Validation of a DNA methylation microarray for 285, 000 CpG sites in the mouse genome. Issue 12 (2nd December 2022)

• Record Type: Journal Article
• Authors: Garcia-Prieto, Carlos A.; Álvarez-Errico, Damiana; Musulen, Eva; Bueno-Costa, Alberto; N. Vazquez, Berta; Vaquero, Alejandro; Esteller, Manel
• Is Part Of: Epigenetics. Volume 17:Issue 12(2022)
• Page Start: 1677
• Page End: 1685
• Publication Date: 2022-12-02
• Subjects: Mouse -- DNA methylation -- microarray -- epigenetics -- CpG sites -- validation; Epigenesis -- Periodicals; Epigenetica; 572.86505
• DOI: 10.1080/15592294.2022.2053816
• Languages: English
• ISSNs: 1559-2294

Abstract

ABSTRACT: Mouse has been extensively used as a model organism in many studies to characterize biological pathways and drug effects and to mimic human diseases. Similar DNA sequences between both species facilitate these types of experiments. However, much less is known about the mouse epigenome, particularly for DNA methylation. Progress in delivering mouse DNA methylomes has been slow due to the currently available time-consuming and expensive methodologies. Following the great acceptance of the human DNA methylation microarrays, we have herein validated a newly developed DNA methylation microarray (Infinium Mouse Methylation BeadChip) that interrogates 280, 754 unique CpG sites within the mouse genome. The CpGs included in the platform cover CpG Islands, shores, shelves and open sea sequences, and loci surrounding transcription start sites and gene bodies. From a functional standpoint, mouse ENCODE representative DNase hypersensitivity sites (rDHSs) and candidate cis-Regulatory Elements (cCREs) are also included. Herein, we show that the profiled mouse DNA methylation microarray provides reliable values among technical replicates; matched results from fresh frozen versus formalin-fixed samples; detects hemimethylated X-chromosome and imprinted CpG sites; and is able to determine CpG methylation changes in mouse cell lines treated with a DNA demethylating agent or upon genetic disruption of a DNA methyltransferase. Most important, using unsupervised hierarchical clustering and t-SNE approaches, the platform is able to classify all types of normal mouse tissues and organs. These data underscore the great features of the assessed microarray to obtain comprehensive DNA methylation profiles of the mouse genome.