bioRxivMolecular BiologyPreprint
CDCA7 facilitates MET1-mediated CG DNA methylation maintenance in centromeric heterochromatin via histone H1
Shuya WangiD, Tong LiiD, Matthew NaishiD, Russell Chuang, Evan K. LiniD, Christian Fonkalsrud, Yan HeiD, Suhua FengiD, Ian R. HendersoniD, Steven E. JacobseniD
Abstract
DNA methylation is a conserved epigenetic modification essential for maintaining genome stability. However, how methyltransferases maintain CG methylation within compact chromatin, including centromeres, remains unclear. In humans, CDCA7 is necessary for the inheritance of DNA methylation at juxta-centromeres. Mutations that impair its ability to bind chromatin result in Immunodeficiency, Centromeric Instability, and Facial Anomalies (ICF) syndrome, characterized by centromeric instability. To investigate whether CDCA7 function is conserved, we identified two Arabidopsis thaliana orthologs, CDCA7A and CDCA7B. The loss of both copies results in CG hypomethylation at pericentromeric regions and centromeric satellite repeat arrays. Machine learning analysis suggested that heterochromatic nucleosomes, with enrichment of H1, H2A.W, and H3K9me2 levels, depend heavily on CDCA7 proteins for CG methylation maintenance of the associated DNA. Loss of H1 restores heterochromatic DNA methylation in cdca7a cdca7b mutants, indicating that CDCA7A and CDCA7B mainly remodel H1-containing nucleosomes for methyltransferases to access DNA. Notably, in h1.1 h1.2 mutants, CG methylation shows a significant increase in centromeres, which reveals a new inhibitory role of H1 in DNA methylation maintenance within satellite repeat arrays. Centromeric DNA hypermethylation is lost in h1.1 h1.2 cdca7a cdca7b quadruple mutants, demonstrating that CDCA7A and CDCA7B can act independently of H1 to enhance MET1 activity. Overall, these findings establish CDCA7A and CDCA7B as conserved regulators of DNA methylation within heterochromatin and centromeric satellite repeat arrays.
- organism: Arabidopsis
- assay: DNA methylation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 2
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