Main content area

Comprehensive transcriptional profiling of porcine brain aging

Chen, Jianning, Zou, Qin, Lv, Daojun, Raza, Muhammad Ali, Wang, Xue, Li, Peilin, Chen, Yan, Xi, Xiaoyu, Wen, Anxiang, Zhu, Li, Tang, Guoqing, Li, Mingzhou, Li, Xuewei, Jiang, Yanzhi
Gene 2019 v.693 pp. 1-9
cerebral cortex, circular RNA, gene expression regulation, genes, high-throughput nucleotide sequencing, immune response, messenger RNA, microRNA, non-coding RNA, signal transduction, stress response, swine, synaptic transmission, transcription (genetics)
The brain as an important organ can be affected largely by aging, and the comprehensive transcriptional underpinnings of brain aging remain poorly understood. Here, we performed a high throughput RNA sequencing to evaluate the expression profiles of messenger RNA (mRNA), long non-coding RNAs (lncRNAs), micro RNAs (miRNAs), and circular RNAs (circRNAs) in porcine brain. We have identified 714 mRNAs, 38lncRNAs, 41miRNAs, and 148circRNAs were age-related genes in the porcine cerebral cortex. The lncRNAs, miRNAs and circRNAs have effect on the age of porcine brain due to the much changes of expression level as noncoding RNAs. The up-regulated genes were significantly enriched for stress response, reproductive regulatory process, immune response and metabolic process, and the down-regulated genes were related to neurologic function, stress response and signaling pathway. The synaptic transmission pathway may be the key role in aging of porcine brain that it was co-enriched for in both differentially expressed mRNAs and lncRNAs. Moreover, some lncRNAs and their target genes were also differentially expressed during brain aging. We further assessed the multi-group cooperative control relationships and constructed circRNA-miRNA co-expression networks during brain aging. We also selected 2 mRNAs, 2 lncRNAs, 2 miRNAs, and 1 circRNAs to perform the q-PCR, and the expression patterns were highly consistent between the two methods confirming the high reproducibility and reliability of the gene expression profiling in our study. In conclusion, our findings will contribute to understand the transcriptional underpinnings of brain aging and provide a foundation for future studies on the molecular mechanisms underlying brain aging.