Highly sensitive RNA sequencing (RNA-Seq) methods now enable gene expression analysis of very low-input samples and even single cells. 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.
With ultra-low-input and single-cell RNA-Seq, you can explore the distinct biology of different cells within an organ or a tumor, and understand subpopulation responses to environmental cues. These assays enhance 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, including splice junctions and alternative splicing, from the lowest amount of source material.
Dr. Matt Huentelman, Ph.D., a neurogeneticist at the Translational Genomics Research Institute (TGen), is working to understand the genetic and neurological variables that affect learning and memory. His latest project, MindCrowd, uses the power of crowdsourcing to ask users to take online evaluations, complete questionnaires, and submit DNA samples. See how Dr. Huentelman is using the power of single-cell RNA sequencing to understand how individual neurons are involved in the formation of human memories.Read Interview
Single-cell sequencing studies are on the rise with applications in a myriad of fields. Here we provide an introduction to single-cell sequencing.View Video
Illumina sequencing by synthesis (SBS) chemistry is the most widely adopted NGS technology, generating approximately 90% of sequencing data worldwide.*
In addition to our industry-leading data quality, Illumina offers integrated ultra-low-input and single-cell RNA sequencing workflows that simplify the entire process, from library preparation to data analysis and biological interpretation.
Click on the below to view products for each workflow step.
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.
Optimal for preparing an Illumina RNA sequencing library from cDNA generated with the Clontech SMART-Seq Ultra Low Input RNA kit.
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.
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.
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.
Dr. Ramunas Stepanauskas, Ph.D., a senior research scientist at Bigelow Laboratory for Ocean Sciences, uses whole-genome, single-cell RNA sequencing to study bacteria inhabiting the surface layers of the ocean. Learn more about single-cell RNA-Seq in marine research.
Tumors commonly contain several clonal populations that reflect the ongoing accumulation of mutations. Evaluating transcriptome profile differences in different areas of a tumor can enhance our understanding of relapse and metastasis. Learn more about cancer RNA-Seq.
Biochem Pharmacol 86 1074-832013View Summary
Nat Biotechnol 32 381-62014View Summary
Nature 509 371-52014View Summary
*Data calculations on file. Illumina, Inc., 2015