Background : The prefrontal cortex (PFC) constitutes a large part of the human central nervous system and is essential for the normal social affection and executive function of humans and other primates. Despite ongoing research in this region, the evolution of interactions between PFC genes is still unknown, and there is a need to better understand changes in expression of age-related genes over the lifespan. To investigate the evolution of PFC gene interaction networks and further identify hub genes, we obtained time-series gene expression data of human PFC tissues from the Gene Expression Omnibus (GEO) database. A statistical model, loggle, was used to construct time-varying networks and explore the evolution of PFC gene networks over time. Several common network attributes were used to explore the evolution of PFC gene networks over time. The hub genes of different evolutionary stages were identified. At the same time, we explored several known KEGG pathways in PFC and the corresponding development patterns of central genes.
Results : Network similarity analysis showed that the development of human PFC is divided into three stages, namely, fast development period, deceleration to stationary period, and destructive recession period. We identified some genes related to PFC evolution at these different stages, including genes involved in neuronal differentiation or synapse formation, genes involved in nerve impulse transmission, and genes involved in the development of myelin around neurons. Some of these genes are consistent with findings in previous reports. Pathway evolution analysis suggests that the axon guidance pathway has been most responsive during the evolution of PFC.
Conclusions : This study clarified the evolutionary trajectory of the interaction between PFC genes, and proposed a set of candidate genes related to PFC development, which helps further study of human brain development at the genomic level supplemental to regular anatomical analyses. The analytical process used in this study, involving the loggle model, similarity analysis, and central analysis, provides a comprehensive strategy to gain novel insights into the evolution and development of brain networks in other organisms.