New tools reveal molecular barcodes distinguishing cell types
There are about 75 different types of cells in the human brain. What makes them all different? Researchers at Baylor College of Medicine have developed a new set of computational tools to help answer this question. Although different cell types from the same organism carry the same DNA, they look and function differently because a different set of genes is active or inactive in each. Cells switch genes on or off by using epigenetic mechanisms, such as DNA methylation, which involves tagging genes with methyl chemical groups.
To better understand how epigenetic regulation works, researchers study DNA methylation signals in whole genome datasets. These datasets contain the sequences of the building blocks that make up the DNA in a cell population. However, when the tissue being studied, like the brain, is made up of many different cell types, existing analytical approaches can not distinguish methylation signals arising from those different cell types.
Now, a new set of computational methods developed at Baylor allows researchers to identify cell-type specific methylation patterns – molecular barcodes – in complex cell mixtures. These new computational tools, published in the journal Genome Biology and available for free download, can be applied to existing whole-genome methylation datasets from any species. This opens exciting new possibilities to improve our understanding of how DNA methylation regulates cellular function.
Identifying cell type-specific molecular barcodes
“The current gold-standard approach to study DNA methylation is whole genome bisulfite sequencing (WGBS), a next-generation sequencing technology that determines DNA methylation of each cytosine, one of the DNA building blocks, in the entire genome,” said co-corresponding author Dr. Cristian Coarfa, associate professor of molecular and cellular biology and part of the Center for Precision Environmental Health at Baylor.
WGBS studies typically report the average methylation level at each cytosine. In tissues made up of multiple cell types, however, this average reflects a mashup of the methylation level of each cell type in the mixture, obscuring cell-type specific differences.