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.
Assess key metrics of multiplexed single-cell gene expression libraries to evaluate quality before high-depth runs.Read Application Note »
This scalable, robust, single-cell NGS methodology enables routine transcriptome profiling at single-cell resolution.Read Application Note »
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 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 NextSeq 1000 and NextSeq 2000 Sequencing Systems are groundbreaking benchtop sequencers that allow you to explore new science across a variety of current and emerging applications, with higher efficiency and fewer restraints.
The iSeq 100 Sequencing System makes next-generation sequencing easier and more affordable than ever. Designed for simplicity, it allows labs of all sizes to sequence DNA and RNA at the push of a button. Learn more »
The NovaSeq 6000 System combines benchtop sequencer ease of use with production-scale power in a single platform, with adjustable data output for maximum efficiency. Learn more »
Optimal for preparing an Illumina RNA sequencing library from cDNA generated with the SMART-Seq Ultra Low Input RNA kit. View Product »
Single-cell sequencing can reveal the cell types present and how individual cells are contributing to the function of that system. Learn how insights gained from single-cell NGS are within your reach.View Video »
Hear from Dr. Alka Saxena, head of the Genomics Research Platform and the Single Cell Laboratory at the NIHR Guy’s and St. Thomas’s Biomedical Research Centre.View Video »
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 »
Microbes have been around for billions of years, and they continue to shape our planet and all life on it. Dr. Ramunas Stepanasukas of the Bigelow Laboratory for Ocean Sciences explains how single-cell genomics can help us to better understand microbial diversity and microbial biology. He even discuss how single-cell genomics can help us in our exploration of other planets, like Mars.Listen to Podcast
Cell ontology is the vocabulary for defining cell types, and it's important in biology. Single-cell genomics is revolutionizing cell ontology but combining large data sets with classical knowledge is challenging. Dr. Richard Scheuermann, La Jolla Campus Director at the Venter Institute, discusses single-cell sequencing and computational methods to classify cell types.Listen to Podcast
Eukaryotic cells and their membrane bound organelles evolved from the uptake of a prokaryotic cell into another cell - a process called endosymbiosis. Professors Bebashish Bhattacharya and Dana Price of Rutgers University discuss how single-cell genomics of algae can help unravel the mystery of endosymbiosis and its impact on our health and the environment.Listen to Podcast
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
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 characterize cell-to-cell communication via ligand-receptor interactions across cell types in a tumor microenvironment.Read Publication
A computer scientist transforms the world of biology by making bioinformatics tools available to all.Read Interview
See how single-cell sequencing is transforming our view of cellular development in stem cells.Read Interview
Gain insight into how individual cells contribute to the function of a complex tissue such as peripheral blood.Read App Note
TGen researchers use single-cell RNA sequencing to understand how individual neurons are involved in memory formation.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
Researchers at Bigelow Laboratory for Ocean Sciences use single-cell RNA sequencing to study bacteria inhabiting the surface layers of the ocean.Read Article
User-friendly software tools simplify RNA-Seq data analysis for biologists, regardless of bioinformatics experience. Learn more about single-cell RNA-Seq Data Analysis.
Evaluating transcriptome profile differences within tumor regions can enhance researchers' understanding of relapse and metastasis. Learn more about cancer RNA-Seq.
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.