Single-Cell RNA Sequencing

Technology for sequencing of all RNA transcripts, also known as the transcriptome, comes from techniques presented by two research groups in the early 1990s, in the labs of P. Coleman and Norman Iscove. The groups presented the technology of expanding the complementary DNA (cDNA) of an individual cell using in vitro transcription for linear amplification and PCR for exponential amplification. Initially the technologies were applied to commercially available, high-density DNA microarray chips and later adapted for single-cell RNA sequencing. In 2009, single-cell transcriptome analysis with a next-generation sequencing platform was published, describing cells from early developmental stages. The research was Led by M Azim Surani at the University of Cambridge.

Single-cell RNA sequencing (scRNA-seq) examines the gene expression of individual cells. Compared to traditional RNA sequencing it provides a higher resolution of cellular differences. scRN- seq can provide information about an individual cell in the context of its microenvironment. Bulk RNA sequencing groups together different cells and provides an average expression signal. scRNA-seq allows the resolution of rare cell populations, regulatory relationships between genes and the trajectories of distinct cell lineages during development. Research has shown that gene expression is heterogeneous even in cell typescell types the are similar. scRNA-seq can identify stochastic biological processes. The technology can identify outlier cells within a population, which has applications in drug resistance and cancer relapse.

Technology for sequencing of all RNA transcripts, also known as the transcriptome, comes from techniques presented by two research groups in the early 1990s, ledin bythe Jameslabs Eberwineof P. Coleman and Norman Iscove. The groups presented the technology of expanding the complementary DNA (cDNA) of an individual cell using in vitro transcription for linear amplification and PCR for exponential amplification. Initially the technologies were applied to commercially available, high-density DNA microarray chips and later adapted for single-cell RNA sequencing. In 2009, single-cell transcriptome analysis with a next-generation sequencing platform was published, describing cells from early developmental stages. The research was Led by M Azim Surani at the University of Cambridge.

Cells are the basic unit of life. The ability to reveal complex cellular events in biological systems is critical to a better understanding of cellular contributions during development or in disease progression. Single-cell RNA-Seq can be used to examine the gene expression of individual cells and provides a higher resolution of cellular differences as compared to traditional RNA-Seq. Single-cell RNA-Seq enables us to understand the function of an individual cell in the context of its microenvironment.

Single-cell RNA sequencing (scRNA-seq) examines the gene expression of individual cells. Compared to traditional RNA sequencing it provides a higher resolution of cellular differences. scRN- seq can provide information about an individual cell in the context of its microenvironment. Bulk RNA sequencing groups together different cells and provides an average expression signal. scRNA-seq allows the resolution of rare cell populations, regulatory relationships between genes and the trajectories of distinct cell lineages during development. Research has shown that gene expression is heterogeneous even in cell types the are similar. scRNA-seq can identify stochastic biological processes. The technology can identify outlier cells within a population, which has applications in drug resistance and cancer relapse.

Technology for sequencing of all RNA transcripts, also known as the transcriptome, comes from techniques presented by two research groups in the early 1990s, led by James Eberwine and Norman Iscove. The groups presented the technology of expanding the complementary DNA (cDNA) of an individual cell using in vitro transcription for linear amplification and PCR for exponential amplification. Initially the technologies were applied to commercially available, high-density DNA microarray chips and later adapted for single-cell RNA sequencing. In 2009, single-cell transcriptome analysis with a next-generation sequencing platform was published, describing cells from early developmental stages.

The first step is single-cell isolation, by limiting dilution with a pipette. Micromanipulation is used for early embryos or uncultivated microorganisms. Flow-activated cell sorting (FACS) and microfluidics methods are also used to isolate individual cells. Laser capture microdissection is aided by a computer system to isolate cells from solid samples.

The next step is library preparation which involves cell lysis, reverse transcription into first-strand cDNA, second-strand synthesis and cDNA amplification. The raw data is handled using computational software such as those provided by 10X Genomics and Fluidigm. Quality control tests are performed using tools such as FastQC (Babraham Institute). Alignment of sequences, de-duplication and normalization with raw expression data is done using statistical methods.

Cells are the basic unit of life and each cell is unique. The ability to reveal complex cellular events in biological systems is critical to a better understanding of cellular contributions during development or in disease progression. Gene expression research at the single-cell resolution on samples composed of mixed cell populations allows for deep insight into c into the transcriptome complexity of diverse cell types.

The advent of cell sorting/partitioning technologies, such as flow cytometry and microfluidics, has made it possible to capture single cells, and the DNA or RNA of single cells is amplified for single-cell sequencing.

Cells are the basic unit of life. The ability to reveal complex cellular events in biological systems is critical to a better understanding of cellular contributions during development or in disease progression. Single-cell RNA-Seq can be used to examine the gene expression of individual cells and provides a higher resolution of cellular differences as compared to traditional RNA-Seq. Single-cell RNA-Seq enables us to understand the function of an individual cell in the context of its microenvironment.

Fluidigm C1 Single-Cell mRNA Workflow. With Fluidigm C1 system, We provide single-cell transcriptome profiling service at an optional scale. C1 can rapidly and reliably capture and process individual cells. The steps in Integrated C1 Single-Cell mRNA Seq workflow include fluidics circuits (IFCs) to capture cells, convert polyA+ RNA into full-length cDNA, and perform universal amplification of the cDNA. With the customizable microfluidic circuits, C1 enables seamlessly transition from identifying critical cell populations to generate sequencing libraries for transcript 3′ End Counting, full-length mRNA sequencing, DNA sequencing, epigenetic analysis, micro-RNA expression profiling and more.

Cells are the basic unit of life and each cell is unique. The ability to reveal complex cellular events in biological systems is critical to a better understanding of cellular contributions during development or in disease progression. Gene expressionGene expression research at the single-cell resolution on samples composed of mixed cell populations allows for deep insight into c into the transcriptome complexity of diverse cell types.

Fluidigm C1 Single-Cell mRNA Workflow. With Fluidigm C1 system, We provide single-cell transcriptome profiling service at an optional scale. C1 can rapidly and reliably capture and process individual cells. The steps in Integrated C1 Single-Cell mRNA Seq workflow include fluidics circuits (IFCs) to capture cells, convert polyA+ RNA into full-length cDNA, and perform universal amplification of the cDNA. With the customizable microfluidic circuits, C1 enables seamlessly transition from identifying critical cell populations to generate sequencing libraries for transcript 3′ End Counting, full-length mRNA sequencing, DNA sequencingDNA sequencing, epigenetic analysis, micro-RNA expression profiling and more.

CD Genomics provides robust transcriptome research service down to single-cell input levels in high-quality samples These global gene expression patterns in single cells already have dramatically advanced cell biology.

The advent of cell sorting/partitioning technologies, such as flow cytometry and microfluidics, has made it possible to capture single cells, and the DNA or RNA of single cells is amplified for single-cell sequencing. The general workflow for single-cell RNA sequencing is outlined below.

CD Genomics provides robust transcriptome research service down to single-cell input levels in high-quality samples These global gene expressiongene expression patterns in single cells already have dramatically advanced cell biology.

CD GenomicsCD Genomics provides robust transcriptome research service down to single-cell input levels in high-quality samples These global gene expression patterns in single cells already have dramatically advanced cell biology.

CD Genomics provides robust transcriptome research service down to single-cell input levels in high-quality samples These global gene expression patterns in single cells already have dramatically advanced cell biology.

Cells are the basic unit of life and each cell is unique. The ability to reveal complex cellular events in biological systems is critical to a better understanding of cellular contributions during development or in disease progression. Gene expression research at the single-cell resolution on samples composed of mixed cell populations allows for deep insight into c into the transcriptome complexity of diverse cell types.

The advent of cell sorting/partitioning technologies, such as flow cytometry and microfluidics, has made it possible to capture single cells, and the DNA or RNA of single cells is amplified for single-cell sequencing. The general workflow for single-cell RNA sequencing is outlined below.

Fluidigm C1 Single-Cell mRNA Workflow. With Fluidigm C1 system, We provide single-cell transcriptome profiling service at an optional scale. C1 can rapidly and reliably capture and process individual cells. The steps in Integrated C1 Single-Cell mRNA Seq workflow include fluidics circuits (IFCs) to capture cells, convert polyA+ RNA into full-length cDNA, and perform universal amplification of the cDNA. With the customizable microfluidic circuits, C1 enables seamlessly transition from identifying critical cell populations to generate sequencing libraries for transcript 3′ End Counting, full-length mRNA sequencing, DNA sequencing, epigenetic analysis, micro-RNA expression profiling and more.