Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells

The Emerging Roles of Alternative Splicing in Human Oncovirus Infection

Alternative splicing (AS) is one of the most potent mechanisms for expanding the diversity of proteomes. During infection, human oncogenic viruses may exploit the AS to facilitate their replication cycle. Moreover, persistently infecting viruses can target key genes involved in classical signaling pathways to promote viral persistence and tumor progression. Here, we highlight how oncogenic viruses hijack AS system to manipulate host biological processes, and the host's AS system in turn modulates viral infection and replication. In addition, we have summarized the relatively underexplored involvement of noncoding RNAs in AS following tumor virus infection. This bidirectional interaction provides novel insights into interaction of virus-host and opens new avenues for therapeutic strategies targeting oncogenic viral infections.

Single-cell RNA sequencing of nc886, a non-coding RNA transcribed by RNA polymerase III, with a primer spike-in strategy

Single-cell RNA sequencing (scRNA-seq) has emerged as a versatile tool in biology, enabling comprehensive genomic-level characterization of individual cells. Currently, most scRNA-seq methods generate barcoded cDNAs by capturing the polyA tails of mRNAs, which exclude many non-coding RNAs (ncRNAs), especially those transcribed by RNA polymerase III (Pol III). Although previously thought to be expressed constitutively, Pol III-transcribed ncRNAs are expressed variably in healthy and disease states and play important roles therein, necessitating their profiling at the single-cell level. In this study, we developed a measurement protocol for nc886 as a model case and initial step for scRNA-seq for Pol III-transcribed ncRNAs. Specifically, we spiked in an oligo-tagged nc886-specific primer during the polyA tail capture process for the 5'scRNA-seq. We then produced sequencing libraries for standard 5' gene expression and oligo-tagged nc886 separately, to accommodate different cDNA sizes and ensure undisturbed transcriptome analysis. We applied this protocol in three cell lines that express high, low, and zero levels of nc886. Our results show that the identification of oligo tags exhibited limited target specificity, and sequencing reads of nc886 enabled the correction of non-specific priming. These findings suggest that gene-specific primers (GSPs) can be employed to capture RNAs lacking a polyA tail, with subsequent sequence verification ensuring accurate gene expression counting. Moreover, we embarked on an analysis of differentially expressed genes in cell line sub-clusters with differential nc886 expression, demonstrating variations in gene expression phenotypes. Collectively, the primer spike-in strategy allows combined analysis of ncRNAs and gene expression phenotype.

Transcriptomic Signatures of Zika Virus Infection in Patients and a Cell Culture Model

Zika virus (ZIKV), a re-emerging flavivirus, is associated with devasting developmental and neurological disease outcomes particularly in infants infected in utero. Towards understanding the molecular underpinnings of the unique ZIKV disease pathologies, numerous transcriptome-wide studies have been undertaken. Notably, these studies have overlooked the assimilation of RNA-seq analysis from ZIKV-infected patients with cell culture model systems. In this study we find that ZIKV-infection of human lung adenocarcinoma A549 cells, mirrored both the transcriptional and alternative splicing profiles from previously published RNA-seq data of peripheral blood mononuclear cells collected from pediatric patients during early acute, late acute, and convalescent phases of ZIKV infection. Our analyses show that ZIKV infection in cultured cells correlates with transcriptional changes in patients, while the overlap in alternative splicing profiles was not as extensive. Overall, our data indicate that cell culture model systems support dissection of select molecular changes detected in patients and establishes the groundwork for future studies elucidating the biological implications of alternative splicing during ZIKV infection.

Zika virus infection in a cell culture model reflects the transcriptomic signatures in patients

Zika virus (ZIKV), a re-emerging flavivirus, is associated with devasting developmental and neurological disease outcomes particularly in infants infected in utero. Towards understanding the molecular underpinnings of the unique ZIKV disease pathologies, numerous transcriptome-wide studies have been undertaken. Notably, these studies have overlooked the assimilation of RNA-seq analysis from ZIKV-infected patients with cell culture model systems. In this study we find that ZIKV-infection of human lung adenocarcinoma A549 cells, mirrored both the transcriptional and alternative splicing profiles from previously published RNA-seq data of peripheral blood mononuclear cells collected from pediatric patients during early acute, late acute, and convalescent phases of ZIKV infection. Our analyses show that ZIKV infection in cultured cells correlates with transcriptional changes in patients, while the overlap in alternative splicing profiles was not as extensive. Overall, our data indicate that cell culture model systems support dissection of select molecular changes detected in patients and establishes the groundwork for future studies elucidating the biological implications of alternative splicing during ZIKV infection.

How Deepbics Quantifies Intensities of Transcription Factor-DNA Binding and Facilitates Prediction of Single Nucleotide Variant Pathogenicity With a Deep Learning Model Trained On ChIP-Seq Data Sets

The binding of DNA sequences to cell type-specific transcription factors is essential for regulating gene expression in all organisms. Many variants occurring in these binding regions play crucial roles in human disease by disrupting the cis-regulation of gene expression. We first implemented a sequence-based deep learning model called deepBICS to quantify the intensity of transcription factors-DNA binding. The experimental results not only showed the superiority of deepBICS on ChIP-seq data sets but also suggested deepBICS as a language model could help the classification of disease-related and neutral variants. We then built a language model-based method called deepBICS4SNV to predict the pathogenicity of single nucleotide variants. The good performance of deepBICS4SNV on 2 tests related to Mendelian disorders and viral diseases shows the sequence contextual information derived from language models can improve prediction accuracy and generalization capability.

Single-cell RNA-seq methods to interrogate virus-host interactions

The twenty-first century has seen the emergence of many epidemic and pandemic viruses, with the most recent being the SARS-CoV-2-driven COVID-19 pandemic. As obligate intracellular parasites, viruses rely on host cells to replicate and produce progeny, resulting in complex virus and host dynamics during an infection. Single-cell RNA sequencing (scRNA-seq), by enabling broad and simultaneous profiling of both host and virus transcripts, represents a powerful technology to unravel the delicate balance between host and virus. In this review, we summarize technological and methodological advances in scRNA-seq and their applications to antiviral immunity. We highlight key scRNA-seq applications that have enabled the understanding of viral genomic and host response heterogeneity, differential responses of infected versus bystander cells, and intercellular communication networks. We expect further development of scRNA-seq technologies and analytical methods, combined with measurements of additional multi-omic modalities and increased availability of publicly accessible scRNA-seq datasets, to enable a better understanding of viral pathogenesis and enhance the development of antiviral therapeutics strategies.

Clinically relevant fusion oncogenes: detection and practical implications

Mechanistically, chimeric genes result from DNA rearrangements and include parts of preexisting normal genes combined at the genomic junction site. Some rearranged genes encode pathological proteins with altered molecular functions. Those which can aberrantly promote carcinogenesis are called fusion oncogenes. Their formation is not a rare event in human cancers, and many of them were documented in numerous study reports and in specific databases. They may have various molecular peculiarities like increased stability of an oncogenic part, self-activation of tyrosine kinase receptor moiety, and altered transcriptional regulation activities. Currently, tens of low molecular mass inhibitors are approved in cancers as the drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins, that is, including ALK, ABL, EGFR, FGFR1-3, NTRK1-3, MET, RET, ROS1 moieties. Therein, the presence of the respective RTK fusion in the cancer genome is the diagnostic biomarker for drug prescription. However, identification of such fusion oncogenes is challenging as the breakpoint may arise in multiple sites within the gene, and the exact fusion partner is generally unknown. There is no gold standard method for RTK fusion detection, and many alternative experimental techniques are employed nowadays to solve this issue. Among them, RNA-seq-based methods offer an advantage of unbiased high-throughput analysis of only transcribed RTK fusion genes, and of simultaneous finding both fusion partners in a single RNA-seq read. Here we focus on current knowledge of biology and clinical aspects of RTK fusion genes, related databases, and laboratory detection methods.

Modeling HPV-Associated Disease and Cancer Using the Cottontail Rabbit Papillomavirus

Approximately 5% of all human cancers are attributable to human papillomavirus (HPV) infections. HPV-associated diseases and cancers remain a substantial public health and economic burden worldwide despite the availability of prophylactic HPV vaccines. Current diagnosis and treatments for HPV-associated diseases and cancers are predominantly based on cell/tissue morphological examination and/or testing for the presence of high-risk HPV types. There is a lack of robust targets/markers to improve the accuracy of diagnosis and treatments. Several naturally occurring animal papillomavirus models have been established as surrogates to study HPV pathogenesis. Among them, the Cottontail rabbit papillomavirus (CRPV) model has become known as the gold standard. This model has played a pivotal role in the successful development of vaccines now available to prevent HPV infections. Over the past eighty years, the CRPV model has been widely applied to study HPV carcinogenesis. Taking advantage of a large panel of functional mutant CRPV genomes with distinct, reproducible, and predictable phenotypes, we have gained a deeper understanding of viral–host interaction during tumor progression. In recent years, the application of genome-wide RNA-seq analysis to the CRPV model has allowed us to learn and validate changes that parallel those reported in HPV-associated cancers. In addition, we have established a selection of gene-modified rabbit lines to facilitate mechanistic studies and the development of novel therapeutic strategies. In the current review, we summarize some significant findings that have advanced our understanding of HPV pathogenesis and highlight the implication of the development of novel gene-modified rabbits to future mechanistic studies.

Functional Annotation of a Full-Length Transcriptome and Identification of Genes Associated with Flower Development in Rhododendronsimsii (Ericaceae)

Rhododendronsimsii is one of the top ten famous flowers in China. Due to its historical value and high aesthetic, it is widely popular among Chinese people. Various colors are important breeding objectives in Rhododendron L. The understanding of the molecular mechanism of flower color formation can provide a theoretical basis for the improvement of flower color in Rhododendron L. To generate the R.simsii transcriptome, PacBio sequencing technology has been used. A total of 833,137 full-length non-chimeric reads were obtained and 726,846 high-quality full-length transcripts were found. Moreover, 40,556 total open reading frames were obtained; of which 36,018 were complete. In gene annotation analyses, 39,411, 18,565, 16,102 and 17,450 transcriptions were allocated to GO, Nr, KEGG and COG databases, correspondingly. To identify long non-coding RNAs (lncRNAs), we utilized four computational methods associated with Protein families (Pfam), Cooperative Data Classification (CPC), Coding Assessing Potential Tool (CPAT) and Coding Non Coding Index (CNCI) databases and observed 6170, 2265, 4084 and 1240 lncRNAs, respectively. Based on the results, most genes were enriched in the flavonoid biosynthetic pathway. The eight key genes on the anthocyanin biosynthetic pathway were further selected and analyzed by qRT-PCR. The F3'H and ANS showed an upward trend in the developmental stages of R. simsii. The highest expression of F3'5'H and FLS in the petal color formation of R. simsii was observed. This research provided a huge number of full-length transcripts, which will help to proceed genetic analyses of R.simsii. native, which is a semi-deciduous shrub.

AGO-accessible anticancer siRNAs designed with synergistic miRNA-like activity

Small interfering RNAs (siRNAs) therapeutically induce RNA interference (RNAi) of disease-causing genes, but they also silence hundreds of seed-matched off-targets as behaving similar to microRNAs (miRNAs). miRNAs control the pathophysiology of tumors, wherein their accessible binding sites can be sequenced by Argonaute crosslinking immunoprecipitation (AGO CLIP). Herein, based on AGO CLIP, we develop potent anticancer siRNAs utilizing miRNA-like activity (mi/siRNAs). The mi/siRNAs contain seed sequences (positions 2-7) of tumor-suppressive miRNAs while maintaining perfect sequence complementarity to the AGO-accessible tumor target sites. Initially, host miRNA interactions with human papillomavirus 18 (HPV18) were identified in cervical cancer by AGO CLIP, revealing tumor-suppressive activity of miR-1/206 and miR-218. Based on the AGO-miRNA binding sites, mi/siRNAs were designed to target E6 and E7 (E6/E7) transcript with seed sequences of miR-1/206 (206/E7) and miR-218 (218/E7). Synergistic anticancer activity of 206/E7 and 218/E7 was functionally validated and confirmed via RNA sequencing and in vivo xenograft models (206/E7). Other mi/siRNA sequences were additionally designed for cervical, ovarian, and breast cancer, and available as an online tool (http://ago.korea.ac.kr/misiRNA); some of the mi/siRNAs were validated for their augmented anticancer activity (206/EphA2 and 206/Her2). mi/siRNAs could coordinate miRNA-like activity with robust siRNA function, demonstrating the potential of AGO CLIP analysis for RNAi therapeutics.

Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has high relapse and low 5-year survival rates. Single-cell profiling in relapsed HCC may aid in the design of effective anticancer therapies, including immunotherapies. We profiled the transcriptomes of ∼17,000 cells from 18 primary or early-relapse HCC cases. Early-relapse tumors have reduced levels of regulatory T cells, increased dendritic cells (DCs), and increased infiltrated CD8+ T cells, compared with primary tumors, in two independent cohorts. Remarkably, CD8+ T cells in recurrent tumors overexpressed KLRB1 (CD161) and displayed an innate-like low cytotoxic state, with low clonal expansion, unlike the classical exhausted state observed in primary HCC. The enrichment of these cells was associated with a worse prognosis. Differential gene expression and interaction analyses revealed potential immune evasion mechanisms in recurrent tumor cells that dampen DC antigen presentation and recruit innate-like CD8+ T cells. Our comprehensive picture of the HCC ecosystem provides deeper insights into immune evasion mechanisms associated with tumor relapse.

Multiregion single-cell sequencing reveals the transcriptional landscape of the immune microenvironment of colorectal cancer

The tumor microenvironment is a complex ecosystem formed by distinct and interacting cell populations, and its composition is related to cancer prognosis and response to clinical treatment. In this study, we have taken the advantage of two single-cell RNA sequencing technologies (Smart-seq2 and DNBelab C4) to generate an atlas of 15,115 immune and nonimmune cells from primary tumors and hepatic metastases of 18 colorectal cancer (CRC) patients. We observed extensive changes in the proportions and functional states of T cells and B cells in tumor tissues, compared to those of paired non-tumor tissues. Importantly, we found that B cells from early CRC tumor were identified to be pre-B like expressing tumor suppressors, whereas B cells from advanced CRC tumors tended to be developed into plasma cells. We also identified the association of IgA+ IGLC2+ plasma cells with poor CRC prognosis, and demonstrated a significant interaction between B-cell and myeloid-cell signaling, and found CCL8+ cycling B cells/CCR5+ T-cell interactions as a potential antitumoral mechanism in advanced CRC tumors. Our results provide deeper insights into the immune infiltration within CRC, and a new perspective for the future research in immunotherapies for CRC.

Embryonic liver developmental trajectory revealed by single-cell RNA sequencing in the Foxa2eGFP mouse

The liver and gallbladder are among the most important internal organs derived from the endoderm, yet the development of the liver and gallbladder in the early embryonic stages is not fully understood. Using a transgenic Foxa2^eGFP reporter mouse line, we performed single-cell full-length mRNA sequencing on endodermal and hepatic cells isolated from ten embryonic stages, ranging from E7.5 to E15.5. We identified the embryonic liver developmental trajectory from gut endoderm to hepatoblasts and characterized the transcriptome of the hepatic lineage. More importantly, we identified liver primordium as the nascent hepatic progenitors with both gut and liver features and documented dynamic gene expression during the epithelial-hepatic transition (EHT) at the stage of liver specification during E9.5–11.5. We found six groups of genes switched on or off in the EHT process, including diverse transcripitional regulators that had not been previously known to be expressed during EHT. Moreover, we identified and revealed transcriptional profiling of gallbladder primordium at E9.5. The present data provides a high-resolution resource and critical insights for understanding the liver and gallbladder development.

The authors report a single cell-resolution gene expression atlas for the developing mouse liver and gallbladder using a transgenic Foxa2^eGFP mouse line. By tracing the development of cells from gut endoderm to hepatoblasts they identify key transcriptional changes during liver specification.

Single-cell RNA profiling links ncRNAs to spatiotemporal gene expression during C. elegans embryogenesis

Recent studies show that non-coding RNAs (ncRNAs) can regulate the expression of protein-coding genes and play important roles in mammalian development. Previous studies have revealed that during C. elegans (Caenorhabditis elegans) embryo development, numerous genes in each cell are spatiotemporally regulated, causing the cell to differentiate into distinct cell types and tissues. We ask whether ncRNAs participate in the spatiotemporal regulation of genes in different types of cells and tissues during the embryogenesis of C. elegans. Here, by using marker-free full-length high-depth single-cell RNA sequencing (scRNA-seq) technique, we sequence the whole transcriptomes from 1031 embryonic cells of C. elegans and detect 20,431 protein-coding genes, including 22 cell-type-specific protein-coding markers, and 9843 ncRNAs including 11 cell-type-specific ncRNA markers. We induce a ncRNAs-based clustering strategy as a complementary strategy to the protein-coding gene-based clustering strategy for single-cell classification. We identify 94 ncRNAs that have never been reported to regulate gene expressions, are co-expressed with 1208 protein-coding genes in cell type specific and/or embryo time specific manners. Our findings suggest that these ncRNAs could potentially influence the spatiotemporal expression of the corresponding genes during the embryogenesis of C. elegans.

Single-Cell Sequencing in Human Genital Infections

Human genital infections are one of the most concerning issues worldwide and can be categorized into sexually transmitted, urinary tract and vaginal infections. These infections, if left untreated, can disseminate to the other parts of the body and cause more complicated illnesses such as pelvic inflammatory disease, urethritis, and anogenital cancers. The effective treatment against these infections is further complicated by the emergence of antimicrobial resistance in the genital infection causing pathogens. Furthermore, the development and applications of single-cell sequencing technologies have open new possibilities to study the drug resistant clones, cell to cell variations, the discovery of acquired drug resistance mutations, transcriptional diversity of a pathogen across different infection stages, to identify rare cell types and investigate different cellular states of genital infection causing pathogens, and to develop novel therapeutical strategies. In this chapter, I will provide a complete review of the applications of single-cell sequencing in human genital infections before discussing their limitations and challenges.

Fusion transcript detection using spatial transcriptomics

BACKGROUND

Fusion transcripts are involved in tumourigenesis and play a crucial role in tumour heterogeneity, tumour evolution and cancer treatment resistance. However, fusion transcripts have not been studied at high spatial resolution in tissue sections due to the lack of full-length transcripts with spatial information. New high-throughput technologies like spatial transcriptomics measure the transcriptome of tissue sections on almost single-cell level. While this technique does not allow for direct detection of fusion transcripts, we show that they can be inferred using the relative poly(A) tail abundance of the involved parental genes.

METHOD

We present a new method STfusion, which uses spatial transcriptomics to infer the presence and absence of poly(A) tails. A fusion transcript lacks a poly(A) tail for the 5' gene and has an elevated number of poly(A) tails for the 3' gene. Its expression level is defined by the upstream promoter of the 5' gene. STfusion measures the difference between the observed and expected number of poly(A) tails with a novel C-score.

RESULTS

We verified the STfusion ability to predict fusion transcripts on HeLa cells with known fusions. STfusion and C-score applied to clinical prostate cancer data revealed the spatial distribution of the cis-SAGe SLC45A3-ELK4 in 12 tissue sections with almost single-cell resolution. The cis-SAGe occurred in disease areas, e.g. inflamed, prostatic intraepithelial neoplastic, or cancerous areas, and occasionally in normal glands.

CONCLUSIONS

STfusion detects fusion transcripts in cancer cell line and clinical tissue data, and distinguishes chimeric transcripts from chimeras caused by trans-splicing events. With STfusion and the use of C-scores, fusion transcripts can be spatially localised in clinical tissue sections on almost single cell level.

Single-cell RNA-seq unveils critical regulators of human FOXP3+ regulatory T cell stability

The heterogeneity and plasticity of T lymphocytes is critical for determining immune response outcomes. Functional regulatory T (Treg) cells are commonly characterized by stable FOXP3 expression and have reported to exhibit heterogeneous phenotypes under inflammatory conditions. However, the interplay between inflammation and Treg cell suppressive activity still remains elusive. Here, we utilized single-cell RNA sequencing to investigate how human Treg cells respond to the pro-inflammatory cytokine interleukin-6 (IL-6). We observed that Treg cells divided into two subpopulations after IL-6 stimulation. TIGIT^- unstable Treg cells lost FOXP3 expression and gained an effector-like T cell phenotype, whereas TIGIT⁺ Treg cells retained robust suppressive function. Single cell transcriptome analysis revealed a spectrum of cellular states of IL-6-stimulated Treg cells and how cytochrome P450 family 1 subfamily A member 1 (CYP1A1) is a crucial regulator of Treg cell suppressive capability and stability. CYP1A1-deficient human Treg cells developed a Th17-like phenotype after IL-6 stimulation. Our findings implicate CYP1A1 as a previously unidentified regulator of Treg cells that may have target potential for clinical application for biotherapies.

Comprehensive analysis of prognostic alternative splicing signature in cervical cancer

Background

Alternative splicing (AS) is a key factor in protein-coding gene diversity, and is associated with the development and progression of malignant tumours. However, the role of AS in cervical cancer is unclear.

Methods

The AS data for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq website. Few prognostic AS events were identified through univariate Cox analysis. We further identified the prognostic prediction models of the seven subtypes of AS events and assessed their predictive power. We constructed a clinical prediction model through global analysis of prognostic AS events and established a nomogram using the risk score calculated from the prognostic model and relevant clinical information. Unsupervised cluster analysis was used to explore the relationship between prognostic AS events in the model and clinical features.

Results

A total of 2860 prognostic AS events in cervical cancer were identified. The best predictive effect was shown by a single alternate acceptor subtype with an area under the curve of 0.96. Our clinical prognostic model included a nine-AS event signature, and the c-index of the predicted nomogram model was 0.764. SNRPA and CCDC12 were hub genes for prognosis-associated splicing factors. Unsupervised cluster analysis through the nine prognostic AS events revealed three clusters with different survival patterns.

Conclusions

AS events affect the prognosis and biological progression of cervical cancer. The identified prognostic AS events and splicing regulatory networks can increase our understanding of the underlying mechanisms of cervical cancer, providing new therapeutic strategies.

Microfluidics in Single-Cell Virology: Technologies and Applications

Microfluidics has proven to be a powerful tool for probing biology at the single-cell level. However, it is only in the past 5 years that single-cell microfluidics has been used in the field of virology. An array of strategies based on microwells, microvalves, and droplets is now available for tracking viral infection dynamics, identifying cell subpopulations with particular phenotypes, as well as high-throughput screening. The insights into the virus-host interactions gained at the single-cell level are unprecedented and usually inaccessible by population-based experiments. Therefore, single-cell microfluidics, which opens new avenues for mechanism elucidation and development of antiviral therapeutics, would be a valuable tool for the study of viral pathogenesis.

Technological advances and computational approaches for alternative splicing analysis in single cells

Alternative splicing of RNAs generates isoform diversity, resulting in different proteins that are necessary for maintaining cellular function and identity. The discovery of alternative splicing has been revolutionized by next-generation transcriptomic sequencing mainly using bulk RNA-sequencing, which has unravelled RNA splicing and mis-splicing of normal cells under steady-state and stress conditions. Single-cell RNA-sequencing studies have focused on gene-level expression analysis and revealed gene expression signatures distinguishable between different cellular types. Single-cell alternative splicing is an emerging area of research with the promise to reveal transcriptomic dynamics invisible to bulk- and gene-level analysis. In this review, we will discuss the technological advances for single-cell alternative splicing analysis, computational strategies for isoform detection and quantitation in single cells, and current applications of single-cell alternative splicing analysis and its potential future contributions to personalized medicine.

scRNA-seq assessment of the human lung, spleen, and esophagus tissue stability after cold preservation

BACKGROUND

The Human Cell Atlas is a large international collaborative effort to map all cell types of the human body. Single-cell RNA sequencing can generate high-quality data for the delivery of such an atlas. However, delays between fresh sample collection and processing may lead to poor data and difficulties in experimental design.

RESULTS

This study assesses the effect of cold storage on fresh healthy spleen, esophagus, and lung from ≥ 5 donors over 72 h. We collect 240,000 high-quality single-cell transcriptomes with detailed cell type annotations and whole genome sequences of donors, enabling future eQTL studies. Our data provide a valuable resource for the study of these 3 organs and will allow cross-organ comparison of cell types. We see little effect of cold ischemic time on cell yield, total number of reads per cell, and other quality control metrics in any of the tissues within the first 24 h. However, we observe a decrease in the proportions of lung T cells at 72 h, higher percentage of mitochondrial reads, and increased contamination by background ambient RNA reads in the 72-h samples in the spleen, which is cell type specific.

CONCLUSIONS

In conclusion, we present robust protocols for tissue preservation for up to 24 h prior to scRNA-seq analysis. This greatly facilitates the logistics of sample collection for Human Cell Atlas or clinical studies since it increases the time frames for sample processing.

Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing

Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.

Dissecting CLL through high-dimensional single-cell technologies

We now have the potential to undertake detailed analysis of the inner workings of thousands of cancer cells, one cell at a time, through the emergence of a range of techniques that probe the genome, transcriptome, and proteome combined with the development of bioinformatics pipelines that enable their interpretation. This provides an unprecedented opportunity to better understand the heterogeneity of chronic lymphocytic leukemia and how mutations, activation states, and protein expression at the single-cell level have an impact on disease course, response to treatment, and outcomes. Herein, we review the emerging application of these new techniques to chronic lymphocytic leukemia and examine the insights already attained through this transformative technology.

Single-cell RNA-seq reveals dynamic transcriptome profiling in human early neural differentiation

Background

Investigating cell fate decision and subpopulation specification in the context of the neural lineage is fundamental to understanding neurogenesis and neurodegenerative diseases. The differentiation process of neural-tube-like rosettes in vitro is representative of neural tube structures, which are composed of radially organized, columnar epithelial cells and give rise to functional neural cells. However, the underlying regulatory network of cell fate commitment during early neural differentiation remains elusive.

Results

In this study, we investigated the genome-wide transcriptome profile of single cells from six consecutive reprogramming and neural differentiation time points and identified cellular subpopulations present at each differentiation stage. Based on the inferred reconstructed trajectory and the characteristics of subpopulations contributing the most toward commitment to the central nervous system lineage at each stage during differentiation, we identified putative novel transcription factors in regulating neural differentiation. In addition, we dissected the dynamics of chromatin accessibility at the neural differentiation stages and revealed active cis-regulatory elements for transcription factors known to have a key role in neural differentiation as well as for those that we suggest are also involved. Further, communication network analysis demonstrated that cellular interactions most frequently occurred in the embryoid body stage and that each cell subpopulation possessed a distinctive spectrum of ligands and receptors associated with neural differentiation that could reflect the identity of each subpopulation.

Conclusions

Our study provides a comprehensive and integrative study of the transcriptomics and epigenetics of human early neural differentiation, which paves the way for a deeper understanding of the regulatory mechanisms driving the differentiation of the neural lineage.

Cytometry meets next-generation sequencing - RNA-Seq of sorted subpopulations reveals regional replication and iron-triggered prophage induction in Corynebacterium glutamicum

Phenotypic diversification is key to microbial adaptation. Currently, advanced technological approaches offer insights into cell-to-cell variation of bacterial populations at a spatiotemporal resolution. However, the underlying molecular causes or consequences often remain obscure. In this study, we developed a workflow combining fluorescence-activated cell sorting and RNA-sequencing, thereby allowing transcriptomic analysis of 106 bacterial cells. As a proof of concept, the workflow was applied to study prophage induction in a subpopulation of Corynebacterium glutamicum. Remarkably, both the phage genes and flanking genomic regions of the CGP3 prophage revealed significantly increased coverage upon prophage induction - a phenomenon that to date has been obscured by bulk approaches. Genome sequencing of prophage-induced populations suggested regional replication at the CGP3 locus in C. glutamicum. Finally, the workflow was applied to unravel iron-triggered prophage induction in early exponential cultures. Here, an up-shift in iron levels resulted in a heterogeneous response of an SOS (PdivS) reporter. RNA-sequencing of the induced subpopulation confirmed induction of the SOS response triggering also activation of the CGP3 prophage. The fraction of CGP3-induced cells was enhanced in a mutant lacking the iron regulator DtxR suffering from enhanced iron uptake. Altogether, these findings demonstrate the potential of the established workflow to gain insights into the phenotypic dynamics of bacterial populations.

The Human Cell Atlas: Technical approaches and challenges

The Human Cell Atlas is a large, international consortium that aims to identify and describe every cell type in the human body. The comprehensive cellular maps that arise from this ambitious effort have the potential to transform many aspects of fundamental biology and clinical practice. Here, we discuss the technical approaches that could be used today to generate such a resource and also the technical challenges that will be encountered.

Tumour virology in the era of high-throughput genomics

With the advent of massively parallel sequencing, oncogenic viruses in tumours can now be detected in an unbiased and comprehensive manner. Additionally, new viruses or strains can be discovered based on sequence similarity with known viruses. Using this approach, the causative agent for Merkel cell carcinoma was identified. Subsequent studies using data from large collections of tumours have confirmed models built during decades of hypothesis-driven and low-throughput research, and a more detailed and comprehensive description of virus-tumour associations have emerged. Notably, large cohorts and high sequencing depth, in combination with newly developed bioinformatical techniques, have made it possible to rule out several suggested virus-tumour associations with a high degree of confidence. In this review we discuss possibilities, limitations and insights gained from using massively parallel sequencing to characterize tumours with viral content, with emphasis on detection of viral sequences and genomic integration events.This article is part of the themed issue 'Human oncogenic viruses'.

Human papillomavirus genome integration in squamous carcinogenesis: what have next-generation sequencing studies taught us?

Human papillomavirus (HPV) infection is associated with ∼5% of all human cancers, including a range of squamous cell carcinomas. Persistent infection by high-risk HPVs (HRHPVs) is associated with the integration of virus genomes (which are usually stably maintained as extrachromosomal episomes) into host chromosomes. Although HRHPV integration rates differ across human sites of infection, this process appears to be an important event in HPV-associated neoplastic progression, leading to deregulation of virus oncogene expression, host gene expression modulation, and further genomic instability. However, the mechanisms by which HRHPV integration occur and by which the subsequent gene expression changes take place are incompletely understood. The advent of next-generation sequencing (NGS) of both RNA and DNA has allowed powerful interrogation of the association of HRHPVs with human disease, including precise determination of the sites of integration and the genomic rearrangements at integration loci. In turn, these data have indicated that integration occurs through two main mechanisms: looping integration and direct insertion. Improved understanding of integration sites is allowing further investigation of the factors that provide a competitive advantage to some integrants during disease progression. Furthermore, advanced approaches to the generation of genome-wide samples have given novel insights into the three-dimensional interactions within the nucleus, which could act as another layer of epigenetic control of both virus and host transcription. It is hoped that further advances in NGS techniques and analysis will not only allow the examination of further unanswered questions regarding HPV infection, but also direct new approaches to treating HPV-associated human disease. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Single-cell RNA-seq reveals hidden transcriptional variation in malaria parasites

Single-cell RNA-sequencing is revolutionising our understanding of seemingly homogeneous cell populations but has not yet been widely applied to single-celled organisms. Transcriptional variation in unicellular malaria parasites from the Plasmodium genus is associated with critical phenotypes including red blood cell invasion and immune evasion, yet transcriptional variation at an individual parasite level has not been examined in depth. Here, we describe the adaptation of a single-cell RNA-sequencing (scRNA-seq) protocol to deconvolute transcriptional variation for more than 500 individual parasites of both rodent and human malaria comprising asexual and sexual life-cycle stages. We uncover previously hidden discrete transcriptional signatures during the pathogenic part of the life cycle, suggesting that expression over development is not as continuous as commonly thought. In transmission stages, we find novel, sex-specific roles for differential expression of contingency gene families that are usually associated with immune evasion and pathogenesis.

The use of single-cell RNA-Seq to understand virus-host interactions

Single-cell analyses allow uncovering cellular heterogeneity, not only per se, but also in response to viral infection. Similarly, single cell transcriptome analyses (scRNA-Seq) can highlight specific signatures, identifying cell subsets with particular phenotypes, which are relevant in the understanding of virus-host interactions.

High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications

Single cell sequencing (SCS) can be harnessed to acquire the genomes, transcriptomes and epigenomes from individual cells. Next generation sequencing (NGS) technology is the driving force for single cell sequencing. scRNA-seq requires a lengthy pipeline comprising of single cell sorting, RNA extraction, reverse transcription, amplification, library construction, sequencing and subsequent bioinformatic analysis. Computational algorithms are essential to fulfill many tasks of interest using scRNA-seq data. scRNA-seq has already enabled researchers to revisit long-standing questions in cancer biology, including cancer metastasis, heterogeneity and evolution. Circulating Tumor Cells (CTC) are not only an important mechanism for cancer metastasis, but also provide a possibility to diagnose and monitor cancer in a convenient way independent of surgical resection of the cancer.

ZIKV infection effects changes in gene splicing, isoform composition and lncRNA expression in human neural progenitor cells

BACKGROUND

The Zika virus (ZIKV) is a mosquito-borne flavivirus that causes microcephaly and Guillain-Barré syndrome in infected individuals. To obtain insights into the mechanism of ZIKV infection and pathogenesis, we analyzed the transcriptome of ZIKV infected human neural progenitor cells (hNPCs) for changes in alternative splicing (AS), gene isoform (ISO) composition and long noncoding RNAs (lncRNAs) expression.

METHODS

We analyzed differentially expressed lncRNAs, AS, ISO from RNA-seq data in ZIKV infected hNPCs.

RESULTS

We obtained 149 differentially expressed lncRNAs, including potential viral targets to modulate cellular processes such as cell cycle, apoptosis and immune response. The infection induced 262 cases of AS occurring in 229 genes, which were enriched in cell death, RNA processing, transport, and neuron development. Among 691 differentially expressed ISOs, upregulated ISOs were enriched in signaling, regulation of transcription, and amino acid biosynthesis, while downregulated ISOs were mostly enriched in cell cycle. Importantly, these analyses revealed specific links between ZIKV induced changes in cellular pathways and the type of changes in the host transcriptome, suggesting important regulatory mechanisms.

CONCLUSIONS

Our analyses revealed candidate lncRNAs, AS events and ISOs which may function in ZIKV infection induced cell cycle disruption, apoptosis and attenuation of neurogenesis, and shed light on the roles of lncRNAs, AS and ISOs in virus-host interactions, and would facilitate future studies of ZIKV infection and pathogenesis.

The proto-oncogene tyrosine protein kinase Src is essential for macrophage-myofibroblast transition during renal scarring

Src activation has been associated with fibrogenesis after kidney injury. Macrophage-myofibroblast transition is a newly identified process to generate collagen-producing myofibroblasts locally in the kidney undergoing fibrosis in a TGF-β/Smad3-dependent manner. The potential role of the macrophage-myofibroblast transition in Src-mediated renal fibrosis is unknown. In studying this by RNA sequencing at single-cell resolution, we uncovered a unique Src-centric regulatory gene network as a key underlying mechanism of macrophage-myofibroblast transition. A total of 501 differentially expressed genes associated with macrophage-myofibroblast transition were identified. However, Smad3-knockout largely reduced the transcriptome diversity. More importantly, inhibition of Src largely suppresses ureteral obstruction-induced macrophage-myofibroblast transition in the injured kidney in vivo along with transforming growth factor-β1-induced elongated fibroblast-like morphology, α-smooth muscle actin expression and collagen production in bone marrow derived macrophages in vitro. Unexpectedly, we further uncovered that Src serves as a direct Smad3 target gene and also specifically up-regulated in macrophages during macrophage-myofibroblast transition. Thus, macrophage-myofibroblast transition contributes to Src-mediated tissue fibrosis. Hence, targeting Src may represent as a precision therapeutic strategy for macrophage-myofibroblast transition-driven fibrotic diseases.

The determinants of alternative RNA splicing in human cells

Alternative splicing represents an important level of the regulation of gene function in eukaryotic organisms. It plays a critical role in virtually every biological process within an organism, including regulation of cell division and cell death, differentiation of tissues in the embryo and the adult organism, as well as in cellular response to diverse environmental factors. In turn, studies of the last decade have shown that alternative splicing itself is controlled by different mechanisms. Unfortunately, there is no clear understanding of how these diverse mechanisms, or determinants, regulate and constrain the set of alternative RNA species produced from any particular gene in every cell of the human body. Here, we provide a consolidated overview of alternative splicing determinants including RNA-protein interactions, epigenetic regulation via chromatin remodeling, coupling of transcription-to-alternative splicing, effect of secondary structures in pre-RNA, and function of the RNA quality control systems. We also extensively and critically discuss some mechanistic insights on coordinated inclusion/exclusion of exons during the formation of mature RNA molecules. We conclude that the final structure of RNA is pre-determined by a complex interplay between cis- and trans-acting factors. Altogether, currently available empirical data significantly expand our understanding of the functioning of the alternative splicing machinery of cells in normal and pathological conditions. On the other hand, there are still many blind spots that require further deep investigations.

Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines

The relationship between human cytomegalovirus (HCMV) and glioblastoma (GBM) is an ongoing debate with extensive evidence supporting or refuting its existence through molecular assays, pre-clinical studies, and clinical trials. We focus primarily on the crux of the debate, detection of HCMV in GBM samples using molecular assays. We propose that these differences in detection could be affected by cellular heterogeneity. To take this into account, we align the single-cell RNA sequencing (scRNA-seq) reads from five GBM tumors and two cell lines to HCMV and analyze the alignments for evidence of (i) complete viral transcripts and (ii) low-abundance viral reads. We found that neither tumor nor cell line samples showed conclusive evidence of full HCMV viral transcripts. We also identified low-abundance reads aligned across all tumors, with two tumors having higher alignment rates than the rest of the tumor samples. This work is meant to rigorously test for HCMV RNA expression at a single cell level in GBM samples and examine the possible utility of single cell data in tumor virology.

Evolution of multiple cell clones over a 29-year period of a CLL patient

Chronic lymphocytic leukaemia (CLL) is a frequent B-cell malignancy, characterized by recurrent somatic chromosome alterations and a low level of point mutations. Here we present single-nucleotide polymorphism microarray analyses of a single CLL patient over 29 years of observation and treatment, and transcriptome and whole-genome sequencing at selected time points. We identify chromosome alterations 13q14-, 6q- and 12q+ in early cell clones, elimination of clonal populations following therapy, and subsequent appearance of a clone containing trisomy 12 and chromosome 10 copy-neutral loss of heterogeneity that marks a major population dominant at death. Serial single-cell RNA sequencing reveals an expression pattern with high FOS, JUN and KLF4 at disease acceleration, which resolves following therapy, but reoccurs following relapse and death. Transcriptome evolution indicates complex changes in expression occur over time. In conclusion, CLL can evolve gradually during indolent phases, and undergo rapid changes following therapy.

Exploring viral infection using single-cell sequencing

Single-cell sequencing (SCS) has emerged as a valuable tool to study cellular heterogeneity in diverse fields, including virology. By studying the viral and cellular genome and/or transcriptome, the dynamics of viral infection can be investigated at single cell level. Most studies have explored the impact of cell-to-cell variation on the viral life cycle from the point of view of the virus, by analyzing viral sequences, and from the point of view of the cell, mainly by analyzing the cellular host transcriptome. In this review, we will focus on recent studies that use single-cell sequencing to explore viral diversity and cell variability in response to viral replication.

Single-cell analyses of transcriptional heterogeneity in squamous cell carcinoma of urinary bladder

Cell-to-cell expression heterogeneity within a single tumor is a common phenotype among various cancer types including squamous cell carcinoma. To further study the fundamentals and importance of heterogeneity of cell functions and its potential mechanisms, we performed single-cell RNA-seq (scRNA-seq) on human squamous cell carcinoma of the bladder (SCCB) and its corresponding physiologically normal epithelia. Extensive differentially expressed genes were uncovered by comparing cancer and normal single cells, which were preferentially enriched in cancer-correlated pathways, such as p53 signaling and bladder cancer pathway. Furthermore, the most diversely expressed genes were particularly enriched in MAPK signaling pathway, such as CACNG4, CACNA1E and CACNA1H, which involve in cancer evolution and heterogeneity formation. Co-expression network and hub-gene analyses revealed several remarkable "hub genes" of each regulatory module. Some of them are cancer related, such as POU2F3, NKD1 and CYP2C8, while LINC00189, GCC2 and OR9Q1 genes are rarely reported in human diseases. The genes within an interesting module are highly correlated with others, which could be treated as potential targets for SCCB patients. Our findings have fundamental implications for SCCB biology and therapeutic strategies.

Single-Cell Genomics for Virology

Single-cell sequencing technologies, i.e., single cell analysis followed by deep sequencing investigate cellular heterogeneity in many biological settings. It was only in the past year that single-cell sequencing analyses has been applied in the field of virology, providing new ways to explore viral diversity and cell response to viral infection, which are summarized in the present review.

Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells

Background

Viral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line.

Result

We developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins.

Conclusion

Our results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s13742-015-0091-4) contains supplementary material, which is available to authorized users.