Inheritance of DNA methylation differences in the mangrove Rhizophora mangle

The capacity to respond to environmental challenges ultimately relies on phenotypic variation which manifests from complex interactions of genetic and nongenetic mechanisms through development. While we know something about genetic variation and structure of many species of conservation importance, we know very little about the nongenetic contributions to variation. Rhizophora mangle is a foundation species that occurs in coastal estuarine habitats throughout the neotropics where it provides critical ecosystem functions and is potentially threatened by anthropogenic environmental changes. Several studies have documented landscape-level patterns of genetic variation in this species, but we know virtually nothing about the inheritance of nongenetic variation. To assess one type of nongenetic variation, we examined the patterns of DNA sequence and DNA methylation in maternal plants and offspring from natural populations of R. mangle from the Gulf Coast of Florida. We used a reduced representation bisulfite sequencing approach (epi-genotyping by sequencing; epiGBS) to address the following questions: (a) What are the levels of genetic and epigenetic diversity in natural populations of R. mangle? (b) How are genetic and epigenetic variation structured within and among populations? (c) How faithfully is epigenetic variation inherited? We found low genetic diversity but high epigenetic diversity from natural populations of maternal plants in the field. In addition, a large portion (up to ~25%) of epigenetic differences among offspring grown in common garden was explained by maternal family. Therefore, epigenetic variation could be an important source of response to challenging environments in the genetically depauperate populations of this foundation species.</p

Inheritance of DNA methylation differences in the mangrove Rhizophora mangle

The capacity to respond to environmental challenges ultimately relies on phenotypic variation which manifests from complex interactions of genetic and nongenetic mechanisms through development. While we know something about genetic variation and structure of many species of conservation importance, we know very little about the nongenetic contributions to variation. Rhizophora mangle is a foundation species that occurs in coastal estuarine habitats throughout the neotropics where it provides critical ecosystem functions and is potentially threatened by anthropogenic environmental changes. Several studies have documented landscape-level patterns of genetic variation in this species, but we know virtually nothing about the inheritance of nongenetic variation. To assess one type of nongenetic variation, we examined the patterns of DNA sequence and DNA methylation in maternal plants and offspring from natural populations of R. mangle from the Gulf Coast of Florida. We used a reduced representation bisulfite sequencing approach (epi-genotyping by sequencing; epiGBS) to address the following questions: (a) What are the levels of genetic and epigenetic diversity in natural populations of R. mangle? (b) How are genetic and epigenetic variation structured within and among populations? (c) How faithfully is epigenetic variation inherited? We found low genetic diversity but high epigenetic diversity from natural populations of maternal plants in the field. In addition, a large portion (up to ~25%) of epigenetic differences among offspring grown in common garden was explained by maternal family. Therefore, epigenetic variation could be an important source of response to challenging environments in the genetically depauperate populations of this foundation species.Peer reviewe

Environmental and genealogical effects on DNA methylation in a widespread apomictic dandelion lineage

International audienceAbstract DNA methylation in plant genomes occurs in different sequences and genomic contexts that have very different properties. DNA methylation that occurs in CG (mCG) sequence context shows transgenerational stability and high epimutation rate, and can thus provide genealogical information at short time scales. However, due to meta‐stability and because mCG variants may arise due to other factors than epimutation, such as environmental stress exposure, it is not clear how well mCG captures genealogical information at micro‐evolutionary time scales. Here, we analysed DNA methylation variation between accessions from a geographically widespread, apomictic common dandelion ( Taraxacum officinale ) lineage when grown experimentally under different light conditions. Using a reduced‐representation bisulphite sequencing approach, we show that the light treatment induced differentially methylated cytosines (DMCs) in all sequence contexts, with a bias towards transposable elements. Accession differences were associated mainly with DMCs in CG context. Hierarchical clustering of samples based on total mCG profiles revealed a perfect clustering of samples by accession identity, irrespective of light conditions. Using microsatellite information as a benchmark of genetic divergence within the clonal lineage, we show that genetic divergence between accessions correlates strongly with overall mCG profiles. However, our results suggest that environmental effects that do occur in CG context may produce a heritable signal that partly dilutes the genealogical signal. Our study shows that methylation information in plants can be used to reconstruct micro‐evolutionary genealogy, providing a useful tool in systems that lack genetic variation such as clonal and vegetatively propagated plants

ANCOVA results for available nutrients in soil solution.

<p>Diversity of species (<i>F. rubra</i> monoculture, <i>P. lanceolata</i> monoculture and mixture of the two species) and soil depth were fixed factors, and time after plantation was a covariate.</p>*<p>P<0.05;</p>**<p>P<0.01;</p>***<p>P<0.001;</p>ns<p>P>0.09. Bold shows significant effects.</p

Experimental setup and biomass data.

<p>Planting scheme (<b>a</b>); shoot (<b>b</b>) and root mass in the poor top (<b>c</b>) and rich bottom layer (<b>d</b>); percentage belowground biomass at harvest (<b>e</b>), in <i>Festuca rubra</i> (<i>Fr</i>) and <i>Plantago lanceolata</i> (<i>Pl</i>) monocultures and mixtures. Horizontal lines in <b>b–d</b> show expected values for mixtures in case of competitive-equivalence (i.e., 50% of monocultures, or a relative yield of 0.5), and arrows depict the percentage deviation. Asterisks show significant differences between observed and expected values after t-tests. Data are means ± SE, N = 3–4. (*) P<0.06; * P<0.05; ** P<0.01; *** P<0.001.</p

Nutrients dynamics in soil solution over time.

<p>Nitrate (<b>a, b</b>), ammonium (<b>c, d</b>) and phosphate (<b>e, f</b>) concentration in <i>Festuca rubra</i> and <i>Plantago lanceolata</i> monocultures and in mixtures of the two species, at 7 and 35 cm depth. In nitrate, different letters in legends show significant differences between species over time, after ANCOVA_{layer x species}. Data are means ± SE, N = 3–4. No significant second and third order interactions involving species and time were detected (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055805#pone-0055805-t001" target="_blank">Table 1</a>), meaning that similarities/differences between species were consistent all over the experimental period. Soil nutrient concentrations were derived from regular sampling of soil water over the course of the experiment through porous suction cups that had been placed in the soil layers.</p

Root growth observed through minirhizotron tubes.

<p>(<b>a</b>) Root length production over time (m m⁻² image) of <i>Festuca rubra</i> (<i>Fr</i>) and <i>Plantago lanceolata</i> (<i>Pl</i>) in mixtures, obtained from minirhizotron observations at 10 cm depth. Solid lines are for observed values, dashed lines for expected values from monocultures (½ of monocultures). On each date, t-test were run separately to detect significant differences between observed and expected values in each species. <i>P</i>-values were then adjusted using the Sidak correction for multiple comparisons. After correction, * P<0.009; ** P<0.002; *** P<0.001. (<b>b</b>) Linear regression of expected <i>versus</i> observed root length of <i>Plantago</i> and <i>Festuca</i> in mixtures over the whole experiment, and null expectation expected = observed (1∶1). Significance of deviation of slopes from unity is shown by p-values. Data are means ± SE, N = 3–4.</p

Genetic and epigenetic differentiation across intertidal gradients in the foundation plant Spartina alterniflora

Ecological genomics approaches have informed us about the structure of genetic diversity in natural populations that might underlie patterns in trait variation. However, we still know surprisingly little about the mechanisms that permit organisms to adapt to variable environmental conditions. The salt marsh foundation plant Spartina alterniflora exhibits a dramatic range in phenotype that is associated with a pronounced intertidal environmental gradient across a narrow spatial scale. Both genetic and non-genetic molecular mechanisms might underlie this phenotypic variation. To investigate both, we used epigenotyping-by-sequencing (epiGBS) to evaluate the make-up of natural populations across the intertidal environmental gradient. Based on recent findings, we expected that both DNA sequence and DNA methylation diversity would be explained by source population and habitat within populations. However, we predicted that epigenetic variation might be more strongly associated with habitat since similar epigenetic modifications could be rapidly elicited across different genetic backgrounds by similar environmental conditions. Overall, with PERMANOVA we found that population of origin explained a significant amount of the genetic (8.6%) and epigenetic (3.2%) variance. In addition, we found that a small but significant amount of genetic and epigenetic variance (<1%) was explained by habitat within populations. The interaction of population and habitat explained an additional 2.9% of the genetic variance and 1.4% of the epigenetic variance. By examining genetic and epigenetic variation within the same fragments (variation in close-cis), we found that population explained epigenetic variation in 9.2% of 8,960 tested loci, even after accounting for differences in the DNA sequence of the fragment. Habitat alone explained very little (<0.1%) of the variation in these close-cis comparisons, but the interaction of population and habitat explained 2.1% of the epigenetic variation in these loci. Using multiple matrix regression with randomization (MMRR) we found that phenotypic differences in natural populations were correlated with epigenetic and environmental differences even when accounting for genetic differences. Our results support the contention that sequence variation explains most of the variation in DNA methylation, but we have provided evidence that DNA methylation distinctly contributes to plant responses in natural populations.Publikationsfonds ML