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Single-Cell and Ultra-Low-Input RNA-Seq

Introduction to Single-Cell RNA Sequencing

Complex biological systems are determined by the coordinated functions of individual cells. Conventional methods that provide bulk genome or transcriptome data are unable to reveal the cellular heterogeneity that drives this complexity. Single-cell sequencing is a next-generation sequencing (NGS) method that examines the genomes or transcriptomes of individual cells, providing a high-resolution view of cell-to-cell variation.

Highly sensitive ultra-low-input and single-cell RNA sequencing (RNA-Seq) methods enable researchers to explore the distinct biology of individual cells in complex tissues and understand cellular subpopulation responses to environmental cues. These assays enhance the study of cell function and heterogeneity in time-dependent processes such as differentiation, proliferation, and tumorigenesis.

Advantages of Ultra-Low-Input and Single-Cell RNA-Seq

Advantages of Single-Cell RNA-Seq

Single-cell and ultra-low-input RNA-Seq are powerful tools for studying the transcriptome in an unbiased manner from minimal input.

  • Robust transcriptome analysis down to single-cell input levels for high-quality samples
  • Integrated protocol proceeds directly from whole cells and preserves sample integrity
  • High resolution analysis enables discovery of cellular differences usually masked by bulk sampling methods
Deciphering the Role of Long Non-Coding RNA in Cancer

Researchers at Biogazelle are using RNA-Seq to reveal how lncRNAs can be specific to cell types. They discovered that silencing certain lncRNAs can help destroy cancer cells.

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High- and Low-Throughput Methods

Single-cell sequencing methods can be distinguished by cell throughput. Low-throughput methods include mechanical manipulation or cell sorting/partitioning technologies and are able to process dozens to a few hundred cells per experiment.

Recent advances in microfluidic technologies have enabled high-throughput single cell profiling where researchers can examine hundreds to tens of thousands of cells per experiment in a cost-effective manner. Both the high- and low-throughput methods utilize Illumina sequencing by synthesis (SBS) chemistry, the most widely adopted NGS technology, which generates approximately 90% of sequencing data worldwide.*

The Singular Neuron

James Eberwine explains how single-cell RNA sequencing can be used in vivo to understand how individual cells function in their microenvironment within a complex organism.

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High-Throughput Workflow for Ultra-Low-Input and Single-Cell RNA-Seq

The Illumina Bio-Rad Single-Cell RNA Sequencing Solution combines the highly innovative Bio-Rad Droplet Digital™ technology (ddSEQ™) with Illumina NGS library preparation, sequencing, and analysis technologies. Gain valuable insight into gene expression with this sensitive, scalable, and cost-effective high-throughput workflow.

Low-Throughput Workflow for Ultra-Low-Input and Single-Cell RNA-Seq

The low-throughput method below is recommended for researchers who wish to process small numbers of cells for a particular study, such as dozens to a few hundred cells per experiment.

NGS vs. qPCR

The key difference between next-generation sequencing and qPCR is discovery power. Compare the two technologies and learn how the wide dynamic range and high sensitivity of NGS can help you detect and quantify variation.

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NGS vs. qPCR

Related Solutions

Marine Biology: Uncover Hidden Diversity

Researchers at Bigelow Laboratory for Ocean Sciences use single-cell RNA sequencing to study bacteria inhabiting the surface layers of the ocean. Learn more about single-cell RNA-Seq in marine research.

RNA-Seq for Cancer Research

Evaluating transcriptome profile differences within tumor regions can enhance researchers' understanding of relapse and metastasis. Learn more about cancer RNA-Seq.

Single-Cell Research Review

See an overview of peer-reviewed publications using Illumina technology for single-cell sequencing. These publications demonstrate various single-cell sequencing applications and techniques. Read the review.

Featured Publications

Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics

Researchers used single-cell RNA-Seq to characterize cell-to-cell communication via ligand-receptor interactions across cell types in a tumor microenvironment.

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Human haematopoietic stem cell lineage commitment is a continuous process

Researchers used single-cell RNA-Seq to demonstrate that hematopoietic stem cell lineage commitment is a gradual process without differentiation into discrete progenitors.

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Aging increases cell-to-cell transcriptional variability upon immune stimulation

AResearchers used single-cell RNA-Seq to explore the effects of aging on the immune system, observing that age-related cell-to-cell transcriptional variability is a hallmark of aging.

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Additional Resources

The Illumina Bio-Rad Single Cell Sequencing Solution
The Illumina Bio-Rad Single Cell Sequencing Solution

Profile transcriptomes of hundreds to tens of thousands of single cells with this user-friendly solution for gene expression studies.

Single-Cell RNA Sequencing of Peripheral Blood Mononuclear Cells
Single-Cell RNA Sequencing of Peripheral Blood Mononuclear Cells

Gain insight into how individual cells contribute to the function of a complex tissue such as peripheral blood.

RNA-Seq Data Analysis
RNA-Seq Data Analysis

User-friendly software tools simplify RNA-Seq data analysis for biologists, regardless of bioinformatics experience.

Stem Cell Research with Single-Cell RNA-Seq
Stem Cell Research with Single-Cell RNA-Seq

See how single-cell sequencing is transforming our view of cellular development in stem cells.

Mapping Neural Diversity with Single-Cell mRNA-Seq
Mapping Neural Diversity with Single-Cell mRNA-Seq

The ability to analyze gene expression signatures from individual cells is transforming the way neurons are classified.

Single-Cell RNA-Seq, the Internet, and Memory
Single-Cell RNA-Seq, the Internet, and Memory

TGen researchers use single-cell RNA sequencing to understand how individual neurons are involved in memory formation.

Single-Cell Sequencing on the NovaSeq 6000 System
Single-Cell Sequencing on the NovaSeq 6000 System

This scalable, robust, single-cell NGS methodology enables routine transcriptome profiling at single-cell resolution.

Single-Cell Sequencing: Needle in a Haystack
Single-Cell Sequencing: Needle in a Haystack

Single-cell analysis studies are on the rise with applications in a myriad of fields.

*Data calculations on file. Illumina, Inc., 2015