Abstract
N (6)-Methyladenosine (m(6)A) is a key base modification that regulates RNA stability and translation during viral infection. While m(6)A methylation of host mRNAs has been studied in SARS-CoV-2-infected cells, its role in long noncoding RNAs (lncRNAs) is unknown. Here, we analyzed direct RNA sequencing (dRNA-seq) data from infected human lung cells (Calu-3) using a machine learning m(6)A detection framework. We observed a global increase in m(6)A levels across 10 antiviral response-associated lncRNAs, with UCA1, GAS5, and NORAD-regulators of interferon (IFN) signaling-showing the most pronounced changes. This might, in part, explain the attenuated IFN expression observed in infected cells. We identified methylated DRACH motifs in predicted lncRNA duplex-forming regions, which may favor Hoogsteen base-pairing, which destabilize secondary structures and target interaction sites. These results provide new perspectives on how SARS-CoV-2 could impact lncRNAs to modulate host immunity and viral persistence through m(6)A-dependent mechanisms.