Genomic Imprinting in the New Omics Era: A Model for Systems-Level Approaches

Abstract

Genomic imprinting represents a noteworthy inheritance mechanism leading to allele-specific regulations dependent of the parental origin. Imprinted loci are especially involved in essential mammalian functions related to growth, development and behavior. In this mini-review, we first offer a summary of current representations associated with genomic imprinting through key results of the three last decades. We then outline new perspectives allowed by the spread of new omics technologies tackling various interacting levels of imprinting regulations, including genomics, transcriptomics and epigenomics. We finally discuss the expected contribution of new omics data to unresolved big questions in the field.

Increased copy number of imprinted genes in the chromosomal region 20q11-q13.32 is associated with resistance to antitumor agents in cancer cell lines

“…In addition to possible interactions among imprinted and non-imprinted genes located in close proximity from each other, earlier studies identified extensive networks of interactions and co-regulation in mammalian growth and differentiation between imprinted and nonimprinted genes located in different genome regions, [3,167]. For example, the antiapoptotic factor BIRC5, whose gene is located at 17q25.3, has regulatory interactions with several imprinted genes, with the strongest connection to PLAGL1 (ZAC1) at 6q24.2 [2,167].…”

“…They include, e.g., CPA4, PLAGL1, IGF2, GRB10, and other genes whose copy number, expression, and/or methylation measures were associated with drug response (Additional file 7: Table S4, Additional file 8: Table S5, Additional file 9: Table S6) [2,71,113,140,172]. Tissue specificity of their imprinting, in addition to variation in gene expression among tissues regulated by mechanisms other than imprinting, underscores the importance of future analyses of associations of allelic dosage, parent-specific allelic expression, and novel types of omics data [3] with drug response, which would need to be conducted in separate tumor categories with large sample sizes. An additional analysis of the mutation status of the imprinted genes in tumors would add further depth to the understanding of their influence on drug response, since protein-changing mutations in many imprinted genes including those genes which were associated with drug response in our study, e.g., NLRP2, CDKN1C, and GNAS, commonly occur in patients with imprinted disorders and/or cancer [1,129,131,[149][150][151][152][153][154]156].…”

Livestock species as emerging models for genomic imprinting

“…Our understanding of how regions affected by imprinting have evolved and function has expanded considerably ( Llères et al, 2021 ; Kaneko-Ishino and Ishino, 2022 ; Richard Albert et al, 2023 ) and we today have increasingly sophisticated resources and tools ( Hubert and Demars, 2022 ; Jima et al, 2022 ; Akbari et al, 2023 ) to identify and accurately report the links between nuclear architecture, Imprinting Control Regions (ICRs), imprinted genes, other genes including different RNA species and, finally, phenotypes. While cytosine methylation is key to almost all regulations that affect it, including transgenerational maintenance, imprinting involves multi-scale mechanisms ( Monk et al, 2019 ), giving grounds for multi-omics approaches ( Hubert and Demars, 2022 ). A diversity of non-exclusive patterns, such as the recruitment of CCCTC-Binding Factor (CTCF) ( Noordermeer and Feil, 2020 ), the transcriptional interference of long non-coding RNA (lncRNA) ( MacDonald and Mann, 2020 ) or the presence of microRNA (miRNA) clusters ( Malnou et al, 2019 ), have, for example, been highlighted at imprinted loci.…”

Conservation and divergence of canonical and non-canonical imprinting in murids

“…Importantly, parent-of-origin effects, including genomic imprinting, can be delineated from genetic or strain-specific effects by generating F1s from reciprocal crosses [29]. Together, allele-specific analysis of genic expression by RNA sequencing (RNAseq) and DNAme levels by whole genome bisulphite sequencing (WGBS) data derived from reciprocal F1 hybrids represent the gold standard for identifying candidate imprinted genes genome-wide in a given tissue or cell type [30,31].…”