Cytology and Genetics, volume 58, issue 6, pages 615-626

Elucidation of the Gene Regulatory Network Related to Spinal Muscular Atrophy

Kerui Huang 1, 2
Yazhou Huang 1
Xingxin Fang 1
Zhaoxia Zhang 1
Yun Wang 2
Dan Peng 1, 3
1
 
Department of Medical Genetics, Changde Hospital, Xiangya School of Medicine, Central South University (The First People’s Hospital of Changde City), Hunan Changde, China
2
 
Hunan Provincial Key Laboratory for Molecular Immunity Technology of Aquatic Animal Diseases, College of Life and Environmental Sciences, Hunan University of Arts and Science, Hunan Changde, China
3
 
Affiliated Hospital of Changde City, University of South China, Hengyang, China
Publication typeJournal Article
Publication date2024-11-25
scimago Q4
SJR0.174
CiteScore1.1
Impact factor0.5
ISSN00954527, 19349440
Abstract
Spinal muscular atrophy (SMA) is an autosomal recessive heritable disorder leading to abnormalities and dysfunction of alpha motor neurons, paralysis, and eventual death due to respiratory failure. However, the gene regulatory mechanism related to SMA is still not completely clear. Here, we constructed the gene regulatory network of SMA, in which several SMA-related genes and transcription factors played important roles. In the process, 6544 differentially expressed genes (DEGs) associated with SMA were used and the enrichment analysis and gene regulatory network construction using machine learning was performed. The result showed that, firstly, p53 signaling and DNA replication are closely related to SMA. Then, there is a huge and complicated regulatory network guided by SMA, in which transcription factor SNAPC2, MZF1, and ZNF711 interacted closely with SMA-related genes (SMN1, SMN2) and played key roles in regulating genes of p53 signaling, DNA replication and other SMA-related GO (gene ontology) terms. The transcriptome data was well verified through real-time fluorescence quantitative PCR (RT-qPCR) using the peripheral blood of spinal muscular atrophy patients. Our study revealed the complicated gene regulation network of SMA, and uncover several important SMA-related genes, which it deepens our understanding of SMA-related regulatory mechanisms.
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