This guest post is by Claude Becker, Jörg Hagmann and Detlef Weigel on their preprint Century-scale methylome stability in a recently diverged Arabidopsis thaliana lineage, bioRxived here.

This paper is the result of a collaboration between experts in machine learning and statistical analysis (from the group of Karsten Borgwardt at the Max Planck Institute of Intelligent Systems), a lab that has spearheaded the assembly and SNP genotyping of a world-wide collection of Arabidopsis thaliana specimen (Joy Bergelson’s lab at the University of Chicago), a group specialized in large-scale phenotyping (the lab of Thomas Altmann at the Leibniz Institute of Plant Genetics and Crop Plant Research in Gatersleben) and our epigenomics group at the Max Planck Institute for Developmental Biology in Tübingen.

The epigenome of an organism, in a restricted definition, consists of the entirety of post-translational histone modifications (e.g. methylation, acetylation, etc.) and chemical modifications to the DNA, such as methylation of cytosines. Epigenetic marks can influence the transcriptional activity of genes and transposable elements by locally modulating the accessibility of the DNA. The local configuration of the epigenome can change (i) spontaneously, (ii) in dependence of genetic rearrangements, or (iii) as a consequence of external signals. That the epigenome reacts to external signals such as stress and nutrient supply and that it can influence physiological processes – even behavior – has caused much recent excitement. Academic and popular scientific articles have raised the question whether the epigenome has the potential to maintain environmental footprints across generations. The epigenome is thus presented as an entity that fuels acclimation to rapidly changing environmental conditions and that enables adaptation in subsequent generations. Studies investigating the epigenetic basis of the inheritance of acquired traits, however, often either lack the depth of analysis necessary for the identification of locus-specific epigenetic changes or investigate inheritance over a rather short time period of only one or two generations. Moreover, many study designs do not allow for easy distinction between genetic variation causing the observed epigenetic change and epigenetic differences independent of DNA sequence variation.

In our new study we aim to tackle the question to what extent long exposure to varying and diverse environmental conditions can change the heritable DNA methylation landscape. We overcome several of the above-mentioned problems and limitations by studying variation of DNA methylation in a quasi-isogenic lineage of the model plant Arabidopsis thaliana. North America (NA) was only recently colonized by A. thaliana, and approximately half of the current population is made of a single lineage that underwent a recent population bottleneck, having diverged from a common ancestor more a century or two ago, resulting in minimal genetic diversity in the current population [1].

We sequenced the genome and DNA methylome of thirteen closely related NA accessions originating from different geographical locations in order to determine the spectrum, frequency and effect of epigenetic variants. We then compared the epigenetic variation in the NA lineage to that of a previously analyzed set of isogenic A. thaliana lines that had been propagated for 30 generations in the greenhouse [2,3].

Pairwise comparison of the NA accessions revealed that only 3% of the genome-wide methylation showed variable methylation. By using the genetic mutations as a molecular clock, we found that – contrary to our expectation – epimutations did not accumulate at a higher rate under varying natural conditions compared to growth in a stable greenhouse environment. Even more surprisingly, changes in DNA methylation of single cytosines and of larger contiguous regions were often seen in both NA and greenhouse-grown accessions. In both datasets, accumulation of epimutations over time was non-linear, likely reflecting frequent reversions of methylation changes back to the initial configuration. Population structure inferred from methylation data reflected the genetic relatedness of the accessions and showed no signal of a genome-wide environmental footprint. This, together with the fact that most epigenetic variants were neutral and did not correlate with changes in gene expression, indicated that epigenetic variants accumulate to a large extent as a function of time and genetic diversification rather than as a consequence of local adaptation to environmental changes.

In summary, we have shown that long-term methylome variation of plants grown in varying and diverse natural sites is largely stable at the whole-genome level and in several aspects is intriguingly similar to that of lines raised in uniform conditions. This does not rule out a limited number of subtle adaptive DNA methylation changes that are linked to specific growth conditions, but it is in stark contrast to the published claims of broad, genome-wide epigenetic variation reflecting local adaptation. Heritable polymorphisms that arise in response to specific growth conditions certainly appear to be much less frequent than those that arise spontaneously or due to genetic variation.

In addition to the biological findings discussed above, an important part of our paper is an improved method for the detection of differentially methylated regions. Past studies have relied on clustering of differentially methylated positions or on fixed sliding windows, with the caveat of high rates of false negatives and false positives, respectively. We have adapted a Hidden Markov Model, initially developed for animal methylation data, to the more complex DNA methylation patterns in plants. Upon identification of methylated regions in each strain, these are then tested for differential methylation between strains. Our method results in increased specificity and higher accuracy and we believe it will be of broad interest to the epigenomics community.

References

1. Platt A, Horton M, Huang YS, Li Y, Anastasio AE, et al. (2010) The scale of population structure in Arabidopsis thaliana. PLoS Genet 6: e1000843.

2. Becker C, Hagmann J, Müller J, Koenig D, Stegle O, et al. (2011) Spontaneous epigenetic variation in the Arabidopsis thaliana methylome. Nature 480: 245-249.

3. Schmitz RJ, Schultz MD, Lewsey MG, O’Malley RC, Urich MA, et al. (2011) Transgenerational epigenetic instability is a source of novel methylation variants. Science 334: 369-373.