Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
May 6th, 2022
The present study describes the workflow to manage DNA methylation data obtained by microarray technologies. The protocol demonstrates steps from sample preparation to data analysis. All procedures are described in detail, and the video shows the significant steps.
Large scale omics technologies are being used more and more in studies focused on obesity. Epigenetics can be a link between the exposure and health outcomes. This type of study generates a huge amount of data.
Given this, it's important to standardize the protocols in order to make the data technically comparable. In this study, we are going to propose a pipeline in order to obtain and analyze DNA methylation data. The same protocol can be applied for both 400K and epic versions.
Day one:Bisulfite treatment. Start by denaturing genomic DNA, then add the conversion reagents. It is necessary to follow the recommendations of the kit.
And treat the denaturing DNA with bisphosphate. Then incubate the samples in a thermal cycler. Perform the washing steps using the washing buffer.
Day two:Amplification following the methylation assay, manual protocol. Preheat the hybridization oven at 37 degrees Celsius and allow the temperature to equilibrate. Disperse 20 microliters of MA1 into the wells of the plate.
Transfer four microliters of the DNA to the corresponding wells on the plate. Disperse four microliters of sodium hydroxide solution into the plate wells. Seal the plate with a plastic seal.
Vortex the plate to mix the reagents with samples. Incubate for 10 minutes at room temperature. Disperse 68 microliters of RPM into each well, and then 75 microliters of MSM without removing the previously solution.
Use a new seal to cover the plate. Vortex the plate for one minute. Incubate in the hybridization oven for 20 to 24 hours at 37 degrees Celsius.
Day three:Hybridization following the methylation assay, manual protocol. Preheat the block by inserting the plate at 37 degrees Celsius. Carefully remove the plate from the hybridization oven.
Pulse centrifuge the plate. Remove the seal from the plate. Add 50 microliters of FMS to each sample container.
Vortex the plate for one minute. Centrifuge the plate needs. Then place the sealed plate on the heating block at 37 degrees Celsius for one hour.
Add 100 microliters of PM1 to each well containing samples. Seal the plate again. Vortex the plate for one minute.
Incubate at 37 degrees Celsius for five minutes. Then pulse in the centrifuge for one minute, then add 300 microliters of 100%2-propanol to each well with sample. Seal the plate again.
Mix all contents by inverting the plate at least 10 times. Incubate at four degrees Celsius for 30 minutes, and then centrifuge at four degrees Celsius for 20 minutes. Remove the seal from the plate.
Quickly invert the plate in an appropriate place, discarding the supernatant. Tap firmly several times until you've noticed that all wells are free of liquid. At room temperature, leave the plate upside down and uncovered for one hour.
After drying all the liquid, it is necessary to see blue pallets at the bottom of the wells. Then add 46 microliters of RA1 to each well. Apply the heat seal to the plate.
Hold tight to perform the sealing evenly. Put the plate in the hybridization oven at 48 degrees Celsius for one hour, then vortex for one minute. Pulse in the centrifuge, and heat the plate at 95 degrees Celsius for one hour.
Prepare the BeadChip Hyb Chambers together. In this next step, disperse 400 microliters of PB2 into the reservoirs in the Hyb Chambers. After filling the Hyb Chamber reservoirs with PB2, put the lid on immediately.
Carefully load each sample from the plate into the sample entry of the microarray. Load the Hyb Chamber inserts containing the microarrays into the Hyb Chamber. Close the Hyb Chamber crosswise to avoid possible shifting of the Hyb Chamber.
Day four:Staining following the methylation assay, manual protocol. After the night incubation, remove all the microarrays from the inserts. And wash the microarrays slowly and lightly, a total of 10 times, up and down.
Move the microarrays to PB1 container number two and repeat 10 times, up and down. Place the frames of the Flow Chamber in the correct position, and then each microarray. Use a transparent spacer at the top of each one.
The alignment bar needs to be positioned on the alignment accessory. A glass back plate needs to be placed on top of the spacer. Then attach metal clamps to the Flow Chambers.
Use scissors to trim the ends of the Flow Chamber spacers. Place the Flow Chamber with the microarray into the chamber rack. Pipette 150 microliters of RA1.
Incubate for 30 minutes and repeat five times. Pipette 450 microliters of XC1, and incubate for 10 minutes. Pipette 450 microliters of XC2 and incubate for 10 minutes.
Pipette 200 microliters of TEM. Incubate for 15 minutes. Pipette 450 microliters of 95%formamide.
Incubate for one minute, repeating twice. Incubate for five minutes. Pipette 450 microliters of XC3.
Incubate for one minute and repeat. In this step, the following reagents will be dispensed, 250 microliters of STM, 450 microliters of XC3, and 250 microliters of ATM. Do the following repetition scheme.
After all the repeats and incubations, place the microarrays on a standing rack and dip them in the wash container. Moving slowly and lightly with up and down movements, 10 times. Dry the microarrays using the vacuum desiccator for 50 to 55 minutes.
Once the microarrays are dried, proceed to image the microarray with the scan. In this image, we can see all the protocols used, from choosing the participants to processing the IDAT files obtained on the last day of the methylation experiment. The files were transferred to the computer where the bioinformatic analysis were performed.
Analysis were processed using R Studio and the Bioconductor ChAMP package. Make sure you have at least eight gigabytes of RAM on your computer. Other bioinformatic analysis, such as gene enrichment were performed to better present the data to the reader.
In this table, we can observe the two groups used in this study, obese and non obese. There was a difference between groups for variables, body mass index, abdominal circumference, fat mass in kilograms, and fat mass in percent. Observing the scheme presented in this figure, we were able to understand that the proposed protocol was adequate for our data.
And after the bioinformatic analysis, a total of 409, 887 probes were presented after the filter was performed. The density plot revealed that all samples had similar densities of beta distribution. No samples were excluded based on these analysis.
The singular value decomposition analysis of the normalized data revealed that BMI, double C, and FM significantly influenced DNA methylation data variability. Cell type estimation revealed that both natural killer cells, NK and B cells were higher in obese women. DNA methylation levels between obese and non obese women were different before and after cell type correction.
Before correction, 43, 463 different methylation positions were observed. And after that, 3, 329 CPGs remained significantly. A total of 162 CPGs were hypomethylated, and 576 were hypermethylated in obese compared to non obese.
The data is available in the GEO database under registration code GSE166611. We present the CPG sites that were associated with the specific characteristics of the participants which were observed in SVD. For fat mass, 13, 222 CPG sites were found.
There were 6, 159 fat mass related CPGs in the promoter region. 470 hypomethylated and 94 hypermethylated. The respective genes of the associated sites were enriched and are now shown.
We observed that the proposed protocol is capable to identify within your methylations patterns, and it's right to relate within your methylations. Our result confirms that an obesogenic lifestyle can promote epigenetic changes in human DNA.
Overview
This study presents a detailed workflow for managing DNA methylation data obtained through microarray technologies. It outlines the entire process from sample preparation to data analysis, ensuring that protocols are standardized for technical comparability.
Key Study Components
Area of Science
- Epigenetics
- DNA Methylation
- Microarray Technologies
Background
- Large scale omics technologies are increasingly used in obesity studies.
- Epigenetics may link exposure to health outcomes.
- Standardized protocols are essential for data comparability.
- This study proposes a pipeline for DNA methylation data analysis.
Purpose of Study
- To develop a standardized protocol for DNA methylation analysis.
- To demonstrate the workflow from sample preparation to data analysis.
- To ensure technical comparability of large datasets.
Methods Used
- Bisulfite treatment of genomic DNA.
- Amplification and hybridization protocols for methylation assays.
- Staining and imaging of microarrays.
- Bioinformatic analysis using R Studio and Bioconductor ChAMP package.
Main Results
- Successful implementation of a four-day protocol for DNA methylation analysis.
- Standardized procedures allow for reproducible results.
- Data analysis revealed differences between obese and non-obese groups.
- Bioinformatic tools provided insights into gene enrichment.
Conclusions
- The proposed workflow enhances the reliability of DNA methylation studies.
- Standardization is crucial for comparing large datasets in epigenetic research.
- Future studies can build upon this protocol for further insights into obesity and health outcomes.
Frequently Asked Questions
Chapters in this video
0:03
Introduction
0:43
Day 1: Bisulfite Treatment
1:21
Day 2: Amplification - Methylation Assay, Manual Protocol
2:52
Day 3: Hybridization - Methylation Assay, Manual Protocol
6:39
Day 4: Staining - Methylation Assay, Manual Protocol
10:48
Representative Results
14:34
Conclusion
