CITE-Seq

Fuel discoveries by merging transcriptomic and phenotypic data at the resolution of single cells

What is CITE-Seq?

CITE-Seq (cellular indexing of transcriptomes and epitopes) is a sequencing-based method that simultaneously quantifies cell surface protein and transcriptomic data within a single cell readout. Studying cells concurrently at transcriptomic and proteomic levels can offer unprecedented insights into new cell types, disease states, or other conditions

Why is CITE-Seq useful?

Before the development of CITE-Seq, studying the transcriptome and protein expression simultaneously was challenging to achieve at the single-cell level. Using transcriptional information to understand cell physiology is helpful, but it doesn't provide the entire picture as cell function is incomplete without protein expression information. RNA analysis cannot accurately measure post-transcriptional and translational modifications such as protein degradation, isoform detection, and glycosylation. A long-standing method to study surface protein expression, such as flow cytometry, is robust but has been traditionally limited by the number of targets that can be analyzed, plus it cannot simultaneously provide transcriptomic data. CITE-seq accomplishes both of these goals in a single assay to provide a comprehensive view of single-cell function.

What are the advantages of using CITE-Seq?

CITE-Seq solves the problem of detecting a limited number of proteins while using single-cell sequencing to study transcripts in an unbiased way. Wielding the technology of barcoded antibodies, CITE-Seq is capable of analyzing a near-limitless number of cell markers along with transcripts in a single run. Combined with existing single-cell sequencing methods, our sequencing platforms ensure a smooth workflow to identify novel advancements with high throughput, scalability, and speed.

How does CITE-Seq work?

CITE-seq uses unique oligo-tagged antibodies to identify surface proteins, using sequencing as a readout. The number of barcodes that can be conjugated to antibodies surpasses the number of fluorophores or heavy metal tags used in flow cytometry or CyTOF, expanding the number of proteins that can be measured simultaneously with RNA. These barcoded antibodies are part of a unique workflow that produces protein and nucleic acid data using next-generation sequencing (NGS) technologies.

Make cutting-edge discoveries with CITE-Seq

Explore solutions to simultaneously profile surface proteins and mRNA in single cells.

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Recent insights from CITE-Seq

CITE-Seq has enabled important discoveries by using multiplexed quantification of proteins and transcriptomic data all within single cells. Here are just a few examples of CITE-Seq's capabilities

  • Read how scientists used a marker-based approach for accurate cell-type annotation to analyze single-cell data.1

  • Read how researchers can identify a heterogeneous population of macrophages can prevent heart damage.2

  • Learn how scientists used CITE-Seq to create a comprehensive transcriptional atlas and to help unravel the complex heterogeneity of breast cancer cells.3

  • See how CITE-Seq improved the understanding of mild to moderate disease in COVID-19 patients through the analysis of immune cells.4

Get a broader understanding of breast cancer cells

See how scientists are using our NGS-based systems to understand phenotypic and transcriptomic information at the single-cell level.

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Expand and empower your research with multiomics

Get a holistic perspective by combining genomics with transcriptomics, epigenetics, and proteomics.

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CITE-Seq vs. REAP-Seq

RNA expression and protein sequencing (REAP-seq) and CITE-seq are based on similar principles. With the development of commercial reagents to support both protocols, many researchers now refer to them interchangeably or use the terms proteogenomics or multiomic analysis.

Compatible solutions

AbSeq from BD

BD AbSeq Antibody-Oligonucleotide Conjugates allow for the detection of proteins and mRNA expression in a single experiment. These reagents are designed to work seamlessly with the BD Rhapsody Single-Cell Analysis system.

TotalSeq from BioLegend

BioLegend offers multiple formats of antibodies for the simultaneous detection of protein and RNA or DNA by sequencing using their TotalSeq oligo-conjugated antibodies for single-cell analysis.

Featured multiomics applications

Multiomic analysis at single-cell resolution

Simultaneously profile gene and protein expression for B-cells and T-cells at single-cell resolution using 10x Genomics Chromium Single Cell Immune Profiling and Illumina sequencing systems.

CITE-Seq data analysis

Widely available user-friendly tools provide a simple yet powerful way for you to analyze data without a bioinformatics background. 10x Genomics, BD, and Biolegend offer robust analytics pipelines and visualization tools to aid the interpretation of CITE-Seq data. Alternatively, you can conveniently normalize and integrate gene and protein expression data from CITE-Seq experiments using free open source software such as Seurat or CiteFuse.

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Study gene expression and regulation using NGS

Learn how gene expression and protein production are controlled in different types of cells.

Protein and transcript data in a single workflow

The NextSeq 2000 and NovaSeq 6000 systems support high-throughput sequencing capacity to power CITE-Seq assays. Oligo-conjugated antibodies combined with single-cell library preparation solutions use barcodes to link proteome and transcriptome profiles to single cells. Sophisticated software analysis platforms can decode protein and gene expression data to help you identify unique cell phenotypes.

1
Sample and library preparation

Combine gene and protein expression assays into a single workflow.

2
Sequencing

Quantify data using a single sequencing run.

3
Data analysis, storage, & insights

Discover insights using powerful analysis and visualization software platforms.

Single-cell sequencing sample prep tips

Best practices for single-cell sequencing

Whether you are new or experienced in single-cell sequencing techniques, this webinar will provide you with best practices for sample preparation and quality control for your workflow.

A beginner’s guide to single-cell RNA sequencing

Download this guide to learn about single-cell RNA sequencing, from sample prep and library preparation to sequencing, data analysis, visualization, and experimental design.

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References

  1. Caron DP, Specht WL, Chen D, et al. Multimodal hierarchical classification of CITE-seq data delineates immune cell states across lineages and tissues. Cell Rep Methods. 2025 Jan 27;5(1):100938. doi: 10.1016/j.crmeth.2024.100938
  2. Revelo XS, Parthiban P, Chen C, et al. Cardiac Resident Macrophages Prevent Fibrosis and Stimulate Angiogenesis. Circ Res. 2021 Dec 3;129(12):1086-1101. doi: 10.1161/CIRCRESAHA.121.319737
  3. Wu SZ, Al-Eryani G, Roden DL, et al. A single-cell and spatially resolved atlas of human breast cancers. Nat Genet. 2021 Sep;53(9):1334-1347. doi: 10.1038/s41588-021-00911-1
  4. Su Y, Chen D, Yuan D, et al. Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate. COVID-19. Cell. 2020 Dec 10;183(6):1479-1495.e20. doi: 10.1016/j.cell.2020.10.037