Interconnected blood cells glowing with genetic data, symbolizing BloodSpot database.

Decoding Blood: How New Databases are Revolutionizing Leukemia and Stem Cell Research

Elliot Brynn in Science & Nature August 2025 • 5 min read.

"Dive into the world of BloodSpot, the updated database making waves in hematopoiesis research with its enriched single-cell mRNA sequencing profiles, offering groundbreaking insights into blood disorders."

In the realm of medical research, understanding the intricacies of blood cell development and related disorders is crucial. BloodSpot, a gene-centric database focused on mRNA expression in hematopoietic cells, offers a significant leap forward. Its web-based interface provides a multi-faceted approach to visualizing gene queries, analyzing survival rates in Acute Myeloid Leukemia (AML) patients, and presenting expression data in an interactive developmental tree.

The recent integration of single-cell data marks a substantial upgrade, incorporating unbiased dimensionality reduction methods to illustrate gene expression across the entire spectrum of hematopoiesis. This enhancement, combined with select analytical functionalities like Student's t-tests and correlation analysis, empowers researchers to generate and test hypotheses more efficiently.

With updated visualizations accommodating new data types and an expanded collection of RNA-sequencing datasets—both purified in bulk and at single-cell resolution—BloodSpot has amplified its sample size more than tenfold while maintaining simplicity in presentation. This freely available database at www.bloodspot.eu is set to be an invaluable resource for researchers in leukemia, hematopoiesis, cellular development, and stem cell studies.

Unlocking the Secrets of Blood: BloodSpot's Innovative Approach

Interconnected blood cells glowing with genetic data, symbolizing BloodSpot database.

BloodSpot (1) stands as a pioneering database in the study of healthy and diseased hematopoietic cells. Designed with the user in mind, its interface facilitates quick access to information, enabling hypothesis generation through gene-centric mRNA expression lookup throughout hematopoiesis and in expanded leukemic blasts.

Unlike other databases, BloodSpot provides comprehensive details on the definition and inclusion criteria for each cell type, allowing researchers to draw informed conclusions without needing to sift through supplementary materials from original papers.

User-Friendly Interface: One-click, no-scroll access to relevant data on most screens.
Detailed Cell Type Information: Transparent inclusion criteria for each cell type.
Hypothesis Generation: Quick access for testing and generating new ideas.

Initially, BloodSpot (2,3) utilized microarray technology for high-throughput gene expression assessment in hematopoietic cell types. These studies comprehensively mapped the hematopoietic system (4) and large patient cohorts with leukemic blasts (5,6), employing intricate fluorescence-activated cell sorting (FACS) schemes. However, the landscape has shifted with short-read RNA-sequencing becoming the standard. Recent advancements now allow for the investigation of hematopoiesis at single-cell resolution (7), either with FACS (8) or as an unbiased representation of bone marrow composition (9,10). This evolution provides insights into the continuum of hematopoiesis, independent of surface markers used for FACS, making quality assessment and filtering critical steps in processing single-cell RNA.

The Future of Blood Research is Here

The BloodSpot webserver is updated with curated high quality RNA-sequencing data from both single cell and FACS sorted purified cells. It now includes >25 000 samples, that are presented in an easy-to-navigate manner, and requires only a gene name as input for results. The database interface continues to be a one-click service, even if modifications to data inclusion and statistical tests can be performed, if required for publication purposes. On a gene query a plot of expression will be shown along with survival data, or UMAP for single cell data, and a hierarchical display based on the hematopoietic development or sample correlation. A dropdown can display correlating genes or pathways and can be useful for hypothesis generation. The database has a steady growing userbase and fills a niche within existing databases. With this update we ensure that the BloodSpot remains a resource at the forefront of the hematopoietic field. New data will continuously be curated and added to the database. Furthermore, biannual meetings with a user group and developers will systematically review new data releases since the last update, to ensure data is up to date. The database should be relevant for all researchers and clinicians within haematopoiesis, cellular development and stem cells.

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Everything You Need To Know

What is BloodSpot and what makes it unique in the field of blood research?

BloodSpot is a pioneering, gene-centric database focused on mRNA expression within hematopoietic cells. Its uniqueness stems from its user-friendly interface, detailed cell type information, and the ability to facilitate quick hypothesis generation. Unlike other databases, BloodSpot offers comprehensive details on how each cell type is defined and included, allowing researchers to draw informed conclusions without needing to consult external sources. The integration of single-cell mRNA sequencing data further distinguishes BloodSpot by providing an unbiased view of hematopoiesis, enhancing its analytical capabilities and expanding its scope compared to databases that might only offer bulk RNA sequencing or lack detailed cell type information.

How has BloodSpot evolved in terms of the technology and data it utilizes, and what are the implications of these changes?

Initially, BloodSpot used microarray technology. It has evolved to incorporate short-read RNA-sequencing, including single-cell RNA sequencing data. This shift allows for a deeper, more granular understanding of hematopoiesis, independent of surface markers used in traditional Fluorescence-Activated Cell Sorting (FACS) methods. The implications of these changes are significant: the database now offers a more complete picture of cellular development and disease progression, providing researchers with unprecedented insights into the complexities of blood disorders. The incorporation of single-cell data, combined with analytical functionalities such as Student's t-tests and correlation analysis, empowers researchers to test hypotheses more efficiently and understand the continuum of hematopoiesis.

What kind of data can researchers access and analyze through BloodSpot's web interface?

Through BloodSpot's web interface, researchers can access and analyze a wealth of data, including gene expression profiles, survival data for Acute Myeloid Leukemia (AML) patients, and interactive developmental trees illustrating expression data. The database now features >25,000 samples. Upon a gene query, BloodSpot presents expression plots, UMAPs for single-cell data, and hierarchical displays based on hematopoietic development or sample correlation. It also includes a dropdown to display correlating genes or pathways, which supports hypothesis generation. The integration of single-cell data allows for an unbiased representation of bone marrow composition, enhancing the scope of analysis and enabling a more comprehensive understanding of blood-related research.

How does BloodSpot contribute to the understanding of leukemia and stem cell research?

BloodSpot significantly contributes to understanding leukemia and stem cell research by providing a comprehensive platform for analyzing gene expression in both healthy and malignant hematopoietic cells. By offering detailed expression data, survival analysis tools, and interactive visualizations, it helps researchers identify potential therapeutic targets and understand the mechanisms of disease. The database allows researchers to quickly assess gene expression levels, correlate them with patient outcomes, and explore the dynamics of hematopoiesis at a single-cell resolution. This in-depth analysis is crucial for advancing stem cell studies and developing more effective treatments for leukemia and other blood disorders.

What are the key features and benefits of using BloodSpot for hematopoiesis research, and how does it compare to other databases?

The key features of BloodSpot include a user-friendly interface, detailed cell type information, and the ability to facilitate quick hypothesis generation. Its benefits lie in providing comprehensive gene-centric insights into healthy and malignant hematopoiesis, which is particularly valuable for researchers. Unlike other databases, BloodSpot is designed to be easily accessible and simplifies complex data for quick analysis. The inclusion of detailed cell type inclusion criteria allows researchers to interpret data more effectively. Furthermore, BloodSpot's integration of single-cell mRNA sequencing profiles and analytical functionalities sets it apart, offering an unbiased view and enhancing the analytical capabilities for in-depth studies compared to databases that might have limited functionality.