Screening and Verification of Differentially Expressed Long Non-coding RNAs in the Peripheral Blood of Patients With asthma

• Published in: Frontiers in pharmacology Vol. 13; p. 834009
• Main Authors: Ma, Cheng, Wang, Shiyuan, Cao, Yuxue, Tang, Weifeng, Wuniqiemu, Tulake, Teng, Fangzhou, Zhu, Xueyi, Wei, Ying, Dong, Jingcheng
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 22.02.2022
• Subjects: asthma; bioinformatics; full transcriptome sequencing; lncRNAs; mRNAs; Pharmacology; lncRNAs; asthma; full transcriptome sequencing; mRNAs; bioinformatics
• ISSN: 1663-9812; 1663-9812
• DOI: 10.3389/fphar.2022.834009

Growing evidence suggests that long non-coding RNAs (lncRNAs) play a key role in the pathogenesis of asthma. Although some differentially expressed lncRNAs have been identified in asthmatic patients, many asthma-related lncRNAs have not been annotated. In the present study, six patients and three healthy subjects were randomly selected from 34 asthmatic patients and 17 healthy subjects. Second-generation high-throughput sequencing was performed on their peripheral blood samples. There were 1,137 differentially expressed lncRNAs in the asthma patients compared to in the healthy controls, of which 485 were upregulated and 652 were downregulated. The top 30 enriched GO and KEGG terms were identified, and the cytosolic ribosome (GO:0022626) and ribosome (hsa03010) were associated with the most differentially expressed lncRNAs. The top 10 differentially expressed lncRNAs associated with asthma were verified by an lncRNA-mRNA co-expression network and RT-qPCR. Seven of the these (NONHSAT015495.2, MSTRG.71212.2, NONHSAT163272.1, NONHSAT181891.1, NONHSAT190964.1, ENST00000564809, and NONHSAT076890.2) were down-regulated in the peripheral blood of asthmatic patients, which was consistent with the sequencing results. Three patients and three healthy subjects were randomly selected from the remaining subjects to verify these seven lncRNAs by RT-qPCR, which further confirmed the sequencing results. Public database GSE106230 was also in agreement with the FPKM (Fragments Per kilobase of exon model per Million mapped reads) trends of ENST00000564809, NONHSAT015495.2, NONHSAT181891.1, and NONHSAT190964.1. In conclusion, the present study identified seven lncRNAs that may serve as potential biological markers for asthma.