Genome-wide DNA methylation profile change in cancer cell lines under stresses Open Access

Wang, Qingyu (Spring 2020)

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As one of the most studied epigenetic mechanisms, DNA methylation profile provides additional information beyond DNA sequence. Differentially methylated regions have been found to be associated with various diseases. DNA methylation has also been shown to be linked to tumorigenesis. In this study, we take HeLa cell line and D54 cell line as examples to analyze the genome-wide DNA methylation profile change in the cells when they go through different stress conditions including cold shock (TEMP), nutrition depletion (FBS, DPR), chemotherapy agent (MeP) and low glucose (GLUC). We conducted the experiment in two batches and collected the methylation status data (β values) from several replicated samples of each condition (control and stresses). After applying quality control and normalization to the data, we identified the differentially methylated positions (DMPs) in each pairwise comparison group (each stress vs. control) using the combinations of functions in the “minfi” package and a non-parametric test with balanced permutation, and found their nearby regions (genes). Then we tried to find the overlapped DMPs and overlapped differentially methylated (DM) genes among all these comparisons.

Hundreds of DMPs were identified for each pairwise comparison. Since the methylation changes in CTRL vs. TEMP and CTRL vs. DPR group are not very consistent with other data, we only focused on the overlaps between HeLa MeP, HeLa FBS, HeLa Glucose and D54 MeP groups. Only one overlapped DMP was found between HeLa MeP and FBS groups, while there was none overlapped DMP was found between D54 MeP and other HeLa stresses. There are 72, 21 and 12 overlapped DM genes between HeLa MeP and FBS, HeLa Glucose and MeP and FBS, and D54 MeP and other HeLa, respectively. Thus, in our study, we conclude that HeLa and D54 cell lines share DMRs under different stress conditions. Also we found that the 12 overlapped DMRs is not related to the distribution of mutations in cancer cells. For further studies, we plan to find biological properties they share (such as pathways) and explore more about the functions and roles the overlapped genes have.

Table of Contents

1.       Introduction

2.       Methods

2.1.   Methylation Data

2.2.   Quality Control

2.3.   Quantile Normalization

2.4.   Methylation Change Analyses

3.       Results

4.       Discussion

4.1.   Interpretation of Results

4.2.   Further Studies

4.3.   Limitations


Appendix. Figures and Tables

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