The extracellular matrix (ECM) within the brain possesses a distinctive composition and functionality, influencing a spectrum of physiological and pathological states. Among its constituents, perineuronal nets (PNNs) are unique ECM structures that wrap around the cell body of many neurons and extend along their dendrites within the central nervous system (CNS). PNNs are pivotal regulators of plasticity in CNS, both during development and adulthood stages. Characterized by their condensed glycosaminoglycan-rich structures and heterogeneous molecular composition, PNNs not only offer neuroprotection but also participate in signal transduction, orchestrating neuronal activity and plasticity. Interfering with the PNNs in adult animals induces the reactivation of critical period plasticity, permitting modifications in neuronal connections and promoting the recovery of neuroplasticity following spinal cord damage. Interestingly, in the adult brain, PNN expression is dynamic, potentially modulating plasticity-associated states. Given their multifaceted roles, PNNs have emerged as regulators in the domains of learning, memory, addiction behaviors, and other neuropsychiatric disorders. In this review, we aimed to address how PNNs contribute to the memory processes in physiological and pathological conditions.

(1) Background: Goose meat is highly valued for its economic significance and vast market potential due to its desirable qualities, including a rich nutritional profile, tender texture, relatively low-fat content, and high levels of beneficial unsaturated fatty acids. However, there is an urgent need to improve goose breeding by identifying molecular markers associated with meat quality. (2) Methods: We evaluated meat quality traits, such as meat color, shear force (SF), cooking loss rate (CLR), and crude fat content (CFC), in a population of 215 male Sichuan white geese at 70 days of age. A GWAS was performed to identify potential molecular markers associated with goose meat quality. Furthermore, the selected SNPs linked to meat quality traits were genotyped using the MALDI-TOP MS method. (3) Results: A dataset of 2601.19 Gb of WGS data was obtained from 215 individuals, with an average sequencing depth of 10.89×. The GWAS revealed the identification of 43 potentially significant SNP markers associated with meat quality traits in the Sichuan white goose population. Additionally, 28 genes were identified as important candidate genes for meat quality. The gene enrichment analysis indicated a substantial enrichment of genes within a 1Mb vicinity of SNPs in both the protein digestion and absorption pathway and the Glycerolipid metabolism pathway. (4) Conclusion: This study provides valuable insights into the genetic and molecular mechanisms underlying goose meat quality traits, offering crucial references for molecular breeding in this field.