MicroRNAs: A novel signature in the metastasis of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a malignant epithelial tumor, characterized by squamous cell differentiation, it is the sixth leading cause of cancer-related deaths globally. The increased mortality rate of ESCC patients is predominantly due to the advanced stage of the disease when discovered, coupled with higher risk of metastasis, which is an exceedingly malignant characteristic of cancer, frequently leading to a high mortality rate. Unfortunately, there is currently no specific and effective marker to predict and treat metastasis in ESCC. MicroRNAs (miRNAs) are a class of small non-coding RNA molecules, approximately 22 nucleotides in length. miRNAs are vital in modulating gene expression and serve pivotal regulatory roles in the occurrence, progression, and prognosis of cancer. Here, we have examined the literature to highlight the intimate correlations between miRNAs and ESCC metastasis, and show that ESCC metastasis is predominantly regulated or regulated by genetic and epigenetic factors. This review proposes a potential role for miRNAs as diagnostic and therapeutic biomarkers for metastasis in ESCC metastasis, with the ultimate aim of reducing the mortality rate among patients with ESCC.

Special Issue "Epigenetics in Neurodegenerative Diseases".

Epigenetic mechanisms inducing phenotypic changes without altering the DNA genome are increasingly recognized as key factors modulating gene expression and, consequently, cell functions [...].

The Role of Epigenetic Factors in the Pathogenesis of Psoriasis.

Psoriasis is a chronic inflammatory skin disease, the prevalence of which is increasing. Genetic, genomic, and epigenetic changes play a significant role in the pathogenesis of psoriasis. This review summarizes the impact of epigenetics on the development of psoriasis and highlights challenges for the future. The development of epigenetics provides a basis for the search for genetic markers associated with the major histocompatibility complex. Genome-wide association studies have made it possible to link psoriasis to genes and therefore to epigenetics. The acquired knowledge may in the future serve as a solid foundation for developing newer, increasingly effective methods of treating psoriasis. In this narrative review, we discuss the role of epigenetic factors in the pathogenesis of psoriasis.

FGFR1 fusions as a novel molecular driver in rhabdomyosarcoma.

The wide application of RNA sequencing in clinical practice has allowed the discovery of novel fusion genes, which have contributed to a refined molecular classification of rhabdomyosarcoma (RMS). Most fusions in RMS result in aberrant transcription factors, such as PAX3/7::FOXO1 in alveolar RMS (ARMS) and fusions involving VGLL2 or NCOA2 in infantile spindle cell RMS. However, recurrent fusions driving oncogenic kinase activation have not been reported in RMS. Triggered by an index case of an unclassified RMS (overlapping features between ARMS and sclerosing RMS) with a novel FGFR1::ANK1 fusion, we reviewed our molecular files for cases harboring FGFR1-related fusions. One additional case with an FGFR1::TACC1 fusion was identified in a tumor resembling embryonal RMS (ERMS) with anaplasia, but with no pathogenic variants in TP53 or DICER1 on germline testing. Both cases occurred in males, aged 7 and 24, and in the pelvis. The 2nd case also harbored additional alterations, including somatic TP53 and TET2 mutations. Two additional RMS cases (one unclassified, one ERMS) with FGFR1 overexpression but lacking FGFR1 fusions were identified by RNA sequencing. These two cases and the FGFR1::TACC1-positive case clustered together with the ERMS group by RNAseq. This is the first report of RMS harboring recurrent FGFR1 fusions. However, it remains unclear if FGFR1 fusions define a novel subset of RMS or alternatively, whether this alteration can sporadically drive the pathogenesis of known RMS subtypes, such as ERMS. Additional larger series with integrated genomic and epigenetic datasets are needed for better subclassification, as the resulting oncogenic kinase activation underscores the potential for targeted therapy.

Integrative analysis reveals associations between oral microbiota dysbiosis and host genetic and epigenetic aberrations in oral cavity squamous cell carcinoma.

Dysbiosis of the human oral microbiota has been reported to be associated with oral cavity squamous cell carcinoma (OSCC) while the host-microbiota interactions with respect to the potential impact of pathogenic bacteria on host genomic and epigenomic abnormalities remain poorly studied. In this study, the mucosal bacterial community, host genome-wide transcriptome and DNA CpG methylation were simultaneously profiled in tumors and their adjacent normal tissues of OSCC patients. Significant enrichment in the relative abundance of seven bacteria species (Fusobacterium nucleatum, Treponema medium, Peptostreptococcus stomatis, Gemella morbillorum, Catonella morbi, Peptoanaerobacter yurli and Peptococcus simiae) were observed in OSCC tumor microenvironment. These tumor-enriched bacteria formed 254 positive correlations with 206 up-regulated host genes, mainly involving signaling pathways related to cell adhesion, migration and proliferation. Integrative analysis of bacteria-transcriptome and bacteria-methylation correlations identified at least 20 dysregulated host genes with inverted CpG methylation in their promoter regions associated with enrichment of bacterial pathogens, implying a potential of pathogenic bacteria to regulate gene expression, in part, through epigenetic alterations. An in vitro model further confirmed that Fusobacterium nucleatum might contribute to cellular invasion via crosstalk with E-cadherin/ß-catenin signaling, TNFα/NF-κB pathway and extracellular matrix remodeling by up-regulating SNAI2 gene, a key transcription factor of epithelial-mesenchymal transition (EMT). Our work using multi-omics approaches explored complex host-microbiota interactions and provided important insights into genetic and functional basis in OSCC tumorigenesis, which may serve as a precursor for hypothesis-driven study to better understand the causational relationship of pathogenic bacteria in this deadly cancer.

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation.

BACKGROUND: Regulation of transcription is central to the emergence of new cell types during development, and it often involves activation of genes via proximal and distal regulatory regions. The activity of regulatory elements is determined by transcription factors (TFs) and epigenetic marks, but despite extensive mapping of such patterns, the extraction of regulatory principles remains challenging. RESULTS: Here we study differentially and similarly expressed genes along with their associated epigenomic profiles, chromatin accessibility and DNA methylation, during lineage specification at gastrulation in mice. Comparison of the three lineages allows us to identify genomic and epigenomic features that distinguish the two classes of genes. We show that differentially expressed genes are primarily regulated by distal elements, while similarly expressed genes are controlled by proximal housekeeping regulatory programs. Differentially expressed genes are relatively isolated within topologically associated domains, while similarly expressed genes tend to be located in gene clusters. Transcription of differentially expressed genes is associated with differentially open chromatin at distal elements including enhancers, while that of similarly expressed genes is associated with ubiquitously accessible chromatin at promoters. CONCLUSION: Based on these associations of (linearly) distal genes' transcription start sites (TSSs) and putative enhancers for developmental genes, our findings allow us to link putative enhancers to their target promoters and to infer lineage-specific repertoires of putative driver transcription factors, within which we define subgroups of pioneers and co-operators.

Infant Bronchiolitis Endotypes and the Risk of Developing Childhood Asthma: Lessons From Cohort Studies

Severe bronchiolitis (i.e., bronchiolitis requiring hospitalization) during infancy is a heterogeneous condition associated with a high risk of developing childhood asthma. Yet, the exact mechanisms underlying the bronchiolitis-asthma link remain uncertain. Birth cohort studies have reported this association at the population level, including only small groups of patients with a history of bronchiolitis, and have attempted to identify the underlying biological mechanisms. Although this evidence has provided valuable insights, there are still unanswered questions regarding severe bronchiolitis-asthma pathogenesis. Recently, a few bronchiolitis cohort studies have attempted to answer these questions by applying unbiased analytical approaches to biological data. These cohort studies have identified novel bronchiolitis subtypes (i.e., endotypes) at high risk for asthma development, representing essential and enlightening evidence. For example, one distinct severe respiratory syncytial virus (RSV) bronchiolitis endotype is characterized by the presence of Moraxella catarrhalis and Streptococcus pneumoniae, higher levels of type I/II IFN expression, and changes in carbohydrate metabolism in nasal airway samples, and is associated with a high risk for childhood asthma development. Although these findings hold significance for the design of future studies that focus on childhood asthma prevention, they require validation. However, this scoping review puts the above findings into clinical context and emphasizes the significance of future research in this area aiming to offer new bronchiolitis treatments and contribute to asthma prevention. (AU)

The genetic regulatory architecture and epigenomic basis for age-related changes in rattlesnake venom.

Developmental phenotypic changes can evolve under selection imposed by age- and size-related ecological differences. Many of these changes occur through programmed alterations to gene expression patterns, but the molecular mechanisms and gene-regulatory networks underlying these adaptive changes remain poorly understood. Many venomous snakes, including the eastern diamondback rattlesnake (Crotalus adamanteus), undergo correlated changes in diet and venom expression as snakes grow larger with age, providing models for identifying mechanisms of timed expression changes that underlie adaptive life history traits. By combining a highly contiguous, chromosome-level genome assembly with measures of expression, chromatin accessibility, and histone modifications, we identified cis-regulatory elements and trans-regulatory factors controlling venom ontogeny in the venom glands of C. adamanteus. Ontogenetic expression changes were significantly correlated with epigenomic changes within genes, immediately adjacent to genes (e.g., promoters), and more distant from genes (e.g., enhancers). We identified 37 candidate transcription factors (TFs), with the vast majority being up-regulated in adults. The ontogenetic change is largely driven by an increase in the expression of TFs associated with growth signaling, transcriptional activation, and circadian rhythm/biological timing systems in adults with corresponding epigenomic changes near the differentially expressed venom genes. However, both expression activation and repression contributed to the composition of both adult and juvenile venoms, demonstrating the complexity and potential evolvability of gene regulation for this trait. Overall, given that age-based trait variation is common across the tree of life, we provide a framework for understanding gene-regulatory-network-driven life-history evolution more broadly.

Epigenetics in diabetic cardiomyopathy.

Diabetic cardiomyopathy (DCM) is a critical complication that poses a significant threat to the health of patients with diabetes. The intricate pathological mechanisms of DCM cause diastolic dysfunction, followed by impaired systolic function in the late stages. Accumulating researches have revealed the association between DCM and various epigenetic regulatory mechanisms, including DNA methylation, histone modifications, non-coding RNAs, and other epigenetic molecules. Recently, a profound understanding of epigenetics in the pathophysiology of DCM has been broadened owing to advanced high-throughput technologies, which assist in developing potential therapeutic strategies. In this review, we briefly introduce the epigenetics regulation and update the relevant progress in DCM. We propose the role of epigenetic factors and non-coding RNAs (ncRNAs) as potential biomarkers and drugs in DCM diagnosis and treatment, providing a new perspective and understanding of epigenomics in DCM.

Epigenomic insights into common human disease pathology.

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Metabologenomic characterization uncovers a clinically aggressive IDH mutant glioma subtype.

Mutations in the pivotal metabolic isocitrate dehydrogenase (IDH) enzymes are recognized to drive the molecular footprint of diffuse gliomas, and patients with IDH mutant gliomas have overall favorable outcomes compared to patients with IDH wild-type tumors. However, survival still varies widely among patients with IDH mutated tumors. Here, we aimed to characterize molecular signatures that explain the range of IDH mutant gliomas. By integrating matched epigenome-wide methylome, transcriptome, and global metabolome data in 154 patients with gliomas, we identified a group of IDH mutant gliomas with globally altered metabolism that resembled IDH wild-type tumors. IDH-mutant gliomas with altered metabolism have significantly shorter overall survival from their IDH mutant counterparts that is not fully accounted for by recognized molecular prognostic markers of CDKN2A/B loss and glioma CpG Island Methylator Phenotype (GCIMP) status. IDH-mutant tumors with dysregulated metabolism harbored distinct epigenetic alterations that converged to drive proliferative and stem-like transcriptional profiles, providing a window to target novel dependencies in gliomas.

EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics.

DNA methylation analysis based on supervised machine learning algorithms with static reference data, allowing diagnostic tumour typing with unprecedented precision, has quickly become a new standard of care. Whereas genome-wide diagnostic methylation profiling is mostly performed on microarrays, an increasing number of institutions additionally employ nanopore sequencing as a faster alternative. In addition, methylation-specific parallel sequencing can generate methylation and genomic copy number data. Given these diverse approaches to methylation profiling, to date, there is no single tool that allows (1) classification and interpretation of microarray, nanopore and parallel sequencing data, (2) direct control of nanopore sequencers, and (3) the integration of microarray-based methylation reference data. Furthermore, no software capable of entirely running in routine diagnostic laboratory environments lacking high-performance computing and network infrastructure exists. To overcome these shortcomings, we present EpiDiP/NanoDiP as an open-source DNA methylation and copy number profiling suite, which has been benchmarked against an established supervised machine learning approach using in-house routine diagnostics data obtained between 2019 and 2021. Running locally on portable, cost- and energy-saving system-on-chip as well as gpGPU-augmented edge computing devices, NanoDiP works in offline mode, ensuring data privacy. It does not require the rigid training data annotation of supervised approaches. Furthermore, NanoDiP is the core of our public, free-of-charge EpiDiP web service which enables comparative methylation data analysis against an extensive reference data collection. We envision this versatile platform as a useful resource not only for neuropathologists and surgical pathologists but also for the tumour epigenetics research community. In daily diagnostic routine, analysis of native, unfixed biopsies by NanoDiP delivers molecular tumour classification in an intraoperative time frame.

Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues.

Expression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125 489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence and epigenomic characteristics. Based on these classifications, we developed a machine-learning model, E-SpotFinder, for augmented discovery of tissue- or cell-type-specific eQTL-hotspots. We applied this model to 36 tissues or cell types. Using augmented eQTL-hotspots, we recovered 655 402 eSNPs and reconstructed a comprehensive regulatory network of 2 725 380 cis-interactions among eQTL-hotspots. We further identified 52 012 modules representing transcriptional programs with unique functional backgrounds. In summary, our study provided a framework of epigenome-augmented eQTL analysis and thereby constructed comprehensive genome-wide networks of cis-regulations across diverse human tissues or cell types.

Accelerated epigenetic aging in alcohol dependence.

Alcohol dependence poses a global health threat associated with aging and reduced life expectancy. Recently, aging research through deoxyribonucleic acid (DNA) methylation has gained attention. New epigenetic clocks have been developed; however, no study has investigated GrimAge components, GrimAge2 components and DunedinPACE in patients with alcohol dependence. In this study, we aimed to perform epigenetic clock analysis to evaluate epigenetic age acceleration and DNA methylation-based age-predictive components in patients with alcohol dependence and controls. We utilized publicly available DNA methylation data (GSE98876) for our analysis. Additionally, we compared the values of the same items before and after the patients underwent a treatment program. The dataset comprised 23 controls and 24 patients. We observed that DunedinPACE accelerated more in patients with alcohol dependence. AgeAccelGrim and AgeAccelGrim2 decelerated more after the treatment program than before, and beta-2-microglobulin and Cystatin C decreased after the treatment program than before. These findings are crucial as they affect the cranial nerve area, potentially contributing to cognitive dysfunction and psychiatric symptoms in patients with alcohol dependence.

Tutorial on survival modeling with applications to omics data.

MOTIVATION: Identification of genomic, molecular and clinical markers prognostic of patient survival is important for developing personalized disease prevention, diagnostic and treatment approaches. Modern omics technologies have made it possible to investigate the prognostic impact of markers at multiple molecular levels, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, and how these potential risk factors complement clinical characterization of patient outcomes for survival prognosis. However, the massive sizes of the omics datasets, along with their correlation structures, pose challenges for studying relationships between the molecular information and patients' survival outcomes. RESULTS: We present a general workflow for survival analysis that is applicable to high-dimensional omics data as inputs when identifying survival-associated features and validating survival models. In particular, we focus on the commonly used Cox-type penalized regressions and hierarchical Bayesian models for feature selection in survival analysis, which are especially useful for high-dimensional data, but the framework is applicable more generally. AVAILABILITY AND IMPLEMENTATION: A step-by-step R tutorial using The Cancer Genome Atlas survival and omics data for the execution and evaluation of survival models has been made available at https://ocbe-uio.github.io/survomics.

Evaluating offspring Genomic and Epigenomic alterations after prenatal exposure to Cancer treatment In Pregnancy (GE-CIP): a multicentric observational study.

INTRODUCTION: Around 1 in 1000-2000 pregnancies are affected by a cancer diagnosis. Previous studies have shown that chemotherapy during pregnancy has reassuring cognitive and cardiac neonatal outcomes, and hence has been proposed as standard of care. However, although these children perform within normal ranges for their age, subtle differences have been identified. Given that chemotherapeutic compounds can cross the placenta, the possibility that prenatal chemotherapy exposure mutates the offspring's genome and/or epigenome, with potential deleterious effects later in life, urges to be investigated. METHODS AND ANALYSES: This multicentric observational study aims to collect cord blood, meconium and neonatal buccal cells at birth, as well as peripheral blood, buccal cells and urine from infants when 6, 18 and/or 36 months of age. Using bulk and single-cell approaches, we will compare samples from chemotherapy-treated pregnant patients with cancer, pregnant patients with cancer not treated with chemotherapy and healthy pregnant women. Potential chemotherapy-related newborn genomic and/or epigenomic alterations, such as single nucleotide variants, copy number variants and DNA-methylation alterations, will be identified in mononuclear and epithelial cells, isolated from blood, buccal swabs and urine. DNA from maternal peripheral blood and paternal buccal cells will be used to determine de novo somatic mutations in the neonatal blood and epithelial cells. Additionally, the accumulated exposure of the fetus, and biological effective dose of alkylating agents, will be assessed in meconium and cord blood via mass spectrometry approaches. ETHICS AND DISSEMINATION: The Ethics Committee Research of UZ/KU Leuven (EC Research) and the Medical Ethical Review Committee of University Medical Center Amsterdam have approved the study. Results of this study will be disseminated via presentations at (inter)national conferences, through peer-reviewed, open-access publications, via social media platforms aimed to inform patients and healthcare workers, and through the website of the International Network on Cancer, Infertility and Pregnancy (www.cancerinpregnancy.org).

Molecular pathological approach to cancer epigenomics and its clinical application.

Careful microscopic observation of histopathological specimens, accumulation of large numbers of high-quality tissue specimens, and analysis of molecular pathology in relation to morphological features are considered to yield realistic data on the nature of multistage carcinogenesis. Since the morphological hallmark of cancer is disruption of the normal histological structure maintained through cell-cell adhesiveness and cellular polarity, attempts have been made to investigate abnormalities of the cadherin-catenin cell adhesion system in human cancer cells. It has been shown that the CDH1 tumor suppressor gene encoding E-cadherin is silenced by DNA methylation, suggesting that a "double hit" involving DNA methylation and loss of heterozygosity leads to carcinogenesis. Therefore, in the 1990s, we focused on epigenomic mechanisms, which until then had not received much attention. In chronic hepatitis and liver cirrhosis associated with hepatitis virus infection, DNA methylation abnormalities were found to occur frequently, being one of the earliest indications that such abnormalities are present even in precancerous tissue. Aberrant expression and splicing of DNA methyltransferases, such as DNMT1 and DNMT3B, was found to underlie the mechanism of DNA methylation alterations in various organs. The CpG island methylator phenotype in renal cell carcinoma was identified for the first time, and its therapeutic targets were identified by multilayer omics analysis. Furthermore, the DNA methylation profile of nonalcoholic steatohepatitis (NASH)-related hepatocellular carcinoma was clarified in groundbreaking studies. Since then, we have developed diagnostic markers for carcinogenesis risk in NASH patients and noninvasive diagnostic markers for upper urinary tract cancer, as well as developing a new high-performance liquid chromatography-based diagnostic system for DNA methylation diagnosis. Research on the cancer epigenome has revealed that DNA methylation alterations occur from the precancerous stage as a result of exposure to carcinogenic factors such as inflammation, smoking, and viral infections, and continuously contribute to multistage carcinogenesis through aberrant expression of cancer-related genes and genomic instability. DNA methylation alterations at the precancerous stages are inherited by or strengthened in cancers themselves and determine the clinicopathological aggressiveness of cancers as well as patient outcome. DNA methylation alterations have applications as biomarkers, and are expected to contribute to diagnosis, as well as preventive and preemptive medicine.

Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis.

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data provided new insights into the understanding of epigenetic heterogeneity and transcriptional regulation. With the increasing abundance of dataset resources, there is an urgent need to extract more useful information through high-quality data analysis methods specifically designed for scATAC-seq. However, analyzing scATAC-seq data poses challenges due to its near binarization, high sparsity and ultra-high dimensionality properties. Here, we proposed a novel network diffusion-based computational method to comprehensively analyze scATAC-seq data, named Single-Cell ATAC-seq Analysis via Network Refinement with Peaks Location Information (SCARP). SCARP formulates the Network Refinement diffusion method under the graph theory framework to aggregate information from different network orders, effectively compensating for missing signals in the scATAC-seq data. By incorporating distance information between adjacent peaks on the genome, SCARP also contributes to depicting the co-accessibility of peaks. These two innovations empower SCARP to obtain lower-dimensional representations for both cells and peaks more effectively. We have demonstrated through sufficient experiments that SCARP facilitated superior analyses of scATAC-seq data. Specifically, SCARP exhibited outstanding cell clustering performance, enabling better elucidation of cell heterogeneity and the discovery of new biologically significant cell subpopulations. Additionally, SCARP was also instrumental in portraying co-accessibility relationships of accessible regions and providing new insight into transcriptional regulation. Consequently, SCARP identified genes that were involved in key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to diseases and predicted reliable cis-regulatory interactions. To sum up, our studies suggested that SCARP is a promising tool to comprehensively analyze the scATAC-seq data.

Genomic and Epigenomic Changes in the Progeny of Cold-Stressed Arabidopsis thaliana Plants.

Plants are continuously exposed to various environmental stresses. Because they can not escape stress, they have to develop mechanisms of remembering stress exposures somatically and passing it to the progeny. We studied the Arabidopsis thaliana ecotype Columbia plants exposed to cold stress for 25 continuous generations. Our study revealed that multigenerational exposure to cold stress resulted in the changes in the genome and epigenome (DNA methylation) across generations. Main changes in the progeny were due to the high frequency of genetic mutations rather than epigenetic changes; the difference was primarily in single nucleotide substitutions and deletions. The progeny of cold-stressed plants exhibited the higher rate of missense non-synonymous mutations as compared to the progeny of control plants. At the same time, epigenetic changes were more common in the CHG (C = cytosine, H = cytosine, adenine or thymine, G = guanine) and CHH contexts and favored hypomethylation. There was an increase in the frequency of C to T (thymine) transitions at the CHH positions in the progeny of cold stressed plants; because this type of mutations is often due to the deamination of the methylated cytosines, it can be hypothesized that environment-induced changes in methylation contribute to mutagenesis and may be to microevolution processes and that RNA-dependent DNA methylation plays a crucial role. Our work supports the existence of heritable stress response in plants and demonstrates that genetic changes prevail.