Advancements in detection of SARS-CoV-2 infection for confronting COVID-19 pandemics.

As one of the major approaches in combating the COVID-19 pandemics, the availability of specific and reliable assays for the SARS-CoV-2 viral genome and its proteins is essential to identify the infection in suspected populations, make diagnoses in symptomatic or asymptomatic individuals, and determine clearance of the virus after the infection. For these purposes, use of the quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) for detection of the viral nucleic acid remains the most valuable in terms of its specificity, fast turn-around, high-throughput capacity, and reliability. It is critical to update the sequences of primers and probes to ensure the detection of newly emerged variants. Various assays for increased levels of IgG or IgM antibodies are available for detecting ongoing or past infection, vaccination responses, and persistence and for identifying high titers of neutralizing antibodies in recovered individuals. Viral genome sequencing is increasingly used for tracing infectious sources, monitoring mutations, and subtype classification and is less valuable in diagnosis because of its capacity and high cost. Nanopore target sequencing with portable options is available for a quick process for sequencing data. Emerging CRISPR-Cas-based assays, such as SHERLOCK and AIOD-CRISPR, for viral genome detection may offer options for prompt and point-of-care detection. Moreover, aptamer-based probes may be multifaceted for developing portable and high-throughput assays with fluorescent or chemiluminescent probes for viral proteins. In conclusion, assays are available for viral genome and protein detection, and the selection of specific assays depends on the purposes of prevention, diagnosis and pandemic control, or monitoring of vaccination efficacy.

Clinical Perspectives of Single-Cell RNA Sequencing.

The ability of single-cell genomics to resolve cellular heterogeneity is highly appreciated in cancer and is being exploited for precision medicine. In the recent decade, we have witnessed the incorporation of cancer genomics into the clinical decision-making process for molecular-targeted therapies. Compared with conventional genomics, which primarily focuses on the specific and sensitive detection of the molecular targets, single-cell genomics addresses intratumoral heterogeneity and the microenvironmental components impacting the treatment response and resistance. As an exploratory tool, single-cell genomics provides an unprecedented opportunity to improve the diagnosis, monitoring, and treatment of cancer. The results obtained upon employing bulk cancer genomics indicate that single-cell genomics is at an early stage with respect to exploration of clinical relevance and requires further innovations to become a widely utilized technology in the clinic.

Neuroepigenetics of psychiatric disorders: Focus on lncRNA.

Understanding the pathology of psychiatric disorders is challenging due to their complexity and multifactorial origin. However, development of high-throughput technologies has allowed for better insight into their molecular signatures. Advancement of sequencing methodologies have made it possible to study not only the protein-coding but also the noncoding genome. It is now clear that besides the genetic component, different epigenetic mechanisms play major roles in the onset and development of psychiatric disorders. Among them, examining the role of long noncoding RNAs (lncRNAs) is a relatively new field. Here, we present an overview of what is currently known about the involvement of lncRNAs in schizophrenia, major depressive and bipolar disorders, as well as suicide. The diagnosis of psychiatric disorders mainly relies on clinical evaluation without using measurable biomarkers. In this regard, lncRNA may open new opportunities for development of molecular tests. However, so far only a small set of known lncRNAs have been characterized at molecular level, which means they have a long way to go before clinical implementation. Understanding how changes in lncRNAs affect the appearance and development of psychiatric disorders may lead to a more classified and objective diagnostic system, but also open up new therapeutic targets for these patients.

[Progress in Single-cell RNA Sequencing of Lung Adenocarcinoma].

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer and one of the main causes of cancer-related deaths. In the past decade, with the widespread use of computed tomography (CT) in routine screening for lung cancer, the incidence of LUAD presenting as small pulmonary nodules radiologically, has increased remarkably. The mechanisms of the occurrence and progression of LUADs are complex, and the prognoses of patients with LUAD vary significantly. Although significant progress has been made in targeted therapy and immunotherapy for LUADs in recent years, the drug resistance of tumor cells has not been effectively overcome, which limits the benefits of patients. With the accomplishment of the Human Genome Project, sequencing-based genomic and transcriptomics have come into the field of clinical and scientific researches. Single-cell sequencing, as a new type of sequencing method that has captured increasing attention recently, can perform specific analysis of cell populations at single-cell level, which can reveal the unique changes of each cell type. Single-cell sequencing can also provide accurate assessment on heterogeneous stromal cells and cancer cells, which is helpful to reveal the complexity of molecular compositions and differences between non- and malignant tissues. To sum up, it is an urgent need for clinicians and basic scientists to deeply understand the pathogenesis and development of LUAD, the heterogeneity of tumor microenvironment (TME) and the mechanism of drug resistance formation through single-cell sequencing, so as to discover new therapeutic targets. In this paper, we reviewed and summarized the application and progress in single-cell sequencing of LUADs.
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Quantifying the effect of experimental perturbations at single-cell resolution.

Current methods for comparing single-cell RNA sequencing datasets collected in multiple conditions focus on discrete regions of the transcriptional state space, such as clusters of cells. Here we quantify the effects of perturbations at the single-cell level using a continuous measure of the effect of a perturbation across the transcriptomic space. We describe this space as a manifold and develop a relative likelihood estimate of observing each cell in each of the experimental conditions using graph signal processing. This likelihood estimate can be used to identify cell populations specifically affected by a perturbation. We also develop vertex frequency clustering to extract populations of affected cells at the level of granularity that matches the perturbation response. The accuracy of our algorithm at identifying clusters of cells that are enriched or depleted in each condition is, on average, 57% higher than the next-best-performing algorithm tested. Gene signatures derived from these clusters are more accurate than those of six alternative algorithms in ground truth comparisons.

Patch-seq: Past, Present, and Future.

Single-cell transcriptomic approaches are revolutionizing neuroscience. Integrating this wealth of data with morphology and physiology, for the comprehensive study of neuronal biology, requires multiplexing gene expression data with complementary techniques. To meet this need, multiple groups in parallel have developed "Patch-seq," a modification of whole-cell patch-clamp protocols that enables mRNA sequencing of cell contents after electrophysiological recordings from individual neurons and morphologic reconstruction of the same cells. In this review, we first outline the critical technical developments that enabled robust Patch-seq experimental efforts and analytical solutions to interpret the rich multimodal data generated. We then review recent applications of Patch-seq that address novel and long-standing questions in neuroscience. These include the following: (1) targeted study of specific neuronal populations based on their anatomic location, functional properties, lineage, or a combination of these factors; (2) the compilation and integration of multimodal cell type atlases; and (3) the investigation of the molecular basis of morphologic and functional diversity. Finally, we highlight potential opportunities for further technical development and lines of research that may benefit from implementing the Patch-seq technique. As a multimodal approach at the intersection of molecular neurobiology and physiology, Patch-seq is uniquely positioned to directly link gene expression to brain function.

New Twists in Detecting mRNA Modification Dynamics.

Modified nucleotides in mRNA are an essential addition to the standard genetic code of four nucleotides in animals, plants, and their viruses. The emerging field of epitranscriptomics examines nucleotide modifications in mRNA and their impact on gene expression. The low abundance of nucleotide modifications and technical limitations, however, have hampered systematic analysis of their occurrence and functions. Selective chemical and immunological identification of modified nucleotides has revealed global candidate topology maps for many modifications in mRNA, but further technical advances to increase confidence will be necessary. Single-molecule sequencing introduced by Oxford Nanopore now promises to overcome such limitations, and we summarize current progress with a particular focus on the bioinformatic challenges of this novel sequencing technology.

Review of Single-Cell RNA Sequencing in the Heart.

Single-cell RNA sequencing (scRNA-seq) technology is a powerful, rapidly developing tool for characterizing individual cells and elucidating biological mechanisms at the cellular level. Cardiovascular disease is one of the major causes of death worldwide and its precise pathology remains unclear. scRNA-seq has provided many novel insights into both healthy and pathological hearts. In this review, we summarize the various scRNA-seq platforms and describe the molecular mechanisms of cardiovascular development and disease revealed by scRNA-seq analysis. We then describe the latest technological advances in scRNA-seq. Finally, we discuss how to translate basic research into clinical medicine using scRNA-seq technology.