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Identify Down syndrome transcriptome associations using integrative analysis of microarray database and correlation-interaction network.
Chen, Min; Wang, Jiayan; Luo, Yingjun; Huang, Kailing; Shi, Xiaoshun; Liu, Yanhui; Li, Jin; Lai, Zhengfei; Xue, Shuya; Gao, Haimei; Chen, Allen; Chen, Dunjin.
Afiliação
  • Chen M; Department of Fetal Medicine and Prenatal Diagnosis, the Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China.
  • Wang J; Obstetrics and Gynecology Institute of Guangzhou, Guangzhou, 510150, China.
  • Luo Y; The Medical Centre for Critical Pregnant Women in Guangzhou, Guangzhou, 510150, China.
  • Huang K; Key Laboratory for Major Obstetric Diseases of Guangdong Province, Guangzhou, 510150, China.
  • Shi X; Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Guangzhou, China.
  • Liu Y; Department of Fetal Medicine and Prenatal Diagnosis, the Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China.
  • Li J; Obstetrics and Gynecology Institute of Guangzhou, Guangzhou, 510150, China.
  • Lai Z; The Medical Centre for Critical Pregnant Women in Guangzhou, Guangzhou, 510150, China.
  • Xue S; Key Laboratory for Major Obstetric Diseases of Guangdong Province, Guangzhou, 510150, China.
  • Gao H; Mendel Genes Inc, Manhattan Beach, CA, Manhattan Beach, CA, 90266, USA.
  • Chen A; Mendel Genes Inc, Manhattan Beach, CA, Manhattan Beach, CA, 90266, USA.
  • Chen D; Department of Thoracic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Hum Genomics ; 12(1): 2, 2018 01 19.
Article em En | MEDLINE | ID: mdl-29351810
ABSTRACT

BACKGROUND:

Long non-coding RNAs (lncRNAs) have previously been emerged as key players in a series of biological processes. Dysregulation of lncRNA is correlated to human diseases including neurological disorders. Here, we developed a multi-step bioinformatics analysis to study the functions of a particular Down syndrome-associated gene DSCR9 including the lncRNAs. The method is named correlation-interaction-network (COIN), based on which a pipeline is implemented. Co-expression gene network analysis and biological network analysis results are presented.

METHODS:

We identified the regulation function of DSCR9, a lncRNA transcribed from the Down syndrome critical region (DSCR) of chromosome 21, by analyzing its co-expression genes from over 1700 sets and nearly 60,000 public Affymetrix human U133-Plus 2 transcriptional profiling microarrays. After proper evaluations, a threshold is chosen to filter the data and get satisfactory results. Microarray data resource is from EBI database and protein-protein interaction (PPI) network information is incorporated from the most complete network databases. PPI integration strategy guarantees complete information regarding DSCR9. Enrichment analysis is performed to identify significantly correlated pathways.

RESULTS:

We found that the most significant pathways associated with the top DSCR9 co-expressed genes were shown to be involved in neuro-active ligand-receptor interaction (GLP1R, HTR4, P2RX2, UCN3, and UTS2R), calcium signaling pathway (CACNA1F, CACNG4, HTR4, P2RX2, and SLC8A3), neuronal system (KCNJ5 and SYN1) by the KEGG, and GO analysis. The A549 and U251 cell lines with stable DSCR9 overexpression were constructed. We validated 10 DSCR9 co-expression genes by qPCR in both cell lines with over 70% accuracy.

CONCLUSIONS:

DSCR9 was highly correlated with genes that were known as important factors in the developments and functions of nervous system, indicating that DSCR9 may regulate neurological proteins regarding Down syndrome and other neurological-related diseases. The pipeline can be properly adjusted to other applications.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Síndrome de Down / Transcriptoma / RNA Longo não Codificante Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Hum Genomics Assunto da revista: GENETICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Síndrome de Down / Transcriptoma / RNA Longo não Codificante Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Hum Genomics Assunto da revista: GENETICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China