GENCODE: the reference human genome annotation for The ENCODE Project

Dynamic Foxp3-chromatin interaction controls tunable Treg cell function

Nuclear factor Foxp3 determines regulatory T (Treg) cell fate and function via mechanisms that remain unclear. Here, we investigate the nature of Foxp3-mediated gene regulation in suppressing autoimmunity and antitumor immune response. Contrasting with previous models, we find that Foxp3-chromatin binding is regulated by Treg activation states, tumor microenvironment, and antigen and cytokine stimulations. Proteomics studies uncover dynamic proteins within Foxp3 proximity upon TCR or IL-2 receptor signaling in vitro, reflecting intricate interactions among Foxp3, signal transducers, and chromatin. Pharmacological inhibition and genetic knockdown experiments indicate that NFAT and AP-1 protein Batf are required for enhanced Foxp3-chromatin binding in activated Treg cells and tumor-infiltrating Treg cells to modulate target gene expression. Furthermore, mutations at the Foxp3 DNA-binding domain destabilize the Foxp3-chromatin association. These representative settings delineate context-dependent Foxp3-chromatin interaction, suggesting that Foxp3 associates with chromatin by hijacking DNA-binding proteins resulting from Treg activation or differentiation, which is stabilized by direct Foxp3-DNA binding, to dynamically regulate Treg cell function according to immunological contexts.

Predicting regulatory mutations and their target genes by new computational integrative analysis: A study of follicular lymphoma

Mutations in DNA regulatory regions are increasingly being recognized as important drivers of cancer and other complex diseases. These mutations can regulate gene expression by affecting DNA-protein binding and epigenetic profiles, such as DNA methylation in genome regulatory elements. However, identifying mutation hotspots associated with expression regulation and disease progression in non-coding DNA remains a challenge. Unlike most existing approaches that assign a mutation score to individual single nucleotide polymorphisms (SNP), a mutation block (MB)-based approach was introduced in this study to assess the collective impact of a cluster of SNPs on transcription factor-DNA binding affinity, differential gene expression (DEG), and nearby DNA methylation. Moreover, the long-distance target genes of functional MBs were identified using a new permutation-based algorithm that assessed the significance of correlations between DNA methylation at regulatory regions and target gene expression. Two new Python packages were developed. The Differential Methylation Region (DMR-analysis) analysis tool was used to detect DMR and map them to regulatory elements. The second tool, an integrated DMR, DEG, and SNP analysis tool (DDS-analysis), was used to combine the omics data to identify functional MBs and long-distance target genes. Both tools were validated in follicular lymphoma (FL) cohorts, where not only known functional MBs and their target genes (BCL2 and BCL6) were recovered, but also novel genes were found, including CDCA4 and JAG2, which may be associated with FL development. These genes are linked to target gene expression and are significantly correlated with the methylation of nearby DNA sequences in FL. The proposed computational integrative analysis of multiomics data holds promise for identifying regulatory mutations in cancer and other complex diseases.

Transposable elements contribute to tissue-specific gene regulation in humans

BACKGROUND

Transposable elements (TEs) contribute to approximately half of the human genome, and along with many other functions, they have been known to play a role in gene regulation in the genome. With TEs' active/repressed states varying across tissue and cell types, they have the potential to regulate gene expression in a tissue-specific manner.

OBJECTIVE AND METHODS

To provide a systematic analysis of TEs' contribution in tissue-specific gene regulation, we examined the regulatory elements and genes in association with TE-derived regulatory sequences in 14 human cell lines belonging to 10 different tissue types using the functional genomics data from the ENCODE project. Specifically, we separately analyzed regulatory regions identified by three different approaches (DNase hypersensitive sites (DHS), histone active sites (HA), and histone repressive sites (HR)).

RESULTS

These regulatory regions showed to be distinct from each other by sharing less than 2.5% among all three types and more than 95% showed to be cell line-specific. Despite a lower total TE content overall than the genome average, each regulatory sequence type showed enrichment for one or two specific TE type(s): DHS for long terminal repeats (LTRs) and DNA transposons, HA for short interspersed nucleotide elements (SINEs), and HR for LTRs. In contrast, SINE was shown to be overrepresented in all three types of regulatory sequences located in gene-neighboring regions. TE-regulated genes were mostly shown to have cell line specific pattern, and tissue-specific genes (TSGs) showed higher usage of TE regulatory sequences in the tissue of their expression. While TEs in the regulatory sequences showed to be older than their genome-wide counterparts, younger TEs were shown to be more likely used in cell line specific regulatory sequences.

CONCLUSIONS

Collectively, our study provided further evidence enforcing an important contribution of TEs to tissue-specific gene regulation in humans.

Transformers and large language models in healthcare: A review

With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications. Transformer is a type of deep learning architecture initially developed to solve general-purpose Natural Language Processing (NLP) tasks and has subsequently been adapted in many fields, including healthcare. In this survey paper, we provide an overview of how this architecture has been adopted to analyze various forms of healthcare data, including clinical NLP, medical imaging, structured Electronic Health Records (EHR), social media, bio-physiological signals, biomolecular sequences. Furthermore, which have also include the articles that used the transformer architecture for generating surgical instructions and predicting adverse outcomes after surgeries under the umbrella of critical care. Under diverse settings, these models have been used for clinical diagnosis, report generation, data reconstruction, and drug/protein synthesis. Finally, we also discuss the benefits and limitations of using transformers in healthcare and examine issues such as computational cost, model interpretability, fairness, alignment with human values, ethical implications, and environmental impact.

Advances of long non-coding RNAs in osteoclast differentiation and osteoporosis

INTRODUCTION

Osteoclasts, which are responsible for bone resorption, are specialized multinucleated cells generated from monocyte/macrophage progenitor cells or hematopoietic stem cells (HSCs). Physiological bone remodeling can become pathological, such as osteoporosis, when osteoclastogenesis is out of balance. Thousands of long noncoding RNAs (lncRNAs) influence important molecular and biological processes. Recent research has revealed gene expression regulation function that numerous lncRNAs regulate nuclear domain organization, genome stability. Furthermore, the research of lncRNAs has substantial clinical implications for the treatment of existing and new diseases.

AREAS COVERED

In this review, we gather the most recent research on lncRNAs and their potential for basic research and clinical applications in osteoclast and osteoporosis. We also discuss the findings here in order to fully understand the role of lncRNAs in osteoclast differentiation and osteoporosis, as well as to provide a solid basis for future research exploring associated mechanisms and treatments.

EXPERT OPINION

LncRNA has been considered as an important role in the regulation of osteoclast differentiation and osteoporosis. It is exciting to investigate pathophysiological processes in osteoporosis and the therapeutic potential of lncRNAs. We hope that this review will offer promising prospects for the development of precision and individualized approaches to treatment.

Expanding the genetic and phenotypic landscape of replication factor C complex-related disorders: RFC4 deficiency is linked to a multisystemic disorder

The precise regulation of DNA replication is vital for cellular division and genomic integrity. Central to this process is the replication factor C (RFC) complex, encompassing five subunits, which loads proliferating cell nuclear antigen onto DNA to facilitate the recruitment of replication and repair proteins and enhance DNA polymerase processivity. While RFC1's role in cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS) is known, the contributions of RFC2-5 subunits on human Mendelian disorders is largely unexplored. Our research links bi-allelic variants in RFC4, encoding a core RFC complex subunit, to an undiagnosed disorder characterized by incoordination and muscle weakness, hearing impairment, and decreased body weight. We discovered across nine affected individuals rare, conserved, predicted pathogenic variants in RFC4, all likely to disrupt the C-terminal domain indispensable for RFC complex formation. Analysis of a previously determined cryo-EM structure of RFC bound to proliferating cell nuclear antigen suggested that the variants disrupt interactions within RFC4 and/or destabilize the RFC complex. Cellular studies using RFC4-deficient HeLa cells and primary fibroblasts demonstrated decreased RFC4 protein, compromised stability of the other RFC complex subunits, and perturbed RFC complex formation. Additionally, functional studies of the RFC4 variants affirmed diminished RFC complex formation, and cell cycle studies suggested perturbation of DNA replication and cell cycle progression. Our integrated approach of combining in silico, structural, cellular, and functional analyses establishes compelling evidence that bi-allelic loss-of-function RFC4 variants contribute to the pathogenesis of this multisystemic disorder. These insights broaden our understanding of the RFC complex and its role in human health and disease.

Mining alternative splicing patterns in scRNA-seq data using scASfind

Single-cell RNA-seq (scRNA-seq) is widely used for transcriptome profiling, but most analyses focus on gene-level events, with less attention devoted to alternative splicing. Here, we present scASfind, a novel computational method to allow for quantitative analysis of cell type-specific splicing events using full-length scRNA-seq data. ScASfind utilizes an efficient data structure to store the percent spliced-in value for each splicing event. This makes it possible to exhaustively search for patterns among all differential splicing events, allowing us to identify marker events, mutually exclusive events, and events involving large blocks of exons that are specific to one or more cell types.

Reinventing gene expression connectivity through regulatory and spatial structural empowerment via principal node aggregation graph neural network

The intricacies of the human genome, manifested as a complex network of genes, transcend conventional representations in text or numerical matrices. The intricate gene-to-gene relationships inherent in this complexity find a more suitable depiction in graph structures. In the pursuit of predicting gene expression, an endeavor shared by predecessors like the L1000 and Enformer methods, we introduce a novel spatial graph-neural network (GNN) approach. This innovative strategy incorporates graph features, encompassing both regulatory and structural elements. The regulatory elements include pair-wise gene correlation, biological pathways, protein-protein interaction networks, and transcription factor regulation. The spatial structural elements include chromosomal distance, histone modification and Hi-C inferred 3D genomic features. Principal Node Aggregation models, validated independently, emerge as frontrunners, demonstrating superior performance compared to traditional regression and other deep learning models. By embracing the spatial GNN paradigm, our method significantly advances the description of the intricate network of gene interactions, surpassing the performance, predictable scope, and initial requirements set by previous methods.

Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

Aberrant DNA methylation patterns have been used for cancer detection. However, DNA hemi-methylation, present at about 10% CpG dinucleotides, has been less well studied. Here we show that a majority of differentially hemi-methylated regions (DHMRs) in liver tumor DNA or plasma cells free (cf) DNA do not overlap with differentially methylated regions (DMRs) of the same samples, indicating that DHMRs could serve as independent biomarkers. Furthermore, we analyzed the cfDNA methylomes of 215 samples from individuals with liver or brain cancer and individuals without cancer (controls), and trained machine learning models using DMRs, DHMRs or both. The models incorporated with both DMRs and DHMRs show a superior performance compared to models trained with DMRs or DHMRs, with AUROC being 0.978, 0.990, and 0.983 in distinguishing control, liver and brain cancer, respectively, in a validation cohort. This study supports the potential of utilizing both DMRs and DHMRs for multi-cancer detection.

Huntingtin is an RNA binding protein and participates in NEAT1-mediated paraspeckles

Huntingtin protein, mutated in Huntington's disease, is implicated in nucleic acid-mediated processes, yet the evidence for direct huntingtin-nucleic acid interaction is limited. Here, we show wild-type and mutant huntingtin copurify with nucleic acids, primarily RNA, and interact directly with G-rich RNAs in in vitro assays. Huntingtin RNA-immunoprecipitation sequencing from patient-derived fibroblasts and neuronal progenitor cells expressing wild-type and mutant huntingtin revealed long noncoding RNA NEAT1 as a significantly enriched transcript. Altered NEAT1 levels were evident in Huntington's disease cells and postmortem brain tissues, and huntingtin knockdown decreased NEAT1 levels. Huntingtin colocalized with NEAT1 in paraspeckles, and we identified a high-affinity RNA motif preferred by huntingtin. This study highlights NEAT1 as a huntingtin interactor, demonstrating huntingtin's involvement in RNA-mediated functions and paraspeckle regulation.

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

Disease risk prediction based on genomic sequence and transcriptional profile can improve disease screening and prevention. Despite identifying many disease-associated DNA variants, distinguishing deleterious non-coding DNA variations remains poor for most common diseases. In this study, we designed in vitro experiments to uncover the significance of occupancy and competitive binding between P53 and cMYC on common target genes. Analyzing publicly available ChIP-seq data for P53 and cMYC in embryonic stem cells showed that ~344-366 regions are co-occupied, and on average, two cis-overlapping motifs (CisOMs) per region were identified, suggesting that co-occupancy is evolutionarily conserved. Using U2OS and Raji cells untreated and treated with doxorubicin to increase P53 protein level while potentially reducing cMYC level, ChIP-seq analysis illustrated that around 16 to 922 genomic regions were co-occupied by P53 and cMYC, and substitutions of cMYC signals by P53 were detected post doxorubicin treatment. Around 187 expressed genes near co-occupied regions were altered at mRNA level according to RNA-seq data analysis. We utilized a computational motif-matching approach to illustrate that changes in predicted P53 binding affinity in CisOMs of co-occupied elements significantly correlate with alterations in reporter gene expression. We performed a similar analysis using SNPs mapped in CisOMs for P53 and cMYC from ChIP-seq data, and expression of target genes from GTEx portal. We found significant correlation between change in cMYC-motif binding affinity in CisOMs and altered expression. Our study brings us closer to developing a generally applicable approach to filter etiological non-coding variations associated with common diseases.

MYC Binding Near Transcriptional End Sites Regulates Basal Gene Expression, Read-Through Transcription and Intragenic Contacts

The MYC oncoprotein regulates numerous genes involved in cellular processes such as cell cycle and mitochondrial and ribosomal structure and function. This requires heterodimerization with its partner, MAX, and binding to specific promoter and enhancer elements. Here, we show that MYC and MAX also bind near transcriptional end sites (TESs) of over one-sixth of all annotated genes. These interactions are dose-dependent, evolutionarily conserved, stabilize the normally short-lived MYC protein and regulate expression both in concert with and independent of MYC's binding elsewhere. MYC's TES binding occurs in association with other transcription factors, alters the chromatin landscape, increases nuclease susceptibility and can alter transcriptional read-through, particularly in response to certain stresses. MYC-bound TESs can directly contact promoters and may fine-tune gene expression in response to both physiologic and pathologic stimuli. Collectively, these findings support a previously unrecognized role for MYC in regulating transcription and its read-through via direct intragenic contacts between TESs and promoters.

An epidermal growth factor receptor-targeting immunotoxin based on IgG shows potent antitumor activity against head and neck cancer

The epidermal growth factor receptor (EGFR) is an important target for cancer therapies. Many head and neck cancer (HNC) cells have been reported to overexpress EGFR; therefore, anti-EGFR therapies have been attempted in patients with HNC. However, its clinical efficacy is limited owing to the development of drug resistance. In this study, we developed an EGFR-targeting immunotoxin consisting of a clinically proven anti-EGFR IgG (cetuximab; CTX) and a toxin fragment (LR-LO10) derived from Pseudomonas exotoxin A (PE) using a novel site-specific conjugation technology (peptide-directed photo-crosslinking reaction), as an alternative option. The immunotoxin (CTX-LR-LO10) showed specific binding to EGFR and properties of a typical IgG, such as stability, interactions with receptors of immune cells, and pharmacokinetics, and inhibited protein synthesis via modification of elongation factor-2. Treatment of EGFR-positive HNC cells with the immunotoxin resulted in apoptotic cell death and the inhibition of cell migration and invasion. The efficacy of CTX-LR-LO10 was evaluated in xenograft mouse models, and the immunotoxin exhibited much stronger tumor suppression than CTX or LR-LO10. Transcriptome analyses revealed that the immunotoxins elicited immune responses and altered the expression of genes related to its mechanisms of action. These results support the notion that CTX-LR-LO10 may serve as a new therapeutic agent targeting EGFR-positive cancers.

RNA editing regulates glutamatergic synapses in the frontal cortex of a molecular subtype of Amyotrophic Lateral Sclerosis

BACKGROUND

Amyotrophic Lateral Sclerosis (ALS) is a highly heterogenous neurodegenerative disorder that primarily affects upper and lower motor neurons, affecting additional cell types and brain regions. Underlying molecular mechanisms are still elusive, in part due to disease heterogeneity. Molecular disease subtyping through integrative analyses including RNA editing profiling is a novel approach for identification of molecular networks involved in pathogenesis.

METHODS

We aimed to highlight the role of RNA editing in ALS, focusing on the frontal cortex and the prevalent molecular disease subtype (ALS-Ox), previously determined by transcriptomic profile stratification. We established global RNA editing (editome) and gene expression (transcriptome) profiles in control and ALS-Ox cases, utilizing publicly available RNA-seq data (GSE153960) and an in-house analysis pipeline. Functional annotation and pathway analyses identified molecular processes affected by RNA editing alterations. Pearson correlation analyses assessed RNA editing effects on expression. Similar analyses on additional ALS-Ox and control samples (GSE124439) were performed for verification. Targeted re-sequencing and qRT-PCR analysis targeting CACNA1C, were performed using frontal cortex tissue from ALS and control samples (n = 3 samples/group).

RESULTS

We identified reduced global RNA editing in the frontal cortex of ALS-Ox cases. Differentially edited transcripts are enriched in synapses, particularly in the glutamatergic synapse pathway. Bioinformatic analyses on additional ALS-Ox and control RNA-seq data verified these findings. We identified increased recoding at the Q621R site in the GRIK2 transcript and determined positive correlations between RNA editing and gene expression alterations in ionotropic receptor subunits GRIA2, GRIA3 and the CACNA1C transcript, which encodes the pore forming subunit of a post-synaptic L-type calcium channel. Experimental data verified RNA editing alterations and editing-expression correlation in CACNA1C, highlighting CACNA1C as a target for further study.

CONCLUSIONS

We provide evidence on the involvement of RNA editing in the frontal cortex of an ALS molecular subtype, highlighting a modulatory role mediated though recoding and gene expression regulation on glutamatergic synapse related transcripts. We report RNA editing effects in disease-related transcripts and validated editing alterations in CACNA1C. Our study provides targets for further functional studies that could shed light in underlying disease mechanisms enabling novel therapeutic approaches.

SimSpliceEvol2: alternative splicing-aware simulation of biological sequence evolution and transcript phylogenies

BACKGROUND

SimSpliceEvol is a tool for simulating the evolution of eukaryotic gene sequences that integrates exon-intron structure evolution as well as the evolution of the sets of transcripts produced from genes. It takes a guide gene tree as input and generates a gene sequence with its transcripts for each node of the tree, from the root to the leaves. However, the sets of transcripts simulated at different nodes of the guide gene tree lack evolutionary connections. Consequently, SimSpliceEvol is not suitable for evaluating methods for transcript phylogeny inference or gene phylogeny inference that rely on transcript conservation.

RESULTS

Here, we introduce SimSpliceEvol2, which, compared to the first version, incorporates an explicit model of transcript evolution for simulating alternative transcripts along the branches of a guide gene tree, as well as the transcript phylogenies inferred. We offer a comprehensive software with a graphical user interface and an updated version of the web server, ensuring easy and user-friendly access to the tool.

CONCLUSION

SimSpliceEvol2 generates synthetic datasets that are useful for evaluating methods and tools for spliced RNA sequence analysis, such as spliced alignment methods, methods for identifying conserved transcripts, and transcript phylogeny reconstruction methods. The web server is accessible at https://simspliceevol.cobius.usherbrooke.ca , where you can also download the standalone software. Comprehensive documentation for the software is available at the same address. For developers interested in the source code, which requires the installation of all prerequisites to run, it is provided at  https://github.com/UdeS-CoBIUS/SimSpliceEvol .

Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene expression and differential methylation

BACKGROUND

Changing cell-type proportions can confound studies of differential gene expression or DNA methylation (DNAm) from peripheral blood mononuclear cells (PBMCs). We examined how cell-type proportions derived from the transcriptome versus the methylome (DNAm) influence estimates of differentially expressed genes (DEGs) and differentially methylated positions (DMPs).

METHODS

Transcriptome and DNAm data were obtained from PBMC RNA and DNA of Kenyan children (n = 8) before, during, and 6 weeks following uncomplicated malaria. DEGs and DMPs between time points were detected using cell-type adjusted modeling with Cibersortx or IDOL, respectively.

RESULTS

Most major cell types and principal components had moderate to high correlation between the two deconvolution methods (r = 0.60-0.96). Estimates of cell-type proportions and DEGs or DMPs were largely unaffected by the method, with the greatest discrepancy in the estimation of neutrophils.

CONCLUSION

Variation in cell-type proportions is captured similarly by both transcriptomic and methylome deconvolution methods for most major cell types.

Basis of gene-specific transcription regulation by the Integrator complex

The Integrator complex attenuates gene expression via the premature termination of RNA polymerase II (RNAP2) at promoter-proximal pausing sites. It is required for stimulus response, cell differentiation, and neurodevelopment, but how gene-specific and adaptive regulation by Integrator is achieved remains unclear. Here, we identify two sites on human Integrator subunits 13/14 that serve as binding hubs for sequence-specific transcription factors (TFs) and other transcription effector complexes. When Integrator is attached to paused RNAP2, these hubs are positioned upstream of the transcription bubble, consistent with simultaneous TF-promoter tethering. The TFs co-localize with Integrator genome-wide, increase Integrator abundance on target genes, and co-regulate responsive transcriptional programs. For instance, sensory cilia formation induced by glucose starvation depends on Integrator-TF contacts. Our data suggest TF-mediated promoter recruitment of Integrator as a widespread mechanism for targeted transcription regulation.

Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data

The uncovering of protein-RNA interactions enables a deeper understanding of RNA processing. Recent multiplexed crosslinking and immunoprecipitation (CLIP) technologies such as antibody-barcoded eCLIP (ABC) dramatically increase the throughput of mapping RNA binding protein (RBP) binding sites. However, multiplex CLIP datasets are multivariate, and each RBP suffers non-uniform signal-to-noise ratio. To address this, we developed Mudskipper, a versatile computational suite comprising two components: a Dirichlet multinomial mixture model to account for the multivariate nature of ABC datasets and a softmasking approach that identifies and removes non-specific protein-RNA interactions in RBPs with low signal-to-noise ratio. Mudskipper demonstrates superior precision and recall over existing tools on multiplex datasets and supports analysis of repetitive elements and small non-coding RNAs. Our findings unravel splicing outcomes and variant-associated disruptions, enabling higher-throughput investigations into diseases and regulation mediated by RBPs.

Circulating small non-coding RNAs are associated with the insulin-resistant and obesity-related type 2 diabetes clusters

AIM

To uncover differences in small non-coding RNAs (sncRNAs) in individuals with type 2 diabetes (T2D) categorized into five clusters based on individual characteristics, which may aid in the identification of those prone to rapid progression.

MATERIALS AND METHODS

In the Hoorn Diabetes Care System (DCS) cohort, participants were clustered by age, body mass index (BMI), and glycated haemoglobin, C-peptide and high-density lipoprotein (HDL) cholesterol levels, yielding severe insulin-deficient diabetes, severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), mild diabetes, and mild diabetes with high HDL cholesterol clusters (n = 412). Utilizing plasma sncRNA-sequencing, we identified distinct cluster-specific sncRNAs. Validation was performed in a smaller DCS Hoorn dataset (n = 138). To elucidate their potential functions, we examined tissue expression, identified potential targets or (co-)regulated proteins, conducted gene set enrichment analyses on the targets through Reactome, and examined tissue expression of the (co-)regulated proteins.

RESULTS

The insulin-resistant cluster exhibited aberrant expression of 10 sncRNAs, while the high BMI cluster featured eight differentially expressed sncRNAs. Multiple (co-)regulated proteins were identified for sncRNAs associated with both clusters. Proteins associated with both clusters showed enrichment for metabolism. Proteins that specifically and only associated with the SIRD cluster showed enrichment for immune-related signalling. Furthermore, MOD cluster-specific associated proteins showed enrichment for the complement system.

CONCLUSIONS

Our research showed differential sncRNA levels among type 2 diabetes clusters. This may reflect and could deepen our understanding of molecular mechanisms, in development, progression, and risk factors for each cluster.

Fine mapping of candidate effector genes for heart rate

An elevated resting heart rate (RHR) is associated with increased cardiovascular mortality. Genome-wide association studies (GWAS) have identified > 350 loci. Uniquely, in this study we applied genetic fine-mapping leveraging tissue specific chromatin segmentation and colocalization analyses to identify causal variants and candidate effector genes for RHR. We used RHR GWAS summary statistics from 388,237 individuals of European ancestry from UK Biobank and performed fine mapping using publicly available genomic annotation datasets. High-confidence causal variants (accounting for > 75% posterior probability) were identified, and we collated candidate effector genes using a multi-omics approach that combined evidence from colocalisation with molecular quantitative trait loci (QTLs), and long-range chromatin interaction analyses. Finally, we performed druggability analyses to investigate drug repurposing opportunities. The fine mapping pipeline indicated 442 distinct RHR signals. For 90 signals, a single variant was identified as a high-confidence causal variant, of which 22 were annotated as missense. In trait-relevant tissues, 39 signals colocalised with cis-expression QTLs (eQTLs), 3 with cis-protein QTLs (pQTLs), and 75 had promoter interactions via Hi-C. In total, 262 candidate genes were highlighted (79% had promoter interactions, 15% had a colocalised eQTL, 8% had a missense variant and 1% had a colocalised pQTL), and, for the first time, enrichment in nervous system pathways. Druggability analyses highlighted ACHE, CALCRL, MYT1 and TDP1 as potential targets. Our genetic fine-mapping pipeline prioritised 262 candidate genes for RHR that warrant further investigation in functional studies, and we provide potential therapeutic targets to reduce RHR and cardiovascular mortality.

An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5' single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4+ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type-specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type-resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

HuR controls glutaminase RNA metabolism

Glutaminase (GLS) is directly related to cell growth and tumor progression, making it a target for cancer treatment. The RNA-binding protein HuR (encoded by the ELAVL1 gene) influences mRNA stability and alternative splicing. Overexpression of ELAVL1 is common in several cancers, including breast cancer. Here we show that HuR regulates GLS mRNA alternative splicing and isoform translation/stability in breast cancer. Elevated ELAVL1 expression correlates with high levels of the glutaminase isoforms C (GAC) and kidney-type (KGA), which are associated with poor patient prognosis. Knocking down ELAVL1 reduces KGA and increases GAC levels, enhances glutamine anaplerosis into the TCA cycle, and drives cells towards glutamine dependence. Furthermore, we show that combining chemical inhibition of GLS with ELAVL1 silencing synergistically decreases breast cancer cell growth and invasion. These findings suggest that dual inhibition of GLS and HuR offers a therapeutic strategy for breast cancer treatment.

Implications of noncoding regulatory functions in the development of insulinomas

Insulinomas are rare neuroendocrine tumors arising from pancreatic β cells, characterized by aberrant proliferation and altered insulin secretion, leading to glucose homeostasis failure. With the aim of uncovering the role of noncoding regulatory regions and their aberrations in the development of these tumors, we coupled epigenetic and transcriptome profiling with whole-genome sequencing. As a result, we unraveled somatic mutations associated with changes in regulatory functions. Critically, these regions impact insulin secretion, tumor development, and epigenetic modifying genes, including polycomb complex components. Chromatin remodeling is apparent in insulinoma-selective domains shared across patients, containing a specific set of regulatory sequences dominated by the SOX17 binding motif. Moreover, many of these regions are H3K27me3 repressed in β cells, suggesting that tumoral transition involves derepression of polycomb-targeted domains. Our work provides a compendium of aberrant cis-regulatory elements affecting the function and fate of β cells in their progression to insulinomas and a framework to identify coding and noncoding driver mutations.

Deconstructing Intratumoral Heterogeneity through Multiomic and Multiscale Analysis of Serial Sections

Tumors may contain billions of cells, including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that are consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

The annotation of GBA1 has been concealed by its protein-coding pseudogene GBAP1

Mutations in GBA1 cause Gaucher disease and are the most important genetic risk factor for Parkinson's disease. However, analysis of transcription at this locus is complicated by its highly homologous pseudogene, GBAP1. We show that >50% of short RNA-sequencing reads mapping to GBA1 also map to GBAP1. Thus, we used long-read RNA sequencing in the human brain, which allowed us to accurately quantify expression from both GBA1 and GBAP1. We discovered significant differences in expression compared to short-read data and identify currently unannotated transcripts of both GBA1 and GBAP1. These included protein-coding transcripts from both genes that were translated in human brain, but without the known lysosomal function-yet accounting for almost a third of transcription. Analyzing brain-specific cell types using long-read and single-nucleus RNA sequencing revealed region-specific variations in transcript expression. Overall, these findings suggest nonlysosomal roles for GBA1 and GBAP1 with implications for our understanding of the role of GBA1 in health and disease.

KDM5-mediated transcriptional activation of ribosomal protein genes alters translation efficiency to regulate mitochondrial metabolism in neurons

Genes encoding the KDM5 family of transcriptional regulators are disrupted in individuals with intellectual disability (ID). To understand the link between KDM5 and ID, we characterized five Drosophila strains harboring missense alleles analogous to those observed in patients. These alleles disrupted neuroanatomical development, cognition and other behaviors, and displayed a transcriptional signature characterized by the downregulation of many ribosomal protein genes. A similar transcriptional profile was observed in KDM5C knockout iPSC-induced human glutamatergic neurons, suggesting an evolutionarily conserved role for KDM5 proteins in regulating this class of gene. In Drosophila, reducing KDM5 changed neuronal ribosome composition, lowered the translation efficiency of mRNAs required for mitochondrial function, and altered mitochondrial metabolism. These data highlight the cellular consequences of altered KDM5-regulated transcriptional programs that could contribute to cognitive and behavioral phenotypes. Moreover, they suggest that KDM5 may be part of a broader network of proteins that influence cognition by regulating protein synthesis.

A replication-deficient gammaherpesvirus vaccine protects mice from lytic disease and reduces latency establishment

Gammaherpesviruses are oncogenic viruses that establish lifelong infections and are significant causes of morbidity and mortality. Vaccine strategies to limit gammaherpesvirus infection and disease are in development, but there are no FDA-approved vaccines for Epstein-Barr or Kaposi sarcoma herpesvirus. As a new approach to gammaherpesvirus vaccination, we developed and tested a replication-deficient virus (RDV) platform, using murine gammaherpesvirus 68 (MHV68), a well-established mouse model for gammaherpesvirus pathogenesis studies and preclinical therapeutic evaluations. We employed codon-shuffling-based complementation to generate revertant-free RDV lacking expression of the essential replication and transactivator protein encoded by ORF50 to arrest viral gene expression early after de novo infection. Inoculation with RDV-50.stop exposes the host to intact virion particles and leads to limited lytic gene expression in infected cells yet does not produce additional infectious particles. Prime-boost vaccination of mice with RDV-50.stop elicited virus-specific neutralizing antibody and effector T cell responses in the lung and spleen. In contrast to vaccination with heat-inactivated WT MHV68, vaccination with RDV-50.stop resulted in a near complete abolishment of virus replication in the lung 7 days post-challenge and reduction of latency establishment in the spleen 16 days post-challenge with WT MHV68. Ifnar1-/- mice, which lack the type I interferon receptor, exhibit severe disease and high mortality upon infection with WT MHV68. RDV-50.stop vaccination of Ifnar1-/- mice prevented wasting and mortality upon challenge with WT MHV68. These results demonstrate that prime-boost vaccination with a gammaherpesvirus that is unable to undergo lytic replication offers protection against acute replication, impairs the establishment of latency, and prevents severe disease upon the WT virus challenge. Our study also reveals that the ability of a gammaherpesvirus to persist in vivo despite potent pre-existing immunity is an obstacle to obtaining sterilizing immunity.

LncRNA AFAP1-AS1 Promotes Oral Squamous Cell Carcinoma Development by Ubiquitin-Mediated Proteolysis

BACKGROUND AND PURPOSE

Long noncoding RNA (lncRNA) dysregulation has been reported to play a pivotal role in the development of cancers. In this study, we aimed to screen the key lncRNA in oral squamous cell carcinoma (OSCC) via bioinformatics analysis and further validate the function of lncRNA in vitro and in vivo.

METHODS

Bioinformatics analysis was conducted to identify differentially expressed lncRNAs between control and OSCC samples. Quantitative real-time-polymerase chain reaction was employed to detect the expression of differentially expressed lncRNAs in human tongue squamous cell carcinoma and human oral keratinocytes cell lines. The biological function of lncRNA and its mechanism were examined via the experimental assessment of the cell lines with the lncRNA overexpressed and silenced. Additionally, to further explore the function of lncRNA in the progression of OSCC, xenograft tumour mouse models were established using 25 mice (5 groups, each with 5 mice). Tumour formation was observed at 2 weeks after the cell injection, and the tumours were resected at 5 weeks post-implantation.

RESULTS

Two lncRNAs, LINC00958 and AFAP1-AS1, were found to be correlated with the prognosis of OSCC. The results of the quantitative real-time-polymerase chain reaction indicated that the 2 lncRNAs were highly expressed in OSCC. In combination with the previous literature, we found AFAP1-AS1 to be a potentially important biomarker for OSCC. Thus, we further investigated its biological function and found that AFAP1-AS1 silencing inhibited cell proliferation, migration, and invasion whereas AFAP1-AS1 overexpression reversed the effect of AFAP1-AS1 silencing (P < .05). Mechanism analysis revealed that AFAP1-AS1 regulated the development of OSCC through the ubiquitin-mediated proteolysis pathway.

CONCLUSIONS

AFAP1-AS1 is an oncogene that aggravates the development of OSCC via the ubiquitin-mediated proteolysis pathway. It also provides a novel potential therapy for OSCC.

HNF4A and HNF1A exhibit tissue specific target gene regulation in pancreatic beta cells and hepatocytes

HNF4A and HNF1A encode transcription factors that are important for the development and function of the pancreas and liver. Mutations in both genes have been directly linked to Maturity Onset Diabetes of the Young (MODY) and type 2 diabetes (T2D) risk. To better define the pleiotropic gene regulatory roles of HNF4A and HNF1A, we generated a comprehensive genome-wide map of their binding targets in pancreatic and hepatic cells using ChIP-Seq. HNF4A was found to bind and regulate known (ACY3, HAAO, HNF1A, MAP3K11) and previously unidentified (ABCD3, CDKN2AIP, USH1C, VIL1) loci in a tissue-dependent manner. Functional follow-up highlighted a potential role for HAAO and USH1C as regulators of beta cell function. Unlike the loss-of-function HNF4A/MODY1 variant I271fs, the T2D-associated HNF4A variant (rs1800961) was found to activate AKAP1, GAD2 and HOPX gene expression, potentially due to changes in DNA-binding affinity. We also found HNF1A to bind to and regulate GPR39 expression in beta cells. Overall, our studies provide a rich resource for uncovering downstream molecular targets of HNF4A and HNF1A that may contribute to beta cell or hepatic cell (dys)function, and set up a framework for gene discovery and functional validation.

Differential impact of quiescent non-coding loci on chromatin entropy

Non-coding regions of the human genome are important for functional regulations, but their mechanisms remain elusive. We used machine learning to guide a CRISPR screening on hubs (i.e. non-coding loci forming many 3D contacts) and significantly increased the discovery rate of hubs essential for cell growth. We found no clear genetic or epigenetic differences between essential and nonessential hubs, but we observed that some neighboring hubs in the linear genome have distinct spatial contacts and opposite effects on cell growth. One such pair in an epigenetically quiescent region showed different impacts on gene expression, chromatin accessibility and chromatin organization. We also found that deleting the essential hub altered the genetic network activity and increased the entropy of chromatin accessibility, more severe than that caused by deletion of the nonessential hub, suggesting that they are critical for maintaining an ordered chromatin structure. Our study reveals new insights into the system-level roles of non-coding regions in the human genome.

Multi-ancestry Genome-Wide Association Meta-Analysis Identifies Novel Loci in Atopic Dermatitis

Atopic dermatitis (AD) is a highly heritable and common inflammatory skin condition affecting children and adults worldwide. Multi-ancestry approaches to AD genetic association studies are poised to boost power to detect genetic signal and identify ancestry-specific loci contributing to AD risk. Here, we present a multi-ancestry GWAS meta-analysis of twelve AD cohorts from five ancestral populations totaling 56,146 cases and 602,280 controls. We report 101 genomic loci associated with AD, including 15 loci that have not been previously associated with AD or eczema. Fine-mapping, QTL colocalization, and cell-type enrichment analyses identified genes and cell types implicated in AD pathophysiology. Functional analyses in keratinocytes provide evidence for genes that could play a role in AD through epidermal barrier function. Our study provides new insights into the etiology of AD by harnessing multiple genetic and functional approaches to unveil the mechanisms by which AD-associated variants impact genes and cell types.

Precise editing of pathogenic nucleotide repeat expansions in iPSCs using paired prime editor

Nucleotide repeat expansion disorders, a group of genetic diseases characterized by the expansion of specific DNA sequences, pose significant challenges to treatment and therapy development. Here, we present a precise and programmable method called prime editor-mediated correction of nucleotide repeat expansion (PE-CORE) for correcting pathogenic nucleotide repeat expansion. PE-CORE leverages a prime editor and paired pegRNAs to achieve targeted correction of repeat sequences. We demonstrate the effectiveness of PE-CORE in HEK293T cells and patient-derived induced pluripotent stem cells (iPSCs). Specifically, we focus on spinal and bulbar muscular atrophy and spinocerebellar ataxia type, two diseases associated with nucleotide repeat expansion. Our results demonstrate the successful correction of pathogenic expansions in iPSCs and subsequent differentiation into motor neurons. Specifically, we detect distinct downshifts in the size of both the mRNA and protein, confirming the functional correction of the iPSC-derived motor neurons. These findings highlight PE-CORE as a precision tool for addressing the intricate challenges of nucleotide repeat expansion disorders, paving the way for targeted therapies and potential clinical applications.

Big data and deep learning for RNA biology

The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively.

PML restrains p53 activity and cellular senescence in clear cell renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC), the major subtype of RCC, is frequently diagnosed at late/metastatic stage with 13% 5-year disease-free survival. Functional inactivation of the wild-type p53 protein is implicated in ccRCC therapy resistance, but the detailed mechanisms of p53 malfunction are still poorly characterized. Thus, a better understanding of the mechanisms of disease progression and therapy resistance is required. Here, we report a novel ccRCC dependence on the promyelocytic leukemia (PML) protein. We show that PML is overexpressed in ccRCC and that PML depletion inhibits cell proliferation and relieves pathologic features of anaplastic disease in vivo. Mechanistically, PML loss unleashed p53-dependent cellular senescence thus depicting a novel regulatory axis to limit p53 activity and senescence in ccRCC. Treatment with the FDA-approved PML inhibitor arsenic trioxide induced PML degradation and p53 accumulation and inhibited ccRCC expansion in vitro and in vivo. Therefore, by defining non-oncogene addiction to the PML gene, our work uncovers a novel ccRCC vulnerability and lays the foundation for repurposing an available pharmacological intervention to restore p53 function and chemosensitivity.

Spatial omics reveals molecular changes in focal cortical dysplasia type II

Focal cortical dysplasia (FCD) represents a group of diverse localized cortical lesions that are highly epileptogenic and occur due to abnormal brain development caused by genetic mutations, involving the mammalian target of rapamycin (mTOR). These somatic mutations lead to mosaicism in the affected brain, posing challenges to unravel the direct and indirect functional consequences of these mutations. To comprehensively characterize the impact of mTOR mutations on the brain, we employed here a multimodal approach in a preclinical mouse model of FCD type II (Rheb), focusing on spatial omics techniques to define the proteomic and lipidomic changes. Mass Spectrometry Imaging (MSI) combined with fluorescence imaging and label free proteomics, revealed insight into the brain's lipidome and proteome within the FCD type II affected region in the mouse model. MSI visualized disrupted neuronal migration and differential lipid distribution including a reduction in sulfatides in the FCD type II-affected region, which play a role in brain myelination. MSI-guided laser capture microdissection (LMD) was conducted on FCD type II and control regions, followed by label free proteomics, revealing changes in myelination pathways by oligodendrocytes. Surgical resections of FCD type IIb and postmortem human cortex were analyzed by bulk transcriptomics to unravel the interplay between genetic mutations and molecular changes in FCD type II. Our comparative analysis of protein pathways and enriched Gene Ontology pathways related to myelination in the FCD type II-affected mouse model and human FCD type IIb transcriptomics highlights the animal model's translational value. This dual approach, including mouse model proteomics and human transcriptomics strengthens our understanding of the functional consequences arising from somatic mutations in FCD type II, as well as the identification of pathways that may be used as therapeutic strategies in the future.

Sex dimorphic response to osteocyte miR21 deletion in murine calvaria bone as determined by RNAseq analysis

Low levels of microRNA (miR) 21 may explain the higher osteocyte apoptosis with Cx43-deficient and aged female mice. However, miR21 exerts a sex-divergent role in osteocytes, regulating bone mass and architecture through non-cell autonomous effects on osteoblasts and osteoclasts, via sex-specific regulation of osteocyte cytokine production. miR21 deficiency improves bone strength in females, and, to a higher extent, in male miR21-deficient mice. To understand the molecular basis for the effects of miR21 deletion, mRNA was isolated from miR21fl/fl (controls) or miR21-deficient (by deletion in cells expressing Cre recombinase under the control of the 8 kb fragment of the DMP1 promoter: miR21ΔOt mice). miR21 was 50% lower in miR21ΔOt whole calvaria bone compared to control mice of the corresponding sex. RNAseq was performed in 4 samples/sex and genotype. There were 152 genes with <.05 P-value and >1 absolute log2 fold change in the male data analysis, and expression of most genes was higher in the miR21fl/fl group. Two of the genes, Actn3 and Myh4, had a false discovery rate < 0.1. Gene enrichment analysis of significant genes on both KEGG pathways and gene ontology (GO) gene sets shows that the significant genes were enriched in muscle contraction. Some muscle-related genes like Actn3 were included in multiple significant pathways. For females, only 65 genes had P-value <.05 and >1 absolute log2 fold change. Yet, no significant KEGG or GO pathways, including ≥5 significant genes, were seen, and no overlap of significant genes was found between male and female samples. Therefore, deletion of miR21 has a stronger effect on male transcriptome in calvaria, compared to females. Further, no enrichment of any pathway was detected in female samples. Thus, either there are no differences between 2 groups in female or the effect size is small, and a larger sample size is needed to uncover miR21-dependent differences.

PNPO-PLP axis senses prolonged hypoxia in macrophages by regulating lysosomal activity

Oxygen is critical for all metazoan organisms on the earth and impacts various biological processes in physiological and pathological conditions. While oxygen-sensing systems inducing acute hypoxic responses, including the hypoxia-inducible factor pathway, have been identified, those operating in prolonged hypoxia remain to be elucidated. Here we show that pyridoxine 5'-phosphate oxidase (PNPO), which catalyses bioactivation of vitamin B6, serves as an oxygen sensor and regulates lysosomal activity in macrophages. Decreased PNPO activity under prolonged hypoxia reduced an active form of vitamin B6, pyridoxal 5'-phosphate (PLP), and inhibited lysosomal acidification, which in macrophages led to iron dysregulation, TET2 protein loss and delayed resolution of the inflammatory response. Among PLP-dependent metabolism, supersulfide synthesis was suppressed in prolonged hypoxia, resulting in the lysosomal inhibition and consequent proinflammatory phenotypes of macrophages. The PNPO-PLP axis creates a distinct layer of oxygen sensing that gradually shuts down PLP-dependent metabolism in response to prolonged oxygen deprivation.

Loss of LPAR6 and CAB39L dysregulates the basal-to-luminal urothelial differentiation program, contributing to bladder carcinogenesis

We describe a strategy that combines histologic and molecular mapping that permits interrogation of the chronology of changes associated with cancer development on a whole-organ scale. Using this approach, we present the sequence of alterations around RB1 in the development of bladder cancer. We show that RB1 is not involved in initial expansion of the preneoplastic clone. Instead, we found a set of contiguous genes that we term "forerunner" genes whose silencing is associated with the development of plaque-like field effects initiating carcinogenesis. Specifically, we identified five candidate forerunner genes (ITM2B, LPAR6, MLNR, CAB39L, and ARL11) mapping near RB1. Two of these genes, LPAR6 and CAB39L, are preferentially downregulated in the luminal and basal subtypes of bladder cancer, respectively. Their loss of function dysregulates urothelial differentiation, sensitizing the urothelium to N-butyl-N-(4-hydroxybutyl)nitrosamine-induced cancers, which recapitulate the luminal and basal subtypes of human bladder cancer.

Small RNA sequencing reveals snoRNAs and piRNA-019825 as novel players in diabetic kidney disease

INTRODUCTION

Micro- and macrovascular complications are common among persons with type 2 diabetes. Recently there has been growing interest to investigate the potential of circulating small non-coding RNAs (sncRNAs) as contributors to the development of diabetic complications. In this study we investigate to what extent circulating sncRNAs levels associate with prevalent diabetic kidney disease (DKD) in persons with type 2 diabetes.

METHODS

Plasma sncRNAs levels were determined using small RNA-seq, allowing detection of miRNAs, snoRNAs, piRNAs, tRNA fragments, and various other sncRNA classes. We tested for differentially expressed sncRNAs in persons with type 2 diabetes, with DKD (n = 69) or without DKD (n = 405). In secondary analyses, we also tested the association with eGFR, albuminuria (UACR), and the plasma proteome.

RESULTS

In total seven sncRNAs were negatively associated with prevalent DKD (all PFDR ≤ 0.05). Including one microRNA (miR-143-5p), five snoRNAs (U8, SNORD118, SNORD24, SNORD107, SNORD87) and a piRNA (piR-019825 | DQ597218). Proteomic analyses showed that the seven sncRNAs, and especially the piRNA piR-019825, were associated with plasma levels of 24 proteins of which several have known associations with kidney function including TNF sR-I (TNFRFS1A), DAN (NBL1) and cystatin C (CST3).

CONCLUSION

We have identified novel small non-coding RNAs, primarily from classes other than microRNAs, that are associated with diabetic kidney disease. Our results show that the involvement of small non-coding RNAs in DKD goes beyond the already known microRNAs and also involves other classes of sncRNA, in particular snoRNAs and the piRNA piR-019825, that have never been studied before in relation to kidney function.

Molecular and functional profiling of cell diversity and identity in the lateral superior olive, an auditory brainstem center with ascending and descending projections

The lateral superior olive (LSO), a prominent integration center in the auditory brainstem, contains a remarkably heterogeneous population of neurons. Ascending neurons, predominantly principal neurons (pLSOs), process interaural level differences for sound localization. Descending neurons (lateral olivocochlear neurons, LOCs) provide feedback into the cochlea and are thought to protect against acoustic overload. The molecular determinants of the neuronal diversity in the LSO are largely unknown. Here, we used patch-seq analysis in mice at postnatal days P10-12 to classify developing LSO neurons according to their functional and molecular profiles. Across the entire sample (n = 86 neurons), genes involved in ATP synthesis were particularly highly expressed, confirming the energy expenditure of auditory neurons. Two clusters were identified, pLSOs and LOCs. They were distinguished by 353 differentially expressed genes (DEGs), most of which were novel for the LSO. Electrophysiological analysis confirmed the transcriptomic clustering. We focused on genes affecting neuronal input-output properties and validated some of them by immunohistochemistry, electrophysiology, and pharmacology. These genes encode proteins such as osteopontin, Kv11.3, and Kvβ3 (pLSO-specific), calcitonin-gene-related peptide (LOC-specific), or Kv7.2 and Kv7.3 (no DEGs). We identified 12 "Super DEGs" and 12 genes showing "Cluster similarity." Collectively, we provide fundamental and comprehensive insights into the molecular composition of individual ascending and descending neurons in the juvenile auditory brainstem and how this may relate to their specific functions, including developmental aspects.

p300/CBP degradation is required to disable the active AR enhanceosome in prostate cancer

Prostate cancer is an exemplar of an enhancer-binding transcription factor-driven disease. The androgen receptor (AR) enhanceosome complex comprised of chromatin and epigenetic coregulators assembles at enhancer elements to drive disease progression. The paralog lysine acetyltransferases p300 and CBP deposit histone marks that are associated with enhancer activation. Here, we demonstrate that p300/CBP are determinant cofactors of the active AR enhanceosome in prostate cancer. Histone H2B N-terminus multisite lysine acetylation (H2BNTac), which is exclusively reliant on p300/CBP catalytic function, marked active enhancers and was notably elevated in prostate cancer lesions relative to the adjacent benign epithelia. Degradation of p300/CBP rapidly depleted acetylation marks associated with the active AR enhanceosome, which was only partially phenocopied by inhibition of their reader bromodomains. Notably, H2BNTac was effectively abrogated only upon p300/CBP degradation, which led to a stronger suppression of p300/CBP-dependent oncogenic gene programs relative to bromodomain inhibition or the inhibition of its catalytic domain. In vivo experiments using an orally active p300/CBP proteolysis targeting chimera (PROTAC) degrader (CBPD-409) showed that p300/CBP degradation potently inhibited tumor growth in preclinical models of castration-resistant prostate cancer and synergized with AR antagonists. While mouse p300/CBP orthologs were effectively degraded in host tissues, prolonged treatment with the PROTAC degrader was well tolerated with no significant signs of toxicity. Taken together, our study highlights the pivotal role of p300/CBP in maintaining the active AR enhanceosome and demonstrates how target degradation may have functionally distinct effects relative to target inhibition, thus supporting the development of p300/CBP degraders for the treatment of advanced prostate cancer.

Energy stress-induced circDDX21 promotes glycolysis and facilitates hepatocellular carcinogenesis

Cancer cells undergo metabolic reprogramming in response to hostile microenvironments, such as energy stress; however, the underlying mechanisms remain largely unclear. It is also unknown whether energy stress-responsive circular RNA (circRNA) is involved in the regulation of glucose metabolism. Here we report that circDDX21 is upregulated in response to glucose deprivation by the transcription factor c-Myc. Functionally, circDDX21 is shown to promote glycolysis by increasing PGAM1 expression. Mechanistically, circDDX21 interacts with the RNA binding protein PABPC1, disrupting its association with the ubiquitin E3 ligase MKRN3. This disassociation attenuates MKRN3-mediated PABPC1 ubiquitination and enhances the binding of PABPC1 to PGAM1 mRNA, thereby leading to PGAM1 mRNA stabilization. The ability of the circDDX21-PGAM1 axis to promote hepatocellular carcinogenesis is validated in a xenograft mouse model. Additionally, in clinical hepatocellular carcinoma tissues, there is a positive correlation between circDDX21 and PGAM1 expression. These findings establish circDDX21 as an important regulator of glycolysis and suggest circDDX21 as a potential therapeutic target for hepatocellular carcinoma.

Integrated electrophysiological and genomic profiles of single cells reveal spiking tumor cells in human glioma

Prior studies have described the complex interplay that exists between glioma cells and neurons, however, the electrophysiological properties endogenous to tumor cells remain obscure. To address this, we employed Patch-sequencing on human glioma specimens and found that one third of patched cells in IDH mutant (IDH mut ) tumors demonstrate properties of both neurons and glia by firing single, short action potentials. To define these hybrid cells (HCs) and discern if they are tumor in origin, we developed a computational tool, Single Cell Rule Association Mining (SCRAM), to annotate each cell individually. SCRAM revealed that HCs represent tumor and non-tumor cells that feature GABAergic neuron and oligodendrocyte precursor cell signatures. These studies are the first to characterize the combined electrophysiological and molecular properties of human glioma cells and describe a new cell type in human glioma with unique electrophysiological and transcriptomic properties that are likely also present in the non-tumor mammalian brain.

Glycometabolism and lipid metabolism related genes predict the prognosis of endometrial carcinoma and their effects on tumor cells

BACKGROUND

Glycometabolism and lipid metabolism are critical in cancer metabolic reprogramming. The primary aim of this study was to develop a prognostic model incorporating glycometabolism and lipid metabolism-related genes (GLRGs) for accurate prognosis assessment in patients with endometrial carcinoma (EC).

METHODS

Data on gene expression and clinical details were obtained from publicly accessible databases. GLRGs were obtained from the Genecards database. Through nonnegative matrix factorization (NMF) clustering, molecular groupings with various GLRG expression patterns were identified. LASSO Cox regression analysis was employed to create a prognostic model. Use rich algorithms such as GSEA, GSVA, xCELL ssGSEA, EPIC,CIBERSORT, MCPcounter, ESTIMATE, TIMER, TIDE, and Oncoppredict to analyze functional pathway characteristics of the forecast signal, immune status, anti-tumor therapy, etc. The expression was assessed using Western blot and quantitative real-time PCR techniques. A total of 113 algorithm combinations were combined to screen out the most significant GLRGs in the signature for in vitro experimental verification, such as colony formation, EdU cell proliferation, wound healing, apoptosis, and Transwell assays.

RESULTS

A total of 714 GLRGs were found, and 227 of them were identified as prognostic-related genes. And ten GLRGs (AUP1, ESR1, ERLIN2, ASS1, OGDH, BCKDHB, SLC16A1, HK2, LPCAT1 and PGR-AS1) were identified to construct the prognostic model of patients with EC. Based on GLRGs, the risk model's prognosis and independent prognostic value were established. The signature of GLRGs exhibited a robust correlation with the infiltration of immune cells and the sensitivity to drugs. In cytological experiments, we selected HK2 as candidate gene to verify its value in the occurrence and development of EC. Western blot and qRT-PCR revealed that HK2 was substantially expressed in EC cells. According to in vitro experiments, HK2 knockdown can increase EC cell apoptosis while suppressing EC cell migration, invasion, and proliferation.

CONCLUSION

The GLRGs signature constructed in this study demonstrated significant prognostic value for patients with endometrial carcinoma, thereby providing valuable guidance for treatment decisions.

Transcriptome- and proteome-wide effects of a circular RNA encompassing four early exons of the spinal muscular atrophy genes

Spinal muscular atrophy (SMA) genes, SMN1 and SMN2 (hereinafter referred to as SMN1/2), produce multiple circular RNAs (circRNAs), including C2A-2B-3-4 that encompasses early exons 2A, 2B, 3 and 4. C2A-2B-3-4 is a universally and abundantly expressed circRNA of SMN1/2. Here we report the transcriptome- and proteome-wide effects of overexpression of C2A-2B-3-4 in inducible HEK293 cells. Our RNA-Seq analysis revealed altered expression of ~ 15% genes (4172 genes) by C2A-2B-3-4. About half of the affected genes by C2A-2B-3-4 remained unaffected by L2A-2B-3-4, a linear transcript encompassing exons 2A, 2B, 3 and 4 of SMN1/2. These findings underscore the unique role of the structural context of C2A-2B-3-4 in gene regulation. A surprisingly high number of upregulated genes by C2A-2B-3-4 were located on chromosomes 4 and 7, whereas many of the downregulated genes were located on chromosomes 10 and X. Supporting a cross-regulation of SMN1/2 transcripts, C2A-2B-3-4 and L2A-2B-3-4 upregulated and downregulated SMN1/2 mRNAs, respectively. Proteome analysis revealed 61 upregulated and 57 downregulated proteins by C2A-2B-3-4 with very limited overlap with those affected by L2A-2B-3-4. Independent validations confirmed the effect of C2A-2B-3-4 on expression of genes associated with chromatin remodeling, transcription, spliceosome function, ribosome biogenesis, lipid metabolism, cytoskeletal formation, cell proliferation and neuromuscular junction formation. Our findings reveal a broad role of C2A-2B-3-4, and expands our understanding of functions of SMN1/2 genes.

Scalable integration of multiomic single-cell data using generative adversarial networks

MOTIVATION

Single-cell profiling has become a common practice to investigate the complexity of tissues, organs, and organisms. Recent technological advances are expanding our capabilities to profile various molecular layers beyond the transcriptome such as, but not limited to, the genome, the epigenome, and the proteome. Depending on the experimental procedure, these data can be obtained from separate assays or the very same cells. Yet, integration of more than two assays is currently not supported by the majority of the computational frameworks avaiable.

RESULTS

We here propose a Multi-Omic data integration framework based on Wasserstein Generative Adversarial Networks suitable for the analysis of paired or unpaired data with a high number of modalities (>2). At the core of our strategy is a single network trained on all modalities together, limiting the computational burden when many molecular layers are evaluated.

AVAILABILITY AND IMPLEMENTATION

Source code of our framework is available at https://github.com/vgiansanti/MOWGAN.

Identification and classification of glioma subtypes based on RNA-binding proteins

BACKGROUND

Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy.

METHODS

RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using WGCNA and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers.

RESULTS

Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through WGCNA, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA splicing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways.

CONCLUSIONS

The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.

Structural insights into branch site proofreading by human spliceosome

Selection of the pre-mRNA branch site (BS) by the U2 small nuclear ribonucleoprotein (snRNP) is crucial to prespliceosome (A complex) assembly. The RNA helicase PRP5 proofreads BS selection but the underlying mechanism remains unclear. Here we report the atomic structures of two sequential complexes leading to prespliceosome assembly: human 17S U2 snRNP and a cross-exon pre-A complex. PRP5 is anchored on 17S U2 snRNP mainly through occupation of the RNA path of SF3B1 by an acidic loop of PRP5; the helicase domain of PRP5 associates with U2 snRNA; the BS-interacting stem-loop (BSL) of U2 snRNA is shielded by TAT-SF1, unable to engage the BS. In the pre-A complex, an initial U2-BS duplex is formed; the translocated helicase domain of PRP5 stays with U2 snRNA and the acidic loop still occupies the RNA path. The pre-A conformation is specifically stabilized by the splicing factors SF1, DNAJC8 and SF3A2. Cancer-derived mutations in SF3B1 damage its association with PRP5, compromising BS proofreading. Together, these findings reveal key insights into prespliceosome assembly and BS selection or proofreading by PRP5.

Endogenous retroelement expression in the gut microenvironment of people living with HIV-1

BACKGROUND

Endogenous retroelements (EREs), including human endogenous retroviruses (HERVs) and long interspersed nuclear elements (LINEs), comprise almost half of the human genome. Our previous studies of the interferome in the gut suggest potential mechanisms regarding how IFNb may drive HIV-1 gut pathogenesis. As ERE activity is suggested to partake in type 1 immune responses and is incredibly sensitive to viral infections, we sought to elucidate underlying interactions between ERE expression and gut dynamics in people living with HIV-1 (PLWH).

METHODS

ERE expression profiles from bulk RNA sequencing of colon biopsies and PBMC were compared between a cohort of PLWH not on antiretroviral therapy (ART) and uninfected controls.

FINDINGS

59 EREs were differentially expressed in the colon of PLWH when compared to uninfected controls (padj <0.05 and FC ≤ -1 or ≥ 1) [Wald's Test]. Of these 59, 12 EREs were downregulated in PLWH and 47 were upregulated. Colon expression of the ERE loci LTR19_12p13.31 and L1FLnI_1q23.1s showed significant correlations with certain gut immune cell subset frequencies in the colon. Furthermore L1FLnI_1q23.1s showed a significant upregulation in peripheral blood mononuclear cells (PBMCs) of PLWH when compared to uninfected controls suggesting a common mechanism of differential ERE expression in the colon and PBMC.

INTERPRETATION

ERE activity has been largely understudied in genomic characterizations of human pathologies. We show that the activity of certain EREs in the colon of PLWH is deregulated, supporting our hypotheses that their underlying activity could function as (bio)markers and potential mediators of pathogenesis in HIV-1 reservoirs.

FUNDING

US NIH grants NCI CA260691 (DFN) and NIAID UM1AI164559 (DFN).

NextDenovo: an efficient error correction and accurate assembly tool for noisy long reads

Long-read sequencing data, particularly those derived from the Oxford Nanopore sequencing platform, tend to exhibit high error rates. Here, we present NextDenovo, an efficient error correction and assembly tool for noisy long reads, which achieves a high level of accuracy in genome assembly. We apply NextDenovo to assemble 35 diverse human genomes from around the world using Nanopore long-read data. These genomes allow us to identify the landscape of segmental duplication and gene copy number variation in modern human populations. The use of NextDenovo should pave the way for population-scale long-read assembly using Nanopore long-read data.