Dingdong Zhang

Multiple gene methylation of nonsmall cell lung cancers evaluated with 3‐dimensional microarray

Aberrant DNA methylation of the CpG islands for cancer‐related genes is among the earliest and most frequent alterations in cancer and may be useful for diagnosing cancer or evaluating recurrent disease.

A novel method to quantify local CpG methylation density by regional methylation elongation assay on microarray

BackgroundDNA methylation based techniques are important tools in both clinical diagnostics and therapeutics. But most of these methods only analyze a few CpG sites in a target region. Indeed, difference of site-specific methylation may also lead to a change of methylation density in many cases, and it has been found that the density of methylation is more important than methylation of single CpG site for gene silencing.ResultsWe have developed a novel approach for quantitative analysis of CpG methylation density on the basis of microarray-based hybridization and incorporation of Cy5-dCTP into the Cy3 labeled target DNA by using Taq DNA Polymerase on microarray. The quantification is achieved by measuring Cy5/Cy3 signal ratio which is proportional to methylation density. This methylation-sensitive technique, termed RMEAM (regional methylation elongation assay on microarray), provides several advantages over existing methods used for methylation analysis. It can determine an exact methylation density of the given region, and has potential of high throughput. We demonstrate a use of this method in determining the methylation density of the promoter region of the tumor-related gene MLH1, TERT and MGMT in colorectal carcinoma patients.ConclusionThis technique allows for quantitative analysis of regional methylation density, which is the representative of all allelic methylation patterns in the sample. The results show that this technique has the characteristics of simplicity, rapidness, specificity and high-throughput.

Identification of methylated regions with peak search based on Poisson model from massively parallel methylated DNA immunoprecipitation-sequencing data.

DNA methylation is one of the most important epigenetic modification types, which plays a critical role in gene expression. High efficient surveying of whole genome DNA methylation has been aims of many researchers for long. Recently, the rapidly developed massively parallel DNA‐sequencing technologies open the floodgates to vast volumes of sequence data, enabling a paradigm shift in profiling the whole genome methylation. Here, we describe a strategy, combining methylated DNA immunoprecipitation sequencing with peak search to identify methylated regions on a whole‐genome scale. Massively parallel methylated DNA immunoprecipitation sequencing combined with methylation DNA immunoprecipitation was adopted to obtain methylated DNA sequence data from human leukemia cell line K562, and the methylated regions were identified by peak search based on Poison model. From our result, 140 958 non‐overlapping methylated regions have been identified in the whole genome. Also, the credibility of result has been proved by its strong correlation with bisulfite‐sequencing data (Pearson R2=0.92). It suggests that this method provides a reliable and high‐throughput strategy for whole genome methylation identification.

Microarray Detection of Fetal DNA Levels in Maternal Plasma

Abstract The discovery of fetal DNA in maternal plasma has made non‐invasive prenatal diagnosis possible. Microarrays are promising tools for detecting fetal DNA for such purposes. We report the development of a microarray based quantitative detection method and the investigation of fetal DNA levels at different gestation ages and in abnormal pregnancies. Samples from 66 male carriers at different gestation stages and 6 male carriers from abnormal pregnancies were collected and DNA microarrays were used to measure the level of fetal DNA in maternal plasma in these samples. The male‐specific DYS gene was used as the male fetus marker. Results showed that the fetal DNA levels in maternal plasma increased with the gestation age. The level of fetal DNA in Downs syndrome pregnancy samples was higher than in control samples, while no differences were found between gestational hypertension samples and the control.