Evolutionary Quantitative Genetics of Genomic Imprinting

Abstract

Genomic imprinting shapes the genotype-phenotype relationship by creating an asymmetry between the influences of paternally and maternally inherited gene copies. Consequently, imprinting can impact heritable and nonheritable variation, resemblance of relatives, and evolutionary dynamics. Although previous analyses have identified some of the quantitative genetic consequences of imprinting, we lack a framework that cleanly separates the influence of imprinting from other components of variation, particularly dominance. Here we apply a simple orthogonal genetic model to evaluate the roles of genetic (additive and dominance) and epigenetic (imprinting) effects. Imprinting increases the resemblance of relatives who share the expressed allele, and therefore increases variance among families of full or half-siblings. However, only part of this increased variance is heritable and contributes to selection responses. When selection is within, or among, families sharing only a single parent (half-siblings), which is common in selective breeding programs, imprinting can alter overall responses. Selection is more efficient when it acts among families sharing the expressed parent, or within families sharing the parent with lower expression. Imprinting also affects responses to sex-specific selection. When selection is on the sex whose gene copy has lower expression, the response is diminished or delayed the next generation, although the long-term response is unaffected. Our findings have significant implications for understanding patterns of variation, interpretation of short-term selection responses, and the efficacy of selective breeding programs, demonstrating the importance of considering the independent influence of genomic imprinting in quantitative genetics.

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

“…Investigating multi-scale GI-phenotype relationships could provide insights on unusual patterns of missing heritability, with the potential for many applications. Genomic prediction in domestic animals could for example benefit from explicitly modeling GI for some economically important phenotypes ( O’Doherty et al, 2015 ; Hu et al, 2016 ; O’Brien and Wolf, 2019 ). In cancer, evasion of growth suppression is mediated through many imprinted loci ( Stampone et al, 2018 ; Lecerf et al, 2019 ; Sutton et al, 2019 ).…”

Review: optimizing genomic selection for crossbred performance by model improvement and data collection

“…In other words, the effects of genes are “uniquely defined” in the CB population ( Stuber and Cockerham, 1966 ). In reality, however, the effects of marker alleles can be breed-specific because of 1) differences in marker-QTL LD between parental lines ( Wientjes et al, 2015 ), 2) imprinting effects ( O’Brien and Wolf, 2019 ), and 3) dominance (and likely epistasis) in combination with differences in QTL allele frequencies between parental lines ( Wei et al, 1991 ). The latter can be seen from equation (4) , which shows that the average effect of an allele that is transmitted from the first parental line to a CB offspring depends on the allele frequency in the second line, and vice versa (e.g., Pirchner and Mergl, 1977 ; Dekkers, 1999 ; Duenk, 2020 ).…”

A methyl-seq tool to capture genomic imprinted loci

“…Here, we optimized and compared capture-based methylation sequencing technologies aiming for imprinted loci across the genome. We performed our study in the pig (Sus scrofa) because porcine GI is largely under-characterized, despite wideranging implications not limited to the improvement of major agronomical phenotypes 9,10 . We (i) selected 165 regions in the pig genome based on human and mouse orthologies 1,11 (https://www.geneimprint.com and https://corpapp.otago.ac.nz/gene-catalogue), since GI mechanisms are quite well conserved in mammals 12 , (ii) exploited reciprocal crosses to identify PofO methylation 6 and (iii) tested two different technologies, the novel Twist NGS Bioscience Methylation Detection System (TB), with two protocols (called TB1 and TB2), and the widely used Agilent SureSelect Custom DNA Target Enrichment Probes (AG) (Fig.…”

“…However, such cost-consuming methods could not be used as routine molecular tools. Here, we optimized and compared capture-based methylation sequencing technologies aiming for imprinted loci across the genome.We performed our study in the pig (Sus scrofa) because porcine GI is largely under-characterized, despite wideranging implications not limited to the improvement of major agronomical phenotypes 9,10 . The strategy implemented below may be applied to any other species with its own custom capture.…”

“…We performed our study in the pig ( Sus scrofa ) because porcine GI is largely under-characterized, despite wide-ranging implications not limited to the improvement of major agronomical phenotypes 9,10 . The strategy implemented below may be applied to any other species with its own custom capture.…”