair of the SLC3A1 gene was identified in a Chinese boy with type A cystinuria, enriching the mutational spectrum of the SLC3A1 gene. We attempted to find a pattern for the association between the genotype of SLC3A1 variants and the manifestations of cystinuria in patients with different onset ages. Our findings have important implications for genetic counseling and the early clinical diagnosis of cystinuria.