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Ribosome Footprinting (RiboSeq) analysis of mRNA translation in HEK293T WT and METTL2A/2B/6 knockout cells

ABSTRACT: Ribosome Footprinting (RiboSeq) analysis of mRNA translation in HEK293T WT and METTL2A/2B/6 knockout cells

PROVIDER: PRJNA926112 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR23176614.fastq.gz	Fastqsanger.gz
	SRR23176615.fastq.gz	Fastqsanger.gz
	SRR23176616.fastq.gz	Fastqsanger.gz
	SRR23176617.fastq.gz	Fastqsanger.gz
	SRR23176618.fastq.gz	Fastqsanger.gz

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Ribosome Footprinting (RiboSeq) analysis of mRNA translation in HEK293T WT and METTL2A/2B/6 knockout cells

Project description:The ‘epitranscriptome’ includes a diversity of RNA modifications that influence gene expression. N3-methylcytidine (m3C) mainly occurs in the anticodon loop (position C32) of certain tRNAs yet its role is poorly understood. Here, using HAC-Seq, we report comprehensive METTL2A/B-, METTL6-, and METTL2A/B/6-dependent m3C profiles in human cells. METTL2A/B modifies most tRNA-Arginine and tRNA-Threonine members, whereas METTL6 modifies the tRNA-Serine family. However, decreased m3C32 on tRNA-Ser-GCT isodecoders was only observed with combined METTL2A/B/6 deletion. Ribo-Seq revealed altered translation of genes related to cell cycle and DNA repair pathways in METTL2A/2B/6-deficient cells, and these mRNAs are enriched in AGU codons that require tRNA-Ser-GCT for translation. These results, supported by reporter assays, help explain the observed slowed proliferation, altered cell cycle, and increased Cisplatin-sensitivity phenotypes of METTL2A/B/6-deficient cells. Thus, we define METTL2A/B/6-dependent methylomes and uncover a particular requirement of m3C tRNA modification for Serine codon-biased mRNA translation of cell cycle, and DNA repair genes.

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Project description:We treated HEK293T cells with different doses of RNase and sequence RNA fragements after the treatments. Furthermore, we developed a low-input RNase footprinting approach to quantify genome-wide RNA translation using 50,000 and 1,000 HEK293T and K562 cells. The ribosome profiling and RNA-seq data were used as the control.

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