Standardized Workflow Simplifies Single-Cell DNA Methylation Studies

Researchers from the Chinese Academy of Sciences have developed a standardized workflow for analyzing DNA methylation patterns at the level of individual cells.

The protocol, described in Nature Protocols, pairs an upgraded laboratory procedure with an automated data-analysis tool, making it simpler to compare differences between individual cells.

DNA methylation is a chemical modification that helps regulate gene activity, and it plays an important role in both normal cell development and in disease processes. Traditional sequencing approaches typically measure average methylation levels across large populations of cells, a method that can mask meaningful differences between individual cells. Single-cell sequencing is capable of revealing those cell-to-cell differences, but the extremely small amount of DNA contained in a single cell makes preparing samples for this kind of analysis particularly challenging.

To address this, the team streamlined several steps of the process: cell preparation, DNA digestion, and subsequent reactions now all take place within the same microwell, cutting down on repeated purification steps and reducing DNA loss along the way. Molecular barcodes are used to label individual samples, which lets as many as 24 single-cell samples be pooled together for processing—a change that cuts reagent use and makes the overall workflow more efficient.

The researchers also built an automated analysis tool called SingleCellMethPipe, which processes sequencing data, identifies methylation patterns, and checks the quality of the resulting data.

To evaluate the new method, the team applied it to 96 individual blood-forming stem and progenitor cells, drawn from both a healthy donor and a patient diagnosed with myelodysplastic syndrome, a disorder that interferes with the body’s production of healthy blood cells. Of the 96 cells analyzed, 86 passed the method’s quality checks, for a success rate of 89.6 percent, and the resulting data revealed differences in DNA methylation patterns both across different cell types and between the healthy and disease samples.

The protocol gives researchers a practical tool for studying how cells develop and how shifts in DNA methylation relate to blood disorders and cancer.