Alu RNA Modulates the Expression of Cell Cycle Genes in Human Fibroblasts

Adenovirus small E1A directs activation of Alu transcription at YAP/TEAD- and AP-1-bound enhancers through interactions with the EP400 chromatin remodeler

Alu retrotransposons, which form the largest family of mobile DNA elements in the human genome, have recently come to attention as a potential source of regulatory novelties, most notably by participating in enhancer function. Even though Alu transcription by RNA polymerase III is subjected to tight epigenetic silencing, their expression has long been known to increase in response to various types of stress, including viral infection. Here we show that, in primary human fibroblasts, adenovirus small e1a triggered derepression of hundreds of individual Alus by promoting TFIIIB recruitment by Alu-bound TFIIIC. Epigenome profiling revealed an e1a-induced decrease of H3K27 acetylation and increase of H3K4 monomethylation at derepressed Alus, making them resemble poised enhancers. The enhancer nature of e1a-targeted Alus was confirmed by the enrichment, in their upstream regions, of the EP300/CBP acetyltransferase, EP400 chromatin remodeler and YAP1 and FOS transcription factors. The physical interaction of e1a with EP400 was critical for Alu derepression, which was abrogated upon EP400 ablation. Our data suggest that e1a targets a subset of enhancer Alus whose transcriptional activation, which requires EP400 and is mediated by the e1a-EP400 interaction, may participate in the manipulation of enhancer activity by adenoviruses.

Targeting transposable elements in cancer: developments and opportunities

Transposable elements (TEs), comprising nearly 50% of the human genome, have transitioned from being perceived as "genomic junk" to key players in cancer progression. Contemporary research links TE regulatory disruptions with cancer development, underscoring their therapeutic potential. Advances in long-read sequencing, computational analytics, single-cell sequencing, proteomics, and CRISPR-Cas9 technologies have enriched our understanding of TEs' clinical implications, notably their impact on genome architecture, gene regulation, and evolutionary processes. In cancer, TEs, including long interspersed element-1 (LINE-1), Alus, and long terminal repeat (LTR) elements, demonstrate altered patterns, influencing both tumorigenic and tumor-suppressive mechanisms. TE-derived nucleic acids and tumor antigens play critical roles in tumor immunity, bridging innate and adaptive responses. Given their central role in oncology, TE-targeted therapies, particularly through reverse transcriptase inhibitors and epigenetic modulators, represent a novel avenue in cancer treatment. Combining these TE-focused strategies with existing chemotherapy or immunotherapy regimens could enhance efficacy and offer a new dimension in cancer treatment. This review delves into recent TE detection advancements, explores their multifaceted roles in tumorigenesis and immune regulation, discusses emerging diagnostic and therapeutic approaches centered on TEs, and anticipates future directions in cancer research.

Retrotransposons in Werner syndrome-derived macrophages trigger type I interferon-dependent inflammation in an atherosclerosis model

The underlying mechanisms of atherosclerosis, the second leading cause of death among Werner syndrome (WS) patients, are not fully understood. Here, we establish an in vitro co-culture system using macrophages (iMφs), vascular endothelial cells (iVECs), and vascular smooth muscle cells (iVSMCs) derived from induced pluripotent stem cells. In co-culture, WS-iMφs induces endothelial dysfunction in WS-iVECs and characteristics of the synthetic phenotype in WS-iVSMCs. Transcriptomics and open chromatin analysis reveal accelerated activation of type I interferon signaling and reduced chromatin accessibility of several transcriptional binding sites required for cellular homeostasis in WS-iMφs. Furthermore, the H3K9me3 levels show an inverse correlation with retrotransposable elements, and retrotransposable element-derived double-stranded RNA activates the DExH-box helicase 58 (DHX58)-dependent cytoplasmic RNA sensing pathway in WS-iMφs. Conversely, silencing type I interferon signaling in WS-iMφs rescues cell proliferation and suppresses cellular senescence and inflammation. These findings suggest that Mφ-specific inhibition of type I interferon signaling could be targeted to treat atherosclerosis in WS patients.

The Pol III transcriptome: Basic features, recurrent patterns, and emerging roles in cancer

The RNA polymerase III (Pol III) transcriptome is universally comprised of short, highly structured noncoding RNA (ncRNA). Through RNA-protein interactions, the Pol III transcriptome actuates functional activities ranging from nuclear gene regulation (7SK), splicing (U6, U6atac), and RNA maturation and stability (RMRP, RPPH1, Y RNA), to cytoplasmic protein targeting (7SL) and translation (tRNA, 5S rRNA). In higher eukaryotes, the Pol III transcriptome has expanded to include additional, recently evolved ncRNA species that effectively broaden the footprint of Pol III transcription to additional cellular activities. Newly evolved ncRNAs function as riboregulators of autophagy (vault), immune signaling cascades (nc886), and translation (Alu, BC200, snaR). Notably, upregulation of Pol III transcription is frequently observed in cancer, and multiple ncRNA species are linked to both cancer progression and poor survival outcomes among cancer patients. In this review, we outline the basic features and functions of the Pol III transcriptome, and the evidence for dysregulation and dysfunction for each ncRNA in cancer. When taken together, recurrent patterns emerge, ranging from shared functional motifs that include molecular scaffolding and protein sequestration, overlapping protein interactions, and immunostimulatory activities, to the biogenesis of analogous small RNA fragments and noncanonical miRNAs, augmenting the function of the Pol III transcriptome and further broadening its role in cancer. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Processing > Processing of Small RNAs RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

Estimating tissue-specific peptide abundance from public RNA-Seq data

Several novel MHC class I epitope prediction tools additionally incorporate the abundance levels of the peptides' source antigens and have shown improved performance for predicting immunogenicity. Such tools require the user to input the MHC alleles and peptide sequences of interest, as well as the abundance levels of the peptides' source proteins. However, such expression data is often not directly available to users, and retrieving the expression level of a peptide's source antigen from public databases is not trivial. We have developed the Peptide eXpression annotator (pepX), which takes a peptide as input, identifies from which proteins the peptide can be derived, and returns an estimate of the expression level of those source proteins from selected public databases. We have also investigated how the abundance level of a peptide can be best estimated in cases when it can originate from multiple transcripts and proteins and found that summing up transcript-level expression values performs best in distinguishing ligands from decoy peptides.

The role of antigen expression in shaping the repertoire of HLA presented ligands

Human leukocyte antigen (HLA) presentation of peptides is a prerequisite of T cell immune activation. The understanding of the rules defining this event has large implications for our knowledge of basic immunology and for the rational design of immuno-therapeutics and vaccines. Historically, most of the available prediction methods have been solely focused on the information related to antigen processing and presentation. Recent work has, however, demonstrated that method performance can be boosted by integrating information related to antigen abundance. Here we expand on these later findings and develop an extended version of NetMHCpan, called NetMHCpanExp, integrating information on antigen abundance from RNA-Seq experiments. In line with earlier works, the model demonstrates improved performance for both HLA ligand and cancer neoantigen epitope prediction. Optimal results are obtained by use of sample-specific abundance information but also reference datasets can be applied with a limited performance drop. The developed tool is available at https://services.healthtech.dtu.dk/service.php?NetMHCpanExp-1.0.

Blood Transcriptome Analysis of Septic Patients Reveals a Long Non-Coding Alu-RNA in the Complement C5a Receptor 1 Gene

Many severe inflammation conditions are complement-dependent with the complement component C5a-C5aR1 axis as an important driver. At the RNA level, the blood transcriptome undergoes programmed expression of coding and long non-coding RNAs to combat invading microorganisms. Understanding the expression of long non-coding RNAs containing Alu elements in inflammation is important for reconstructing cell fate trajectories leading to severe disease. We have assembled a pipeline for computation mining of new Alu-containing long non-coding RNAs by intersecting immune genes with known Alu coordinates in the human genome. By applying the pipeline to patient bulk RNA-seq data with sepsis, we found immune genes containing 48 Alu insertion as robust candidates for further study. Interestingly, 1 of the 48 candidates was located within the complement system receptor gene C5aR1 and holds promise as a target for RNA therapeutics.

Epigenetic regulation of human non-coding RNA gene transcription

Recent investigations on the non-protein-coding transcriptome of human cells have revealed previously hidden layers of gene regulation relying on regulatory non-protein-coding (nc) RNAs, including the widespread ncRNA-dependent regulation of epigenetic chromatin states and of mRNA translation and stability. However, despite its centrality, the epigenetic regulation of ncRNA genes has received relatively little attention. In this mini-review, we attempt to provide a synthetic account of recent literature suggesting an unexpected complexity in chromatin-dependent regulation of ncRNA gene transcription by the three human nuclear RNA polymerases. Emerging common features, like the heterogeneity of chromatin states within ncRNA multigene families and their influence on 3D genome organization, point to unexplored issues whose investigation could lead to a better understanding of the whole human epigenomic network.

Combined assessment of MHC binding and antigen abundance improves T cell epitope predictions

Many steps of the MHC class I antigen processing pathway can be predicted using computational methods. Here we show that epitope predictions can be further improved by considering abundance levels of peptides' source proteins. We utilized biophysical principles and existing MHC binding prediction tools in concert with abundance estimates of source proteins to derive a function that estimates the likelihood of a peptide to be an MHC class I ligand. We found that this combination improved predictions for both naturally eluted ligands and cancer neoantigen epitopes. We compared the use of different measures of antigen abundance, including mRNA expression by RNA-Seq, gene translation by Ribo-Seq, and protein abundance by proteomics on a dataset of SARS-CoV-2 epitopes. Epitope predictions were improved above binding predictions alone in all cases and gave the highest performance when using proteomic data. Our results highlight the value of incorporating antigen abundance levels to improve epitope predictions.

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HLA ligands originate from highly expressed transcripts

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Antigen abundance and HLA binding are independent predictors of ligands and epitopes

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Utilizing RNA-Seq, Ribo-Seq, or proteomic data improves epitope predictions

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Cancer-type-matched TCGA RNA-Seq data can be used to estimate gene expression in patient

Coordination of transcription and processing of tRNA

Coordination of transcription and processing of RNA is a basic principle in regulation of gene expression in eukaryotes. In the case of mRNA, coordination is primarily founded on a co-transcriptional processing mechanism by which a nascent precursor mRNA undergoes maturation via cleavage and modification by the transcription machinery. A similar mechanism controls the biosynthesis of rRNA. However, the coordination of transcription and processing of tRNA, a rather short transcript, remains unknown. Here, we present a model for high molecular weight initiation complexes of human RNA polymerase III that assemble on tRNA genes and process precursor transcripts to mature forms. These multifunctional initiation complexes may support co-transcriptional processing, such as the removal of the 5' leader of precursor tRNA by RNase P. Based on this model, maturation of tRNA is predetermined prior to transcription initiation.

The Malignant Role of Exosomes as Nanocarriers of Rare RNA Species

Nowadays, advancements in the oncology sector regarding diagnosis methods allow us to specifically detect an increased number of cancer patients, some of them in incipient stages. However, one of the main issues consists of the invasive character of most of the diagnosis protocols or complex medical procedures associated with it, that impedes part of the patients to undergo routine checkups. Therefore, in order to increase the number of cancer cases diagnosed in incipient stages, other minimally invasive alternatives must be considered. The current review paper presents the value of rare RNA species isolated from circulatory exosomes as biomarkers of diagnosis, prognosis or even therapeutic intervention. Rare RNAs are most of the time overlooked in current research in favor of the more abundant RNA species like microRNAs. However, their high degree of stability, low variability and, for most of them, conservation across species could shift the interest toward these types of RNAs. Moreover, due to their low abundance, the variation interval in terms of the number of sequences with differential expression between samples from healthy individuals and cancer patients is significantly diminished and probably easier to interpret in a clinical context.

Interpreting and integrating big data in non-coding RNA research

In the last two decades, we have witnessed an impressive crescendo of non-coding RNA studies, due to both the development of high-throughput RNA-sequencing strategies and an ever-increasing awareness of the involvement of newly discovered ncRNA classes in complex regulatory networks. Together with excitement for the possibility to explore previously unknown layers of gene regulation, these advancements led to the realization of the need for shared criteria of data collection and analysis and for novel integrative perspectives and tools aimed at making biological sense of very large bodies of molecular information. In the last few years, efforts to respond to this need have been devoted mainly to the regulatory interactions involving ncRNAs as direct or indirect regulators of protein-coding mRNAs. Such efforts resulted in the development of new computational tools, allowing the exploitation of the information spread in numerous different ncRNA data sets to interpret transcriptome changes under physiological and pathological cell responses. While experimental validation remains essential to identify key RNA regulatory interactions, the integration of ncRNA big data, in combination with systematic literature mining, is proving to be invaluable in identifying potential new players, biomarkers and therapeutic targets in cancer and other diseases.