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.
Want to learn valuable insights about the single-cell sequencing workflow?
See an overview of peer-reviewed publications using Illumina technology for single-cell sequencing.
Single-cell sequencing can reveal the cell types present and how individual cells are contributing to the function of complex biological systems. See how you can use the Illumina workflow for single-cell sequencing, from tissue preparation through analysis.
Learn best practices for preparing cell suspensions with sample preparation solutions from Miltenyi Biotec.
View WebinarResearchers from UCSF discuss MULTI-Seq, a sample barcoding strategy for single-cell and single-nucleus RNA sequencing.
View WebinarWe highlight several applications of fully supported workflows that can take you from single-cell suspensions to analyzed data.
View WebinarThe DRAGEN Bio-IT Platform now features a single-cell RNA pipeline that offers a cell-by-gene-expression matrix output starting point for downstream single-cell analysis.
Key features include:
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 InterviewBy analyzing one cell at a time, Professor Amit is improving our understanding of biological systems in health and disease.
Read ArticleSingle-cell sequencing proves invaluable in detecting intracellular communication in tumors.
Read InterviewSwetha Anandhan from the MD Anderson Cancer Center joins Illumina and 10x Genomics for this webinar. She highlights the use of single cell RNA-sequencing to identify a unique population of macrophages in glioblastoma multiforme that persists after treatment with immune checkpoint inhibitors.
View WebinarSingle-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.*
Gain valuable insight into gene expression with this sensitive, scalable, and cost-effective high-throughput workflow.
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.
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.
Researchers used single-cell RNA-Seq to characterize cell-to-cell communication via ligand-receptor interactions across cell types in a tumor microenvironment.
Read PublicationResearchers used single-cell RNA-Seq to demonstrate that hematopoietic stem cell lineage commitment is a gradual process without differentiation into discrete progenitors.
Read PublicationAResearchers 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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