Genome-wide expression profiling of long non-coding RNAs and competing endogenous RNA networks in alopecia areata

Sisi Qi; Youyu Sheng; Ruiming Hu; Feng Xu; Ying Miao; Jun Zhao; Qinping Yang; Sisi Qi; Youyu Sheng; Ruiming Hu; Feng Xu; Ying Miao; Jun Zhao; Qinping Yang

doi:10.3934/mbe.2021037

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 1: 696-711. doi: 10.3934/mbe.2021037

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Research article

Genome-wide expression profiling of long non-coding RNAs and competing endogenous RNA networks in alopecia areata

Department of Dermatology, Huashan Hospital, Fudan University, 12 Cent Urumqi Rd, Shanghai 200040, China

Received: 14 July 2020 Accepted: 14 October 2020 Published: 18 December 2020

Background Long non-coding RNAs (lncRNAs) regulate gene expression in concert with microRNAs (miRNAs) and mRNAs. This study was designed to explore the potential roles of lncRNAs and their related competing endogenous RNA (ceRNA) networks in alopecia areata (AA). Methods This study comprised six participants (three AA patients and three healthy individuals) whose serum lncRNA profiles were evaluated by lncRNA sequencing. Following differential expression analysis, and function enrichment analysis, a lncRNA-miRNA-mRNA network was then constructed using various bioinformatics tools and validated using quantitative reverse-transcription PCR (qRT-PCR). Results We identified 220 mRNAs and 166 lncRNAs that were differentially expressed in AA patients. The differentially expressed mRNAs were predominantly associated with cytokine-cytokine receptor interactions, MAPK signaling and Ras signaling pathways. The differentially expressed lncRNAs were primarily associated with cytokine-cytokine receptor interactions, chemokine signaling pathways, axon guidance, and legionellosis. In addition, qRT-PCR analyses verified the upregulation of AC005562.1, AF131217.1, and RP11-251G23.5 and downregulation of RP11-231E19.1 in AA patients. Conclusion We constructed a complex ceRNA network for AA and discovered that various RP11 lncRNAs including RP11-251G23.5 and RP11-231E19 may play a crucial role in the pathogenesis of AA via the regulation of the cytokine-cytokine receptor interaction pathway, which could serve as a therapeutic target for alopecia areata in clinical interventions.
- sequencing,
- long non-coding RNAs,
- competing endogenous RNAs,
- differential expression analysis,
- alopecia areata
Citation: Sisi Qi, Youyu Sheng, Ruiming Hu, Feng Xu, Ying Miao, Jun Zhao, Qinping Yang. Genome-wide expression profiling of long non-coding RNAs and competing endogenous RNA networks in alopecia areata[J]. Mathematical Biosciences and Engineering, 2021, 18(1): 696-711. doi: 10.3934/mbe.2021037

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Abstract

Background Long non-coding RNAs (lncRNAs) regulate gene expression in concert with microRNAs (miRNAs) and mRNAs. This study was designed to explore the potential roles of lncRNAs and their related competing endogenous RNA (ceRNA) networks in alopecia areata (AA). Methods This study comprised six participants (three AA patients and three healthy individuals) whose serum lncRNA profiles were evaluated by lncRNA sequencing. Following differential expression analysis, and function enrichment analysis, a lncRNA-miRNA-mRNA network was then constructed using various bioinformatics tools and validated using quantitative reverse-transcription PCR (qRT-PCR). Results We identified 220 mRNAs and 166 lncRNAs that were differentially expressed in AA patients. The differentially expressed mRNAs were predominantly associated with cytokine-cytokine receptor interactions, MAPK signaling and Ras signaling pathways. The differentially expressed lncRNAs were primarily associated with cytokine-cytokine receptor interactions, chemokine signaling pathways, axon guidance, and legionellosis. In addition, qRT-PCR analyses verified the upregulation of AC005562.1, AF131217.1, and RP11-251G23.5 and downregulation of RP11-231E19.1 in AA patients. Conclusion We constructed a complex ceRNA network for AA and discovered that various RP11 lncRNAs including RP11-251G23.5 and RP11-231E19 may play a crucial role in the pathogenesis of AA via the regulation of the cytokine-cytokine receptor interaction pathway, which could serve as a therapeutic target for alopecia areata in clinical interventions.

References

[1]	L. C. Strazzulla, E. H. C. Wang, L. Avila, K. Lo Sicco, N. Brinster, A. M. Christiano, et al., Alopecia areata: Disease characteristics, clinical evaluation, and new perspectives on pathogenesis, J. Am. Acad. Derm., 78 (2018), 1–12.
[2]	J. H. Lee, H. J. Kim, K. D. Han, J. H. Han, C. H. Bang, Y. M. Park, et al., Incidence and prevalence of alopecia areata according to subtype: A nationwide, population-based study in South Korea (2006–2015), Brit. J. Derm., (2019).
[3]	E. Tan, Y. K. Tay, C. L. Goh, Y. Chin Giam, The pattern and profile of alopecia areata in Singapore--a study of 219 Asians, Int. J. Derm., 41 (2002), 748–753. doi: 10.1046/j.1365-4362.2002.01357.x
[4]	F. L. Xiao, S. Yang, J. B. Liu, P. P. He, J. Yang, Y. Cui, et al., The epidemiology of childhood alopecia areata in China: A study of 226 patients, Pediat. Derm., 23 (2006), 13–18. doi: 10.1111/j.1525-1470.2006.00161.x
[5]	S. Yang, J. Yang, J. B. Liu, H. Y. Wang, Q. Yang, M. Gao, et al., The genetic epidemiology of alopecia areata in China, Brit. J. Derm., 151 (2004), 16–23. doi: 10.1111/j.1365-2133.2004.05915.x
[6]	L. Petukhova, A. V. Patel, R. K. Rigo, L. Bian, M. Verbitsky, S. S. Cherchi, et al., Integrative analysis of rare copy number variants and gene expression data in Alopecia Areata implicates an etiological role for autophagy, Exp. Dermatol., (2019).
[7]	Z. X. Lei, W. J. Chen, J. Q. Liang, Y. J. Wang, L. Jin, C. Xu, et al., The association between rs2476601 polymorphism in PTPN22 gene and risk of alopecia areata: A meta-analysis of case-control studies, Medicine (Baltimore), 98 (2019), e15448.
[8]	T. R. Mercer, M. E. Dinger, J. S. Mattick, Long non-coding RNAs: Insights into functions, Nat. Rev. Genet., 10 (2009), 155–159. doi: 10.1038/nrg2521
[9]	V. Simion, S. Haemmig, M. W. Feinberg, LncRNAs in vascular biology and disease, Vascul. Pharmacol., 114 (2019), 145–156. doi: 10.1016/j.vph.2018.01.003
[10]	L. Bao, A. Yu, Y. Luo, T. Tian, Y. Dong, H. Zong, et al., Genomewide differential expression profiling of long non-coding RNAs in androgenetic alopecia in a Chinese male population, J. Eur. Acad. Dermatol. Venereol., 31 (2017), 1360–1371.
[11]	Y. Sheng, J. Ma, J. Zhao, S. Qi, R. Hu, Q. Yang, Differential expression patterns of specific long noncoding RNAs and competing endogenous RNA network in alopecia areata, J. Cell Biochem., 120 (2019), 10737–10747. doi: 10.1002/jcb.28365
[12]	S. Ghosh, C. K. Chan, Analysis of RNA-Seq data using TopHat and Cufflinks, Methods Mol. Biol., 1374 (2016), 339–361. doi: 10.1007/978-1-4939-3167-5_18
[13]	Y. Liao, G. K. Smyth, W. Shi, featureCounts: an efficient general purpose program for assigning sequence reads to genomic features, Bioinformatics, 30 (2014), 923–930. doi: 10.1093/bioinformatics/btt656
[14]	O. Nikolayeva, M. D. Robinson, edgeR for differential RNA-seq and ChIP-seq analysis: An application to stem cell biology, Methods Mol. Biol., 1150 (2014), 45–79. doi: 10.1007/978-1-4939-0512-6_3
[15]	M. D. Robinson, D. J. McCarthy, G. K. Smyth, edgeR: A Bioconductor package for differential expression analysis of digital gene expression data, Bioinformatics, 26 (2010), 139–140. doi: 10.1093/bioinformatics/btp616
[16]	G. Yu, L. G. Wang, Y. Han, Q. Y. He, clusterProfiler: An R package for comparing biological themes among gene clusters, OMICS, 16 (2012), 284–287. doi: 10.1089/omi.2011.0118
[17]	M. Ashburner, C. A. Ball, J. A. Blake, D. Botstein, H. Butler, J. M. Cherry, et al., Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium, Nat.Genet., 25 (2000), 25–29.
[18]	M. Kanehisa, S. Goto, KEGG: Kyoto encyclopedia of genes and genomes, Nucl. Acids Res., 28 (2000), 27–30. doi: 10.1093/nar/28.1.27
[19]	P. Shannon, A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D. Ramage, et al., Cytoscape: A software environment for integrated models of biomolecular interaction networks, Genome Res., 13 (2003), 2498–2504.
[20]	H. Dweep, N. Gretz, miRWalk2.0: A comprehensive atlas of microRNA-target interactions, Nat. Methods, 12 (2015), 697.
[21]	S. Das, S. Ghosal, R. Sen, J. Chakrabarti, lnCeDB: Database of human long noncoding RNA acting as competing endogenous RNA, PLoS One, 9 (2014), e98965.
[22]	Y. Tang, M. Li, J. Wang, Y. Pan, F. X. Wu, CytoNCA: A cytoscape plugin for centrality analysis and evaluation of protein interaction networks, Biosystems, 127 (2015), 67–72. doi: 10.1016/j.biosystems.2014.11.005
[23]	T. Barrett, T. O. Suzek, D. B. Troup, S. E. Wilhite, W.-C. Ngau, P. Ledoux, et al., NCBI GEO: Mining millions of expression profiles—database and tools, Nucl. Acids Res., 33 (2005), D562–D566.
[24]	L. C. Tsoi, M. K. Iyer, P. E. Stuart, W. R. Swindell, J. E. Gudjonsson, T. Tejasvi, et al., Analysis of long non-coding RNAs highlights tissue-specific expression patterns and epigenetic profiles in normal and psoriatic skin, Genome Biol., 16 (2015), 24.
[25]	K. R. Sigdel, A. Cheng, Y. Wang, L. Duan, Y. Zhang, The emerging functions of Long Noncoding RNA in immune cells: Autoimmune diseases, J. Immunol. Res., 2015 (2015), 848790.
[26]	Y. M. Han, Y. Y. Sheng, F. Xu, S. S. Qi, X. J. Liu, R. M. Hu, et al., Imbalance of T-helper 17 and regulatory T cells in patients with alopecia areata, J. Dermatol., 42 (2015), 981–988.
[27]	M. Hordinsky, D. H. Kaplan, Low-dose interleukin 2 to reverse alopecia areata, JAMA Dermatol., 150 (2014), 696–697. doi: 10.1001/jamadermatol.2014.510
[28]	H. Guo, Y. Cheng, J. Shapiro and K. McElwee, The role of lymphocytes in the development and treatment of alopecia areata, Expert Rev. Clin. Immunol., 11 (2015), 1335–1351. doi: 10.1586/1744666X.2015.1085306
[29]	H. Chen, Z. Xu, X. Liu, Y. Gao, J. Wang, P. Qian, et al., Increased expression of Lncrna RP11-397A15.4 in gastric cancer and its clinical significance, Ann. Clin. Lab. Sci., 48 (2018), 707–711.
[30]	R. Huang, W. Nie, K. Yao, J. Chou, Depletion of the lncRNA RP11-567G11.1 inhibits pancreatic cancer progression, Biomed. Pharmacother., 112 (2019), 108685.
[31]	Y. Wu, X. Yang, Z. Chen, L. Tian, G. Jiang, F. Chen, et al., m(6)A-induced lncRNA RP11 triggers the dissemination of colorectal cancer cells via upregulation of Zeb1, Mol. Cancer, 18 (2019), 87.

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