A new online tool reveals how different types of DNA sequences work together to regulate gene expression, and how genetic variants disrupt this process. The resource was described in March in Nature Methods1.
The researchers focused on three types of DNA segments: promoters, which regulate the expression of nearby genes; enhancers, which control the expression of distant genes; and tiny sequences that serve as landing strips for proteins called transcription factors.
The researchers culled promoters and enhancers from an existing atlas of regulatory regions for 808 human cell and tissue types. They scanned the sequences to determine whether they contain binding sites for any of 662 transcription factors.
A computer algorithm linked these three types of regulators to the genes they are likely to control and constructed ‘regulatory networks’ for each of the cell and tissue types. It then merged the networks for the same cell or tissue types to create networks for 283 cell types and 111 tissues.
The results suggest that cells and tissues with similar functions or developmental origins — such as those involved in inflammation or derived from the same region of a developing embryo — tend to use some of the same DNA segments to regulate certain genes.
Based on these similarities, the researchers grouped the networks into 32 categories, including 1 associated with neurons and 1 specific to the nervous system.
They also used the networks to investigate how common variants — those that occur in at least 5 percent of the population — affect gene regulation. To this end, they integrated the results from 37 genome-wide association studies, which link certain common variants to an increased risk of having a condition such as autism. They found that the variants often disrupt networks in cells or tissues relevant to a given condition. For example, schizophrenia-linked variants tend to affect networks in the adult brain.
All of the networks the researchers constructed are available online. No autism-linked variants identified so far cluster in any of the networks.
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