hnRNPM protects against the dsRNA-mediated interferon response by repressing LINE-associated cryptic splicing.

RNA splicing is pivotal in post-transcriptional gene regulation, yet the exponential expansion of intron length in humans poses a challenge for accurate splicing. Here, we identify hnRNPM as an essential RNA-binding protein that suppresses cryptic splicing through binding to deep introns, maintaining human transcriptome integrity. Long interspersed nuclear elements (LINEs) in introns harbor numerous pseudo splice sites. hnRNPM preferentially binds at intronic LINEs to repress pseudo splice site usage for cryptic splicing. Remarkably, cryptic exons can generate long dsRNAs through base-pairing of inverted ALU transposable elements interspersed among LINEs and consequently trigger an interferon response, a well-known antiviral defense mechanism. Significantly, hnRNPM-deficient tumors show upregulated interferon-associated pathways and elevated immune cell infiltration. These findings unveil hnRNPM as a guardian of transcriptome integrity by repressing cryptic splicing and suggest that targeting hnRNPM in tumors may be used to trigger an inflammatory immune response, thereby boosting cancer surveillance.

Splicing-specific transcriptome-wide association uncovers genetic mechanisms for schizophrenia.

Recent studies have highlighted the essential role of RNA splicing, a key mechanism of alternative RNA processing, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with genome-wide association studies to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-sequencing datasets, BrainGVEX and CommonMind, revealing 137 and 88 trait-associated exons (in 84 and 67 genes), respectively. Enriched biological functions in the associated gene sets converged on neuronal function and development, immune cell activation, and cellular transport, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein binding sites, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level, identifying 36 genes and 48 exons as putatively causal for SCZ. We highlight VPS45 and APOPT1, where splicing of specific exons was associated with disease risk, eluding detection by conventional gene expression analysis. Collectively, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ, providing a valuable approach for future investigations in this area.

dsRID: in silico identification of dsRNA regions using long-read RNA-seq data.

MOTIVATION: Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases. RESULTS: Here, we report dsRID (double-stranded RNA identifier), a machine-learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data. AVAILABILITY AND IMPLEMENTATION: Software implementation of dsRID, and genomic coordinates of regions predicted by dsRID in all samples are available at the GitHub repository: https://github.com/gxiaolab/dsRID.

dsRID: Editing-free in silico identification of dsRNA region using long-read RNA-seq data.

Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases. Here, we report dsRID (double-stranded RNA identifier), a machine learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data.

L-GIREMI uncovers RNA editing sites in long-read RNA-seq.

Although long-read RNA-seq is increasingly applied to characterize full-length transcripts it can also enable detection of nucleotide variants, such as genetic mutations or RNA editing sites, which is significantly under-explored. Here, we present an in-depth study to detect and analyze RNA editing sites in long-read RNA-seq. Our new method, L-GIREMI, effectively handles sequencing errors and read biases. Applied to PacBio RNA-seq data, L-GIREMI affords a high accuracy in RNA editing identification. Additionally, our analysis uncovered novel insights about RNA editing occurrences in single molecules and double-stranded RNA structures. L-GIREMI provides a valuable means to study nucleotide variants in long-read RNA-seq.

Widespread RNA hypoediting in schizophrenia and its relevance to mitochondrial function.

RNA editing, the endogenous modification of nucleic acids, is known to be altered in genes with important neurological function in schizophrenia (SCZ). However, the global profile and molecular functions of disease-associated RNA editing remain unclear. Here, we analyzed RNA editing in postmortem brains of four SCZ cohorts and uncovered a significant and reproducible trend of hypoediting in patients of European descent. We report a set of SCZ-associated editing sites via WGCNA analysis, shared across cohorts. Using massively parallel reporter assays and bioinformatic analyses, we observed that differential 3' untranslated region (3'UTR) editing sites affecting host gene expression were enriched for mitochondrial processes. Furthermore, we characterized the impact of two recoding sites in the mitofusin 1 (MFN1) gene and showed their functional relevance to mitochondrial fusion and cellular apoptosis. Our study reveals a global reduction of editing in SCZ and a compelling link between editing and mitochondrial function in the disease.

LINE-associated cryptic splicing induces dsRNA-mediated interferon response and tumor immunity.

RNA splicing plays a critical role in post-transcriptional gene regulation. Exponential expansion of intron length poses a challenge for accurate splicing. Little is known about how cells prevent inadvertent and often deleterious expression of intronic elements due to cryptic splicing. In this study, we identify hnRNPM as an essential RNA binding protein that suppresses cryptic splicing through binding to deep introns, preserving transcriptome integrity. Long interspersed nuclear elements (LINEs) harbor large amounts of pseudo splice sites in introns. hnRNPM preferentially binds at intronic LINEs and represses LINE-containing pseudo splice site usage for cryptic splicing. Remarkably, a subgroup of the cryptic exons can form long dsRNAs through base-pairing of inverted Alu transposable elements scattered in between LINEs and trigger interferon immune response, a well-known antiviral defense mechanism. Notably, these interferon-associated pathways are found to be upregulated in hnRNPM-deficient tumors, which also exhibit elevated immune cell infiltration. These findings unveil hnRNPM as a guardian of transcriptome integrity. Targeting hnRNPM in tumors may be used to trigger an inflammatory immune response thereby boosting cancer surveillance.

Genetic pathways regulating the longitudinal acquisition of cocaine self-administration in a panel of inbred and recombinant inbred mice.

To identify addiction genes, we evaluate intravenous self-administration of cocaine or saline in 84 inbred and recombinant inbred mouse strains over 10 days. We integrate the behavior data with brain RNA-seq data from 41 strains. The self-administration of cocaine and that of saline are genetically distinct. We maximize power to map loci for cocaine intake by using a linear mixed model to account for this longitudinal phenotype while correcting for population structure. A total of 15 unique significant loci are identified in the genome-wide association study. A transcriptome-wide association study highlights the Trpv2 ion channel as a key locus for cocaine self-administration as well as identifying 17 additional genes, including Arhgef26, Slc18b1, and Slco5a1. We find numerous instances where alternate splice site selection or RNA editing altered transcript abundance. Our work emphasizes the importance of Trpv2, an ionotropic cannabinoid receptor, for the response to cocaine.

Identifying Cell Type-Specific Transcription Factors by Integrating ChIP-seq and eQTL Data-Application to Monocyte Gene Regulation.

We describe a novel computational approach to identify transcription factors (TFs) that are candidate regulators in a human cell type of interest. Our approach involves integrating cell type-specific expression quantitative trait locus (eQTL) data and TF data from chromatin immunoprecipitation-to-tag-sequencing (ChIP-seq) experiments in cell lines. To test the method, we used eQTL data from human monocytes in order to screen for TFs. Using a list of known monocyte-regulating TFs, we tested the hypothesis that the binding sites of cell type-specific TF regulators would be concentrated in the vicinity of monocyte eQTLs. For each of 397 ChIP-seq data sets, we obtained an enrichment ratio for the number of ChIP-seq peaks that are located within monocyte eQTLs. We ranked ChIP-seq data sets according to their statistical significances for eQTL overlap, and from this ranking, we observed that monocyte-regulating TFs are more highly ranked than would be expected by chance. We identified 27 TFs that had significant monocyte enrichment scores and mapped them into a protein interaction network. Our analysis uncovered two novel candidate monocyte-regulating TFs, BCLAF1 and SIN3A. Our approach is an efficient method to identify candidate TFs that can be used for any cell/tissue type for which eQTL data are available.