Several reduced-representation bisulfite sequencing methods have been developed in recent years to determine cytosine methylation de novo in nonmodel species. Here, we present epiGBS2, a laboratory protocol based on epiGBS with a revised and user-friendly bioinformatics pipeline for a wide range of species with or without a reference genome. epiGBS2 is cost- and time-efficient and the computational workflow is designed in a user-friendly and reproducible manner. The library protocol allows a flexible choice of restriction enzymes and a double digest. The bioinformatics pipeline was integrated in the Snakemake workflow management system, which makes the pipeline easy to execute and modular, and parameter settings for important computational steps flexible. We implemented bismark for alignment and methylation analysis and we preprocessed alignment files by double masking to enable single nucleotide polymorphism calling with Freebayes (epiFreebayes). The performance of several critical steps in epiGBS2 was evaluated against baseline data sets from Arabidopsis thaliana and great tit (Parus major), which confirmed its overall good performance. We provide a detailed description of the laboratory protocol and an extensive manual of the bioinformatics pipeline, which is publicly accessible on github (https://github.com/nioo-knaw/epiGBS2) and zenodo (https://doi.org/10.5281/zenodo.4764652).

Plant interactions are as important belowground as aboveground. Belowground plant interactions are however inherently difficult to quantify, as roots of different species are difficult to disentangle. Although for a couple of decades molecular techniques have been successfully applied to quantify root abundance, root identification and quantification in multispecies plant communities remains particularly challenging. Here we present a novel methodology, multispecies genotyping by sequencing (msGBS), as a next step to tackle this challenge. First, a multispecies meta-reference database containing thousands of gDNA clusters per species is created from GBS derived High Throughput Sequencing (HTS) reads. Second, GBS derived HTS reads from multispecies root samples are mapped to this meta-reference which, after a filter procedure to increase the taxonomic resolution, allows the parallel quantification of multiple species. The msGBS signal of 111 mock-mixture root samples, with up to 8 plant species per sample, was used to calculate the within-species abundance. Optional subsequent calibration yielded the across-species abundance. The within- and across-species abundances highly correlated (R-2 range 0.72-0.94 and 0.85-0.98, respectively) to the biomass-based species abundance. Compared to a qPCR based method which was previously used to analyse the same set of samples, msGBS provided similar results. Additional data on 11 congener species groups within 105 natural field root samples showed high taxonomic resolution of the method. msGBS is highly scalable in terms of sensitivity and species numbers within samples, which is a major advantage compared to the qPCR method and advances our tools to reveal hidden belowground interactions.

epiGBS is an existing reduced representation bisulfite sequencing method to determine cytosine methylation and genetic polymorphisms de novo . Here, we present epiGBS2, an improved epiGBS laboratory protocol and user-friendly bioinformatics pipeline for a wide range of species with or without reference genome. epiGBS2 decreases costs and time investment and increases user-friendliness and reproducibility. The library protocol was adjusted to allow for a flexible choice of restriction enzymes and a double digest. Instead of fully methylated adapters, semi-methylated adapters are now used. The bioinformatics pipeline was improved in speed and integrated in the snakemake workflow management system, which now makes the pipeline easy to execute, modular, and parameter settings flexible. We also provide a detailed description of the laboratory protocol, an extensive manual of the bioinformatics pipeline, which is publicly accessible on github ( https://github.com/nioo-knaw/epiGBS2 ) and zenodo ( https://doi.org/10.5281/zenodo.3819996 ), and example output.

Stochastic changes in DNA methylation (i.e., spontaneous epimutations) contribute to methylome diversity in plants. Here, we describe AlphaBeta, a computational method for estimating the precise rate of such stochastic events using pedigree-based DNA methylation data as input. We demonstrate how AlphaBeta can be employed to study transgenerationally heritable epimutations in clonal or sexually derived mutation accumulation lines, as well as somatic epimutations in long-lived perennials. Application of our method to published and new data reveals that spontaneous epimutations accumulate neutrally at the genome-wide scale, originate mainly during somatic development and that they can be used as a molecular clock for age-dating trees.

Summary Despite the limitations of genetic bottlenecks, several invasive species appear to thrive in non-native ranges with extremely low levels of sequence-based genetic variation. We previously demonstrated differentiation of DNA methylation to habitat types of the highly clonal, genetically depauperate Japanese knotweeds using anonymous markers, but the functional relevance of this DNA methylation variation is unknown. Here, we sequenced the full transcriptome combined with a reduced representation bisulfite sequencing approach, epigenotyping by sequencing (epiGBS), to characterize the association among DNA methylation, functional transcripts and the diverse habitat types occupied by the invasive Reynoutria species. We identified 50,435 putative transcripts overall, of which 48,866 were annotated with the NCBI NR database. Of these 17,872 (35%) and 16,122 (32%) transcripts shared sequence identity with Arabidopsis thaliana and Beta vulgaris , respectively. We found genetic differentiation by habitat type suggesting the action of selection and a marginal pattern of differentiation of DNA methylation among habitats, which appears to be associated with sequence differences. However, we found no individual methylation loci associated with habitat, limiting our ability to make functional interpretations. Regardless of the source of variation in DNA methylation, these changes may represent an important component of the response to environmental conditions, particularly in highly clonal plants, but more fine scale genomics analysis is required to test if DNA methylation variation in this system is responsible for functional divergence.

In long-term grassland experiments, positive biodiversity effects on plant productivity commonly increase with time. Subsequent glasshouse experiments showed that these strengthened positive biodiversity effects persist not only in the local environment but also when plants are transferred into a common environment. Thus, we hypothesized that community diversity had acted as a selective agent, resulting in the emergence of plant monoculture and mixture types with differing genetic composition. To test our hypothesis, we grew offspring from plants that were grown for eleven years in monoculture or mixture environments in a biodiversity experiment (Jena Experiment) under controlled glasshouse conditions in monocultures or two-species mixtures. We used epiGBS, a genotyping-by-sequencing approach combined with bisulphite conversion, to provide integrative genetic and epigenetic (i.e., DNA methylation) data. We observed significant divergence in genetic and DNA methylation data according to selection history in three out of five perennial grassland species, namely Galium mollugo, Prunella vulgaris and Veronica chamaedrys, with DNA methylation differences mostly reflecting the genetic differences. In addition, current diversity levels in the glasshouse had weak effects on epigenetic variation. However, given the limited genome coverage of the reference-free bisulphite method epiGBS, it remains unclear how much of the differences in DNA methylation was independent of underlying genetic differences. Our results thus suggest that selection of genetic variants, and possibly epigenetic variants, caused the rapid emergence of monoculture and mixture types within plant species in the Jena Experiment.

AbstractIntroductionHeritable changes in cytosine methylation can arise stochastically in plant genomes independently of DNA sequence alterations. These so-called ‘spontaneous epimutations’ appear to be a byproduct of imperfect DNA methylation maintenance during mitotic or meitotic cell divisions. Accurate estimates of the rate and spectrum of these stochastic events are necessary to be able to quantify how epimutational processes shape methylome diversity in the context of plant evolution, development and aging.MethodHere we describe AlphaBeta, a computational method for estimating epimutation rates and spectra from pedigree-based high-throughput DNA methylation data. The approach requires that the topology of the pedigree is known, which is typically the case in the experimental construction of mutation accumulation lines (MA-lines) in sexually or clonally reproducing species. However, this method also works for inferring somatic epimutation rates in long-lived perennials, such as trees, using leaf methylomes and coring data as input. In this case, we treat the tree branching structure as an intra-organismal phylogeny of somatic lineages and leverage information about the epimutational history of each branch.ResultsTo illustrate the method, we applied AlphaBeta to multi-generational data from selfing- and asexually-derived MA-lines in Arabidopsis and dandelion, as well as to intra-generational leaf methylome data of a single poplar tree. Our results show that the epimutation landscape in plants is deeply conserved across angiosperm species, and that heritable epimutations originate mainly during somatic development, rather than from DNA methylation reinforcement errors during sexual reproduction. Finally, we also provide the first evidence that DNA methylation data, in conjunction with statistical epimutation models, can be used as a molecular clock for age-dating trees.ConclusionAlphaBeta faciliates unprecedented quantitative insights into epimutational processes in a wide range of plant systems. Software implementing our method is available as a Bioconductor R package at http://bioconductor.org/packages/3.10/bioc/html/AlphaBeta.html

Theory predicts that environmental challenges can shape the composition of populations, which is manifest at the molecular level. Previously, we demonstrated that oil pollution affected gene expression patterns and altered genetic variation in natural populations of the foundation salt marsh grass, Spartina alterniflora. Here, we used a reduced representation bisulfite sequencing approach, epigenotyping by sequencing (epiGBS), to examine relationships among DNA sequence, DNA methylation, gene expression, and exposure to oil pollution. We documented genetic and methylation differentiation between oil-exposed and unexposed populations, suggesting that the Deepwater Horizon oil spill may have selected on genetic variation, and either selected on epigenetic variation or induced particular epigenotypes and expression patterns in exposed compared to unexposed populations. In support of the potential for differential response to the Deepwater Horizon oil spill, we demonstrate genotypic differences in response to oil under controlled conditions. Overall, these findings demonstrate genetic variation, epigenetic variation and gene expression are correlated to exposure to oil pollution, which may all contribute to the response to environmental stress.

LC-MS data of dandelion leaf tissue after direct and/or parental JA treatment: normalized peak intensity signals from nagative and positive ionisation modes. Total phenolics quantification (in tannic acid equivalents) in dandelion leaf tissue after direct and/or parental JA treatment.

Growing evidence makes a strong case that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology from dissecting developmental processes to understanding aspects of human health and disease. In ecology, recent studies have merged ecological experimental design with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress response, adaptation to habitat, or species range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, many studies with non-model species have so far been limited to describing broad patterns based on anonymous markers of DNA methylation. In contrast, studies with model species have benefited from powerful genomic resources, which allow for a more mechanistic understanding but have limited ecological realism. To understand the true significance of epigenetics for plant ecology and evolution, we must combine both approaches transferring knowledge and methods from model-species research to genomes of evolutionarily divergent species, and examining responses to complex natural environments at a more mechanistic level. This requires transforming genomics tools specifically for studying non-model species, which is challenging given the large and often polyploid genomes of plants. Collaboration between molecular epigeneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes.

Summary Parental environments can influence offspring traits. However, the magnitude of the impact of parental environments on offspring molecular phenotypes is poorly understood. Here, we test the direct effects and intergenerational effects of jasmonic acid (JA) treatment, which is involved in herbivory‐induced defense signaling, on transcriptomes and metabolomes in apomictic common dandelion (Taraxacum officinale). In a full factorial crossed design with parental and offspring JA and control treatments, we performed leaf RNA‐seq gene expression analysis, LC‐MS metabolomics and total phenolics assays in offspring plants. Expression analysis, leveraged by a de novo assembled transcriptome, revealed an induced response to JA exposure that is consistent with known JA effects. The intergenerational effect of treatment was considerable: 307 of 858 detected JA‐responsive transcripts were affected by parental JA treatment. In terms of the numbers of metabolites affected, the magnitude of the chemical response to parental JA exposure was c. 10% of the direct JA treatment response. Transcriptome and metabolome analyses both identified the phosphatidylinositol signaling pathway as a target of intergenerational JA effects. Our results highlight that parental environments can have substantial effects in offspring generations. Transcriptome and metabolome assays provide a basis for zooming in on the potential mechanisms of inherited JA effects.

Christina L. Richards,* Conchita Alonso, Claude Becker, Oliver Bossdorf, Etienne Bucher, Maria Colom e-Tatch e, Walter Durka, Jan Engelhardt, Bence Gaspar, Andreas Gogol-D€ oring, Ivo Grosse, Thomas P. van Gurp, Katrin Heer, Ilkka Kronholm, Christian Lampei, V ıt Latzel, Marie Mirouze, Lars Opgenoorth, Ovidiu Paun, Sonja J. Prohaska, Stefan A. Rensing, Peter F. Stadler, Emiliano Trucchi, Kristian Ullrich and Koen J. F. Verhoeven Abstract Growing evidence shows that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology. In plant ecology, recent studies have attempted to merge ecological experiments with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress responses, adaptation to habitat, and range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, studies with non-model species have so far been limited to describing broad patterns based on anonymous markers of DNA methylation. In contrast, studies with model species have benefited from powerful genomic resources, which contribute to a more mechanistic understanding but have limited ecological realism. Understanding the significance of epigenetics for plant ecology requires increased transfer of knowledge and methods from model species research to genomes of evolutionarily divergent species, and examination of responses to complex natural environments at a more mechanistic level. This requires transforming genomics tools specifically for studying non-model species, which is challenging given the large and often polyploid genomes of plants. Collaboration among molecular geneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes.

We describe epiGBS, a reduced representation bisulfite sequencing method for cost-effective exploration and comparative analysis of DNA methylation and genetic variation in hundreds of samples de novo. This method uses genotyping by sequencing of bisulfite-converted DNA followed by reliable de novo reference construction, mapping, variant calling, and distinction of single-nucleotide polymorphisms (SNPs) versus methylation variation (software is available at https://github.com/thomasvangurp/epiGBS). The output can be loaded directly into a genome browser for visualization and into RnBeads for analysis of differential methylation.

Background Transposable elements (TEs) are mobile pieces of genetic information with high mutagenic potential for the host genome. Transposition is often neutral or deleterious but may also generate potentially adaptive genetic variation. This additional source of variation could be especially relevant in non-recombining species reproducing asexually. However, evidence is lacking to determine the relevance of TEs in plant asexual genome evolution and their associated effects. Here, we characterize the repetitive fraction of the genome of the common dandelion, Taraxacum officinale and compare it between five accessions from the same apomictic lineage. The main objective of this study is to evaluate the extent of within-lineage divergence attributed to TE content and activity. We examined the repetitive genomic contribution, diversity, transcription and methylation changes to characterize accession-specific TEs. Results Using low-coverage genomic sequencing, we report a highly heterogeneous TE compartment in the triploid apomict T. officinale representing up to 38.6 % of the homoploid genome. The repetitive compartment is dominated by LTR retrotransposon families accompanied by few non-LTR retrotransposons and DNA transposons. Up to half of the repeat clusters are biased towards very high read identity, indicating recent and potentially ongoing activity of these TE families. Interestingly, the five accessions are divided into two main clades based on their TE composition. Clade 2 is more dynamic than clade 1 with higher abundance of Gypsy Chromovirus sequences and transposons. Furthermore, a few low-abundant genomic TE clusters exhibit high level of transcription in two of the accessions analysed. Using reduced representation bisulfite sequencing, we detected 18.9 % of loci differentially methylated, of which 25.4 and 40.7 % are annotated as TEs or functional genes, respectively. Additionally, we show clear evidence for accession-specific TE families that are differentially transcribed and differentially methylated within the apomictic lineage, including one Copia Ale II LTR element and a PIF-Harbinger DNA transposon. Conclusion We report here a very young and dynamic repetitive compartment that enhances divergence within one asexual lineage of T. officinale . We speculate that accession-specific TE families that are both transcriptionally and epigenetically variable are more prone to trigger changes in expression on nearby coding sequences. These findings emphasize the potential of TE-induced mutations on functional genes during asexual genome evolution.

Priming of random hexamers in cDNA synthesis is known to show sequence bias, but in addition it has been suggested recently that mismatches in random hexamer priming could be a cause of mismatches between the original RNA fragment and observed sequence reads. To explore random hexamer mispriming as a potential source of these errors, we analyzed two independently generated RNA-seq datasets of synthetic ERCC spikes for which the reference is known. First strand cDNA synthesized by random hexamer priming on RNA showed consistent position and nucleotide-specific mismatch errors in the first seven nucleotides. The mismatch errors found in both datasets are consistent in distribution and thermodynamically stable mismatches are more common. This strongly indicates that RNA-DNA mispriming of specific random hexamers causes these errors. Due to their consistency and specificity, mispriming errors can have profound implications for downstream applications if not dealt with properly.

Heritable epigenetic modulation of gene expression is a candidate mechanism to explain parental environmental effects on offspring phenotypes, but current evidence for environment-induced epigenetic changes that persist in offspring generations is scarce. In apomictic dandelions, exposure to various stresses was previously shown to heritably alter DNA methylation patterns. In this study we explore whether these induced changes are accompanied by heritable effects on offspring phenotypes. We observed effects of parental jasmonic acid treatment on offspring specific leaf area and on offspring interaction with a generalist herbivore; and of parental nutrient stress on offspring root-shoot biomass ratio, tissue P-content and leaf morphology. Some of the effects appeared to enhance offspring ability to cope with the same stresses that their parents experienced. Effects differed between apomictic genotypes and were not always consistently observed between different experiments, especially in the case of parental nutrient stress. While this context-dependency of the effects remains to be further clarified, the total set of results provides evidence for the existence of transgenerational effects in apomictic dandelions. Zebularine treatment affected the within-generation response to nutrient stress, pointing at a role of DNA methylation in phenotypic plasticity to nutrient environments. This study shows that stress exposure in apomictic dandelions can cause transgenerational phenotypic effects, in addition to previously demonstrated transgenerational DNA methylation effects.

Background SNP (Single Nucleotide Polymorphism) markers are rapidly becoming the markers of choice for applications in breeding because of next generation sequencing technology developments. For SNP development by NGS technologies, correct assembly of the huge amounts of sequence data generated is essential. Little is known about assembler's performance, especially when dealing with highly heterogeneous species that show a high genome complexity and what the possible consequences are of differences in assemblies on SNP retrieval. This study tested two assemblers (CAP3 and CLC) on 454 data from four lily genotypes and compared results with respect to SNP retrieval. Results CAP3 assembly resulted in higher numbers of contigs, lower numbers of reads per contig, and shorter average read lengths compared to CLC. Blast comparisons showed that CAP3 contigs were highly redundant. Contrastingly, CLC in rare cases combined paralogs in one contig. Redundant and chimeric contigs may lead to erroneous SNPs. Filtering for redundancy can be done by blasting selected SNP markers to the contigs and discarding all the SNP markers that show more than one blast hit. Results on chimeric contigs showed that only four out of 2,421 SNP markers were selected from chimeric contigs. Conclusion In practice, CLC performs better in assembling highly heterogeneous genome sequences compared to CAP3, and consequently SNP retrieval is more efficient. Additionally a simple flow scheme is suggested for SNP marker retrieval that can be valid for all non-model species.