Contiguous and stochastic CHH methylation patterns of plant DRM2 and CMT2 revealed by single-read methylome analysis

5-mC methylation study of sORFs in 3'UTR of transcription factor JUNGBRUNNEN 1-like during leaf rust pathogenesis in wheat

BACKGROUND

JUB1, a NAC domain containing hydrogen peroxide-induced transcription factor, plays a critical role in plant immunity. Little is known about how JUB1 responds to leaf rust disease in wheat. Recent discoveries in genomics have also unveiled a multitude of sORFs often assumed to be non-functional, to argue for the necessity of including them as potential regulatory players of translation. However, whether methylation on sORFs spanning the 3'UTR of regulatory genes like JUB1 modulate gene expression, remains unclear.

METHODS AND RESULTS

In this study, we identified the methylation states of two sORFs in 3'UTR of a homologous gene of JUB1 in wheat, TaJUB1-L, at cytosine residues in CpG, CHH and CHG sites at different time points of disease progression in two near-isogenic lines of wheat (HD2329), with and without Lr24 gene during leaf rust pathogenesis. Here, we report a significant demethylation of the CpG dinucleotides occurring in the sORFs of the 3'UTR in the resistant isolines after 24 h post-infection. Also, the up-regulated gene expression observed through RT-qPCR was directly proportional to the demethylation of the CpG sites in the sORFs.

CONCLUSIONS

Our findings indicate that TaJUB1-L might be a positive regulator in providing tolerance during leaf rust pathogenesis and cytosine methylation at 3'UTR might act as a switch for its expression control. These results enrich the potential benefit of conventional methylation assay techniques for unraveling the unexplored enigma in epigenetics during plant-pathogen interaction in a cost-effective and confidentially conclusive manner.

Reprogramming of DNA methylation and changes of gene expression in grafted Hevea brasiliensis

Rubber tree (Hevea brasiliensis) is reproduced by bud grafting for commercial planting, but significant intraclonal variations exist in bud-grafted clones. DNA methylation changes related to grafting may be partly responsible for intraclonal variations. In the current study, whole-genome DNA methylation profiles of grafted rubber tree plants (GPs) and their donor plants (DPs) were evaluated by whole-genome bisulfite sequencing. Data showed that DNA methylation was downregulated and DNA methylations in CG, CHG, and CHH sequences were reprogrammed in GPs, suggesting that grafting induced the reprogramming of DNA methylation. A total of 5,939 differentially methylated genes (DMGs) were identified by comparing fractional methylation levels between GPs and DPs. Transcriptional analysis revealed that there were 9,798 differentially expressed genes (DEGs) in the DP and GP comparison. A total of 1,698 overlapping genes between DEGs and DMGs were identified. These overlapping genes were markedly enriched in the metabolic pathway and biosynthesis of secondary metabolites by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Global DNA methylation and transcriptional analyses revealed that reprogramming of DNA methylation is correlated with gene expression in grafted rubber trees. The study provides a whole-genome methylome of rubber trees and an insight into the molecular mechanisms underlying the intraclonal variations existing in the commercial planting of grafted rubber trees.

Estimating genome-wide DNA methylation heterogeneity with methylation patterns

BACKGROUND

In a heterogeneous population of cells, individual cells can behave differently and respond variably to the environment. This cellular diversity can be assessed by measuring DNA methylation patterns. The loci with variable methylation patterns are informative of cellular heterogeneity and may serve as biomarkers of diseases and developmental progression. Cell-to-cell methylation heterogeneity can be evaluated through single-cell methylomes or computational techniques for pooled cells. However, the feasibility and performance of these approaches to precisely estimate methylation heterogeneity require further assessment.

RESULTS

Here, we proposed model-based methods adopted from a mathematical framework originally from biodiversity, to estimate genome-wide DNA methylation heterogeneity. We evaluated the performance of our models and the existing methods with feature comparison, and tested on both synthetic datasets and real data. Overall, our methods have demonstrated advantages over others because of their better correlation with the actual heterogeneity. We also demonstrated that methylation heterogeneity offers an additional layer of biological information distinct from the conventional methylation level. In the case studies, we showed that distinct profiles of methylation heterogeneity in CG and non-CG methylation can predict the regulatory roles between genomic elements in Arabidopsis. This opens up a new direction for plant epigenomics. Finally, we demonstrated that our score might be able to identify loci in human cancer samples as putative biomarkers for early cancer detection.

CONCLUSIONS

We adopted the mathematical framework from biodiversity into three model-based methods for analyzing genome-wide DNA methylation heterogeneity to monitor cellular heterogeneity. Our methods, namely MeH, have been implemented, evaluated with existing methods, and are open to the research community.

On the prediction of non-CG DNA methylation using machine learning

DNA methylation can be detected and measured using sequencing instruments after sodium bisulfite conversion, but experiments can be expensive for large eukaryotic genomes. Sequencing nonuniformity and mapping biases can leave parts of the genome with low or no coverage, thus hampering the ability of obtaining DNA methylation levels for all cytosines. To address these limitations, several computational methods have been proposed that can predict DNA methylation from the DNA sequence around the cytosine or from the methylation level of nearby cytosines. However, most of these methods are entirely focused on CG methylation in humans and other mammals. In this work, we study, for the first time, the problem of predicting cytosine methylation for CG, CHG and CHH contexts on six plant species, either from the DNA primary sequence around the cytosine or from the methylation levels of neighboring cytosines. In this framework, we also study the cross-species prediction problem and the cross-context prediction problem (within the same species). Finally, we show that providing gene and repeat annotations allows existing classifiers to significantly improve their prediction accuracy. We introduce a new classifier called AMPS (annotation-based methylation prediction from sequence) that takes advantage of genomic annotations to achieve higher accuracy.

Re-analysis of publicly available methylomes using signal detection yields new information

Cytosine methylation is an epigenetic mark that participates in regulation of gene expression and chromatin stability in plants. Advancements in whole genome sequencing technologies have enabled investigation of methylome dynamics under different conditions. However, the computational methods for analyzing bisulfite sequence data have not been unified. Contention remains in the correlation of differentially methylated positions with the investigated treatment and exclusion of noise, inherent to these stochastic datasets. The prevalent approaches apply Fisher's exact test, logistic, or beta regression, followed by an arbitrary cut-off for differences in methylation levels. A different strategy, the MethylIT pipeline, utilizes signal detection to determine cut-off based on a fitted generalized gamma probability distribution of methylation divergence. Re-analysis of publicly available BS-seq data from two epigenetic studies in Arabidopsis and applying MethylIT revealed additional, previously unreported results. Methylome repatterning in response to phosphate starvation was confirmed to be tissue-specific and included phosphate assimilation genes in addition to sulfate metabolism genes not implicated in the original study. During seed germination plants undergo major methylome reprogramming and use of MethylIT allowed us to identify stage-specific gene networks. We surmise from these comparative studies that robust methylome experiments must account for data stochasticity to achieve meaningful functional analyses.

Unravelling Differential DNA Methylation Patterns in Genotype Dependent Manner under Salinity Stress Response in Chickpea

DNA methylation is one of the epigenetic mechanisms that govern gene regulation in response to abiotic stress in plants. Here, we analyzed the role of epigenetic variations by exploring global DNA methylation and integrating it with differential gene expression in response to salinity stress in tolerant and sensitive chickpea genotypes. Genome-wide DNA methylation profiles showed higher CG methylation in the gene body regions and higher CHH methylation in the TE body regions. The analysis of differentially methylated regions (DMRs) suggested more hyper-methylation in response to stress in the tolerant genotype compared to the sensitive genotype. We observed higher enrichment of CG DMRs in genes and CHH DMRs in transposable elements (TEs). A positive correlation of gene expression with CG gene body methylation was observed. The enrichment analysis of DMR-associated differentially expressed genes revealed they are involved in biological processes, such as lateral root development, transmembrane transporter activity, GTPase activity, and regulation of gene expression. Further, a high correlation of CG methylation with CHG and CHH methylation under salinity stress was revealed, suggesting crosstalk among the methylation contexts. Further, we observed small RNA-mediated CHH hypermethylation in TEs. Overall, the interplay between DNA methylation, small RNAs, and gene expression provides new insights into the regulatory mechanism underlying salinity stress response in chickpeas.

Methylome Imputation by Methylation Patterns

DNA methylation is studied extensively for its relations with several biological processes such as transcriptional regulation. While methylation levels are usually estimated per cytosine or genomic region, additional information on methylation heterogeneity can be obtained when considering stretches of successive cytosines on the same reads; however, the majority of methylomes suffer from low coverage of genomic regions with sequencing depths enough for accurate estimation of methylation heterogeneity using existing methods. Here we describe a probabilistic-based imputation method that makes use of methylation information from neighboring sites to recover partially observed methylation patterns. Our method and software are proven to be faster and more accurate among all evaluated. Ultimately, our method allows for a more streamlined monitoring of epigenetic changes within cellular populations and their putative role in disease.

Mitotically heritable epigenetic modifications of CmMYB6 control anthocyanin biosynthesis in chrysanthemum

Flower color, which is determined by various chemical pigments, is a vital trait for ornamental plants, in which anthocyanin is a major component. However, the epigenetic regulation of anthocyanin biosynthesis remains poorly understood. During chrysanthemum cultivation, we found a heterochromatic chrysanthemum accession (YP) whose progeny generated by asexual reproduction contained both yellow-flowered (YP-Y) and pink-flowered (YP-P) plants. In this study, we aimed to elucidate the epigenetic mechanisms of different flower colors in the YP plant progeny. Metabolome and transcriptome analyses revealed that the difference in flower color between YP-Y and YP-P was caused by expression variation of the anthocyanin biosynthesis gene CmMYB6. Bisulfite sequencing revealed that methylation at the CmMYB6 promoter, especially in the CHH context, was higher in YP-Y than YP-P. After demethylation of the CmMYB6 promoter using the dCas9-TET1cd system, the flower color returned from yellow to pink. Furthermore, the methylation status of the CmMYB6 promoter was higher in YP-Y over three consecutive generations, indicating that this methylation status was heritable mitotically. Finally, investigation of other chrysanthemum cultivars showed that the methylation of CmMYB6 decreased gradually with the increase in anthocyanin content. These results lay an epigenetic foundation for the improvement of flower color in horticultural plants.

Identification of Putative Markers of Non-infectious Bud Failure in Almond [Prunus dulcis (Mill.) D.A. Webb] Through Genome Wide DNA Methylation Profiling and Gene Expression Analysis in an Almond × Peach Hybrid Population

Almond [Prunus dulcis (Mill.) D.A. Webb] is an economically important nut crop susceptible to the genetic disorder, Non-infectious Bud Failure (NBF). Despite the severity of exhibition in several prominent almond cultivars, no causal mechanism has been identified underlying NBF development. The disorder is hypothesized to be associated with differential DNA methylation patterns based on patterns of inheritance (i.e., via sexual reproduction and clonal propagation) and previous work profiling methylation in affected trees. Peach (Prunus persica L. Batsch) is a closely related species that readily hybridizes with almond; however, peach is not known to exhibit NBF. A cross between an NBF-exhibiting 'Carmel' cultivar and early flowering peach ('40A17') produced an F₁ where ∼50% of progeny showed signs of NBF, including canopy die-back, erratic branching patterns (known as "crazy-top"), and rough bark. In this study, whole-genome DNA methylation profiles were generated for three F₁ progenies exhibiting NBF and three progenies considered NBF-free. Subsequent alignment to both the almond and peach reference genomes showed an increase in genome-wide methylation levels in NBF hybrids in CG and CHG contexts compared to no-NBF hybrids when aligned to the almond genome but no difference in methylation levels when aligned to the peach genome. Significantly differentially methylated regions (DMRs) were identified by comparing methylation levels across the genome between NBF- and no-NBF hybrids in each methylation context. In total, 115,635 DMRs were identified based on alignment to the almond reference genome, and 126,800 DMRs were identified based on alignment to the peach reference genome. Nearby genes were identified as associated with the 39 most significant DMRs occurring either in the almond or peach alignments alone or occurring in both the almond and peach alignments. These DMR-associated genes include several uncharacterized proteins and transposable elements. Quantitative PCR was also performed to analyze the gene expression patterns of these identified gene targets to determine patterns of differential expression associated with differential DNA methylation. These DMR-associated genes, particularly those showing corresponding patterns of differential gene expression, represent key targets for almond breeding for future cultivars and mitigating the effects of NBF-exhibition in currently affected cultivars.

BSImp: Imputing Partially Observed Methylation Patterns for Evaluating Methylation Heterogeneity

DNA methylation is one of the most studied epigenetic modifications that has applications ranging from transcriptional regulation to aging, and can be assessed by bisulfite sequencing (BS-seq) or enzymatic methyl sequencing (EM-seq) at single base-pair resolution. The permutations of methylation statuses given by aligned reads reflect the methylation patterns of individual cells. These patterns at specific genomic locations are sought to be indicative of cellular heterogeneity within a cellular population, which are predictive of developments and diseases; therefore, methylation heterogeneity has potentials in early detection of these changes. Computational methods have been developed to assess methylation heterogeneity using methylation patterns formed by four consecutive CpGs, but the nature of shotgun sequencing often give partially observed patterns, which makes very limited data available for downstream analysis. While many programs are developed to impute genome-wide methylation levels, currently there is only one method developed for recovering partially observed methylation patterns; however, the program needs lots of data to train and cannot be used directly; therefore, we developed a probabilistic-based imputation method that uses information from neighbouring sites to recover partially observed methylation patterns speedily. It is demonstrated to allow for the evaluation of methylation heterogeneity at 15% more regions genome-wide with high accuracy for data with moderate depth. To make it more user-friendly we also provide a computational pipeline for genome-screening, which can be used in both evaluating methylation levels and profiling methylation patterns genomewide for all cytosine contexts, which is the first of its kind. Our method allows for accurate estimation of methylation levels and makes evaluating methylation heterogeneity available for much more data with reasonable coverage, which has important implications in using methylation heterogeneity for monitoring changes within the cellular populations that were impossible to detect for the assessment of development and diseases.

Grafting vigour is associated with DNA de-methylation in eggplant

In horticulture, grafting is a popular technique used to combine positive traits from two different plants. This is achieved by joining the plant top part (scion) onto a rootstock which contains the stem and roots. Rootstocks can provide resistance to stress and increase plant production, but despite their wide use, the biological mechanisms driving rootstock-induced alterations of the scion phenotype remain largely unknown. Given that epigenetics plays a relevant role during distance signalling in plants, we studied the genome-wide DNA methylation changes induced in eggplant (Solanum melongena) scion using two interspecific rootstocks to increase vigour. We found that vigour was associated with a change in scion gene expression and a genome-wide hypomethylation in the CHH context. Interestingly, this hypomethylation correlated with the downregulation of younger and potentially more active long terminal repeat retrotransposable elements (LTR-TEs), suggesting that graft-induced epigenetic modifications are associated with both physiological and molecular phenotypes in grafted plants. Our results indicate that the enhanced vigour induced by heterografting in eggplant is associated with epigenetic modifications, as also observed in some heterotic hybrids.

Perspectives for epigenetic editing in crops

Site-specific nucleases (SSNs) have drawn much attention in plant biotechnology due to their ability to drive precision mutagenesis, gene targeting or allele replacement. However, when devoid of its nuclease activity, the underlying DNA-binding activity of SSNs can be used to bring other protein functional domains close to specific genomic sites, thus expanding further the range of applications of the technology. In particular, the addition of functional domains encoding epigenetic effectors and chromatin modifiers to the CRISPR/Cas ribonucleoprotein complex opens the possibility to introduce targeted epigenomic modifications in plants in an easily programmable manner. Here we examine some of the most important agronomic traits known to be controlled epigenetically and review the best studied epigenetic catalytic effectors in plants, such as DNA methylases/demethylases or histone acetylases/deacetylases and their associated marks. We also review the most efficient strategies developed to date to functionalize Cas proteins with both catalytic and non-catalytic epigenetic effectors, and the ability of these domains to influence the expression of endogenous genes in a regulatable manner. Based on these new technical developments, we discuss the possibilities offered by epigenetic editing tools in plant biotechnology and their implications in crop breeding.

DNA methylation mutants in Physcomitrella patens elucidate individual roles of CG and non-CG methylation in genome regulation

Cytosine (DNA) methylation in plants regulates the expression of genes and transposons. While methylation in plant genomes occurs at CG, CHG, and CHH sequence contexts, the comparative roles of the individual methylation contexts remain elusive. Here, we present Physcomitrella patens as the second plant system, besides Arabidopsis thaliana, with viable mutants with an essentially complete loss of methylation in the CG and non-CG contexts. In contrast to A. thaliana, P. patens has more robust CHH methylation, similar CG and CHG methylation levels, and minimal cross-talk between CG and non-CG methylation, making it possible to study context-specific effects independently. Our data found CHH methylation to act in redundancy with symmetric methylation in silencing transposons and to regulate the expression of CG/CHG-depleted transposons. Specific elimination of CG methylation did not dysregulate transposons or genes. In contrast, exclusive removal of non-CG methylation massively up-regulated transposons and genes. In addition, comparing two exclusively but equally CG- or CHG-methylated genomes, we show that CHG methylation acts as a greater transcriptional regulator than CG methylation. These results disentangle the transcriptional roles of CG and non-CG, as well as symmetric and asymmetric methylation in a plant genome, and point to the crucial role of non-CG methylation in genome regulation.