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.
Single-cell and ultra-low-input RNA-Seq are powerful tools for studying the transcriptome in an unbiased manner from minimal input.
See how to use the Illumina workflow for single-cell sequencing, from tissue preparation through analysis.View Video
Researchers from UCSF discuss MULTI-Seq, a sample barcoding strategy for single-cell and single-nucleus RNA sequencing.View Webinar
We highlight several applications of fully supported workflows that can take you from single-cell suspensions to analyzed data.View Webinar
Cole Trapnell, PhD, is the principal developer of TopHat, Cufflinks, and other widely used bioinformatics tools. He shared with us his views on the importance of understanding cell lineage, his lab's experience with single-cell RNA sequencing, and his application of combinatorial indexing.Read Interview
By analyzing one cell at a time, Professor Amit is improving our understanding of biological systems in health and disease.Read Article
Single-cell sequencing proves invaluable in detecting intracellular communication in tumors.Read Interview
See an overview of peer-reviewed publications using Illumina technology for single-cell sequencing.Read Review
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.*
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.View Video
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.
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.
Methods that allow researchers to simultaneously sequence RNA and detect extracellular proteins in individual cells reveal new cell types and states associated with disease.Read More
ATAC-Seq is a widely used method that uses the hyperactive transposase Tn5 to assess chromatin accessibility. It can be performed on single cells at high resolution.Learn more about ATAC-Seq
Detect cancer gene expression and transcriptome changes and identify novel cancer transcripts with RNA-Seq.Learn More
Expand cell and molecular biology research beyond conventional methods with next-generation sequencing.Learn More
Researchers used single-cell RNA-Seq to characterize cell-to-cell communication via ligand-receptor interactions across cell types in a tumor microenvironment.Read Publication
Researchers used single-cell RNA-Seq to demonstrate that hematopoietic stem cell lineage commitment is a gradual process without differentiation into discrete progenitors.Read Publication
Researchers 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.Read Publication