Single cardiomyocyte nuclear transcriptomes reveal a lincRNA-regulated de-differentiation and cell cycle stress-response in vivo

Unveiling Long Non-coding RNA Networks from Single-Cell Omics Data Through Artificial Intelligence

Single-cell omics technologies have revolutionized the study of long non-coding RNAs (lncRNAs), offering unprecedented resolution in elucidating their expression dynamics, cell-type specificity, and associated gene regulatory networks (GRNs). Concurrently, the integration of artificial intelligence (AI) methodologies has significantly advanced our understanding of lncRNA functions and its implications in disease pathogenesis. This chapter discusses the progress in single-cell omics data analysis, emphasizing its pivotal role in unraveling the molecular mechanisms underlying cellular heterogeneity and the associated regulatory networks involving lncRNAs. Additionally, we provide a summary of single-cell omics resources and AI models for constructing single-cell gene regulatory networks (scGRNs). Finally, we explore the challenges and prospects of exploring scGRNs in the context of lncRNA biology.

Heart regeneration from the whole-organism perspective to single-cell resolution

Cardiac regenerative potential in the animal kingdom displays striking divergence across ontogeny and phylogeny. Here we discuss several fundamental questions in heart regeneration and provide both a holistic view of heart regeneration in the organism as a whole, as well as a single-cell perspective on intercellular communication among diverse cardiac cell populations. We hope to provide valuable insights that advance our understanding of organ regeneration and future therapeutic strategies.

Uncovering functional lncRNAs by scRNA-seq with ELATUS

Long non-coding RNAs (lncRNAs) play fundamental roles in cellular processes and pathologies, regulating gene expression at multiple levels. Despite being highly cell type-specific, their study at single-cell (sc) level is challenging due to their less accurate annotation and low expression compared to protein-coding genes. Here, we systematically benchmark different preprocessing methods and develop a computational framework, named ELATUS, based on the combination of the pseudoaligner Kallisto with selective functional filtering. ELATUS enhances the detection of functional lncRNAs from scRNA-seq data, detecting their expression with higher concordance than standard methods with the ATAC-seq profiles in single-cell multiome data. Interestingly, the better results of ELATUS are due to its advanced performance with an inaccurate reference annotation such as that of lncRNAs. We independently confirm the expression patterns of cell type-specific lncRNAs exclusively detected with ELATUS and unveil biologically important lncRNAs, such as AL121895.1, a previously undocumented cis-repressor lncRNA, whose role in breast cancer progression is unnoticed by traditional methodologies. Our results emphasize the necessity for an alternative scRNA-seq workflow tailored to lncRNAs that sheds light on the multifaceted roles of lncRNAs.

From Cell to Gene: Deciphering the Mechanism of Heart Failure With Single-Cell Sequencing

Heart failure (HF) is a prevalent cardiovascular disease with significant morbidity and mortality rates worldwide. Due to the intricate structure of the heart, diverse cell types, and the complex pathogenesis of HF, further in-depth investigation into the underlying mechanisms  is required. The elucidation of the heterogeneity of cardiomyocytes and the intercellular communication network is particularly important. Traditional high-throughput sequencing methods provide an average measure of gene expression, failing to capture the "heterogeneity" between cells and impacting the accuracy of gene function knowledge. In contrast, single-cell sequencing techniques allow for the amplification of the entire genome or transcriptome at the individual cell level, facilitating the examination of gene structure and expression with unparalleled precision. This approach offers valuable insights into disease mechanisms, enabling the identification of changes in cellular components and gene expressions during hypertrophy associated with HF. Moreover, it reveals distinct cell populations and their unique roles in the HF microenvironment, providing a comprehensive understanding of the cellular landscape that underpins HF pathogenesis. This review focuses on the insights provided by single-cell sequencing techniques into the mechanisms underlying HF and discusses the challenges encountered in current cardiovascular research.

Single-Cell RNA Sequencing and Combinatorial Approaches for Understanding Heart Biology and Disease

By directly measuring multiple molecular features in hundreds to millions of single cells, single-cell techniques allow for comprehensive characterization of the diversity of cells in the heart. These single-cell transcriptome and multi-omic studies are transforming our understanding of heart development and disease. Compared with single-dimensional inspections, the combination of transcriptomes with spatial dimensions and other omics can provide a comprehensive understanding of single-cell functions, microenvironment, dynamic processes, and their interrelationships. In this review, we will introduce the latest advances in cardiac health and disease at single-cell resolution; single-cell detection methods that can be used for transcriptome, genome, epigenome, and proteome analysis; single-cell multi-omics; as well as their future application prospects.

Long non-coding RNAs in cardiac hypertrophy and heart failure: functions, mechanisms and clinical prospects

The surge in reports describing non-coding RNAs (ncRNAs) has focused attention on their possible biological roles and effects on development and disease. ncRNAs have been touted as previously uncharacterized regulators of gene expression and cellular processes, possibly working to fine-tune these functions. The sheer number of ncRNAs identified has outpaced the capacity to characterize each molecule thoroughly and to reliably establish its clinical relevance; it has, nonetheless, created excitement about their potential as molecular targets for novel therapeutic approaches to treat human disease. In this Review, we focus on one category of ncRNAs - long non-coding RNAs - and their expression, functions and molecular mechanisms in cardiac hypertrophy and heart failure. We further discuss the prospects for this specific class of ncRNAs as novel targets for the diagnosis and treatment of these conditions.

Preclinical Models of Cardiac Disease: A Comprehensive Overview for Clinical Scientists

For recent decades, cardiac diseases have been the leading cause of death and morbidity worldwide. Despite significant achievements in their management, profound understanding of disease progression is limited. The lack of biologically relevant and robust preclinical disease models that truly grasp the molecular underpinnings of cardiac disease and its pathophysiology attributes to this stagnation, as well as the insufficiency of platforms that effectively explore novel therapeutic avenues. The area of fundamental and translational cardiac research has therefore gained wide interest of scientists in the clinical field, while the landscape has rapidly evolved towards an elaborate array of research modalities, characterized by diverse and distinctive traits. As a consequence, current literature lacks an intelligible and complete overview aimed at clinical scientists that focuses on selecting the optimal platform for translational research questions. In this review, we present an elaborate overview of current in vitro, ex vivo, in vivo and in silico platforms that model cardiac health and disease, delineating their main benefits and drawbacks, innovative prospects, and foremost fields of application in the scope of clinical research incentives.

Single-cell transcriptional landscape of long non-coding RNAs orchestrating mouse heart development

Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and statistical techniques to define co-expression modules linked to heart development and cardiovascular diseases. We also uncovered differentially expressed transcripts in subpopulations of cardiomyocytes. Finally, from this work, we were able to identify eight cardiac cell-types; several new coding, lncRNA, and pcRNA markers; two cardiomyocyte subpopulations at four different time points (ventricle E9.5, left ventricle E11.5, right ventricle E14.5 and left atrium P0) that harbored co-expressed gene modules enriched in mitochondrial, heart development and cardiovascular diseases. Our results evidence the role of particular lncRNAs in heart development and highlight the usage of co-expression modular approaches in the cell-type functional definition.

LncRNA GAS5 Attenuates Cardiac Electrical Remodeling Induced by Rapid Pacing via the miR-27a-3p/HOXa10 Pathway

Previous studies indicated long non-coding RNAs (lncRNAs) participated in the pathogenesis of atrial fibrillation (AF). However, little is known about the role of lncRNAs in AF-induced electrical remodeling. This study aimed to investigate the regulatory effect of lncRNA GAS5 (GAS5) on the electrical remodeling of neonatal rat cardiomyocytes (NRCMs) induced by rapid pacing (RP). RNA microarray analysis yielded reduced GAS5 level in NRCMs after RP. RT-qPCR, western blot, and immunofluorescence yielded downregulated levels of Nav1.5, Kv4.2, and Cav1.2 after RP, and whole-cell patch-clamp yielded decreased sodium, potassium, and calcium current. Overexpression of GAS5 attenuated electrical remodeling. Bioinformatics tool prediction analysis and dual luciferase reporter assay confirmed a direct negative regulatory effect for miR-27a-3p on lncRNA-GAS5 and HOXa10. Further analysis demonstrated that either miR-27a-3p overexpression or the knockdown of HOXa10 further downregulated Nav1.5, Kv4.2, and Cav1.2 expression. GAS5 overexpression antagonized such effects in Nav1.5 and Kv4.2 but not in Cav1.2. These results indicate that, in RP-treated NRCMs, GAS5 could restore Nav1.5 and Kv4.2 expression via the miR-27a-3p/HOXa10 pathway. However, the mechanism of GAS5 restoring Cav1.2 level remains unclear. Our study suggested that GAS5 regulated cardiac ion channels via the GAS5/miR-27a-3p/HOXa10 pathway and might be a potential therapeutic target for AF.

Orchestrating information across tissues via a novel multitask GAT framework to improve quantitative gene regulation relation modeling for survival analysis

Survival analysis is critical to cancer prognosis estimation. High-throughput technologies facilitate the increase in the dimension of genic features, but the number of clinical samples in cohorts is relatively small due to various reasons, including difficulties in participant recruitment and high data-generation costs. Transcriptome is one of the most abundantly available OMIC (referring to the high-throughput data, including genomic, transcriptomic, proteomic and epigenomic) data types. This study introduced a multitask graph attention network (GAT) framework DQSurv for the survival analysis task. We first used a large dataset of healthy tissue samples to pretrain the GAT-based HealthModel for the quantitative measurement of the gene regulatory relations. The multitask survival analysis framework DQSurv used the idea of transfer learning to initiate the GAT model with the pretrained HealthModel and further fine-tuned this model using two tasks i.e. the main task of survival analysis and the auxiliary task of gene expression prediction. This refined GAT was denoted as DiseaseModel. We fused the original transcriptomic features with the difference vector between the latent features encoded by the HealthModel and DiseaseModel for the final task of survival analysis. The proposed DQSurv model stably outperformed the existing models for the survival analysis of 10 benchmark cancer types and an independent dataset. The ablation study also supported the necessity of the main modules. We released the codes and the pretrained HealthModel to facilitate the feature encodings and survival analysis of transcriptome-based future studies, especially on small datasets. The model and the code are available at http://www.healthinformaticslab.org/supp/.

Recent Advances in Translational Research for Heart Failure in Japan

Despite decades of intensive research and therapeutic development, heart failure remains a leading cause of death worldwide. However, recent advances in several basic and translational research fields, such as genomic analysis and single-cell analysis, have increased the possibility of developing novel diagnostic approaches to heart failure. Most cardiovascular diseases that predispose individuals to heart failure are caused by genetic and environmental factors. It follows that genomic analysis can contribute to the diagnosis and prognostic stratification of patients with heart failure. In addition, single-cell analysis has shown great potential for unveiling the pathogenesis and/or pathophysiology and for discovering novel therapeutic targets for heart failure. Here, we summarize the recent advances in translational research on heart failure in Japan, based mainly on our studies.

Single-cell transcriptomics for the assessment of cardiac disease

Cardiovascular disease is the leading cause of death globally. An advanced understanding of cardiovascular disease mechanisms is required to improve therapeutic strategies and patient risk stratification. State-of-the-art, large-scale, single-cell and single-nucleus transcriptomics facilitate the exploration of the cardiac cellular landscape at an unprecedented level, beyond its descriptive features, and can further our understanding of the mechanisms of disease and guide functional studies. In this Review, we provide an overview of the technical challenges in the experimental design of single-cell and single-nucleus transcriptomics studies, as well as a discussion of the type of inferences that can be made from the data derived from these studies. Furthermore, we describe novel findings derived from transcriptomics studies for each major cardiac cell type in both health and disease, and from development to adulthood. This Review also provides a guide to interpreting the exhaustive list of newly identified cardiac cell types and states, and highlights the consensus and discordances in annotation, indicating an urgent need for standardization. We describe advanced applications such as integration of single-cell data with spatial transcriptomics to map genes and cells on tissue and define cellular microenvironments that regulate homeostasis and disease progression. Finally, we discuss current and future translational and clinical implications of novel transcriptomics approaches, and provide an outlook of how these technologies will change the way we diagnose and treat heart disease.

European Society of Toxicologic Pathology (Pathology 2.0 Molecular Pathology Special Interest Group): Review of In Situ Hybridization Techniques for Drug Research and Development

In situ hybridization (ISH) is used for the localization of specific nucleic acid sequences in cells or tissues by complementary binding of a nucleotide probe to a specific target nucleic acid sequence. In the last years, the specificity and sensitivity of ISH assays were improved by innovative techniques like synthetic nucleic acids and tandem oligonucleotide probes combined with signal amplification methods like branched DNA, hybridization chain reaction and tyramide signal amplification. These improvements increased the application spectrum for ISH on formalin-fixed paraffin-embedded tissues. ISH is a powerful tool to investigate DNA, mRNA transcripts, regulatory noncoding RNA, and therapeutic oligonucleotides. ISH can be used to obtain spatial information of a cell type, subcellular localization, or expression levels of targets. Since immunohistochemistry and ISH share similar workflows, their combination can address simultaneous transcriptomics and proteomics questions. The goal of this review paper is to revisit the current state of the scientific approaches in ISH and its application in drug research and development.

Single-cell transcriptomes in the heart: when every epigenome counts

The response of an organ to stimuli emerges from the actions of individual cells. Recent cardiac single-cell RNA-sequencing studies of development, injury, and reprogramming have uncovered heterogeneous populations even among previously well-defined cell types, raising questions about what level of experimental resolution corresponds to disease-relevant, tissue-level phenotypes. In this review, we explore the biological meaning behind this cellular heterogeneity by undertaking an exhaustive analysis of single-cell transcriptomics in the heart (including a comprehensive, annotated compendium of studies published to date) and evaluating new models for the cardiac function that have emerged from these studies (including discussion and schematics that depict new hypotheses in the field). We evaluate the evidence to support the biological actions of newly identified cell populations and debate questions related to the role of cell-to-cell variability in development and disease. Finally, we present emerging epigenomic approaches that, when combined with single-cell RNA-sequencing, can resolve basic mechanisms of gene regulation and variability in cell phenotype.

Single-cell technologies to decipher cardiovascular diseases

Cardiovascular disease remains the leading cause of death worldwide. A deeper understanding of the multicellular composition and molecular processes may help to identify novel therapeutic strategies. Single-cell technologies such as single-cell or single-nuclei RNA sequencing provide expression profiles of individual cells and allow for dissection of heterogeneity in tissue during health and disease. This review will summarize (i) how these novel technologies have become critical for delineating mechanistic drivers of cardiovascular disease, particularly, in humans and (ii) how they might serve as diagnostic tools for risk stratification or individualized therapy. The review will further discuss technical pitfalls and provide an overview of publicly available human and mouse data sets that can be used as a resource for research.

Postnatal state transition of cardiomyocyte as a primary step in heart maturation

Postnatal heart maturation is the basis of normal cardiac function and provides critical insights into heart repair and regenerative medicine. While static snapshots of the maturing heart have provided much insight into its molecular signatures, few key events during postnatal cardiomyocyte maturation have been uncovered. Here, we report that cardiomyocytes (CMs) experience epigenetic and transcriptional decline of cardiac gene expression immediately after birth, leading to a transition state of CMs at postnatal day 7 (P7) that was essential for CM subtype specification during heart maturation. Large-scale single-cell analysis and genetic lineage tracing confirm the presence of transition state CMs at P7 bridging immature state and mature states. Silencing of key transcription factor JUN in P1-hearts significantly repressed CM transition, resulting in perturbed CM subtype proportions and reduced cardiac function in mature hearts. In addition, transplantation of P7-CMs into infarcted hearts exhibited cardiac repair potential superior to P1-CMs. Collectively, our data uncover CM state transition as a key event in postnatal heart maturation, which not only provides insights into molecular foundations of heart maturation, but also opens an avenue for manipulation of cardiomyocyte fate in disease and regenerative medicine.

Allele-specific differential regulation of monoallelically expressed autosomal genes in the cardiac lineage

Each mammalian autosomal gene is represented by two alleles in diploid cells. To our knowledge, no insights have been made in regard to allele-specific regulatory mechanisms of autosomes. Here we use allele-specific single cell transcriptomic analysis to elucidate the establishment of monoallelic gene expression in the cardiac lineage. We find that monoallelically expressed autosomal genes in mESCs and mouse blastocyst cells are differentially regulated based on the genetic background of the parental alleles. However, the genetic background of the allele does not affect the establishment of monoallelic genes in differentiated cardiomyocytes. Additionally, we observe epigenetic differences between deterministic and random autosomal monoallelic genes. Moreover, we also find a greater contribution of the maternal versus paternal allele to the development and homeostasis of cardiac tissue and in cardiac health, highlighting the importance of maternal influence in male cardiac tissue homeostasis. Our findings emphasize the significance of allele-specific insights into gene regulation in development, homeostasis and disease.

Microfluidics Facilitates the Development of Single-Cell RNA Sequencing

Single-cell RNA sequencing (scRNA-seq) technology provides a powerful tool for understanding complex biosystems at the single-cell and single-molecule level. The past decade has been a golden period for the development of single-cell sequencing, with scRNA-seq undergoing a tremendous leap in sensitivity and throughput. The application of droplet- and microwell-based microfluidics in scRNA-seq has contributed greatly to improving sequencing throughput. This review introduces the history of development and important technical factors of scRNA-seq. We mainly focus on the role of microfluidics in facilitating the development of scRNA-seq technology. To end, we discuss the future directions for scRNA-seq.

Advances in Single-Cell Multi-Omics and Application in Cardiovascular Research

With the development of ever more powerful and versatile high-throughput sequencing techniques and innovative ways to capture single cells, mapping the multicellular tissues at the single-cell level is becoming routine practice. However, it is still challenging to depict the epigenetic landscape of a single cell, especially the genome-wide chromatin accessibility, histone modifications, and DNA methylation. We summarize the most recent methodologies to profile these epigenetic marks at the single-cell level. We also discuss the development and advancement of several multi-omics sequencing technologies from individual cells. Advantages and limitations of various methods to compare and integrate datasets obtained from different sources are also included with specific practical notes. Understanding the heart tissue at single-cell resolution and multi-modal levels will help to elucidate the cell types and states involved in physiological and pathological events during heart development and disease. The rich information produced from single-cell multi-omics studies will also promote the research of heart regeneration and precision medicine on heart diseases.

Utilization and Potential of RNA-Based Therapies in Cardiovascular Disease

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RNA-based therapeutics have the potential to reach previously “undruggable” pathways in cardiovascular disease

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RNA-based therapeutics constitute a vast array of technologies, including unique forms, chemistries, and modalities of delivery

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Rapid development of RNA-based vaccines was made possible by decades of foundational work

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Specificity and efficacy of targeting and determination of mechanism(s) of action remain a distinct challenge

Cardiovascular disease (CVD) remains the largest cause of mortality worldwide. The development of new effective therapeutics is a major unmet need. The current review focuses broadly on the concept of nucleic acid (NA)–based therapies, considering the use of various forms of NAs, including mRNAs, miRNAs, siRNA, and guide RNAs, the latter specifically for the purpose of CRISPR-Cas directed gene editing. We describe the current state-of-the-art of RNA target discovery and development, the status of RNA therapeutics in the context of CVD, and some of the challenges and hurdles to be overcome.

Single-cell dual-omics reveals the transcriptomic and epigenomic diversity of cardiac non-myocytes

AIMS

The precise cellular identity and molecular features of non-myocytes (non-CMs) in a mammalian heart at a single-cell level remain elusive. Depiction of epigenetic landscape with transcriptomic signatures using the latest single-cell multi-omics has the potential to unravel the molecular programs underlying the cellular diversity of cardiac non-myocytes. Here, we characterized the molecular and cellular features of cardiac non-CM populations in the adult murine heart at the single-cell level.

METHODS AND RESULTS

Through single-cell dual omics analysis, we mapped the epigenetic landscapes, characterized the transcriptomic profiles and delineated the molecular signatures of cardiac non-CMs in the adult murine heart. Distinct cis-regulatory elements and trans-acting factors for the individual major non-CM cell types (endothelial cells, fibroblast, pericytes, and immune cells) were identified. In particular, unbiased sub-clustering and functional annotation of cardiac fibroblasts (FBs) revealed extensive FB heterogeneity and identified FB sub-types with functional states related to the cellular response to stimuli, cytoskeleton organization, and immune regulation, respectively. We further explored the function of marker genes Hsd11b1 and Gfpt2 that label major FB subpopulations and determined the distribution of Hsd11b1+ and Gfp2+ FBs in murine healthy and diseased hearts.

CONCLUSIONS

In summary, we characterized the non-CM cellular identity at the transcriptome and epigenome levels using single-cell omics approaches and discovered previously unrecognized cardiac fibroblast subpopulations with unique functional states.

Deciphering Cardiac Biology and Disease by Single-Cell Transcriptomic Profiling

By detecting minute molecular changes in hundreds to millions of single cells, single-cell RNA sequencing allows for the comprehensive characterization of the diversity and dynamics of cells in the heart. Our understanding of the heart has been transformed through the recognition of cellular heterogeneity, the construction of regulatory networks, the building of lineage trajectories, and the mapping of intercellular crosstalk. In this review, we introduce cardiac progenitors and their transcriptional regulation during embryonic development, highlight cellular heterogeneity and cell subtype functions in cardiac health and disease, and discuss insights gained from the study of pluripotent stem-cell-derived cardiomyocytes.

Dissecting the transcriptome in cardiovascular disease

The human transcriptome comprises a complex network of coding and non-coding RNAs implicated in a myriad of biological functions. Non-coding RNAs exhibit highly organized spatial and temporal expression patterns and are emerging as critical regulators of differentiation, homeostasis, and pathological states, including in the cardiovascular system. This review defines the current knowledge gaps, unmet methodological needs, and describes the challenges in dissecting and understanding the role and regulation of the non-coding transcriptome in cardiovascular disease. These challenges include poor annotation of the non-coding genome, determination of the cellular distribution of transcripts, assessment of the role of RNA processing and identification of cell-type specific changes in cardiovascular physiology and disease. We highlight similarities and differences in the hurdles associated with the analysis of the non-coding and protein-coding transcriptomes. In addition, we discuss how the lack of consensus and absence of standardized methods affect reproducibility of data. These shortcomings should be defeated in order to make significant scientific progress and foster the development of clinically applicable non-coding RNA-based therapeutic strategies to lessen the burden of cardiovascular disease.

Perspectives on Bulk-Tissue RNA Sequencing and Single-Cell RNA Sequencing for Cardiac Transcriptomics

The heart has been the center of numerous transcriptomic studies in the past decade. Even though our knowledge of the key organ in our cardiovascular system has significantly increased over the last years, it is still not fully understood yet. In recent years, extensive efforts were made to understand the genetic and transcriptomic contribution to cardiac function and failure in more detail. The advent of Next Generation Sequencing (NGS) technologies has brought many discoveries but it is unable to comprehend the finely orchestrated interactions between and within the various cell types of the heart. With the emergence of single-cell sequencing more than 10 years ago, researchers gained a valuable new tool to enable the exploration of new subpopulations of cells, cell-cell interactions, and integration of multi-omic approaches at a single-cell resolution. Despite this innovation, it is essential to make an informed choice regarding the appropriate technique for transcriptomic studies, especially when working with myocardial tissue. Here, we provide a primer for researchers interested in transcriptomics using NGS technologies.

Progress of Single-Cell RNA Sequencing Technology in Myocardial Infarction Research

After myocardial infarction, the heart enters a remodeling and repair phase that involves myocardial cell damage, inflammatory response, fibroblast activation, and, ultimately, angiogenesis. In this process, the proportions and functions of cardiomyocytes, immune cells, fibroblasts, endothelial cells, and other cells change. Identification of the potential differences in gene expression among cell types and/or transcriptome heterogeneity among cells of the same type greatly contribute to understanding the cellular changes that occur in heart and disease conditions. Recent advent of the single-cell transcriptome sequencing technology has facilitated the exploration of single cell diversity as well as comprehensive elucidation of the natural history and molecular mechanisms of myocardial infarction. In this manner, novel putative therapeutic targets for myocardial infarction treatment may be detected and clinically applied.

lncExACT1 and DCHS2 Regulate Physiological and Pathological Cardiac Growth

BACKGROUND

The heart grows in response to pathological and physiological stimuli. The former often precedes cardiomyocyte loss and heart failure; the latter paradoxically protects the heart and enhances cardiomyogenesis. The mechanisms underlying these differences remain incompletely understood. While long noncoding RNAs (lncRNAs) are important in cardiac development and disease, less is known about their roles in physiological hypertrophy or cardiomyogenesis.

METHODS

RNA sequencing was applied to hearts from mice after eight weeks voluntary exercise-induced physiological hypertrophy and cardiomyogenesis or transverse aortic constriction (TAC) for two or eight weeks to induce pathological hypertrophy or heart failure. The top lncRNA candidate was overexpressed in hearts with adeno-associated virus (AAV) vectors and inhibited with antisense locked nucleic acid (LNA)-GapmeRs to examine its function. Downstream effectors were identified through promoter analyses and binding assays. The functional roles of a novel downstream effector, dachsous cadherin-related 2 (DCHS2), were examined through transgenic overexpression in zebrafish and cardiac-specific deletion in Cas9-knockin mice.

RESULTS

We identified exercise-regulated cardiac lncRNAs, termed lncExACTs. lncExACT1 was evolutionarily conserved and decreased in exercised hearts but increased in human and experimental heart failure. Cardiac lncExACT1 overexpression caused pathological hypertrophy and heart failure, while lncExACT1 inhibition induced physiological hypertrophy and cardiomyogenesis, protecting against cardiac fibrosis and dysfunction. lncExACT1 functioned by regulating microRNA-222, calcineurin signaling, and Hippo/Yap1 signaling through DCHS2. Cardiomyocyte DCHS2 overexpression in zebrafish induced pathological hypertrophy and impaired cardiac regeneration, promoting scarring after injury. In contrast, murine DCHS2 deletion induced physiological hypertrophy and promoted cardiomyogenesis.

CONCLUSIONS

These studies identify lncExACT1-DCHS2 as a novel pathway regulating cardiac hypertrophy and cardiomyogenesis. lncExACT1-DCHS2 acts as a master switch toggling the heart between physiological and pathological growth to determine functional outcomes, providing a potentially tractable therapeutic target for harnessing the beneficial effects of exercise.

A human cell atlas of the pressure-induced hypertrophic heart

Pathological cardiac hypertrophy is a leading cause of heart failure, but knowledge of the full repertoire of cardiac cells and their gene expression profiles in the human hypertrophic heart is missing. Here, by using large-scale single-nucleus transcriptomics, we present the transcriptional response of human cardiomyocytes to pressure overload caused by aortic valve stenosis and describe major alterations in cardiac cellular crosstalk. Hypertrophied cardiomyocytes had reduced input from endothelial cells and fibroblasts. Genes encoding Eph receptor tyrosine kinases, particularly EPHB1, were significantly downregulated in cardiomyocytes of the hypertrophied heart. Consequently, EPHB1 activation by its ligand ephrin (EFN)B2, which is mainly expressed by endothelial cells, was reduced. EFNB2 inhibited cardiomyocyte hypertrophy in vitro, while silencing its expression in endothelial cells induced hypertrophy in co-cultured cardiomyocytes. Our human cell atlas of the hypertrophied heart highlights the importance of intercellular crosstalk in disease pathogenesis and provides a valuable resource.

The cardiac-enriched microprotein mitolamban regulates mitochondrial respiratory complex assembly and function in mice

Microproteins are a growing class of versatile small proteins previously overlooked by standard gene annotation methods due to their small size. Here we characterize mitolamban as a cardiac-enriched inner mitochondrial membrane–localized microprotein, which interacts with complex III of the electron transport chain and contributes to complex III assembly and function. Mitolamban gene deletion in mice leads to a reduction in complex III activity and metabolic perturbations in the heart that are consistent with complex III deficiency, as well as altered complex III assembly into respiratory supercomplexes. These findings define a functional role for mitolamban in the heart and highlight the importance of microproteins in regulating mitochondrial function and cardiomyocyte biology.

Emerging evidence indicates that a subset of RNA molecules annotated as noncoding contain short open reading frames that code for small functional proteins called microproteins, which have largely been overlooked due to their small size. To search for cardiac-expressed microproteins, we used a comparative genomics approach and identified mitolamban (Mtlbn) as a highly conserved 47-amino acid transmembrane protein that is abundantly expressed in the heart. Mtlbn localizes specifically to the inner mitochondrial membrane where it interacts with subunits of complex III of the electron transport chain and with mitochondrial respiratory supercomplexes. Genetic deletion of Mtlbn in mice altered complex III assembly dynamics and reduced complex III activity. Unbiased metabolomic analysis of heart tissue from Mtlbn knockout mice further revealed an altered metabolite profile consistent with deficiencies in complex III activity. Cardiac-specific Mtlbn overexpression in transgenic (TG) mice induced cardiomyopathy with histological, biochemical, and ultrastructural pathologic features that contributed to premature death. Metabolomic analysis and biochemical studies indicated that hearts from Mtlbn TG mice exhibited increased oxidative stress and mitochondrial dysfunction. These findings reveal Mtlbn as a cardiac-expressed inner mitochondrial membrane microprotein that contributes to mitochondrial electron transport chain activity through direct association with complex III and the regulation of its assembly and function.

Recent Progress in Cardiovascular Research Involving Single-Cell Omics Approaches

Cardiovascular diseases are among the leading causes of morbidity and mortality worldwide. Although the spectrum of the heart from development to disease has long been studied, it remains largely enigmatic. The emergence of single-cell omics technologies has provided a powerful toolbox for defining cell heterogeneity, unraveling previously unknown pathways, and revealing intercellular communications, thereby boosting biomedical research and obtaining numerous novel findings over the last 7 years. Not only cell atlases of normal and developing hearts that provided substantial research resources, but also some important findings regarding cell-type-specific disease gene program, could never have been established without single-cell omics technologies. Herein, we briefly describe the latest technological advances in single-cell omics and summarize the major findings achieved by such approaches, with a focus on development and homeostasis of the heart, myocardial infarction, and heart failure.

Single-Cell RNA Sequencing (scRNA-seq) in Cardiac Tissue: Applications and Limitations

Cardiovascular diseases (CVDs) are a group of disorders of the blood vessels and heart, which are considered as the leading causes of death worldwide. The pathology of CVDs could be related to the functional abnormalities of multiple cell types in the heart. Single-cell RNA sequencing (scRNA-seq) technology is a powerful method for characterizing individual cells and elucidating the molecular mechanisms by providing a high resolution of transcriptomic changes at the single-cell level. Specifically, scRNA-seq has provided novel insights into CVDs by identifying rare cardiac cell types, inferring the trajectory tree, estimating RNA velocity, elucidating the cell-cell communication, and comparing healthy and pathological heart samples. In this review, we summarize the different scRNA-seq platforms and published single-cell datasets in the cardiovascular field, and describe the utilities and limitations of this technology. Lastly, we discuss the future perspective of the application of scRNA-seq technology into cardiovascular research.

Single-cell and spatial transcriptomics approaches of cardiovascular development and disease

Recent advancements in the resolution and throughput of single-cell analyses, including single-cell RNA sequencing (scRNA-seq), have achieved significant progress in biomedical research in the last decade. These techniques have been used to understand cellular heterogeneity by identifying many rare and novel cell types and characterizing subpopulations of cells that make up organs and tissues. Analysis across various datasets can elucidate temporal patterning in gene expression and developmental cues and is also employed to examine the response of cells to acute injury, damage, or disruption. Specifically, scRNA-seq and spatially resolved transcriptomics have been used to describe the identity of novel or rare cell subpopulations and transcriptional variations that are related to normal and pathological conditions in mammalian models and human tissues. These applications have critically contributed to advance basic cardiovascular research in the past decade by identifying novel cell types implicated in development and disease. In this review, we describe current scRNA-seq technologies and how current scRNA-seq and spatial transcriptomic (ST) techniques have advanced our understanding of cardiovascular development and disease. [BMB Reports 2020; 53(8): 393-399].

Understanding the Adult Mammalian Heart at Single-Cell RNA-Seq Resolution

During the last decade, extensive efforts have been made to comprehend cardiac cell genetic and functional diversity. Such knowledge allows for the definition of the cardiac cellular interactome as a reasonable strategy to increase our understanding of the normal and pathologic heart. Previous experimental approaches including cell lineage tracing, flow cytometry, and bulk RNA-Seq have often tackled the analysis of cardiac cell diversity as based on the assumption that cell types can be identified by the expression of a single gene. More recently, however, the emergence of single-cell RNA-Seq technology has led us to explore the diversity of individual cells, enabling the cardiovascular research community to redefine cardiac cell subpopulations and identify relevant ones, and even novel cell types, through their cell-specific transcriptomic signatures in an unbiased manner. These findings are changing our understanding of cell composition and in consequence the identification of potential therapeutic targets for different cardiac diseases. In this review, we provide an overview of the continuously changing cardiac cellular landscape, traveling from the pre-single-cell RNA-Seq times to the single cell-RNA-Seq revolution, and discuss the utilities and limitations of this technology.

Cardiac Derived CD51-Positive Mesenchymal Stem Cells Enhance the Cardiac Repair Through SCF-Mediated Angiogenesis in Mice With Myocardial Infarction

Objective: Many tissues contained resident mesenchymal stromal/stem cells (MSCs) that facilitated tissue hemostasis and repair. However, there is no typical marker to identify the resident cardiac MSCs. We aimed to determine if CD51 could be an optimal marker of cardiac MSCs and assess their therapeutic potential for mice with acute myocardial infarction (AMI).

Methods: Cardiac-derived CD51⁺CD31^–CD45^–Ter119^– cells (named CD51⁺cMSCs) were isolated from C57BL/6 mice(7-day-old) by flow cytometry. The CD51⁺cMSCs were characterized by proliferation capacity, multi-differentiation potential, and expression of typical MSC-related markers. Adult C57BL/6 mice (12-week-old) were utilized for an AMI model via permanently ligating the left anterior descending coronary artery. The therapeutic efficacy of CD51⁺cMSCs was estimated by echocardiography and pathological staining. To determine the underlying mechanism, lentiviruses were utilized to knock down gene (stem cell factor [SCF]) expression of CD51⁺cMSCs.

Results: In this study, CD51 was expressed in the entire layers of the cardiac wall in mice, including endocardium, epicardium, and myocardium, and its expression was decreased with age. Importantly, the CD51⁺cMSCs possessed potent self-renewal potential and multi-lineage differentiation capacity in vitro and also expressed typical MSC-related surface proteins. Furthermore, CD51⁺cMSC transplantation significantly improved cardiac function and attenuated cardiac fibrosis through pro-angiogenesis activity after myocardial infarction in mice. Moreover, SCF secreted by CD51⁺cMSCs played an important role in angiogenesis both in vivo and in vitro.

Conclusions: Collectively, CD51 is a novel marker of cardiac resident MSCs, and CD51⁺cMSC therapy enhances cardiac repair at least partly through SCF-mediated angiogenesis.

One potential biomarker for teratozoospermia identified by in-depth integrative analysis of multiple microarray data

Teratozoospermia is a common category of male infertility and with the increase in clinical patients and the increasing sophistication of assisted reproductive technology, there is an urgent need for an accurate semen diagnostic biomarker to accomplish rapid diagnosis of patients with teratozoospermia and accurately assess the success rate of assisted reproductive technologies. In this study, we performed gene differential expression analysis on two publicly available DNA microarray datasets (GSE6872 and GSE6967), followed by GSEA analysis to parse their enriched KEGG pathways, and WGCNA analysis to obtain the most highly correlated modules. Subsequent in-depth comparative analysis of the modules screened into the two datasets resulted in a gene set containing the identical expression trend, and then the differentially expressed genes in the set were screened using the corresponding criteria. Finally, three differentially expressed genes common to both datasets were selected. In addition, we validated the expression changes of this gene using another dataset (GSE6968) and in vitro experiments, and only screened one potential semen biomarker gene whose expression trend was identical to those in other datasets, which will also provide an important theoretical basis for the diagnosis and treatment of teratozoospermia.

Taking Data Science to Heart: Next Scale of Gene Regulation

PURPOSE OF REVIEW

Technical advances have facilitated high-throughput measurements of the genome in the context of cardiovascular biology. These techniques bring a deluge of gargantuan datasets, which in turn present two fundamentally new opportunities for innovation-data processing and knowledge integration-toward the goal of meaningful basic and translational discoveries.

RECENT FINDINGS

Big data, integrative analyses, and machine learning have brought cardiac investigations to the cutting edge of chromatin biology, not only to reveal basic principles of gene regulation in the heart, but also to aid in the design of targeted epigenetic therapies.

SUMMARY

Cardiac studies using big data are only beginning to integrate the millions of recorded data points and the tools of machine learning are aiding this process. Future experimental design should take into consideration insights from existing genomic datasets, thereby focusing on heretofore unexplored epigenomic contributions to disease pathology.

Translational insights from single-cell technologies across the cardiovascular disease continuum

Cardiovascular disease is the leading cause of death worldwide. The societal health burden it represents can be reduced by taking preventive measures and developing more effective therapies. Reaching these goals, however, requires a better understanding of the pathophysiological processes leading to and occurring in the diseased heart. In the last 5 years, several biological advances applying single-cell technologies have enabled researchers to study cardiovascular diseases with unprecedented resolution. This has produced many new insights into how specific cell types change their gene expression level, activation status and potential cellular interactions with the development of cardiovascular disease, but a comprehensive overview of the clinical implications of these findings is lacking. In this review, we summarize and discuss these recent advances and the promise of single-cell technologies from a translational perspective across the cardiovascular disease continuum, covering both animal and human studies, and explore the future directions of the field.

A Perspective on Personalized Therapies in Hypertrophic Cardiomyopathy

ABSTRACT

A dominant mechanism of sudden cardiac death in the young is the progression of maladaptive responses to genes encoding proteins linked to hypertrophic cardiomyopathy. Most are mutant sarcomere proteins that trigger the progression by imposing a biophysical defect on the dynamics and levels of myofilament tension generation. We discuss approaches for personalized treatments that are indicated by recent advanced understanding of the progression.

Long non-coding RNAs: A double-edged sword in aging kidney and renal disease

Aging as one of intrinsic biological processes is a risk factor for many chronic diseases. Kidney disease is a global problem and health care burden worldwide. The diagnosis of kidney disease is currently based on serum creatinine and urea levels. Novel biomarkers may improve diagnostic accuracy, thereby allowing early prevention and treatment. Over the past few years, advances in genome analyses have identified an emerging class of noncoding RNAs that play critical roles in the regulation of gene expression and epigenetic reprogramming. Long noncoding RNAs (lncRNAs) are pervasively transcribed in the genome and could bind DNA, RNA and protein. Emerging evidence has demonstrated that lncRNAs played an important role in all stages of kidney disease. To date, only some lncRNAs were well identified and characterized, but the complexity of multilevel regulation of transcriptional programs involved in these processes remains undefined. In this review, we summarized the lncRNA expression profiling of large-scale identified lncRNAs on kidney diseases including acute kidney injury, chronic kidney disease, diabetic nephropathy and kidney transplantation. We further discussed a number of annotated lncRNAs linking with complex etiology of kidney diseases. Finally, several lncRNAs were highlighted as diagnostic biomarkers and therapeutic targets. Targeting lncRNAs may represent a precise therapeutic strategy for progressive renal fibrosis.

Single-Cell RNA Sequencing of the Adult Mammalian Heart-State-of-the-Art and Future Perspectives

Purpose of the Review

Cardiovascular disease remains the leading cause of death worldwide, resulting in cardiac dysfunction and, subsequently, heart failure (HF). Single-cell RNA sequencing (scRNA-seq) is a rapidly developing tool for studying the transcriptional heterogeneity in both healthy and diseased hearts. Wide applications of techniques like scRNA-seq could significantly contribute to uncovering the molecular mechanisms involved in the onset and progression to HF and contribute to the development of new, improved therapies. This review discusses several studies that successfully applied scRNA-seq to the mouse and human heart using various methods of tissue processing and downstream analysis.

Recent Findings

The application of scRNA-seq in the cardiovascular field is continuously expanding, providing new detailed insights into cardiac pathophysiology.

Summary

Increased understanding of cardiac pathophysiology on the single-cell level will contribute to the development of novel, more effective therapeutic strategies. Here, we summarise the possible application of scRNA-seq to the adult mammalian heart.

Ex uno, plures-From One Tissue to Many Cells: A Review of Single-Cell Transcriptomics in Cardiovascular Biology

Recent technological advances have revolutionized the study of tissue biology and garnered a greater appreciation for tissue complexity. In order to understand cardiac development, heart tissue homeostasis, and the effects of stress and injury on the cardiovascular system, it is essential to characterize the heart at high cellular resolution. Single-cell profiling provides a more precise definition of tissue composition, cell differentiation trajectories, and intercellular communication, compared to classical bulk approaches. Here, we aim to review how recent single-cell multi-omic studies have changed our understanding of cell dynamics during cardiac development, and in the healthy and diseased adult myocardium.

Infertility network and hub genes for nonobstructive azoospermia utilizing integrative analysis

Non-obstructive azoospermia (NOA) is the most severe form of male infertility owing to the absence of sperm during ejaculation as a result of failed spermatogenesis. The molecular mechanisms of NOA have not been well studied. Here, we revealed the dysregulated differentially expressed genes in NOA and related signaling pathways or biological processes. Cluster features of biological processes include spermatogenesis, fertilization, cilium movement, penetration of zona pellucida, sperm chromatin condensation, and being significantly enriched metabolic pathways in proximal tubule bicarbonate reclamation, aldosterone synthesis and secretion, glycolysis and glycogenesis pathways in NOA using Gene Ontology analysis and pathway enrichment analysis. The NOA gene co-expression network was constructed by weighted gene co-expression network analysis to identify the hub genes (CHD5 and SPTBN2). In addition, we used another Gene Expression Omnibus dataset (GSE45887) to validate these hub genes. Furthermore, we used the Seurat package to classify testicular tissue cells from NOA patients and to characterize the differential expression of hub genes in different cell types from different adult males based on the scRNA-seq dataset (GSE106487). These results provide new insights into the pathogenesis of NOA. Of particular note, CHD5 and SPTBN2 may be potential biomarkers for the diagnosis and treatment of NOA.

Long non-coding RNAs: the tentacles of chromatin remodeler complexes

Chromatin remodeler complexes regulate gene transcription, DNA replication and DNA repair by changing both nucleosome position and post-translational modifications. The chromatin remodeler complexes are categorized into four families: the SWI/SNF, INO80/SWR1, ISWI and CHD family. In this review, we describe the subunits of these chromatin remodeler complexes, in particular, the recently identified members of the ISWI family and novelties of the CHD family. Long non-coding (lnc) RNAs regulate gene expression through different epigenetic mechanisms, including interaction with chromatin remodelers. For example, interaction of lncBRM with BRM inhibits the SWI/SNF complex associated with a differentiated phenotype and favors assembly of a stem cell-related SWI/SNF complex. Today, over 50 lncRNAs have been shown to affect chromatin remodeler complexes and we here discuss the mechanisms involved.

Single-cell transcriptomics following ischemic injury identifies a role for B2M in cardiac repair

The efficiency of the repair process following ischemic cardiac injury is a crucial determinant for the progression into heart failure and is controlled by both intra- and intercellular signaling within the heart. An enhanced understanding of this complex interplay will enable better exploitation of these mechanisms for therapeutic use. We used single-cell transcriptomics to collect gene expression data of all main cardiac cell types at different time-points after ischemic injury. These data unveiled cellular and transcriptional heterogeneity and changes in cellular function during cardiac remodeling. Furthermore, we established potential intercellular communication networks after ischemic injury. Follow up experiments confirmed that cardiomyocytes express and secrete elevated levels of beta-2 microglobulin in response to ischemic damage, which can activate fibroblasts in a paracrine manner. Collectively, our data indicate phase-specific changes in cellular heterogeneity during different stages of cardiac remodeling and allow for the identification of therapeutic targets relevant for cardiac repair.

Single-cell genomics to understand disease pathogenesis

Cells are minimal functional units in biological phenomena, and therefore single-cell analysis is needed to understand the molecular behavior leading to cellular function in organisms. In addition, omics analysis technology can be used to identify essential molecular mechanisms in an unbiased manner. Recently, single-cell genomics has unveiled hidden molecular systems leading to disease pathogenesis in patients. In this review, I summarize the recent advances in single-cell genomics for the understanding of disease pathogenesis and discuss future perspectives.

Single-cell RNA Sequencing: In-depth Decoding of Heart Biology and Cardiovascular Diseases

Background

The cardiac system is a combination of a complex structure, various cells, and versatile specified functions and sophisticated regulatory mechanisms. Moreover, cardiac diseases that encompass a wide range of endogenous conditions, remain a serious health burden worldwide. Recent genome-wide profiling techniques have taken the lead in uncovering a new realm of cell types and molecular programs driving physiological and pathological processes in various organs and diseases. In particular, the emerging technique single-cell RNA sequencing dominates a breakthrough in decoding the cell heterogeneity, phenotype transition, and developmental dynamics in cardiovascular science.

Conclusion

Herein, we review recent advances in single cellular studies of cardiovascular system and summarize new insights provided by single-cell RNA sequencing in heart developmental sciences, stem-cell researches as well as normal or disease-related working mechanisms.

Cell-Type-Specific Gene Regulatory Networks Underlying Murine Neonatal Heart Regeneration at Single-Cell Resolution

The adult mammalian heart has limited capacity for regeneration following injury, whereas the neonatal heart can readily regenerate within a short period after birth. Neonatal heart regeneration is orchestrated by multiple cell types intrinsic to the heart, as well as immune cells that infiltrate the heart after injury. To elucidate the transcriptional responses of the different cellular components of the mouse heart following injury, we perform single-cell RNA sequencing on neonatal hearts at various time points following myocardial infarction and couple the results with bulk tissue RNA-sequencing data collected at the same time points. Concomitant single-cell ATAC sequencing exposes underlying dynamics of open chromatin landscapes and regenerative gene regulatory networks of diverse cardiac cell types and reveals extracellular mediators of cardiomyocyte proliferation, angiogenesis, and fibroblast activation. Together, our data provide a transcriptional basis for neonatal heart regeneration at single-cell resolution and suggest strategies for enhancing cardiac function after injury.

Proximity to injury, but neither number of nuclei nor ploidy define pathological adaptation and plasticity in cardiomyocytes

The adult mammalian heart consists of mononuclear and binuclear cardiomyocytes (CMs) with various ploidies. However, it remains unclear whether a variation in ploidy or number of nuclei is associated with distinct functions and injury responses in CMs, including regeneration. Therefore, we investigated transcriptomes and cellular as well as nuclear features of mononucleated and binucleated CMs in adult mouse hearts with and without injury. To be able to identify the role of ploidy we analyzed control and failing human ventricular CMs because human CMs show a larger and disease-sensitive degree of polyploidization. Using transgenic Myh6-H2BmCh to identify mononucleated and binucleated mouse CMs, we found that cellular volume and RNA content were similar in both. On average nuclei of mononuclear CMs showed a 2-fold higher ploidy, as compared to binuclear CMs indicating that most mononuclear CMs are tetraploid. After myocardial infarction mononucleated and binucleated CMs in the border zone of the lesion responded with hypertrophy and corresponding changes in gene expression, as well as a low level of induction of cell cycle gene expression. Human CMs allowed us to study a wide range of polyploidy spanning from 2n to 16n. Notably, basal as well as pathological gene expression signatures and programs in failing CMs proved to be independent of ploidy. In summary, gene expression profiles were induced in proximity to injury, but independent of number of nuclei or ploidy levels in CMs.

What we know about cardiomyocyte dedifferentiation

Cardiomyocytes (CMs) lost during cardiac injury and heart failure (HF) cannot be replaced due to their limited proliferative capacity. Regenerating the failing heart by promoting CM cell-cycle re-entry is an ambitious solution, currently vigorously pursued. Some genes have been proven to promote endogenous CM proliferation, believed to be preceded by CM dedifferentiation, wherein terminally differentiated CMs are initially reversed back to the less mature state which precedes cell division. However, very little else is known about CM dedifferentiation which remains poorly defined. We lack robust molecular markers and proper understanding of the mechanisms driving dedifferentiation. Even the term dedifferentiation is debated because there is no objective evidence of pluripotency, and could rather reflect CM plasticity instead. Nonetheless, the significance of CM transition states on cardiac function, and whether they necessarily lead to CM proliferation, remains unclear. This review summarises the current state of knowledge of both natural and experimentally induced CM dedifferentiation in non-mammalian vertebrates (primarily the zebrafish) and mammals, as well as the phenotypes and molecular mechanisms involved. The significance and potential challenges of studying CM dedifferentiation are also discussed. In summary, CM dedifferentiation, essential for CM plasticity, may have an important role in heart regeneration, thereby contributing to the prevention and treatment of heart disease. More attention is needed in this field to overcome the technical limitations and knowledge gaps.

Methods for isolation and transcriptional profiling of individual cells from the human heart

BACKGROUND

Global transcriptional profiling of individual cells represents a powerful approach to systematically survey contributions from cell-specific molecular phenotypes to human disease states but requires tissue-specific protocols. Here we sought to comprehensively evaluate protocols for single cell isolation and transcriptional profiling from heart tissue, focusing particularly on frozen tissue which is necessary for study of human hearts at scale.

METHODS AND RESULTS

Using flow cytometry and high-content screening, we found that enzymatic dissociation of fresh murine heart tissue resulted in a sufficient yield of intact cells while for frozen murine or human heart resulted in low-quality cell suspensions across a range of protocols. These findings were consistent across enzymatic digestion protocols and whether samples were snap-frozen or treated with RNA-stabilizing agents before freezing. In contrast, we show that isolation of cardiac nuclei from frozen hearts results in a high yield of intact nuclei, and leverage expression arrays to show that nuclear transcriptomes reliably represent the cytoplasmic and whole-cell transcriptomes of the major cardiac cell types. Furthermore, coupling of nuclear isolation to PCM1-gated flow cytometry facilitated specific cardiomyocyte depletion, expanding resolution of the cardiac transcriptome beyond bulk tissue transcriptomes which were most strongly correlated with PCM1+ transcriptomes (r = 0.8). We applied these methods to generate a transcriptional catalogue of human cardiac cells by droplet-based RNA-sequencing of 8,460 nuclei from which cellular identities were inferred. Reproducibility of identified clusters was confirmed in an independent biopsy (4,760 additional PCM1- nuclei) from the same human heart.

CONCLUSION

Our results confirm the validity of single-nucleus but not single-cell isolation for transcriptional profiling of individual cells from frozen heart tissue, and establishes PCM1-gating as an efficient tool for cardiomyocyte depletion. In addition, our results provide a perspective of cell types inferred from single-nucleus transcriptomes that are present in an adult human heart.

Systematic Identification of Key Functional Modules and Genes in Gastric Cancer

Gastric cancer (GC) is associated with high incidence and mortality rates worldwide. Differentially expressed gene (DEG) analysis and weighted gene coexpression network analysis (WGCNA) are important bioinformatic methods for screening core genes. In our study, DEG analysis and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the DEGs. SBNO2 was identified as the hub gene based on the intersection between the DEGs and the purple module in WGCNA. The expression and prognostic value of SBNO2 were verified in UALCAN, GEPIA2, Human Cancer Metastasis Database, Kaplan-Meier plotter, and TIMER. We identified 1974 DEGs, and 28 modules were uncovered via WGCNA. The purple module was identified as the hub module in WGCNA. SBNO2 was identified as the hub gene, which was upregulated in tumour tissues. Moreover, patients with GC and higher SBNO2 expression had worse prognoses. In addition, SBNO2 was suggested to play an important role in immune cell infiltration. In summary, based on DEGs and key modules related to GC, we identified SBNO2 as a hub gene, thereby offering novel insights into the development and treatment of GC.