High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing

Single-cell transcriptome profiling highlights the importance of telocyte, kallikrein genes, and alternative splicing in mouse testes aging

Advancing healthcare for elderly men requires a deeper understanding of testicular aging processes. In this study, we conducted transcriptomic profiling of 43,323 testicular single cells from young and old mice, shedding light on 1032 telocytes-an underexplored testicular cell type in previous research. Our study unveiled 916 age-related differentially expressed genes (age-DEGs), with telocytes emerging as the cell type harboring the highest count of age-DEGs. Of particular interest, four genes (Klk1b21, Klk1b22, Klk1b24, Klk1b27) from the Kallikrein family, specifically expressed in Leydig cells, displayed down-regulation in aged testes. Moreover, cell-type-level splicing analyses unveiled 1838 age-related alternative splicing (AS) events. While we confirmed the presence of more age-DEGs in somatic cells compared to germ cells, unexpectedly, more age-related AS events were identified in germ cells. Further experimental validation highlighted 4930555F03Rik, a non-coding RNA gene exhibiting significant age-related AS changes. Our study represents the first age-related single-cell transcriptomic investigation of testicular telocytes and Kallikrein genes in Leydig cells, as well as the first delineation of cell-type-level AS dynamics during testicular aging in mice.

The mechanism of Laceyella sacchari FBKL4.010 produced tetramethylpyrazine in the liquid fermentation by comparative transcriptomic techniques

Tetramethylpyrazine (TTMP) is considered a crucial flavor component in Moutai-flavored liquor. Laceyeella sacchari FBKL4.010 (L. sacchari) is the dominant species found in Moutai-flavor Daqu, and this study aims to determine the mechanism by which L. sacchari produces TTMP during liquid fermentation of Moutai-flavor Daqu. The results of the liquid fermentation performance demonstrated a gradual increase in biomass over time, while there was a gradual decline in residual glucose content and pH value. Furthermore, analysis of volatile components revealed that liquid fermentation significantly enhanced the production of TTMP in Moutai-flavor Daqu, with the relative content of TTMP reaching 14.24 mg/L after 96 h of liquid fermentation. Additionally, to explore the synthesis mechanism of TTMP, we compared differentially expressed genes (DEGs) of L. sacchari between 24 and 96 h using comparative transcriptomic techniques. The results indicated that DEGs involved in isoleucine, valine, and leucine biosynthesis pathway were upregulated, while those associated with isoleucine, valine, and leucine degradation pathway were downregulated, suggesting that the valine, leucine, and isoleucine biosynthesis pathway primarily contributes ammonia for TTMP synthesis. The findings of this study present an opportunity for further elucidating the production process of TTMP in Moutai-flavor Daqu during liquid fermentation.

Advances in single-cell long-read sequencing technologies

With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.

Development of new techniques and clinical applications of liquid biopsy in lung cancer management

Lung cancer is an exceedingly malignant tumor reported as having the highest morbidity and mortality of any cancer worldwide, thus posing a great threat to global health. Despite the growing demand for precision medicine, current methods for early clinical detection, treatment and prognosis monitoring in lung cancer are hampered by certain bottlenecks. Studies have found that during the formation and development of a tumor, molecular substances carrying tumor-related genetic information can be released into body fluids. Liquid biopsy (LB), a method for detecting these tumor-related markers in body fluids, maybe a way to make progress in these bottlenecks. In recent years, LB technology has undergone rapid advancements. Therefore, this review will provide information on technical updates to LB and its potential clinical applications, evaluate its effectiveness for specific applications, discuss the existing limitations of LB, and present a look forward to possible future clinical applications. Specifically, this paper will introduce technical updates from the prospectives of engineering breakthroughs in the detection of membrane-based LB biomarkers and other improvements in sequencing technology. Additionally, it will summarize the latest applications of liquid biopsy for the early detection, diagnosis, treatment, and prognosis of lung cancer. We will present the interconnectedness of clinical and laboratory issues and the interplay of technology and application in LB today.

Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

Advancements in single-cell sequencing have transformed the genomics field by allowing researchers to delve into the intricate cellular heterogeneity within tissues at greater resolution. While single-cell omics are more widely applied in model organisms and humans, their use in livestock species is just beginning. Studies in cattle, sheep, and goats have already leveraged single-cell and single-nuclei RNA-seq as well as single-cell and single-nuclei ATAC-seq to delineate cellular diversity in tissues, track changes in cell populations and gene expression over developmental stages, and characterize immune cell populations important for disease resistance and resilience. Although challenges exist for the use of this technology in ruminant livestock, such as the precise annotation of unique cell populations and spatial resolution of cells within a tissue, there is vast potential to enhance our understanding of the cellular and molecular mechanisms underpinning traits essential for healthy and productive livestock. This review intends to highlight the insights gained from published single-cell omics studies in cattle, sheep, and goats, particularly those with publicly accessible data. Further, this manuscript will discuss the challenges and opportunities of this technology in ruminant livestock and how it may contribute to enhanced profitability and sustainability of animal agriculture in the future.

Advances in long-read single-cell transcriptomics

Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

High-throughput RNA isoform sequencing using programmed cDNA concatenation

Full-length RNA-sequencing methods using long-read technologies can capture complete transcript isoforms, but their throughput is limited. We introduce multiplexed arrays isoform sequencing (MAS-ISO-seq), a technique for programmably concatenating complementary DNAs (cDNAs) into molecules optimal for long-read sequencing, increasing the throughput >15-fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. When applied to single-cell RNA sequencing of tumor-infiltrating T cells, MAS-ISO-seq demonstrated a 12- to 32-fold increase in the discovery of differentially spliced genes.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

Analytical Validation of Loss of Heterozygosity and Mutation Detection in Pancreatic Fine-Needle Aspirates by Capillary Electrophoresis and Sanger Sequencing

Pancreatic cystic disease, including duct dilation, represents precursor states towards the development of pancreatic cancer, a form of malignancy with relatively low incidence but high mortality. While most of these cysts (>85%) are benign, the remainder can progress over time, leading to malignant transformation, invasion, and metastasis. Cytologic diagnosis is challenging, limited by the paucity or complete absence of cells representative of cystic lesions and fibrosis. Molecular analysis of fluids collected from endoscopic-guided fine-needle aspiration of pancreatic cysts and dilated duct lesions can be used to evaluate the risk of progression to malignancy. The basis for the enhanced diagnostic utility of molecular approaches is the ability to interrogate cell-free nucleic acid of the cyst/duct and/or extracellular fluid. The allelic imbalances at tumor suppressor loci and the selective oncogenic drivers are used clinically to help differentiate benign stable pancreatic cysts from those progressing toward high-grade dysplasia. Methods are discussed and used to determine the efficacy for diagnostic implementation. Here, we report the analytical validation of methods to detect causally associated molecular changes integral to the pathogenesis of pancreatic cancer from pancreatic cyst fluids.

Single-cell analysis of isoform switching and transposable element expression during preimplantation embryonic development

Alternative splicing is an essential regulatory mechanism for development and pathogenesis. Through alternative splicing one gene can encode multiple isoforms and be translated into proteins with different functions. Therefore, this diversity is an important dimension to understand the molecular mechanism governing embryo development. Isoform expression in preimplantation embryos has been extensively investigated, leading to the discovery of new isoforms. However, the dynamics of isoform switching of different types of transcripts throughout the development remains unexplored. Here, using single-cell direct isoform sequencing in over 100 single blastomeres from the mouse oocyte to blastocyst stage, we quantified isoform expression and found that 3-prime partial transcripts lacking stop codons are highly accumulated in oocytes and zygotes. These transcripts are not transcription by-products and might play a role in maternal to zygote transition (MZT) process. Long-read sequencing also enabled us to determine the expression of transposable elements (TEs) at specific loci. In this way, we identified 3,894 TE loci that exhibited dynamic changes along the preimplantation development, likely regulating the expression of adjacent genes. Our work provides novel insights into the transcriptional regulation of early embryo development.

FLIBase: a comprehensive repository of full-length isoforms across human cancers and tissues

Regulatory processes at the RNA transcript level play a crucial role in generating transcriptome diversity and proteome composition in human cells, impacting both physiological and pathological states. This study introduces FLIBase (www.FLIBase.org), a specialized database that focuses on annotating full-length isoforms using long-read sequencing techniques. We collected and integrated long-read (351 samples) and short-read (12 469 samples) RNA sequencing data from diverse normal and cancerous human tissues and cells. The current version of FLIBase comprises a total of 983 789 full-length spliced isoforms, identified through long-read sequences and verified using short-read exon-exon splice junctions. Of these, 188 248 isoforms have been annotated, while 795 541 isoforms remain unannotated. By overcoming the limitations of short-read RNA sequencing methods, FLIBase provides an accurate and comprehensive representation of full-length transcripts. These comprehensive annotations empower researchers to undertake various downstream analyses and investigations. Importantly, FLIBase exhibits a significant advantage in identifying a substantial number of previously unannotated isoforms and tumor-specific RNA transcripts. These tumor-specific RNA transcripts have the potential to serve as a source of immunogenic recurrent neoantigens. This remarkable discovery holds tremendous promise for advancing the development of tailored RNA-based diagnostic and therapeutic strategies for various types of human cancer.

The use of single-cell RNA-seq to study heterogeneity at varying levels of virus-host interactions

The outcome of viral infection depends on the diversity of the infecting viral population and the heterogeneity of the cell population that is infected. Until almost a decade ago, the study of these dynamic processes during viral infection was challenging and limited to certain targeted measurements. Presently, with the use of single-cell sequencing technology, the complex interface defined by the interactions of cells with infecting virus can now be studied across the breadth of the transcriptome in thousands of individual cells simultaneously. In this review, we will describe the use of single-cell RNA sequencing (scRNA-seq) to study the heterogeneity of viral infections, ranging from individual virions to the immune response between infected individuals. In addition, we highlight certain key experimental limitations and methodological decisions that are critical to analyzing scRNA-seq data at each scale.

Improving the RNA velocity approach with single-cell RNA lifecycle (nascent, mature and degrading RNAs) sequencing technologies

We presented an experimental method called FLOUR-seq, which combines BD Rhapsody and nanopore sequencing to detect the RNA lifecycle (including nascent, mature, and degrading RNAs) in cells. Additionally, we updated our HIT-scISOseq V2 to discover a more accurate RNA lifecycle using 10x Chromium and Pacbio sequencing. Most importantly, to explore how single-cell full-length RNA sequencing technologies could help improve the RNA velocity approach, we introduced a new algorithm called 'Region Velocity' to more accurately configure cellular RNA velocity. We applied this algorithm to study spermiogenesis and compared the performance of FLOUR-seq with Pacbio-based HIT-scISOseq V2. Our findings demonstrated that 'Region Velocity' is more suitable for analyzing single-cell full-length RNA data than traditional RNA velocity approaches. These novel methods could be useful for researchers looking to discover full-length RNAs in single cells and comprehensively monitor RNA lifecycle in cells.

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

Single-cell analysis technologies for cancer research: from tumor-specific single cell discovery to cancer therapy

Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.

Comprehensive transcript-level analysis reveals transcriptional reprogramming during the progression of Alzheimer's disease

Background

Alzheimer's disease (AD) is a common neurodegenerative disorder that has a multi-step disease progression. Differences between moderate and advanced stages of AD have not yet been fully characterized.

Materials and methods

Herein, we performed a transcript-resolution analysis in 454 AD-related samples, including 145 non-demented control, 140 asymptomatic AD (AsymAD), and 169 AD samples. We comparatively characterized the transcriptome dysregulation in AsymAD and AD samples at transcript level.

Results

We identified 4,056 and 1,200 differentially spliced alternative splicing events (ASEs) that might play roles in the disease progression of AsymAD and AD, respectively. Our further analysis revealed 287 and 222 isoform switching events in AsymAD and AD, respectively. In particular, a total of 163 and 119 transcripts showed increased usage, while 124 and 103 transcripts exhibited decreased usage in AsymAD and AD, respectively. For example, gene APOA2 showed no expression changes between AD and non-demented control samples, but expressed higher proportion of transcript ENST00000367990.3 and lower proportion of transcript ENST00000463812.1 in AD compared to non-demented control samples. Furthermore, we constructed RNA binding protein (RBP)-ASE regulatory networks to reveal potential RBP-mediated isoform switch in AsymAD and AD.

Conclusion

In summary, our study provided transcript-resolution insights into the transcriptome disturbance of AsymAD and AD, which will promote the discovery of early diagnosis biomarkers and the development of new therapeutic strategies for patients with AD.