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While DNA methyltransferase1 (DNMT1) is classically known for its functions as a maintenance methyltransferase enzyme, additional roles for DNMT1 in gene expression are not as clearly understood. Several groups have shown that deletion of the catalytic domain from DNMT1 does not abolish repressive activity of the protein against a reporter gene. In our studies, we examine the repressor function of catalytically inactive DNMT1 at endogenous genes. First, potential DNMT1 target genes were identified by searching for genes up-regulated in HCT116 colon cancer cells genetically disrupted for DNMT1 (DNMT1(-/-) hypomorph cells). Next, the requirement for DNMT1 activity for repression of these genes was assessed by stably restoring expression of wild-type or catalytically inactive DNMT1. Both wild-type and mutant proteins are able to occupy the promoters and repress the expression of a set of target genes, and induce, at these promoters, both the depletion of active histone marks and the recruitment of a H3K4 demethylase, KDM1A/LSD1. Together, our findings show that there are genes for which DNMT1 acts as a transcriptional repressor independent from its methyltransferase function and that this repressive function may invoke a role for a scaffolding function of the protein at target genes.

Epigenetics, and more specifically DNA methylation is a fast evolving research area. In almost every cancer type, each month new publications confirm the differentiated regulation of specific genes due to methylation and mention the discovery of novel methylation markers. Therefore, it would be extremely useful to have an annotated, reviewed, sorted and summarized overview of all available data. PubMeth is a cancer methylation database that includes genes that are reported to be methylated in various cancer types. A query can be based either on genes (to check in which cancer types the genes are reported as being methylated) or on cancer types (which genes are reported to be methylated in the cancer (sub) types of interest). The database is freely accessible at http://www.pubmeth.org. PubMeth is based on text-mining of Medline/PubMed abstracts, combined with manual reading and annotation of preselected abstracts. The text-mining approach results in increased speed and selectivity (as for instance many different aliases of a gene are searched at once), while the manual screening significantly raises the specificity and quality of the database. The summarized overview of the results is very useful in case more genes or cancer types are searched at the same time.