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DOI 10.1159/000381478

Медицинская библиотека · Ophthalmic research · 2015

Bioinformatics Analysis of Potential Candidates for Therapy of TDRD7 Deficiency-Induced Congenital Cataract.

Shao De-Wang, Yang Chun-Yan, Liu Bing, Chen Wei, Wang Hua, Ru Hai-Xia, Zhang Min, Wang Ying

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Аннотация

AIMS: The aim of this study was to identify potential candidates and explore the possible mechanism in congenital cataract induced by tudor domain-containing 7 (TDRD7) deficiency.

METHODS

The gene expression profile GSE25812 generated from 18 samples was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between disease and normal groups were identified. Then, gene ontology and pathway enrichment analysis of DEGs were performed. The protein-protein interaction (PPI) network and transcription factor (TF) regulatory network were constructed. The modules in the PPI network were identified. Significant target genes were selected from the TF regulatory network.

RESULTS

A total of 329 DEGs were obtained, and downregulated DEGs were significantly enriched in biological processes including defense response and immune response. In the PPI network, high-degree genes of complement component 1, q subcomponent, A/B/C chain (C1QA/C1QB/C1QC), lymphocyte antigen 86 (LY86) and neuroblastoma RAS viral oncogene homolog (NRAS) were identified. From the TF regulatory network, the heat shock 27 kDa protein 1 (HSPB1) was the target of the estrogen receptor 1, and LY86 was the target of the v-myc avian myelocytomatosis viral oncogene homolog.

CONCLUSION

HSPB1, NRAS, immune response, defense response and the related genes LY86, C1QA/C1QB/C1QC may play an important role in the development of congenital cataract induced by TDRD7 deficiency. However, further experiments are still needed.

Для цитирования: Shao De-Wang, Yang Chun-Yan, Liu Bing, Chen Wei, Wang Hua, Ru Hai-Xia, Zhang Min, Wang Ying. Bioinformatics Analysis of Potential Candidates for Therapy of TDRD7 Deficiency-Induced Congenital Cataract.. Ophthalmic research. 2015. DOI: 10.1159/000381478.

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