Noncoding Y RNAs regulate the levels, subcellular distribution and protein interactions of their Ro60 autoantigen partner

Biological basis of extensive pleiotropy between blood traits and cancer risk

BACKGROUND

The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations.

METHODS

Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis.

RESULTS

The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis.

CONCLUSIONS

This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.

Intracellular localisation and extracellular release of Y RNA and Y RNA binding proteins

Cells can communicate via the release and uptake of extracellular vesicles (EVs), which are nano-sized membrane vesicles that can transfer protein and RNA cargo between cells. EVs contain microRNAs and various other types of non-coding RNA, of which Y RNA is among the most abundant types. Studies on how RNAs and their binding proteins are sorted into EVs have mainly focused on comparing intracellular (cytoplasmic) levels of these RNAs to the extracellular levels in EVs. Besides overall transcriptional levels that may regulate sorting of RNAs into EVs, the process may also be driven by local intracellular changes in RNA/RBP concentrations. Changes in extracellular Y RNA have been linked to cancer and cardiovascular diseases. Although the loading of RNA cargo into EVs is generally thought to be influenced by cellular stimuli and regulated by RNA binding proteins (RBP), little is known about Y RNA shuttling into EVs. We previously reported that immune stimulation alters the levels of Y RNA in EVs independently of cytosolic Y RNA levels. This suggests that Y RNA binding proteins, and/or changes in the local Y RNA concentration at EV biogenesis sites, may affect Y RNA incorporation into EVs. Here, we investigated the subcellular distribution of Y RNA and Y RNA binding proteins in activated and non-activated THP1 macrophages. We demonstrate that Y RNA and its main binding protein Ro60 abundantly co-fractionate in organelles involved in EV biogenesis and in EVs. Cellular activation led to an increase in Y RNA concentration at EV biogenesis sites and this correlated with increased EV-associated levels of Y RNA and Ro60. These results suggest that Y RNA incorporation into EVs may be controlled by local intracellular changes in the concentration of Y RNA and their protein binding partners.

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.

NCYPred: A Bidirectional LSTM Network With Attention for Y RNA and Short Non-Coding RNA Classification

Short non-coding RNAs (sncRNAs) are involved in multiple cellular processes and can be divided into dozens of classes. Among such classes, Y RNAs have been gaining attention, being essential factors for the initiation of DNA replication on vertebrates, as well as potential tumor biomarkers. Homologs have also been described in nematodes and insects, as well as related sequences in bacteria. Methods capable of accurately predicting Y RNA transcripts are lacking. In this work, we developed an attention-based LSTM network and built a classification model able to classify sncRNAs (including Y RNA) directly from nucleotide sequences. A dataset consisting of 45,447 sncRNA sequences, from a wide range of organisms, obtained from Rfam 14.3 was built. Performance evaluation demonstrated that our proposed method, NCYPred (Non-Coding/Y RNA Prediction), can accurately predict Y RNA sequences and their homologs, as well as 11 additional classes, achieving results comparable with state-of-the-art methods. We also demonstrate that applying t-SNE on learned sequence representations could be useful for sequence analysis. Our model is freely available as a web-server (https://www.gpea.uem.br/ncypred/).

CoLoC-seq probes the global topology of organelle transcriptomes

Proper RNA localisation is essential for physiological gene expression. Various kinds of genome-wide approaches permit to comprehensively profile subcellular transcriptomes. Among them, cell fractionation methods, that couple RNase treatment of isolated organelles to the sequencing of protected transcripts, remain most widely used, mainly because they do not require genetic modification of the studied system and can be easily implemented in any cells or tissues, including in non-model species. However, they suffer from numerous false-positives since incompletely digested contaminant RNAs can still be captured and erroneously identified as resident transcripts. Here we introduce Controlled Level of Contamination coupled to deep sequencing (CoLoC-seq) as a new subcellular transcriptomics approach that efficiently bypasses this caveat. CoLoC-seq leverages classical enzymatic kinetics and tracks the depletion dynamics of transcripts in a gradient of an exogenously added RNase, with or without organellar membranes. By means of straightforward mathematical modelling, CoLoC-seq infers the localisation topology of RNAs and robustly distinguishes between genuinely resident, luminal transcripts and merely abundant surface-attached contaminants. Our generic approach performed well on human mitochondria and is in principle applicable to other membrane-bounded organelles, including plastids, compartments of the vacuolar system, extracellular vesicles, and viral particles.

Support for a career in science

I am so very honored to receive the Women in Cell Biology Sandra K. Masur Senior Leadership Award from the American Society for Cell Biology (ASCB), particularly because many of the previous awardees have served as mentors and sources of inspiration throughout my own career. I also thank the ASCB for always striving to be maximally inclusive, in terms of both the scientists it supports and its broad vision of what constitutes cell biology. As a graduate student I gave one of my first talks at an ASCB meeting, and I am proud to have been an ASCB member for almost 30 years. In this essay, I describe my own career to illustrate the support that I believe is needed to achieve a career in science.

Anti-Ro60 and anti-Ro52/TRIM21: Two distinct autoantibodies in systemic autoimmune diseases

As iconic and important diagnostic autoantibodies, anti-Ro60 and anti-Ro52/tri-partite motif-containing 21 (TRIM21) make a common appearance in a number of systemic autoimmune disorders such as systemic lupus erythematosus (SLE). These autoantibodies often co-exist together; yet despite their close relationship, there is no evidence that they are physically linked and probably reflect a convergence of separate processes of failed immunological tolerance. Confusingly, they are sometimes classed together as the "SSA" or "Ro" autoantibody system without clear distinction between the two. In this Short Communication, we discuss the diagnostic merits for separate detection and reporting of these two autoantibodies, and discuss avenues for future research. Indeed, further insight into their fascinating origins and pathogenic roles in autoimmunity will surely shed light on how we can prevent and treat devastating autoimmune disorders.

The Autoantigen Repertoire and the Microbial RNP World

Although autoimmunity and autoimmune disease (AID) are relatively common, the repertoire of autoantigens is paradoxically very limited. Highly enriched in this autoantigen repertoire are nucleic acids and their binding proteins, which together form large macromolecular structures. Most of these complexes are of ancient evolutionary origin, with homologs throughout multiple kingdoms of life. Why and if these nucleic acid-protein particles drive the development of autoimmunity remains unresolved. Recent advances in our understanding of the microbiome may provide clues about the origins of autoimmunity - and the particular puzzle of why the autoantigen repertoire is so particularly enriched in ribonucleoprotein particles (RNPs). We discuss the possibility that autoimmunity to some RNPs may arise from molecular mimicry to microbial orthologs.