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Locate and Quantify the Exact m6A Site at Single Nucleotide Resolution

Profiling m6A at single nucleotide resolution has been challenging. Conventional methods such as m6A/MeRIP-seq cannot precisely identify which adenosines in a MeRIP-seq peak are actually modified, nor can they quantify the modification fraction for each site [1].

To address these challenges, Arraystar has developed m6A Single Nucleotide Arrays based on methyl-sensitive MazF RNase that precisely locate the m6A modification at exact adenosine and quantify the stoichiometry of m6A modification fractions.

The arrays add invaluable benefits which are lacking for conventional methods:

• High tolerant of poor quality RNAs extracted from serum, plasma, exosomes, or FFPE samples.

• Low demand for sample amounts, as low as 1 ug total RNA.

• Precise detection of m6ACA at single nucleotide resolution.

• Quantifying m6A modification stoichiometry and abundance.

• Specialized pipeline to collect and annotate the quantifiable m6ACA sites(Table 1).


Table 1. Systematic annotation for m6A sites

TransID m6A_Transcript_Location Gene Symbol Trans_Biotype m6A_Site_Locus m6A Location
NM_080598 547 DDX39B protein_coding chr1:201845569-201845570_+ 3'UTR
NM_213589 3952 RAPH1 protein_coding chr6:31508289-31508290_- cDs

m6A Conservation Transcript Length Transcript sequence
m6A Conservation Transcript Length Transcript sequence
NM_213589 3952 RAPH1

Customer Success Story: Specific RNA m6A modification sites in bone marrow mesenchymal stem cells from the jawbone marrow of type 2 diabetes patients with dental implant failure. Int J Oral Sci, 2023, 15(1):6 [PMID:36631441].



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Reference:
[1] Garcia-Campos M A, Edelheit S, Toth U, et al. Deciphering the "m(6)A Code" via Antibody-Independent Quantitative Profiling. Cell, 2019,178(3):731-747.




Selected Publications

• Epitranscriptomic Array
   [PMID: 38355624] Xiong YW, et al.
   (2024) Nature Communications

• Small RNA Modification Array
   [PMID: 38747146] Zhang J, et al.
   (2024) Circulation Research

• Circular RNA Array
   [PMID: 39695693] Hu Y, et al.
   (2024) Molecular Cancer

• tRNA Sequencing
   [PMID: 38519786] Wu X, et al.
   (2024) Nature Cancer

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