Single cell RNA sequencing approaches to cardiac development and congenital heart disease

Dissecting the dynamic cellular transcriptional atlas of adult teleost testis development throughout the annual reproductive cycle

Teleost testis development during the annual cycle involves dramatic changes in cellular compositions and molecular events. In this study, the testicular cells derived from adult black rockfish at distinct stages - regressed, regenerating and differentiating - were meticulously dissected via single-cell transcriptome sequencing. A continuous developmental trajectory of spermatogenic cells, from spermatogonia to spermatids, was delineated, elucidating the molecular events involved in spermatogenesis. Subsequently, the dynamic regulation of gene expression associated with spermatogonia proliferation and differentiation was observed across spermatogonia subgroups and developmental stages. A bioenergetic transition from glycolysis to mitochondrial respiration of spermatogonia during the annual developmental cycle was demonstrated, and a deeper level of heterogeneity and molecular characteristics was revealed by re-clustering analysis. Additionally, the developmental trajectory of Sertoli cells was delineated, alongside the divergence of Leydig cells and macrophages. Moreover, the interaction network between testicular micro-environment somatic cells and spermatogenic cells was established. Overall, our study provides detailed information on both germ and somatic cells within teleost testes during the annual reproductive cycle, which lays the foundation for spermatogenesis regulation and germplasm preservation of endangered species.

Innovative aspects and applications of single cell technology for different diseases

Recent developments in single-cell technologies have provided valuable insights from cancer genomics to complex microbial communities. Single-cell technologies including the RNA-seq, next-generation sequencing (NGS), epigenomics, genomics, and transcriptomics can be used to uncover the single cell nature and molecular characterization of individual cells. These technologies also reveal the cellular transition states, evolutionary relationships between genes, the complex structure of single-cell populations, cell-to-cell interaction leading to biological discoveries and more reliable than traditional bulk technologies. These technologies are becoming the first choice for the early detection of inflammatory biomarkers affecting the proliferation and progression of tumor cells in the tumor microenvironment and improving the clinical efficacy of patients undergoing immunotherapy. These technologies also hold a central position in the detection of checkpoint inhibitors and thus determining the signaling pathways evoked by tumor invasion. This review addressed the emerging approaches of single cell-based technologies in cancer immunotherapies and different human diseases at cellular and molecular levels and the emerging role of sequencing technologies leading to drug discovery. Advancements in these technologies paved for discovering novel diagnostic markers for better understanding the pathological and biochemical mechanisms also for controlling the rate of different diseases.

Machine Learning in Identifying Marker Genes for Congenital Heart Diseases of Different Cardiac Cell Types

Congenital heart disease (CHD) represents a spectrum of inborn heart defects influenced by genetic and environmental factors. This study advances the field by analyzing gene expression profiles in 21,034 cardiac fibroblasts, 73,296 cardiomyocytes, and 35,673 endothelial cells, utilizing single-cell level analysis and machine learning techniques. Six CHD conditions: dilated cardiomyopathy (DCM), donor hearts (used as healthy controls), hypertrophic cardiomyopathy (HCM), heart failure with hypoplastic left heart syndrome (HF_HLHS), Neonatal Hypoplastic Left Heart Syndrome (Neo_HLHS), and Tetralogy of Fallot (TOF), were investigated for each cardiac cell type. Each cell sample was represented by 29,266 gene features. These features were first analyzed by six feature-ranking algorithms, resulting in several feature lists. Then, these lists were fed into incremental feature selection, containing two classification algorithms, to extract essential gene features and classification rules and build efficient classifiers. The identified essential genes can be potential CHD markers in different cardiac cell types. For instance, the LASSO identified key genes specific to various heart cell types in CHD subtypes. FOXO3 was found to be up-regulated in cardiac fibroblasts for both Dilated and hypertrophic cardiomyopathy. In cardiomyocytes, distinct genes such as TMTC1, ART3, ARHGAP24, SHROOM3, and XIST were linked to dilated cardiomyopathy, Neo-Hypoplastic Left Heart Syndrome, hypertrophic cardiomyopathy, HF-Hypoplastic Left Heart Syndrome, and Tetralogy of Fallot, respectively. Endothelial cell analysis further revealed COL25A1, NFIB, and KLF7 as significant genes for dilated cardiomyopathy, hypertrophic cardiomyopathy, and Tetralogy of Fallot. LightGBM, Catboost, MCFS, RF, and XGBoost further delineated key genes for specific CHD subtypes, demonstrating the efficacy of machine learning in identifying CHD-specific genes. Additionally, this study developed quantitative rules for representing the gene expression patterns related to CHDs. This research underscores the potential of machine learning in unraveling the molecular complexities of CHD and establishes a foundation for future mechanism-based studies.

Cardiac Development at a Single-Cell Resolution

Mammalian cardiac development is a complex, multistage process. Though traditional lineage tracing studies have characterized the broad trajectories of cardiac progenitors, the advent and rapid optimization of single-cell RNA sequencing methods have yielded an ever-expanding toolkit for characterizing heterogeneous cell populations in the developing heart. Importantly, they have allowed for a robust profiling of the spatiotemporal transcriptomic landscape of the human and mouse heart, revealing the diversity of cardiac cells-myocyte and non-myocyte-over the course of development. These studies have yielded insights into novel cardiac progenitor populations, chamber-specific developmental signatures, the gene regulatory networks governing cardiac development, and, thus, the etiologies of congenital heart diseases. Furthermore, single-cell RNA sequencing has allowed for the exquisite characterization of distinct cardiac populations such as the hard-to-capture cardiac conduction system and the intracardiac immune population. Therefore, single-cell profiling has also resulted in new insights into the regulation of cardiac regeneration and injury repair. Single-cell multiomics approaches combining transcriptomics, genomics, and epigenomics may uncover an even more comprehensive atlas of human cardiac biology. Single-cell analyses of the developing and adult mammalian heart offer an unprecedented look into the fundamental mechanisms of cardiac development and the complex diseases that may arise from it.

Small but strong: the emerging role of small nucleolar RNA in cardiovascular diseases

Cardiovascular diseases (CVDs) are the leading cause of mortality and disability worldwide. Numerous studies have demonstrated that non-coding RNAs (ncRNAs) play a primary role in CVD development. Therefore, studies on the mechanisms of ncRNAs are essential for further efforts to prevent and treat CVDs. Small nucleolar RNAs (snoRNAs) are a novel species of non-conventional ncRNAs that guide post-transcriptional modifications and the subsequent maturation of small nuclear RNA and ribosomal RNA. Evidently, snoRNAs are extensively expressed in human tissues and may regulate different illnesses. Particularly, as the next-generation sequencing techniques have progressed, snoRNAs have been shown to be differentially expressed in CVDs, suggesting that they may play a role in the occurrence and progression of cardiac illnesses. However, the molecular processes and signaling pathways underlying the function of snoRNAs remain unidentified. Therefore, it is of great value to comprehensively investigate the association between snoRNAs and CVDs. The aim of this review was to collate existing literature on the biogenesis, characteristics, and potential regulatory mechanisms of snoRNAs. In particular, we present a scientific update on these snoRNAs and their relevance to CVDs in an effort to cast new light on the functions of snoRNAs in the clinical diagnosis of CVDs.

Quantitative proteomic profiling identifies global protein network dynamics in murine embryonic heart development

Defining the mechanisms that govern heart development is essential for identifying the etiology of congenital heart disease. Here, quantitative proteomics was used to measure temporal changes in the proteome at critical stages of murine embryonic heart development. Global temporal profiles of the over 7,300 proteins uncovered signature cardiac protein interaction networks that linked protein dynamics with molecular pathways. Using this integrated dataset, we identified and demonstrated a functional role for the mevalonate pathway in regulating the cell cycle of embryonic cardiomyocytes. Overall, our proteomic datasets are a resource for studying events that regulate embryonic heart development and contribute to congenital heart disease.

Strategy of Patient-Specific Therapeutics in Cardiovascular Disease Through Single-Cell RNA Sequencing

Recently, single cell RNA sequencing (scRNA-seq) technology has enabled the discovery of novel or rare subtypes of cells and their characteristics. This technique has advanced unprecedented biomedical research by enabling the profiling and analysis of the transcriptomes of single cells at high resolution and throughput. Thus, scRNA-seq has contributed to recent advances in cardiovascular research by the generation of cell atlases of heart and blood vessels and the elucidation of mechanisms involved in cardiovascular development and diseases. This review summarizes the overall workflow of the scRNA-seq technique itself and key findings in the cardiovascular development and diseases based on the previous studies. In particular, we focused on how the single-cell sequencing technology can be utilized in clinical field and precision medicine to treat specific diseases.

Single-cell sequencing: promises and challenges for human genetics

Over the last decade, single-cell sequencing has transformed many fields. It has enabled the unbiased molecular phenotyping of even whole organisms with unprecedented cellular resolution. In the field of human genetics, where the phenotypic consequences of genetic and epigenetic alterations are of central concern, this transformative technology promises to functionally annotate every region in the human genome and all possible variants within them at a massive scale. In this review aimed at the clinicians in human genetics, we describe the current status of the field of single-cell sequencing and its role for human genetics, including how the technology works as well as how it is being applied to characterize and monitor diseases, to develop human cell atlases, and to annotate the genome.

Identification and functional analysis of variants of MYH6 gene promoter in isolated ventricular septal defects

BACKGROUND

Ventricular septal defect is the most common form of congenital heart diseases. MYH6 gene has a critical effect on the growth and development of the heart but the variants in the promoter of MYH6 is unknown.

PATIENTS AND METHODS

In 604 of the subjects (311 isolated and sporadic ventricular septal defect patients and 293 healthy controls), DNA was extracted from blood samples and MYH6 gene promoter region variants were analyzed by sequencing. Further functional verification was performed by cellular experiments using dual luciferase reporter gene analysis, electrophoretic mobility shift assays, and bioinformatics analysis.

RESULTS

Nine variants were identified in the MYH6 gene promoter and two of those variants [g.4085G>C(rs1222539675) and g.4716G>A(rs377648095)] were only found in the ventricular septal defect patients. Cellular function experiments showed that these two variants reduced the transcriptional activity of the MYH6 gene promoter (p < 0.001). Further analysis with online JASPAR database suggests that these variants may alter a set of putative transcription factor binding sites that possibly lead to changes in myosin subunit expression and ventricular septal defect formation.

CONCLUSIONS

Our study for the first time identifies variants in the promoter region of the MYH6 gene in Chinese patients with isolated and sporadic ventricular septal defect. These variants significantly reduced MYH6 gene expression and affected transcription factor binding sites and therefore are pathogenic. The present study provides new insights in the role of the MYH6 gene promoter region to better understand the genetic basis of VSD formation.

The need for a standard for informed consent for collection of human fetal material

The ISSCR has developed the Informed Consent Standards for Human Fetal Tissue Donation and Research to promote uniformity and transparency in tissue donation and collection. This standard is designed to assist those working with and overseeing the regulation of such tissue and reassure the wider community and public.

Cardiovascular mechanobiology-a Special Issue to look at the state of the art and the newest insights into the role of mechanical forces in cardiovascular development, physiology and disease

There has been much progress recently in the area of cardiovascular mechanobiology and this Special Issue aims at taking stock. This editorial gives context of the main motivation for this special issue as well as a brief summary of its content.

Methods and platforms for analysis of nucleic acids from single-cell based on microfluidics

Single-cell nucleic acid analysis aims at discovering the genetic differences between individual cells which is well known as the cellular heterogeneity. This technology facilitates cancer diagnosis, stem cell research, immune system analysis, and other life science applications. The conventional platforms for single-cell nucleic acid analysis more rely on manual operation or bulky devices. Recently, the emerging microfluidic technology has provided a perfect platform for single-cell nucleic acid analysis with the characteristic of accurate and automatic single-cell manipulation. In this review, we briefly summarized the procedure of single-cell nucleic acid analysis including single-cell isolation, single-cell lysis, nucleic acid amplification, and genetic analysis. And then, three representative microfluidic platforms for single-cell nucleic acid analysis are concluded as valve-, microwell-, and droplet-based platforms. Furthermore, we described the state-of-the-art integrated single-cell nucleic acid analysis systems based on the three platforms. Finally, the future development and challenges of microfluidics-based single-cell nucleic acid analysis are discussed as well.