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Single-cell CITE-seq profiling of human bone marrow B cells with IgD and IgM antibody-derived tags

ABSTRACT: We performed single-cell RNA sequencing with cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) on human bone marrow samples to characterize B cell populations. Cells were profiled using the 10x Genomics Chromium platform with simultaneous measurement of gene expression and antibody-derived tags (ADT), including IgD and IgM surface markers. This dataset enables integrated analysis of transcriptomic and protein-level features to resolve B cell developmental and functional states within the bone marrow microenvironment.

ORGANISM(S): Homo sapiens

PROVIDER: GSE328023 | GEO | 2026/04/15

REPOSITORIES: GEO

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Project description:Understanding the cellular heterogeneity and lineage potential of human bone marrow hematopoietic progenitors is required to understand normal differentiation and the mechanisms of hematological disease. Central to this objective are protocols that enable the delineation, isolation and functional characterization or known and novel cell populations, which are traditionally empowered by flow cytometry. Recognizing the need for tackling cellular heterogeneity, we have designed a use case for compiling next-generation processing methods via existing and highly curated single-cell interrogation technologies. Multi-omics approaches, such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), enable concurrent transcriptomic and immunophenotyping at a single-cell level but necessitate precision antibody titration mixes that can be directly integrated with parallel flow cytometry strategies. To bridge this gap, we performed a molecular titration of 266 antibodies using primary human bone marrow cells spanning race and sex to approximate diversity. Through machine learning and user curation, we created an optimized titrated bone marrow CITE-seq panel of 132 antibodies. Multimodal integration of these data using a game-theory driven approach, improved our ability to resolve new stable stem, progenitor, and transitional cell populations, readily defined by unique RNA and ADT markers. Leveraging complexity-matching high-dimensional flow cytometry (pyInfinityFlow), we consolidated the findings from CITE-seq and subsequently developed novel isolation strategies for maturing granulocytes, late-stage erythroid progenitors and improved purification of megakaryocyte/erythrocyte progenitors (MEP). Finally, we integrated CITE-seq with flow cytometry data from matching donors, successfully identified 37 cell surface markers consistently expressed across donors and technologies. The compiled bone marrow cell atlas serves as an advanced digital analytical resource for progenitor analyses in health and disease.

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Single-cell CITE-seq profiling of human bone marrow B cells with IgD and IgM antibody-derived tags

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