Genome-wide DNA methylation profiling using Infinium<sup>®</sup> assay

Bibikova, Marina; Le, Jennie; Barnes, Bret; Saedinia-Melnyk, Shadi; Zhou, Lixin; Shen, Richard; Gunderson, Kevin L.

doi:10.2217/epi.09.14

Cited by 534 publications

(445 citation statements)

References 34 publications

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“…The primary alternate approach to methylation analysis that does not use NGS is high density microarrays (Bibikova et al 2009;Bibikova et al 2011). These micorarrays are adaptations of SNP microarrays widely used in the genetics field, coupled with bisulfite conversion.…”

Section: Methylation Microarraysmentioning

confidence: 99%

Analysis of DNA modifications in aging research

et al. 2018

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As geroscience research extends into the role of epigenetics in aging and age-related disease, researchers are being confronted with unfamiliar molecular techniques and data analysis methods that can be difficult to integrate into their work. In this review, we focus on the analysis of DNA modifications, namely cytosine methylation and hydroxymethylation, through nextgeneration sequencing methods. While older techniques for modification analysis performed relative quantitation across regions of the genome or examined average genome levels, these analyses lack the desired specificity, rigor, and genomic coverage to firmly establish the nature of genomic methylation patterns and their response to aging. With recent methodological advances, such as whole genome bisulfite sequencing (WGBS), bisulfite oligonucleotide capture sequencing (BOCS), and bisulfite amplicon sequencing (BSAS), cytosine modifications can now be readily analyzed with base-specific, absolute quantitation at both cytosine-guanine dinucleotide (CG) and non-CG sites throughout the genome or within specific regions of interest by next-generation sequencing. Additional advances, such as oxidative bisulfite conversion to differentiate methylation from hydroxymethylation and analysis of limited input/single-cells, have great promise for continuing to expand epigenomic capabilities. This review provides a background on DNA modifications, the current state-of-theart for sequencing methods, bioinformatics tools for converting these large data sets into biological insights, and perspectives on future directions for the field.

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Section: Methylation Microarraysmentioning

confidence: 99%

Analysis of DNA modifications in aging research

et al. 2018

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“…The Illumina Infinium HumanMethylation27 (HM27) BeadChip (Illumina) was used to interrogate the DNA methylation status of 27,578 individual CpG sites located at promoter regions of 14,495 genes (Bibikova et al 2009). Briefly, 1 lg of genomic DNA was bisulfite-converted using the EZ-96 DNA Methylation Kit (Zymo Research) according to the manufacturer's protocol.…”

Section: Dnmt Activity Assaymentioning

confidence: 99%

“…DNA methylation b-values represent the ratio of the intensity of the methylated bead type to the combined locus intensity ranging from 0 to 1. Values close to 0 indicate low levels of DNA methylation, while values close to 1 indicate high levels of DNA methylation (Bibikova et al 2009). The detection P-values measure the difference of the signal intensities at the interrogated CpG site compared with those from a set of 16 negative control probes embedded in the assay.…”

Section: Dnmt Activity Assaymentioning

confidence: 99%

“…We determined the b-value difference of 0.2 as having 99 % confidence based on intra-and inter-assay variations (Bibikova et al 2009). …”

Section: Dnmt Activity Assaymentioning

confidence: 99%

“…We used a b-value difference (|Db|) of 0.20 as a threshold for differential DNA methylation between Sense and Control-S and between siRNA and Control-si. This threshold of |Db| = 0.20 was determined previously as a stringent estimate of Db detection sensitivity across the range of b-values (Bibikova et al 2009). Gene expression data with (1) a fold change greater or less than 1.3 and (2) a one-way ANOVA with a Benjamini and Hochberg-corrected P-value B0.05 were used for integrated analysis.…”

Section: Dnmt Activity Assaymentioning

confidence: 99%

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γ-Glutamyl hydrolase modulation significantly influences global and gene-specific DNA methylation and gene expression in human colon and breast cancer cells

et al. 2014

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c-Glutamyl hydrolase (GGH) plays an important role in folate homeostasis by catalyzing hydrolysis of polyglutamylated folate into monoglutamates. Polyglutamylated folates are better substrates for several enzymes involved in the generation of S-adenosylmethionine, the primary methyl group donor, and hence, GGH modulation may affect DNA methylation. DNA methylation is an important epigenetic determinant in gene expression, in the maintenance of DNA integrity and stability, and in chromatin modifications, and aberrant or dysregulation of DNA methylation has been mechanistically linked to the development of human diseases including cancer. Using a recently developed in vitro model of GGH modulation in HCT116 colon and MDA-MB-435 breast cancer cells, we investigated whether GGH modulation would affect global and gene-specific DNA methylation and whether these alterations were associated with significant gene expression changes. In both cell lines, GGH overexpression decreased global DNA methylation and DNA methyltransferase (DNMT) activity, while GGH inhibition increased global DNA methylation and DNMT activity. Epigenomic and gene expression analyses revealed that GGH modulation influenced CpG promoter DNA methylation and gene expression involved in important biological pathways including cell cycle, cellular development, and cellular growth and proliferation. Some of the observed altered gene expression appeared to be regulated by changes in CpG promoter DNA methylation. Our data suggest that the GGH modulation-induced changes in total intracellular folate concentrations and content of long-chain Electronic supplementary material The online version of this article

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