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. 2021 Apr;16(4):425-435.
doi: 10.1080/15592294.2020.1805684. Epub 2020 Aug 12.

Comprehensive analysis of the transcriptome-wide m6A methylome in colorectal cancer by MeRIP sequencing

Affiliations

Comprehensive analysis of the transcriptome-wide m6A methylome in colorectal cancer by MeRIP sequencing

Zhen Zhang et al. Epigenetics. 2021 Apr.

Abstract

Accumulating evidence has demonstrated that N6-methyladenosine (m6A) plays important roles in various cancers, making it essential to profile m6A modifications at a transcriptome-wide scale in colorectal cancer (CRC). In the present study, we performed high-throughput sequencing to determine the m6A methylome in CRC. We obtained six pairs of CRC samples and tumour-adjacent normal tissues from Peking University People's Hospital. We used MeRIP-seq to determine that compared to the tumour-adjacent normal tissues, the CRC samples had 1343 dysregulated m6A peaks, and 625 m6A peaks were significantly upregulated and 718 m6A peaks were significantly downregulated. Genes with altered m6A peaks play critical roles in regulating glucose metabolism, RNA metabolism, and cancer stem cells. Furthermore, we identified 297 hypermethylated m6A peaks and 328 hypomethylated m6A peaks in mRNAs through conjoint analyses of MeRIP-seq and RNA-seq data. After analysing these genes with differentially methylated m6A peaks and synchronously differential expression, we identified four genes (WDR72, SPTBN2, MORC2, and PARM1) that were associated with prognosis of colorectal cancer patients by searching The Cancer Genome Atlas (TCGA). Our study suggests that m6A modifications play important roles in tumour progression and survival of CRC patients. The results also indicate that modulating m6A modifications may represent an alternative strategy to predict the survival of cancer patients and interfere with tumour progression in the future.

Keywords: M6A; MeRIP sequencing; colorectal cancer.

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Conflict of interest statement

The authors declare no conflicts of interest for this article.

Figures

Figure 1.
Figure 1.
Characteristics of m6A methylation in CRC
Figure 2.
Figure 2.
GO and KEGG pathway analyses of differentially methylated mRNA
Figure 3.
Figure 3.
Conjoint analysis of MeRIP-seq and RNA-seq data
Figure 4.
Figure 4.
The relationship between gene expression regulated by m6A modification and clinical parameters in TCGA database

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