Identification and analysis of adenine N6-methylation sites in the rice genome

N4-acetyldeoxycytosine DNA modification marks euchromatin regions in Arabidopsis thaliana

BACKGROUND

Direct analogs of chemically modified bases that carry important epigenetic information, such as 5-methylcytosine (m5C)/5-methyldeoxycytosine (5mC), 5-hydroxymethylcytosine (hm5C)/5-hydroxymethyldeoxycytosine (5hmC), and N6-methyladenosine (m6A)/N6-methyldeoxyadenosine (6mA), are detected in both RNA and DNA, respectively. The modified base N4-acetylcytosine (ac4C) is well studied in RNAs, but its presence and epigenetic roles in cellular DNA have not been explored.

RESULTS

Here, we demonstrate the existence of N4-acetyldeoxycytosine (4acC) in genomic DNA of Arabidopsis with multiple detection methods. Genome-wide profiling of 4acC modification reveals that 4acC peaks are mostly distributed in euchromatin regions and present in nearly half of the expressed protein-coding genes in Arabidopsis. 4acC is mainly located around transcription start sites and positively correlates with gene expression levels. Imbalance of 5mC does not directly affect 4acC modification. We also characterize the associations of 4acC with 5mC and histone modifications that cooperatively regulate gene expression. Moreover, 4acC is also detected in genomic DNA of rice, maize, mouse, and human by mass spectrometry.

CONCLUSIONS

Our findings reveal 4acC as a hitherto unknown DNA modification in higher eukaryotes. We identify potential interactions of this mark with other epigenetic marks in gene expression regulation.

Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes

As one of the most common post-transcriptional epigenetic modifications, N6-methyladenine (6 mA), plays an essential role in various cellular processes and disease pathogenesis. Therefore, accurately identifying 6 mA modifications is necessary for a deep understanding of cellular processes and other possible functional mechanisms. Although a few computational methods have been proposed, their respective models were developed with small training datasets. Hence, their practical application is quite limited in genome-wide detection. To overcome the existing limitations, we present a novel model based on transformer architecture and deep learning to identify DNA 6 mA sites from the cross-species genome. The model is constructed on a benchmark dataset and explored a feature derived from pre-trained transformer word embedding approaches. Subsequently, a convolutional neural network was employed to learn the generated features and generate the prediction outcomes. As a result, our predictor achieved excellent performance during independent test with the accuracy and Matthews correlation coefficient (MCC) of 79.3% and 0.58, respectively. Overall, its performance achieved better accuracy than the baseline models and significantly outperformed the existing predictors, demonstrating the effectiveness of our proposed hybrid framework. Furthermore, our model is expected to assist biologists in accurately identifying 6mAs and formulate the novel testable biological hypothesis. We also release source codes and datasets freely at https://github.com/khanhlee/bert-dna for front-end users.

RNA demethylation increases the yield and biomass of rice and potato plants in field trials

RNA N⁶-methyladenosine (m⁶A) modifications are essential in plants. Here, we show that transgenic expression of the human RNA demethylase FTO in rice caused a more than threefold increase in grain yield under greenhouse conditions. In field trials, transgenic expression of FTO in rice and potato caused ~50% increases in yield and biomass. We demonstrate that the presence of FTO stimulates root meristem cell proliferation and tiller bud formation and promotes photosynthetic efficiency and drought tolerance but has no effect on mature cell size, shoot meristem cell proliferation, root diameter, plant height or ploidy. FTO mediates substantial m⁶A demethylation (around 7% of demethylation in poly(A) RNA and around 35% decrease of m⁶A in non-ribosomal nuclear RNA) in plant RNA, inducing chromatin openness and transcriptional activation. Therefore, modulation of plant RNA m⁶A methylation is a promising strategy to dramatically improve plant growth and crop yield.

Using k-mer embeddings learned from a Skip-gram based neural network for building a cross-species DNA N6-methyladenine site prediction model

This study used k-mer embeddings as effective feature to identify DNA N6-Methyladenine sites in plant genomes and obtained improved performance without substantial effort in feature extraction, combination and selection. Identification of DNA N6-methyladenine sites has been a very active topic of computational biology due to the unavailability of suitable methods to identify them accurately, especially in plants. Substantial results were obtained with a great effort put in extracting, heuristic searching, or fusing a diverse types of features, not to mention a feature selection step. In this study, we regarded DNA sequences as textual information and employed natural language processing techniques to decipher hidden biological meanings from those sequences. In other words, we considered DNA, the human life book, as a book corpus for training DNA language models. K-mer embeddings then were generated from these language models to be used in machine learning prediction models. Skip-gram neural networks were the base of the language models and ensemble tree-based algorithms were the machine learning algorithms for prediction models. We trained the prediction model on Rosaceae genome dataset and performed a comprehensive test on 3 plant genome datasets. Our proposed method shows promising performance with AUC performance approaching an ideal value on Rosaceae dataset (0.99), a high score on Rice dataset (0.95) and improved performance on Rice dataset while enjoying an elegant, yet efficient feature extraction process.

Epigenome and Epitranscriptome: Potential Resources for Crop Improvement

Crop breeding faces the challenge of increasing food demand, especially under climatic changes. Conventional breeding has relied on genetic diversity by combining alleles to obtain desired traits. In recent years, research on epigenetics and epitranscriptomics has shown that epigenetic and epitranscriptomic diversity provides additional sources for crop breeding and harnessing epigenetic and epitranscriptomic regulation through biotechnologies has great potential for crop improvement. Here, we review epigenome and epitranscriptome variations during plant development and in response to environmental stress as well as the available sources for epiallele formation. We also discuss the possible strategies for applying epialleles and epitranscriptome engineering in crop breeding.

Epigenetic regulation of salinity stress responses in cereals

Cereals are important crops and are exposed to various types of environmental stresses that affect the overall growth and yield. Among the various abiotic stresses, salt stress is a major environmental factor that influences the genetic, physiological, and biochemical responses of cereal crops. Epigenetic regulation which includes DNA methylation, histone modification, and chromatin remodelling plays an important role in salt stress tolerance. Recent studies in rice genomics have highlighted that the epigenetic changes are heritable and therefore can be considered as molecular signatures. An epigenetic mechanism under salinity induces phenotypic responses involving modulations in gene expression. Association between histone modification and altered DNA methylation patterns and differential gene expression has been evidenced for salt sensitivity in rice and other cereal crops. In addition, epigenetics also creates stress memory that helps the plant to better combat future stress exposure. In the present review, we have discussed epigenetic influences in stress tolerance, adaptation, and evolution processes. Understanding the epigenetic regulation of salinity could help for designing salt-tolerant varieties leading to improved crop productivity.

R-loop and its functions at the regulatory interfaces between transcription and (epi)genome

R-loop represents a prevalent and specialized chromatin structure critically involved in a wide range of biological processes. In particular, co-transcriptional R-loops, produced often due to RNA polymerase pausing or RNA biogenesis malfunction, can initiate molecular events to context-dependently regulate local gene transcription and crosstalk with chromatin modifications. Cellular "readers" of R-loops are identified, exerting crucial impacts on R-loop homeostasis and gene regulation. Mounting evidence also supports R-loop deregulation as a frequent, sometimes initiating, event during the development of human pathologies, notably cancer and neurological disorder. The purpose of this review is to cover recent advances in understanding the fundamentals of R-loop biology, which have started to unveil complex interplays of R-loops with factors involved in various biological processes such as transcription, RNA processing and epitranscriptomic modification (such as N6-methyladenosine), DNA damage sensing and repair, and epigenetic regulation.

Characterization of transcription factor MYB59 and expression profiling in response to low K+ and NO3- in indica rice (Oryza sativa L.)

Background

Nitrogen and potassium are crucial supplements for plant development and growth. Plants can detect potassium and nitrate ions in soils and in like way, they modify root-to-shoot transport of these ions to adjust the conveyance among roots and shoots. Transcription factor MYB59 plays essential roles in numerous physiological processes inclusive of hormone response, abiotic stress tolerance, plant development, and metabolic regulation. In this study, we retrieved 56 MYB59 proteins from different plant species. Multiple sequence alignment, phylogenetic tree, conserved motif, chromosomal localization, and cis-regulatory elements of the retrieved sequences were analyzed. Gene structure, protein 3D structure, and DNA binding of OsMYB59 indica were also predicted. Finally, we characterized OsMYB59 and its function under low K⁺/NO₃⁻ conditions in Oryza sativa subsp. indica.

Results

Data analysis showed that MYB59s from various groups separated in terms of conserved functional domains and gene structure, where members of genus Oryza clustered together. Plants showed reduced height and yellowish appearance when grown on K⁺ and NO₃⁻ deficient medium. Quantitative real-time PCR uncovered that the OsMYB59 reacted to abiotic stresses where its expression was increased in BRRI dhan56 but decreased in other varieties on K⁺ deficient medium. In addition, OsMYB59 transcript level increased on NO₃⁻ deficient medium.

Conclusions

Our results can help to explain the biological functions of indica rice MYB59 protein and gave a theoretical premise to additionally describe its biological roles in response to abiotic stresses particularly drought.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-021-00248-6.

A deep learning approach to automate whole-genome prediction of diverse epigenomic modifications in plants

Epigenetic modifications function in gene transcription, RNA metabolism, and other biological processes. However, multiple factors currently limit the scientific utility of epigenomic datasets generated for plants. Here, using deep-learning approaches, we developed a Smart Model for Epigenetics in Plants (SMEP) to predict six types of epigenomic modifications: DNA 5-methylcytosine (5mC) and N6-methyladenosine (6mA) methylation, RNA N6-methyladenosine (m⁶ A) methylation, and three types of histone modification. Using the datasets from the japonica rice Nipponbare, SMEP achieved 95% prediction accuracy for 6mA, and also achieved around 80% for 5mC, m⁶ A, and the three types of histone modification based on the 10-fold cross-validation. Additionally, > 95% of the 6mA peaks detected after a heat-shock treatment were predicted. We also successfully applied the SMEP for examining epigenomic modifications in indica rice 93-11 and even the B73 maize line. Taken together, we show that the deep-learning-enabled SMEP can reliably mine epigenomic datasets from diverse plants to yield actionable insights about epigenomic sites. Thus, our work opens new avenues for the application of predictive tools to facilitate functional research, and will almost certainly increase the efficiency of genome engineering efforts.

Eragrostis curvula, a Model Species for Diplosporous Apomixis

Eragrostis curvula (Schrad.) Ness is a grass with a particular apomictic embryo sac development called Eragrostis type. Apomixis is a type of asexual reproduction that produces seeds without fertilization in which the resulting progeny is genetically identical to the mother plant and with the potential to fix the hybrid vigour from more than one generation, among other advantages. The absence of meiosis and the occurrence of only two rounds of mitosis instead of three during embryo sac development make this model unique and suitable to be transferred to economically important crops. Throughout this review, we highlight the advances in the knowledge of apomixis in E. curvula using different techniques such as cytoembryology, DNA methylation analyses, small-RNA-seq, RNA-seq, genome assembly, and genotyping by sequencing. The main bulk of evidence points out that apomixis is inherited as a single Mendelian factor, and it is regulated by genetic and epigenetic mechanisms controlled by a complex network. With all this information, we propose a model of the mechanisms involved in diplosporous apomixis in this grass. All the genetic and epigenetic resources generated in E. curvula to study the reproductive mode changed its status from an orphan to a well-characterised species.

The exploration of N6-deoxyadenosine methylation in mammalian genomes

N⁶-methyladenine (N⁶-mA, m⁶dA, or 6mA), a prevalent DNA modification in prokaryotes, has recently been identified in higher eukaryotes, including mammals. Although 6mA has been well-studied in prokaryotes, the function and regulatory mechanism of 6mA in eukaryotes are still poorly understood. Recent studies indicate that 6mA can serve as an epigenetic mark and play critical roles in various biological processes, from transposable-element suppression to environmental stress response. Here, we review the significant advances in methodology for 6mA detection and major progress in understanding the regulation and function of this non-canonical DNA methylation in eukaryotes, predominantly mammals.

Quantification and mapping of DNA modifications

Apart from the four canonical nucleobases, DNA molecules carry a number of natural modifications. Substantial evidence shows that DNA modifications can regulate diverse biological processes. Dynamic and reversible modifications of DNA are critical for cell differentiation and development. Dysregulation of DNA modifications is closely related to many human diseases. The research of DNA modifications is a rapidly expanding area and has been significantly stimulated by the innovations of analytical methods. With the recent advances in methods and techniques, a series of new DNA modifications have been discovered in the genomes of prokaryotes and eukaryotes. Deciphering the biological roles of DNA modifications depends on the sensitive detection, accurate quantification, and genome-wide mapping of modifications in genomic DNA. This review provides an overview of the recent advances in analytical methods and techniques for both the quantification and genome-wide mapping of natural DNA modifications. We discuss the principles, advantages, and limitations of these developed methods. It is anticipated that new methods and techniques will resolve the current challenges in this burgeoning research field and expedite the elucidation of the functions of DNA modifications.

Epigenetic insight into regulatory role of chromatin covalent modifications in lifecycle and virulence of Phytophthora

The Oomycota phylum includes fungi-like filamentous microorganisms classified as plant pathogens. The most destructive genus within oomycetes is Phytophthora, which causes diseases in plants of economic importance in agriculture, forestry and ornamental. Phytophthora species are widespread worldwide and some of them enable adaptation to different hosts and environmental changes. The development of sexual and asexual reproductive structures and the secretion of proteins to control plant immunity are critical for the adaptative lifestyle. However, molecular mechanisms underlying the adaptation of Phytophthora to different hosts and environmental changes are poorly understood. In the last decade, the role of epigenetics has gained attention, and important evidence has demonstrated the potential role of chromatin covalent modifications, such as DNA methylation and histone acetylation/methylation, in the regulation of gene expression during Phytophthora development and plant infection. Here, we review for the first time the evidence of the potential role of chromatin covalent modifications in the lifecycle of the phytopathogenic genus Phytophthora, including virulence, and host and environment adaptation processes.

iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization

Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate understanding of the sequence(-structure)-function paradigm for DNAs, RNAs and proteins. Rapid accumulation of sequences requires equally pervasive development of new predictive models, which depends on the availability of effective tools that support these efforts. We introduce iLearnPlus, the first machine-learning platform with graphical- and web-based interfaces for the construction of machine-learning pipelines for analysis and predictions using nucleic acid and protein sequences. iLearnPlus provides a comprehensive set of algorithms and automates sequence-based feature extraction and analysis, construction and deployment of models, assessment of predictive performance, statistical analysis, and data visualization; all without programming. iLearnPlus includes a wide range of feature sets which encode information from the input sequences and over twenty machine-learning algorithms that cover several deep-learning approaches, outnumbering the current solutions by a wide margin. Our solution caters to experienced bioinformaticians, given the broad range of options, and biologists with no programming background, given the point-and-click interface and easy-to-follow design process. We showcase iLearnPlus with two case studies concerning prediction of long noncoding RNAs (lncRNAs) from RNA transcripts and prediction of crotonylation sites in protein chains. iLearnPlus is an open-source platform available at https://github.com/Superzchen/iLearnPlus/ with the webserver at http://ilearnplus.erc.monash.edu/.

The dynamics of N6-methyladenine RNA modification in interactions between rice and plant viruses

BACKGROUND

N6-methyladenosine (m6A) is the most common RNA modification in eukaryotes and has been implicated as a novel epigenetic marker that is involved in various biological processes. The pattern and functional dissection of m6A in the regulation of several major human viral diseases have already been reported. However, the patterns and functions of m6A distribution in plant disease bursting remain largely unknown.

RESULTS

We analyse the high-quality m6A methylomes in rice plants infected with two devastating viruses. We find that the m6A methylation is mainly associated with genes that are not actively expressed in virus-infected rice plants. We also detect different m6A peak distributions on the same gene, which may contribute to different antiviral modes between rice stripe virus or rice black-stripe dwarf virus infection. Interestingly, we observe increased levels of m6A methylation in rice plant response to virus infection. Several antiviral pathway-related genes, such as RNA silencing-, resistance-, and fundamental antiviral phytohormone metabolic-related genes, are also m6A methylated. The level of m6A methylation is tightly associated with its relative expression levels.

CONCLUSIONS

We revealed the dynamics of m6A modification during the interaction between rice and viruses, which may act as a main regulatory strategy in gene expression. Our investigations highlight the significance of m6A modifications in interactions between plant and viruses, especially in regulating the expression of genes involved in key pathways.

Interplay of DNA and RNA N 6 -methyladenine with R-loops in regulating gene transcription in Arabidopsis

R-loops and covalent modifications of N ⁶ -methyladenine on DNA (D-6 mA) or RNA (R-m⁶A) have been documented to function in various cellular processes in eukaryotes. However, the relationships between R-loops and both covalent modifications are still elusive in plants. Here, we integrated existing ssDRIP-seq with D-6 mA and R-m⁶A data from Arabidopsis thaliana. We found that the presence of either of both modifications facilitates R-loop formation and transcription of overlapping genes. Interestingly, our study suggests that the presence of R-m⁶A is key to affect R-loop intensity and positively regulate gene transcription. Moreover, the presence of D-6 mA plays an additive role to facilitate the effect of R-m⁶A on R-loop intensity, however, D-6 mA may negatively regulate gene transcription when coexisted with R-m⁶A. Our analyses indicate that D-6 mA, R-m⁶A, or histone marks may act individually and cooperatively with R-loops in regulating gene transcription. Our study is the first to link R-loops with D-6 mA and R-m⁶A in plants, thereby providing new insights into interactions between R-loops with D-6 mA, R-m⁶A, and histone marks for regulating gene transcription.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01010-5.

N6-Methyladenine in Eukaryotic DNA: Tissue Distribution, Early Embryo Development, and Neuronal Toxicity

DNA methylation is one of the most important epigenetic modifications and is closely related with several biological processes such as regulation of gene transcription and the development of non-malignant diseases. The prevailing dogma states that DNA methylation in eukaryotes occurs essentially through 5-methylcytosine (5mC) but recently adenine methylation was also found to be present in eukaryotes. In mouse embryonic stem cells, 6-methyladenine (6mA) was associated with the repression and silencing of genes, particularly in the X-chromosome, known to play an important role in cell fate determination. Here, we have demonstrated that 6mA is a ubiquitous eukaryotic epigenetic modification that is put in place during epigenetically sensitive periods such as embryogenesis and fetal development. In somatic cells there are clear tissue specificity in 6mA levels, with the highest 6mA levels being observed in the brain. In zebrafish, during the first 120 h of embryo development, from a single pluripotent cell to an almost fully formed individual, 6mA levels steadily increase. An identical pattern was observed over embryonic days 7–21 in the mouse. Furthermore, exposure to a neurotoxic environmental pollutant during the same early life period may led to a decrease in the levels of this modification in female rats. The identification of the periods during which 6mA epigenetic marks are put in place increases our understanding of this mammalian epigenetic modification, and raises the possibility that it may be associated with developmental processes.

A convolution based computational approach towards DNA N6-methyladenine site identification and motif extraction in rice genome

DNA N6-methylation (6mA) in Adenine nucleotide is a post replication modification responsible for many biological functions. Automated and accurate computational methods can help to identify 6mA sites in long genomes saving significant time and money. Our study develops a convolutional neural network (CNN) based tool i6mA-CNN capable of identifying 6mA sites in the rice genome. Our model coordinates among multiple types of features such as PseAAC (Pseudo Amino Acid Composition) inspired customized feature vector, multiple one hot representations and dinucleotide physicochemical properties. It achieves auROC (area under Receiver Operating Characteristic curve) score of 0.98 with an overall accuracy of 93.97% using fivefold cross validation on benchmark dataset. Finally, we evaluate our model on three other plant genome 6mA site identification test datasets. Results suggest that our proposed tool is able to generalize its ability of 6mA site identification on plant genomes irrespective of plant species. An algorithm for potential motif extraction and a feature importance analysis procedure are two by products of this research. Web tool for this research can be found at: https://cutt.ly/dgp3QTR.

Differential Methylation Patterns in Apomictic vs. Sexual Genotypes of the Diplosporous Grass Eragrostis curvula

DNA methylation is an epigenetic mechanism by which a methyl group is added to a cytosine or an adenine. When located in a gene/regulatory sequence it may repress or de-repress genes, depending on the context and species. Eragrostis curvula is an apomictic grass in which facultative genotypes increases the frequency of sexual pistils triggered by epigenetic mechanisms. The aim of the present study was to look for correlations between the reproductive mode and specific methylated genes or genomic regions. To do so, plants with contrasting reproductive modes were investigated through MCSeEd (Methylation Context Sensitive Enzyme ddRad) showing higher levels of DNA methylation in apomictic genotypes. Moreover, an increased proportion of differentially methylated positions over the regulatory regions were observed, suggesting its possible role in regulation of gene expression. Interestingly, the methylation pathway was also found to be self-regulated since two of the main genes (ROS1 and ROS4), involved in de-methylation, were found differentially methylated between genotypes with different reproductive behavior. Moreover, this work allowed us to detect several genes regulated by methylation that were previously found as differentially expressed in the comparisons between apomictic and sexual genotypes, linking DNA methylation to differences in reproductive mode.

Harnessing Current Knowledge of DNA N6-Methyladenosine From Model Plants for Non-model Crops

Epigenetic modifications alter the gene activity and function by causing change in the chromosomal architecture through DNA methylation/demethylation, or histone modifications without causing any change in DNA sequence. In plants, DNA cytosine methylation (5mC) is vital for various pathways such as, gene regulation, transposon suppression, DNA repair, replication, transcription, and recombination. Thanks to recent advances in high throughput sequencing (HTS) technologies for epigenomic “Big Data” generation, accumulated studies have revealed the occurrence of another novel DNA methylation mark, N6-methyladenosine (6mA), which is highly present on gene bodies mainly activates gene expression in model plants such as eudicot Arabidopsis (Arabidopsis thaliana) and monocot rice (Oryza sativa). However, in non-model crops, the occurrence and importance of 6mA remains largely less known, with only limited reports in few species, such as Rosaceae (wild strawberry), and soybean (Glycine max). Given the aforementioned vital roles of 6mA in plants, hereinafter, we summarize the latest advances of DNA 6mA modification, and investigate the historical, known and vital functions of 6mA in plants. We also consider advanced artificial-intelligence biotechnologies that improve extraction and prediction of 6mA concepts. In this Review, we discuss the potential challenges that may hinder exploitation of 6mA, and give future goals of 6mA from model plants to non-model crops.

Biodiversity-based development and evolution: the emerging research systems in model and non-model organisms

Evolutionary developmental biology, or Evo-Devo for short, has become an established field that, broadly speaking, seeks to understand how changes in development drive major transitions and innovation in organismal evolution. It does so via integrating the principles and methods of many subdisciplines of biology. Although we have gained unprecedented knowledge from the studies on model organisms in the past decades, many fundamental and crucially essential processes remain a mystery. Considering the tremendous biodiversity of our planet, the current model organisms seem insufficient for us to understand the evolutionary and physiological processes of life and its adaptation to exterior environments. The currently increasing genomic data and the recently available gene-editing tools make it possible to extend our studies to non-model organisms. In this review, we review the recent work on the regulatory signaling of developmental and regeneration processes, environmental adaptation, and evolutionary mechanisms using both the existing model animals such as zebrafish and Drosophila, and the emerging nonstandard model organisms including amphioxus, ascidian, ciliates, single-celled phytoplankton, and marine nematode. In addition, the challenging questions and new directions in these systems are outlined as well.

A Mutation-Based Method for Pinpointing a DNA N6 -Methyladenine Methyltransferase Modification Site at Single Base Resolution

DNA N⁶ -methyladenine (6mA) has recently received notable attention due to an increased finding of its functional roles in higher eukaryotes. Here we report an enzyme-assisted chemical labeling method to pinpoint the DNA 6mA methyltransferase (MTase) substrate modification site at single base resolution. A designed allyl-substituted MTase cofactor was applied in the catalytic transfer reaction, and the allyl group was installed to the N⁶ -position of adenine within a specific DNA sequence to form N⁶ -allyladenine (6aA). The iodination of 6aA allyl group induced the formation of 1, N⁶ -cyclized adenine which caused mutations during DNA replication by a polymerase. Thus the modification site could be precisely detected by a mutation signal. We synthesized 6aA deoxynucleoside and deoxynucleotide model compounds and a 6aA-containing DNA probe, and screened nine DNA polymerases to define an optimal system capable of detecting the substrate modification site of a DNA 6mA MTase at single-base resolution.

i6mA-VC: A Multi-Classifier Voting Method for the Computational Identification of DNA N6-methyladenine Sites

DNA N6-methyladenine (6 mA), as an essential component of epigenetic modification, cannot be neglected in genetic regulation mechanism. The efficient and accurate prediction of 6 mA sites is beneficial to the development of biological genetics. Biochemical experimental methods are considered to be time-consuming and laborious. Most of the established machine learning methods have a single dataset. Although some of them have achieved cross-species prediction, their results are not satisfactory. Therefore, we designed a novel statistical model called i6mA-VC to improve the accuracy for 6 mA sites. On the one hand, kmer and binary encoding are applied to extract features, and then gradient boosting decision tree (GBDT) embedded method is applied as the feature selection strategy. On the other hand, DNA sequences are represented by vectors through the feature extraction method of ring-function-hydrogen-chemical properties (RFHCP) and the feature selection strategy of ExtraTree. After fusing the two optimal features, a voting classifier based on gradient boosting decision tree (GBDT), light gradient boosting machine (LightGBM) and multilayer perceptron classifier (MLPC) is constructed for final classification and prediction. The accuracy of Rice dataset and M.musculus dataset with five-fold cross-validation are 0.888 and 0.967, respectively. The cross-species dataset is selected as independent testing dataset, and the accuracy reaches 0.848. Through rigorous experiments, it is demonstrated that the proposed predictor is convincing and applicable. The development of i6mA-VC predictor will become an effective way for the recognition of N6-methyladenine sites, and it will also be beneficial for biological geneticists to further study gene expression and DNA modification. In addition, an accessible web-server for i6mA-VC is available from http://www.zhanglab.site/ .

DNA Modification Patterns within the Transposable Elements of the Fig (Ficus carica L.) Genome

Transposable element activity can be harmful to the host’s genome integrity, but it can also provide selective advantages. One strategy to cope with transposons is epigenetic control through DNA base modifications. We report the non-canonic DNA modification dynamics of fig (Ficus carica L.) by exploiting high-quality genome reference and related N4-methylcytosine (4mC) and N6-methyladenine (6mA) data. Overall, 1.49% of transposon nucleotides showed either 4mC or 6mA modifications: the 4mC/6mA ratio was similar in Class I and Class II transposons, with a prevalence of 4mC, which is comparable to coding genes. Different percentages of 4mC or 6mA were observed among LTR-retrotransposon lineages and sub-lineages. Furthermore, both the Copia and Gypsy retroelements showed higher modification rates in the LTR and coding regions compared with their neighbour regions. Finally, the unconventional methylation of retrotransposons is unrelated to the number of close genes, suggesting that the 4mC and 6mA frequency in LTR-retrotransposons should not be related to transcriptional repression in the adjacency of the element. In conclusion, this study highlighted unconventional DNA modification patterns in fig transposable elements. Further investigations will focus on functional implications, in regards to how modified retroelements affect the expression of neighbouring genes, and whether these epigenetic markers can spread from repeats to genes, shaping the plant phenotype.

Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species

N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA’s biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.

DNA N6 methyladenine (6mA) is a newly recognized methylation modification in eukaryotes. It exists widely and conservatively in organisms, and its modification level changes dynamically in the whole life cycle. This study proposes an algorithm based on a deep learning framework including LSTM and CNN to predict 6mA sites. The results showed that our method could accurately predict the 6mA sites in different species, which means DNA sub-sequences containing 6mA sites among species have certain conservation. Importantly, we found that 6mA methylation in most different species is more likely to occur on the GAGG motif. In addition, we also found that 6mA is rich in the promoter’s TATA box, which may be a mechanism of regulating downstream gene expression.

Accessible chromatin regions and their functional interrelations with gene transcription and epigenetic modifications in sorghum genome

Accessible chromatin regions (ACRs) provide physical scaffolds to recruit transcriptional co-regulators and displace their nearby nucleosomes in multiple plant species. Characterization of ACRs and investigation of their biological effects in Sorghum bicolor has lagged behind. Regulation of gene expression relies on the transcriptional co-regulators that are recruited to ACRs to affect epigenomic modifications of surrounding nucleosomes. In this study, we employed transposase-accessible chromatin sequencing to identify ACRs and decipher how the presence of ACRs affects gene expression and epigenetic signatures in the Sorghum genome. As a result, 21 077 ACRs, which are mapped to 22.9% of genes and 2.7% of repeats, were identified. The profiling of ACRs on gene structures reveals a narrow and sharp peak around the transcription start site, with relatively weak and broad signals covering the entire gene body and an explicit but wide peak from the transcription termination site to its downstream regions. We discovered that the correlations between gene expression levels and profiled ACR densities are dependent on the positions of ACRs. The occurrence of genic ACRs cumulatively enhances the transcriptional activity of intergenic ACR-associated genes. In addition, an intricate crosstalk among ACRs, gene expression, and epigenetic marks has been unveiled by integrating multiple-omics analyses of whole-genome bisulfite sequencing, 6mA immunoprecipitation followed by sequencing, RNA sequencing, chromatin immunoprecipitation sequencing, and DNase I hypersensitive sites sequencing datasets. Our study provides a genome-wide landscape of ACRs in sorghum, decrypts their interrelations with various epigenetic marks, and sheds new light on their roles in transcriptional regulation.

Dynamics of DNA Methylation and Its Functions in Plant Growth and Development

Epigenetic modifications in DNA bases and histone proteins play important roles in the regulation of gene expression and genome stability. Chemical modification of DNA base (e.g., addition of a methyl group at the fifth carbon of cytosine residue) switches on/off the gene expression during developmental process and environmental stresses. The dynamics of DNA base methylation depends mainly on the activities of the writer/eraser guided by non-coding RNA (ncRNA) and regulated by the developmental/environmental cues. De novo DNA methylation and active demethylation activities control the methylation level and regulate the gene expression. Identification of ncRNA involved in de novo DNA methylation, increased DNA methylation proteins guiding DNA demethylase, and methylation monitoring sequence that helps maintaining a balance between DNA methylation and demethylation is the recent developments that may resolve some of the enigmas. Such discoveries provide a better understanding of the dynamics/functions of DNA base methylation and epigenetic regulation of growth, development, and stress tolerance in crop plants. Identification of epigenetic pathways in animals, their existence/orthologs in plants, and functional validation might improve future strategies for epigenome editing toward climate-resilient, sustainable agriculture in this era of global climate change. The present review discusses the dynamics of DNA methylation (cytosine/adenine) in plants, its functions in regulating gene expression under abiotic/biotic stresses, developmental processes, and genome stability.

Small DNA Methylation, Big Player in Plant Abiotic Stress Responses and Memory

DNA methylation is a conserved epigenetic mark that plays important roles in maintaining genome stability and regulating gene expression. As sessile organisms, plants have evolved sophisticated regulatory systems to endure or respond to diverse adverse abiotic environmental challenges, i.e., abiotic stresses, such as extreme temperatures (cold and heat), drought and salinity. Plant stress responses are often accompanied by changes in chromatin modifications at diverse responsive loci, such as 5-methylcytosine (5mC) and N 6-methyladenine (6mA) DNA methylation. Some abiotic stress responses are memorized for several hours or days through mitotic cell divisions and quickly reset to baseline levels after normal conditions are restored, which is referred to as somatic memory. In some cases, stress-induced chromatin marks are meiotically heritable and can impart the memory of stress exposure from parent plants to at least the next stress-free offspring generation through the mechanisms of transgenerational epigenetic inheritance, which may offer the descendants the potential to be adaptive for better fitness. In this review, we briefly summarize recent achievements regarding the establishment, maintenance and reset of DNA methylation, and highlight the diverse roles of DNA methylation in plant responses to abiotic stresses. Further, we discuss the potential role of DNA methylation in abiotic stress-induced somatic memory and transgenerational inheritance. Future research directions are proposed to develop stress-tolerant engineered crops to reduce the negative effects of abiotic stresses.

DNA adenine methylation in eukaryotes: Enzymatic mark or a form of DNA damage?

6-methyladenine (6mA) is fairly abundant in nuclear DNA of basal fungi, ciliates and green algae. In these organisms, 6mA is maintained near transcription start sites in ApT context by a parental-strand instruction dependent maintenance methyltransferase and is positively associated with transcription. In animals and plants, 6mA levels are high only in organellar DNA. The 6mA levels in nuclear DNA are very low. They are attributable to nucleotide salvage and the activity of otherwise mitochondrial METTL4, and may be considered as a price that cells pay for adenine methylation in RNA and/or organellar DNA. Cells minimize this price by sanitizing dNTP pools to limit 6mA incorporation, and by converting 6mA that has been incorporated into DNA back to adenine. Hence, 6mA in nuclear DNA should be described as an epigenetic mark only in basal fungi, ciliates and green algae, but not in animals and plants.

6mA-Finder: a novel online tool for predicting DNA N6-methyladenine sites in genomes

MOTIVATION

DNA N6-methyladenine (6 mA) has recently been found as an essential epigenetic modification, playing its roles in a variety of cellular processes. The abnormal status of DNA 6 mA modification has been reported in cancer and other disease. The annotation of 6 mA marks in genome is the first crucial step to explore the underlying molecular mechanisms including its regulatory roles.

RESULTS

We present a novel online DNA 6 mA site tool, 6 mA-Finder, by incorporating seven sequence-derived information and three physicochemical-based features through recursive feature elimination strategy. Our multiple cross-validations indicate the promising accuracy and robustness of our model. 6 mA-Finder outperforms its peer tools in general and species-specific 6 mA site prediction, suggesting it can provide a useful resource for further experimental investigation of DNA 6 mA modification.

AVAILABILITY AND IMPLEMENTATION

https://bioinfo.uth.edu/6mA_Finder.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Decoding the plant genome: From epigenome to 3D organization

The linear genome of eukaryotes is partitioned into diverse chromatin states and packaged into a three-dimensional (3D) structure, which has functional implications in DNA replication, DNA repair, and transcriptional regulation. Over the past decades, research on plant functional genomics and epigenomics has made great progress, with thousands of genes cloned and molecular mechanisms of diverse biological processes elucidated. Recently, 3D genome research has gradually attracted great attention of many plant researchers. Herein, we briefly review the progress in genomic and epigenomic research in plants, with a focus on Arabidopsis and rice, and summarize the currently used technologies and advances in plant 3D genome organization studies. We also discuss the relationships between one-dimensional linear genome sequences, epigenomic states, and the 3D chromatin architecture. This review provides basis for future research on plant 3D genomics.

i6mA-stack: A stacking ensemble-based computational prediction of DNA N6-methyladenine (6mA) sites in the Rosaceae genome

DNA N6-methyladenine (6 mA) is an epigenetic modification that plays a vital role in a variety of cellular processes in both eukaryotes and prokaryotes. Accurate information of 6 mA sites in the Rosaceae genome may assist in understanding genomic 6 mA distributions and various biological functions such as epigenetic inheritance. Various studies have shown the possibility of identifying 6 mA sites through experiments, but the procedures are time-consuming and costly. To overcome the drawbacks of experimental methods, we propose an accurate computational paradigm based on a machine learning (ML) technique to identify 6 mA sites in Rosa chinensis (R.chinensis) and Fragaria vesca (F.vesca). To improve the performance of the proposed model and to avoid overfitting, a recursive feature elimination with cross-validation (RFECV) strategy is used to extract the optimal number of features (ONF) subset from five different DNA sequence encoding schemes, i.e., Binary Encoding (BE), Ring-Function-Hydrogen-Chemical Properties (RFHC), Electron-Ion-Interaction Pseudo Potentials of Nucleotides (EIIP), Dinucleotide Physicochemical Properties (DPCP), and Trinucleotide Physicochemical Properties (TPCP). Subsequently, we use the ONF subset to train a double layers of ML-based stacking model to create a bioinformatics tool named 'i6mA-stack'. This tool outperforms its peer tool in general and is currently available at http://nsclbio.jbnu.ac.kr/tools/i6mA-stack/.

MM-6mAPred: identifying DNA N6-methyladenine sites based on Markov model

MOTIVATION

Recent studies have shown that DNA N6-methyladenine (6mA) plays an important role in epigenetic modification of eukaryotic organisms. It has been found that 6mA is closely related to embryonic development, stress response and so on. Developing a new algorithm to quickly and accurately identify 6mA sites in genomes is important for explore their biological functions.

RESULTS

In this paper, we proposed a new classification method called MM-6mAPred based on a Markov model which makes use of the transition probability between adjacent nucleotides to identify 6mA site. The sensitivity and specificity of our method are 89.32% and 90.11%, respectively. The overall accuracy of our method is 89.72%, which is 6.59% higher than that of the previous method i6mA-Pred. It indicated that, compared with the 41 nucleotide chemical properties used by i6mA-Pred, the transition probability between adjacent nucleotides can capture more discriminant sequence information.

AVAILABILITY AND IMPLEMENTATION

The web server of MM-6mAPred is freely accessible at http://www.insect-genome.com/MM-6mAPred/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DNA6mA-MINT: DNA-6mA Modification Identification Neural Tool

DNA N6-methyladenine (6mA) is part of numerous biological processes including DNA repair, DNA replication, and DNA transcription. The 6mA modification sites hold a great impact when their biological function is under consideration. Research in biochemical experiments for this purpose is carried out and they have demonstrated good results. However, they proved not to be a practical solution when accessed under cost and time parameters. This led researchers to develop computational models to fulfill the requirement of modification identification. In consensus, we have developed a computational model recommended by Chou's 5-steps rule. The Neural Network (NN) model uses convolution layers to extract the high-level features from the encoded binary sequence. These extracted features were given an optimal interpretation by using a Long Short-Term Memory (LSTM) layer. The proposed architecture showed higher performance compared to state-of-the-art techniques. The proposed model is evaluated on Mus musculus, Rice, and "Combined-species" genomes with 5- and 10-fold cross-validation. Further, with access to a user-friendly web server, publicly available can be accessed freely.

DNA N6-Methyladenine Modification in Wild and Cultivated Soybeans Reveals Different Patterns in Nucleus and Cytoplasm

DNA 6mA modification, an important newly discovered epigenetic mark, plays a crucial role in organisms and has been attracting more and more attention in recent years. The soybean is economically the most important bean in the world, providing vegetable protein for millions of people. However, the distribution pattern and function of 6mA in soybean are still unknown. In this study, we decoded 6mA modification to single-nucleotide resolution in wild and cultivated soybeans, and compared the 6mA differences between cytoplasmic and nuclear genomes and between wild and cultivated soybeans. The motif of 6mA in the nuclear genome was conserved across the two kinds of soybeans, and ANHGA was the most dominant motif in wild and cultivated soybeans. Genes with 6mA modification in the nucleus had higher expression than those without modification. Interestingly, 6mA distribution patterns in cytoplasm for each soybean were significantly different from those in nucleus, which was reported for the first time in soybean. Our research provides a new insight in the deep analysis of cytoplasmic genomic DNA modification in plants.

A distinct class of eukaryotic MT-A70 methyltransferases maintain symmetric DNA N6-adenine methylation at the ApT dinucleotides as an epigenetic mark associated with transcription

Rediscovered as a potential eukaryotic epigenetic mark, DNA N⁶-adenine methylation (6mA) varies across species in abundance and its relationships with transcription. Here we characterize AMT1—representing a distinct MT-A70 family methyltransferase—in the ciliate Tetrahymena thermophila. AMT1 loss-of-function leads to severe defects in growth and development. Single Molecule, Real-Time (SMRT) sequencing reveals that AMT1 is required for the bulk of 6mA and all symmetric methylation at the ApT dinucleotides. The detection of hemi-methylated ApT sites suggests a semi-conservative mechanism for maintaining symmetric methylation. AMT1 affects expression of many genes; in particular, RAB46, encoding a Rab family GTPase involved in contractile vacuole function, is likely a direct target. The distribution of 6mA resembles H3K4 methylation and H2A.Z, two conserved epigenetic marks associated with RNA polymerase II transcription. Furthermore, strong 6mA and nucleosome positioning in wild-type cells is attenuated in ΔAMT1 cells. Our results support that AMT1-catalyzed 6mA is an integral part of the transcription-associated epigenetic landscape. AMT1 homologues are generally found in protists and basal fungi featuring ApT hyper-methylation associated with transcription, which are missing in animals, plants, and true fungi. This dichotomy of 6mA functions and the underlying molecular mechanisms may have implications in eukaryotic diversification.

Adenine DNA methylation, 3D genome organization, and gene expression in the parasite Trichomonas vaginalis

Trichomonas vaginalis is a common sexually transmitted parasite that colonizes the human urogenital tract causing infections that range from asymptomatic to highly inflammatory. Recent works have highlighted the importance of histone modifications in the regulation of transcription and parasite pathogenesis. However, the nature of DNA methylation in the parasite remains unexplored. Using a combination of immunological techniques and ultrahigh-performance liquid chromatography (UHPLC), we analyzed the abundance of DNA methylation in strains with differential pathogenicity demonstrating that N6-methyladenine (6mA), and not 5-methylcytosine (5mC), is the main DNA methylation mark in T. vaginalis Genome-wide distribution of 6mA reveals that this mark is enriched at intergenic regions, with a preference for certain superfamilies of DNA transposable elements. We show that 6mA in T. vaginalis is associated with silencing when present on genes. Interestingly, bioinformatics analysis revealed the presence of transcriptionally active or repressive intervals flanked by 6mA-enriched regions, and results from chromatin conformation capture (3C) experiments suggest these 6mA flanked regions are in close spatial proximity. These associations were disrupted when parasites were treated with the demethylation activator ascorbic acid. This finding revealed a role for 6mA in modulating three-dimensional (3D) chromatin structure and gene expression in this divergent member of the Excavata.

Regulation of Adipocyte Differentiation by METTL4, a 6 mA Methylase

As one of the most abundant DNA methylation form in prokaryotes, N⁶-methyladenine nucleotide (6 mA) was however only recently identified in eukaryotic genomes. To explore the implications of N⁶-adenine methylation in adipogenesis, genomic N⁶-adenine methylation was examined across adipocyte differentiation stages of 3T3-L1 cells. When the N⁶-adenine methylation profiles were analyzed and compared with the levels of gene expression, a positive correlation between the density of promoter 6 mA and gene expression level was uncovered. By means of in vitro methylation and gene knockdown assay, METTL4, a homologue of Drosophila methylase CG14906 and C. elegans methylase DAMT-1, was demonstrated to be a mammalian N⁶-adenine methylase that functions in adipogenesis. Knockdown of Mettl4 led to altered adipocyte differentiation, shown by defective gene regulation and impaired lipid production. We also found that the effects of N⁶-adenine methylation on lipid production involved the regulation of INSR signaling pathway, which promotes glucose up-taking and lipid production in the terminal differentiation stage.

Understanding epigenomics based on the rice model

The purpose of this paper provides a comprehensive overview of the recent researches on rice epigenomics, including DNA methylation, histone modifications, noncoding RNAs, and three-dimensional genomics. The challenges and perspectives for future research in rice are discussed. Rice as a model plant for epigenomic studies has much progressed current understanding of epigenetics in plants. Recent results on rice epigenome profiling and three-dimensional chromatin structure studies reveal specific features and implication in gene regulation during rice plant development and adaptation to environmental changes. Results on rice chromatin regulator functions shed light on mechanisms of establishment, recognition, and resetting of epigenomic information in plants. Cloning of several rice epialleles associated with important agronomic traits highlights importance of epigenomic variation in rice plant growth, fitness, and yield. In this review, we summarize and analyze recent advances in rice epigenomics and discuss challenges and directions for future research in the field.

Epigenetic patterns within the haplotype phased fig (Ficus carica L.) genome

Due to DNA heterozygosity and repeat content, assembly of non-model plant genomes is challenging. Herein, we report a high-quality genome reference of one of the oldest known domesticated species, fig (Ficus carica L.), using Pacific Biosciences single-molecule, real-time sequencing. The fig genome is ~333 Mbp in size, of which 80% has been anchored to 13 chromosomes. Genome-wide analysis of N⁶ -methyladenine and N⁴ -methylcytosine revealed high methylation levels in both genes and transposable elements, and a prevalence of methylated over non-methylated genes. Furthermore, the characterization of N⁶ -methyladenine sites led to the identification of ANHGA, a species-specific motif, which is prevalent for both genes and transposable elements. Finally, exploiting the contiguity of the 13 pseudomolecules, we identified 13 putative centromeric regions. The high-quality reference genome and the characterization of methylation profiles, provides an important resource for both fig breeding and for fundamental research into the relationship between epigenetic changes and phenotype, using fig as a model species.

iDNA-MS: An Integrated Computational Tool for Detecting DNA Modification Sites in Multiple Genomes

5hmC, 6mA, and 4mC are three common DNA modifications and are involved in various of biological processes. Accurate genome-wide identification of these sites is invaluable for better understanding their biological functions. Owing to the labor-intensive and expensive nature of experimental methods, it is urgent to develop computational methods for the genome-wide detection of these sites. Keeping this in mind, the current study was devoted to construct a computational method to identify 5hmC, 6mA, and 4mC. We initially used K-tuple nucleotide component, nucleotide chemical property and nucleotide frequency, and mono-nucleotide binary encoding scheme to formulate samples. Subsequently, random forest was utilized to identify 5hmC, 6mA, and 4mC sites. Cross-validated results showed that the proposed method could produce the excellent generalization ability in the identification of the three modification sites. Based on the proposed model, a web-server called iDNA-MS was established and is freely accessible at http://lin-group.cn/server/iDNA-MS.

Structural insights into target DNA recognition by R2R3-MYB transcription factors

As the largest group of MYB family transcription factors, R2R3-MYB proteins play essential roles during plant growth and development. However, the structural basis underlying how R2R3-MYBs recognize the target DNA remains elusive. Here, we report the crystal structure of Arabidopsis WEREWOLF (WER), an R2R3-MYB protein, in complex with its target DNA. Structural analysis showed that the third α-helices in both the R2 and R3 repeats of WER fit in the major groove of the DNA, specifically recognizing the DNA motif 5'-AACNGC-3'. In combination with mutagenesis, in vitro binding and in vivo luciferase assays, we showed that K55, N106, K109 and N110 are critical for the function of WER. Although L59 of WER is not involved in DNA binding in the structure, ITC analysis suggested that L59 plays an important role in sensing DNA methylation at the fifth position of cytosine (5mC). Like 5mC, methylation at the sixth position of adenine (6mA) in the AAC element also inhibits the interaction between WER and its target DNA. Our study not only unravels the molecular basis of how WER recognizes its target DNA, but also suggests that 5mC and 6mA modifications may block the interaction between R2R3-MYB transcription factors and their target genes.

Identification of DNA N6-methyladenine sites by integration of sequence features

Background

An increasing number of nucleic acid modifications have been profiled with the development of sequencing technologies. DNA N⁶-methyladenine (6mA), which is a prevalent epigenetic modification, plays important roles in a series of biological processes. So far, identification of DNA 6mA relies primarily on time-consuming and expensive experimental approaches. However, in silico methods can be implemented to conduct preliminary screening to save experimental resources and time, especially given the rapid accumulation of sequencing data.

Results

In this study, we constructed a 6mA predictor, p6mA, from a series of sequence-based features, including physicochemical properties, position-specific triple-nucleotide propensity (PSTNP), and electron–ion interaction pseudopotential (EIIP). We performed maximum relevance maximum distance (MRMD) analysis to select key features and used the Extreme Gradient Boosting (XGBoost) algorithm to build our predictor. Results demonstrated that p6mA outperformed other existing predictors using different datasets.

Conclusions

p6mA can predict the methylation status of DNA adenines, using only sequence files. It may be used as a tool to help the study of 6mA distribution pattern. Users can download it from https://github.com/Konglab404/p6mA.

DNA N6-Methyladenine Modification in Plant Genomes-A Glimpse into Emerging Epigenetic Code

N6-methyladenine (6mA) is a DNA base modification at the 6th nitrogen position; recently, it has been resurfaced as a potential reversible epigenetic mark in eukaryotes. Despite its existence, 6mA was considered to be absent due to its undetectable level. However, with the new advancements in methods, considerable 6mA distribution is identified across the plant genome. Unlike 5-methylcytosine (5mC) in the gene promoter, 6mA does not have a definitive role in repression but is exposed to have divergent regulation in gene expression. Though 6mA information is less known, the available evidences suggest its function in plant development, tissue differentiation, and regulations in gene expression. The current review article emphasizes the research advances in DNA 6mA modifications, identification, available databases, analysis tools and its significance in plant development, cellular functions and future perspectives of research.

N 6-Methyladenine DNA Modification in the Woodland Strawberry (Fragaria vesca) Genome Reveals a Positive Relationship With Gene Transcription

N 6-methyladenine (6mA) DNA modification has been detected in several eukaryotic organisms, where it plays important roles in gene regulation and epigenetic memory maintenance. However, the genome-wide distribution patterns and potential functions of 6mA DNA modification in woodland strawberry (Fragaria vesca) remain largely unknown. Here, we examined the 6mA landscape in the F. vesca genome by adopting single-molecule real-time sequencing technology and found that 6mA modification sites were broadly distributed across the woodland strawberry genome. The pattern of 6mA distribution in the long non-coding RNA was significantly different from that in protein-coding genes. The 6mA modification influenced the gene transcription and was positively associated with gene expression, which was validated by computational and experimental analyses. Our study provides new insights into the DNA methylation in F. vesca.

Epigenetic Modifications of mRNA and DNA in Plants

Advances in the detection and mapping of messenger RNA (mRNA) N⁶-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C), and DNA N⁶-methyldeoxyadenosine (6mA) redefined our understanding of these modifications as additional tiers of epigenetic regulation. In plants, the most prevalent internal mRNA modifications, m⁶A and m⁵C, play crucial and dynamic roles in many processes, including embryo development, stem cell fate determination, trichome branching, leaf morphogenesis, floral transition, stress responses, fruit ripening, and root development. The newly identified and widespread epigenetic marker 6mA DNA methylation is associated with gene expression, plant development, and stress responses. Here, we review the latest research progress on mRNA and DNA epigenetic modifications, including the detection, dynamics, distribution, functions, regulatory proteins, and evolution, with a focus on m⁶A, m⁵C, and 6mA. We also provide some perspectives on future research of the newly identified and unknown epigenetic modifications of mRNA and DNA in plants.

A Bioinformatics Tool for the Prediction of DNA N6-Methyladenine Modifications Based on Feature Fusion and Optimization Protocol

DNA N⁶-methyladenine (6mA) is closely involved with various biological processes. Identifying the distributions of 6mA modifications in genome-scale is of great significance to in-depth understand the functions. In recent years, various experimental and computational methods have been proposed for this purpose. Unfortunately, existing methods cannot provide accurate and fast 6mA prediction. In this study, we present 6mAPred-FO, a bioinformatics tool that enables researchers to make predictions based on sequences only. To sufficiently capture the characteristics of 6mA sites, we integrate the sequence-order information with nucleotide positional specificity information for feature encoding, and further improve the feature representation capacity by analysis of variance-based feature optimization protocol. The experimental results show that using this feature protocol, we can significantly improve the predictive performance. Via further feature analysis, we found that the sequence-order information and positional specificity information are complementary to each other, contributing to the performance improvement. On the other hand, the improvement is also due to the use of the feature optimization protocol, which is capable of effectively capturing the most informative features from the original feature space. Moreover, benchmarking comparison results demonstrate that our 6mAPred-FO outperforms several existing predictors. Finally, we establish a web-server that implements the proposed method for convenience of researchers' use, which is currently available at http://server.malab.cn/6mAPred-FO.

SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome

DNA N6-adenine methylation (6mA) is an epigenetic modification in prokaryotes and eukaryotes. Identifying 6mA sites in rice genome is important in rice epigenetics and breeding, but non-random distribution and biological functions of these sites remain unclear. Several machine-learning tools can identify 6mA sites but show limited prediction accuracy, which limits their usability in epigenetic research. Here, we developed a novel computational predictor, called the Sequence-based DNA N6-methyladenine predictor (SDM6A), which is a two-layer ensemble approach for identifying 6mA sites in the rice genome. Unlike existing methods, which are based on single models with basic features, SDM6A explores various features, and five encoding methods were identified as appropriate for this problem. Subsequently, an optimal feature set was identified from encodings, and corresponding models were developed individually using support vector machine and extremely randomized tree. First, all five single models were integrated via ensemble approach to define the class for each classifier. Second, two classifiers were integrated to generate a final prediction. SDM6A achieved robust performance on cross-validation and independent evaluation, with average accuracy and Matthews correlation coefficient (MCC) of 88.2% and 0.764, respectively. Corresponding metrics were 4.7%-11.0% and 2.3%-5.5% higher than those of existing methods, respectively. A user-friendly, publicly accessible web server (http://thegleelab.org/SDM6A) was implemented to predict novel putative 6mA sites in rice genome.