Drop-seq

Single cell RNA sequencing has become an important method to identify cell types, delineate the trajectories of cell differentiation in whole organisms and understand the heterogeneity in cellular responses. Nevertheless, sample collection and processing remain a severe bottleneck for single cell RNA sequencing experiments. Cell isolation protocols often lead to significant changes in the transcriptomes of cells, requiring novel methods to preserve cell states. Here, we developed and benchmarked protocols using glyoxal as a fixative for single cell RNA sequencing application...

The classification of cells in non-model organisms has lagged behind the classification of cells in model organisms that have established cluster of differentiation marker sets. To reduce fish diseases, research is needed to better understand immune-related cells, or hemocytes, in non-model organisms like shrimp and other marine invertebrates. In this study, we used Drop-seq to examine how virus infection affected the populations of hemocytes in kuruma shrimp, Penaeus japonicus, which had been artificially infected with a virus...

The advance in single-cell RNA-sequencing (scRNA-seq) sheds light on cell-specific transcriptomic studies of cell developments, complex diseases and cancers. Nevertheless, scRNA-seq techniques suffer from 'dropout' events, and imputation tools are proposed to address the sparsity. Here, rather than imputation, we propose a tool, SMURF, to extract the low-dimensional embeddings from cells and genes utilizing matrix factorization with a mixture of Poisson-Gamma divergent as objective while preserving self-consistency...

Single-cell transcriptomic analysis (scRNA-seq) can enable researchers to explore the gene expression patterns of thousands of individual cells simultaneously. Processing the complex data generated by scRNA-seq requires specialized computational tools. This chapter focuses on the analytical aspect of scRNA-seq workflow, with a focus on resolving biological signals from large-scale scRNA-seq data produced by the Drop-Seq platform.

Droplet-based single-cell RNA-seq (scRNA-seq) requires the addition of bar codes that mark the cell and transcript of origin. Cell-specific bar codes, typically added by cDNA elongation on beads, label each transcript derived from an individual cell. Transcript-specific bar codes serve as unique molecular identifiers and allow for the maintenance of transcript proportions after PCR-based amplification of cDNA. This chapter provides methods for generating bar-coded scRNA-seq libraries after droplet encapsulation...

Single-cell RNA sequencing (scRNA-seq) allows for the transcriptomic profiling of a sample tissue with single-cell resolution. The concept of scRNA-seq builds on traditional, "bulk" RNA-seq by recording and preserving the cellular origin of each transcript throughout library preparation. Here we describe an adaptation of the Drop-Seq method (Macosko et al. Cell 161, 1202-1214, 2015), in which nanoliter-scale droplets are used to physically separate dissociated cells, while a cell-specific DNA barcode is simultaneously introduced...

CellMarker 2.0 (https://bio-bigdata.hrbmu.edu.cn/CellMarker or https://117.50.127.228/CellMarker/) is an updated database that provides a manually curated collection of experimentally supported markers of various cell types in different tissues of human and mouse. In addition, web tools for analyzing single cell sequencing data are described. We have updated CellMarker 2.0 with more data and several new features, including (i) Appending 36 300 tissue-cell type-maker entries, 474 tissues, 1901 cell types and 4566 markers over the previous version...

High-throughput single-cell analysis today is facilitated by protocols like the 10X Genomics platform or Drop-Seq which generate cDNA pools in which the origin of a transcript is encoded at its 5' or 3' end. Here, we used R2C2 to sequence and demultiplex 12 million full-length cDNA molecules generated by the 10X Genomics platform from ~3000 peripheral blood mononuclear cells. We use these reads, independent from Illumina data, to identify B cell, T cell, and monocyte clusters and generate isoform-level transcriptomes for cells and cell types...

Advances in high-throughput single-cell RNA sequencing (scRNA-seq) have been limited by technical challenges such as tough cell walls and low RNA quantity that prevent transcriptomic profiling of microbial species at throughput. We present microbial Drop-seq or mDrop-seq, a high-throughput scRNA-seq technique that is demonstrated on two yeast species, Saccharomyces cerevisiae , a popular model organism, and Candida albicans , a common opportunistic pathogen. We benchmarked mDrop-seq for sensitivity and specificity and used it to profile 35,109 S...

The ovary is a highly organized composite of germ cells and various types of somatic cells, whose communications dictate ovary development to generate functional oocytes. The differences between individual cells might have profound effects on ovary functions. Single cell RNA sequencing techniques are promising approaches to explore the cell type composition of organisms, the dynamics of transcriptomes, the regulatory network between genes and the signaling pathways between cell types at the single cell resolution...

Hypothalamic Kiss1 neurons control gonadotropin-releasing hormone release through the secretion of kisspeptin. Kiss1 neurons serve as a nodal center that conveys essential regulatory cues for the attainment and maintenance of reproductive function. Despite this critical role, the mechanisms that control kisspeptin synthesis and release remain largely unknown. Using Drop-Seq data from the arcuate nucleus of adult mice and in situ hybridization, we identified Nescient Helix-Loop-Helix 2 ( Nhlh2 ), a transcription factor of the basic helix-loop-helix family, to be enriched in Kiss1 neurons...

Meiosis is a cellular division process that produces gametes for sexual reproduction. Disruption of complex events throughout meiosis, such as synapsis and homologous recombination, can lead to infertility and aneuploidy. To reveal the molecular mechanisms of these events, transcriptome studies of specific substages must be conducted. However, conventional methods, such as bulk RNA-seq and RT-qPCR, are not able to detect the transcriptional variations effectively and precisely, especially for identifying cell types and stages with subtle differences...

High-throughput single-cell RNA sequencing (scRNA-seq) has advantages over traditional RNA-seq to explore spatiotemporal information on gene dynamic expressions in heterogenous tissues. We performed Drop-seq, a method for the dropwise sequestration of single cells for sequencing, on protoplasts from the differentiating xylem of Populus alba × Populus glandulosa. The scRNA-seq profiled 9,798 cells, which were grouped into 12 clusters. Through characterization of differentially expressed genes in each cluster and RNA in situ hybridizations, we identified vessel cells, fiber cells, ray parenchyma cells and xylem precursor cells...

Bovine mammary function at molecular level is often studied using mammary tissue or primary bovine mammary epithelial cells (pbMECs). However, bulk tissue and primary cells are heterogeneous with respect to cell populations, adding further transcriptional variation in addition to genetic background. Thus, understanding of the variation in gene expression profiles of cell populations and their effect on function are limited. To investigate the mononuclear cell composition in bovine milk, we analyzed a single-cell suspension from a milk sample...

Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells...

Osmotic equilibrium and membrane potential in animal cells depend on concentration gradients of sodium (Na+ ) and potassium (K+ ) ions across the plasma membrane, a function catalyzed by the Na+ ,K+ -ATPase α-subunit. Here, we describe ATP1A3 variants encoding dysfunctional α3-subunits in children affected by polymicrogyria, a developmental malformation of the cerebral cortex characterized by abnormal folding and laminar organization. To gain cell-biological insights into the spatiotemporal dynamics of prenatal ATP1A3 expression, we built an ATP1A3 transcriptional atlas of fetal cortical development using mRNA in situ hybridization and transcriptomic profiling of ∼125,000 individual cells with single-cell RNA sequencing (Drop-seq) from 11 areas of the midgestational human neocortex...

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has led to remarkable progress in our understanding of tissue heterogeneity in health and disease. Recently, the need for scRNA-seq sample fixation has emerged in many scenarios, such as when samples need long-term transportation, or when experiments need to be temporally synchronized. Methanol fixation is a simple and gentle method that has been routinely applied in scRNA-sEq. Yet, concerns remain that fixation may result in biases which may change the RNA-seq outcome...

Crystal-like structures find application in several fields ranging from biomedical engineering to material science. For instance, droplet crystals are critical for high throughput assays and material synthesis, while particle crystals are important for particles and cell encapsulation, Drop-seq technologies, and single-cell analysis. Formation of crystal-like structures relies entirely on the possibility of manipulating with great accuracy the micrometer-size objects forming the crystal. In this context, microfluidic devices offer versatile tools for the precise manipulation of droplets and particles, thus enabling fabrication of crystal-like structures that form due to hydrodynamic interactions among droplets or particles...

The mammary gland is a highly dynamic organ which undergoes periods of expansion, differentiation and cell death in each reproductive cycle. Partly because of the dynamic nature of the gland, mammary epithelial cells (MECs) are extraordinarily heterogeneous. Single cell RNA-seq (scRNA-seq) analyses have contributed to understand the cellular and transcriptional heterogeneity of this complex tissue. Here, we integrate scRNA-seq data from three foundational reports that have explored the mammary gland cell populations throughout development at single-cell level using 10× Chromium Drop-Seq...

BACKGROUND: The technology of single cell RNA sequencing (scRNA-seq) has gained massively in popularity as it allows unprecedented insights into cellular heterogeneity as well as identification and characterization of (sub-)cellular populations. Furthermore, scRNA-seq is almost ubiquitously applicable in medical and biological research. However, these new opportunities are accompanied by additional challenges for researchers regarding data analysis, as advanced technical expertise is required in using bioinformatic software...