key: cord-1005789-5cviw6kl
authors: An, Sanqi; Xie, Zhouhua; Liao, Yanyan; Jiang, Junjun; Dong, Wenyi; Yin, Fuqiang; Li, Wen-Xing; Ye, Li; Lin, Jianyan; Liang, Hao
title: Systematic analysis of clinical relevance and molecular characterization of m6A in COVID-19 patients
date: 2022-01-05
journal: Genes Dis
DOI: 10.1016/j.gendis.2021.12.005
sha: dc9f224332bc8b8b0d5eae4df69ba3a2f93aaba0
doc_id: 1005789
cord_uid: 5cviw6kl

The outbreak of coronavirus disease 2019 (COVID-19) has affected more than 200 countries and regions to date. mRNA m6A methylation has been reported as a new therapeutic target in COVID-19 patients, and has received widespread attention. However, the effects of m6A on COVID-19 clinical features as well as the molecular characterization of m6A in real COVID-19 patients are largely unclear. We collected RNA-seq data and clinical data from 100 COVID-19 patients, and sequenced m6A-seq from peripheral blood mononuclear cells (PBMCs) of two COVID-19 patients. Using bioinformatics analysis, we found that m6A is associated with several clinical features of COVID-19 patients. Furthermore, molecular characterization of m6A of COVID-19 patients in vivo rather than cell lines is demonstrated for the first time. Our findings will be valuable for the development of novel treatment strategies for COVID-19 patients.

modifications, acting as m 6 A writers (1) . m 6 A demethylase ALKBH5 as well as m 6 A 39 demethylase FTO mediate the demethylation of m 6 As, acting as the m 6 A erasers (3). 40

A variety of proteins including YTH domain-containing proteins can bind m 6 A marks 41 as the m 6 A readers (4). The role of mRNA m 6 A methylation in COVID-19 patients is 42 of great concern (5-8) due to reports that m 6 A may provide potential new strategies 43 for the development of vaccine and antiviral drug (6). For Ontology analysis was performed using DAVID (12). Differential gene expression 79 analyses were performed based on the input data using DESeq2 (13). 80

3. Analyses of m 6 A-seq data 81 brief, we made sliding windows of 100 bp with 50 bp overlap on the exon regions and 83 calculated the RPKM of each window. The sliding windows with winscore 84 (enrichment score) >2 were identified as m 6 A peaks. The m 6 A ratio of each m 6 A peak 85 was calculated as the RPKM (without adding 1) of IP library divided by the RPKM 86 (without adding 1) of input library. m 6 A ratios based on the denominators (peak 87 RPKM of input) <5 were treated as NAs (not available) in the downstream analyses. 88 (Fig. S1E) , which are consistent with the results of one previous study 132 (5). In that study, the mechanism of m 6 A affecting SARS-CoV-2 replication is verified 133 by wet experiments in vitro (5). Furthermore, the pathway enrichment analysis show 134 that immune functions were disturbed (Fig. S1F) . 135

Taken together, our study reported that m 6 A is associated with multiple clinical state 136 of COVID-19 patients, supporting the strategy that m 6 A could be act as a therapeutic 137 target for COVID-19 patients. In fact, one previous study has shown that a highly 138 specific METTL3 inhibitor is able to inhibit the replication of SARS-CoV-2 (5). 

Integrative network analysis identifies 180 cell-specific trans regulators of m6A

)A modification in coding and non-coding RNAs: 182 roles and therapeutic implications in cancer

Function and evolution of RNA N6-methyladenosine 184 modification

YTHDF2 promotes the liver cancer stem cell 186 phenotype and cancer metastasis by regulating OCT4 expression via m6A RNA 187 methylation

Targeting the m(6)A RNA 189 modification pathway blocks SARS-CoV-2 and HCoV-OC43 replication

RBM15-mediated N6-methyladenosine 192 modification affects COVID-19 severity by regulating the expression of multitarget 193 genes

METTL3 regulates viral m6A RNA modification and 195 host cell innate immune responses during SARS-CoV-2 infection

The m(6)A methylome of SARS-CoV-2 in host cells

Safety and immunogenicity of an inactivated 200 SARS-CoV-2 vaccine, BBIBP-CorV: a randomised, double-blind, placebo-controlled, 201 phase 1/2 trial

Graph-based genome 203 alignment and genotyping with HISAT2 and HISAT-genotype

StringTie enables improved reconstruction of a transcriptome from RNA-seq reads

Bioinformatics enrichment tools: paths 209 toward the comprehensive functional analysis of large gene lists

RNA-Seq workflow: gene-level exploratory 212 analysis and differential expression

Dynamic transcriptomic m(6)A decoration: 214 writers, erasers, readers and functions in RNA metabolism

m(6)A regulator-mediated 217 methylation modification patterns and tumor microenvironment infiltration 218 characterization in gastric cancer