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Small Molecule-Catalyzed Deamination: Applications in Transcriptome-Wide Profiling of N6-Methyladenosine in RNA (Maize)

ABSTRACT: Small Molecule-Catalyzed Deamination: Applications in Transcriptome-Wide Profiling of N6-Methyladenosine in RNA (Maize)

PROVIDER: PRJNA1119229 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR29259135_1.fastq.gz	Fastqsanger.gz
	SRR29259135_2.fastq.gz	Fastqsanger.gz
	SRR29259136_1.fastq.gz	Fastqsanger.gz
	SRR29259136_2.fastq.gz	Fastqsanger.gz
	SRR29259137_1.fastq.gz	Fastqsanger.gz

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Small Molecule-Catalyzed Deamination: Applications in Transcriptome-Wide Profiling of N6-Methyladenosine in RNA (Arabidopsis)

Project description:We present a novel N-nitrosation strategy for deamination capable of tolerating DNA/RNA biological macromolecules under mild conditions. A cooperative catalysis combining a carbonyl organocatalyst with a Lewis acid catalyst facilitates the formation of a C-nitro intermediate from a primary amine, which, upon rearrangement into N-nitrosamine, leads to selective deamination of unsubstituted canonical DNA/RNA bases under mild conditions. We employed this new approach to deamination of adenine into hypoxanthine, read as guanine by reverse transcriptases or DNA polymerases, while N6-methyladenosine (m6A) sites resist deamination and remain identified as adenine. We therefore report a chemically mild, low-input detection method for adenosine methylation sequencing at base resolution, named Chemical cooperative catalysis-Assisted for m6A sequencing (CAM-seq).

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Project description:We report evolved TadA-assisted N6-methyladenosine sequencing (eTAM-seq), an enzyme-assisted sequencing technology for quantitative, base-resolution profiling of m6A. eTAM-seq functions by global adenosine deamination, enabling detection of m6A as persistent A. We demonstrate adenosine-to-inosine (I) conversion rates up to 99% using a hyperactive TadA variant. With eTAM-seq, we profile and quantify m6A in the whole transcriptomes of HeLa cells and mouse embryonic stem cells (mESCs), with simultaneous deconvolution of the transcriptome and epitranscriptome. Further, we showcase deep sequencing-free, site-specific m6A quantification with as few as 10 cells, an input demand that is at least 4 orders of magnitude lower than existing methods. Collectively, eTAM-seq enables sensitive detection and faithful quantification of m6A with limited RNA input, representing a novel solution to deciphering the epitranscriptome.

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