Ready for your all-in-one single cell sequencing solution?

Don’t be sO-negative and AB-positive: Donate blood to further hematopoietic research with single cell sequencing

Don’t be sO-negative and AB-positive: Donate blood to further hematopoietic research with single cell sequencing

Donating blood has the potential to save lives. It can be a lifeline in emergency situations, as well as, helping patients undergoing cancer treatments, requiring transfusions, surviving blood diseases and other chronic illnesses. According to the American Red Cross, a person in the US requires a blood transfusion every 2 seconds, therefore there is a constant battle with acquiring enough blood to treat patients. One donation can save as many as 3 lives and only takes 10 mins to donate. There are 4 major blood groups, A, B, AB and O (Figure 1), however there are individuals which fall outside of these blood groups, therefore to maintain diversity in blood donations, is essential. Antigens on the cell surface of red blood cells determine a person’s blood type. There are more than 600 known antigens, where certain antigens are specific to certain racial and ethnic groups (1). To reduce the risk of developing complications from a transfusion, blood is phenotypically matched. Blood transfusions are vital for patients undergoing major surgery, or who have experienced serious injuries (e.g., from car crashes or natural disasters), in addition to, illnesses causing anemia, such as leukemia or kidney disease. To overcome reduced levels of platelets following intensive treatments such as chemotherapy or radiotherapy, cancer patients also require regular blood transfusions.

Figure 1. Table displaying different groups of blood type (A) and Simon giving blood (B).

Human red blood cell (RBC) or erythrocyte disorders include anemia diseases and malaria which affects millions of people worldwide. Extensive research has been conducted into RBC disorders; however, the complex phenotypes and cellular heterogeneity is still unknown. For example, sickle cell disease (SCD), was first characterized as a ‘monogenetic molecular disease’ in the late 1940s (2). However due to the varying symptoms of SCD in the severity of the anemia and other complications, it is now considered a monogenic disease with polygenetic manifestations (3). Studies using GWAS and genomic sequencing were performed to elucidate associated genetic variants (4), however the results were unable to explain the phenotypic heterogeneity of SCD. Patients with the same sickle point mutation even display heterogeneous symptoms. It is speculated this is due to phenotypic differences in the RBC population of individuals. Characterizing the RBC heterogeneity would allow the development of novel therapeutics towards SCD.

Generous individuals around the globe donate their blood, resulting in more than 100 million units of blood to be collected annually (5). Donated RBC can be stored for up to 42 days prior to transfusion. However contradictory studies have shown a negative correlation between the quality of the RBC and the storage time (6). It is hypothesized this is due to various molecular and biochemical alterations occurring during storage. Bulk RNA sequencing analysis revealed significant changes to the RBC transcriptome during storage, however this analysis conceals cellular heterogeneity in RBC populations. Single cell sequencing analyses on RBCs from healthy doners which were stored for 1 or 15 days revealed distinct cellular clusters, where RBC stored for a longer time exhibited differing cell cluster patterns and marker gene expression (7).

The hematopoietic system involves several organs and tissues for the production of cellular blood components. It relies on a pool of hematopoietic stem/progenitor cells (HSPCs) for continuous production of red blood cells/ erythrocytes, megakaryocytes, myeloid cells, and lymphocytes, which is vital throughout the human lifespan (8) and regulated through a process called hematopoiesis. Through flow cytometry techniques in combination with bulk genomic and transcriptomic analysis, has led to models depicting the differentiation of HSPCs into mature cell types called the ‘hematopoietic tree’ model. The introduction of scRNAseq has revealed detailed diversity into blood cell types reassessing the differential dynamics of blood cell types to be a continuous instead of a discrete process (9). For example, the human cell atlas (HCA) analyzed 100,000 hematopoietic cells from 8 healthy donors to provide the first initial assessment of hematopoietic heterogeneity (10). This instigated a challenge to the tree model, where computational analyses have suggested cellular transition from undifferentiated cellular states to mature cell types lays along a continuous trajectory and is dependent on CD38 (11).

scRNAseq has recently played a vital role in researching hematological diseases, such as leukemia, multiple myeloma, and lymphoma. This revolutionary sequencing technique has been able to reveal the diverse cellular populations and high heterogeneity, characterized by these disorders. With scRNAseq, researchers have been able to uncover insights in cellular variation of the tumor microenvironment and dissect the pathogenesis of diseases, which greatly improves diagnosis and treatment therapies.

One such example involves the characterization of acute myeloid leukemia (AML). Advancements in single cell technology has led to the identification of 6 malignant AML cell types and the discovery of alternations to T-cell phenotypes within these malignant cell which contribute to the immunosuppressive AML microenvironment (12). Lymphoid malignancies, such as leukemias, lymphomas and myelomas, have been dissected using scRNAseq analysis. The heterogeneity of patients with multiple myelomas was examined with scRNAseq to identify specific targets and pathways for diagnosis and therapy (Figure 2), in addition to discovering a signature to predict the prognosis for patients (13).

Figure 2. Differential gene expression and associated pathways with progression of multiple myeloma (MM). Comparison analysis of different cellular groups (L1 – L4, taken from patients at different stages of MM) highlighted signaling and response pathways (A) involved in MM, as well as 44 signature genes (B) consistently expressed among the 4 groups. Adapted from (13).

In conclusion, blood donations are not only vital for saving lives, but also essential to progress forward in scientific discoveries for certain diseases, where research institutions, biopharmaceutical companies and hospitals rely on donations for ongoing medical research.

Are you thinking about applying single cell sequencing to your research project? Get in touch with our experts at


  1. Drew VJ, Barro L, Seghatchian J, Burnouf T. (2017) Towards pathogen inactivation of red blood cells and whole blood targeting viral DNA/RNA: design, technologies, and future prospects for developing countries. Blood Transfus. 15(6):512-521.
  2. Pauling, L., Itano, H. A., Singer, S. J., and Wells, I. C. (1949). Sickle Cell Anemia, a Molecular Disease. Science 110, 543–548. doi:10.1126/science.110.2865.543
  3. Driss, A., Asare, K. O., Hibbert, J. M., Gee, B. E., Adamkiewicz, T. V., and Stiles, J. K. (2009). Sickle Cell Disease in the Post Genomic Era: A Monogenic Disease with a Polygenic Phenotype. Genomics Insights 2009, 23–48. doi:10.4137/gei.s2626
  4. Piel, F. B., Steinberg, M. H., and Rees, D. C. (2017). Sickle Cell Disease. N. Engl. J. Med. 376, 1561–1573. doi:10.1056/nejmra1510865
  5. World Health Organization (2014). Blood Safety and Availability. Geneva, Switzerland: WHO Fact Sheet.
  6. D’Alessandro, A., Kriebardis, A. G., Rinalducci, S., Antonelou, M. H., Hansen, K. C., Papassideri, I. S., et al. (2015). An Update on Red Blood Cell Storage Lesions, as Gleaned Through Biochemistry and Omics Technologies. Transfusion 55, 205–219. doi:10.1111/trf.12804
  7. Jain V, Yang W-H, Wu J, Roback JD, Gregory SG and Chi J-T (2022) Single Cell RNA-Seq Analysis of Human Red Cells. Front. Physiol. 13:828700. doi: 10.3389/fphys.2022.828700
  8. Alvarez-Errico D, Vento-Tormo R, Sieweke M, Ballestar E. Epigenetic control of myeloid cell differentiation, identity and function. Nat Rev Immunol. 2015;15:7–17.
  9. Liggett LA, Sankaran VG. Unraveling hematopoiesis through the lens of genomics. Cell. 2020;182:1384–1400.
  10. Hay SB, Ferchen K, Chetal K, Grimes HL, Salomonis N. The Human Cell Atlas bone marrow single-cell interactive web portal. Exp Hematol. 2018;68:51–61.
  11. Velten L, Haas SF, Raffel S, et al. Human haematopoietic stem cell lineage commitment is a continuous process. Nat Cell Biol. 2017;19:271–281
  12. van Galen P, Hovestadt V, Wadsworth MH II, et al. Single-cell RNA-Seq reveals AML hierarchies relevant to disease progression and immunity. Cell. 2019;176. 1265−1281.e24.
  13. Jang JS, Li Y, Mitra AK, Bi L, et al. Molecular signatures of multiple myeloma progression through single cell RNA-Seq. Blood Cancer J. 2019;9:2.