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Dandelions ‘remember’ stress: heritable stress‐induced methylation patterns in asexual dandelions

2010· letter· en· W1603354667 on OpenAlexaff
Keith L. Adams

Bibliographic record

VenueNew Phytologist · 2010
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEpigeneticsBiologyDNA methylationMethylationSalicylic acidGeneticsJasmonic acidGeneBotanyEvolutionary biologyGene expression

Abstract

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Plants exhibit a variety of genetic and epigenetic responses to environmental stresses. A well-known response is that transposable elements can be activated (reviewed in Wessler, 1996); other common responses include changes in gene expression levels and patterns (e.g. Kilian et al., 2007), as well as changes in alternative splicing patterns (e.g. Palusa et al., 2007). Among epigenetic phenomena, changes in DNA methylation in response to stress have been investigated in several plants, and both increases and decreases in methylation levels have been discovered (reviewed in Bruce et al., 2007; Lukens & Zhan, 2007; Boyko & Kovalchuk, 2008; Chinnusamy & Zhu, 2009). In some cases the altered methylation levels did not change back to the original levels after the stress was removed (e.g. Steward et al., 2002). In this issue of New Phytologist, Verhoeven et al. (pp. 1108–1118) now show that cytosine methylation patterns in asexual triploid dandelions can change at some loci in response to stress conditions. Moreover, and most notably, some of the altered methylation patterns were heritable in the next generation. …most notably, some of the altered [stress induced] methylation patterns were heritable in the next generation.’ In their study, Verhoeven et al. used asexual, or apomictic, triploid dandelions that reproduce with unfertilized seeds, thus minimizing or eliminating genetic variation among individuals. They used eight plants in each of four stress treatments plus untreated control plants. The stress conditions included high salt, low nutrients, salicylic acid and jasmonic acid stresses; the latter two were used to induce anti-herbivore and anti-pathogen defenses. Changes in methylation were assayed in each plant using the amplified fragment length polymorphism (AFLP) technique with diagnostic methylation-sensitive and methylation-insensitive restriction enzymes. Twenty out of 359 scorable fragments showed evidence of a change in methylation (either gain or loss of methylation) in one or more treatments and in one or more individuals. A large majority (74–92%) of the altered methylation patterns were transmitted to the progeny of the stressed plants that were not exposed to the stresses. The salicylic acid treatments showed the largest number of heritable methylation changes. The fascinating results uncovered by Verhoeven et al. raise many questions about the phenomenon of heritable stress-induced methylation patterns. It will be particularly interesting and important to determine which types of DNA sequences undergo methylation changes in response to environmental stress that are heritable. Are they coding regions, introns, or regulatory regions of genes? Or are they intergenic regions of the genome? Might many of the methylation changes be in transposable elements? Sequencing of the AFLP fragments that displayed the heritable methylation changes in the study by Verhoeven et al. could begin to answer those questions. In addition, the number of methylation changes in a locus could be determined by bisulfite sequencing on some of the loci that were identified by AFLP analysis. In addition, a larger number of loci could be screened by AFLP to identify additional loci that undergo heritable methylation changes in order to shed light on the frequency of different types of DNA sequences involved. If some of the methylation changes occurred in genes it would be important to determine if they affect gene expression. DNA methylation changes are sometimes accompanied by changes in histone modifications, including methylation and acetylation, which affect chromatin structure. Future studies could examine the molecular architecture of chromatin to determine if other epigenetic marks that are affected by stress conditions are also heritable. Verhoeven et al. assayed four stress conditions. Are methylation changes that occur in response to other abiotic and biotic stresses also heritable? Or does the phenomenon occur just after exposure to some types of stresses? Other environmental stresses, such as heat, cold and drought, could be examined. In addition, it would be interesting to expose the plants showing heritable methylation changes to the same stress condition to which their parents were exposed and to compare the responses with plants that had not been treated with the stress in the previous generation. Such experiments might provide insights into the phenotypic consequences of heritable stress-induced methylation changes. Finally, are stress-induced methylation changes heritable in sexual plant species, in addition to apomicts? The dandelions (Taraxicum officinale) provide a nice system in this regard because there are also sexual populations (van Dijk, 2003). In my view, the study of Verhoeven et al. raises more questions than it answers – the authors have opened the door to a potentially vast, unexplored and fascinating avenue of research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.291
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations12
Published2010
Admission routes1
Has abstractyes

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