ABSTRACT
Osteosarcoma (OSA) is a highly aggressive bone tumor primarily affecting pediatric or adolescent humans and large-breed dogs. Canine OSA shares striking similarities with its human counterpart, making it an invaluable translational model for uncovering the disease's complexities and developing novel therapeutic strategies. Tumor heterogeneity, a hallmark of OSA, poses significant challenges to effective treatment due to the evolution of diverse cell populations that influence tumor growth, metastasis, and resistance to therapies. In this study, we apply single-nuclei multiome sequencing, encompassing ATAC (Assay for Transposase-Accessible Chromatin) and GEX (Gene Expression, or RNA) sequencing, to a treatment-naïve primary canine osteosarcoma. This comprehensive approach reveals the complexity of the tumor microenvironment by simultaneously capturing the transcriptomic and epigenomic profiles within the same nucleus. Furthermore, these results are analyzed in conjunction with bulk RNA sequencing and differential analysis of the same tumor and patient-matched normal bone. By delving into the intricacies of OSA at this unprecedented level of detail, we aim to unravel the underlying mechanisms driving intra-tumoral heterogeneity, opening new avenues for therapeutic interventions in both human and canine patients. This study pioneers an approach that is broadly applicable, while demonstrating significant heterogeneity in the context of a single individual's tumor.
Subject(s)
Bone Neoplasms , Dog Diseases , Osteosarcoma , Animals , Dogs , Bone Neoplasms/genetics , Bone Neoplasms/veterinary , Bone Neoplasms/drug therapy , Dog Diseases/metabolism , Gene Expression , Osteosarcoma/genetics , Osteosarcoma/veterinary , Osteosarcoma/metabolism , RNA , Tumor Microenvironment/geneticsABSTRACT
The molecular mechanisms controlling the transition from meiotic arrest to meiotic resumption in mammalian oocytes have not been fully elucidated. Single-cell omics technology provides a new opportunity to decipher the early molecular events of oocyte growth in mammals. Here we focused on analyzing oocytes that were collected from antral follicles in different diameters of porcine pubertal ovaries, and used single-cell M&T-seq technology to analyze the nuclear DNA methylome and cytoplasmic transcriptome in parallel for 62 oocytes. 10× Genomics single-cell transcriptomic analyses were also performed to explore the bi-directional cell-cell communications within antral follicles. A new pipeline, methyConcerto, was developed to specifically and comprehensively characterize the methylation profile and allele-specific methylation events for a single-cell methylome. We characterized the gene expressions and DNA methylations of individual oocyte in porcine antral follicle, and both active and inactive gene's bodies displayed high methylation levels, thereby enabled defining two distinct types of oocytes. Although the methylation levels of Type II were higher than that of Type I, Type II contained nearly two times more of cytoplasmic transcripts than Type I. Moreover, the imprinting methylation patterns of Type II were more dramatically divergent than Type I, and the gene expressions and DNA methylations of Type II were more similar with that of MII oocytes. The crosstalk between granulosa cells and Type II oocytes was active, and these observations revealed that Type II was more poised for maturation. We further confirmed Insulin Receptor Substrate-1 in insulin signaling pathway is a key regulator on maturation by in vitro maturation experiments. Our study provides new insights into the regulatory mechanisms between meiotic arrest and meiotic resumption in mammalian oocytes. We also provide a new analytical package for future single-cell methylomics study.
Subject(s)
Multiomics , Oocytes , Female , Swine , Animals , Ovarian Follicle , Cell Nucleus , Cell Cycle , MammalsABSTRACT
The pineal gland presents a powerful genetic tool to study a broad range of physiological processes. It has been instrumental as a model in understanding transduction processes and daily changes in gene expression and holds great promise in understanding development. Currently, the field is at an exciting point, with methods available for the isolation of individual cells and, as presented here, the preparation of these single cells for sequencing. The resulting cellular transcriptomes have played a role in categorizing cells in the pineal gland, with current estimates including two types of pinealocytes, three types of astrocytes, two types of microglia, and two types of endothelial cells, including the poorly understood vascular and meningeal cell. The methods described in this chapter will serve to support and advance cellular studies of the pineal gland in the twenty-first century.
Subject(s)
Pineal Gland , Astrocytes/metabolism , Endothelial Cells , Microglia/metabolism , Pineal Gland/metabolism , Sequence Analysis, RNAABSTRACT
Single-cell RNA sequencing (scRNA-seq) is emerging as an essential technique for studying the physiology of individual cells in populations. Although well-established and optimized for mammalian cells, research of microorganisms has been faced with major technical challenges for using scRNA-seq, because of their rigid cell wall, smaller cell size and overall lower total RNA content per cell. Here, we describe an easy-to-implement adaptation of the protocol for the yeast Saccharomyces cerevisiae using the 10× Genomics platform, originally optimized for mammalian cells. Introducing Zymolyase, a cell wall-digesting enzyme, to one of the initial steps of single-cell droplet formation allows efficient in-droplet lysis of yeast cells, without affecting the droplet emulsion and further sample processing. In addition, we also describe the downstream data analysis, which combines established scRNA-seq analysis protocols with specific adaptations for yeast, and R-scripts for further secondary analysis of the data.
Subject(s)
Saccharomyces cerevisiae , Single-Cell Analysis , Animals , Chromium , Gene Expression Profiling/methods , Genomics , Mammals/genetics , RNA/genetics , RNA-Seq , Saccharomyces cerevisiae/genetics , Sequence Analysis, RNA/methods , Single-Cell Analysis/methodsABSTRACT
Recent advances in multimodal approaches toward single-cell analyses present valuable data points that can complement standard flow cytometry data. In particular, the overlay of cell-surface proteome data with gene expression analysis presents a necessary advancement, particularly in the field of immunology. Here we describe a copper-free click chemistry method for the generation of antibody-oligonucleotide complexes and present the steps for its employment in the context of the 10× genomics droplet-based single-cell RNA-seq workflow, providing a method for coupling proteomic and transcriptomic analyses in an efficient and cost-effect manner.
Subject(s)
Oligonucleotides , Proteomics , Antibodies , Click Chemistry/methods , Oligonucleotides/genetics , RNA-SeqABSTRACT
Single cell RNA sequencing (scRNA-seq) allows to uncover cellular heterogeneity and the identification of novel subpopulations. In non-alcoholic steatohepatitis (NASH), scRNA-seq is particularly powerful to understand non-parenchymal cell heterogeneity in the liver, e.g. for inflammatory cells. Myeloid immune cells, particularly macrophages, play a critical role in response of the innate immune system and significantly contribute to the progression of fatty liver disease. Due to their high heterogeneity and complex phenotypes, their functional role in health and disease is difficult to analyze. Here, we describe the isolation and analysis of myeloid cell populations from mouse liver using microdroplet-based scRNA-seq. This approach allows the identification and characterization of different hepatic cell types, exemplified here by hepatic macrophage populations, as well as analyses of differentially expressed genes between samples (e.g., cells from healthy or NASH livers).
Subject(s)
Non-alcoholic Fatty Liver Disease , Animals , Kupffer Cells/metabolism , Liver/metabolism , Macrophages/metabolism , Mice , Non-alcoholic Fatty Liver Disease/genetics , Non-alcoholic Fatty Liver Disease/metabolism , Sequence Analysis, RNAABSTRACT
The supraneural body, also known as dorsal fat body is considered from adipose progenitors, and possesses hematopoietic activity. However, in-depth knowledge of cell-type by single-cell transcriptome sequencing and physiological functions are still lacking. Here, we determined at least four types of cells, such as white adipocytes, granulocytes, lymphocytes, and red blood cells by using 10 ×Genomics single-cell RNA sequencing (scRNA-Seq), hematoxylin-eosin (HE) staining, electron microscopy, immunofluorescence, and histochemistry. Additionally, most immune cells contain scattered small fat droplets except for white adipocytes with one large lipid droplet. The content of triglyceride in supraneural body is the highest compared with other tissues. The mRNA expression of both lipolysis-related genes and brown adipocytes-specific marker genes were up-regulated in supraneural body cells in response to epinephrine. Taken together, these data indicate that the supraneural body may play an important role in immune and fat storage. Our findings not only provided detailed insights into the unique molecular make-up of the supraneural body tissue, but also shed new light on future analyses of physiological functions in immune or lipid regulating.
Subject(s)
Single-Cell AnalysisABSTRACT
Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.
Subject(s)
Organ Transplantation/instrumentation , Sequence Analysis, RNA/methods , Single-Cell Analysis/methods , Gene Expression Profiling/methods , Humans , Organ Transplantation/methods , Sequence Analysis, RNA/instrumentation , Single-Cell Analysis/instrumentationABSTRACT
The stroma constitutes the structural framework of an organ and plays crucial roles in health and following organ damage. The major player of the stroma with respect to extracellular matrix deposition, maintenance, and remodeling is the fibroblast and its activated derivative, the myofibroblast. It has long been recognized that there is considerable variability to the fibroblast phenotype. The recent advent of new single cell "omics" technologies has revolutionized our understanding and appreciation of cellular heterogeneity of fibroblasts been revolutionized. With these tools, the nature and defining characteristics of the cells comprising the stroma is finally being defined not just through a few markers, but by taking a wholistic look at transcriptional programs. It is now apparent that stromal cells are not only transcriptionally diverse, but also functionally, epigenetically, and spatially heterogeneous. Studying populations at single cell resolution has enabled identification of new clusters of cells with unique transcriptional signatures. Whether these clusters truly represent distinct subpopulations or different states of the same population remains to be clarified. In this chapter, we first describe a procedure for purification and preparation of a single cell suspension from tissue samples (in this case the heart) for single cell RNA sequencing. We also describe preparation of high-quality tissue sections for spatial transcriptomics. Secondly, we outline a workflow for computational analysis of single cell RNA sequencing and spatial transcriptomics data, as well as integrating them together, to explore the heterogeneity within fibroblasts/myofibroblasts and identify different subtypes and their locations in the heart.
Subject(s)
Gene Expression Profiling/methods , Gene Regulatory Networks , Myofibroblasts/cytology , Single-Cell Analysis/methods , Animals , Cell Differentiation , Cells, Cultured , Computational Biology , Extracellular Matrix/metabolism , Fibroblasts/chemistry , Fibroblasts/cytology , Mice , Myofibroblasts/chemistry , Sequence Analysis, RNA , WorkflowABSTRACT
Centella asiatica is a herbaceous, perennial species indigenous to India and Southeast Asia. C. asiatica possesses several medicinal properties: anti-aging, anti-inflammatory, wound healing and memory enhancing. The lack of available genomics resources significantly impedes the improvement of C. asiatica varieties through molecular breeding. Here, we combined the 10× Genomics linked-read technology and the long-range HiC technique to obtain the genome assembly. The final assembly contained nine pseudomolecules, corresponding to the haploid chromosome number in C. asiatica. These nine chromosomes covered 402,536,584 bases or 93.6% of the 430-Mb assembly. Comparative genomics analyses based on single-copy orthologous genes showed that C. asiatica and the common ancestor of Coriandrum sativum (coriander) and Daucus carota (carrot) diverged about 48 million years ago. This assembly provides a valuable reference genome for future molecular studies, varietal development through marker-assisted breeding and comparative genomics studies in C. asiatica.
Subject(s)
Centella , Centella/genetics , Chromosomes , Genome , Genomics/methods , Plant BreedingABSTRACT
Drosophila provides a powerful genetic system and an excellent model to study the development and function of the nervous system. The fly's small brain and complex behavior has been instrumental in mapping neuronal circuits and elucidating the neural basis of behavior. The fast pace of fly development and the wealth of genetic tools has enabled systematic studies on cell differentiation and fate specification, and has uncovered strategies for axon guidance and targeting. The accessibility of neuronal structures and the ability to edit and manipulate gene expression in selective cells and/or synaptic compartments has revealed mechanisms for synapse assembly and neuronal connectivity. Recent advances in single-cell RNA sequencing (scRNA-seq) have further enhanced our appreciation and understanding of neuronal diversity in a fly brain. However, due to the small size of the fly brain and its constituent cells, scRNA-seq methodologies require a few adaptations. Here, we describe a set of protocols optimized for scRNA-seq analysis of the Drosophila larval ventral nerve cord, starting from tissue dissection and cell dissociation to cDNA library preparation, sequencing, and data analysis. We apply this workflow to three separate samples and detail the technical challenges associated with successful application of scRNA-seq to studies on neuronal diversity. An accompanying article (Vicidomini, Nguyen, Choudhury, Brody, & Serpe, 2021) presents a custom multistage analysis pipeline that integrates modules contained in different R packages to ensure high-flexibility, high-quality RNA-seq data analysis. These protocols are developed for Drosophila larval ventral nerve cord, but could easily be adapted to other tissues and model organisms. © 2021 U.S. Government. Basic Protocol 1: Dissection of larval ventral nerve cords and preparation of single-cell suspensions Basic Protocol 2: Preparation and sequencing of single-cell transcriptome libraries Basic Protocol 3: Alignment of raw sequencing data to indexed genome and generation of count matrices.
Subject(s)
Drosophila , Single-Cell Analysis , Animals , Drosophila/genetics , Larva/genetics , Sequence Analysis, RNA , SoftwareABSTRACT
Next generation sequencing (NGS) has changed our approach to diagnosis of genetic disorders. Nowadays, the most comprehensive application of NGS is whole genome sequencing (WGS) that is able to detect virtually all DNA variations. However, even after accurate WGS, many genetic conditions remain unsolved. This may be due to the current NGS protocols, based on DNA fragmentation and short reads. To overcome these limitations, we applied a linked-read sequencing technology that combines single-molecule barcoding with short-read WGS. We were able to assemble haplotypes and distinguish between alleles along the genome. As an exemplary case, we studied the case of a female carrier of X-linked muscular dystrophy with an unsolved genetic status. A deletion of exons 16-29 in DMD gene was responsible for the disease in her family, but she showed a normal dosage of these exons by Multiplex Ligation-dependent Probe Amplification (MLPA) and array CGH. This situation is usually considered compatible with a "non-carrier" status. Unexpectedly, the girl also showed an increased dosage of flanking exons 1-15 and 30-34. Using linked-read WGS, we were able to distinguish between the two X chromosomes. In the first allele, we found the 16-29 deletion, while the second allele showed a 1-34 duplication: in both cases, linked-read WGS correctly mapped the borders at single-nucleotide resolution. This duplication in trans apparently restored the normal dosage of exons 16-29 seen by quantitative assays. This had a dramatic impact in genetic counselling, by converting a non-carrier into a double carrier status prediction. We conclude that linked-read WGS should be considered as a valuable option to improve our understanding of unsolved genetic conditions.
Subject(s)
Dystrophin/genetics , Gene Rearrangement , Muscular Dystrophy, Duchenne/genetics , Whole Genome Sequencing , Child , Comparative Genomic Hybridization , Genetic Association Studies , Genetic Predisposition to Disease , Humans , Male , Mutation , Pedigree , Polymorphism, Single NucleotideABSTRACT
Single-cell RNA sequencing (scRNA-Seq) allows the complete and unbiased analysis of the transcriptional state of an individual cell. In the past 5 years, scRNA-Seq contributed to the progress of the hematology field, advancing our knowledge of both normal and malignant hematopoiesis. Different scRNA-Seq methods are available, all relying on the conversion of RNA to cDNA, followed by amplification of cDNA in order to obtain a sufficient amount of genetic material for sequencing. Currently available scRNA-Seq platforms can be broadly divided into two categories: droplet-based and plate-based. Each of these approaches has advantages and disadvantages that need to be considered when designing the experiment. Here, we describe detailed protocols of two of the most used methods for scRNA-Seq of hematopoietic cells: Smart-Seq2 (plate-based) and 10× Genomics (droplet-based).
Subject(s)
Hematopoietic Stem Cells , RNA-Seq , RNA/genetics , Single-Cell Analysis , DNA, Complementary/genetics , Humans , RNA/biosynthesisABSTRACT
Single-cell RNA-sequencing (scRNA-seq) enables a comprehensive analysis of the transcriptome of individual cells by next-generation sequencing. ScRNA-seq offers an unbiased approach to investigate the cellular heterogeneity and dynamics of diverse biological systems, including the immune system. Optimization of the technical procedures performed prior to RNA-seq analysis is imperative to the success of a scRNA-seq experiment. Here, three major experimental procedures are described: (1) the isolation of immune CD8a+ T cells from primary murine tissue, (2) the generation of single-cell cDNA libraries using the 10× Genomics Chromium Controller and the Chromium Single Cell 3' Solution, and (3) cDNA library quality control. In this protocol, CD8a+ T cells are isolated from murine spleen tissue, but any cell type of interest can be enriched and used for single-cell cDNA library generation and subsequent RNA-seq experiments.
Subject(s)
CD8-Positive T-Lymphocytes/metabolism , Gene Expression Profiling/methods , RNA, Small Cytoplasmic/genetics , RNA/genetics , Sequence Analysis, RNA/methods , Single-Cell Analysis/methods , Transcriptome/genetics , Animals , Cell Separation/methods , Cells, Cultured , Computational Biology/methods , Gene Library , Genomics/methods , High-Throughput Nucleotide Sequencing/methods , Mice , Software , Spleen/metabolismABSTRACT
The sweet cherry (Prunus avium) is one of the most economically important fruit species in the world. However, there is a limited amount of genetic information available for this species, which hinders breeding efforts at a molecular level. We were able to describe a high-quality reference genome assembly and annotation of the diploid sweet cherry (2n = 2x = 16) cv. Tieton using linked-read sequencing technology. We generated over 750 million clean reads, representing 112.63 GB of raw sequencing data. The Supernova assembler produced a more highly-ordered and continuous genome sequence than the current P. avium draft genome, with a contig N50 of 63.65 KB and a scaffold N50 of 2.48 MB. The final scaffold assembly was 280.33 MB in length, representing 82.12% of the estimated Tieton genome. Eight chromosome-scale pseudomolecules were constructed, completing a 214 MB sequence of the final scaffold assembly. De novo, homology-based, and RNA-seq methods were used together to predict 30,975 protein-coding loci. 98.39% of core eukaryotic genes and 97.43% of single copy orthologues were identified in the embryo plant, indicating the completeness of the assembly. Linked-read sequencing technology was effective in constructing a high-quality reference genome of the sweet cherry, which will benefit the molecular breeding and cultivar identification in this species.
ABSTRACT
High-throughput sequencing technologies are a proposed solution for accessing the molecular data in historical specimens. However, degraded DNA combined with the computational demands of short-read assemblies has posed significant laboratory and bioinformatics challenges for de novo genome assembly. Linked-read or "synthetic long-read" sequencing technologies, such as 10× Genomics, may provide a cost-effective alternative solution to assemble higher quality de novo genomes from degraded tissue samples. Here, we compare assembly quality (e.g., genome contiguity and completeness, presence of orthogroups) between four new deer mouse (Peromyscus spp.) genomes assembled using linked-read technology and four published genomes assembled from a single shotgun library. At a similar price-point, these approaches produce vastly different assemblies, with linked-read assemblies having overall higher contiguity and completeness, measured by larger N50 values and greater number of genes assembled, respectively. As a proof-of-concept, we used annotated genes from the four Peromyscus linked-read assemblies and eight additional rodent taxa to generate a phylogeny, which reconstructed the expected relationships among species with 100% support. Although not without caveats, our results suggest that linked-read sequencing approaches are a viable option to build de novo genomes from degraded tissues, which may prove particularly valuable for taxa that are extinct, rare or difficult to collect.
Subject(s)
Genome/genetics , Genomics/methods , High-Throughput Nucleotide Sequencing/methods , Peromyscus/genetics , Animals , Computational Biology/methods , Gene Library , Molecular Sequence Annotation/methods , Phylogeny , Sequence Analysis, DNA/methodsABSTRACT
The southern elephant seal Mirounga leonina is the largest phocid seal and one of the two species of elephant seals. They are listed as 'least concern' by the International Union for Conservation of Nature (IUCN) Red List of Threatened Species 2015. Here, we have assembled the reference genome for M. leonina using the 10× chromium sequencing platform. The final genome assembly of M. leonina was 2.42 Gb long, with a contig N50 length of 54 Mb and a maximum length of 111.6 Mb. The M. leonina genome contained 20,457 predicted protein-coding genes and possessed 41.51% repeated sequences. The completeness of the M. leonina genome was evaluated using benchmarking universal single-copy orthologous genes (BUSCOs): the assembly was highly complete, containing 95.6% of the core set of mammalian genes. The high-quality genomic information on M. leonina will be essential for further understanding of adaptive metabolism upon repeated breath-hold dives and the exploration of molecular mechanisms contributing to its unique biochemical and physiological characteristics. The southern elephant seal genome project was deposited at NCBI (National Center for Biotechnology Information) under BioProject number PRJNA587380.
Subject(s)
Gene Expression Regulation , Genetics, Population , Genome , Molecular Sequence Annotation , Seals, Earless/genetics , Animals , Gene Ontology , Genomics , Seals, Earless/classification , Whole Genome SequencingABSTRACT
Single-cell transcriptomic analysis has become a new and powerful tool to study complex multicellular systems. Single-cell RNA sequencing provides an unbiased classification of heterogeneous cellular states at the transcriptional level, but it does not always correlate to cell-surface protein expression. A recently developed method called cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) simultaneously measures surface proteins and gene expression from single cells. Briefly, based on the existing single-cell sequencing technology, oligonucleotide-labeled antibodies and barcoded primer gel beads are used to bind to corresponding cell-surface proteins and mRNA, respectively. Further, libraries of labeled protein and RNA information are sequenced to integrate cellular protein and transcriptome reads together efficiently. CITE-seq is transforming comprehensive genomic studies into models of causal gene-protein investigation.
Subject(s)
Gene Expression Profiling/methods , Membrane Proteins/analysis , Single-Cell Analysis/methods , Epitopes/analysis , Gene Library , High-Throughput Nucleotide Sequencing , Humans , Membrane Proteins/genetics , Sequence Analysis, RNAABSTRACT
RNA sequencing has proven to be a key innovation for the study of biological processes by enabling scientists to measure differences in gene expression in different tissues.With recent advances in sequencing technology, researchers are able to measure gene transcription at the single-cell level, revealing previously unknown diversity and specificity of immune cells. The single-cell sequencing method now enables profiling of the T-cell receptor (TCR) genes resulting from V(D)J recombination.Here we describe how to adapt single-cell RNA sequencing data generated using the 10× genomics 5'V(D)J immune cell profiling workflow for integration into the R analysis pipeline.We will start with the data matrix files generated from the 10× genomics Cell Ranger alignment software and detail how to format this data as input for the R analysis package called Seurat such that data from both the overall cell transcript abundance and the targeted V(D)J transcript abundance data can be visualized on the same plots.
Subject(s)
Computational Biology/methods , Gene Expression Profiling/methods , Receptors, Antigen, T-Cell/genetics , Single-Cell Analysis/methods , High-Throughput Nucleotide Sequencing , Humans , Sequence Analysis, RNA , Software , V(D)J Recombination , WorkflowABSTRACT
Single-cell sequencing experiments are a new mainstay in biology and have been advancing science especially in the biomedical field. The high pressure to integrate the technology into daily laboratory live requires solid knowledge with respect to potential limitations and precautions to be taken care of before applying it to complex research questions. In the past, we have identified two issues with quality measures neglected by the growing community involving SmartSeq and droplet or micro-well-based scRNASeq methods (1) how to ensure that only single cells are introduced without biasing on light scattering when handling complex cell mixtures and organ preparations or (2) how best to control for (pro-)apoptotic cell contaminations in single-cell sequencing approaches. Sighting of concurrent literature involving single-cell sequencing technologies revealed that these topics are generally neglected or simply approached in silico but not at the bench before generating single-cell data sets. We fear that those important quality aspects are overlooked due to reduced awareness of their importance for guaranteeing the quality of experiments. In this Cytometry rigor issue, we provide experimentally supported guidance on how to circumvent those critical shortcomings in order to promote a better use of the fantastic single-cell sequencing toolbox in biology. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.