Abstract

Domestic animals are members of the broader ecological context, in which humans are situated. Yet, genomics and systems science research have lagged behind and been relatively underappreciated in domestic animals compared to human genetics/genomics. Harnessing big data calls for omics data mapping studies in a broad range of mammals. To this end, microRNAs (miRNAs) regulate posttranscriptional expression of target genes, hence, governing different biological pathways and physiological processes. The knowledge of miRNA regulatory networks and maps is important for understanding regulation of gene expression and functions in both humans and domestic animals. However, complete miRNA regulatory networks have not yet been described in all species, particularly in domestic animals. We report here an original analysis so as to map the miRNA regulatory networks in domestic animals based on miRNA-target interactions (MTIs). Validated MTIs for five species; cattle, pig, sheep, dog, and chicken were extracted from the miRTarBase. miRNA regulomes were visualized using the Cytoscape software. The data in cattle, chicken, and pig were sufficient to visualize networks, identify central molecules, and subnetworks associated with the same phenotype; however, the MTI data in dog and sheep are still limited. We found several hub genes with large number of interactions, for example, 1 miRNA (bta-miR-17-5p) interacting with 27 genes and 7 miRNAs interacting with the same gene (tumor necrosis factor [TNF]) in cattle. In addition, two single-nucleotide polymorphisms were identified within the seed region of a previously demonstrated MTI, namely, between HMGB3 (high mobility group box 3) gene and bta-miR-17-5p. In summary, this miRNA regulome mapping study will enable and guide further studies of genome function in mammals with a view to applications in human as well as veterinary medicine. Furthermore, these miRNA regulomes can help to clarify fundamental pathways in cell biology and reveal molecular insights on phenotypic trait variability in common complex diseases and response phenotypes of drugs or other health interventions for precision medicine in the future.

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