Reimagining Hematology Research with Single Cell RNA-Seq

Peripheral blood and bone marrow provide two of the most informative windows into the hematopoietic system. Peripheral blood offers an accessible, minimally invasive snapshot of circulating immune activity, while bone marrow reveals the developmental hierarchies that generate the full diversity of hematopoietic and immune cells. For hematology researchers, studying both tissues is essential to understanding how lineage decisions, immune activation, and disease processes unfold across the hematopoietic landscape.

Single cell RNA sequencing (scRNA-seq) makes it possible to study each of these tissues with unprecedented resolution. By profiling thousands to millions of individual cells, scRNA-seq reveals rare populations, activation states, and developmental trajectories that bulk assays cannot detect. Applied to peripheral blood mononuclear cells (PBMCs), scRNA-seq captures systemic immune activity reflecting signals from throughout the body. Applied to bone marrow, it illuminates the progenitor and clonal programs that give rise to these responses. Together, these complementary tissues provide a comprehensive view of hematopoiesis, transforming how researchers investigate malignancies, bone marrow failure, clonal hematopoiesis, and therapeutic response.

PBMCs have long served as a practical and biologically rich material for probing the immune system. Comprising T cells, B cells, NK cells, and monocytes, they mirror many aspects of systemic immune activity while remaining straightforward to isolate and preserve. Because of this balance of accessibility and biological complexity, PBMCs are the cornerstone of thousands of studies in hematology, immunology, and translational medicine.

From flow cytometry and ELISA-based assays that quantify cytokine production and immune activation to bulk RNA-sequencing and qPCR analyses to quantify transcriptional profiles, PBMCs have powered a wide range of analytical approaches. Indeed, decades of work with PBMCs have established them as a critical link between molecular and functional immunology, linking gene expression signatures to cellular behavior and clinical outcomes across diseases from leukemia to autoimmunity and viral infection.

scRNA-seq Expands what PBMCs Can Reveal

The application of scRNA-seq provides an opportunity to amplify the value of PBMC studies. By profiling thousands of individual cells simultaneously, researchers can distinguish rare immune subsets, define activation trajectories, and detect subtle shifts in lineage commitment all from the same familiar sample type that forms the basis of countless biobanks and clinical trials.

Traditional bulk RNA-seq assays average signals across mixed populations, often obscuring the very cellular heterogeneity that drives functional diversity and disease biology. In contrast, scRNA-seq assigns a full transcriptomic profile to each cell, enabling quantitative mapping of immune state diversity and developmental hierarchies across hematologic and inflammatory conditions.

A recent PNAS study by Gervais et al. (2024) provides a compelling example of how scRNA-seq can accelerate biomarker discovery and patient stratification. Motivated by the need for faster, more scalable diagnostics for severe viral disease, the authors examined patients with inborn errors of the type I interferon (IFN) pathway or autoantibodies neutralizing type I IFNs, both known to increase susceptibility to viral infections. Existing diagnostic assays for these conditions were labor-intensive and time-consuming, prompting the search for a more practical biomarker.

Using a combined bulk and single cell transcriptomic approach, the team first identified CXCL10 (encoding the protein IP-10) as a robust interferon-stimulated gene and then used scRNA-seq to validate its induction across all major blood immune cell types. This confirmed CXCL10/IP-10 as a consistent marker of type I IFN pathway activation. Subsequent protein-level analyses verified that IP-10 expression was elevated in response to IFN stimulation but absent in patients with IFN-blocking antibodies or genetic IFN-signaling defects.

These findings established IP-10 detection as a potential high-throughput assay for identifying individuals with impaired type I IFN responses, demonstrating how single cell data can de-risk biomarker development and shorten the path to clinical utility. Similar strategies could be applied in hematology to validate transcriptional biomarkers, identify response predictors, or stratify patients based on immune or progenitor cell activity.

While PBMCs capture circulating immune states, bone marrow reveals where those cells originate and how they are regulated. As the central site of blood and immune cell production, it contains hematopoietic stem and progenitor cells (HSPCs), early lineage intermediates, and the stromal and niche populations that guide differentiation. Because of this complexity, bone marrow has long been indispensable for diagnosing and studying hematologic malignancies, marrow failure syndromes, clonal hematopoiesis, and immune reconstitution.

From Traditional Assays to Single Cell Profiling

Traditionally, studies of bone marrow have relied on methods such as flow cytometry, morphological analysis, and bulk RNA or targeted molecular assays. These approaches provide essential information, but they average signals across mixed populations or require predefined marker panels, making it difficult to resolve rare populations or intermediate cell states.

Applying scRNA-seq to bone marrow captures cells across the developmental lineage, revealing ordered lineage trajectories from HSPCs to mature cells, intermediate progenitor states that are invisible in bulk data, clonal evolution patterns underlying leukemia initiation and relapse, and the niche–immune interactions that shape disease progression or immune reconstitution. Unlike PBMCs, which reflect systemic immune activity, bone marrow profiling shows where those immune states originate and provides the developmental context needed to interpret circulating signatures.

These insights have quickly made scRNA-seq of bone marrow or bone marrow-derived cell lines central to hematologic research. For example, single cell profiling has been used to uncover the transcriptional plasticity of stromal cells, the transcriptional dynamics of bone-marrow derived megakaryocytes in a mouse model of aplastic anemia, and characterize the bone marrow composition of immunodeficient mice engrafted with mononuclear bone marrow cells derived from patients with multiple myeloma (https://insight.jci.org/articles/view/177300).

The adoption of scRNA-seq profiling of PBMCs and bone marrow is rapidly expanding across multiple areas of hematological research, including:

• Hematologic malignancies: Map transcriptional heterogeneity among leukemic blasts or immune microenvironments to uncover mechanisms of resistance and relapse.
• Bone marrow failure syndromes: Trace differentiation from progenitor to mature lineages to identify blocked or dysregulated stages.
• Transplantation and immune reconstitution: Monitor donor and recipient immune recovery at cellular resolution.
• Inflammation, infection, and immunotherapy: Capture dynamic monocyte and lymphocyte activation patterns over time.
• Biomarker discovery: Identify rare or transitional cell populations predictive of treatment response or disease progression.

While transcriptomics reveals the functional identity of individual immune cells, immune repertoire profiling provides a complementary readout of adaptive immunity by capturing T- and B-cell receptor diversity and clonal architecture.

Paired with scRNA-seq, repertoire profiling links functional gene expression programs to specific clonotypes – revealing not only how immune cells behave, but which clonal lineages drive those responses. This dual characterization enables researchers to track clonal expansion during infection, evolution under therapy, or persistence through remission and relapse.

Integrating clonotype and transcriptome information from the same sample provides a multidimensional view of adaptive immunity by connecting cellular state, function, and clonal identity in a single assay.

Early single cell workflows required specialized microfluidic instruments, limiting scale and flexibility. Today, scalable combinatorial indexing technologies eliminate those barriers. Parse Biosciences’ split-pool barcoding allows hundreds of PBMC or bone marrow samples from thousands to millions of cells to be processed in parallel, reducing cost and instrument dependency.

Advances in cell fixation and stabilization have expanded accessibility even further. Samples can now be preserved at collection, stored, and processed later without compromising gene-expression fidelity. This enables multi-site studies, longitudinal sampling, and cohesive cohort analyses without batch effects.

This means that for groups already collecting PBMCs or bone marrow aspirates, single cell analysis can be incorporated directly into ongoing workflows with no new infrastructure required.

PBMCs and bone marrow are complementary windows into the hematopoietic system. PBMCs capture systemic immune activity, while bone marrow reveals the developmental and clonal architectures underlying those responses. By applying scRNA-seq to both tissues, researchers gain a multilayered understanding of the immune and hematopoietic systems.

With scalable chemistry, fixation workflows, and integrated clonotype profiling, single cell RNA-seq is ushering in a new era of hematology research – where the next wave of breakthroughs will come from studying familiar cell types differently, one cell and one clone at a time.