Methyl-CpG-Binding Domain Sequencing: MBD-seq

Epigenetic signatures of social status in wild female spotted hyenas (Crocuta crocuta)

In mammalian societies, dominance hierarchies translate into inequalities in health, reproductive performance and survival. DNA methylation is thought to mediate the effects of social status on gene expression and phenotypic outcomes, yet a study of social status-specific DNA methylation profiles in different age classes in a wild social mammal is missing. We tested for social status signatures in DNA methylation profiles in wild female spotted hyenas (Crocuta crocuta), cubs and adults, using non-invasively collected gut epithelium samples. In spotted hyena clans, female social status influences access to resources, foraging behavior, health, reproductive performance and survival. We identified 149 differentially methylated regions between 42 high- and low-ranking female spotted hyenas (cubs and adults). Differentially methylated genes were associated with energy conversion, immune function, glutamate receptor signalling and ion transport. Our results provide evidence that socio-environmental inequalities are reflected at the molecular level in cubs and adults in a wild social mammal.

Broodstock nutritional programming differentially affects the hepatic transcriptome and genome-wide DNA methylome of farmed gilthead sea bream (Sparus aurata) depending on genetic background

BACKGROUND

Broodstock nutritional programming improves the offspring utilization of plant-based diets in gilthead sea bream through changes in hepatic metabolism. Attention was initially focused on fatty acid desaturases, but it can involve a wide range of processes that remain largely unexplored. How all this can be driven by a different genetic background is hardly underlined, and the present study aimed to assess how broodstock nutrition affects differentially the transcriptome and genome-wide DNA methylome of reference and genetically selected fish within the PROGENSA® selection program.

RESULTS

After the stimulus phase with a low fish oil diet, two offspring subsets of each genetic background received a control or a FUTURE-based diet. This highlighted a different hepatic transcriptome (RNA-seq) and genome-wide DNA methylation (MBD-seq) pattern depending on the genetic background. The number of differentially expressed transcripts following the challenge phase varied from 323 in reference fish to 2,009 in genetically selected fish. The number of discriminant transcripts, and associated enriched functions, were also markedly higher in selected fish. Moreover, correlation analysis depicted a hyper-methylated and down-regulated gene expression state in selected fish with the FUTURE diet, whereas the opposite pattern appeared in reference fish. After filtering for highly represented functions in selected fish, 115 epigenetic markers were retrieved in this group. Among them, lipid metabolism genes (23) were the most reactive following ordering by fold-change in expression, rendering a final list of 10 top markers with a key role on hepatic lipogenesis and fatty acid metabolism (cd36, pitpna, cidea, fasn, g6pd, lipt1, scd1a, acsbg2, acsl14, acsbg2).

CONCLUSIONS

Gene expression profiles and methylation signatures were dependent on genetic background in our experimental model. Such assumption affected the magnitude, but also the type and direction of change. Thus, the resulting epigenetic clock of reference fish might depict an older phenotype with a lower methylation for the epigenetically responsive genes with a negative methylation-expression pattern. Therefore, epigenetic markers will be specific of each genetic lineage, serving the broodstock programming in our selected fish to prevent and mitigate later in life the risk of hepatic steatosis through changes in hepatic lipogenesis and fatty acid metabolism.

Epigenetic analysis in a murine genetic model of Gulf War illness

Of the nearly 1 million military personnel who participated in the 1990-1991 Gulf War, between 25% and 35% became ill with what now is referred to as Gulf War Illness (GWI) by the Department of Defense. Symptoms varied from gastrointestinal distress to lethargy, memory loss, inability to concentrate, depression, respiratory, and reproductive problems. The symptoms have persisted for 30 years in those afflicted but the basis of the illness remains largely unknown. Nerve agents and other chemical exposures in the war zone have been implicated but the long-term effects of these acute exposures have left few if any identifiable signatures. The major aim of this study is to elucidate the possible genomic basis for the persistence of symptoms, especially of the neurological and behavioral effects. To address this, we performed a whole genome epigenetic analysis of the proposed cause of GWI, viz., exposure to organophosphate neurotoxicants combined with high circulating glucocorticoids in two inbred mouse strains, C57BL/6J and DBA/2J. The animals received corticosterone in their drinking water for 7 days followed by injection of diisopropylfluorophosphate, a nerve agent surrogate. Six weeks after DFP injection, the animals were euthanized and medial prefrontal cortex harvested for genome-wide DNA methylation analysis using high-throughput sequencing. We observed 67 differentially methylated genes, notably among them, Ttll7, Akr1c14, Slc44a4, and Rusc2, all related to different symptoms of GWI. Our results support proof of principle of genetic differences in the chronic effects of GWI-related exposures and may reveal why the disease has persisted in many of the now aging Gulf War veterans.

Epigenetic analytical approaches in ecotoxicological aquatic research

Environmental epigenetics has become a key research focus in global climate change studies and environmental pollutant investigations impacting aquatic ecosystems. Specifically, triggered by environmental stress conditions, intergenerational DNA methylation changes contribute to biological adaptive responses and survival of organisms to increase their tolerance towards these conditions. To critically review epigenetic analytical approaches in ecotoxicological aquatic research, we evaluated 78 publications reported over the past five years (2016-2021) that applied these methods to investigate the responses of aquatic organisms to environmental changes and pollution. The results show that DNA methylation appears to be the most robust epigenetic regulatory mark studied in aquatic animals. As such, multiple DNA methylation analysis methods have been developed in aquatic organisms, including enzyme restriction digestion-based and methyl-specific immunoprecipitation methods, and bisulfite (in)dependent sequencing strategies. In contrast, only a handful of aquatic studies, i.e. about 15%, have been focusing on histone variants and post-translational modifications due to the lack of species-specific affinity based immunological reagents, such as specific antibodies for chromatin immunoprecipitation applications. Similarly, ncRNA regulation remains as the least popular method used in the field of environmental epigenetics. Insights into the opportunities and challenges of the DNA methylation and histone variant analysis methods as well as decreasing costs of next generation sequencing approaches suggest that large-scale epigenetic environmental studies in model and non-model organisms will soon become available in the near future. Moreover, antibody-dependent and independent methods, such as mass spectrometry-based methods, can be used as an alternative epigenetic approach to characterize global changes of chromatin histone modifications in future aquatic research. Finally, a systematic guide for DNA methylation and histone variant methods is offered for ecotoxicological aquatic researchers to select the most relevant epigenetic analytical approach in their research.

Epigenetic Dysregulation in Alcohol-Associated Behaviors: Preclinical and Clinical Evidence

Alcohol use disorder (AUD) is characterized by loss of control over intake and drinking despite harmful consequences. At a molecular level, AUD is associated with long-term neuroadaptations in key brain regions that are involved in reward processing and decision-making. Over the last decades, a great effort has been made to understand the neurobiological basis underlying AUD. Epigenetic mechanisms have emerged as an important mechanism in the regulation of long-term alcohol-induced gene expression changes. Here, we review the literature supporting a role for epigenetic processes in AUD. We particularly focused on the three most studied epigenetic mechanisms: DNA methylation, Histone modification and non-coding RNAs. Clinical studies indicate an association between AUD and DNA methylation both at the gene and global levels. Using behavioral paradigms that mimic some of the characteristics of AUD, preclinical studies demonstrate that changes in epigenetic mechanisms can functionally impact alcohol-associated behaviors. While many studies support a therapeutic potential for targeting epigenetic enzymes, more research is needed to fully understand their role in AUD. Identification of brain circuits underlying alcohol-associated behaviors has made major advances in recent years. However, there are very few studies that investigate how epigenetic mechanisms can affect these circuits or impact the neuronal ensembles that promote alcohol-associated behaviors. Studies that focus on the role of circuit-specific and cell-specific epigenetic changes for clinically relevant alcohol behaviors may provide new insights on the functional role of epigenetic processes in AUD.

DNA methylation signatures of childhood trauma predict psychiatric disorders and other adverse outcomes 17 years after exposure

Childhood trauma is robustly linked to a broad range of adverse outcomes with consequences persisting far into adulthood. We conducted a prospective longitudinal study to predict psychiatric disorders and other adverse outcomes from trauma-related methylation changes 16.9 years after trauma exposure in childhood. Methylation was assayed using a sequencing-based approach that provides near-complete coverage of all 28 million sites in the blood methylome. Methylation data involved 673 assays from 489 participants aged 13.6 years (SD = 1.9) with outcomes measures collected at age 30.4 (SD = 2.26). For a subset of 303 participants we also generated methylation data in adulthood. Trauma-related methylation risk scores (MRSs) significantly predicted adult depression, externalizing problems, nicotine dependence, alcohol use disorder, serious medical problems, social problems and poverty. The predictive power of the MRSs was higher than that of reported trauma and could not be explained by the reported trauma, correlations with demographic variables, or a continuity of the predicted health problems from childhood to adulthood. Rather than measuring the occurrence of traumatic events, the MRSs seemed to capture the subject-specific impact of trauma. The majority of predictive sites did not remain associated with the outcomes suggesting the signatures of trauma do not become biologically embedded in the blood methylome. Instead, the long-term effects of trauma therefore seemed more consistent with a developmental mechanism where the initial subject-specific impacts of trauma are magnified over time. The MRSs have the potential to be a novel clinical biomarker for the assessment of trauma-related health risks.

Invertebrate methylomes provide insight into mechanisms of environmental tolerance and reveal methodological biases

There is a growing focus on the role of DNA methylation in the ability of marine invertebrates to rapidly respond to changing environmental factors and anthropogenic impacts. However, genome-wide DNA methylation studies in nonmodel organisms are currently hampered by a limited understanding of methodological biases. Here, we compare three methods for quantifying DNA methylation at single base-pair resolution-whole genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS), and methyl-CpG binding domain bisulfite sequencing (MBDBS)-using multiple individuals from two reef-building coral species with contrasting environmental sensitivity. All methods reveal substantially greater methylation in Montipora capitata (11.4%) than the more sensitive Pocillopora acuta (2.9%). The majority of CpG methylation in both species occurs in gene bodies and flanking regions. In both species, MBDBS has the greatest capacity for detecting CpGs in coding regions at our sequencing depth, but MBDBS may be influenced by intrasample methylation heterogeneity. RRBS yields robust information for specific loci albeit without enrichment of any particular genome feature and with significantly reduced genome coverage. Relative genome size strongly influences the number and location of CpGs detected by each method when sequencing depth is limited, illuminating nuances in cross-species comparisons. As genome-wide methylation differences, supported by data across bisulfite sequencing methods, may contribute to environmental sensitivity phenotypes in critical marine invertebrate taxa, these data provide a genomic resource for investigating the functional role of DNA methylation in environmental tolerance.

The Detection of Cancer Epigenetic Traces in Cell-Free DNA

Nucleic acid fragments found in blood circulation originate mostly from dying cells and carry signs pointing to specific features of the parental cell types. Deciphering these clues may be transformative for numerous research and clinical applications but strongly depends on the development and implementation of robust analytical methods. Remarkable progress has been achieved in the reliable detection of sequence alterations in cell-free DNA while decoding epigenetic information from methylation and fragmentation patterns requires more sophisticated approaches. This review discusses the currently available strategies for detecting and analyzing the epigenetic marks in the liquid biopsies.

Body weight and high-fat diet are associated with epigenetic aging in female members of the BXD murine family

DNA methylation (DNAm) is shaped by genetic and environmental factors and modulated by aging. Here, we examine interrelations between epigenetic aging, body weight (BW), and life span in 12 isogenic strains from the BXD family of mice that exhibit over twofold variation in longevity. Genome-wide DNAm was assayed in 70 liver specimens from predominantly female cases, 6-25 months old, that were maintained on normal chow or high-fat diet (HFD). We defined subsets of CpG regions associated with age, BW at young adulthood, and strain-by-diet-dependent life span. These age-associated differentially methylated CpG regions (age-DMRs) featured distinct genomic characteristics, with DNAm gains over time occurring in sites such as promoters and exons that have high CpG density and low average methylation. CpG regions associated with BW were enriched in introns, tended to have lower methylation in mice with higher BW, and were inversely correlated with gene expression (i.e., higher mRNA levels in mice with higher BW). CpG regions associated with life span were linked to genes involved in life span modulation, including the telomerase reverse transcriptase gene, Tert, which had both lower methylation and higher expression in long-lived strains. An epigenetic clock defined from age-DMRs revealed accelerated aging in mice belonging to strains with shorter life spans. Both higher BW and the HFD were associated with accelerated epigenetic aging. Our results highlight the age-accelerating effect of heavier BW. Furthermore, we demonstrate that the measure of epigenetic aging derived from age-DMRs can predict genotype and diet-induced differences in life span among female BXD members.

Translational Opportunities for Microfluidic Technologies to Enable Precision Epigenomics

Personalizing health care by taking genetic, environmental, and lifestyle factors into account is central to modern medicine. The crucial and pervasive roles epigenetic factors play in shaping gene-environment interactions are now well recognized. However, identifying robust epigenetic biomarkers and translating them to clinical tests has been difficult due in part to limitations of available platforms to detect epigenetic features genome-wide (epigenomic assays). This Feature introduces several important prospects for precision epigenomics, highlights capabilities and limitations of current laboratory technologies, and emphasizes opportunities for microfluidic tools to facilitate translation of epigenetic analyses to the clinic, with a particular focus on methods to profile gene-associated histone modifications and their impacts on chromatin structure and gene expression.

A Practical Guide to the Measurement and Analysis of DNA Methylation

DNA methylation represents a fundamental epigenetic mark that is associated with transcriptional repression during development, maintenance of homeostasis, and disease. In addition to methylation-sensitive PCR and targeted deep-amplicon bisulfite sequencing to measure DNA methylation at defined genomic loci, numerous unsupervised techniques exist to quantify DNA methylation on a genome-wide scale, including affinity enrichment strategies and methods involving bisulfite conversion. Both affinity-enriched and bisulfite-converted DNA can serve as input material for array hybridization or sequencing using next-generation technologies. In this practical guide to the measurement and analysis of DNA methylation, the goal is to convey basic concepts in DNA methylation biology and explore genome-scale bisulfite sequencing as the current gold standard for assessment of DNA methylation. Bisulfite conversion chemistry and library preparation are discussed in addition to a bioinformatics approach to quality assessment, trimming, alignment, and methylation calling of individual cytosine residues. Bisulfite-converted DNA presents challenges for standard next-generation sequencing library preparation protocols and data-processing pipelines, but these challenges can be met with elegant solutions that leverage the power of high-performance computing systems. Quantification of DNA methylation, data visualization, statistical approaches to compare DNA methylation between sample groups, and examples of integrating DNA methylation data with other -omics data sets are also discussed. The reader is encouraged to use this article as a foundation to pursue advanced topics in DNA methylation measurement and data analysis, particularly the application of bioinformatics and computational biology principles to generate a deeper understanding of mechanisms linking DNA methylation to cellular function.

The DNA hypermethylation phenotype of colorectal cancer liver metastases resembles that of the primary colorectal cancers

BACKGROUND

Identifying molecular differences between primary and metastatic colorectal cancers-now possible with the aid of omics technologies-can improve our understanding of the biological mechanisms of cancer progression and facilitate the discovery of novel treatments for late-stage cancer. We compared the DNA methylomes of primary colorectal cancers (CRCs) and CRC metastases to the liver. Laser microdissection was used to obtain epithelial tissue (10 to 25 × 10⁶ μm²) from sections of fresh-frozen samples of primary CRCs (n = 6), CRC liver metastases (n = 12), and normal colon mucosa (n = 3). DNA extracted from tissues was enriched for methylated sequences with a methylCpG binding domain (MBD) polypeptide-based protocol and subjected to deep sequencing. The performance of this protocol was compared with that of targeted enrichment for bisulfite sequencing used in a previous study of ours.

RESULTS

MBD enrichment captured a total of 322,551 genomic regions (249.5 Mb or ~ 7.8% of the human genome), which included over seven million CpG sites. A few of these regions were differentially methylated at an expected false discovery rate (FDR) of 5% in neoplastic tissues (primaries: 0.67%, i.e., 2155 regions containing 279,441 CpG sites; liver metastases: 1%, i.e., 3223 regions containing 312,723 CpG sites) as compared with normal mucosa samples. Most of the differentially methylated regions (DMRs; 94% in primaries; 70% in metastases) were hypermethylated, and almost 80% of these (1882 of 2396) were present in both lesion types. At 5% FDR, no DMRs were detected in liver metastases vs. primary CRC. However, short regions of low-magnitude hypomethylation were frequent in metastases but rare in primaries. Hypermethylated DMRs were far more abundant in sequences classified as intragenic, gene-regulatory, or CpG shelves-shores-island segments, whereas hypomethylated DMRs were equally represented in extragenic (mainly, open-sea) and intragenic (mainly, gene bodies) sequences of the genome. Compared with targeted enrichment, MBD capture provided a better picture of the extension of CRC-associated DNA hypermethylation but was less powerful for identifying hypomethylation.

CONCLUSIONS

Our findings demonstrate that the hypermethylation phenotype in CRC liver metastases remains similar to that of the primary tumor, whereas CRC-associated DNA hypomethylation probably undergoes further progression after the cancer cells have migrated to the liver.

A model of pulldown alignments from SssI-treated DNA improves DNA methylation prediction

Background

Protein pulldown using Methyl-CpG binding domain (MBD) proteins followed by high-throughput sequencing is a common method to determine DNA methylation. Algorithms have been developed to estimate absolute methylation level from read coverage generated by affinity enrichment-based techniques, but the most accurate one for MBD-seq data requires additional data from an SssI-treated Control experiment.

Results

Using our previous characterizations of Methyl-CpG/MBD2 binding in the context of an MBD pulldown experiment, we build a model of expected MBD pulldown reads as drawn from SssI-treated DNA. We use the program BayMeth to evaluate the effectiveness of this model by substituting calculated SssI Control data for the observed SssI Control data. By comparing methylation predictions against those from an RRBS data set, we find that BayMeth run with our modeled SssI Control data performs better than BayMeth run with observed SssI Control data, on both 100 bp and 10 bp windows. Adapting the model to an external data set solely by changing the average fragment length, our calculated data still informs the BayMeth program to a similar level as observed data in predicting methylation state on a pulldown data set with matching WGBS estimates.

Conclusion

In both internal and external MBD pulldown data sets tested in this study, BayMeth used with our modeled pulldown coverage performs better than BayMeth run without the inclusion of any estimate of SssI Control pulldown, and is comparable to – and in some cases better than – using observed SssI Control data with the BayMeth program. Thus, our MBD pulldown alignment model can improve methylation predictions without the need to perform additional control experiments.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3011-2) contains supplementary material, which is available to authorized users.

DNA methylation as a transcriptional regulator of the immune system

DNA methylation is a dynamic epigenetic modification with a prominent role in determining mammalian cell development, lineage identity, and transcriptional regulation. Primarily linked to gene silencing, novel technologies have expanded the ability to measure DNA methylation on a genome-wide scale and uncover context-dependent regulatory roles. The immune system is a prototypic model for studying how DNA methylation patterning modulates cell type- and stimulus-specific transcriptional programs. Preservation of host defense and organ homeostasis depends on fine-tuned epigenetic mechanisms controlling myeloid and lymphoid cell differentiation and function, which shape innate and adaptive immune responses. Dysregulation of these processes can lead to human immune system pathology as seen in blood malignancies, infections, and autoimmune diseases. Identification of distinct epigenotypes linked to pathogenesis carries the potential to validate therapeutic targets in disease prevention and management.