Transcriptional Profiling of the Landes Goose Cecum Following Infection with Eimeria stigmosa Isolated from Shanxi Province, North China

Though a number of Eimeria species have been described in geese, the host responses to these parasites at the molecular level have yet to be explored. In the present study, fresh fecal samples were collected for single-oocyst isolation. The recovered oocysts were identified based on molecular analysis using PCR and sequencing. Subsequently, we examined the transcriptional response of the Landes goose cecum following infection with the isolated Eimeria strain. Molecular analysis showed that the isolated Eimeria strain was Eimeria stigmosa, which was named the E. stigmosa SX-01 strain. Transcriptomic profiling identified 3806 differentially expressed genes (DEGs), including 2238 genes with increased expression and 1568 genes with decreased expression. The results obtained from the quantitative reverse transcription PCR (qRT-PCR) analysis confirmed that the RNA sequencing (RNA-seq) data were reliable. According to pathway enrichment analysis for the obtained DEGs, 24 pathways were significantly affected following infection with the E. stigmosa SX-01 strain, such as cytokine–cytokine receptor interaction, intestinal immune network for IgA production, cell adhesion molecules, gap junction, arachidonic acid metabolism, alpha-Linolenic acid metabolism, retinol metabolism, and PPAR signaling pathway. These transcriptional alterations were observed in E. stigmosa-infected geese without obvious clinical signs, indicating that E. stigmosa infection may trigger a strong subclinical host response related to metabolism, immune and inflammatory responses, and intercellular junctional complex-associated processes. Collectively, these findings have implications for better understanding the E. stigmosa–goose interactions at the molecular level and provide a foundation for future functional and comparative studies to dissect the pathogenic mechanisms and molecular markers associated with disease resistance, which are expected to inform the design of effective control strategies.