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Updated: Jul 24, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
Published on: March 1, 2024
Imprinted Genes: Genomic Conservation, Transcriptomic Dynamics and Phenomic Significance in Health and Diseases
Shane A Carrion1, Jennifer J Michal1, Zhihua Jiang1
1Department of Animal Sciences and Center for Reproductive Biology, Washington State University, Pullman WA 99164-7620, USA.
None:
Since its discovery in 1991, genomic imprinting has been the subject of numerous studies into its mechanisms of establishment and regulation, evolution and function, and presence in multiple genomes. Disturbance of imprinting has been implicated in a range of diseases, ranging from debilitating syndromes to cancers to fetal deficiencies. Despite this, studies done on the prevalence and relevance of imprinting on genes have been limited in scope, tissue types available, and focus, by both availability and resources. This has left a gap in comparative studies. To address this, we assembled a collection of imprinted genes available in current literature covering five species. Here we sought to identify trends and motifs in the imprinted gene set (IGS) in three distinct arenas: evolutionary conservation, across-tissue expression, and health phenomics. Overall, we found that imprinted genes displayed less conservation and higher proportions of non-coding RNA while maintaining synteny. Maternally expressed genes (MEGs) and paternally expressed genes (PEGs) occupied distinct roles in tissue expression and biological pathway use, while imprinted genes collectively showed a broader tissue range, notable preference for tissue specific expression and limited gene pathways than comparable sex differentiation genes. Both human and murine imprinted genes showed the same clear phenotypic trends, that were distinct from those displayed by sex differentiation genes which were less involved in mental and nervous system disease. While both sets had representation across the genome, the IGS showed clearer clustering as expected, with PEGs significantly more represented than MEGs.
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