An integrative analysis of DNA methylation and RNA-Seq data for human heart, kidney and liver.
BACKGROUND
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.


RESULTS
In this study, we have used (insert statistical method here) to compile unique DNA methylation signatures from normal human heart, lung, and kidney using the Illumina Infinium 27 K 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.


CONCLUSIONS
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.
Department of Biochemistry and Molecular Biology, University of North Dakota School of Medicine, Grand Forks, ND 58201, USA.
Linglin
L
Xie
Brent
B
Weichel
Joyce Ellen
JE
Ohm
Ke
K
Zhang
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D019175:DNA Methylation; D005786:Gene Expression Regulation / Q000235:genetics; D006801:Humans; D007668:Kidney / Q000378:metabolism*; D008099:Liver / Q000378:metabolism*; D009206:Myocardium / Q000378:metabolism*; D009928:Organ Specificity; D017423:Sequence Analysis, RNA / Q000379:methods*