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

Effects of stacking breeding on the methylome and transcriptome profile of transgenic rice with glyphosate tolerance

MAIN CONCLUSION

Transcriptomics and methylomics were used to identify the potential effects resulting from GM rice breeding stacks, which provided scientific data for the safety assessment strategy of stacked GM crops in China. Gene interaction is one of the main concerns for stacked genetically modified crop safety. With the development of technology, the combination of omics and bioinformatics has become a useful tool to evaluate the unintended effects of genetically modified crops. In this study, transcriptomics and methylomics were used as molecular profiling techniques to identify the potential effects of stack through breeding. Stacked transgenic rice En-12 × Ec-26 was used as material, which was obtained through hybridization using parents En-12 and Ec-26, in which the foreign protein can form functional EPSPS protein by intein-mediated trans-splitting. Differentially methylated region (DMR) analysis showed that the effect of stacking breeding on methylation was less than that of genetic transformation at the methylome level. Differentially expressed gene (DEG) analysis showed that the DEGs between En-12 × Ec-26 and its parents were far fewer than those between transgenic rice and Zhonghua 11 (ZH11), and no unintended new genes were found in En-12 × Ec-26. Statistical analysis of gene expression and methylation involved in shikimic acid metabolism showed that there was no difference in gene expression, although there were 16 and 10 DMR genes between En-12 × Ec-26 and its parents (En and Ec) in methylation, respectively. The results indicated that the effect of stacking breeding on gene expression and DNA methylation was less than the effect of genetic transformation. This study provides scientific data supporting safety assessments of stacked GM crops in China.

Unlocking the Secret to Higher Crop Yield: The Potential for Histone Modifications

Histone modifications are epigenetic mechanisms, termed relative to genetics, and they refer to the induction of heritable changes without altering the DNA sequence. It is widely known that DNA sequences precisely modulate plant phenotypes to adapt them to the changing environment; however, epigenetic mechanisms also greatly contribute to plant growth and development by altering chromatin status. An increasing number of recent studies have elucidated epigenetic regulations on improving plant growth and adaptation, thus making contributions to the final yield. In this review, we summarize the recent advances of epigenetic regulatory mechanisms underlying crop flowering efficiency, fruit quality, and adaptation to environmental stimuli, especially to abiotic stress, to ensure crop improvement. In particular, we highlight the major discoveries in rice and tomato, which are two of the most globally consumed crops. We also describe and discuss the applications of epigenetic approaches in crop breeding programs.

DGA-5mC: A 5-methylcytosine site prediction model based on an improved DenseNet and bidirectional GRU method

The 5-methylcytosine (5mC) in the promoter region plays a significant role in biological processes and diseases. A few high-throughput sequencing technologies and traditional machine learning algorithms are often used by researchers to detect 5mC modification sites. However, high-throughput identification is laborious, time-consuming and expensive; moreover, the machine learning algorithms are not so advanced. Therefore, there is an urgent need to develop a more efficient computational approach to replace those traditional methods. Since deep learning algorithms are more popular and have powerful computational advantages, we constructed a novel prediction model, called DGA-5mC, to identify 5mC modification sites in promoter regions by using a deep learning algorithm based on an improved densely connected convolutional network (DenseNet) and the bidirectional GRU approach. Furthermore, we added a self-attention module to evaluate the importance of various 5mC features. The deep learning-based DGA-5mC model algorithm automatically handles large proportions of unbalanced data for both positive and negative samples, highlighting the model's reliability and superiority. So far as the authors are aware, this is the first time that the combination of an improved DenseNet and bidirectional GRU methods has been used to predict the 5mC modification sites in promoter regions. It can be seen that the DGA-5mC model, after using a combination of one-hot coding, nucleotide chemical property coding and nucleotide density coding, performed well in terms of sensitivity, specificity, accuracy, the Matthews correlation coefficient (MCC), area under the curve and Gmean in the independent test dataset: 90.19%, 92.74%, 92.54%, 64.64%, 96.43% and 91.46%, respectively. In addition, all datasets and source codes for the DGA-5mC model are freely accessible at https://github.com/lulukoss/DGA-5mC.

Epigenetic Dynamics and Regulation of Plant Male Reproduction

Flowering plant male germlines develop within anthers and undergo epigenetic reprogramming with dynamic changes in DNA methylation, chromatin modifications, and small RNAs. Profiling the epigenetic status using different technologies has substantially accumulated information on specific types of cells at different stages of male reproduction. Many epigenetically related genes involved in plant gametophyte development have been identified, and the mutation of these genes often leads to male sterility. Here, we review the recent progress on dynamic epigenetic changes during pollen mother cell differentiation, microsporogenesis, microgametogenesis, and tapetal cell development. The reported epigenetic variations between male fertile and sterile lines are summarized. We also summarize the epigenetic regulation-associated male sterility genes and discuss how epigenetic mechanisms in plant male reproduction can be further revealed.

Same modification, different location: the mythical role of N6-adenine methylation in plant genomes

The present review summarizes recent advances in the understanding of 6mA in DNA as an emergent epigenetic mark with distinctive characteristics, discusses its importance in plant genomes, and highlights its chemical nature and functions. Adenine methylation is an epigenetic modification present in DNA (6mA) and RNA (m6A) that has a regulatory function in many cellular processes. This modification occurs through a reversible reaction that covalently binds a methyl group, usually at the N⁶ position of the purine ring. This modification carries biophysical properties that affect the stability of nucleic acids as well as their binding affinity with other molecules. DNA 6mA has been related to genome stability, gene expression, DNA replication, and repair mechanisms. Recent advances have shown that 6mA in plant genomes is related to development and stress response. In this review, we present recent advances in the understanding of 6mA in DNA as an emergent epigenetic mark with distinctive characteristics. We discuss the key elements of this modification, focusing mainly on its importance in plant genomes. Furthermore, we highlight its chemical nature and the regulatory effects that it exerts on gene expression and plant development. Finally, we emphasize the functions of 6mA in photosynthesis, stress, and flowering.

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.

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.

Whole-genome characterization of chronological age-associated changes in methylome and circular RNAs in moso bamboo (Phyllostachys edulis) from vegetative to floral growth

In mammals, DNA methylation is associated with aging. However, age-related DNA methylation changes during phase transitions largely remain unstudied in plants. Moso bamboo (Phyllostachys edulis) requires a very long time to transition from the vegetative to the floral phase. To comprehensively investigate the association of DNA methylation with aging, we present here single-base-resolution DNA methylation profiles using both high-throughput bisulfite sequencing and single-molecule nanopore-based DNA sequencing, covering the long period of vegetative growth and transition to flowering in moso bamboo. We discovered that CHH methylation gradually accumulates from vegetative to reproductive growth in a time-dependent fashion. Differentially methylated regions, correlating with chronological aging, occurred preferentially at both transcription start sites and transcription termination sites. Genes with CG methylation changes showed an enrichment of Gene Ontology (GO) categories in 'vegetative to reproductive phase transition of meristem'. Combining methylation data with mRNA sequencing revealed that DNA methylation in promoters, introns and exons may have different roles in regulating gene expression. Finally, circular RNA (circRNA) sequencing revealed that the flanking introns of circRNAs are hypermethylated and enriched in long terminal repeat (LTR) retrotransposons. Together, the observations in this study provide insights into the dynamic DNA methylation and circRNA landscapes, correlating with chronological age, which paves the way to study further the impact of epigenetic factors on flowering in moso bamboo.

Whole-Genome DNA Methylation Analysis in Hydrogen Peroxide Overproducing Transgenic Tobacco Resistant to Biotic and Abiotic Stresses

Epigenetic regulation is a key component of stress responses, acclimatization and adaptation processes in plants. DNA methylation is a stable mark plausible for the inheritance of epigenetic traits, such that it is a potential scheme for plant breeding. However, the effect of modulators of stress responses, as hydrogen peroxide (H₂O₂), in the methylome status has not been elucidated. A transgenic tobacco model to the CchGLP gene displayed high H₂O₂ endogen levels correlated with biotic and abiotic stresses resistance. The present study aimed to determine the DNA methylation status changes in the transgenic model to obtain more information about the molecular mechanism involved in resistance phenotypes. The Whole-genome bisulfite sequencing analysis revealed a minimal impact of overall levels and distribution of methylation. A total of 9432 differential methylated sites were identified in distinct genome regions, most of them in CHG context, with a trend to hypomethylation. Of these, 1117 sites corresponded to genes, from which 83 were also differentially expressed in the plants. Several genes were associated with respiration, energy, and calcium signaling. The data obtained highlighted the relevance of the H₂O₂ in the homeostasis of the system in stress conditions, affecting at methylation level and suggesting an association of the H₂O₂ in the physiological adaptation to stress functional linkages may be regulated in part by DNA methylation.

Noncoding RNA: An Insight into Chloroplast and Mitochondrial Gene Expressions

Regulation of gene expression in any biological system is a complex process with many checkpoints at the transcriptional, post-transcriptional and translational levels. The control mechanism is mediated by various protein factors, secondary metabolites and a newly included regulatory member, i.e., noncoding RNAs (ncRNAs). It is known that ncRNAs modulate the mRNA or protein profiles of the cell depending on the degree of complementary and context of the microenvironment. In plants, ncRNAs are essential for growth and development in normal conditions by controlling various gene expressions and have emerged as a key player to guard plants during adverse conditions. In order to have smooth functioning of the plants under any environmental pressure, two very important DNA-harboring semi-autonomous organelles, namely, chloroplasts and mitochondria, are considered as main players. These organelles conduct the most crucial metabolic pathways that are required to maintain cell homeostasis. Thus, it is imperative to explore and envisage the molecular machineries responsible for gene regulation within the organelles and their coordination with nuclear transcripts. Therefore, the present review mainly focuses on ncRNAs origination and their gene regulation in chloroplasts and plant mitochondria.