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Pigs are the most important source of meat and valuable biomedical models. However, the porcine immune system, especially the heterogeneity of CD8 T cell subtypes, has not been fully characterized. Here, using single-cell RNA sequencing, we identified 14 major cell types from peripheral blood circulating cells of pigs and observed remarkable heterogeneity among CD8 T cell types. Upon re-clustering of CD8+ T cells, we defined four CD8 T cell subtypes and revealed their potential differentiation trajectories and transcriptomic differences among them. Additionally, we identified transcription factors with potential regulatory roles in maintaining CD8 T cell differentiation. The cell-cell communication analysis inferred an extensive interaction between CD8 T cells and other immune cells. Finally, cross-species analysis further identified species-specific and conserved cell types across different species. Overall, our study provides the first insight into the extensive functional heterogeneity and state transitions among porcine CD8 T cell subtypes in pig peripheral blood, complements the knowledge of porcine immunity, and enhances its potential as a biomedical model. [ABSTRACT FROM AUTHOR]

Pleiotropy is an important biological phenomenon with complicated genetic architectures for multiple traits. To date, pleiotropy has been mainly identified by multi‐trait genome‐wide association studies, but this method has its disadvantages, and new developments for pleiotropy detection methods are needed. Here we define a novel metric, self‐product, to measure individual‐level co‐variation of two traits, and develop a novel self‐product‐based transcriptome method to detect pleiotropic genes (PGs). Our method was tested using four immune–growth trait pairs and four immune–immune trait pairs in pigs. Comparative transcriptome analyses identified hundreds of candidate PGs related to eight trait pairs from two tails of self‐product distribution. Gene Ontology enrichment analysis indicated that most of identified PGs were involved in immune‐ or growth‐related biological processes. We established PG interaction networks to exhibit core genes shared by eight trait pairs, of which CCL5 and IL‐10 genes were the hub genes. Genetic association analyses showed that SmaI‐polymorphisms of CCL5 and IL‐10 genes had significant associations with phenotypic co‐variations of multiple trait pairs, indicating that the variants in pleiotropic genes were also pleiotropic variants. Taken together, the validity of our proposed method was preliminarily verified, and our findings provide new insights into the genetic basis of pleiotropic architectures of immune and growth trait pairs in pigs. [ABSTRACT FROM AUTHOR]

Although large-scale and accurate identification of cis -regulatory elements on pig protein-coding and long non-coding genes has been reported, similar study on pig miRNAs is still lacking. Here, we systematically characterized the cis -regulatory elements of pig miRNAs in muscle and fat by adopting miRNAomes, ChIP-seq, ATAC-seq, RNA-seq and Hi-C data. In total, the cis -regulatory elements of 257 (85.95%) expressed miRNAs including 226 known and 31 novel miRNAs were identified. Especially, the miRNAs associated with super-enhancers, active promoters, and "A" compartment were significantly higher than those associated by typical enhancers, prompters without H3K27ac, and "B" compartment, respectively. The tissue specific transcription factors were the primary determination of core miRNA expression pattern in muscle and fat. Moreover, the miRNA promoters are more evolutionarily conserved than miRNA enhancers, like other type genes. Our study adds additional important information to existing pig epigenetic data and provides essential resource for future in-depth investigation of pig epigenetics. • The cis -regulatory elements of expressed miRNAs in pig muscle and fat were annotated and verified. • Core miRNAs in muscle and fat which related to the corresponding tissue function were identified. • Upstream transcription factors regulating core miRNAs were identified through the annotated miRNA cis -regulatory elements. [ABSTRACT FROM AUTHOR]