A highly sensitive method for measuring gene expression from single cells

Generating RNA libraries from ultra-low-input samples

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

Single-cell sequencing is a method that examines the genomes or transcriptomes of individual cells, providing a high-resolution view of cell-to-cell variation. Highly sensitive RNA sequencing (RNA-Seq) methods enable researchers to assess the individual contributions of single cells in complex tissues by profiling the transcriptome in an unbiased manner.

With ultra-low-input and single-cell RNA-Seq, you can explore the distinct biology of individual cells within a complex tissue, and understand 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.

Ultra-low-input and single-cell RNA sequencing are powerful tools for studying the full transcriptome in an unbiased manner from minimal input.

  • Robust transcriptome analysis down to single-cell input levels in high-quality samples
  • Protocol works directly on whole cells and preserves sample integrity
  • High resolution enables discovery of cellular differences usually masked by bulk sampling methods
Advantages of Ultra-Low-Input and Single-Cell RNA-Seq

Single cell RNA-Seq 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.

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.

View Video

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

Click on the below to view products for each workflow step.

ddSEQ™ Single-Cell Isolator

Scalable, flexible single-cell isolation to process tens of thousands of cells in a single day.

Illumina Bio-Rad® SureCell™ WTA 3′ Library Prep Kit for the ddSEQ™ System

Transcriptome profiling of hundreds to tens of thousands of single cells in a single experiment.

NextSeq Series

Flexible power and simplicity for whole genome, exome, or transcriptome sequencing.

HiSeq 2500 System

Power and efficiency for large-scale genomics.

HiSeq 3000/HiSeq 4000 Systems

Maximum throughput, lowest cost for production-scale genomics.

NovaSeq Series

Scalable throughput and flexibility for virtually any genome, sequencing method, and scale of project.

Single-Cell RNA-Seq BaseSpace App

Simple, yet powerful app enables streamlined primary and secondary analysis.

SeqGeq™ Software by FlowJo, LLC

Cluster and subset populations of cells, navigate this data stream using gene tables and families, and rapidly produce reports and visualizations.

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. 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.*

Click on the below to view products for each workflow step.

SMART-Seq® Ultra® Low Input RNA Kit

Synthesize full-length cDNA from only 1–1000 whole cells or 10 pg–10 ng high-quality total RNA. Sold and supported by Clontech, and optimized for Illumina sequencing.

Nextera XT DNA Library Preparation Kit

Optimal for preparing an Illumina RNA sequencing library from cDNA generated with the Clontech SMART-Seq Ultra Low Input RNA kit.

NextSeq Series

Flexible power and simplicity for whole genome, exome, or transcriptome sequencing. 3-10 total RNA samples per run.

HiSeq 2500 System

Power and efficiency to sequence 8-96 total RNA samples per run.

HiSeq 3000/HiSeq 4000 Systems

High-throughput RNA-Seq, with up to 50 human transcriptomes per run on the HiSeq 3000 and 100 transcriptomes on the HiSeq 4000.

Platform Comparison Tool

Compare sequencing platforms and identify the best system for your lab and applications.

Sequencing Reagents

Find reagents, flow cells, and buffers tailored to each Illumina sequencing system.

RNA Express App

Aligns RNA-Seq reads with the STAR aligner and assigns aligned reads to genes, followed by differential expression with DESeq2.

TopHat Alignment App

Maps reads, performs abundance estimations of reference genes and transcripts, calls variants, and offers optional fusion calling.

Cufflinks Assembly & Differential Expression (DE) App

Assembles novel transcripts and performs differential expression of novel and reference transcripts.

The Broad’s IGV

A genome browser developed by the Broad Institute of MIT and Harvard that displays NGS data for complex variant analysis.

Genomatix Pathway System (GePS)

Associates single gene or list of genes with annotation data for pathways, diseases, tissues, and small molecules.

iPathway Guide

Differential gene expression, drug interaction, and disease analysis.

BaseSpace Sequence Hub

The Illumina genomics computing environment for NGS data analysis and management.

BaseSpace Correlation Engine

A growing library of curated genomic data to support researchers in identifying disease mechanisms, drug targets, and biomarkers.

Marine Biology: Uncover Hidden Diversity
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
Cancer Research: Study Individual Clonal Populations

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

Transcriptional regulation by nicotine in dopaminergic neurons.

Biochem Pharmacol 86 1074-83 2013

View Summary

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.

Nat Biotechnol 32 381-6 2014

View Summary

Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq.

Nature 509 371-5 2014

View Summary
Interested in receiving newsletters, case studies, and information on sequencing methods? Enter your email address.
Single-Cell RNA-Seq and Stem Cell Research
Review of Single Cell Research

See selected publications using Illumina technology for single-cell sequencing.

Download Review
RNA-Seq Data Analysis
RNA-Seq Data Analysis

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

Learn More
Single-Cell RNA-Seq and Stem Cell Research
Single-Cell RNA-Seq and Stem Cell Research

See how ultra-low-input RNA-Seq is transforming our view of cellular development in stem cells.

Read Interview
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.

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

Dr. Matt Huentelman, PhD uses single-cell RNA-Seq to understand how individual neurons are involved in memory formation.

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

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

Watch Video

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