Showing papers on "Gene expression published in 2020"

Generalizing RNA velocity to transient cell states through dynamical modeling.

Abstract: RNA velocity has opened up new ways of studying cellular differentiation in single-cell RNA-sequencing data. It describes the rate of gene expression change for an individual gene at a given time point based on the ratio of its spliced and unspliced messenger RNA (mRNA). However, errors in velocity estimates arise if the central assumptions of a common splicing rate and the observation of the full splicing dynamics with steady-state mRNA levels are violated. Here we present scVelo, a method that overcomes these limitations by solving the full transcriptional dynamics of splicing kinetics using a likelihood-based dynamical model. This generalizes RNA velocity to systems with transient cell states, which are common in development and in response to perturbations. We apply scVelo to disentangling subpopulation kinetics in neurogenesis and pancreatic endocrinogenesis. We infer gene-specific rates of transcription, splicing and degradation, recover each cell's position in the underlying differentiation processes and detect putative driver genes. scVelo will facilitate the study of lineage decisions and gene regulation.

NicheNet: modeling intercellular communication by linking ligands to target genes

Abstract: Computational methods that model how gene expression of a cell is influenced by interacting cells are lacking. We present NicheNet (https://github.com/saeyslab/nichenetr), a method that predicts ligand-target links between interacting cells by combining their expression data with prior knowledge on signaling and gene regulatory networks. We applied NicheNet to tumor and immune cell microenvironment data and demonstrate that NicheNet can infer active ligands and their gene regulatory effects on interacting cells.

Regulatory Mechanism of MicroRNA Expression in Cancer.

Abstract: Altered gene expression is the primary molecular mechanism responsible for the pathological processes of human diseases, including cancer. MicroRNAs (miRNAs) are virtually involved at the post-transcriptional level and bind to 3′ UTR of their target messenger RNA (mRNA) to suppress expression. Dysfunction of miRNAs disturbs expression of oncogenic or tumor-suppressive target genes, which is implicated in cancer pathogenesis. As such, a large number of miRNAs have been found to be downregulated or upregulated in human cancers and to function as oncomiRs or oncosuppressor miRs. Notably, the molecular mechanism underlying the dysregulation of miRNA expression in cancer has been recently uncovered. The genetic deletion or amplification and epigenetic methylation of miRNA genomic loci and the transcription factor-mediated regulation of primary miRNA often alter the landscape of miRNA expression in cancer. Dysregulation of the multiple processing steps in mature miRNA biogenesis can also cause alterations in miRNA expression in cancer. Detailed knowledge of the regulatory mechanism of miRNAs in cancer is essential for understanding its physiological role and the implications of cancer-associated dysfunction and dysregulation. In this review, we elucidate how miRNA expression is deregulated in cancer, paying particular attention to the cancer-associated transcriptional and post-transcriptional factors that execute miRNA programs.

mRNAs, proteins and the emerging principles of gene expression control.

Abstract: Gene expression involves transcription, translation and the turnover of mRNAs and proteins. The degree to which protein abundances scale with mRNA levels and the implications in cases where this dependency breaks down remain an intensely debated topic. Here we review recent mRNA-protein correlation studies in the light of the quantitative parameters of the gene expression pathway, contextual confounders and buffering mechanisms. Although protein and mRNA levels typically show reasonable correlation, we describe how transcriptomics and proteomics provide useful non-redundant readouts. Integrating both types of data can reveal exciting biology and is an essential step in refining our understanding of the principles of gene expression control.

Chromatin potential identified by shared single cell profiling of RNA and chromatin

Abstract: Cell differentiation and function are regulated across multiple layers of gene regulation, including the modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of the regulatory events leading to cell fate commitment. Here, we developed SHARE-seq, a highly scalable approach for measurement of chromatin accessibility and gene expression within the same single cell. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define Domains of Regulatory Chromatin (DORCs), which significantly overlap with super-enhancers. We show that during lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting changes in chromatin accessibility may prime cells for lineage commitment. We therefore develop a computational strategy (chromatin potential) to quantify chromatin lineage-priming and predict cell fate outcomes. Together, SHARE-seq provides an extensible platform to study regulatory circuitry across diverse cells within tissues.

The impact of sex on gene expression across human tissues

Abstract: Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows

Abstract: Single-cell RNA sequencing has been widely adopted to estimate the cellular composition of heterogeneous tissues and obtain transcriptional profiles of individual cells. Multiple approaches for optimal sample dissociation and storage of single cells have been proposed as have single-nuclei profiling methods. What has been lacking is a systematic comparison of their relative biases and benefits. Here, we compare gene expression and cellular composition of single-cell suspensions prepared from adult mouse kidney using two tissue dissociation protocols. For each sample, we also compare fresh cells to cryopreserved and methanol-fixed cells. Lastly, we compare this single-cell data to that generated using three single-nucleus RNA sequencing workflows. Our data confirms prior reports that digestion on ice avoids the stress response observed with 37 °C dissociation. It also reveals cell types more abundant either in the cold or warm dissociations that may represent populations that require gentler or harsher conditions to be released intact. For cell storage, cryopreservation of dissociated cells results in a major loss of epithelial cell types; in contrast, methanol fixation maintains the cellular composition but suffers from ambient RNA leakage. Finally, cell type composition differences are observed between single-cell and single-nucleus RNA sequencing libraries. In particular, we note an underrepresentation of T, B, and NK lymphocytes in the single-nucleus libraries. Systematic comparison of recovered cell types and their transcriptional profiles across the workflows has highlighted protocol-specific biases and thus enables researchers starting single-cell experiments to make an informed choice.

Nanopore direct RNA sequencing maps the complexity of Arabidopsis mRNA processing and m6A modification.

Abstract: Understanding genome organization and gene regulation requires insight into RNA transcription, processing and modification. We adapted nanopore direct RNA sequencing to examine RNA from a wild-type accession of the model plant Arabidopsis thaliana and a mutant defective in mRNA methylation (m6A). Here we show that m6A can be mapped in full-length mRNAs transcriptome-wide and reveal the combinatorial diversity of cap-associated transcription start sites, splicing events, poly(A) site choice and poly(A) tail length. Loss of m6A from 3' untranslated regions is associated with decreased relative transcript abundance and defective RNA 3' end formation. A functional consequence of disrupted m6A is a lengthening of the circadian period. We conclude that nanopore direct RNA sequencing can reveal the complexity of mRNA processing and modification in full-length single molecule reads. These findings can refine Arabidopsis genome annotation. Further, applying this approach to less well-studied species could transform our understanding of what their genomes encode.

In vivo antiviral host transcriptional response to SARS-CoV-2 by viral load, sex, and age.

Abstract: Despite limited genomic diversity, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown a wide range of clinical manifestations in different patient populations. The mechanisms behind these host differences are still unclear. Here, we examined host response gene expression across infection status, viral load, age, and sex among shotgun RNA sequencing profiles of nasopharyngeal (NP) swabs from 430 individuals with PCR-confirmed SARS-CoV-2 and 54 negative controls. SARS-CoV-2 induced a strong antiviral response with up-regulation of antiviral factors such as OAS1-3 and IFIT1-3 and T helper type 1 (Th1) chemokines CXCL9/10/11, as well as a reduction in transcription of ribosomal proteins. SARS-CoV-2 culture in human airway epithelial (HAE) cultures replicated the in vivo antiviral host response 7 days post infection, with no induction of interferon-stimulated genes after 3 days. Patient-matched longitudinal specimens (mean elapsed time = 6.3 days) demonstrated reduction in interferon-induced transcription, recovery of transcription of ribosomal proteins, and initiation of wound healing and humoral immune responses. Expression of interferon-responsive genes, including ACE2, increased as a function of viral load, while transcripts for B cell–specific proteins and neutrophil chemokines were elevated in patients with lower viral load. Older individuals had reduced expression of the Th1 chemokines CXCL9/10/11 and their cognate receptor CXCR3, as well as CD8A and granzyme B, suggesting deficiencies in trafficking and/or function of cytotoxic T cells and natural killer (NK) cells. Relative to females, males had reduced B cell–specific and NK cell–specific transcripts and an increase in inhibitors of nuclear factor kappa-B (NF-κB) signaling, possibly inappropriately throttling antiviral responses. Collectively, our data demonstrate that host responses to SARS-CoV-2 are dependent on viral load and infection time course, with observed differences due to age and sex that may contribute to disease severity.

The emerging role of RNA modifications in the regulation of mRNA stability

Abstract: Many studies have highlighted the importance of the tight regulation of mRNA stability in the control of gene expression. mRNA stability largely depends on the mRNA nucleotide sequence, which affects the secondary and tertiary structures of the mRNAs, and the accessibility of various RNA-binding proteins to the mRNAs. Recent advances in high-throughput RNA-sequencing techniques have resulted in the elucidation of the important roles played by mRNA modifications and mRNA nucleotide sequences in regulating mRNA stability. To date, hundreds of different RNA modifications have been characterized. Among them, several RNA modifications, including N6-methyladenosine (m6A), N6,2'-O-dimethyladenosine (m6Am), 8-oxo-7,8-dihydroguanosine (8-oxoG), pseudouridine (Ψ), 5-methylcytidine (m5C), and N4-acetylcytidine (ac4C), have been shown to regulate mRNA stability, consequently affecting diverse cellular and biological processes. In this review, we discuss our current understanding of the molecular mechanisms underlying the regulation of mammalian mRNA stability by various RNA modifications.

YTHDF2 promotes the liver cancer stem cell phenotype and cancer metastasis by regulating OCT4 expression via m6A RNA methylation.

Abstract: N6-methyladenosine (m6A) RNA methylation contributes to the cancer stem cell (CSC) phenotype through regulating gene expression. YTHDF2, an m6A reader, was shown to be associated with hepatocellular carcinoma (HCC) patient prognosis. However, the effect of YTHDF2 on liver CSC and cancer metastasis and the molecular mechanism of this effect have not been documented. Here, we show that YTHDF2 expression is negatively correlated with HCC patient survival in both data from the Cancer Genome Atlas (TCGA) database and clinical data from our center. By detecting CD133+ cells and carrying out sphere culture assays, we found that knockdown of YTHDF2 led to impaired stemness in Hep3B and Huh7 cells. In contrast, overexpression of YTHDF2 increased the CSC phenotype. Mechanistically, the knockdown and overexpression of YTHDF2 in liver cancer cells resulted in decreased and increased m6A levels in the 5'-untranslated region (UTR) of OCT4 mRNA, respectively, leading to decreased and increased OCT4 protein expression, respectively. A luciferase activity assay showed that mutation of the corresponding m6A methylation sequence in the 5'-UTR of OCT4 mRNA caused significantly decreased gene expression, suggesting a role for YTHDF2-dependent m6A methylation in protein translation. Polysome profiling results also indicated the knockdown and overexpression of YTHDF2 could decrease and increase OCT4 translation, respectively. In particular, overexpression of OCT4 rescued the impaired stemness caused by YTHDF2 depletion, which confirmed the effect of YTHDF2 on CSC phenotype is dependent on OCT4. In vivo, the loss of YTHDF2 reduced tumor burden and inhibited lung metastasis following orthotopic transplantation in nude mice. Last, we demonstrated that YTHDF2 expression is positively correlated with OCT4 expression and m6A levels in the 5'-UTR of OCT4 mRNA in clinical HCC specimens. In conclusion, YTHDF2 promotes the CSC liver phenotype and cancer metastasis by modulating the m6A methylation of OCT4 mRNA.

Molecular topography of an entire nervous system

Abstract: Nervous systems are constructed from a deep repertoire of neuron types but the underlying gene expression programs that specify individual neuron identities are poorly understood. To address this deficit, we have produced an expression profile of all 302 neurons of the C. elegans nervous system that matches the single cell resolution of its anatomy and wiring diagram. Our results suggest that individual neuron classes can be solely identified by combinatorial expression of specific gene families. For example, each neuron class expresses unique codes of ~23 neuropeptide-encoding genes and ~36 neuropeptide receptors thus pointing to an expansive "wireless" signaling network. To demonstrate the utility of this uniquely comprehensive gene expression catalog, we used computational approaches to (1) identify cis-regulatory elements for neuron-specific gene expression across the nervous system and (2) reveal adhesion proteins with potential roles in synaptic specificity and process placement. These data are available at cengen.org and can be interrogated at the web application CengenApp. We expect that this neuron-specific directory of gene expression will spur investigations of underlying mechanisms that define anatomy, connectivity and function throughout the C. elegans nervous system.

SPOTlight:Seeded NMF regression to Deconvolute Spatial Transcriptomics Spots with Single-Cell Transcriptomes

Abstract: The integration of orthogonal data modalities greatly supports the interpretation of transcriptomic landscapes in complex tissues. In particular, spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes, and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Using synthetic spots, simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. We trained the NMF regression model with sample-matched or external datasets, resulting in accurate and sensitive spatial predictions. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus. In human pancreatic cancer, we successfully segmented patient sections into healthy and cancerous areas, and further fine-mapped normal and neoplastic cell states. Trained on an external pancreatic tumor immune reference, we charted the localization of clinical-relevant and tumor-specific immune cell states. Using SPOTlight to detect regional enrichment of immune cells and their co-localization with tumor and adjacent stroma provides an illustrative example in its flexible application spectrum and future potential in digital pathology.

Mechanism of RNA modification N6-methyladenosine in human cancer.

Abstract: Since the breakthrough discoveries of DNA and histone modifications, the field of RNA modifications has gained increasing interest in the scientific community. The discovery of N6-methyladenosine (m6A), a predominantly internal epigenetic modification in eukaryotes mRNA, heralded the creation of the field of epi-transcriptomics. This post-transcriptional RNA modification is dynamic and reversible, and is regulated by methylases, demethylases and proteins that preferentially recognize m6A modifications. Altered m6A levels affect RNA processing, degradation and translation, thereby disrupting gene expression and key cellular processes, ultimately resulting in tumor initiation and progression. Furthermore, inhibitors and regulators of m6A-related factors have been explored as therapeutic approaches for treating cancer. In the present review, the mechanisms of m6A RNA modification, the clinicopathological relevance of m6A alterations, the type and frequency of alterations and the multiple functions it regulates in different types of cancer are discussed.

Deciphering eukaryotic gene-regulatory logic with 100 million random promoters.

Abstract: How transcription factors (TFs) interpret cis-regulatory DNA sequence to control gene expression remains unclear, largely because past studies using native and engineered sequences had insufficient scale. Here, we measure the expression output of >100 million synthetic yeast promoter sequences that are fully random. These sequences yield diverse, reproducible expression levels that can be explained by their chance inclusion of functional TF binding sites. We use machine learning to build interpretable models of transcriptional regulation that predict ~94% of the expression driven from independent test promoters and ~89% of the expression driven from native yeast promoter fragments. These models allow us to characterize each TF's specificity, activity and interactions with chromatin. TF activity depends on binding-site strand, position, DNA helical face and chromatin context. Notably, expression level is influenced by weak regulatory interactions, which confound designed-sequence studies. Our analyses show that massive-throughput assays of fully random DNA can provide the big data necessary to develop complex, predictive models of gene regulation.

Changes in m6A RNA methylation contribute to heart failure progression by modulating translation.

Abstract: Aims Deregulation of epigenetic processes and aberrant gene expression are important mechanisms in heart failure. Here we studied the potential relevance of m6A RNA methylation in heart failure development. Methods and results We analysed m6A RNA methylation via next-generation sequencing. We found that approximately one quarter of the transcripts in the healthy mouse and human heart exhibit m6A RNA methylation. During progression to heart failure we observed that changes in m6A RNA methylation exceed changes in gene expression both in mouse and human. RNAs with altered m6A RNA methylation were mainly linked to metabolic and regulatory pathways, while changes in RNA expression level mainly represented changes in structural plasticity. Mechanistically, we could link m6A RNA methylation to altered RNA translation and protein production. Interestingly, differentially methylated but not differentially expressed RNAs showed differential polysomal occupancy, indicating transcription-independent modulation of translation. Furthermore, mice with a cardiomyocyte restricted knockout of the RNA demethylase Fto exhibited an impaired cardiac function compared to control mice. Conclusions We could show that m6A landscape is altered in heart hypertrophy and heart failure. m6A RNA methylation changes lead to changes in protein abundance, unconnected to mRNA levels. This uncovers a new transcription-independent mechanisms of translation regulation. Therefore, our data suggest that modulation of epitranscriptomic processes such as m6A methylation might be an interesting target for therapeutic interventions.

Nucleated transcriptional condensates amplify gene expression.

Abstract: Membraneless organelles or condensates form through liquid–liquid phase separation1–4, which is thought to underlie gene transcription through condensation of the large-scale nucleolus5–7 or in smaller assemblies known as transcriptional condensates8–11. Transcriptional condensates have been hypothesized to phase separate at particular genomic loci and locally promote the biomolecular interactions underlying gene expression. However, there have been few quantitative biophysical tests of this model in living cells, and phase separation has not yet been directly linked with dynamic transcriptional outputs12,13. Here, we apply an optogenetic approach to show that FET-family transcriptional regulators exhibit a strong tendency to phase separate within living cells, a process that can drive localized RNA transcription. We find that TAF15 has a unique charge distribution among the FET family members that enhances its interactions with the C-terminal domain of RNA polymerase II. Nascent C-terminal domain clusters at primed genomic loci lower the energetic barrier for nucleation of TAF15 condensates, which in turn further recruit RNA polymerase II to drive transcriptional output. These results suggest that positive feedback between interacting transcriptional components drives localized phase separation to amplify gene expression. Wei et al. show that clusters of unphosphorylated RNA polymerase II seed the nucleation of phase-separated condensates of TAF15, which further recruit RNA polymerase II to amplify transcriptional activation.

Single-nucleus RNA-seq identifies Huntington disease astrocyte states.

Abstract: Huntington Disease (HD) is an inherited movement disorder caused by expanded CAG repeats in the Huntingtin gene. We have used single nucleus RNASeq (snRNASeq) to uncover cellular phenotypes that change in the disease, investigating single cell gene expression in cingulate cortex of patients with HD and comparing the gene expression to that of patients with no neurological disease. In this study, we focused on astrocytes, although we found significant gene expression differences in neurons, oligodendrocytes, and microglia as well. In particular, the gene expression profiles of astrocytes in HD showed multiple signatures, varying in phenotype from cells that had markedly upregulated metallothionein and heat shock genes, but had not completely lost the expression of genes associated with normal protoplasmic astrocytes, to astrocytes that had substantially upregulated glial fibrillary acidic protein (GFAP) and had lost expression of many normal protoplasmic astrocyte genes as well as metallothionein genes. When compared to astrocytes in control samples, astrocyte signatures in HD also showed downregulated expression of a number of genes, including several associated with protoplasmic astrocyte function and lipid synthesis. Thus, HD astrocytes appeared in variable transcriptional phenotypes, and could be divided into several different “states”, defined by patterns of gene expression. Ultimately, this study begins to fill the knowledge gap of single cell gene expression in HD and provide a more detailed understanding of the variation in changes in gene expression during astrocyte “reactions” to the disease.

The Nuclear Factor Kappa B (NF-kB) signaling in cancer development and immune diseases.

Abstract: The nuclear factor kappa B (NF-kB) family of transcription factors plays an essential role as stressors in the cellular environment, and controls the expression of important regulatory genes such as immunity, inflammation, death, and cell proliferation. NF-kB protein is located in the cytoplasm, and can be activated by various cellular stimuli. There are two pathways for NF-kB activation, as the canonical and non-canonical pathways, which require complex molecular interactions with adapter proteins and phosphorylation and ubiquitinase enzymes. Accordingly, this increases NF-kB translocation in the nucleus and regulates gene expression. In this study, the concepts that emerge in different cellular systems allow the design of NF-kB function in humans. This would not only allow the development for rare diseases associated with NF-kB, but would also be used as a source of useful information to eliminate widespread consequences such as cancer or inflammatory/immune diseases.

Computational analysis of microRNA-mediated interactions in SARS-CoV-2 infection

Abstract: MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression found in more than 200 diverse organisms. Although it is still not fully established if RNA viruses could generate miRNAs, there are examples of miRNA like sequences from RNA viruses with regulatory functions. In the case of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there are several mechanisms that would make miRNAs impact the virus, like interfering with viral replication, translation and even modulating the host expression. In this study, we performed a machine learning based miRNA prediction analysis for the SARS-CoV-2 genome to identify miRNA-like hairpins and searched for potential miRNA-based interactions between the viral miRNAs and human genes and human miRNAs and viral genes. Overall, 950 hairpin structured sequences were extracted from the virus genome and based on the prediction results, 29 of them could be precursor miRNAs. Targeting analysis showed that 30 viral mature miRNA-like sequences could target 1,367 different human genes. PANTHER gene function analysis results indicated that viral derived miRNA candidates could target various human genes involved in crucial cellular processes including transcription, metabolism, defense system and several signaling pathways such as Wnt and EGFR signalings. Protein class-based grouping of targeted human genes showed that host transcription might be one of the main targets of the virus since 96 genes involved in transcriptional processes were potential targets of predicted viral miRNAs. For instance, basal transcription machinery elements including several components of human mediator complex (MED1, MED9, MED12L, MED19), basal transcription factors such as TAF4, TAF5, TAF7L and site-specific transcription factors such as STAT1 were found to be targeted. In addition, many known human miRNAs appeared to be able to target viral genes involved in viral life cycle such as S, M, N, E proteins and ORF1ab, ORF3a, ORF8, ORF7a and ORF10. Considering the fact that miRNA-based therapies have been paid attention, based on the findings of this study, comprehending mode of actions of miRNAs and their possible roles during SARS-CoV-2 infections could create new opportunities for the development and improvement of new therapeutics.

N 6 -Methyladenosine co-transcriptionally directs the demethylation of histone H3K9me2.

Abstract: A dynamic epigenome is critical for appropriate gene expression in development and health1-5. Central to this is the intricate process of transcription6-11, which integrates cellular signaling with chromatin changes, transcriptional machinery and modifications to messenger RNA, such as N6-methyladenosine (m6A), which is co-transcriptionally incorporated. The integration of these aspects of the dynamic epigenome, however, is not well understood mechanistically. Here we show that the repressive histone mark H3K9me2 is specifically removed by the induction of m6A-modified transcripts. We demonstrate that the methyltransferase METTL3/METTL14 regulates H3K9me2 modification. We observe a genome-wide correlation between m6A and occupancy by the H3K9me2 demethylase KDM3B, and we find that the m6A reader YTHDC1 physically interacts with and recruits KDM3B to m6A-associated chromatin regions, promoting H3K9me2 demethylation and gene expression. This study establishes a direct link between m6A and dynamic chromatin modification and provides mechanistic insight into the co-transcriptional interplay between RNA modifications and histone modifications.

N6-methyladenosine modification enables viral RNA to escape recognition by RNA sensor RIG-I.

Abstract: Internal N6-methyladenosine (m6A) modification is one of the most common and abundant modifications of RNA. However, the biological roles of viral RNA m6A remain elusive. Here, using human metapneumovirus (HMPV) as a model, we demonstrate that m6A serves as a molecular marker for innate immune discrimination of self from non-self RNAs. We show that HMPV RNAs are m6A methylated and that viral m6A methylation promotes HMPV replication and gene expression. Inactivating m6A addition sites with synonymous mutations or demethylase resulted in m6A-deficient recombinant HMPVs and virion RNAs that induced increased expression of type I interferon, which was dependent on the cytoplasmic RNA sensor RIG-I, and not on melanoma differentiation-associated protein 5 (MDA5). Mechanistically, m6A-deficient virion RNA induces higher expression of RIG-I, binds more efficiently to RIG-I and facilitates the conformational change of RIG-I, leading to enhanced interferon expression. Furthermore, m6A-deficient recombinant HMPVs triggered increased interferon in vivo and were attenuated in cotton rats but retained high immunogenicity. Collectively, our results highlight that (1) viruses acquire m6A in their RNA as a means of mimicking cellular RNA to avoid detection by innate immunity and (2) viral RNA m6A can serve as a target to attenuate HMPV for vaccine purposes. This study reports a novel function for the N6-methyladenosine RNA modification in allowing RIG-I to discriminate self from non-self RNA and shows that human metapneumovirus induces this modification of its RNA to evade recognition in vivo.

MicroRNAs (miRNAs) and Long Non-Coding RNAs (lncRNAs) as New Tools for Cancer Therapy: First Steps from Bench to Bedside.

Abstract: Non-coding RNAs represent a significant proportion of the human genome. After having been considered as ‘junk’ for a long time, non-coding RNAs are now well established as playing important roles in maintaining cellular homeostasis and functions. Some non-coding RNAs show cell- and tissue-specific expression patterns and are specifically deregulated under pathological conditions (e.g. cancer). Therefore, non-coding RNAs have been extensively studied as potential biomarkers in the context of different diseases with a focus on microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) for several years. Since their discovery, miRNAs have attracted more attention than lncRNAs in research studies; however, both families of non-coding RNAs have been established to play an important role in gene expression control, either as transcriptional or post-transcriptional regulators. Both miRNAs and lncRNAs can regulate key genes involved in the development of cancer, thus influencing tumour growth, invasion, and metastasis by increasing the activation of oncogenic pathways and limiting the expression of tumour suppressors. Furthermore, miRNAs and lncRNAs are also emerging as important mediators in drug-sensitivity and drug-resistance mechanisms. In the light of these premises, a number of pre-clinical and early clinical studies are exploring the potential of non-coding RNAs as new therapeutics. The aim of this review is to summarise the latest knowledge of the use of miRNAs and lncRNAs as therapeutic tools for cancer treatment.

Multimodal single-cell chromatin analysis with Signac

Abstract: The recent development of experimental methods for measuring chromatin state at single-cell resolution has created a need for computational tools capable of analyzing these datasets. Here we developed Signac, a framework for the analysis of single-cell chromatin data, as an extension of the Seurat R toolkit for single-cell multimodal analysis. Signac enables an end-to-end analysis of single-cell chromatin data, including peak calling, quantification, quality control, dimension reduction, clustering, integration with single-cell gene expression datasets, DNA motif analysis, and interactive visualization. Furthermore, Signac facilitates the analysis of multimodal single-cell chromatin data, including datasets that co-assay DNA accessibility with gene expression, protein abundance, and mitochondrial genotype. We demonstrate scaling of the Signac framework to datasets containing over 700,000 cells. Availability Installation instructions, documentation, and tutorials are available at: https://satijalab.org/signac/

An RNA thermoswitch regulates daytime growth in Arabidopsis.

Abstract: Temperature is a major environmental cue affecting plant growth and development. Plants often experience higher temperatures in the context of a 24 h day–night cycle, with temperatures peaking in the middle of the day. Here, we find that the transcript encoding the bHLH transcription factor PIF7 undergoes a direct increase in translation in response to warmer temperature. Diurnal expression of PIF7 transcript gates this response, allowing PIF7 protein to quickly accumulate in response to warm daytime temperature. Enhanced PIF7 protein levels directly activate the thermomorphogenesis pathway by inducing the transcription of key genes such as the auxin biosynthetic gene YUCCA8, and are necessary for thermomorphogenesis to occur under warm cycling daytime temperatures. The temperature-dependent translational enhancement of PIF7 messenger RNA is mediated by the formation of an RNA hairpin within its 5′ untranslated region, which adopts an alternative conformation at higher temperature, leading to increased protein synthesis. We identified similar hairpin sequences that control translation in additional transcripts including WRKY22 and the key heat shock regulator HSFA2, suggesting that this is a conserved mechanism enabling plants to respond and adapt rapidly to high temperatures. Temperature-dependent translational enhancement of PIF7 promotes gene expression for thermomorphogenesis in Arabidopsis during warm daytime. This enhanced translation is mediated by an RNA hairpin which shifts conformation at higher temperatures.