Long non-coding RNAs MALAT1 and NEAT1 in non-syndromic orofacial clefts

被引:5
作者
Wang, Errui [1 ]
Guo, Yumeng [1 ]
Gao, Shuting [2 ]
Zhou, Ying [1 ]
Liu, Bin [1 ,3 ]
Dissanayaka, Waruna Lakmal [2 ]
Zheng, Yayuan [1 ]
Zhou, Qiaozhen [1 ]
Zhai, Junkai [1 ]
Gao, Zhengkun [1 ]
Zhang, Baoping [1 ,3 ,4 ]
Liu, Ruimin [5 ]
Zhang, Kailiang [1 ,3 ]
机构
[1] Lanzhou Univ, Sch Stomatol, Lanzhou, Peoples R China
[2] Univ Hong Kong, Fac Dent, Appl Oral Sci & Community Dent Care, Hong Kong, Peoples R China
[3] Gansu Prov Key Lab Maxillofacial Reconstruct & In, Lanzhou, Peoples R China
[4] Lanzhou Univ, Key Lab Mech Disaster & Environm Western China, Minist Educ, Inst Biomech & Med Engn, Lanzhou, Peoples R China
[5] Gansu Prov Hosp, Dept Oral & Maxillofacial Surg, Lanzhou, Peoples R China
关键词
CeRNA; cleft lip and palate; enrichment analysis; GEO database; microarray; RT-Qpcr; LIP; TRANSCRIPTION; ASSOCIATION; EXPRESSION; CELLS; CLASSIFICATION; EPIDEMIOLOGY; PALATE; GENE;
D O I
10.1111/odi.14177
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Long non-coding RNAs (lncRNAs) are thought to play important roles in non-syndromic orofacial clefts (NSOFC). Clinical diagnosis was categorized as either non-syndromic cleft lip with or without cleft palate (NSCL/P), or non-syndromic cleft palate only (NSCPO). Tissues excised from the trimmed wound edge were reserved as experimental samples; adjacent normal control was used as a positive control, and tissue from healthy individuals was used as a blank control. Target lncRNAs in the collected tissues were identified using microarrays and quantitative reverse transcription PCR (RT-qPCR). Immunohistochemical (IHC) staining and RT-qPCR were used to verify the target mRNAs. Pathway, gene ontology (GO) enrichment, and TargetScan predictions were employed to construct competing endogenous RNA networks (ceRNA networks) and explore their potential functions. RNA-Seq revealed 24 upregulated and 43 downregulated lncRNAs; MALAT1 and NEAT1 were screened and validated using RT-qPCR. Common NSOFC risk factors were positively correlated with MALAT1 and NEAT1 expression. Bioinformatics predicted four ceRNA networks; GO enrichment focused on their potential functions. RT-qPCR and IHC data were consistent with respect to expression levels of proteins and the mRNAs that encode them. As MALAT1 and NEAT1 are associated with the severity of NSOFC, they represent potential therapeutic targets and prognostic biomarkers.
引用
收藏
页码:1668 / 1679
页数:12
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