Methylation variation promotes phenotypic diversity and evolutionary potential in a millenium-old clonal seagrass meadow
Jueterbock, A.; Boström, C.; Coyer, J. A.; Olsen, J. L.; Kopp, M.; Dhanasiri, A. K.; Smolina, I.; Arnaud-Haond, S.; Van de Peer, Y.; Hoarau, G.
Show abstract
Evolutionary theory predicts that clonal organisms are more susceptible to extinction than sexually reproducing organisms, due to low genetic variation and slow rates of evolution. In agreement, conservation management considers genetic variation as the ultimate measure of a populations ability to survive over time. However, clonal plants are among the oldest living organisms on our planet. Here, we test the hypothesis that clonal seagrass meadows display epigenetic variation that complements genetic variation as a source of phenotypic variation. In a clonal meadow of the seagrass Zostera marina we characterized DNA methylation among 42 shoots. We also sequenced the whole genome of 10 shoots to correlate methylation patterns with photosynthetic performance under exposure to, and recovery from 27{degrees}C, while controlling for somatic mutations. Here, we show for the first time that clonal seagrass shoots display DNA methylation variation that is associated with variation in fitness-related traits: photosynthetic performance and heat stress resilience. The co-variation in DNA methylation and phenotype may be linked via gene expression because methylation patterns varied in functionally relevant genes involved in photosynthesis, and in the repair and prevention of heat-induced protein damage. A >five week epigenetic heat stress memory may heat-harden previously heat-exposed shoots. While genotypic diversity has been shown to enhance stress resilience in seagrass meadows, we suggest that epigenetic variation plays a similar role in meadows dominated by a single genotype. Consequently, conservation management of clonal plants should consider epigenetic variation as indicator of resilience and stability, and restoration efforts may benefit from stress-priming transplanted seeds or shoots.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Plasticity across levels: relating epigenomic, transcriptomic, and phenotypic responses to osmotic stress in a halotolerant microalga 95%
- What can cold-induced transcriptomes of Arctic Brassicaceae tell us about the evolution of cold tolerance? 95%
- Experimental validation of genome-environment associations in Arabidopsis 94%
Similar papers in this journal
- Lifetime genealogical divergence within plants leads to epigenetic mosaicism in the long lived shrub Lavandula latifolia (Lamiaceae) 95%
- Positive Selection and Heat-Response Transcriptomes Reveal Adaptive Features of the Brassicaceae Desert Model, Anastatica hierochuntica 95%
- The architecture of resilience: a genome assembly of Myrothamnus flabellifolia sheds light on desiccation tolerance and sex determination 94%
Similar papers in this journal
- Profiling genome-wide methylation in two maples: fine-scale approaches to detection with nanopore technology 94%
- Genomic and common garden approaches yield complementary results for quantifying environmental drivers of local adaptation in rubber rabbitbrush, a foundational Great Basin shrub 92%
- Within-host adaptation of a foliar pathogen, Xanthomonas, on pepper in presence of quantitative resistance and ozone stress 92%
Similar papers in this journal
- High-resolution methylome analysis in the clonal Populus nigra cv. 'Italica' reveals environmentally sensitive hotspots and drought-responsive TE superfamilies 96%
- Phylogenetically diverse wild plant species use common biochemical strategies to thrive in the Atacama Desert 93%
- Testing the evolutionary potential of an alpine plant: Phenotypic plasticity in response to growth temperature far outweighs parental environmental effects and other genetic causes of variation 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.