Cell RNA Analysis Research Articles

Comparative computational RNA analysis of cardiac-derived progenitor cells and their extracellular vesicles

Stem/progenitor cells, including cardiac-derived c-kit+ progenitor cells (CPCs), are under clinical evaluation for treatment of cardiac disease. Therapeutic efficacy of cardiac cell therapy can be attributed to paracrine signaling and the release of extracellular vesicles (EVs) carrying diverse cargo molecules. Despite some successes and demonstrated safety, large variation in cell populations and preclinical/clinical outcomes remains a problem. Here, we investigated this variability by sequencing coding and non-coding RNAs of CPCs and CPC-EVs from 30 congenital heart disease patients and used machine learning methods to determine potential mechanistic insights. CPCs retained RNAs related to extracellular matrix organization and exported RNAs related to various signaling pathways to CPC-EVs. CPC-EVs are enriched in miRNA clusters related to cell proliferation and angiogenesis. With network analyses, we identified differences in non-coding RNAs which give insight into age-dependent functionality of CPCs. By taking a quantitative computational approach, we aimed to uncover sources of CPC cell therapy variability.

Application of nucleoside or nucleotide analogues in RNA dynamics and RNA-binding protein analysis.

Cellular RNAs undergo dynamic changes during RNA biological processes, which are tightly orchestrated by RNA-binding proteins (RBPs). Yet, the investigation of RNA dynamics is hurdled by highly abundant steady-state RNAs, which make the signals of dynamic RNAs less detectable. Notably, the exert of nucleoside or nucleotide analogue-based RNA technologies has provided a remarkable platform for RNA dynamics research, revealing diverse unnoticed features in RNA metabolism. In this review, we focus on the application of two types of analogue-based RNA sequencing, antigen-/antibody- and click chemistry-based methodologies, and summarize the RNA dynamics features revealed. Moreover, we discuss emerging single-cell newly transcribed RNA sequencing methodologies based on nucleoside analogue labeling, which provides novel insights into RNA dynamics regulation at single-cell resolution. On the other hand, we also emphasize the identification of RBPs that interact with polyA, non-polyA RNAs, or newly transcribed RNAs and also their associated RNA-binding domains at genomewide level through ultraviolet crosslinking and mass spectrometry in different contexts. We anticipated that further modification and development of these analogue-based RNA and RBP capture technologies will aid in obtaining an unprecedented understanding of RNA biology. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA Methods > RNA Analyses in Cells.

Single cell RNA analysis of antigen-presenting cells in inflammatory skin diseases

Single cell RNA analysis of antigen-presenting cells in inflammatory skin diseases

Single Cell RNA Analysis of Glioma Neural Stem Cells Shows Disturbed Amino Acids Metabolism and Axonal Growth Cone Dynamics in Glioblastoma Multiforme

Glioblastoma multiforme(GBM) is a group of aggressive tumors of the central nervous system. Despite advancements in the treatment of GBM, patients diagnosed with these tumors typically have a poor prognosis and poor quality of life as the disease develops. The single-cell RNA high-throughput sequencing processed data for Glioma cancer stem cells were taken from GEO and analyzed to find out the underlying expression differences at the gene level between glioma neural stem cells(GSCs) and Normal neural stem cells(NSCs). In the current study, we have performed an RNA-sequencing analysis between GSCs and NSCs to better understand the origin of GBM. We have performed bioinformatics analysis on the transcriptional profile of 134 samples which consisted of 75 GSCs and 59 NSCs obtained from the NCBI bio project(PRJNA546254). First, an exploratory analysis was performed which showed significant variation patterns between GSCs and NSCs. Subsequently, Deseq2 differential gene expression analysis identified 1436 differentially expressed genes be-tween GSCs and NSCs[(padj. value <0.05, log2 fold change (>=+/-1.5)]. This study reveals genes like MAOA, MAOB, GATM, GLDC, AMT, and SHMT1 as the key features contributing to the disturbed processes of Glycine, threonine, and serine amino acid metabolism, axonal cone growth curve, and cell migration in Glioma. Conclusively, our study also depicts gene expression changes in amyloid beta-binding protein in between GSCs and NSCs which plays an important role in tumor microenvironment formation. Besides, the results presented here reveal new insight into the progression of GBM and the identification of novel genes involved in gliomagenesis.

Multiplexed Single-Cell in situ RNA Profiling

The ability to quantify a large number of varied transcripts in single cells in their native spatial context is crucial to accelerate our understanding of health and disease. Bulk cell RNA analysis masks the heterogeneity in the cell population, while the conventional RNA imaging approaches suffer from low multiplexing capacity. Recent advances in multiplexed fluorescence in situ hybridization (FISH) methods enable comprehensive RNA profiling in individual cells in situ. These technologies will have wide applications in many biological and biomedical fields, including cell type classification, signaling network analysis, tissue architecture, disease diagnosis and patient stratification, etc. In this minireview, we will present the recent technological advances of multiplexed single-cell in situ RNA profiling assays, discuss their advantages and limitations, describe their biological applications, highlight the current challenges, and propose potential solutions.

Single cell T cell landscape and T cell receptor repertoire profiling of AML in context of PD-1 blockade therapy

In contrast to the curative effect of allogenic stem cell transplantation in acute myeloid leukemia via T cell activity, only modest responses are achieved with checkpoint-blockade therapy, which might be explained by T cell phenotypes and T cell receptor (TCR) repertoires. Here, we show by paired single-cell RNA analysis and TCR repertoire profiling of bone marrow cells in relapsed/refractory acute myeloid leukemia patients pre/post azacytidine+nivolumab treatment that the disease-related T cell subsets are highly heterogeneous, and their abundance changes following PD-1 blockade-based treatment. TCR repertoires expand and primarily emerge from CD8+ cells in patients responding to treatment or having a stable disease, while TCR repertoires contract in therapy-resistant patients. Trajectory analysis reveals a continuum of CD8+ T cell phenotypes, characterized by differential expression of granzyme B and a bone marrow-residing memory CD8+ T cell subset, in which a population with stem-like properties expressing granzyme K is enriched in responders. Chromosome 7/7q loss, on the other hand, is a cancer-intrinsic genomic marker of PD-1 blockade resistance in AML. In summary, our study reveals that adaptive T cell plasticity and genomic alterations determine responses to PD-1 blockade in acute myeloid leukemia.

Understanding the burden of interstitial lung disease post-COVID-19: the UK Interstitial Lung Disease-Long COVID Study (UKILD-Long COVID)

IntroductionThe COVID-19 pandemic has led to over 100 million cases worldwide. The UK has had over 4 million cases, 400 000 hospital admissions and 100 000 deaths. Many patients with...

FYN, SARS-CoV-2, and IFITM3 in the neurobiology of Alzheimer's disease

Introduction(IFITM3) is an innate immune protein that has been identified as a novel γ-secretase (γs) modulator. FYN is a kinase that stabilizes IFITM3 on the membrane, primes APP for amyloidogenic γs processing and mediates tau oligomerization. The purpose of this study is to explore the role of FYN and IFITM3 in AD and COVID-19, expanding on previous research from our group. MethodsA 520 gene signature containing FYN and IFITM3 (termed Ia) was extracted from a previously published meta-analysis of Alzheimer's disease (AD) bulk- and single nuclei sequencing data. Exploratory analyses involved meta-analysis of bulk and single cell RNA data for IFITM3 and FYN differential expression per CNS site and cellular type. Confirmatory analyses, gene set enrichment analysis (GSEA) on Ia was performed to detect overlapping enriched biological networks between COVID-19 with AD. ResultsBulk RNA data analysis revealed that IFITM3 and FYN were overexpressed in two CNS regions in AD vs. Controls: the temporal cortex Wilcoxon p-value=1.3e-6) and the parahippocampal cortex Wilcoxon p-value=0.012). Correspondingly, single cell RNA analysis of IFITM3 and FYN revealed that it was differentially expressed in neurons, glial and endothelial cells donated b AD patients, when compared to controls. DiscussionIFITM3 and FYN were found as interactors within biological networks overlapping between AD and SARS-CoV-2 infection. Within the context of SARS-CoV-2 induced tau aggregation and interactions between tau and Ab1–42, the FYN – IFITM3 regulome may outline an important innate immunity element responsive to viral infection and IFN-I signaling in both AD and COVID-19.

Distinct microglial response against Alzheimer's amyloid and tau pathologies characterized by P2Y12 receptor.

Microglia are the resident phagocytes of the central nervous system, and microglial activation is considered to play an important role in the pathogenesis of neurodegenerative diseases. Recent studies with single-cell RNA analysis of CNS cells in Alzheimer’s disease and diverse other neurodegenerative conditions revealed that the transition from homeostatic microglia to disease-associated microglia was defined by changes of gene expression levels, including down-regulation of the P2Y12 receptor gene (P2Y12R). However, it is yet to be clarified in Alzheimer’s disease brains whether and when this down-regulation occurs in response to amyloid-β and tau depositions, which are core pathological processes in the disease etiology. To further evaluate the significance of P2Y12 receptor alterations in the neurodegenerative pathway of Alzheimer’s disease and allied disorders, we generated an anti-P2Y12 receptor antibody and examined P2Y12 receptor expressions in the brains of humans and model mice bearing amyloid-β and tau pathologies. We observed that the brains of both Alzheimer’s disease and non-Alzheimer’s disease tauopathy patients and tauopathy model mice (rTg4510 and PS19 mouse lines) displayed declined microglial P2Y12 receptor levels in regions enriched with tau inclusions, despite an increase in the total microglial population. Notably, diminution of microglial immunoreactivity with P2Y12 receptor was noticeable prior to massive accumulations of phosphorylated tau aggregates and neurodegeneration in rTg4510 mouse brains, despite a progressive increase of total microglial population. On the other hand, Iba1-positive microglia encompassing compact and dense-cored amyloid-β plaques expressed P2Y12 receptor at varying levels in amyloid precursor protein (APP) mouse models (APP23 and AppNL-F/NL-F mice). By contrast, neuritic plaques in Alzheimer’s disease brains were associated with P2Y12 receptor-negative microglia. These data suggest that the down-regulation of microglia P2Y12 receptor, which is characteristic of disease-associated microglia, is intimately associated with tau rather than amyloid-β pathologies from an early stage and could be a sensitive index for neuroinflammatory responses to Alzheimer’s disease-related neurodegenerative processes.

GCAnno: a graph-based single cell type annotation method

BackgroundCurrent single cell analysis methods annotate cell types at cluster-level rather than ideally at single cell level. Multiple exchangeable clustering methods and many tunable parameters have a substantial impact on the clustering outcome, often leading to incorrect cluster-level annotation or multiple runs of subsequent clustering steps. To address these limitations, methods based on well-annotated reference atlas has been proposed. However, these methods are currently not robust enough to handle datasets with different noise levels or from different platforms.ResultsHere, we present gCAnno, a graph-based Cell type Annotation method. First, gCAnno constructs cell type-gene bipartite graph and adopts graph embedding to obtain cell type specific genes. Then, naïve Bayes (gCAnno-Bayes) and SVM (gCAnno-SVM) classifiers are built for annotation. We compared the performance of gCAnno to other state-of-art methods on multiple single cell datasets, either with various noise levels or from different platforms. The results showed that gCAnno outperforms other state-of-art methods with higher accuracy and robustness.ConclusionsgCAnno is a robust and accurate cell type annotation tool for single cell RNA analysis. The source code of gCAnno is publicly available at https://github.com/xjtu-omics/gCAnno.

Recent advances and future perspectives in vector-omics.

We have reviewed recent progress and the remaining challenges in vector-omics. We have highlighted several technologies and applications that facilitate novel biological insights beyond achieving a reference-quality genome assembly. Among other topics, we have discussed the applications of chromatin conformation capture, chromatin accessibility assays, optical mapping, full-length RNA sequencing, single cell RNA analysis, proteomics, and population genomics. We anticipate that we will witness a great expansion in vector-omics research not only in its application in a broad range of species, but also its ability to uncover novel genetic elements and tackle previously inaccessible regions of the genome. It is our hope that the continued innovation in device portability, cost reduction, and informatics support will in the foreseeable future bring vector-omics to every vector laboratory and field station in the world, which will have an unparalleled impact on basic research and the control of vector-borne infectious diseases.

De Novo Truncating Variants in the Last Exon of SEMA6B Cause Progressive Myoclonic Epilepsy

De novo variants (DNVs) cause many genetic diseases. When DNVs are examined in the whole coding regions of genes in next-generation sequencing analyses, pathogenic DNVs often cluster in a specific region. One such region is the last exon and the last 50bp of the penultimate exon, where truncating DNVs cause escape from nonsense-mediated mRNA decay [NMD(-) region]. Such variants can have dominant-negative or gain-of-function effects. Here, we first developed a resource of rates of truncating DNVs in NMD(-) regions under the null model of DNVs. Utilizing this resource, we performed enrichment analysis of truncating DNVs in NMD(-) regions in 346 developmental and epileptic encephalopathy (DEE) trios. We observed statistically significant enrichment of truncating DNVs in semaphorin 6B (SEMA6B) (p value: 2.8× 10-8; exome-wide threshold: 2.5× 10-6). The initial analysis of the 346 individuals and additionalscreening of 1,406 and 4,293 independent individuals affected by DEE and developmental disorders collectively identified four truncating DNVs in theSEMA6BNMD(-) region in five individuals who came from unrelated families (p value: 1.9×10-13) and consistently showed progressive myoclonic epilepsy. RNA analysis of lymphoblastoid cells established from an affected individual showed that the mutant allele escaped NMD, indicating stable production of the truncated protein. Importantly, heterozygous truncating variants in the NMD(+) region of SEMA6B are observed in general populations, and SEMA6B is most likely loss-of-function tolerant. Zebrafish expressing truncating variants in the NMD(-) region of SEMA6B orthologs displayed defective development of brain neurons and enhanced pentylenetetrazole-induced seizure behavior. In summary, we show that truncating DNVs in the final exon of SEMA6B cause progressive myoclonic epilepsy.

Dissolvable Polyacrylamide Beads for High-Throughput Droplet DNA Barcoding.

Droplet‐based single cell sequencing technologies, such as inDrop, Drop‐seq, and 10X Genomics, are catalyzing a revolution in the understanding of biology. Barcoding beads are key components for these technologies. What is limiting today are barcoding beads that are easy to fabricate, can efficiently deliver primers into drops, and thus achieve high detection efficiency. Here, this work reports an approach to fabricate dissolvable polyacrylamide beads, by crosslinking acrylamide with disulfide bridges that can be cleaved with dithiothreitol. The beads can be rapidly dissolved in drops and release DNA barcode primers. The dissolvable beads are easy to synthesize, and the primer cost for the beads is significantly lower than that for the previous barcoding beads. Furthermore, the dissolvable beads can be loaded into drops with >95% loading efficiency of a single bead per drop and the dissolution of beads does not influence reverse transcription or the polymerase chain reaction (PCR) in drops. Based on this approach, the dissolvable beads are used for single cell RNA and protein analysis.

Conservation of a core neurite transcriptome across neuronal types and species.

The intracellular localization of mRNAs allows neurons to control gene expression in neurite extensions (axons and dendrites) and respond rapidly to local stimuli. This plays an important role in diverse processes including neuronal growth and synaptic plasticity, which in turn serves as a foundation for learning and memory. Recent high-throughput analyses have revealed that neurites contain hundreds to thousands of mRNAs, but an analysis comparing the transcriptomes derived from these studies has been lacking. Here we analyze 20 datasets pertaining to neuronal mRNA localization across species and neuronal types and identify a conserved set of mRNAs that had robustly localized to neurites in a high number of the studies. The set includes mRNAs encoding for ribosomal proteins and other components of the translation machinery, mitochondrial proteins, cytoskeletal components, and proteins associated with neurite formation. Our combinatorial analysis provides a unique resource for future hypothesis-driven research. This article is categorized under: RNA Export and Localization > RNA Localization RNA Evolution and Genomics > Computational Analyses of RNA RNA Methods > RNA Analyses in Cells.

Methods for analysis of circular RNAs.

Eukaryotic cells express a myriad of circular RNAs (circRNAs), many of them displaying tissue-specific expression patterns. They arise from linear precursor RNAs in which 5' and 3' ends become covalently ligated. Given these features, biochemical and computational approaches traditionally used to study linear RNA must be adapted for analysis of circular RNAs. Such circRNA-specific methodologies are allowing the systematic identification of circRNAs and the analysis of their biological functions. Here, we review the resources and molecular methods currently utilized to quantify circRNAs, visualize their distribution, identify interacting partners, and elucidate their function. We discuss the challenges of analyzing circRNAs and propose alternative approaches for studying this unique class of transcripts. This article is characterized under: RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Methods > RNA Analyses in vitro and In Silico RNA Methods > RNA Analyses in Cells.

Chemo-enzymatic treatment of RNA to facilitate analyses.

Labeling RNA is a recurring problem to make RNA compatible with state-of-the-art methodology and comes in many flavors. Considering only cellular applications, the spectrum still ranges from site-specific labeling of individual transcripts, for example, for live-cell imaging of mRNA trafficking, to metabolic labeling in combination with next generation sequencing to capture dynamic aspects of RNA metabolism on a transcriptome-wide scale. Combining the specificity of RNA-modifying enzymes with non-natural substrates has emerged as a valuable strategy to modify RNA site- or sequence-specifically with functional groups suitable for subsequent bioorthogonal reactions and thus label RNA with reporter moieties such as affinity or fluorescent tags. In this review article, we will cover chemo-enzymatic approaches (a) for in vitro labeling of RNA for application in cells, (b) for treatment of total RNA, and (c) for metabolic labeling of RNA. This article is categorized under: RNA Processing < RNA Editing and Modification RNA Methods < RNA Analyses in vitro and In Silico RNA Methods < RNA Analyses in Cells.

Abstract 1008: S-Equol inhibits breast cancer growth by regulating phosphorylation status of estrogen receptor β

Abstract Background: Breast cancer is the most common malignancy in females and second most common cause of cancer related mortality in women. Since 70% of all breast cancers are estrogen receptor-positive (ER+ve), endocrine therapy such as anti-estrogens or aromatase inhibitors, targeting the estrogen receptor (ER) pathway is the most common treatment used for ER+ve breast cancers. However, patients will develop de novo or acquired resistance to therapy, leads to tumor progression, and metastasis. It is well documented that ERβ functions as tumor suppressor in different cancers including breast cancer. We recently showed that phosphorylation status of ERβ is important for its antitumor activity. However, little is known about the role of ERβ phosphorylation status in hormone therapy and resistance; therefore, we investigated whether phosphorylation status of ERβ has role in overcoming hormone therapy resistance in ER+ve breast cancers. Experimental design: To elucidate the importance of phosphorylation status of ERβ, we used CRISPR-Cas9 system to knockout ERβ in MCF7-Aro (therapy-sensitive) and Letrozole resistant (MCF7aro-LTLT) cells. Several mutant clones were identified for both MCF7-Aro cells and LTLT cells and the depletion of ERβ protein in both cell clones was confirmed by immunoblotting. The parental and knockout cells with or without treatment of S-equol were analyzed for cell proliferation, protein (Western) and RNA (RT-qPCR) analysis. Results: First we analyzed the cell proliferation in parental (MCF7 Aro and LTLT) and ERβ knock out cells. The proliferation rate is increased in the ERβ knockout cells compared to the parental cells. Treatment with ERβ agonist S-Equol to the parental cells inhibited the cell proliferation whereas in the knock out cells, the effect of S-equol is compromised. RNA-seq analysis of S-equol treated parental cells showed the downregulation of ERβ target genes involved in tumor progression and resistance to hormone therapies. In contrast, compared to parental cells, ERβ knock out cells showed diverse effects to S-equol treatment. RT-qPCR analysis revealed that S-Equol could not modulate the ERβ-target genes in ERβ knock out cells compared to parental cells. Conclusions: Our findings provide evidence that phosphorylation status of ERβ is important for elucidating its antitumor activity in therapy-resistant cells. The differential effects of S-equol on parental and ERβ knockout cells suggest that the antiproliferative action of S-equol is partly mediated by ERβ. We believe that our ongoing studies may further validate the role of phosphorylation status of ERβ by using both ERβ agonists and phosphorylation-regulating compounds in both therapy sensitive and resistant cells. Citation Format: Kumaraguruparan Ramasamy, Cathy Samayoa, Shaorong Chen, Rong Li, Ratna K. Vadlamudi, Rajeshwar R. Tekmal. S-Equol inhibits breast cancer growth by regulating phosphorylation status of estrogen receptor β [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1008.

Classical and emerging techniques to identify and quantify localized RNAs.

In essentially every cell, proteins are asymmetrically distributed according to their function. For many genes, this protein sorting problem is solved by transporting RNA molecules encoding the protein, rather than the protein itself, to the desired subcellular location. The protein is then translated on-site to immediately produce a correctly localized protein. This strategy is widely used as thousands of RNAs localize to distinct locations across diverse cell types and species. One of the fundamental challenges to study this process is the determination of the subcellular spatial distribution of any given RNA. The number of tools available for the study of RNA localization, from classical and state-of-the-art methods for the visualization of individual RNA molecules within cells to the profiling of localized transcriptomes, is rapidly growing. These include imaging-based approaches, a variety of biochemical and mechanical fractionation techniques, and proximity-labeling methods. These procedures allow for both the detailed study of the molecular requirements for the localization of individual RNA molecules and computational studies of RNA transport on a genomic scale. Together, they have the ability to allow insight into the regulatory principles that govern the localization of diverse RNAs. These new techniques provide the framework for integrating our knowledge of the regulation of RNA localization with that of other posttranscriptional processes. This article is categorized under: RNA Export and Localization > RNA Localization RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Methods > RNA Analyses in Cells.

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues.

The analysis of single cell gene expression across thousands of individual cells within a tissue or microenvironment is a valuable tool for identifying cell composition, discrimination of functional states, and molecular pathways underlying observed tissue functions and animal behaviors. However, the isolation of intact, healthy single cells from adult mammalian tissues for subsequent downstream single cell molecular analysis can be challenging. This protocol describes the general processes and quality control checks necessary to obtain high-quality adult single cell preparations from the nervous system or skin that enabled subsequent unbiased single cell RNA sequencing and analysis. Guidelines for downstream bioinformatic analysis are also provided.

Single cell RNA analysis identifies cellular heterogeneity and adaptive responses of the lung at birth

The respiratory system undergoes a diversity of structural, biochemical, and functional changes necessary for adaptation to air breathing at birth. To identify the heterogeneity of pulmonary cell types and dynamic changes in gene expression mediating adaptation to respiration, here we perform single cell RNA analyses of mouse lung on postnatal day 1. Using an iterative cell type identification strategy we unbiasedly identify the heterogeneity of murine pulmonary cell types. We identify distinct populations of epithelial, endothelial, mesenchymal, and immune cells, each containing distinct subpopulations. Furthermore we compare temporal changes in RNA expression patterns before and after birth to identify signaling pathways selectively activated in specific pulmonary cell types, including activation of cell stress and the unfolded protein response during perinatal adaptation of the lung. The present data provide a single cell view of the adaptation to air breathing after birth.