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Understanding CMOs in CITE-seq Data

In the context of CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing), CMOs, or Cellular Marker Objects, are crucial components that represent the antibody-derived tags (ADTs) used to identify specific cell surface proteins. CITE-seq combines RNA sequencing with protein expression profiling, allowing researchers to analyze both transcriptomic and proteomic data from individual cells simultaneously.

What are CITE-seq and CMOs?

CITE-seq is a powerful technique that utilizes antibodies tagged with unique oligonucleotides to label proteins on the surface of cells. These tags are then sequenced alongside the RNA from the same cells, enabling a comprehensive view of cellular identity and function. CMOs specifically refer to the data structures that encapsulate the information about these antibody-derived tags, including their counts and associated metadata.

How are CMOs Used?

• Identification: CMOs help in identifying specific cell types based on the expression of surface markers.
• Quantification: They provide quantitative data on the abundance of each marker, which can be crucial for understanding cellular states and functions.
• Integration with Transcriptomics: By linking protein expression data with transcriptomic profiles, CMOs facilitate a more holistic understanding of cellular behavior.

Example of CMO Application

In a recent study, CITE-seq was employed to analyze B cell populations, where CMOs were used to track the expression of various surface markers such as CD19 and CD27. This allowed researchers to delineate different B cell subsets and their functional states, providing insights into immune responses and potential dysregulations in conditions like common variable immunodeficiency (CVID) CVID Study.

Conclusion

CMOs are integral to the analysis of CITE-seq data, providing essential information about cell surface protein expression that complements transcriptomic data. Understanding these objects enhances the ability to interpret complex biological systems at the single-cell level.

Further Reading

For more detailed insights into CITE-seq methodologies and applications, consider exploring the following resources:

• 10X Genomics CITE-seq Overview
• CITE-seq: A Comprehensive Review