Addiction is a chronic and relapsing medical condition characterized by the compulsive use of drugs or alcohol despite harmful consequences. While transcriptional regulation has long been recognized for its role in addiction, recent genome-wide analyses have uncovered widespread alternative splicing changes that shift protein isoform diversity in multiple brain reward regions central to addiction. In this review, we discuss emerging research and evidence that alternative splicing is dysregulated in cocaine, alcohol, and opioid use disorders.

Alcohol use disorder (AUD) is a highly prevalent, complex, multifactorial and heterogeneous disorder, with 11 % and 30 % of adults meeting criteria for past-year and lifetime AUD, respectively. Identification of the molecular mechanisms underlying risk for AUD would facilitate effective deployment of personalized interventions. Studies using rhesus monkeys and rats, have demonstrated that individuals with low cognitive flexibility and a predisposition towards habitual behaviors show an increased risk for future heavy drinking. Further, low cognitive flexibility is associated with reduced dorsolateral prefrontal cortex (dlPFC) function in rhesus monkeys. To explore the underlying unique molecular signatures that increase risk for chronic heavy drinking, a genome-wide DNA methylation (DNAm) analysis of the alcohol-naïve dlPFC-A46 biopsy prior to chronic alcohol self-administration was conducted. The DNAm profile provides a molecular snapshot of the alcohol-naïve dlPFC, with mapped genes and associated signaling pathways that vary across individuals. The analysis identified 1,463 differentially methylated regions (DMRs) related to unique genes that were strongly associated with average ethanol intake consumed over 6 months of voluntary self-administration. These findings translate behavioral phenotypes into neural markers of risk for AUD, and hold promise for parallel discoveries in risk for other disorders involving impaired cognitive flexibility. SIGNIFICANCE: Alcohol use disorder (AUD) is a highly prevalent and heterogeneous disorder. Prevention strategies to accurately identify individuals with a high risk for AUD, would help reduce the prevalence, and severity of AUD. Our novel epigenomic analysis of the alcohol-naïve nonhuman primate cortex provides a molecular snapshot of the vulnerable brain, pointing to circuitry and molecular mechanisms associated with cortical development, synaptic functions, glutamatergic signaling and coordinated signaling pathways. With a complex disorder like AUD, having the ability to identify the molecular mechanisms underlying AUD risk is critical for better development of personalized effective treatments.

Changes in alternative splicing between groups or conditions contribute to protein-protein interaction rewiring, a consequence often neglected in data analysis. The web server and database DIGGER overcomes this limitation by augmenting a protein-protein interaction network with domain-domain interactions and splicing information. Here, we present DIGGER 2.0, which now features both experimental and newly added predicted domain-domain interactions. In addition to the human interactome, DIGGER 2.0 adds support for mouse as an important model organism. Additionally, we integrated the splicing analysis tool NEASE, which allows users to perform online splicing- and interactome-informed enrichment analysis on RNA-seq data. In two application cases (multiple sclerosis and mice models of cardiac diseases), we show the utility of DIGGER 2.0 for deeper exploration and functional interpretation of changes in alternative splicing in human and mouse disorders. DIGGER 2.0 is available at https://exbio.wzw.tum.de/digger/.

There are primarily two computational approaches to alternative splicing (AS) detection using short reads: splice junction-based and exon-based approaches. Despite their shared goal of addressing the same biological problem, these approaches have not been reconciled before. We devised a novel graph structure and algorithm aimed at mapping between the exonic parts and splicing events detected by the two different methods. Through simulations, we demonstrated disparities in sensitivity and specificity between splice junction-based and exon-based methods. When applied to empirical data, there were large discrepancies in the results, suggesting that the methods are complementary. With the discrepancies localized to individual events and exonic parts, we were able to gain insights into the strengths and weaknesses inherent in each approach. Finally, we integrated the results to generate a comprehensive list of both common and unique AS events detected by both methodologies.

Trivalent arsenic, i.e., As(III), is the main form of arsenic species in the environment. Prolonged exposure to arsenicals through ingesting contaminated food and water has been implicated in the development of cancer and diabetes as well as cardiovascular and neurodegenerative diseases. A number of studies have been conducted to examine the mechanisms underlying the toxic effects of arsenite exposure, where As(III) was shown to displace Zn(II) and impair the functions of zinc-binding proteins. Considering that many zinc-binding proteins can bind to nucleic acids, we reason that systematic identification of arsenite-binding proteins in the nucleus may provide additional insights into the molecular targets of arsenite, thereby improving our understanding of the mechanisms of arsenic toxicity. Here, we conducted a quantitative proteomics experiment relying on affinity pull-down from nuclear protein lysate with a biotin-As(III) probe to identify nuclear arsenite-binding proteins. We uncovered a number of candidate As(III)-binding proteins that are involved in mRNA splicing, DNA repair, and replication. We also found that As(III) could bind to splicing factor 1 (SF1) and that this binding perturbs mRNA splicing in human cells. Together, our work provided insights into the mechanisms of As(III) toxicity by revealing new nuclear protein targets of As(III).

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that primarily affects the motor neurons, causing progressive muscle weakness and paralysis. While research has focused on understanding pathological mechanisms in the motor cortex and spinal cord, there is growing evidence that extra-motor brain regions may also play a role in the pathogenesis or progression of ALS.

We generated 165 sample-matched post-mortem brain transcriptomes from 22 sporadic ALS patients with pTDP-43 pathological staging and 11 non-neurological controls. For each individual, five brain regions underwent mRNA sequencing: motor cortex (pTDP-43 inclusions always present), prefrontal cortex and hippocampus (pTDP-43 inclusions sometimes present), and occipital cortex and cerebellum (pTDP-43 inclusions rarely present). We examined gene expression, cell-type composition, transcript usage (% contribution of a transcript to total gene expression) and alternative splicing, comparing ALS-specific changes between brain regions. We also considered whether post-mortem pTDP-43 pathological stage classification defined ALS subgroups with distinct gene expression profiles.

Significant gene expression changes were observed in ALS cases for all five brain regions, with the cerebellum demonstrating the largest number of total (> 3,000) and unique (60%) differentially expressed genes. Pathway enrichment and predicted activity were largely concordant across brain regions, suggesting that ALS-linked mechanisms, including inflammation, mitochondrial dysfunction and oxidative stress, are also dysregulated in non-motor brain regions. Switches in transcript usage were identified for a small set of genes including increased usage of a POLDIP3 transcript, associated with TDP-43 loss-of-function, in the cerebellum and a XBP1 transcript, indicative of unfolded protein response activity, in the motor cortex. Extensive variation in RNA splicing was identified in the ALS brain, with 26-41% of alternatively spliced genes unique to a given brain region. This included detection of TDP-43-associated cryptic splicing events such as the STMN2 cryptic exon which was shown to have a pTDP-43 pathology-specific expression pattern. Finally, ALS patients with stage 4 pTDP-43 pathology demonstrated distinct gene and protein expression changes in the cerebellum.

Together our findings highlighted widespread transcriptome alterations in ALS post-mortem brain and showed that, despite the absence of pTDP-43 pathology in the cerebellum, extensive and pTDP-43 pathological stage-specific RNA changes are evident in this brain region.

TDP-43 mislocalization, aggregation, and loss of splicing function are neuropathological hallmarks in over 97% of Amyotrophic Lateral Sclerosis (ALS), 45% of Frontotemporal Lobar Degeneration (FTLD), and 60% of Alzheimer's Disease, which has been reclassified as LATE-NC. However, the mechanisms underlying TDP-43 dysfunction remain elusive. Here, we utilize APEX2-driven proximity labeling and mass spectrometry to characterize the context-dependent TDP-43 interactome in conditions of cytoplasmic mislocalization, impaired RNA-binding contributing to aggregation, and oxidative stress. We describe context-dependent interactors, including disrupted interactions with splicing-related proteins and altered biomolecular condensate (BMC) associations. By integrating ALS and FTLD snRNA-seq data, we uncover disease-relevant molecular alterations and validate our dataset through a functional screen that identifies key TDP- 43 regulators. We demonstrate that disrupting nuclear speckle integrity, particularly through the downregulation of the splicing factor SRRM2, promotes TDP-43 mislocalization and loss of function. Additionally, we identify NUFIP2 as an interactor associated with mislocalization that sequesters TDP-43 into cytoplasmic aggregates and co-localizes with TDP-43 pathology in patient tissue. We also highlight HNRNPC as a potent TDP-43 splicing regulator, where precise modulation of TDP-43 or HNRNPC can rescue cryptic exon splicing. These findings provide mechanistic insights and potential therapeutic targets for TDP-43 dysfunction.

Perturbation of mRNA splicing is commonly observed in human cancers and plays a role in various aspects of cancer hallmarks. Understanding the mechanisms and functions of alternative splicing (AS) not only enables us to explore the complex regulatory network involved in tumour initiation and progression but also reveals potential for RNA-based cancer treatment strategies. This review provides a comprehensive summary of the significance of AS in liver cancer, covering the regulatory mechanisms, cancer-related AS events, abnormal splicing regulators, as well as the interplay between AS and post-transcriptional and post-translational regulations. We present the current bioinformatic approaches and databases to detect and analyse AS in cancer, and discuss the implications and perspectives of AS in the treatment of liver cancer.

Alternative splicing (AS) plays crucial post-transcriptional gene function regulation roles in eukaryotic. Despite progress in studying AS at the RNA level, existing methods for AS event identification face challenges such as inefficiency, lengthy processing times, and limitations in capturing the complexity of RNA sequences. To overcome these challenges, we evaluated 10 AS detection tools and selected rMATS for dataset construction. We then developed a multi-scale convolutional and Transformer-based model (MCTASmRNA) to classify AS events in mRNA sequences without relying on a reference genome. To handle the problem of large intra-class and small inter-class difference in AS event sequences, we incorporated an efficient channel attention mechanism and designed a new joint loss function to optimize MCTASmRNA training. MCTASmRNA outperformed baseline models, with an accuracy improvement and exhibited enhanced cross-species generalizability. This model provides valuable support for AS research across different organisms. Future work will focus on optimizing and expanding the model to further explore the complex mechanisms underlying AS.

Protein arginine methyltransferase 6 (PRMT6) is a well-characterized epigenetic regulator that methylates histone H3 at arginine 2 (H3R2me2a) in both promoter and enhancer regions, thereby modulating transcriptional initiation. We report here that PRMT6 also regulates gene expression at the post-transcriptional level in the neural pluripotent state and during neuronal differentiation of NT2/D1 cells. PRMT6 knockout causes widespread alternative splicing changes in NT2/D1 cells, most frequently cassette exon alterations. Most of the PRMT6-dependent splicing targets are not transcriptionally affected by the enzyme and regulated in an H3R2me2a-independent manner. However, for a small subset of splicing events, the PRMT6-mediated deposition of H3R2me2a overlaps with the splice site, suggesting a potential dual function in both transcriptional and co-/post-transcriptional regulation. The splicing targets of PRMT6 include ribosomal proteins, splicing factors, and chromatin-modifying enzymes such as PRMT4, DNMT3B, and ASH2L, some of which are associated with differentiation decisions. Taken together, our results in NT2/D1 cells show that PRMT6 exerts predominantly H3R2me2a-independent functions in RNA splicing, which may contribute to pluripotency and neuronal identity.

Millions of ribosomes are packed within mammalian cells, yet we lack tools to visualize them in toto and characterize their subcellular composition. In this study, we present ribosome expansion microscopy (RiboExM) to visualize individual ribosomes and an optogenetic proximity-labeling technique (ALIBi) to probe their composition. We generated a super-resolution ribosomal map, revealing subcellular translational hotspots and enrichment of 60S subunits near polysomes at the endoplasmic reticulum (ER). We found that Lsg1 tethers 60S to the ER and regulates translation of select proteins. Additionally, we discovered ribosome heterogeneity at mitochondria guiding translation of metabolism-related transcripts. Lastly, we visualized ribosomes in neurons, revealing a dynamic switch between monosomes and polysomes in neuronal translation. Together, these approaches enable exploration of ribosomal localization and composition at unprecedented resolution.

Background/Objectives: Missplicing caused by toxic DMPK-mRNA is described as a hallmark of myotonic dystrophy type 1 (DM1). Yet, there is an expressional misregulation of additional splicing factors described in DM1, and missplicing has been observed in other myopathies. Here, we compare the expressional misregulation of splicing factors and the resulting splicing profiles between three different hereditary myopathies. Methods: We used publicly available RNA-sequencing datasets for the three muscular dystrophies-DM1, facioscapulohumeral muscular dystrophy (FSHD) and Emery-Dreifuss muscular dystrophy (EDMD)-to compare the splicing factor expression and missplicing genome-wide using DESeq2 and MAJIQ. Results: Upregulation of alternative splicing factors and downregulation of constitutive splicing factors were detected for all three myopathies, but to different degrees. Correspondingly, the missplicing events were mostly alternative exon usage and skipping events. In DM1, most events were alternative exon usage and intron retention, while exon skipping was prevalent in FSHD, with EDMD being in between the two other myopathies in terms of splice factor regulation as well as missplicing. Accordingly, the missplicing events were only partially shared between these three myopathies, sometimes with the same locus being spliced differently. Conclusions: This indicates a combination of primary (toxic RNA) and more downstream effects (splicing factor expression) resulting in the DM1 missplicing phenotype. Furthermore, this analysis allows the distinction between disease-specific missplicing and general myopathic splicing alteration to be used as biomarkers.

Poison exons (PEs) are a class of alternatively spliced exons whose inclusion targets mRNA transcripts for degradation via the nonsense-mediated decay (NMD) pathway. Although a role for NMD as an essential mRNA quality control pathway has long been appreciated, recent advances in RNA sequencing (RNA-seq) strategies and analyses have revealed that its coupling to RNA splicing is broadly used to regulate mRNA stability and abundance. Regulation of PE splicing affects patterns of targeted degradation across the transcriptome and influences gene expression in both healthy and disease states. Importantly, PEs represent a novel therapeutic opportunity to modulate the expression of disease-relevant genes with sequence-specific resolution. We review the emergence of PE splicing in endogenous gene regulation, its misregulation in disease, and the ways in which it can be leveraged for therapeutic benefit.

Transposable elements (TEs) drive genome evolution and can affect gene expression through diverse mechanisms. In breast cancer, disrupted regulation of TE sequences may facilitate tumor-specific transcriptomic alterations. We examine 142,514 full-length isoforms derived from long-read RNA sequencing (LR-seq) of 30 breast samples to investigate the effects of TEs on the breast cancer transcriptome. Approximately half of these isoforms contain TE sequences, and these contribute to half of the novel annotated splice junctions. We quantify splicing of these LR-seq derived isoforms in 1,135 breast tumors from The Cancer Genome Atlas (TCGA) and 1,329 healthy tissue samples from the Genotype-Tissue Expression (GTEx), and find 300 TE-overlapping tumor-specific splicing events. Some splicing events are enriched in specific breast cancer subtypes - for example, a TE-driven transcription start site upstream of ERBB2 in HER2 + tumors, and several TE-mediated splicing events are associated with patient survival and poor prognosis. The full-length sequences we capture with LR-seq reveal thousands of isoforms with signatures of RNA editing, including a novel isoform belonging to RHOA; a gene previously implicated in tumor progression. We utilize our full-length isoforms to discover polymorphic TE insertions that alter splicing and validate one of these events in breast cancer cell lines. Together, our results demonstrate the widespread effects of dysregulated TEs on breast cancer transcriptomes and highlight the advantages of long-read isoform sequencing for understanding TE biology. TE-derived isoforms may alter the expression of genes important in cancer and can potentially be used as novel, disease-specific therapeutic targets or biomarkers.One sentence summary: Transposable elements generate alternative isoforms and alter post-transcriptional regulation in human breast cancer.

Alternative pre-mRNA splicing (AS) is a fundamental regulatory process that generates transcript diversity and cell type variation. We developed Shiba, a comprehensive method that integrates transcript assembly, splicing event identification, read counting, and differential splicing analysis across RNA-seq platforms. Shiba excels in capturing annotated and unannotated AS events with superior accuracy, sensitivity, and reproducibility. It addresses the often-overlooked issue of junction read imbalance, significantly reducing false positives to aid target prioritization and downstream analyses. Unlike other tools that require large numbers of biological replicates or resulting in low sensitivity and high false positives, Shiba's statistics framework is agnostic to sample size, as demonstrated by simulated data and its effective application to real n= 1 RNA-seq datasets. To extend its utility to single-cell RNA-seq, we developed scShiba, which applies Shiba's pseudobulk approach to analyze splicing at the cluster level. scShiba successfully revealed AS regulation in developmental dopaminergic neurons and differences between excitatory and inhibitory neurons. Both Shiba and scShiba are available in Docker/Singularity containers and Snakemake pipelines, ensuring reproducibility. With their comprehensive capabilities, Shiba and scShiba enable systematic quantification of alternative splicing events across various platforms, laying a solid foundation for mechanistic exploration of the functional complexity in RNA splicing.

Recent development involving long-read single-cell transcriptome sequencing (lr-scRNA-Seq) represents a significant leap forward in single-cell genomics. With the recent introduction of R10 flowcells by Oxford Nanopore, we propose that previous computational methods designed to handle high sequencing error rates are less relevant, and that the traditional approach using short reads to compile "barcode space" (candidate barcode list) to de-multiplex long reads are no longer necessary. Instead, computational methods should now shift focus on harnessing the unique benefits of long reads to analyze transcriptome complexity. In this context, we introduce a comprehensive suite of computational methods named Single-Cell Omics for Transcriptome CHaracterization (SCOTCH). SCOTCH supports both Nanopore and PacBio sequencing platforms, and is compatible with single-cell library preparation protocols from both 10X Genomics and Parse Biosciences. Through a sub-exon identification strategy with dynamic thresholding and read mapping scores, SCOTCH precisely aligns reads to known isoforms and discover novel isoforms, efficiently addressing ambiguous mapping challenges commonly encountered in long-read single-cell data. Comprehensive simulations and real data analyses across multiple platforms (including 10X Genomics and Parse Bioscience, paired with Illumina or Nanopore sequencing technologies with R9 and R10 flowcells, as well as PacBio sequencing) demonstrated that SCOTCH outperforms existing methods in mapping accuracy, quantification accuracy and novel isoform detection, while also uncovering novel biological insights on transcriptome complexity at the single-cell level.

The current diagnostic rate for patients with suspected Mendelian genetic disorders is only 25 to 58%, even though whole exome sequencing (WES) is part of the standard of care. One reason for the low diagnostic rate is that traditional WES analysis methods struggle to detect RNA splicing aberrations. It is estimated that 15-50% of human pathogenic variants alter splicing, with numerous splice-altering variants being causal for known Mendelian disorders. Developing reliable diagnostic tools to detect, quantify, prioritize, and visualize RNA splicing aberrations from patient RNA sequencing is therefore crucial. We present MAJIQ-CLIN, a method to address this need to augment clinical diagnostic using RNA-Seq and compare it to existing tools. We include the first systematic evaluation of the accuracy of such tools using synthetic data across several aberration types and transcript inclusion levels; we also evaluate accuracy on several datasets of biologically validated solved test cases. We show that MAJIQ-CLIN compares favorably to existing tools in both accuracy and efficiency, then use MAJIQ-CLIN to investigate several unsolved patient cases from the Undiagnosed Diseases Network.

Huntington's disease (HD) is caused by a CAG repeat expansion in the HTT gene, leading to altered gene expression. However, the mechanisms leading to disrupted RNA processing in HD remain unclear. Here we identify TDP-43 and the N6-methyladenosine (m6A) writer protein METTL3 to be upstream regulators of exon skipping in multiple HD systems. Disrupted nuclear localization of TDP-43 and cytoplasmic accumulation of phosphorylated TDP-43 occurs in HD mouse and human brains, with TDP-43 also co-localizing with HTT nuclear aggregate-like bodies distinct from mutant HTT inclusions. The binding of TDP-43 onto RNAs encoding HD-associated differentially expressed and aberrantly spliced genes is decreased. Finally, m6A RNA modification is reduced on RNAs abnormally expressed in the striatum of HD R6/2 mouse brain, including at clustered sites adjacent to TDP-43 binding sites. Our evidence supports TDP-43 loss of function coupled with altered m6A modification as a mechanism underlying alternative splicing in HD.

Alternative splicing (AS) of pre-mRNA plays a crucial role in tissue-specific gene regulation, with disease implications due to splicing defects. Predicting and manipulating AS can therefore uncover new regulatory mechanisms and aid in therapeutics design. We introduce TrASPr+BOS, a generative AI model with Bayesian Optimization for predicting and designing RNA for tissue-specific splicing outcomes. TrASPr is a multi-transformer model that can handle different types of AS events and generalize to unseen cellular conditions. It then serves as an oracle, generating labeled data to train a Bayesian Optimization for Splicing (BOS) algorithm to design RNA for condition-specific splicing outcomes. We show TrASPr+BOS outperforms existing methods, enhancing tissue-specific AUPRC by up to 2.4 fold and capturing tissue-specific regulatory elements. We validate hundreds of predicted novel tissue-specific splicing variations and confirm new regulatory elements using dCas13. We envision TrASPr+BOS as a light yet accurate method researchers can probe or adopt for specific tasks.

RNA sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases that hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local splicing variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest. Primers are designed using Optimal Prime, a novel machine learning algorithm trained on the performance of thousands of primer sequences. In experimental benchmarks, LSV-seq achieves high on-target capture rates and concordance with RNA-seq, while requiring significantly lower sequencing depth. Leveraging deep learning splicing code predictions, we used LSV-seq to target events with low coverage in GTEx RNA-seq data and newly discover hundreds of tissue-specific splicing events. Our results demonstrate the ability of LSV-seq to quantify splicing of events of interest at high-throughput and with exceptional sensitivity.

Retinoic acid inducible gene I (RIG-I)-like receptors (RLRs), including RIG-I, MDA5 and LGP2, recognize viral RNA to mount an antiviral interferon (IFN) response RLRs share three different protein domains: C-terminal domain, DExD/H box RNA helicase domain, and an N-terminal domain with two tandem repeats (CARDs). LGP2 lacks tandem CARD and is not able to induce an IFN response. However, LGP2 positively enhances MDA5 and negatively regulates RIG-I signaling. In this study, we determined the LGP2 alternative transcripts in humans to further comprehend the mechanism of its regulation, their evolutionary origin, and the isoforms functionallity. The results showed new eight alternative transcripts in the samples tested. The presence of these transcripts demonstrated that the main mechanisms for the regulation of LGP2 expression are both by insertion of introns and by the loss of exons. The phylogenetic analysis of the comparison between sequences from exon 1 to exon 3 of humans and those previously described in non-human primates showed three well-differentiated groups (lineages) originating from gorillas, suggesting that the transspecies evolution has been maintained for 10 million years. The corresponding protein models (isoforms) were also established, obtaining four isoforms: one complete and three others lacking the C-terminal domain or this domain and the partial or total He2 Helicase domain, which would compromise the functionality of LGP2. In conclusion, this is the first study that elucidate the large genomic organization and complex transcriptional regulation of human LGP2, its pattern of sequence generation, and a mode of evolutionary inheritance across species.

Alternative pre-mRNA splicing (AS) is a fundamental regulatory process that generates transcript diversity and cell type variation. We developed Shiba, a comprehensive method that integrates transcript assembly, splicing event identification, read counting, and differential splicing analysis across RNA-seq platforms. Shiba excels in capturing annotated and unannotated AS events with superior accuracy, sensitivity, and reproducibility. It addresses the often-overlooked issue of junction read imbalance, significantly reducing false positives to aid target prioritization and downstream analyses. Unlike other tools that require large numbers of biological replicates or resulting in low sensitivity and high false positives, Shiba's statistics framework is agnostic to sample size, as demonstrated by simulated data and its effective application to real n=1 RNA-seq datasets. To extend its utility to single-cell RNA-seq, we developed scShiba, which applies Shiba's pseudobulk approach to analyze splicing at the cluster level. scShiba successfully revealed AS regulation in developmental dopaminergic neurons and differences between excitatory and inhibitory neurons. Both Shiba and scShiba are available in Docker/Singularity containers and Snakemake pipelines, ensuring reproducibility. With their comprehensive capabilities, Shiba and scShiba enable systematic quantification of alternative splicing events across various platforms, laying a solid foundation for mechanistic exploration of the functional complexity in RNA splicing.

Mutations of the MECP2 gene lead to Rett syndrome (RTT), a rare developmental disease causing severe intellectual and physical disability. How the loss or defective function of MeCP2 mediates RTT is still poorly understood. MeCP2 is a global gene expression regulator, acting at transcriptional and post-transcriptional levels. Little attention has been given so far to the contribution of alternative splicing (AS) dysregulation to RTT pathophysiology. To perform a comparative analysis of publicly available RNA sequencing (RNA-seq) studies and generate novel data resources for AS, we explored 100 human datasets and 130 mouse datasets from Mecp2-mutant models, processing data for gene expression and alternative splicing. Our comparative analysis across studies indicates common species-specific differentially expressed genes (DEGs) and differentially alternatively spliced (DAS) genes. Human and mouse dysregulated genes are involved in two main functional categories: cell-extracellular matrix adhesion regulation and synaptic functions, the first category more significantly enriched in human datasets. Our extensive bioinformatics study indicates, for the first time, a significant dysregulation of AS in human RTT datasets, suggesting the crucial contribution of altered RNA processing to the pathophysiology of RTT.

Reliable methods for detecting and analyzing gene expression are necessary tools for understanding development and investigating biological responses to genetic and environmental perturbation. With its fully sequenced genome, invariant cell lineage, transparent body, wiring diagram, detailed anatomy, and wide array of genetic tools, Caenorhabditis elegans is an exceptionally useful model organism for linking gene expression to cellular phenotypes. The development of new techniques in recent years has greatly expanded our ability to detect gene expression at high resolution. Here, we provide an overview of gene expression methods for C. elegans, including techniques for detecting transcripts and proteins in situ, bulk RNA sequencing of whole worms and specific tissues and cells, single-cell RNA sequencing, and high-throughput proteomics. We discuss important considerations for choosing among these techniques and provide an overview of publicly available online resources for gene expression data.

Nuclear speckles are membraneless organelles that associate with active transcription sites and participate in post-transcriptional mRNA processing. During the cell cycle, nuclear speckles dissolve following phosphorylation of their protein components. Here, we identify the PP1 family as the phosphatases that counteract kinase-mediated dissolution. PP1 overexpression increases speckle cohesion and leads to retention of mRNA within speckles and the nucleus. Using APEX2 proximity labeling combined with RNA-sequencing, we characterize the recruitment of specific RNAs. We find that many transcripts are preferentially enriched within nuclear speckles compared to the nucleoplasm, particularly chromatin- and nucleus-associated transcripts. While total polyadenylated RNA retention increases with nuclear speckle cohesion, the ratios of most mRNA species to each other are constant, indicating non-selective retention. We further find that cellular responses to heat shock, oxidative stress, and hypoxia include changes to the phosphorylation and cohesion of nuclear speckles and to mRNA retention. Our results demonstrate that tuning the material properties of nuclear speckles provides a mechanism for the acute control of mRNA localization.

Myotonic dystrophy type 1 (DM1), the leading cause of adult-onset muscular dystrophy, is caused by a CTG repeat expansion. Expression of the repeat causes widespread alternative splicing (AS) defects and downstream pathogenesis, including significant skeletal muscle impacts. The HSA LR mouse model plays a significant role in therapeutic development. This mouse model features a transgene composed of approximately 220 interrupted CTG repeats, which results in skeletal muscle pathology that mirrors DM1. To better understand this model and the growing number of therapeutic approaches developed with it, we performed a meta-analysis of publicly available RNA sequencing data for AS changes across three widely examined skeletal muscles: quadriceps, gastrocnemius, and tibialis anterior. Our analysis demonstrated that transgene expression correlated with the extent of splicing dysregulation across these muscles from gastrocnemius (highest), quadriceps (medium), to tibialis anterior (lowest). We identified 95 splicing events consistently dysregulated across all examined datasets. Comparison of splicing rescue across seven therapeutic approaches showed a range of rescue across the 95 splicing events from the three muscle groups. This analysis contributes to our understanding of the HSA LR model and the growing number of therapeutic approaches currently in preclinical development for DM1.

RNA-modifying enzymes have recently garnered considerable attention due to their relevance in cancer biology, identifying them as potential targets for novel therapeutic intervention. THUMPD3 was recently identified as an RNA methyltransferase catalysing N2-methylguanosine (m2G) within certain tRNAs. In this study, we unveil a novel role for THUMPD3 in lung cancer cells. Depletion of the enzyme from lung cancer cells significantly impairs their fitness, negatively impacting key cellular processes such as proliferation and migration. Notably, exogenous expression of THUMPD3 in normal lung fibroblasts stimulates their proliferation rate. Additionally, transcriptome-wide analyses reveal that depletion of THUMPD3 from lung cancer cells induces substantial changes in the expression of cell surface proteins, including those comprising the extracellular matrix (ECM). We further demonstrate that THUMPD3 maintains expression of an extra-domain B (EDB) containing pro-tumour isoform of Fibronectin-1 mRNA, encoding FN1, an important ECM protein. Crucially, depletion of THUMPD3 promotes an alternative splicing event that removes the EDB-encoding exon from Fibronectin-1. This is consistent with THUMPD3 depletion reducing cellular proliferation and migration. Moreover, depletion of THUMPD3 selectively and preferentially affects the alternative splicing of ECM and cell adhesion molecule encoding transcripts, as well as those encoding neurodevelopmental proteins. Overall, these findings highlight THUMPD3 as an important player in regulating cancer-relevant alternative splicing and they provide a rationale for further investigations into THUMPD3 as a candidate target in anti-cancer therapy.

Splicing factors are affected by recurrent somatic mutations and copy number variations in several types of haematologic and solid malignancies, which is often seen as prima facie evidence that splicing aberrations can drive cancer initiation and progression. However, numerous spliceosome components also 'moonlight' in DNA repair and other cellular processes, making their precise role in cancer difficult to pinpoint. Still, few would deny that dysregulated mRNA splicing is a pervasive feature of most cancers. Correctly interpreting these molecular fingerprints can reveal novel tumour vulnerabilities and untapped therapeutic opportunities. Yet multiple technological challenges, lingering misconceptions, and outstanding questions hinder clinical translation. To start with, the general landscape of splicing aberrations in cancer is not well defined, due to limitations of short-read RNA sequencing not adept at resolving complete mRNA isoforms, as well as the shallow read depth inherent in long-read RNA-sequencing, especially at single-cell level. Although individual cancer-associated isoforms are known to contribute to cancer progression, widespread splicing alterations could be an equally important and, perhaps, more readily actionable feature of human cancers. This is to say that in addition to 'repairing' mis-spliced transcripts, possible therapeutic avenues include exacerbating splicing aberration with small-molecule spliceosome inhibitors, targeting recurrent splicing aberrations with synthetic lethal approaches, and training the immune system to recognize splicing-derived neoantigens.

Pangenomes are becoming a powerful framework to perform many bioinformatics analyses taking into account the genetic variability of a population, thus reducing the bias introduced by a single reference genome. With the wider diffusion of pangenomes, integrating genetic variability with transcriptome diversity is becoming a natural extension that demands specific methods for its exploration. In this work, we extend the notion of spliced pangenomes to that of annotated spliced pangenomes; this allows us to introduce a formal definition of Alternative Splicing (AS) events on a graph structure. To investigate the usage of graph pangenomes for the quantification of AS events across conditions, we developed pantas, the first pangenomic method for the detection and differential analysis of AS events from short RNA-Seq reads. A comparison with state-of-the-art linear reference-based approaches proves that pantas achieves competitive accuracy, making spliced pangenomes effective for conducting AS events quantification and opening future directions for the analysis of population-based transcriptomes.

The serine-/arginine-rich splicing factor 2 (SRSF2) plays pivotal roles in pre-mRNA processing and gene transcription. Recurrent mutations, particularly a proline-to-histidine substitution at position 95 (P95H), are common in neoplastic diseases. Here, we assess SRSF2's diverse functions in squamous cell carcinoma. We show that SRSF2 deletion or homozygous P95H mutation both cause extensive DNA damage leading to cell-cycle arrest. Mechanistically, SRSF2 regulates efficient bi-directional transcription of DNA replication and repair genes, independent from its function in splicing. Further, SRSF2 haploinsufficiency induces DNA damage without halting the cell cycle. Exposing mouse skin to tumor-promoting carcinogens enhances the clonal expansion of heterozygous Srsf2 P95H epidermal cells but unexpectedly inhibits tumor formation. To survive carcinogen treatment, Srsf2 P95H+/- cells undergo substantial transcriptional rewiring and restore bi-directional gene expression. Thus, our study underscores SRSF2's importance in regulating transcription to orchestrate the cell cycle and the DNA damage response.

RNA splicing enables the functional adaptation of cells to changing contexts. Impaired splicing has been associated with diseases, including retinitis pigmentosa, but the underlying molecular mechanisms and cellular responses remain poorly understood. In this work, we report that deficiency of ubiquitin-specific protease 39 (USP39) in human cell lines, zebrafish larvae, and mice led to impaired spliceosome assembly and a cytotoxic splicing profile characterized by the use of cryptic 5' splice sites. Disruptive cryptic variants evaded messenger RNA (mRNA) surveillance pathways and were translated into misfolded proteins, which caused proteotoxic aggregates, endoplasmic reticulum (ER) stress, and, ultimately, cell death. The detrimental consequence of splicing-induced proteotoxicity could be mitigated by up-regulating the ubiquitin-proteasome system and selective autophagy. Our findings provide insight into the molecular pathogenesis of spliceosome-associated diseases.

Mapping transcriptomic variations using either short- or long-read RNA sequencing is a staple of genomic research. Long reads are able to capture entire isoforms and overcome repetitive regions, whereas short reads still provide improved coverage and error rates. Yet, open questions remain, such as how to quantitatively compare the technologies, can we combine them, and what is the benefit of such a combined view? We tackle these questions by first creating a pipeline to assess matched long- and short-read data using a variety of transcriptome statistics. We find that across data sets, algorithms, and technologies, matched short-read data detects ∼30% more splice junctions, such that ∼10%-30% of the splice junctions included at ≥20% by short reads are missed by long reads. In contrast, long reads detect many more intron-retention events and can detect full isoforms, pointing to the benefit of combining the technologies. We introduce MAJIQ-L, an extension of the MAJIQ software, to enable a unified view of transcriptome variations from both technologies and demonstrate its benefits. Our software can be used to assess any future long-read technology or algorithm and can be combined with short-read data for improved transcriptome analysis.

Global warming poses a threat for crops, therefore, the identification of thermotolerance mechanisms is a priority. In plants, the core factors that regulate transcription under heat stress (HS) are well described and include several HS transcription factors (HSFs). Despite the relevance of alternative splicing in HS response and thermotolerance, the core regulators of HS-sensitive alternative splicing have not been identified. In tomato, alternative splicing of HSFA2 is important for acclimation to HS. Here, we show that several members of the serine/arginine-rich family of splicing factors (SRSFs) suppress HSFA2 intron splicing. Individual-nucleotide resolution UV cross-linking and immunoprecipitation (iCLIP) combined with RNA-Seq revealed that RS2Z35 and RS2Z36, which make up a plant-specific clade of SR proteins, not only regulate HSFA2 but approximately 50% of RNAs that undergo HS-sensitive alternative splicing, with preferential binding to purine-rich RNA motifs. Single and double CRISPR rs2z mutant lines show a dysregulation of splicing and exhibit lower basal and acquired thermotolerance compared to wild type plants. Our results suggest that RS2Z35 and RS2Z36 have a central role in mitigation of the negative effects of HS on RNA splicing homeostasis, and their emergence might have contributed to the increased capacity of plants to acclimate to high temperatures.

Relapsed or refractory B-cell acute lymphoblastic leukemia (B-ALL) is a major cause of pediatric cancer-related deaths. Relapse-specific mutations do not account for all chemotherapy failures in B-ALL patients, suggesting additional mechanisms of resistance. By mining RNA sequencing datasets of paired diagnostic/relapse pediatric B-ALL samples, we discovered pervasive alternative splicing (AS) patterns linked to relapse and affecting drivers of resistance to glucocorticoids, antifolates, and thiopurines. Most splicing variations represented cassette exon skipping, "poison" exon inclusion, and intron retention, phenocopying well-documented loss-of-function mutations. In contrast, relapse-associated AS of NT5C2 mRNA yielded an isoform with the functionally uncharacterized in-frame exon 6a. Incorporation of the 8-amino acid sequence SQVAVQKR into this enzyme created a putative phosphorylation site and resulted in elevated nucleosidase activity, which is a known consequence of gain-of-function mutations in NT5C2 and a common determinant of 6-mercaptopurine resistance. Consistent with this finding, NT5C2ex6a and the R238W hotspot variant conferred comparable levels of resistance to 6-mercaptopurine in B-ALL cells both in vitro and in vivo. Furthermore, both NT5C2ex6a and the R238W variant induced collateral sensitivity to the inosine monophosphate dehydrogenase inhibitor mizoribine. These results ascribe to splicing perturbations an important role in chemotherapy resistance in relapsed B-ALL and suggest that inosine monophosphate dehydrogenase inhibitors, including the commonly used immunosuppressive agent mycophenolate mofetil, could be a valuable therapeutic option for treating thiopurine-resistant leukemias. Significance: Alternative splicing is a potent mechanism of acquired drug resistance in relapsed/refractory acute lymphoblastic leukemias that has diagnostic and therapeutic implications for patients who lack mutations in known chemoresistance genes.

Previously, we showed that the germ cell-specific nuclear protein RBMXL2 represses cryptic splicing patterns during meiosis and is required for male fertility (Ehrmann et al., 2019). Here, we show that in somatic cells the similar yet ubiquitously expressed RBMX protein has similar functions. RBMX regulates a distinct class of exons that exceed the median human exon size. RBMX protein-RNA interactions are enriched within ultra-long exons, particularly within genes involved in genome stability, and repress the selection of cryptic splice sites that would compromise gene function. The RBMX gene is silenced during male meiosis due to sex chromosome inactivation. To test whether RBMXL2 might replace the function of RBMX during meiosis we induced expression of RBMXL2 and the more distantly related RBMY protein in somatic cells, finding each could rescue aberrant patterns of RNA processing caused by RBMX depletion. The C-terminal disordered domain of RBMXL2 is sufficient to rescue proper splicing control after RBMX depletion. Our data indicate that RBMX and RBMXL2 have parallel roles in somatic tissues and the germline that must have been conserved for at least 200 million years of mammalian evolution. We propose RBMX family proteins are particularly important for the splicing inclusion of some ultra-long exons with increased intrinsic susceptibility to cryptic splice site selection.

TDP-43 mislocalization and pathology occurs across a range of neurodegenerative diseases, but the pathways that modulate TDP-43 in neurons are not well understood. We generated a Halo-TDP-43 knock-in iPSC line and performed a genome-wide CRISPR interference FACS-based screen to identify modifiers of TDP-43 levels in neurons. A meta-analysis of our screen and publicly available screens identified both specific hits and pathways present across multiple screens, the latter likely responsible for generic protein level maintenance. We identified BORC, a complex required for anterograde lysosome transport, as a specific modifier of TDP-43 protein, but not mRNA, levels in neurons. BORC loss led to longer half-life of TDP-43 and other proteins, suggesting lysosome location is required for proper protein turnover. As such, lysosome location and function are crucial for maintaining TDP-43 protein levels in neurons.