MethylRAD-Seq

CD Genomics is providing a novel, flexible, and scalable genome-wide DNA methylation profiling method, MethylRAD, to allow for de novo methylation analysis with extremely low DNA input.

The Introduction of MethylRAD-Seq

MethylRAD uses methylated modified dependent endonuclease, such as FspEI, MspJI, LpnPI, AspBHI, etc., to recognize cytosine methylated on DNA and cut double chains at a distance downstream of the recognition site, and if the DNA double-strand has a central symmetric methylation state, a fixed length of double-strand DNA fragment can be cut and then sequenced. DNA methylation is a heritable epigenetic mark and plays a vital role in many biological processes such as embryogenesis, cellular differentiation, X-chromosome inactivation, genomic imprinting and transposon silencing, perturbed methylation patterns are sometimes a hallmark of important human diseases. Profiling the DNA methylation landscape and its dynamics enable researchers to look deeply into key epigenetic mechanisms that modulate development and diseases. MethylRAD allows for de novo (reference-free) methylation analysis, extremely low DNA input (e.g. 200 ng) and adjustment of tag density, all of which are still unattainable for most widely used methylation profiling methods such as RRBS and MeDIP sequencing.

Advantages of Our MethylRAD-Seq Service

• Extremely low amount of input DNA required
• Adjustable tags density
• High specificity, sensitivity and reproducibility
• Allows for de novo methylation analysis
• Ideally suited for large-scale methylation profiling
• Comprehensive bioinformatics analysis
• Suitable for most species especially plant species

Applications of MethylRAD-Seq 

• Population Epigenetics
• Epigenome-Wide Association Studies (EWAS)
• Environmental Epigenetics
• Comparative Epigenomics
• Functional Genomics
• Marker Development and Crop Improvement

MethylRAD-Seq Workflow

The MethylRAD-Seq Workflow is outlined as below:

Service Specifications

	Sample Requirements DNA amount ≥ 200 ng; DNA concentration ≥ 25 ng/μl, OD260/280=1.8~2.0 Sample Type: Genomic DNA without RNA contamination and severe degradation All DNA should be RNase-treated and should show no degradation or contamination. The sample preparation protocol covers DNA isolation, purification, quantification, QC, etc. Note: Sample amounts are listed for reference only. For detailed information, please contact us with your customized requests.
Click	Sequencing Strategy Illumina HiSeq X-ten PE 150 Recommended Sequencing Depth: 30 M reads per Gb genome size
	Bioinformatics Analysis We provide multiple customized bioinformatics analyses: Removal of adapters and low-quality reads, statistics of sequencing depth and coverage Assembly and mapping the reads to reference genome Genome-wide distribution of methylation sites, annotation and statistics Distribution of methylation site on the function elements Density of methylation sites Relative quantification of DNA methylation levels DNA methylation pattern profiling Comparisons of methylation levels between different groups and analysis of methylation differential genes More data mining upon your request Note: Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Analysis Pipeline

Deliverables

• The original sequencing data
• Experimental results
• Data analysis report
• Details in MethylRAD-Seq for your writing (customization)

CD Genomics uses a simple and flexible method for genome-wide DNA methylation profiling with high specificity, sensitivity and reproducibility, enabling de novo methylation analysis with extremely low DNA input, and flexible adjustment of tag density. If you have any questions, please feel free to contact us.

Partial results are shown below:

1. What about the unique mapping ratios?

Of the mapped reads provided by MethylRAD, the unique mapping ratios were 34.5%~36.1%, which comparable to those (38–43%) reported in a WGBS study on A. thaliana, and the relatively low rate of unique mapping is to be expected as repetitive regions are usually highly methylated in plants.

2. How sensitive MethylRAD-seq can be?

At methylation levels of 20-100%, CCGG and CCWGG sites could be readily detected and the detection rates were 93.8-100%. While lower detection rates were seen at the low methylation level (less than 20%), more than 79% of the CCGG and CCWGG sites could still be detected.

An exemplary chromosomal distribution of (a) methylated CCGG sites and (b) methylated CCWGG sites detected by MethylRAD, RTR-MethylRAD and WGBS:

Fig 1. Comparison of the number of methylation sites detected by MethylRAD and WGBS. (Wang et al., 2015)

A large majority of methylated target sites detected by WGBS are also detected by MethylRAD.

3. Theoretically, MethylRAD sequences methylated fragments only, how to eliminate false positives detected?

For plant applications, it is advisable to use the chloroplast sites as internal control sites to adjust the false discovery rate of detected methylation sites to the desired level.

Reference

1. Wang S, Lv J, Zhang L, et al. MethylRAD: a simple and scalable method for genome-wide DNA methylation profiling using methylation-dependent restriction enzymes. Open biology, 2015, 5(11): 150130.

Case Study

DNA Methylation Changes and Its Associated Genes in Mulberry (Morus alba L.) Yu-711 Response to Drought Stress Using MethylRAD Sequencing

Journal: Plants

Impact factor: 3.935

Published: 12 January 2022

Background

Plants face constant biotic and abiotic challenges and adapt through molecular and morphological changes. Epigenetic regulations, including DNA methylation, play crucial roles in stress tolerance, gene regulation, and genome stability. Drought stress affects DNA methylation patterns, influencing gene expression and plant adaptation. High-throughput techniques like MethylRAD sequencing are essential for accurately assessing these changes.

Materials & Methods

Results

The authors analyzed the DNA methylation profiles of mulberry leaves under drought and control conditions, identifying more CG than CWG methylation sites. They found a slight increase in methylation levels under drought stress and noted higher frequencies of CG sites compared to CWG sites on specific chromosomes.

Figure 1. Distribution of methylation sites in different gene functional elements.

The authors found that under drought and control conditions, CG methylation sites were mostly in exons, intergenic, and intron regions, while CWG sites were mainly in intergenic and exon regions. Drought stress caused changes in the distribution of these sites across different gene components, with CG and CWG patterns remaining similar, concentrating in exons and intergenic regions.

The authors found higher DNA methylation in TSS and TTS regions compared to the gene body, with drought samples showing more methylation. They identified 413 CG and 168 CWG differential methylation sites (DMS), and 129 CG and 41 CWG differentially methylated genes (DMGs). Drought stress led to hypomethylation, suggesting it regulates gene expression during stress.

Figure 2. Distribution of methylation sites in transcription start site (TSS), gene body, and transcription termination site (TTS).

Figure 3. Differential methylation gene at CG and CWG level between EG-vs.-CK.

The authors conducted a GO enrichment analysis on genes associated with differentially methylated sites (DMS). They found 120 differentially expressed genes (DEGs) at CG sites and 43 at CWG sites, with significant enrichment in specific biological processes, cellular components, and molecular functions. Additionally, KEGG pathway analysis revealed that these DEGs are involved in various pathways, notably metabolism, plant hormone signal transduction, and RNA transport.

Figure 4. Bar chart of the top 30 GO functions of the genes where CG and CWG differential methylation sites are located.

Figure 5. The top 20 KEGG enrichment analyses of the genes where the CG and CWG differential methylation sites are located.

Conclusion

This study examined DNA methylation in mulberry Yu-711 under drought stress, revealing higher CG (37.37%) than CWG (28.81%) methylation. Methylation mainly occurs at TSS and TTS, and in exons, intergenic, introns, and downstream regions. Identified 170 DMGs and 581 DMS enriched in GO terms and pathways like plant hormone signal transduction and amino acid biosynthesis. qRT-PCR showed dynamic gene expression patterns influenced by methylation changes, highlighting its role in mulberry's response to drought stress amid climate change.

Reference

1. Ackah M, Guo L, Li S, et al. DNA methylation changes and its associated genes in mulberry (Morus alba L.) Yu-711 response to drought stress using MethylRAD sequencing. Plants, 2022, 11(2): 190.