Construction of DNA methylation analysis platform based on high-throughput sequencing

Author(s):  
Jiangyu Li ◽  
Dongsheng Zhao ◽  
Jiakuan Li ◽  
Siqing Zhao ◽  
Xiaolei Wang
2020 ◽  
Author(s):  
Guangmou Zhang ◽  
Huigen Feng ◽  
Zhiqing Yuan

Abstract Background: The relationship between epigenetic abnormalities and tumorigenesi has been investigated in the past decade and made major advances, particularly the abnormal expression of small RNAs, DNA methylation, and histone modification in cancer. In many tumor-related studies, the regulatory changes in DNA methylation during cancer development and the development of resistance to anticancer drugs have show that DNA methylation can be used as a biomarker for cancer diagnosis and concomitant diagnosis, but there is a lack of clinically useful biomarkers associated with hepatic carcinoma. Using high-throughput sequencing technology, appropriate testing and validation can be carried out in large samples. The relationship between DNA methylation and tumor development can be explored, contributing to clinical diagnosis and personalized treatment of hepatic carcinoma. Methods: In this study, we implemented and evaluated the effectiveness of high-throughput sequencing for DNA methylation analysis in hepatic carcinoma. For the relationship between DNA methylation and gene expression, Pearson correlation analysis was used to evaluate the correlation. Twenty-five isolated genomic regions were amplified by PCR using bisulfite-transformed liver cancer tissue (Ca) and paracancer tissue (T) as template DNA. PCR final product sequence information was obtained by sequence analysis using Illumina Hiseq/Miseq platform. Results: The average depth of coverage across all amplicons was 30,548 for T and 29,346 for Ca, with a maximum of 3,675 at the ARID1A amplicon and a minimum of 65 at the PTEN amplicon. Methylation spectra were obtained for each genomic locus of the two groups of samples, and the results showed that methylation was significantly different at the X target loci and slightly different at the Y target loci. Cluster analysis showed that all T tissues were clustered in one group (except tissues T2 and T3), while Ca tissues were clustered on the other side. The results showed that DNA methylation at the loci may be closely related to liver cancer, providing references for the research and development of biomarkers in clinical diagnosis. Conclusions: The study demonstrates that high-throughput sequencing technology is a powerful and cost-effective method for methylation analysis of target DNA in cancer tissues.


2013 ◽  
Vol 59 (3) ◽  
pp. 314-320 ◽  
Author(s):  
Benson H. MORRILL ◽  
Lindsay COX ◽  
Anika WARD ◽  
Sierra HEYWOOD ◽  
Randall S. PRATHER ◽  
...  

Methods ◽  
2010 ◽  
Vol 52 (3) ◽  
pp. 203-212 ◽  
Author(s):  
Ning Li ◽  
Mingzhi Ye ◽  
Yingrui Li ◽  
Zhixiang Yan ◽  
Lee M. Butcher ◽  
...  

Epigenomics ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 747-755
Author(s):  
Veronika Suni ◽  
Fatemeh Seyednasrollah ◽  
Bishwa Ghimire ◽  
Sini Junttila ◽  
Asta Laiho ◽  
...  

Aim: DNA methylation is a key epigenetic mechanism regulating gene expression. Identifying differentially methylated regions is integral to DNA methylation analysis and there is a need for robust tools reliably detecting regions with significant differences in their methylation status. Materials & methods: We present here a reproducibility-optimized test statistic (ROTS) for detection of differential DNA methylation from high-throughput sequencing or array-based data. Results: Using both simulated and real data, we demonstrate the ability of ROTS to identify differential methylation between sample groups. Conclusion: Compared with state-of-the-art methods, ROTS shows competitive sensitivity and specificity in detecting consistently differentially methylated regions.


2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Ram Vinay Pandey ◽  
Walter Pulverer ◽  
Rainer Kallmeyer ◽  
Gabriel Beikircher ◽  
Stephan Pabinger ◽  
...  

2011 ◽  
Vol 39 (7) ◽  
pp. e44-e44 ◽  
Author(s):  
Martin Kantlehner ◽  
Roland Kirchner ◽  
Petra Hartmann ◽  
Joachim W. Ellwart ◽  
Marianna Alunni-Fabbroni ◽  
...  

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