Livestock genetics is currently navigating through a genomic era promoted by advances in DNA technologies. For instance, massive amounts of genomic information (e.g., arrays that genotype more than 500K SNPs along the bovine genome) are incorporated into the prediction of genetic merit providing higher predictive accuracy (Van Raden et al., 2008). This increment has led to important changes in the animal breeding industry (Dekkers, 2004; Ibanez-Escriche and Gonzalez-Recio, 2011). New advances continue, and efforts are currently placed in whole genome sequencing (e.g., in species such as cattle and swine) for its implementation future implementation to improve accuracy of genomic selection or mapping new QTL of interest (Meuwissen and Goddard, 2010). There is, however, a promising field that has not yet been tackled in livestock breeding and genetics: epigenetics. The modern definition of epigenetics is the study of heritable changes in gene expression and other genomic functions without altering the underlying “DNA” sequence – hence the name “epi” – (derived from the Greek word meaning “over, above, outer” – combined with genetics; Richards, 2006). Epigenetic shows that not all genetic information is in the DNA sequence, but also in some modifications that occur along the epigenome, particularly DNA methylation (DNAm) in which a methyl group is added to the 5′ position of the cytosine pyrimidine ring (Figure (Figure1).1). This variation in methylation patterns between individuals contributes to phenotypic variability even if these individuals are genotypically identical (Coolen et al., 2011). Epigenetic information can be thought as the grammar or orthography of the DNA alphabet because these DNAm events have been shown to be regulation mechanisms associated with gene silencing, expression, chromatin remodeling, or imprinting (Robertson, 2005; Khatib, 2012). This is an emerging field of research that is becoming increasingly important and has attracted much of the interest in genetic studies in cancer and other human diseases (Relton and Davey Smith, 2010; Rakyan et al., 2011). Figure 1 Simple representation of the effect of methylated DNA. Epigenetics is attractive for animal breeding because it may help finding part of the missing causality and missing heritability of complex traits and diseases. DNAm patterns are modified along the life of an individual by environmental forces like diet, stress, drugs, or pollution among many others (Petronis, 2010). Therefore, some environments are more likely to increase certain methylation patterns, and these patterns would contribute to the phenotypic variation between individuals. Removing this noise from the phenotype decomposition equation (infinitesimal model) may help to estimate parameters more accurately. Furthermore, the environment may affect the methylation pattern of up to three generations cohabiting under the same specific circumstances at a given time t during pregnancy: the productive female, the fetus, and the fetus’ germ cells (Figure (Figure2).2). Hence, what happens to an animal during its lifetime may have consequences in future generations. Some examples can be found in humans: mothers who were pregnant during famine in The Netherlands in 1944, also known as the “Hunger Winter,” had children and grandchildren with a wide range of health problems (Heijmans et al., 2008). Nijland et al. (2008) recently showed a similar pattern in sheep: diet of pregnant ewes had some effect on the weight of their grand-daughters. Figure 2 Environmental forces at time t, may affect the methylation patterns of three generations. Interestingly, some authors have also related epigenetics with the missing heritability problem by demonstrating the existence of epigenetic variation and inheritance in plants and animals (Morgan et al., 1999; Henderson and Jacobsen, 2007; Migicovsky and Kovalchuk, 2011), although some controversy exists on this aspect. Epigenetic memory is supposed to be erased in mammals during the meiosis process, and only few cases of trans-generational epigenetic conservation is known in specific loci across the genomes (Jablonka and Raz, 2009). It is however well accepted that some genotypes are more susceptible to methylation than others (Coolen et al., 2011), but it is not clear what part of the genetic variation influences epigenetic variation. The causal relationship of genome–epigenome–phenotype is to be discovered, and the epigenome layer may confer additional knowledge on the relationship between genotype and phenotype. Thus, it will be important to detect the genotypes and practices associated to (un)favorable methylation affecting productive traits, functionality, and metabolic problems.
Search from 250 M+ research papersSearch from 250 M+ research papers
Open Access
Dec 13, 2023
Nathan R Zemke + 32
