Biology is increasingly being studied at the level of individual cells.
For decades, researchers often relied on bulk measurements to study tissues and biological systems. These approaches provide valuable information, but they can also hide important differences between individual cells.
Today, technologies such as single-cell RNA sequencing, spatial transcriptomics, and single-cell multi-omics are allowing researchers to study biological systems at much higher resolution.
This shift is helping scientists move from simply identifying genes and cell types toward mapping how cells are organized, interact, and change within tissues.
Single-Cell RNA Sequencing: A New View of Cellular Biology
Every cell contains RNA molecules that reflect which genes are active at a particular moment. By analyzing these RNA molecules, researchers can obtain information about the molecular state and identity of a cell.
Traditional RNA sequencing often analyzes RNA extracted from many cells together. This produces an average expression profile for the sample.
Single-cell RNA sequencing (scRNA-seq) changes this approach by analyzing gene expression at the level of individual cells.
Instead of obtaining one combined molecular profile, researchers can examine thousands or even millions of individual cells and identify differences between them.
This makes it possible to investigate:
Different cell types within the same tissue
Distinct cellular states
Rare cell populations
Differences in gene expression
Cellular changes during development or disease
Molecular relationships between cell populations
Single-cell RNA sequencing therefore provides an important foundation for studying biology at cellular resolution.
From Bulk Measurements to Individual Cell Profiles
A tissue is not a uniform biological system.
It can contain many different cell populations, each with distinct molecular characteristics and biological functions. A single tissue sample may contain immune cells, endothelial cells, epithelial cells, stromal cells, and other specialized populations.
When these cells are analyzed together, important differences between them can become difficult to observe.
Single-cell approaches help separate these molecular signals and reveal the diversity contained within a tissue.
This transition from average measurements to individual cellular profiles has changed how researchers investigate complex biological systems.
It also opens the door to a broader objective: constructing detailed maps of the cells that make up tissues and organs.
The Transition Toward Cellular Mapping
Single-cell RNA sequencing provides information about cellular identity and molecular activity. However, biological systems are also defined by where cells are located and how they interact.
This has driven the development of a broader approach known as cellular mapping.
Modern cellular mapping can combine several dimensions of biological information:
Identify → Locate → Connect → Track
- Identify: determine which cell types and cellular states are present.
- Locate: determine where cells are positioned within tissues.
- Connect: investigate interactions and communication between cells.
- Track: study how cellular states change during development, disease, or other biological processes.
Spatial transcriptomics adds another layer by connecting molecular information with the physical organization of cells within tissues.
Together, these approaches move research from a simple catalogue of cell types toward increasingly detailed cellular maps.
one of the techniques used for cells mapping is Cellular Mapping of Attributes with Position (CMAP), an algorithm designed to precisely predict single-cell locations by integrating spatial and single-cell transcriptome datasets.
The Tabula Sapiens Cell Atlas and Human Cell Diversity
A major example of this approach is The Tabula Sapiens, a large-scale single-cell transcriptomic atlas of the human body.
Published in Science in 2022, the study analyzed nearly 500,000 cells from 24 tissues and organs, representing more than 400 cell types.
The researchers used single-cell transcriptomics to characterize the molecular profiles of cells across different parts of the human body.
The resulting atlas provides a reference for studying human cell types and their molecular characteristics.
The study also revealed differences in gene expression between cells from different tissues and identified biological patterns that become difficult to observe when cells are analyzed collectively.
This type of research illustrates a central goal of cellular mapping: creating reference maps that help researchers understand which cells are present, what molecular programs they use, and how cellular populations differ across tissues.
From Cell Atlases to Cellular Maps
The Tabula Sapiens study shows how single-cell technologies can reveal biological diversity that is hidden in bulk measurements. By identifying different cell types and their molecular states, researchers can begin to build detailed maps of tissues and organs.
This is an important step toward a broader view of biology — one that connects cell identity, molecular activity, spatial organization, and cellular interactions.
More Studies
Study combines single-cell omics, spatial transcriptomics, and other molecular datasets across 125 healthy adult and fetal tissues.
The researchers integrated single-cell data with spatial transcriptomics and imaging to map human thymus organization during development.
Study demonstrates mapping cell types within human brain tissue, including nearly 60,000 mapped cells and 75 transcriptomic cell types.