Dryad_HDY-13-OR0304R_Survival_Growth_Data

Dryad_HDY-13-OR0304R_Survival_Growth_Dat

PFU_Ulaevis_Dryad_data

PFU_Ulaevis_Dryad_dat

Quantification of cytosine methylation in all analyzed genotypes.

<p>Percentage of cytosine methylation and number of polymorphic fragments are provided for each genotype.</p

Detailed isoschizomer-based analysis of Methylation Sensitive fragments (MS).

<p>Comparison of Methylation Sensitive (MS) fragments between <i>Eco</i>RI/<i>Hpa</i>II and <i>Eco</i>RI/<i>Msp</i>I profiles. PMS.- Polymorphic Methylation Sensitive fragments; MMS.- Monomorphic Methylation Sensitive fragments.</p

Epigenetic Variability in the Genetically Uniform Forest Tree Species <i>Pinus pinea</i> L

<div><p>There is an increasing interest in understanding the role of epigenetic variability in forest species and how it may contribute to their rapid adaptation to changing environments. In this study we have conducted a genome-wide analysis of cytosine methylation pattern in <i>Pinus pinea</i>, a species characterized by very low levels of genetic variation and a remarkable degree of phenotypic plasticity. DNA methylation profiles of different vegetatively propagated trees from representative natural Spanish populations of <i>P. pinea</i> were analyzed with the Methylation Sensitive Amplified Polymorphism (MSAP) technique. A high degree of cytosine methylation was detected (64.36% of all scored DNA fragments). Furthermore, high levels of epigenetic variation were observed among the studied individuals. This high epigenetic variation found in <i>P. pinea</i> contrasted with the lack of genetic variation based on Amplified Fragment Length Polymorphism (AFLP) data. In this manner, variable epigenetic markers clearly discriminate individuals and differentiates two well represented populations while the lack of genetic variation revealed with the AFLP markers fail to differentiate at both, individual or population levels. In addition, the use of different replicated trees allowed identifying common polymorphic methylation sensitive MSAP markers among replicates of a given propagated tree. This set of MSAPs allowed discrimination of the 70% of the analyzed trees.</p></div

UPGM tree for genotype identification.

<p>Genetic similarity was calculated and bootstrapped UPGMA clustering was performed for genotype discrimination. Bootstrap computation percentages are shown over the different branches. Tree has been condensed a 25% and clones from the same genotype clustering together are labeled under the genotype code name for easier visualization.</p