MeRIP-Sequencing Service

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Arraystar m6A-seq profiles the most prominent epitranscriptomic m6A modification by methylated RNA immunoprecipitation sequencing (MeRIP-seq).


Superb expertise: Decade of experience and skills in DNA/RNA modification profiling.

Unlimited range: Covers the m6A methylation in any transcript regions.

High resolution: Accurate peak positioning within 100 bases of the m6A sites.

High accuracy: m6A levels calibrated with the transcript abundance in the input control.

Stringent QC: High MeRIP efficiency verified by MeRIP-PCR.

Publication ready: Differential methylation analysis, m6A peak distribution, and motif identification.

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MeRIP-Sequencing Service

m6A peak distribution in the transcriptome 



Visualization of m6A peaks


Fig 1. m6A peaks in human ADAR1 and UBE2Q1 mRNAs are visualized by loading the provided track files in a genome browser


Distribution of m6A peak reads across mRNA regions


Fig 2. Peak stats (a) and density distribution (b) of m6A peaks in 5’UTR, CDS, and 3’UTR regions of the mRNAs.


Motif analysis of m6A peak sequences


Fig 3. Sequence motifs in the m6A peaks are identified with DREME algorithm and shown in sequence logo representation.

Your samples
Purified total RNA, or frozen tissues, or cell pellets

Please refer to Sample Submission for details in how to get your project started.

Arraystar MeRIP-seq

1. Total RNA isolation (Optional)
2. RNA QC and mRNA isolation from the total RNA
3. mRNA fragmentation
4. m6A immunoprecipitation with anti-N6-methyladenosine (m6A) antibody
5. IP efficiency QC by qPCR
6. Sequencing library preparation
7. Cluster generation
8. Sequencing by illumina platform
9. Data analysis, including alignment, peak calling and annotation, motif analysis, differentially methylated peak analysis, GO and Pathway analysis.

m6A modification of HSATIII lncRNAs regulates temperature-dependent splicing. Ninomiya K, et al. The EMBO Journal, 2021

A defined N6-methyladenosine (m6A) profile conferred by METTL3 regulates muscle stem cell/myoblast state transitions. Gheller B J, et al. Cell Death Discovery, 2020

MTHFD2 links RNA methylation to metabolic reprogramming in renal cell carcinoma. Green N H, et al. Oncogene, 2019