EPFL · Wetenschap

Researchers Map Gene Regulation and Chemical Marks on DNA

EPFL researchers have contributed to the largest map yet of how human cells read DNA, revealing how chemical modifications can alter genetic instructions. This work helps explain how different cell types function and how diseases arise from regulatory errors.

An international collaboration, led by Timothy Hughes at the University of Toronto, has identified DNA-binding preferences for 177 previously poorly characterized transcription factors. By combining five experimental platforms with computational analyses and conducting over 4,800 experiments, they added approximately 130 new motifs to the understanding of human gene regulation. This effort generated a "Codebook," the most comprehensive catalog of human transcription factor binding preferences to date. Bart Deplancke's lab at EPFL played a key role in developing this Codebook, aiming to create a more complete dictionary of proteins that control gene expression.

A companion study introduced meSMiLE-seq, a microfluidic method developed by Deplancke's team to compare transcription factor binding to both methylated and unmethylated DNA within the same experiment. Studying 114 transcription factors, they obtained DNA-binding models for 48. The results showed that 14 transcription factors had a greater affinity for methylated DNA or recognized different methylation-dependent motifs, while 13 showed reduced affinity for methylated sequences. Comparisons with cellular data suggest that DNA methylation influences where some transcription factors bind within the genome, indicating that methylation alters how the genome is interpreted rather than simply switching genes on or off.

Together, these studies enhance the catalog of DNA sequences recognized by human transcription factors and demonstrate how DNA methylation modifies these interactions. The Codebook maps where transcription factors can bind based on DNA sequence, while meSMiLE-seq shows how chemical marks on DNA further modify this recognition. This improved understanding could aid in interpreting genetic variants linked to disease, explaining cell-type-specific DNA sequence behavior, and advancing research into development, aging, and diseases like cancer. The findings suggest that cells interpret the genome as a dynamic document, with both the DNA sequence and its chemical annotations determining the final message.

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