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Zeng, T.

Publications and source records attributed to Zeng, T..

At least 37 records · Page 2Linked to original sources

Deciphering the Cell Specific Transcript Heterogeneity and Alternative Splicing during the Early Embryonic Development of Zebrafish

Cell fate determination during early embryonic development is a complex process modulated by gene expression. The intricate interplay of transcriptional and post-transcriptional regulation is integral to the developmental trajectory of embryogenesis, yet how RNA processing may contribute to early development programming is largely elusive. Leveraging recent technological advances in single-molecule nanopore sequencing, we developed a single-cell long-read transcriptome sequencing technology, allowing a clear view of transcript diversity during zebrafish embryogenesis during pre- and post-zygotic genome activation (ZGA). A closer examination of the dynamic transcript usage and potential alternative splicing revealed that abundant stage-specific transcripts with differential coding potentials are involved in distinct biological functions. Specifically, we identified two cell populations at the onset of ZGA based on isoform diversity instead of gene profiling, which followed divergent developmental trajectories toward the ectoderm and the presumptive ectoderm. These two populations of cells were characterized by divergent splicing regulations linked to differential RNA-binding proteins, including SNRPA and SFPQ. Altogether, using the single-cell long-read transcriptome sequencing strategy, we work has revealed the cell-specific transcriptome dynamics contributing to the cell fate determination during embryogenesis.

developmental biology↗

Telomere-to-telomere African wild rice (Oryza longistaminata) reference genome reveals segmental and structural variation

Rice (Oryza sativa) is one of the most important staple food crops worldwide, and its wild relatives serve as an important gene pool in its breeding. Compared with cultivated rice species, African wild rice (Oryza longistaminata) has several advantageous traits, such as resistance to increased biomass production, clonal propagation via rhizomes, and biotic stresses. However, previous O. longistaminata genome assemblies have been hampered by gaps and incompleteness, restricting detailed investigations into their genomes. To streamline breeding endeavors and facilitate functional genomics studies, we generated a 343-Mb telomere-to-telomere (T2T) genome assembly for this species, covering all telomeres and centromeres across the 12 chromosomes. This newly assembled genome has markedly improved over previous versions. Comparative analysis revealed a high degree of synteny with previously published genomes. A large number of structural variations were identified between the O. longistaminata and O. sativa. A total of 2,466 segmentally duplicated genes were identified and enriched in cellular amino acid metabolic processes. We detected a slight expansion of some subfamilies of resistance genes and transcription factors. This newly assembled T2T genome of O. longistaminata provides a valuable resource for the exploration and exploitation of beneficial alleles present in wild relative species of cultivated rice.

genomics↗

Efficiently Constructing Complete Genomes with CycloneSEQ to Fill Gaps in Bacterial Draft Assemblies

BackgroundCurrent microbial sequencing relies on short-read platforms like Illumina and DNBSEQ, favored for their low cost and high accuracy. However, these methods often produce fragmented draft genomes, hindering comprehensive bacterial function analysis. CycloneSEQ, a novel long-read sequencing platform developed by BGI-Research, its sequencing performance and assembly improvements has been evaluated. FindingsUsing CycloneSEQ long-read sequencing, the type strain produced long reads with an average length of 11.6 kbp and an average quality score of 14.4. After hybrid assembly with short reads data, the assembled genome exhibited an error rate of only 0.04 mismatches and 0.08 indels per 100 kbp compared to the reference genome. This method was validated across 9 diverse species, successfully assembling complete circular genomes. Hybrid assembly significantly enhances genome completeness by using long reads to fill gaps and accurately assemble multi-copy rRNA genes, which unable be achieved by short reads solely. Through data subsampling, we found that over 500 Mbp of short-read data combined with 100 Mbp of long-read data can result in a high-quality circular assembly. Additionally, using CycloneSEQ long reads effectively improves the assembly of circular complete genomes from mixed microbial communities. ConclusionsCycloneSEQs read length is sufficient for circular bacterial genomes, but its base quality needs improvement. Integrating DNBSEQ short reads improved accuracy, resulting in complete and accurate assemblies. This efficient approach can be widely applied in microbial sequencing.

genomics↗

A single-molecule nanopore sequencing platform

Nanopore sequencing, a third-generation sequencing technology, has revolutionized the gene sequencing industry with its advantages of long reads, fast speed, real-time sequencing and analysis, and potential in detecting base modifications. This technology allows researchers to sequence longer DNA fragments in a single read, providing more comprehensive genomic information compared to previous methods. Nanopore sequencing operates on electrical signals generated by a nanopore embedded in a membrane separating two electrolyte-filled chambers. When single-stranded DNA (ssDNA) passes through the nanopore, it creates variations in the current that correspond to different DNA bases. By analyzing these current fluctuations with machine learning algorithms, the DNA sequence can be determined. In this study, we introduced several improvements to nanopore sequencing, including nanopore local chemistry sequencing, novel motor and pore proteins, chip design, and basecalling algorithms. Our new nanopore sequencing platform, CycloneSEQ, demonstrated long-duration sequencing (107 hours) on a single chip with high yield (>50 Gb). In human genomic DNA sequencing, CycloneSEQ was able to produce long reads with N50 33.6 kb and modal identity 97.0%. Preliminary findings on human whole-genome de novo assembly, variant calling, metagenomics sequencing, and single-cell RNA sequencing have further highlighted CycloneSEQs potential across different areas of genomics.

genomics↗

Geometry representations along visual pathways in human spatial navigation

The representation of geometric structures of ones surroundings is key to self-localization during human spatial navigation. However, the spatial organization of geometry representation in the visual system has not been fully characterized. By modeling the synchronized brain activity from participants watching navigational videos from identical realistic virtual environments under different weather and lighting conditions, we found a compact representation of egocentric 3D scene geometric structures is present in a widespread network of brain regions. These regions carrying geometry-related signals form three parallel pathways, which we collectively refer to as "geometry visual pathways", starting from the primary visual cortex: the dorsal and medial pathways end in the intraparietal areas, while the ventral pathway arrives at the hippocampus via the parahippocampal gyrus. The synchronized neural activity in the identified geometry visual pathways allows for reliable decoding of the 3D scene geometric structures. Furthermore, road types, a more abstract representation of the route geometry, are encoded in overlapping pathways, distinctly absent from early visual cortex (V1, V2, V3). In addition to complementing the classical "what" and "where" dichotomy, the identified brain-wide geometry visual pathways narrow a critical gap in understanding how the brain constructs cognitive maps from visual inputs.

neuroscience↗

Genomic evolution reshapes cell type diversification in the amniote brain

Over 320 million years of evolution, amniotes have developed complex brains and cognition through largely unexplored genetic and gene expression mechanisms. We created a comprehensive single-cell atlas of over 1.3 million cells from the telencephalon and cerebellum of turtles, zebra finches, pigeons, mice, and macaques, employing single-cell resolution spatial transcriptomics to validate gene expression patterns across species. Our study revealed significant species-specific variations in cell types, highlighting their conservation and diversification in evolution. We found pronounced differences in telencephalon excitatory neurons (EX) and cerebellar cell types between birds and mammals. Birds predominantly express SLC17A6 in EX, whereas mammals expressed SLC17A7 in neocortex and SLC17A6 elsewhere, possibly due to loss of SLC17A7 function loss in birds. Additionally, we identified a novel bird-specific Purkinje cell subtype (SVIL+), implicating the LSD11/KDM1A pathway in learning and circadian rhythms, and related numerous positively selected genes in birds, suggesting an evolutionary optimization of cerebellar functions for ecological and behavioral adaptation. Our findings elucidate the complex interplay between genetic evolution and environmental adaptation, underscoring the role of genetic diversification in the development of specialized cell types across amniotes.

evolutionary biology↗

Targeting oncogenic K-Ras mutants with a small-molecule degrader through Nedd4-1

K-Ras mutations represent a most prevalent oncogenic alteration in human cancers. Despite of tremendous efforts, it remains a big challenge to develop inhibitors that can target the oncogenic K-Ras mutants, especially mutants without specific active or charged side chains such as K-RasG12V. Here, taking advantage of our previous finding that Nedd4-1 is a bona fide E3 ubiquitin ligase for wild-type Ras proteins, we developed a compound XMU-MP-9 that can promote ubiquitination and degradation of various K-Ras mutants including K-RasG12V, and significantly inhibit proliferation and tumor development of K-Ras mutant harboring cells. Mechanistically, XMU-MP-9 acts as a bifunctional compound to bind the C2 domain of Nedd4-1 and an allosteric site of K-Ras to enhance Nedd4-1 and K-Ras interaction, and to induce a conformational change of Nedd4-1/K-Ras complex to allow Nedd4-1 targeting K128 of K-Ras for ubiquitination. Hence, our study presents a robust strategy to develop small-molecule degrader of K-Ras mutants, and also sheds light on the development of small-molecule degraders for H-Ras and N-Ras mutants.

cancer biology↗

Multiple Omics Find New Cecal Microbial Features Associated with Feed Efficiency in Ducks

As the global population continues to grow exponentially, the competition for resources between livestock and humans has become increasingly intense. Breeding efficient animal breeds, fully utilizing feed resources, and reducing environmental damage are major challenges facing the livestock industry. To address these issues, enhancing the feed utilization efficiency in the poultry industry is crucial. Recent studies have elucidated the pivotal role of gut microbiota in modulating the feeding behavior of their host organisms. Thus, we used metagenomics, transcriptomics, and metabolomics to explore how the intestinal microbiome affects the feed utilization efficiency in ducks. Our metagenomic analysis revealed a significant up-regulation of Elusimicrobiota at the phylum level within the high residual feed intake (HRFI) group, in comparison to the low residual feed intake (LRFI) group. Additionally, functional analysis using Clusters of Orthologous Groups of proteins (COG) indicated prominent disparities in the category of secondary metabolites biosynthesis, transport, and catabolism between the HRFI and LRFI groups. Furthermore, our metabolomics investigation identified an upregulated expression of the secondary metabolite 15-deoxy-{Delta}12,14-prostaglandin J2 (15d-PGJ2) in the HRFI group compared to the LRFI group. Liver transcriptome analysis identified prostaglandin-endoperoxide synthase 2 (PTGS2) as a key hub gene, exerting significant regulatory influence within the arachidonic acid pathway. Notably, the metabolite 15d-PGJ2 is a terminal product in the metabolic pathway of arachidonic acid. The correlation analysis between the cecal microbiota and differential metabolites revealed a significant negative correlation between Elusimicrobiota and the metabolite 15d-PGJ2. In summary, we assumed that the intestinal microbiome Elusimicrobiota regulates the expression of the PTGS2 gene, consequently inducing variations in PTGS2 efficiency between the HRFI and LRFI groups, ultimately leading to diverse residual feed intake levels in ducks. IMPORTANCEThis investigation utilizes metabolomics to elucidate the interplay between genes and microbiome communities. We present evidence of disparities in the composition of microbial consortia among ducks RFI, alongside identification of pivotal genes within the liver that potentially modulate RFI. These results provide novel perspectives on the processes through which the cecum and liver influence RFI.

microbiology↗

Detecting phenotype-specific tumor microenvironment by merging bulk and single cell expression data to spatial transcriptomics

In addressing the limitations of current multimodal analysis methods that largely ignore phenotypic data, leading to a lack of biological interpretability at the phenotypic level, we developed the Single-Cell and Tissue Phenotype prediction (SCTP), a deep-learning-based multimodal fusion framework. SCTP can simultaneously detect phenotype-specific cells and characterize the tumor microenvironment of pathological tissue by integrating essential information from the bulk sample phenotype, the composition of individual cells, and the spatial distribution of cells. Upon evaluating SCTPs efficiency and robustness against traditional analytical methods, we developed a specialized model, SCTP-CRC, tailored for colorectal cancer (CRC). This model integrates RNA-seq, scRNA-seq, and spatial transcriptomic data to offer a better understanding of CRC. SCTP-CRC has proven effective in accurately identifying tumor-associated cells and clusters and continuously defines boundary regions as well as the spatial organization of the entire tumor microenvironment. This enables a detailed depiction of cellular communication networks, capturing the dynamic shifts that occur during tumor progression. Furthermore, SCTP-CRC extends to the identification of abnormal sub-regions in the early state of CRC and uncovers potential early-warning signature genes such as MMP2, IGKC, and PIGR. These biomarkers are not only important in recognizing the onset of CRC but may also play a crucial role in differentiating between CRC-derived liver metastases and primary liver tumors. SCTP stands as a transformative framework, offering a deeper understanding of the tumor microenvironment through its ability to quantitatively characterize cancers fundamental traits and dissect the intricate molecular and cellular interactions at play. This comprehensive insight supports the early diagnosis and enables personalized treatment strategies, marking a significant stride toward improving patient outcomes and tailoring therapies to individual disease profiles.

bioinformatics↗

Unraveling the gut microbiota of Tibetan chickens: insights into highland adaptation and ecological advantages

Tibetan animals have several unique advantages owing to the harsh ecological conditions under which they live. Tibetan mammals have been studied extensively. However, understanding of the advantages and underlying mechanisms of the representative high-latitude bird, the Tibetan chicken (Gallus gallus, TC), remains limited. The gut microbiota of animals has been conclusively shown to be closely related to both host health and host environmental adaptation. This study aimed to explore the relationships between the cecal microbiome and the advantages of TCs based on comparisons among three populations: native TCs residing on the plateau, domestic TCs living in the plain, and one native plain species. Metatranscriptomic sequencing revealed a significant enrichment of active Bacteroidetes but a loss of active Firmicutes in native TCs. Additionally, the upregulated expression of genes in the cecal microbiome of native TCs showed enriched pathways related to energy metabolism, glycan metabolism, and the immune response. Furthermore, the expression of genes involved in the biosynthesis of short-chain fatty acids (SCFAs) and secondary bile acids (SBAs) was upregulated in the cecal microbiome of native TCs. Data from targeted metabolomics further confirmed elevated levels of certain SCFAs and SBAs in the cecum of native TCs. Based on the multi-omics association analysis, we proposed that the higher ratio of active Bacteroidetes/Firmicutes may be attributed to the efficient energy metabolism and stronger immunological activity of native TCs. Our findings provide a better understanding of the interactions between gut microbiota and highland adaptation, and novel insights into the mechanisms by which Tibetan chickens adapt to the plateau hypoxic environment. IMPORTANCEThe composition and function of the active cecal microbiome were significantly different between the plateau Tibetan chicken population and the plain chicken population. Higher expression genes related to energy metabolism and immune response were found in the cecal microbiome of the plateau Tibetan chicken population. The cecal microbiome in the plateau Tibetan chicken population exhibited higher biosynthesis of short-chain fatty and secondary bile acids, resulting in higher cecal content of these metabolites. The active Bacteroidetes/Firmicutes ratio in the cecal microbiome may contribute to the high-altitude adaptive advantage of the plateau Tibetan chicken population.

microbiology↗

Landscape of Large-Scale Somatic Genomic Insertions in Non-Small Cell Lung Carcinoma Revealed by Nanopore Sequencing

Previous NSCLC genomic studies were mostly based on the next-generation sequencing of short reads, which is an efficient approach for identifying single nucleotide variants and small indels but ineffective for identifying structural variants, especially large-scale insertions. Here, we studied 151 lung adenocarcinoma (LUAD) and 106 lung squamous cell carcinoma (LUSC) samples and paired blood samples using nanopore sequencing technology. We developed a rigorous computational pipeline and characterized the landscape of large-scale somatic insertions in NSCLC. Combining other omics data, we report three findings: 1. we identified an LUSC-enriched somatic simple repeat expansion shared by approximately 40% of LUSC patients that regulates PTPRZ1 gene expression through distal enhancers; 2. the somatic insertion of transposable elements (TEs) in NSCLC were mostly complex TEs consisting of multiple TE elements; and 3. the insertion of short interspersed nuclear elements, especially from the Alu family in young lineages, is a frequent somatic mutation type that shapes the transcriptome of NSCLC through the expression of these elements.

genomics↗

The type of DNA damage response after Decitabine treatment depends on the level of DNMT activity

Decitabine and Azacytidine are considered as epigenetic drugs that induce DNA- methyltransferase (DNMT)-DNA crosslinks, resulting in DNA-hypomethylation and -damage. Although they are applied against myeloid cancers, important aspects of their mode of action remain unknown, which highly limits their clinical potential. Using a combinatorial approach, we reveal that the efficacy profile of both compounds primarily depends on the level of induced DNA-damage. Under low DNMT-activity, only Decitabine has a substantial impact. Conversely, when DNMT-activity is high, toxicity and cellular response to both compounds are dramatically increased, but do not primarily depend on DNA-hypomethylation or RNA-associated processes, contradicting an RNA-dependent effect of Azacytidine. By applying spatial proteomics, we show that Decitabine induces a strictly DNMT-dependent multifaceted DNA- damage response based on chromatin-recruitment of various repair-associated proteins. The choice of DNA-repair pathway herby depends on the severity of Decitabine-induced DNA- lesions. While mismatch (MMR) and base-excision DNA repair (BER) as well as RAD50- dependent DNA double-strand break repair are always activated in response to Decitabine, Fanconi anemia-dependent DNA-repair combined with homologous recombination is only activated when DNMT-activity is moderate. In contrast, high DNMT-activity and therefore immense replication stress, induce DNA repair by non-homologous and alternative end-joining.

biochemistry↗

In-vivo whole-cortex estimation of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here we non-invasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically-plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the GABA-agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 years old) and Asian (7.2 to 7.9 years old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth. SignificanceHealthy brain function requires a delicate balance of neural excitation (E) and inhibition (I). In animals, this balance - the E/I ratio - is known to decrease with the maturation of inhibitory circuitry during healthy development. However, in humans, the normative development of cortex-wide E/I ratio remains unclear. Here, we use a biophysical model and non-invasive brain scans to estimate a marker of E/I ratio. Spatial changes in our E/I ratio marker are consistent with a drug that decreases E/I ratio. We also find that our cortex-wide E/I ratio marker decreases during development. Furthermore, North American and Asian children with lower E/I ratio, especially in higher-order cortex, have better cognitive performance. Overall, E/I ratio is a potential index of healthy neurocognitive development.

neuroscience↗

Scaling the Discrete-time Wright Fisher model to biobank-scale datasets

The Discrete-Time Wright Fisher (DTWF) model and its large population diffusion limit are central to population genetics. These models describe the forward-in-time evolution of the frequency of an allele in a population and can include the fundamental forces of genetic drift, mutation, and selection. Computing like-lihoods under the diffusion process is feasible, but the diffusion approximation breaks down for large sample sizes or in the presence of strong selection. Unfortunately, existing methods for computing likelihoods under the DTWF model do not scale to current exome sequencing sample sizes in the hundreds of thousands. Here we present an algorithm that approximates the DTWF model with provably bounded error and runs in time linear in the size of the population. Our approach relies on two key observations about Binomial distributions. The first is that Binomial distributions are approximately sparse. The second is that Binomial distributions with similar success probabilities are extremely close as distributions, allowing us to approximate the DTWF Markov transition matrix as a very low rank matrix. Together, these observations enable matrix-vector multiplication in linear (as opposed to the usual quadratic) time. We prove similar properties for Hypergeometric distributions, enabling fast computation of likelihoods for subsamples of the population. We show theoretically and in practice that this approximation is highly accurate and can scale to population sizes in the billions, paving the way for rigorous biobank-scale population genetic inference. Finally, we use our results to estimate how increasing sample sizes will improve the estimation of selection coefficients acting on loss-of-function variants. We find that increasing sample sizes beyond existing large exome sequencing cohorts will provide essentially no additional information except for genes with the most extreme fitness effects.

evolutionary biology↗

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ~25% of genes, potentially causing important pathogenic mutations to be over-looked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

genetics↗

Duck pan-genome reveals two transposon-derived structural variations caused bodyweight enlarging and white plumage phenotype formation during evolution

Structural variations (SVs) are a major source of domestication and improvement traits, however SV profiles of duck and their phenotypic impacts largely hidden. We present the first duck pan-genome constructed using five genome assemblies capturing [~]40.98 Mb new sequences. This pan-genome together with high-depth sequencing data ([~]46.5X) identified 101,041 SVs, of which substantial proportions were derived from transposable element (TE) activity. Many TE-derived SVs anchoring in a gene body or regulatory region are linked to ducks domestication and improvement. By combining quantitative genetics with molecular experiments, we dissect how TE-derived SVs change gene expression of IGF2BP1 and generate a novel transcript of MITF, shaping bodyweight and white plumage. In the IGF2BP1 locus, the TE-derived SV explains the largest effect on bodyweight among avian species (27.61% of phenotypic variation). Our findings highlight the importance of using a pan-genome as a reference in genomics studies and explore the roles of TE-derived SVs in trait formation and in livestock breeding.

genetics↗

Mapping the convergence of genes for coronary artery disease onto endothelial cell programs

Genome-wide association studies (GWAS) have discovered thousands of risk loci for common, complex diseases, each of which could point to genes and gene programs that influence disease. For some diseases, it has been observed that GWAS signals converge on a smaller number of biological programs, and that this convergence can help to identify causal genes1-6. However, identifying such convergence remains challenging: each GWAS locus can have many candidate genes, each gene might act in one or more possible programs, and it remains unclear which programs might influence disease risk. Here, we developed a new approach to address this challenge, by creating unbiased maps to link disease variants to genes to programs (V2G2P) in a given cell type. We applied this approach to study the role of endothelial cells in the genetics of coronary artery disease (CAD). To link variants to genes, we constructed enhancer-gene maps using the Activity-by-Contact model7,8. To link genes to programs, we applied CRISPRi-Perturb-seq9-12 to knock down all expressed genes within {+/-}500 Kb of 306 CAD GWAS signals13,14 and identify their effects on gene expression programs using single-cell RNA-sequencing. By combining these variant-to-gene and gene-to-program maps, we find that 43 of 306 CAD GWAS signals converge onto 5 gene programs linked to the cerebral cavernous malformations (CCM) pathway--which is known to coordinate transcriptional responses in endothelial cells15, but has not been previously linked to CAD risk. The strongest regulator of these programs is TLNRD1, which we show is a new CAD gene and novel regulator of the CCM pathway. TLNRD1 loss-of-function alters actin organization and barrier function in endothelial cells in vitro, and heart development in zebrafish in vivo. Together, our study identifies convergence of CAD risk loci into prioritized gene programs in endothelial cells, nominates new genes of potential therapeutic relevance for CAD, and demonstrates a generalizable strategy to connect disease variants to functions.

genomics↗

Predicting RNA splicing from DNA sequence using Pangolin

Recent progress in deep learning approaches have greatly improved the prediction of RNA splicing from DNA sequence. Here, we present Pangolin, a deep learning model to predict splice site strength in multiple tissues that has been trained on RNA splicing and sequence data from four species. Pangolin outperforms state of the art methods for predicting RNA splicing on a variety of prediction tasks. We use Pangolin to study the impact of genetic variants on RNA splicing, including lineage-specific variants and rare variants of uncertain significance. Pangolin predicts loss-of-function mutations with high accuracy and recall, particularly for mutations that are not missense or nonsense (AUPRC = 0.93), demonstrating remarkable potential for identifying pathogenic variants.

genomics↗