This article is part of the supplement: The 2010 International Conference on Bioinformatics and Computational Biology (BIOCOMP 2010): Systems Biology
An integrative analysis of DNA methylation and RNA-Seq data for human heart, kidney and liver
1 Department of Biochemistry and Molecular Biology, University of North Dakota School of Medicine, Grand Forks, ND 58201, USA
2 Bioinformatics Core, University of North Dakota School of Medicine, Grand Forks, ND 58201, USA
3 Department of Pathology, University of North Dakota School of Medicine, Grand Forks, ND 58201, USA
Citation and License
BMC Systems Biology 2011, 5(Suppl 3):S4 doi:10.1186/1752-0509-5-S3-S4Published: 23 December 2011
Many groups, including our own, have proposed the use of DNA methylation profiles as biomarkers for various disease states. While much research has been done identifying DNA methylation signatures in cancer vs. normal etc., we still lack sufficient knowledge of the role that differential methylation plays during normal cellular differentiation and tissue specification. We also need thorough, genome level studies to determine the meaning of methylation of individual CpG dinucleotides in terms of gene expression.
In this study, we compiled unique DNA methylation signatures from normal human heart, lung, and kidney using the Illumina Infinium 27K methylation arrays and compared those to gene expression by RNA sequencing. We have identified unique signatures of global DNA methylation for human heart, kidney and liver, and showed that DNA methylation data can be used to correctly classify various tissues. It indicates that DNA methylation reflects tissue specificity and may play an important role in tissue differentiation. The integrative analysis of methylation and RNA-Seq data showed that gene methylation and its transcriptional levels were comprehensively correlated. The location of methylation markers in terms of distance to transcription start site and CpG island showed no effects on the regulation of gene expression by DNA methylation in normal tissues.
This study showed that an integrative analysis of methylation array and RNA-Seq data can be utilized to discover the global regulation of gene expression by DNA methylation and suggests that DNA methylation plays an important role in normal tissue differentiation via modulation of gene expression.