The genomic sequence is not the sole determinant of biological activity; factors such as environmental stress and lifestyle choices can regulate gene expression through epigenetic modifications, such as DNA methylation and RNA methylation, without altering the underlying DNA sequence. Recent studies have indicated that aberrant N6-methyladenosine (m6A) may contribute to Alzheimer's disease pathology by influencing the metabolism of Tau-associated mRNA and synaptic function (Cell, 2020). This article concentrates on the core techniques and applications within epigenetics, detailing the technological evolution from DNA methylation detection to dynamic tracking of RNA modifications, and exploring their potential in early disease screening and precise interventions. The following sections incorporate case studies to illustrate how multi-omics integration addresses complex phenotypes that traditional genetics often struggles to explain.
Exploring the basis of epigenetics
1. Interpreting the genetic code beyond the gene sequence
Epigenetics has unraveled the mysteries of genetic regulation beyond DNA sequences. Environmental responsiveness is one of the key characteristics. Take the Dutch famine as an example; women who were pregnant during the famine had offspring with unique health changes. Research found that certain gene expression patterns in these offspring were affected, and this impact persisted even after the famine ended. This indicates that environmental factors can regulate gene expression without altering DNA sequences, thereby influencing an individuals physiological traits, and this influence can even be passed on to the next generation.
Transgenerational inheritance is equally striking, with transposon silencing being a prime example. Transposons are mobile elements in the genome that can interfere with gene function. In some organisms, epigenetic mechanisms can keep transposons silent, and this state of silence can be passed on to offspring. This demonstrates that epigenetic information is transmitted between generations, which is crucial for maintaining genomic stability and biological genetic traits, highlighting that inheritance is not solely determined by DNA sequences.
The four major epigenetic layers in Eukaryotic genomes (Mahya Mehrmohamadi et al,.2021)
Purpose and Importance of acRIP Sequencing
2. Analysis of the core control mechanism
In epigenetics, DNA methylation, RNA modifications, and non-coding RNAs form a complex and orderly regulatory hierarchy. DNA methylation primarily occurs at CpG islands, playing a crucial role in gene expression regulation. When the CpG island of tumor suppressor genes becomes highly methylated, gene expression is suppressed and fails to function normally as an oncogene, leading to tumor development. This clearly illustrates the mechanism by which DNA methylation operates in gene silencing.
M6A and m5C in RNA modification have significant effects on mRNA metabolism. M6A modification can regulate the stability of mRNA, translation efficiency and other processes. In vaccine development, by m6A modification of mRNA, the stability of vaccine can be improved and the immune effect can be enhanced.
The lncRNA in non-coding RNA plays a crucial role in the three-dimensional reconstitution of chromatin. It can interact with chromatin, altering its spatial structure and influencing gene expression regulation. These core regulatory mechanisms work together to form an epigenetic regulatory network, finely controlling various physiological processes within organisms, which is essential for maintaining normal cellular functions and the health of the organism.
3. Epigenetic and biological function correlation
Epigenetic networks play an indispensable biological role in cell fate determination and disease mechanisms. During embryo reprogramming, methylation erasure plays a crucial role. For example, the activation of key genes like Oct4 and Nanog requires the removal of methylation marks in their associated regions. This allows cells to escape their original differentiation state and regain pluripotency, laying the foundation for normal embryonic development and determining the future direction of cell differentiation.
In terms of disease mechanisms, taking Alzheimers disease as an example, m6A dysregulation is closely associated with Tau protein aggregation. Abnormal m6A modifications can affect the metabolic processes of related mRNA, leading to abnormal expression and processing of Tau protein, which in turn triggers Tau protein aggregation and the formation of neurofibrillary tangles, one of the key pathological features of Alzheimers disease. This indicates that epigenetic abnormalities play a crucial role in the development and progression of diseases. A deeper investigation into the relationship between epigenetics and biological functions can help us better understand the pathogenesis of diseases and provide theoretical basis for developing targeted treatments.
Deep analysis of DNA methylation sequencing technology
1. Principles and design of classical sequencing technology
| technology |
principle |
superiority |
limit |
| WGBS |
Heavy sulfite conversion + whole genome sequencing. Heavy sulfite converts unmethylated cytosine (C) to uracil (U), while methylated cytosine remains unchanged, and whole genome sequencing can determine DNA methylation status at the single base level |
Single base resolution can fully cover the whole genome and accurately detect the methylation of each CpG site |
The cost is high, the demand for DNA samples is large, and the experimental operation process is relatively complex |
| RRBS/XRBS |
Enzymatic enrichment of CpG region + sequencing. Genomes are enzymatically digested with specific enzymes to enrich regions containing CpG islands, followed by sequencing |
The cost is relatively low and suitable for clinical sample testing. It can reduce the sequencing amount to a certain extent and focus on the key CpG region |
The coverage is limited to detect the CpG island near the enzyme cleavage site, and the whole genome cannot be fully detected |
| oxBS-seq |
Oxidation of 5hmC distinguishes 5mC/5hmC. First, 5hmC is oxidized to 5fC, and then metabisulfite treatment is performed to achieve specific detection of 5mC and 5hmC |
It can specifically detect hydroxymethylation, which provides a powerful tool for studying the role of 5hmC in biological processes |
The operation is more complex, the experimental steps are more, and the experimental technology is higher |
These classic techniques have their own characteristics, providing a variety of options for epigenetic research, which can be reasonably selected according to the needs of researchers and sample conditions.
Comparison of sequencing-based methods for genome-wide methylation analysis. (Daniel B Lipka et al,.2014)
2. Breakthrough in cutting-edge sequencing technology
TAPS/EM-seq is a cutting-edge technology that innovatively replaces enzymatic methods with heavy sulfite treatment. Traditional heavy sulfite treatment can damage DNA, affecting its integrity. In contrast, TAPS/EM-seq detects methylation through enzymatic methods, effectively preserving DNA integrity. This technique has significant advantages in early cancer screening, particularly in the detection of cfDNA (circulating free DNA). Given the low concentration and susceptibility to degradation of cfDNA, TAPS/EM-seq better adapts to these characteristics, enhancing the accuracy and reliability of the tests.
Single-cell scWGBS utilizes MDA amplification technology to detect methylation of single-cell DNA. In embryonic development studies, it can elucidate cellular heterogeneity during the process of embryo development. Embryonic development is a complex process, with varying methylation states among different cells. Single-cell scWGBS can delve into the single-cell level, revealing these differences and helping us better understand the mechanisms of gene expression regulation during embryonic development, providing new perspectives and methods for developmental biology research.
3. Data analysis and biological significance mining
The analysis process for DNA methylation sequencing data is rigorous and critical. First, quality control of the raw data is conducted using tools like FastQC to evaluate the quality of the sequencing data, checking for completeness, sequencing error rates, and other metrics to ensure the reliability of subsequent analyses. Next, alignment is performed using software such as Bismark to compare the sequencing data with the reference genome, determining the position of each sequence within the genome. Then, DMR (Differential Methylation Region) identification is carried out using tools like DSS to pinpoint regions where there are significant differences in methylation levels between different samples.
Advanced analytical methods further uncover the biological significance of data. For example, constructing a methylation-expression co-regulation network through WGCNA can reveal the relationship between methylation and gene expression, identifying which genes are regulated by methylation. Cross-species conservation analysis helps identify conserved regions and evolutionary features in methylation regulation across different species, providing clues for a deeper understanding of epigenetic evolution mechanisms and advancing research in epigenetics across multiple fields.
Comprehensive interpretation of RNA methylation sequencing technology
1. Core sequencing technology and experimental optimization strategy
| technology |
resolution ratio |
sample capacity |
applicable scene |
| MeRIP-seq |
~100 nt |
1 - 5 μg RNA |
It is suitable for full transcriptome m6A screening, can identify m6A modification sites in a large range, comprehensively understand the distribution of m6A in the transcriptome, and provide basic data for further research on the function of m6A modification |
| acRIP-seq |
50 - 100 nt |
500 ng RNA |
With the enrichment of highly specific antibodies, it can accurately locate specific RNA methylation modifications, which is suitable for in-depth research on specific modification types and has advantages in exploring methylation modifications of some key genes or specific functional regions |
| RNA-BS |
Single base resolution |
It varies from experiment to experiment |
The treatment of heavy sulfite has played an important role in the screening of bladder cancer markers and other studies. It can determine the specific location of m5C modification at the single base level, which helps to discover new biomarkers |
| Nm-Mut-seq |
It depends on the specific positioning |
It varies depending on the experimental requirements |
Mutagenic reverse transcriptase is located at 2-O-methylation, which has unique value in mRNA stability studies. By using special enzymes to locate specific methylations, it provides a powerful means for studying the regulatory mechanism of mRNA stability |
| Third generation sequencing (real-time detection of nanopores) |
Real-time dynamic detection |
Sample size requirements are relatively flexible |
No fragmentation/enrichment is required, and dynamic modification can be detected in real time. It has irreplaceable advantages for studying the dynamic change process of RNA modification, such as the real-time change of RNA modification in different physiological states of cells |
These core technologies have their own advantages and disadvantages. Researchers need to reasonably select and optimize the experimental scheme according to the research purpose and sample conditions, so as to obtain accurate and valuable research results.
The primary types and mechanisms of RNA methylation. (Yutong Xia et al,.2024)
2. Functional validation and multi-omics integration pathway
Targeted editing of m6A sites using CRISPR-Cas13 is an effective method to verify RNA methylation functions. Taking the knockdown of METTL3 as an example, METTL3 is a key enzyme involved in m6A modification. After knocking down METTL3 using CRISPR-Cas13 technology, changes in the m6A modification levels of related mRNA can be observed, which in turn affects processes such as mRNA stability and translation efficiency. This directly validates the important role of METTL3 in m6A modification and related biological processes.
Combining mRNA sequencing to construct modification-expression regulation networks can provide deep insights into the relationship between RNA methylation and gene expression. For instance, in cancer research, it has been found that the m5C modification is closely related to the translation of oncogenes. By simultaneously performing RNA methylation sequencing and mRNA sequencing, data analysis revealed that certain oncogenes have higher levels of m5C modification on their mRNA, and this modification promotes the translation process of oncogenes, leading to increased expression of relevant proteins in cancer cells and driving tumor progression. This multi-omics integration approach offers a more comprehensive perspective for understanding disease mechanisms.
3. Key points of RNA methylation experiment control
Sample quality: RNA integrity is critical, RIN (RNA Integrity Number) value should be greater than or equal to 7.5, and RNA degradation should be avoided. High quality RNA samples are the basis for ensuring the accuracy of experimental results. Degraded RNA may lead to sequencing data deviation and affect the accurate detection of methylation modification.
Database optimization: The re-sulfite treatment efficiency should be>99% to avoid false positive results. If the treatment efficiency is not up to standard, unmethylated cytosine may not be fully converted, which may be misjudged as methylated and interfere with the experimental conclusion.
Data analysis: Use a dedicated process (such as BS-RNA) to process the converted sequences to ensure the accuracy and consistency of data processing. The dedicated process is designed for the characteristics of RNA methylation sequencing data, which can effectively identify and analyze methylation sites.
Multi-omics integration: Combining mRNA expression profiles to verify functions, such as in cancer research, by analyzing the association between m5C and gene expression, we can gain a deeper understanding of the role of RNA methylation in disease development, providing more comprehensive information for research.
Technical selection and full process solution guide
1. Technical matching according to research objectives
| Research objectives |
DNA methylation technology |
RNA methylation technology |
| Whole genome screening |
WGBS/TAPS |
MeRIP-seq/Nanopore |
| Development of clinical markers |
RRBS/XRBS |
RNA-BS (m5C single base detection) |
| Analysis of single cell heterogeneity |
scWGBS/EM-seq |
scCOOL-seq (multimodal omics) |
| Dynamic modification tracking |
oxBS-seq |
Nanopore real-time sequencing |
With this table, researchers can quickly match the appropriate technology based on their research objectives, understand the approximate delivery cycle, and plan the research process reasonably.
2. Key links of experimental quality control are controlled
DNA methylation: The conversion efficiency of methanesulfonate should be at least 99%, and Lambda DNA can be used as a control for monitoring. Insufficient conversion efficiency will lead to misjudgment of methylation status and affect the accuracy of experimental results. At the same time, attention should be paid to the standardization of experimental operation to avoid contamination and loss of DNA samples.
RNA modification: antibody specificity verification is the key. Knockout cells are used as negative controls to ensure that the antibody only recognizes the target modification and reduces the false positive results caused by non-specific binding. In addition, the preservation and processing of samples should be appropriate to prevent RNA degradation from affecting the experimental results.
Bioinformatics analysis: Standardized processes, such as the Yigene BS-RNA analysis pipeline, are adopted to ensure the accuracy and repeatability of data analysis. Parameters in the analysis process should be set reasonably, and results should be strictly evaluated for quality to avoid incorrect conclusions due to data analysis errors.
3. Benchmark case and data display analysis
In liver cancer research, XRBS technology has been used to identify liver cancer-specific low-methylation regions. The methylated heat map intuitively illustrates the differences in methylation levels across different samples, with darker colors representing higher methylation. This clearly shows the distinct differences between liver cancer and normal samples in certain areas. The ROC curve is used to evaluate the accuracy of this technique for diagnosing liver cancer, with an AUC (area under the curve) value of 0.92, indicating its high diagnostic efficacy. Survival analysis compares the survival conditions of patients with different methylation statuses, revealing the relationship between methylation and patient prognosis.
The acRIP-seq technology plays a crucial role in the screening of m6A inhibitor targets. The peak distribution map illustrates the distribution of m6A modification sites across the genome, aiding in identifying key modification regions. Motif enrichment analysis identifies specific sequence patterns enriched near these modification sites, which helps understand the regulatory mechanisms of m6A modifications. The pathway network diagram presents the signaling pathways involved in m6A modifications, providing direction for further research. A 50% reduction in IC50 indicates that the selected inhibitor targets have good inhibitory effects. These data lay the foundation for further drug development.
Exploration of multi-omics integration and epigenetic mapping
1. Overview of whole genome epigenetic mapping technology
Whole-genome epigenetic mapping technology provides a powerful tool for in-depth research in epigenetics. The ATAC-seq technique in chromatin accessibility analysis works by utilizing the ability of transposases to insert into open chromatin regions, introducing transposon complexes carrying sequencing tags into cells. Through sequencing, it identifies open chromatin regions to understand which genes may be active. DNase-seq, on the other hand, uses DNase I enzyme to cut genomic DNA, prioritizing the cutting of DNA in open chromatin regions, and then determining the location of these regions through sequencing.
In the joint analysis of histone modifications and three-dimensional genomes, ChIP-seq technology enriches DNA fragments bound to specific histone modifications using antibodies, and then sequences these modifications to determine their distribution across the genome. Hi-C technology, on the other hand, employs high-throughput sequencing techniques to analyze spatial interactions between DNA segments within the genome, revealing the three-dimensional structure of chromatin. These technologies work together to help create a comprehensive epigenetic map, providing multidimensional information for understanding gene expression regulation.
2. Data analysis and functional analysis path
Differential methylation regions (DMRs) and differential expression genes (DEGs) association analysis is a crucial method for interpreting epigenetic data. For instance, in cancer research, comparing DNA methylation sequencing and transcriptome sequencing data from tumor and normal tissues reveals that certain gene promoter regions exhibit DMRs, and these genes show differential expression in tumor tissues. Further analysis indicates that high methylation in promoter regions suppresses the expression of related genes, which may be involved in important biological processes such as cell proliferation and apoptosis. Their abnormal expression is closely associated with tumor development and progression.
Epigenetic network modeling involves constructing complex regulatory networks. Taking gene imprinting regulation as an example, insulators interact with lncRNA. Through epigenetic network modeling, their regulatory relationship can be clearly demonstrated. Insulators prevent abnormal interactions between enhancers and promoters, while lncRNA recruits relevant epigenetic regulatory factors. Together, they maintain precise gene expression regulation. This modeling helps deepen our understanding of the intricate mechanisms of epigenetic regulation.
3. Advances in single cell and spatial epigenomics
Single-cell methylated sequencing (scWGBS) plays a crucial role in revealing cellular heterogeneity. In the early stages of embryonic development, the fate decisions of different cells are not yet fully determined. Through scWGBS, the DNA methylation status of each cell can be precisely measured. Research has found that even within groups of cells with similar morphology, there are significant differences in methylation patterns. These differences may determine the future differentiation direction of cells, providing evidence at the single-cell level for understanding the mechanisms of cell fate determination.
Spatial transcriptomics and epigenetic modification co-localization techniques offer new perspectives for studying interactions and functions between cells within tissues. In neuroscience research, this technique can determine the spatial distribution of epigenetic modifications in different neuronal cells and their relationship with gene expression. Through this technology, it is possible to understand the epigenetic characteristics of neurons at specific spatial locations, revealing the spatial specificity of epigenetic regulation during neural development and functional maintenance. This provides spatial dimension information for the study of neurological diseases.
Featured Techniques and Services
Challenges and future prospects of epigenetics development
1. Discussion on technical bottleneck and countermeasures
Epigenetic techniques face numerous bottlenecks in their development. Detecting low-abundance modifications is a significant challenge; some rare modifications are present at extremely low levels within cells, and the sensitivity of current detection methods is limited, making it difficult to accurately identify and quantify these modifications. This has slowed progress in studying the functions of these modifications. Dynamic tracking is also challenging, as epigenetic modifications within cells are in constant flux. Traditional techniques struggle to monitor these changes in real-time and continuously, which limits our understanding of the dynamic processes of epigenetic regulation.
In response to these issues, researchers have actively explored coping strategies. The emergence of nanopore sequencing signal enhancement algorithms (such as EpiNano 2.0) has brought hope for detecting low-abundance modifications. This algorithm improves the ability of nanopore sequencing to capture weak signals by optimizing signal processing, thereby enhancing the sensitivity of detecting low-abundance modifications. For dynamic tracking challenges, real-time imaging techniques in living cells (such as the CRISPR-Sirius system) provide effective solutions. It can observe the dynamic changes in epigenetic modifications within cells in real time without disrupting their physiological state, offering powerful tools for in-depth research on the dynamic mechanisms of epigenetic regulation.
2. Frontier technology layout and clinical transformation trend
The cutting-edge technology layout in the field of epigenetics is moving towards AI-driven and clinical translation directions. In terms of AI-driven approaches, tools like DeepMethyl demonstrate strong predictive capabilities. By analyzing large amounts of epigenetic data using deep learning algorithms, they can accurately predict methylation regulatory elements with an AUC value greater than 0.9, facilitating researchers rapid identification of key regulatory regions and accelerating the progress of epigenetic research.
In terms of clinical translation, EM-seq technology has been included in the NCCN guidelines for early screening of colorectal cancer, marking a significant breakthrough in the clinical application of epigenetic techniques. This technology, with its high accuracy and stability, provides new methods for early cancer diagnosis, facilitating the transition of epigenetic techniques from the laboratory to clinical practice. These cutting-edge technological advancements not only deepen our understanding of epigenetic mechanisms but also bring new ideas and approaches to disease diagnosis, treatment, and prevention, greatly promoting industrial transformation and potentially leading to more clinical application products and services based on epigenetics.
3. Ideal epigenetic partner traits
An ideal epigenetic partner should possess multiple core advantages. Owning patented antibodies is crucial, such as the acRIP-seq patented antibody, which has a cross-reactivity rate below 5%. This ensures high specificity and accuracy in experiments, enabling precise identification of target modifications and reducing interference from non-specific binding, thus providing reliable data support for research.
The success rate of single-cell library construction is also a critical metric, with a success rate exceeding 90% (achieved through optimized MALBAC technology). This reflects the partners exceptional technical proficiency in handling single-cell samples, providing solid support for single-cell epigenetic research. Additionally, an excellent partner should offer comprehensive service commitments, covering the entire cycle from experimental design to top-tier publication chart creation. They should provide professional advice during the experimental design phase to ensure that the protocol is scientifically sound and reasonable; promptly address issues encountered during the research process; and assist in creating high-quality charts during the presentation phase, facilitating better publication and dissemination of research findings, thus fully meeting the clients research needs.
To learn more, please refer to
Overview of m6A RNA Methylation and
Overview of Sequencing Methods for RNA m6A Profiling.
References:
- Chokkalla AK, Mehta SL, Vemuganti R. Epitranscriptomic regulation by m6A RNA methylation in brain development and diseases. Journal of Cerebral Blood Flow & Metabolism. 2020;40(12):2331-2349. doi:10.1177/0271678X20960033
- Heijmans BT, Tobi EW, Stein AD, Putter H, Blauw GJ, Susser ES, Slagboom PE, Lumey LH. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Natl Acad Sci U S A. 2008 Nov 4;105(44):17046-9. DOI: 10.1073/pnas.0806560105
- Smallwood SA, Lee HJ, Angermueller C, Krueger F, Saadeh H, Peat J, Andrews SR, Stegle O, Reik W, Kelsey G. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat Methods. 2014 Aug;11(8):817-820. DOI: 10.1038/nmeth.3035
- Krueger F, Andrews SR. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics. 2011 Jun 1;27(11):1571-2. DOI: 10.1093/bioinformatics/btr167
