RNA Biological Characteristics at the Peak of Cell Death in Different Hereditary Retinal Degeneration Mutants

• Published in: Frontiers in genetics Vol. 12; p. 728791
• Main Authors: Wei, Chunling, Li, Yan, Feng, Xiaoxiao, Hu, Zhulin, Paquet-Durand, François, Jiao, Kangwei
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 29-10-2021
• Subjects: biogenic analysis; cGMP-related genes; Genetics; inherited retinal degeneration (IRD); photoreceptor cell death; RNA-seq
• ISSN: 1664-8021; 1664-8021
• DOI: 10.3389/fgene.2021.728791

Purpose:
The present work investigated changes in the gene expression, molecular mechanisms, and pathogenesis of inherited retinal degeneration (RD) in three different disease models, to identify predictive biomarkers for their varied phenotypes and to provide a better scientific basis for their diagnosis, treatment, and prevention.
Methods:
Differentially expressed genes (DEGs) between retinal tissue from RD mouse models obtained during the photoreceptor cell death peak period (
Pde6b
rd1
at post-natal (PN) day 13,
Pde6b
rd10
at PN23,
Prph
rd2
at PN29) and retinal tissue from C3H wild-type mice were identified using Illumina high-throughput RNA-sequencing. Co-expression gene modules were identified using a combination of GO and KEGG enrichment analyses and gene co-expression network analysis. CircRNA-miRNA-mRNA network interactions were studied by genome-wide circRNA screening.
Results:
Pde6b
rd1
, Pde6b
rd10
, and Prph
rd2
mice had 1,926, 3,096, and 375 DEGs, respectively. Genes related to ion channels, stress, inflammatory processes, tumor necrosis factor (TNF) production, and microglial cell activation were up-regulated, while genes related to endoplasmic reticulum regulation, metabolism, and homeostasis were down-regulated. Differential expression of transcription factors and non-coding RNAs generally implicated in other human diseases was detected (e.g., glaucoma, diabetic retinopathy, and inherited retinal degeneration). CircRNA-miRNA-mRNA network analysis indicated that these factors may be involved in photoreceptor cell death. Moreover, excessive cGMP accumulation causes photoreceptor cell death, and cGMP-related genes were generally affected by different pathogenic gene mutations.
Conclusion:
We screened genes and pathways related to photoreceptor cell death. Additionally, up-stream regulatory factors, such as transcription factors and non-coding RNA and their interaction networks were analyzed. Furthermore, RNAs involved in RD were functionally annotated. Overall, this study lays a foundation for future studies on photoreceptor cell death mechanisms.