A joint NCBI and EMBL-EBI transcript set for clinical genomics and research

Structure-based protein and small molecule generation using EGNN and diffusion models: A comprehensive review

Recent breakthroughs in deep learning have revolutionized protein sequence and structure prediction. These advancements are built on decades of protein design efforts, and are overcoming traditional time and cost limitations. Diffusion models, at the forefront of these innovations, significantly enhance design efficiency by automating knowledge acquisition. In the field of de novo protein design, the goal is to create entirely novel proteins with predetermined structures. Given the arbitrary positions of proteins in 3-D space, graph representations and their properties are widely used in protein generation studies. A critical requirement in protein modelling is maintaining spatial relationships under transformations (rotations, translations, and reflections). This property, known as equivariance, ensures that predicted protein characteristics adapt seamlessly to changes in orientation or position. Equivariant graph neural networks offer a solution to this challenge. By incorporating equivariant graph neural networks to learn the score of the probability density function in diffusion models, one can generate proteins with robust 3-D structural representations. This review examines the latest deep learning advancements, specifically focusing on frameworks that combine diffusion models with equivariant graph neural networks for protein generation.

Single-cell multi-modal chromatin profiles revealing epigenetic regulations of cells in hepatocellular carcinoma

BACKGROUND

Various epigenetic regulations systematically govern gene expression in cells involving various biological processes. Dysregulation of the epigenome leads to aberrant transcriptional programs and subsequently results in diseases, such as cancer. Therefore, comprehensive profiling epigenomics is essential for exploring the mechanisms underlying gene expression regulation during development and disease.

METHODS

In this study, we developed single-cell chromatin proteins and accessibility tagmentation (scCPA-Tag), a multi-modal single-cell epigenetic profile capturing technique based on barcoded Tn5 transposases and a droplet microfluidics platform. scCPA-Tag enables the simultaneous capture of DNA profiles of histone modification and chromatin accessibility in the same cell.

RESULTS

By applying scCPA-Tag to K562 cells and a hepatocellular carcinoma (HCC) sample, we found that the silence of several chromatin-accessible genes can be attributed to lysine-27-trimethylation of the histone H3 tail (H3K27me3) modification. We characterized the epigenetic features of the tumour cells and different immune cell types in the HCC tumour tissue by scCPA-Tag. Besides, a tumour cell subtype (C2) with more aggressive features was identified and characterized by high chromatin accessibility and a lower abundance of H3K27me3 on tumour-promoting genes.

CONCLUSIONS

Our multi-modal scCPA-Tag provides a comprehensive approach for exploring the epigenetic landscapes of heterogeneous cell types and revealing the mechanisms of gene expression regulation during developmental and pathological processes at the single-cell level.

HIGHLIGHTS

scCPA-Tag offers a highly efficient and high throughput technique to simultaneously profile histone modification and chromatin accessibility within a single cell. scCPA-Tag enables to uncover multiple epigenetic modification features of cellular compositions within tumor tissues. scCPA-Tag facilitates the exploration of the epigenetic landscapes of heterogeneous cell types and provides the mechanisms governing gene expression regulation.

GEGA (Gallus Enriched Gene Annotation): an online tool providing genomics and functional information across 47 tissues for a chicken gene-enriched atlas gathering Ensembl and Refseq genome annotations

GEGA is a user-friendly tool designed to navigate through various genomic and functional information related to an enriched gene atlas in chicken that integrates the gene catalogues from the two reference databases, NCBI-RefSeq and EMBL-Ensembl/GENCODE, along with four additional rich resources such as FAANG and NONCODE. Using the latest GRCg7b genome assembly, GEGA encompasses a total of 78 323 genes, including 24 102 protein-coding genes (PCGs) and 44 428 long non-coding RNAs (lncRNAs), significantly increasing the number of genes provided by each resource independently. However, GEGA is more than just a gene database. It offers a range of features that allow us to go deeper into the functional aspects of these genes. Users can explore gene expression and co-expression profiles across 47 tissues from 36 datasets and 1400 samples, discover tissue-specific variations and their expression as a function of sex or age and extract orthologous genes or their genomic configuration relative to the closest gene. For the communities interested in a specific gene, a list of genes or a quantitative trait locus region in chicken, GEGA's user-friendly interface facilitates efficient gene analysis, easy downloading of results and a multitude of graphical representations, from genomic information to detailed visualization of expression levels.

Genotyping sequence-resolved copy-number variation using pangenomes reveals paralog-specific global diversity and expression divergence of duplicated genes

Human pangenomes contain assemblies of non-reference copy-number variable (CNV) genes. We developed a new method, ctyper, to identify the copy-number of specific alleles of CNV genes cataloged in pangenomes with NGS datasets. Applying ctyper to the 1000-genomes samples revealed population stratification of paralogs and two classes of CNVs: recent CNVs due to ongoing duplications, and polymorphic CNVs from non-reference ancient paralogs. Expression quantitative trait locus analysis determined allele-specific expression within gene families, revealing that 7.94% of paralogs and 3.28% orthologs had significantly divergent expression. Case studies of individual genes include finding lower expression on SMN -1 copies that arose from conversion from SMN- 2, and increased expression on a form of AMY2B that has undergone a translocation. Moreover, 4.7% of paralogs and 1.2% of orthologs had different most-expressed tissues. Furthermore, the genotypes explain more expression variance than known eQTL variants. Overall, ctyper enables biobank-scale genotyping of sequence-resolved CNVs.

Replicating the Association of Variants in BSN and APBA1 with Obesity in Diverse Populations

In a recent study by Zhao et al., rare protein-truncating variants (PTVs) in the BSN and APBA1 genes showed effects on obesity that exceeded those of well-known genes such as MC4R in a UK cohort. In this study, we leveraged the All of Us Research Program, to investigate the association of predicted LoF (pLoF) PTVs in BSN and APBA1 with body mass index (BMI) across a population of diverse ancestry. Our analysis revealed that the impact of pLoF variants in BSN and APBA1 on BMI was notably greater in this cohort, especially among individuals of European ancestry. Additionally, a phenome-wide association study (PheWAS) using the extensive phenotypic data available in the All of Us Research Program uncovered novel associations of BSN and APBA1 heterozygous pLoF carriers with various phenotypes. Specifically, BSN pLoF variants were associated with pulmonary hypertension, atrial fibrillation, and anticoagulant use, while APBA1 pLoF variants were linked to disorders of the temporomandibular joint. These findings underscore the potential of large-scale biobanks in advancing genetic discovery.

Major Causes of Conflicting Interpretations of Variant Pathogenicity in Rare Disease: A Systematic Analysis

The identification of the genetic causes of inherited disorders from next-generation sequencing (NGS) data remains a complicated process, in particular due to challenges in interpretation of the vast amount of generated data and hundreds of candidate variants identified. Inconsistencies in variant classification, where genetic centers classify the same variant differently, can hinder accurate diagnoses for rare diseases. Publicly available databases that collect data on human genetic variations and their association with diseases provide ample opportunities to discover conflicts in variant interpretation worldwide. In this study, we explored patterns of variant classification discrepancies using data from ClinVar, a public archive of variant interpretations. We found that 5.7% of variants have conflicting interpretations (COIs) reported, and the vast majority of interpretation conflicts arise for variants of uncertain significance (VUS). As many as 78% of clinically relevant genes harbor variants with COIs, and genes with high COI rates tended to have more exons and longer transcripts, with a greater proportion of genes linked to several distinct conditions. The enrichment analysis of COI-enriched genes revealed that the products of these genes are involved in cardiac disorders, muscle development, and function. To improve diagnoses, we believe that specific variant interpretation rules could be developed for such genes. Additionally, our findings underscore the need for the publication of variant pathogenicity evidence and the importance of considering every variant as VUS unless proven otherwise.

Evidence for widespread translation of 5' untranslated regions

Ribosome profiling experiments support the translation of a range of novel human open reading frames. By contrast, most peptides from large-scale proteomics experiments derive from just one source, 5' untranslated regions. Across the human genome we find evidence for 192 translated upstream regions, most of which would produce protein isoforms with extended N-terminal ends. Almost all of these N-terminal extensions are from highly abundant genes, which suggests that the novel regions we detect are just the tip of the iceberg. These upstream regions have characteristics that are not typical of coding exons. Their GC-content is remarkably high, even higher than 5' regions in other genes, and a large majority have non-canonical start codons. Although some novel upstream regions have cross-species conservation - five have orthologues in invertebrates for example - the reading frames of two thirds are not conserved beyond simians. These non-conserved regions also have no evidence of purifying selection, which suggests that much of this translation is not functional. In addition, non-conserved upstream regions have significantly more peptides in cancer cell lines than would be expected, a strong indication that an aberrant or noisy translation initiation process may play an important role in translation from upstream regions.

Pathogenic variants in KMT2C result in a neurodevelopmental disorder distinct from Kleefstra and Kabuki syndromes

Trithorax-related H3K4 methyltransferases, KMT2C and KMT2D, are critical epigenetic modifiers. Haploinsufficiency of KMT2C was only recently recognized as a cause of neurodevelopmental disorder (NDD), so the clinical and molecular spectrums of the KMT2C-related NDD (now designated as Kleefstra syndrome 2) are largely unknown. We ascertained 98 individuals with rare KMT2C variants, including 75 with protein-truncating variants (PTVs). Notably, ∼15% of KMT2C PTVs were inherited. Although the most highly expressed KMT2C transcript consists of only the last four exons, pathogenic PTVs were found in almost all the exons of this large gene. KMT2C variant interpretation can be challenging due to segmental duplications and clonal hematopoesis-induced artifacts. Using samples from 27 affected individuals, divided into discovery and validation cohorts, we generated a moderate strength disorder-specific KMT2C DNA methylation (DNAm) signature and demonstrate its utility in classifying non-truncating variants. Based on 81 individuals with pathogenic/likely pathogenic variants, we demonstrate that the KMT2C-related NDD is characterized by developmental delay, intellectual disability, behavioral and psychiatric problems, hypotonia, seizures, short stature, and other comorbidities. The facial module of PhenoScore, applied to photographs of 34 affected individuals, reveals that the KMT2C-related facial gestalt is significantly different from the general NDD population. Finally, using PhenoScore and DNAm signatures, we demonstrate that the KMT2C-related NDD is clinically and epigenetically distinct from Kleefstra and Kabuki syndromes. Overall, we define the clinical features, molecular spectrum, and DNAm signature of the KMT2C-related NDD and demonstrate they are distinct from Kleefstra and Kabuki syndromes highlighting the need to rename this condition.

VUStruct: a compute pipeline for high throughput and personalized structural biology

Effective diagnosis and treatment of rare genetic disorders requires the interpretation of a patient's genetic variants of unknown significance (VUSs). Today, clinical decision-making is primarily guided by gene-phenotype association databases and DNA-based scoring methods. Our web-accessible variant analysis pipeline, VUStruct, supplements these established approaches by deeply analyzing the downstream molecular impact of variation in context of 3D protein structure. VUStruct's growing impact is fueled by the co-proliferation of protein 3D structural models, gene sequencing, compute power, and artificial intelligence. Contextualizing VUSs in protein 3D structural models also illuminates longitudinal genomics studies and biochemical bench research focused on VUS, and we created VUStruct for clinicians and researchers alike. We now introduce VUStruct to the broad scientific community as a mature, web-facing, extensible, High Performance Computing (HPC) software pipeline. VUStruct maps missense variants onto automatically selected protein structures and launches a broad range of analyses. These include energy-based assessments of protein folding and stability, pathogenicity prediction through spatial clustering analysis, and machine learning (ML) predictors of binding surface disruptions and nearby post-translational modification sites. The pipeline also considers the entire input set of VUS and identifies genes potentially involved in digenic disease. VUStruct's utility in clinical rare disease genome interpretation has been demonstrated through its analysis of over 175 Undiagnosed Disease Network (UDN) Patient cases. VUStruct-leveraged hypotheses have often informed clinicians in their consideration of additional patient testing, and we report here details from two cases where VUStruct was key to their solution. We also note successes with academic research collaborators, for whom VUStruct has informed research directions in both computational genomics and wet lab studies.

Respiratory Syncytial Virus (RSV) optimizes the translational landscape during infection

Viral infection often triggers eukaryotic initiator factor 2α (eIF2α) phosphorylation, leading to global 5'-cap-dependent translation inhibition. RSV encodes messenger RNAs (mRNAs) mimicking 5'-cap structures of host mRNAs and thus inhibition of cap-dependent translation initiation would likely also reduce viral translation. We confirmed that RSV limits widespread translation initiation inhibition and unexpectedly found that the fraction of ribosomes within polysomes increases during infection, indicating higher ribosome loading on mRNAs during infection. We found that AU-rich host transcripts that are less efficiently translated under normal conditions become more efficient at recruiting ribosomes, similar to RSV transcripts. Viral transcripts are transcribed in cytoplasmic inclusion bodies, where the viral AU-rich binding protein M2-1 has been shown to bind viral transcripts and shuttle them into the cytoplasm. We further demonstrated that M2-1 is found on polysomes, and that M2-1 might deliver host AU-rich transcripts for translation.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

Myotonic dystrophy type 1 testing, 2024 revision: A technical standard of the American College of Medical Genetics and Genomics (ACMG)

Myotonic dystrophy type 1 (DM1) is a form of muscular dystrophy causing progressive muscle loss and weakness. Although clinical features can manifest at any age, it is the most common form of muscular dystrophy with onset in adulthood. DM1 is an autosomal dominant condition, resulting from an unstable CTG expansion in the 3'-untranslated region of the myotonic dystrophy protein kinase (DMPK) gene. The age of onset and the severity of the phenotype are roughly correlated with the size of the CTG expansion. Multiple methodologies can be used to diagnose affected individuals with DM1, including polymerase chain reaction, Southern blot, and triplet repeat-primed polymerase chain reaction. Recently, triplet repeat interruptions have been described, which may affect clinical outcomes of a fully-variable allele in DMPK. This document supersedes the Technical Standards and Guidelines for Myotonic Dystrophy originally published in 2009 and reaffirmed in 2015. It is designed for genetic testing professionals who are already familiar with the disease and the methods of analysis.

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

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

Multisite Validation of a Functional Assay to Adjudicate SCN5A Brugada Syndrome-Associated Variants

BACKGROUND

Brugada syndrome is an inheritable arrhythmia condition that is associated with rare, loss-of-function variants in SCN5A. Interpreting the pathogenicity of SCN5A missense variants is challenging, and ≈79% of SCN5A missense variants in ClinVar are currently classified as variants of uncertain significance. Automated patch clamp technology enables high-throughput functional studies of ion channel variants and can provide evidence for variant reclassification.

METHODS

An in vitro SCN5A-Brugada syndrome automated patch clamp assay was independently performed at Vanderbilt University Medical Center and Victor Chang Cardiac Research Institute. The assay was calibrated according to ClinGen Sequence Variant Interpretation recommendations using high-confidence variant controls (n=49). Normal and abnormal ranges of function were established based on the distribution of benign variant assay results. Odds of pathogenicity values were derived from the experimental results according to ClinGen Sequence Variant Interpretation recommendations. The calibrated assay was then used to study SCN5A variants of uncertain significance observed in 4 families with Brugada syndrome and other arrhythmia phenotypes associated with SCN5A loss-of-function.

RESULTS

Variant channel parameters generated independently at the 2 research sites showed strong correlations, including peak INa density (R2=0.86). The assay accurately distinguished benign controls (24/25 concordant variants) from pathogenic controls (23/24 concordant variants). Odds of pathogenicity values were 0.042 for normal function and 24.0 for abnormal function, corresponding to strong evidence for both American College of Medical Genetics and Genomics/Association for Molecular Pathology benign and pathogenic functional criteria (BS3 and PS3, respectively). Application of the assay to 4 clinical SCN5A variants of uncertain significance revealed loss-of-function for 3/4 variants, enabling reclassification to likely pathogenic.

CONCLUSIONS

This validated high-throughput assay provides clinical-grade functional evidence to aid the classification of current and future SCN5A-Brugada syndrome variants of uncertain significance.

The FXR1 network acts as a signaling scaffold for actomyosin remodeling

It is currently not known whether mRNAs fulfill structural roles in the cytoplasm. Here, we report the fragile X-related protein 1 (FXR1) network, an mRNA-protein (mRNP) network present throughout the cytoplasm, formed by FXR1-mediated packaging of exceptionally long mRNAs. These mRNAs serve as an underlying condensate scaffold and concentrate FXR1 molecules. The FXR1 network contains multiple protein binding sites and functions as a signaling scaffold for interacting proteins. We show that it is necessary for RhoA signaling-induced actomyosin reorganization to provide spatial proximity between kinases and their substrates. Point mutations in FXR1, found in its homolog FMR1, where they cause fragile X syndrome, disrupt the network. FXR1 network disruption prevents actomyosin remodeling-an essential and ubiquitous process for the regulation of cell shape, migration, and synaptic function. Our findings uncover a structural role for cytoplasmic mRNA and show how the FXR1 RNA-binding protein as part of the FXR1 network acts as an organizer of signaling reactions.

Investigating copy number variants in schizophrenia pedigrees using a new consensus pipeline called PECAN

Copy number variants (CNVs) have been implicated in many human diseases, including psychiatric disorders. Whole genome sequencing offers advantages in CNV calling compared to previous array-based methods. Here we present a robust and transparent CNV calling pipeline, PECAN (PEdigree Copy number vAriaNt calling), for short-read, whole genome sequencing data, comprised of a novel combination of four calling methods and structural variant genotyping. This method is scalable and can incorporate pedigree information to retain lower-confidence CNVs that would otherwise be discarded. We have robustly benchmarked PECAN using gold-standard CNV calls for two well-established evaluation samples, NA12878 and HG002, showing that PECAN performs with high precision and recall on both datasets, outperforming another pedigree-based CNV calling pipeline. As part of this work, we provide a list of high-confidence gold standard CNVs for the NA12878 reference sample, curated from multiple studies. We applied PECAN to a collection of pedigrees multiply affected with schizophrenia and identified a rare deletion that perfectly co-segregates with schizophrenia in one of the pedigrees. The CNV overlaps the gene PITRM1, which has been implicated in a complex phenotype including ataxia, developmental delay, and schizophrenia-like episodes in affected adults.

Identification of an Allele-Specific Transcription Factor Binding Interaction that May Regulate PLA2G2A Gene Expression

The secreted phospholipase A2 (sPLA2) isoform, sPLA2-IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA2-IIA. The work in the manuscript leveraged 4 publicly available datasets to investigate the mechanism by which rs11573156 influences sPLA2-IIA levels via bioinformatics and modeling analysis. Through genotype-tissue expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA2-IIA, PLA2G2A. SNP2TFBS was used to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified eQTL SNPs. Subsequently, candidate TF-SNP interactions were cross-referenced with the ChIP-seq results in matched tissues from ENCODE. SP1-rs11573156 emerged as the significant TF-SNP pair in the liver. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was likely affected by tissue SP1 protein levels. Using an ordinary differential equation based on Michaelis-Menten kinetic assumptions, we modeled the dependence of PLA2G2A transcription on SP1 protein levels, incorporating the SNP influence. Collectively, our analysis strongly suggests that the difference in the binding dynamics of SP1 to different rs11573156 alleles may underlie the allele-specific PLA2G2A expression in different tissues, a mechanistic model that awaits future direct experimental validation. This mechanism likely contributes to the variation in circulating sPLA2-IIA protein levels in the human population, with implications for a wide range of human diseases.

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.

hnRNPs: roles in neurodevelopment and implication for brain disorders

Heterogeneous nuclear ribonucleoproteins (hnRNPs) constitute a family of multifunctional RNA-binding proteins able to process nuclear pre-mRNAs into mature mRNAs and regulate gene expression in multiple ways. They comprise at least 20 different members in mammals, named from A (HNRNP A1) to U (HNRNP U). Many of these proteins are components of the spliceosome complex and can modulate alternative splicing in a tissue-specific manner. Notably, while genes encoding hnRNPs exhibit ubiquitous expression, increasing evidence associate these proteins to various neurodevelopmental and neurodegenerative disorders, such as intellectual disability, epilepsy, microcephaly, amyotrophic lateral sclerosis, or dementias, highlighting their crucial role in the central nervous system. This review explores the evolution of the hnRNPs family, highlighting the emergence of numerous new members within this family, and sheds light on their implications for brain development.

Regional-specific calibration enables application of computational evidence for clinical classification of 5' cis-regulatory variants in Mendelian disease

To date, clinical genetic testing for Mendelian disease variants has focused heavily on exonic coding and intronic gene regions. This multi-step study was undertaken to provide an evidence base for selecting and applying computational approaches for use in clinical classification of 5' cis-regulatory region variants. Curated datasets of clinically reported disease-causing 5' cis-regulatory region variants and variants from matched genomic regions in population controls were used to calibrate six bioinformatic tools as predictors of variant pathogenicity. Likelihood ratio estimates were aligned to code weights following ClinGen recommendations for application of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) classification scheme. Considering code assignment across all reference dataset variants, performance was best for CADD (81.2%) and REMM (81.5%). Optimized thresholds provided moderate evidence toward pathogenicity (CADD, REMM) and moderate (CADD) or supporting (REMM) evidence against pathogenicity. Both sensitivity and specificity of prediction were improved when further categorizing variants based on location in an EPDnew-defined promoter region. Combining predictions (CADD, REMM, and location in a promoter region) increased specificity at the expense of sensitivity. Importantly, the optimal CADD thresholds for assigning ACMG/AMP codes PP3 (≥10) and BP4 (≤8) were vastly different from recommendations for protein-coding variants (PP3 ≥25.3; BP4 ≤22.7); CADD <22.7 would incorrectly assign BP4 for >90% of reported disease-causing cis-regulatory region variants. Our results demonstrate the need to consider a tiered approach and tailored score thresholds to optimize bioinformatic impact prediction for clinical classification of 5' cis-regulatory region variants.

The molecular basis of tRNA selectivity by human pseudouridine synthase 3

Pseudouridine (Ψ), the isomer of uridine, is ubiquitously found in RNA, including tRNA, rRNA, and mRNA. Human pseudouridine synthase 3 (PUS3) catalyzes pseudouridylation of position 38/39 in tRNAs. However, the molecular mechanisms by which it recognizes its RNA targets and achieves site specificity remain elusive. Here, we determine single-particle cryo-EM structures of PUS3 in its apo form and bound to three tRNAs, showing how the symmetric PUS3 homodimer recognizes tRNAs and positions the target uridine next to its active site. Structure-guided and patient-derived mutations validate our structural findings in complementary biochemical assays. Furthermore, we deleted PUS1 and PUS3 in HEK293 cells and mapped transcriptome-wide Ψ sites by Pseudo-seq. Although PUS1-dependent sites were detectable in tRNA and mRNA, we found no evidence that human PUS3 modifies mRNAs. Our work provides the molecular basis for PUS3-mediated tRNA modification in humans and explains how its tRNA modification activity is linked to intellectual disabilities.

SeqCAT: Sequence Conversion and Analysis Toolbox

Dealing with sequence coordinates in different formats and reference genomes is challenging in genetic research. This complexity arises from the need to convert and harmonize datasets of different sources using alternating nomenclatures. Since manual processing is time-consuming and requires specialized knowledge, the Sequence Conversion and Analysis Toolbox (SeqCAT) was developed for daily work with genetic datasets. Our tool provides a range of functions designed to standardize and convert gene variant coordinates based on various sequence types. Its user-friendly web interface provides easy access to all functionalities, while the Application Programming Interface (API) enables automation within pipelines. SeqCAT provides access to human genomic, protein and transcript data, utilizing various data resources and packages and extending them with its own unique features. The platform covers a wide range of genetic research needs with its 14 different applications and 3 info points, including search for transcript and gene information, transition between reference genomes, variant mapping, and genetic event review. Notable examples are 'Convert Protein to DNA Position' for translation of amino acid changes into genomic single nucleotide variants, or 'Fusion Check' for frameshift determination in gene fusions. SeqCAT is an excellent resource for converting sequence coordinate data into the required formats and is available at: https://mtb.bioinf.med.uni-goettingen.de/SeqCAT/.

ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia-2024 update

In chronic lymphocytic leukemia (CLL), analysis of TP53 aberrations (deletion and/or mutation) is a crucial part of treatment decision-making algorithms. Technological and treatment advances have resulted in the need for an update of the last recommendations for TP53 analysis in CLL, published by ERIC, the European Research Initiative on CLL, in 2018. Based on the current knowledge of the relevance of low-burden TP53-mutated clones, a specific variant allele frequency (VAF) cut-off for reporting TP53 mutations is no longer recommended, but instead, the need for thorough method validation by the reporting laboratory is emphasized. The result of TP53 analyses should always be interpreted within the context of available laboratory and clinical information, treatment indication, and therapeutic options. Methodological aspects of introducing next-generation sequencing (NGS) in routine practice are discussed with a focus on reliable detection of low-burden clones. Furthermore, potential interpretation challenges are presented, and a simplified algorithm for the classification of TP53 variants in CLL is provided, representing a consensus based on previously published guidelines. Finally, the reporting requirements are highlighted, including a template for clinical reports of TP53 aberrations. These recommendations are intended to assist diagnosticians in the correct assessment of TP53 mutation status, but also physicians in the appropriate understanding of the lab reports, thus decreasing the risk of misinterpretation and incorrect management of patients in routine practice whilst also leading to improved stratification of patients with CLL in clinical trials.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

ASS1 metabolically contributes to the nuclear and cytosolic p53-mediated DNA damage response

Downregulation of the urea cycle enzyme argininosuccinate synthase (ASS1) in multiple tumors is associated with a poor prognosis partly because of the metabolic diversion of cytosolic aspartate for pyrimidine synthesis, supporting proliferation and mutagenesis owing to nucleotide imbalance. Here, we find that prolonged loss of ASS1 promotes DNA damage in colon cancer cells and fibroblasts from subjects with citrullinemia type I. Following acute induction of DNA damage with doxorubicin, ASS1 expression is elevated in the cytosol and the nucleus with at least a partial dependency on p53; ASS1 metabolically restrains cell cycle progression in the cytosol by restricting nucleotide synthesis. In the nucleus, ASS1 and ASL generate fumarate for the succination of SMARCC1, destabilizing the chromatin-remodeling complex SMARCC1-SNF5 to decrease gene transcription, specifically in a subset of the p53-regulated cell cycle genes. Thus, following DNA damage, ASS1 is part of the p53 network that pauses cell cycle progression, enabling genome maintenance and survival. Loss of ASS1 contributes to DNA damage and promotes cell cycle progression, likely contributing to cancer mutagenesis and, hence, adaptability potential.

Laboratory testing for preconception/prenatal carrier screening: A technical standard of the American College of Medical Genetics and Genomics (ACMG)

Carrier screening has historically assessed a relatively small number of autosomal recessive and X-linked conditions selected based on frequency in a specific subpopulation and association with severe morbidity or mortality. Advances in genomic technologies enable simultaneous screening of individuals for several conditions. The American College of Medical Genetics and Genomics recently published a clinical practice resource that presents a framework when offering screening for autosomal recessive and X-linked conditions during pregnancy and preconception and recommends a tier-based approach when considering the number of conditions to screen for and their frequency within the US population in general. This laboratory technical standard aims to complement the practice resource and to put forth considerations for clinical laboratories and clinicians who offer preconception/prenatal carrier screening.

Saturation genome editing of BAP1 functionally classifies somatic and germline variants

Many variants that we inherit from our parents or acquire de novo or somatically are rare, limiting the precision with which we can associate them with disease. We performed exhaustive saturation genome editing (SGE) of BAP1, the disruption of which is linked to tumorigenesis and altered neurodevelopment. We experimentally characterized 18,108 unique variants, of which 6,196 were found to have abnormal functions, and then used these data to evaluate phenotypic associations in the UK Biobank. We also characterized variants in a large population-ascertained tumor collection, in cancer pedigrees and ClinVar, and explored the behavior of cancer-associated variants compared to that of variants linked to neurodevelopmental phenotypes. Our analyses demonstrated that disruptive germline BAP1 variants were significantly associated with higher circulating levels of the mitogen IGF-1, suggesting a possible pathological mechanism and therapeutic target. Furthermore, we built a variant classifier with >98% sensitivity and specificity and quantify evidence strengths to aid precision variant interpretation.

Protein and mRNA Expression in Uveal Melanoma Cell Lines Are Related to GNA and BAP1 Mutation Status

Purpose

Cell lines are being used in preclinical uveal melanoma (UM) research. Because not all cell lines harbor typical GNAQ or GNA11 hotspot mutations, we aimed at better classifying them and determining whether we could find genetic causes to explain the protein and mRNA expression profiles of the cell lines.

Methods

We studied protein and mRNA expression of 14 UM cell lines and determined the presence of single nucleotide variants and small insertions and deletions with next-generation sequencing and copy number alterations with a single nucleotide polymorphism array. The lists of differentially expressed proteins and genes were merged, and shared lists were created, keeping only terms with concordant mRNA and protein expression. Enrichment analyses were performed on the shared lists.

Results

Cell lines Mel285 and Mel290 are separate from GNA-mutated cell lines and show downregulation of melanosome-related markers. Both lack typical UM mutations but each harbors four putatively deleterious variants in CTNNB1, PPP1R10, LIMCH1, and APC in Mel285 and ARID1A, PPP1R10, SPG11, and RNF43 in Mel290. The upregulated terms in Mel285 and Mel290 did not point to a convincing alternative origin. Mel285 shows loss of chromosomes 1p, 3p, partial 3q, 6, and partial 8p, whereas Mel290 shows loss of 1p and 6. Expression in the other 12 cell lines was related to BAP1 expression.

Conclusions

Although Mel285 and Mel290 have copy number alterations that fit UM, multi-omics analyses show that they belong to a separate group compared to the other analyzed UM cell lines. Therefore, they may not be representative models to test potential therapeutic targets for UM.

Genes divided according to the relative position of the longest intron show increased representation in different KEGG pathways

Despite the fact that introns mean an energy and time burden for eukaryotic cells, they play an irreplaceable role in the diversification and regulation of protein production. As a common feature of eukaryotic genomes, it has been reported that in protein-coding genes, the longest intron is usually one of the first introns. The goal of our work was to find a possible difference in the biological function of genes that fulfill this common feature compared to genes that do not. Data on the lengths of all introns in genes were extracted from the genomes of six vertebrates (human, mouse, koala, chicken, zebrafish and fugu) and two other model organisms (nematode worm and arabidopsis). We showed that more than 40% of protein-coding genes have the relative position of the longest intron located in the second or third tertile of all introns. Genes divided according to the relative position of the longest intron were found to be significantly increased in different KEGG pathways. Genes with the longest intron in the first tertile predominate in a range of pathways for amino acid and lipid metabolism, various signaling, cell junctions or ABC transporters. Genes with the longest intron in the second or third tertile show increased representation in pathways associated with the formation and function of the spliceosome and ribosomes. In the two groups of genes defined in this way, we further demonstrated the difference in the length of the longest introns and the distribution of their absolute positions. We also pointed out other characteristics, namely the positive correlation between the length of the longest intron and the sum of the lengths of all other introns in the gene and the preservation of the exact same absolute and relative position of the longest intron between orthologous genes.

Subtype-specific alternative splicing events in breast cancer identified by large-scale data analysis

Genome analysis in cancer has focused mainly on elucidating the function and regulatory mechanisms of genes that exhibit differential expression or mutation in cancer samples compared to normal samples. Recently, transcriptome analysis revealed that abnormal splicing events in cancer samples could contribute to cancer pathogenesis. Moreover, splicing variants in cancer reportedly generate diverse cancer antigens. Although abnormal splicing events are expected to be potential targets in cancer immunotherapy, the exploration of such targets and their biological significance in cancer have not been fully understood. In this study, to explore subtype-specific alternative splicing events, we conducted a comprehensive analysis of splicing events for each breast cancer subtype using large-scale splicing data derived from The Cancer Genome Atlas and found subtype-specific alternative splicing patterns. Analyses indicated that genes that produce subtype-specific alternative splicing events are potential novel targets for immunotherapy against breast cancer. The subtype-specific alternative splicing events identified in this study, which were not identified by mutation or differential expression analysis, bring new significance to previously overlooked splicing events.

Improved selection of canonical proteins for reference proteomes

The 'canonical' protein sets distributed by UniProt are widely used for similarity searching, and functional and structural annotation. For many investigators, canonical sequences are the only version of a protein examined. However, higher eukaryotes often encode multiple isoforms of a protein from a single gene. For unreviewed (UniProtKB/TrEMBL) protein sequences, the longest sequence in a Gene-Centric group is chosen as canonical. This choice can create inconsistencies, selecting >95% identical orthologs with dramatically different lengths, which is biologically unlikely. We describe the ortho2tree pipeline, which examines Reference Proteome canonical and isoform sequences from sets of orthologous proteins, builds multiple alignments, constructs gap-distance trees, and identifies low-cost clades of isoforms with similar lengths. After examining 140 000 proteins from eight mammals in UniProtKB release 2022_05, ortho2tree proposed 7804 canonical changes for release 2023_01, while confirming 53 434 canonicals. Gap distributions for isoforms selected by ortho2tree are similar to those in bacterial and yeast alignments, organisms unaffected by isoform selection, suggesting ortho2tree canonicals more accurately reflect genuine biological variation. 82% of ortho2tree proposed-changes agreed with MANE; for confirmed canonicals, 92% agreed with MANE. Ortho2tree can improve canonical assignment among orthologous sequences that are >60% identical, a group that includes vertebrates and higher plants.

The FXR1 network acts as signaling scaffold for actomyosin remodeling

It is currently not known whether mRNAs fulfill structural roles in the cytoplasm. Here, we report the FXR1 network, an mRNA-protein (mRNP) network present throughout the cytoplasm, formed by FXR1-mediated packaging of exceptionally long mRNAs. These mRNAs serve as underlying condensate scaffold and concentrate FXR1 molecules. The FXR1 network contains multiple protein binding sites and functions as a signaling scaffold for interacting proteins. We show that it is necessary for RhoA signaling-induced actomyosin reorganization to provide spatial proximity between kinases and their substrates. Point mutations in FXR1, found in its homolog FMR1, where they cause Fragile X syndrome, disrupt the network. FXR1 network disruption prevents actomyosin remodeling-an essential and ubiquitous process for the regulation of cell shape, migration, and synaptic function. These findings uncover a structural role for cytoplasmic mRNA and show how the FXR1 RNA-binding protein as part of the FXR1 network acts as organizer of signaling reactions.

Alternative isoform expression of key thermogenic genes in human beige adipocytes

Background

The beneficial effect of thermogenic adipocytes in maintaining body weight and protecting against metabolic disorders has raised interest in understanding the regulatory mechanisms defining white and beige adipocyte identity. Although alternative splicing has been shown to propagate adipose browning signals in mice, this has yet to be thoroughly investigated in human adipocytes.

Methods

We performed parallel white and beige adipogenic differentiation using primary adipose stem cells from 6 unrelated healthy subjects and assessed differential gene and isoform expression in mature adipocytes by RNA sequencing.

Results

We find 777 exon junctions with robust differential usage between white and beige adipocytes in all 6 subjects, mapping to 562 genes. Importantly, only 10% of these differentially spliced genes are also differentially expressed, indicating that alternative splicing constitutes an additional layer of gene expression regulation during beige adipocyte differentiation. Functional classification of alternative isoforms points to a gain of function for key thermogenic transcription factors such as PPARG and CITED1, and enzymes such as PEMT, or LPIN1. We find that a large majority of the splice variants arise from differential TSS usage, with beige-specific TSSs being enriched for PPARγ and MED1 binding compared to white-specific TSSs. Finally, we validate beige specific isoform expression at the protein level for two thermogenic regulators, PPARγ and PEMT.

Discussion

These results suggest that differential isoform expression through alternative TSS usage is an important regulatory mechanism for human adipocyte thermogenic specification.

Predicting functional UTR variants by integrating region-specific features

The untranslated region (UTR) of messenger ribonucleic acid (mRNA), including the 5'UTR and 3'UTR, plays a critical role in regulating gene expression and translation. Variants within the UTR can lead to changes associated with human traits and diseases; however, computational prediction of UTR variant effect is challenging. Current noncoding variant prediction mainly focuses on the promoters and enhancers, neglecting the unique sequence of the UTR and thereby limiting their predictive accuracy. In this study, using consolidated datasets of UTR variants from disease databases and large-scale experimental data, we systematically analyzed more than 50 region-specific features of UTR, including functional elements, secondary structure, sequence composition and site conservation. Our analysis reveals that certain features, such as C/G-related sequence composition in 5'UTR and A/T-related sequence composition in 3'UTR, effectively differentiate between nonfunctional and functional variant sets, unveiling potential sequence determinants of functional UTR variants. Leveraging these insights, we developed two classification models to predict functional UTR variants using machine learning, achieving an area under the curve (AUC) value of 0.94 for 5'UTR and 0.85 for 3'UTR, outperforming all existing methods. Our models will be valuable for enhancing clinical interpretation of genetic variants, facilitating the prediction and management of disease risk.

Rett syndrome diagnostic odyssey: Limitations of NextGen sequencing

Typical (or classic) Rett syndrome (RTT) is an X-linked neurodevelopmental disorder characterized by a period of regression, partial or complete loss of purposeful hand movements, and acquired speech, impaired gait, and stereotyped hand movements. In over 95% of typical RTT, a pathogenic variant is found in the methyl-CPG binding protein 2 gene (MECP2). Here, we describe a young woman with clinically diagnosed typical RTT syndrome who lacked a genetic diagnosis despite 20 years of investigation and multiple rounds of sequencing the MECP2 gene. Recently, additional genetic testing using next-generation sequencing was completed, which revealed a partial insertion of the BCL11A gene within exon 4 of MECP2, resulting in a small deletion in MECP2, causing likely disruption of MeCP2 function due to a frameshift. This case demonstrates the ever-changing limitations of genetic testing, as well as the importance of continual pursuit of a diagnosis as technologies improve and are more widely utilized.

Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Combining DNA and protein alignments to improve genome annotation with LiftOn

As the number and variety of assembled genomes continues to grow, the number of annotated genomes is falling behind, particularly for eukaryotes. DNA-based mapping tools help to address this challenge, but they are only able to transfer annotation between closely-related species. Here we introduce LiftOn, a homology-based software tool that integrates DNA and protein alignments to enhance the accuracy of genome-scale annotation and to allow mapping between relatively distant species. LiftOn's protein-centric algorithm considers both types of alignments, chooses optimal open reading frames, resolves overlapping gene loci, and finds additional gene copies where they exist. LiftOn can reliably transfer annotation between genomes representing members of the same species, as we demonstrate on human, mouse, honey bee, rice, and Arabidopsis thaliana. It can further map annotation effectively across species pairs as far apart as mouse and rat or Drosophila melanogaster and D. erecta.

CONSERVATION ASSESSMENT OF HUMAN SPLICE SITE ANNOTATION BASED ON A 470-GENOME ALIGNMENT

Despite many improvements over the years, the annotation of the human genome remains imperfect, and different annotations of the human reference genome sometimes contradict one another. The use of evolutionarily conserved sequences provides a strategy for selecting a high-confidence subset of the annotation that is more likely to be related to biological functions, and the rapidly growing number of genomes from other species increases its power. Using the latest whole genome alignment, we found that splice sites from protein-coding genes in the high-quality MANE annotation are consistently conserved across more than 400 species. We also studied splice sites from the RefSeq, GENCODE, and CHESS databases that are not present in MANE. We trained a logistic regression classifier to distinguish between the conservation exhibited by sites from MANE versus sites chosen randomly from neutrally evolving sequence. We found that splice sites classified by our model as conserved have lower SNP rates and better transcriptomic support. We then computed a subset of transcripts only using either "conserved" splice sites or ones from MANE. This subset is enriched in high-confidence transcripts of the major gene catalogs that appear to be under purifying selection and are more likely to be correct and functionally relevant.

Discovering Intron Gain Events in Humans through Large-Scale Evolutionary Comparisons

The rapid growth in the number of sequenced genomes makes it possible to search for the appearance of entirely new introns in the human lineage. In this study, we compared the genomic sequences for 19,120 human protein-coding genes to a collection of 3493 vertebrate genomes, mapping the patterns of intron alignments onto a phylogenetic tree. This mapping allowed us to trace many intron gain events to precise locations in the tree, corresponding to distinct points in evolutionary history. We discovered 584 intron gain events, all of them relatively recent, in 514 distinct human genes. Among these events, we explored the hypothesis that intronization was the mechanism responsible for intron gain. Intronization events were identified by locating instances where human introns correspond to exonic sequences in homologous vertebrate genes. Although apparently rare, we found three compelling cases of intronization, and for each of those we compared the human protein sequence and structure to homologous genes that lack the introns.

Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification

CRISPR base editing screens enable analysis of disease-associated variants at scale; however, variable efficiency and precision confounds the assessment of variant-induced phenotypes. Here, we provide an integrated experimental and computational pipeline that improves estimation of variant effects in base editing screens. We use a reporter construct to measure guide RNA (gRNA) editing outcomes alongside their phenotypic consequences and introduce base editor screen analysis with activity normalization (BEAN), a Bayesian network that uses per-guide editing outcomes provided by the reporter and target site chromatin accessibility to estimate variant impacts. BEAN outperforms existing tools in variant effect quantification. We use BEAN to pinpoint common regulatory variants that alter low-density lipoprotein (LDL) uptake, implicating previously unreported genes. Additionally, through saturation base editing of LDLR, we accurately quantify missense variant pathogenicity that is consistent with measurements in UK Biobank patients and identify underlying structural mechanisms. This work provides a widely applicable approach to improve the power of base editing screens for disease-associated variant characterization.

EMQN best practice guidelines for genetic testing in hereditary breast and ovarian cancer

Hereditary Breast and Ovarian Cancer (HBOC) is a genetic condition associated with increased risk of cancers. The past decade has brought about significant changes to hereditary breast and ovarian cancer (HBOC) diagnostic testing with new treatments, testing methods and strategies, and evolving information on genetic associations. These best practice guidelines have been produced to assist clinical laboratories in effectively addressing the complexities of HBOC testing, while taking into account advancements since the last guidelines were published in 2007. These guidelines summarise cancer risk data from recent studies for the most commonly tested high and moderate risk HBOC genes for laboratories to refer to as a guide. Furthermore, recommendations are provided for somatic and germline testing services with regards to clinical referral, laboratory analyses, variant interpretation, and reporting. The guidelines present recommendations where 'must' is assigned to advocate that the recommendation is essential; and 'should' is assigned to advocate that the recommendation is highly advised but may not be universally applicable. Recommendations are presented in the form of shaded italicised statements throughout the document, and in the form of a table in supplementary materials (Table S4). Finally, for the purposes of encouraging standardisation and aiding implementation of recommendations, example report wording covering the essential points to be included is provided for the most common HBOC referral and reporting scenarios. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories.

Evaluation of the pathogenic potential of germline DDX41 variants in hematopoietic neoplasms using the ACMG/AMP guidelines

Clinical use of gene panel testing for hematopoietic neoplasms in areas, such as diagnosis, prognosis prediction, and exploration of treatment options, has increased in recent years. The keys to interpreting gene variants detected in gene panel testing are to distinguish between germline and somatic variants and accurately determine whether the detected variants are pathogenic. If a variant is suspected to be a pathogenic germline variant, it is essential to confirm its consistency with the disease phenotype and gather a thorough family history. Donor eligibility must also be considered, especially if the patient's variant is also detected in the expected donor for hematopoietic stem cell transplantation. However, determining the pathogenicity of gene variants is often complicated, given the current limited availability of databases covering germline variants of hematopoietic neoplasms. This means that hematologists will frequently need to interpret gene variants themselves. Here, we outline how to assess the pathogenicity of germline variants according to criteria from the American College of Medical Genetics and Genomics/Association for Molecular Pathology standards and guidelines for the interpretation of variants using DDX41, a gene recently shown to be closely associated with myeloid neoplasms with a germline predisposition, as an example.

Complex balanced intrachromosomal rearrangement involving PITX2 identified as a cause of Axenfeld-Rieger Syndrome

Axenfeld-Rieger Syndrome (ARS) type 1 is a rare autosomal dominant condition characterized by anterior chamber anomalies, umbilical defects, dental hypoplasia, and craniofacial anomalies, with Meckel's diverticulum in some individuals. Here, we describe a clinically ascertained female of childbearing age with ARS for whom clinical targeted sequencing and deletion/duplication analysis followed by clinical exome and genome sequencing resulted in no pathogenic variants or variants of unknown significance in PITX2 or FOXC1. Advanced bioinformatic analysis of the genome data identified a complex, balanced rearrangement disrupting PITX2. This case is the first reported intrachromosomal rearrangement leading to ARS, illustrating that for patients with compelling clinical phenotypes but negative genomic testing, additional bioinformatic analysis are essential to identify subtle genomic abnormalities in target genes.

Differences in 5'untranslated regions highlight the importance of translational regulation of dosage sensitive genes

BACKGROUND

Untranslated regions (UTRs) are important mediators of post-transcriptional regulation. The length of UTRs and the composition of regulatory elements within them are known to vary substantially across genes, but little is known about the reasons for this variation in humans. Here, we set out to determine whether this variation, specifically in 5'UTRs, correlates with gene dosage sensitivity.

RESULTS

We investigate 5'UTR length, the number of alternative transcription start sites, the potential for alternative splicing, the number and type of upstream open reading frames (uORFs) and the propensity of 5'UTRs to form secondary structures. We explore how these elements vary by gene tolerance to loss-of-function (LoF; using the LOEUF metric), and in genes where changes in dosage are known to cause disease. We show that LOEUF correlates with 5'UTR length and complexity. Genes that are most intolerant to LoF have longer 5'UTRs, greater TSS diversity, and more upstream regulatory elements than their LoF tolerant counterparts. We show that these differences are evident in disease gene-sets, but not in recessive developmental disorder genes where LoF of a single allele is tolerated.

CONCLUSIONS

Our results confirm the importance of post-transcriptional regulation through 5'UTRs in tight regulation of mRNA and protein levels, particularly for genes where changes in dosage are deleterious and lead to disease. Finally, to support gene-based investigation we release a web-based browser tool, VuTR, that supports exploration of the composition of individual 5'UTRs and the impact of genetic variation within them.

Guidelines for releasing a variant effect predictor

Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs. Emphasising open-source availability, transparent methodologies, clear variant effect score interpretations, standardised scales, accessible predictions, and rigorous training data disclosure, we aim to improve the usability and interpretability of VEPs, and promote their integration into analysis and evaluation pipelines. We also provide a large, categorised list of currently available VEPs, aiming to facilitate the discovery and encourage the usage of novel methods within the scientific community.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

A gene pathogenicity tool "GenePy" identifies missed biallelic diagnoses in the 100,000 Genomes Project

PURPOSE

The 100,000 Genomes Project diagnosed a quarter of affected participants, but 26% of diagnoses were not on the applied gene panel(s); with many being de novo variants. Assessing biallelic variants without a gene panel is more challenging.

METHODS

We sought to identify missed biallelic diagnoses using GenePy, which incorporates allele frequency, zygosity, and a user-defined deleterious metric, generating an aggregate GenePy score per gene, per participant. We calculated GenePy scores for 2862 recessive disease genes in 78,216 100,000 Genomes Project participants. For each gene, we ranked participant GenePy scores and scrutinized affected participants without a diagnosis, whose scores ranked among the top 5 for each gene. In cases which participant phenotypes overlapped with the disease gene of interest, we extracted rare variants and applied phase, ClinVar, and ACMG classification.

RESULTS

3184 affected individuals without a molecular diagnosis had a top-5-ranked GenePy score and 682 of 3184 (21%) had phenotypes overlapping with a top-ranking gene. In 122 of 669 (18%) phenotype-matched cases (excluding 13 withdrawn participants), we identified a putative missed diagnosis (2.2% of all undiagnosed participants). A further 334 of 669 (50%) cases have a possible missed diagnosis but require functional validation.

CONCLUSION

Applying GenePy at scale has identified 456 potential diagnoses, demonstrating the value of novel diagnostic strategies.

Upstream open reading frames may contain hundreds of novel human exons

Several recent studies have presented evidence that the human gene catalogue should be expanded to include thousands of short open reading frames (ORFs) appearing upstream or downstream of existing protein-coding genes, each of which would comprise an additional bicistronic transcript in humans. Here we explore an alternative hypothesis that would explain the translational and evolutionary evidence for these upstream ORFs without the need to create novel genes or bicistronic transcripts. We examined 2,199 upstream ORFs that have been proposed as high-quality candidates for novel genes, to determine if they could instead represent protein-coding exons that can be added to existing genes. We checked for the conservation of these ORFs in four recently sequenced, high-quality human genomes, and found a large majority (87.8%) to be conserved in all four as expected. We then looked for splicing evidence that would connect each upstream ORF to the downstream protein-coding gene at the same locus, thus creating a novel splicing variant using the upstream ORF as its first exon. These protein coding exon candidates were further evaluated using protein structure predictions of the protein sequences that included the proposed new exons. We determined that 582 out of 2,199 upstream ORFs have strong evidence that they can form protein coding exons that are part of an existing gene, and that the resulting protein is predicted to have similar or better structural quality than the currently annotated isoform.