Quantitative Epigenetics: A New Avenue for Crop Improvement

Abstract

Plant breeding conventionally depends on genetic variability available in a species to improve a particular trait in the crop. However, epigenetic diversity may provide an additional tier of variation. The recent advent of epigenome technologies has elucidated the role of epigenetic variation in shaping phenotype. Further, the development of epigenetic recombinant inbred lines (epi-RILs) in the model species such as Arabidopsis has enabled accurate genetic analysis of epigenetic variation. Subsequently, mapping of epigenetic quantitative trait loci (epiQTL) allowed association between epialleles and phenotypic traits. Thus, quantitative epigenetics provides ample opportunities to dissect the role of epigenetic variation in trait regulation, which can be eventually utilized in crop improvement programs. Moreover, locus-specific manipulation of DNA methylation by epigenome-editing tools such as clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) can facilitate epigenetic based molecular breeding of important crop plants.

A generalised approach to the study and understanding of adaptive evolution

“…4B. For example, there are epigenetic molecular marks with transition rates which are almost equally low as genetic mutation, and these basically have dynamics that are hard to distinguish from genetic variation (Cortijo et al ., 2014; Banta & Richards, 2018; Sentis et al ., 2018; Thomson et al ., 2018; Gahlaut et al ., 2020). For these to evolve adaptively, the pathway involving natural selection (Fig.…”

“…the breeder's equation, Fisher's theorem, the Price equation, other quantitative genetic models) actually do not make (or need to make) that restriction (Helanterä & Uller, 2010, 2020; Day & Bonduriansky, 2011; Rivoire & Leibler, 2014; Prasad et al ., 2015; Charlesworth, Barton & Charlesworth, 2017; Luque, 2017), and some epigenetic variants (epialleles or epiQTLs) behave virtually identical to genetic variants in terms of stable inheritance and phenotypic effects (e.g. Cortijo et al ., 2014; Banta & Richards, 2018; Gahlaut et al ., 2020). In fact, many estimates of supposedly additive genetic variation may well involve significant portions of non‐genetic variance (Tal, Kisdi & Jablonka, 2010; Danchin et al ., 2011; Banta & Richards, 2018; Danchin, Pocheville & Huneman, 2019 a ).…”

“…copying in the case of a behavioural phenotype, or imprinting in the case of the habitat). [Some non‐genetic epigenetic molecular marks are non‐responsive and long‐lived, so basically operate as genetic alleles in terms of causal effects (Cortijo et al ., 2014; Banta & Richards, 2018; Sentis et al ., 2018; Thomson et al ., 2018; Gahlaut et al ., 2020). For simplicity these are included here in the genetic inheritance pathway.…”

“…We later discuss whether such a between‐generation change in the non‐genetically heritable traits of a population should be seen as evolution [since for some people evolution is exclusively defined by genetic change, but we already note here that many quantitative genetic models and equations (e.g. the breeder's equation, Fisher's theorem, the Price equation) actually do not make (or need to make) that restriction] or perhaps as non‐genetic evolution [good examples of this are cultural evolution (El Mouden et al ., 2014; Creanza, Kolodny & Feldman, 2017; Whiten, 2019) and changes in epigenetic molecular states (Cortijo et al ., 2014; Gahlaut et al ., 2020)]. But for now, for the reasons mentioned above, we postulate that a generalised model of adaptive evolution should incorporate that traits can be inherited genetically as well as non‐genetically .…”

Fab Advances in Fabaceae for Abiotic Stress Resilience: From ‘Omics’ to Artificial Intelligence

“…The trans-generational inheritance of epimarks can thus be exploited for crop improvement programs. This involves the use of epialleles, recombinant inbred lines (RILs), and epigenetic quantitative trait loci (epiQTLs) to breed for abiotic stress resistance [ 60 ]. Schmitz et al [ 61 ] exploited the epigenetic inheritance of local methyl quantitative trait loci (QTLs) in a soybean RIL population and utilized them to study methyl variations contributing to phenotypic variations over generations.…”