The work is supported by CPRIT Research Training Award RP140105, as well as partially supported by US National Institutes of Health (NIH) grants R01 GM114142 and by William &#38; Ella Owens Medical Research Foundation.

All tissues are obtained following approval of the Institutional Review Board committee and when all participants consented to both molecular analyses and follow-up studies. The protocols are approved by the Human Studies Committee at University of Texas Health Science Center at San Antonio.
1. Methyl-binding DNA Capture (MBDCap)
<ol>
	<li>Sample collection and DNA isolation
	<ol>
		<li>Collect bulk tumor or normal tissue samples from patient paraffin embedded tissue samples.</li>
		<li>Use a commercial DNA mini kit to isolate genomic DNA from the paraffin embedded tissue samples according to manufacturer&#39;s protocol.</li>
		<li>Use a methylated DNA enrichment kit with the procedure described here according to manufacturer&#39;s protocol.</li>
	</ol>
	</li>
	<li>Initial bead wash 
	Note: The beads are used to couple with MBD-Biotin protein, which detects DNA methylation on the genome. Beads are usually suspended in a stock solution. Use these steps to wash off this liquid.
	<ol>
		<li>Resuspend the stock of streptavidin beads (See Materials Table) by gently pipetting up and down to obtain a homogeneous suspension. Do not mix the beads by vortexing.</li>
		<li>For one &#181;g of input DNA, add10 &#181;L of beads to a tube with 90 &#181;L of 1x Bind/Wash Buffer. Rotate for 1 min. Do not mix by vortexing.</li>
		<li>Place the tube(s) on a magnetic rack for 1 min.</li>
		<li>Remove the liquid with a pipette and discard the liquid.</li>
		<li>Add 250 &#181;L of 1x Bind/Wash Buffer to the beads and rotate for 1 min.</li>
		<li>Repeat steps 1.2.3 - 1.2.5 twice.</li>
	</ol>
	</li>
	<li>Coupling the MBD-Biotin protein to the beads
	<ol>
		<li>For 1.2 &#181;g of input DNA, add 7 &#181;L (3.5 &#181;g) of MBD-Biotin protein to each tube.</li>
		<li>Add 93 &#181;L of 1x Bind/Wash Buffer to the protein to make a final volume of 100 &#181;L.</li>
		<li>Mix the beads-protein mixture on a rotating mixer at RT&#160;for 1 h.</li>
	</ol>
	</li>
	<li>Fragmented DNA (input)
	<ol>
		<li>Sonicate DNA by adding 1.2 &#181;g of total genomic DNA in 96 &#181;L of TE&#160;buffer and 24 &#181;L of 5x Bind/wash buffer to make a 120 &#181;L solution. Use 30 s&#160;power ON and 30 s&#160;power OFF during sonication, 20 - 25 times.</li>
		<li>Run 1 &#181;L of sonicated DNA solution using a bioanalyzer system with a commercial high sensitivity DNA kit to check the size of the fragments to be in the range of 150 - 350 bp according to manufacturer&#39;s protocol.</li>
	</ol>
	</li>
	<li>Wash the MBD-beads
	<ol>
		<li>Place the tube containing MBD-beads on a magnetic rack for 1 min.</li>
		<li>Remove and discard the liquid with a pipette without touching the beads.</li>
		<li>Resuspend the beads with 250 &#181;L of 1x Bind/Wash Buffer.</li>
		<li>Mix the beads on a rotating mixer at RT for 5 min.</li>
		<li>Repeat steps 1.5.1 - 1.5.4 twice.</li>
	</ol>
	</li>
	<li>Fragmented DNA capture reaction (1 &#181;g input DNA)
	<ol>
		<li>Transfer the DNA/Buffer mixture to the tube containing the MBD-beads.</li>
		<li>Mix the MBD-beads with the DNA on a rotating mixer for 1 h&#160;at RT. Alternatively, mix O/N at 4&#160;oC.</li>
	</ol>
	</li>
	<li>Removing non-captured DNA from the Beads
	<ol>
		<li>After mixing the DNA and MBD-beads, place the tube on the magnetic rack for 1 min to concentrate all of the beads on the inner wall of the tube.</li>
		<li>Remove the supernatant liquid with a pipette and save it in a clean DNase-free microcentrifuge tube as nonmethylated DNA. Store this sample on ice.</li>
		<li>Add 200 &#181;L of 1x Bind/Wash Buffer to the beads to wash the beads.</li>
		<li>Mix the beads on a rotating mixer for 3 min.</li>
		<li>Place the tube on the magnetic rack for 1 min.</li>
		<li>Remove the liquid with a pipette and save it in a microcentrifuge tube.</li>
		<li>For capture reactions of &#8804;1 &#181;g of input DNA, repeat steps 1.7.3 - 1.7.6 for 2 more wash fractions in total.</li>
	</ol>
	</li>
	<li>Single fraction elution
	<ol>
		<li>Mix low-salt buffer with high-salt buffer (1:1) to get elution buffer (1,000 mM NaCl).</li>
		<li>Resuspend the beads in 200 &#181;L of elution buffer (1,000 mM NaCl).</li>
		<li>Incubate the beads on a rotating mixer for 3 min.</li>
		<li>Place the tube on the magnetic rack for 1 min.</li>
		<li>With the tube in place on the magnetic rack, remove the liquid with a pipette without touching the beads with the pipette tip, and save it in a clean DNase-free 1.5 mL microcentrifuge tube. Store this sample on ice.</li>
		<li>Repeat steps 1.8.1 - 1.8.4 once, collecting the second sample in the same tube (total volume will be 400 &#181;L). Store the pooled sample on ice.</li>
	</ol>
	</li>
	<li>Ethanol precipitation (DNA cleanup)
	<ol>
		<li>To each noncaptured, wash, and elution fraction from the previous steps, add 1 &#181;L glycogen (20 &#181;g/&#181;L, included in kit), 1/10 sample volume of 3M sodium acetate, pH 5.2 (e.g., 40 &#181;L per 400 &#181;L of sample) and 2 sample volumes of 100% ethanol (e.g., 800 &#181;L per 400 &#181;L of sample). The total volume is 1,241 &#181;L.</li>
		<li>Mix well and incubate at -80&#160;oC for at least 2 h.</li>
		<li>Centrifuge the tube for 15 min at 11,363 x g at 4&#160;oC.</li>
		<li>Carefully discard the supernatant without disturbing the pellet.</li>
		<li>Add 500 &#181;L of cold 70% ethanol.</li>
		<li>Centrifuge the tube for 5 min at 11,363 x g at 4&#160;oC.</li>
		<li>Carefully discard the supernatant without disturbing the pellet.</li>
		<li>Repeat steps 1.9.6 - 1.9.7 once and remove any remaining residual supernatant.</li>
		<li>Air-dry the pellet for ~5 min. Do not completely dry the pellet.</li>
		<li>Resuspend the DNA pellet in 37.5 &#181;L of DNase-free water or other appropriate volume of buffer.</li>
		<li>Place the DNA on ice or store the DNA at -20&#160;oC or below until further use.</li>
		<li>Check that the total amount of DNA is over 20 ng, (e.g., use fluorometric quantitation system, see Materials Table).</li>
	</ol>
	</li>
</ol>
2. Sequencing
<ol>
	<li>Use the DNA fragments recovered from MBDCap procedure for sequencing. For each sample to be sequenced, a total amount of 20&#160;- 40 ng DNA is required for library preparation.</li>
	<li>For DNA-seq library preparation use a fully automated library construction system (See Materials Table) and follow the standard protocol supplied by the manufacturer. Select DNA fragments of size 200 - 400 bp for library preparation. The automation library preparation system allows standardizing the library preparation procedure and minimizing the variation across the samples due to manual preparation.</li>
	<li>Use adaptor primers and dilute to 100x concentration. Of this, use 10 &#181;L for each sample.</li>
	<li>Following step 2.2, take out the reaction, and quantify the DNA-seq library using a fluorometric quantitation system (See Materials Table).
	<ol>
		<li>Set up PCR amplification procedure. The choice of PCR master mix is to improve the PCR efficiency of GC enriched region of genome. In a PCR tube, add 15 &#181;L DNA-seq library, 25&#160;&#181;L PCR master mix (See Materials Table), 2 &#181;L PCR primer mix (See Materials Table), and 8 &#181;L H2O.&#160;</li>
	</ol>
	</li>
	<li>Follow PCR recommendation from manufacturer of the PCR master mix, altering cycling times and temperatures for differing starting materials: 98&#160;oC for 45 s, X cycles of 98&#160;oC for 15 s, 65&#160;oC for 30 s, 72&#160;oC for 30 s, and then 72&#160;oC for 1 min. Hold at 4&#160;oC.
	<ol>
		<li>Perform enough cycles to end up with 2 -&#160;10 nM of library DNA (8 - 10 cycles).</li>
	</ol>
	</li>
	<li>Clean up PCR reaction with 1:1 ratio of PCR purification beads according to manufacturer&#39;s protocol (See Materials Table).</li>
	<li>Elute with 20 - 30 &#181;L elution buffer.</li>
	<li>Barcode each sample and pool 4 samples together into one lane of a flow cell. Use the standard 50 bp single read protocol for sequencing (See Materials Table).</li>
</ol>
3. Bioinformatics Analysis
Note: Further process the raw fastq files obtained from the sequencing to perform quality control and mapping the short DNA sequences (reads) to the genome.
<ol>
	<li>Use Bowtie short read aligner, genome mapping tool on each sample fastq file to map the reads to the reference genome. Many read mapping tools are available to perform this step and can be used based on individual preference.
	<ol>
		<li>Allow up to 2 mismatches in the whole reads while mapping to the reference genome. Report up to 20 best alignments for each read. For example, use bowtie -v 2 --best -k 20 --chunkmbs 200 &#60;ebwt&#62;&#60;fastqFile&#62;&#60;alignFile&#62;.</li>
	</ol>
	</li>
	<li>Use LONUT9 to recover the multiply mapped reads to improve the detection of the enriched regions. For each read, at most one alignment would be recovered when it is close enough to any of the above called peaks. For example, use: perl lonut.pl -g hg19 -w 250 -p 99 &#60;alignFile&#62;&#60;outputPath&#62;. LONUT will perform the following steps.
	<ol>
		<li>Split alignments into uniquely mapped reads and multiply mapped reads. Call peak on the uniquely mapped reads using peak caller BELT11. The option -w 250 and -p 99 in the example command are for BELT.</li>
		<li>Combine uniquely mapped reads with the recovered reads obtained from LONUT, and the combined reads, in BED format, will be used in further analysis. Calculate the number of combined reads for future normalization.</li>
	</ol>
	</li>
	<li>Bin the reads. Extract reads in region of interest using perl script: perl methyPipeline.pl &#60;sampleInfoFile&#62;&#60;refGeneFile&#62; -up &#60;upstream extending length&#62; -dn&#60;downstream extending length&#62;. For each bed file listed in the sampleInfoFile, the perl script performs the below tasks. 
	Note: See supplementary coding file for the perl script.
	<ol>
		<li>Bin the reads into fixed bin size, e.g., 100 bp, for 24 chromosomes.</li>
		<li>For each gene specified in refGeneFile, extract the bins around transcription start site (TSS), up to the extending length specified by option -up and -dn. For example, extract the data in the region that is up and downstream 4 kb of TSS. At bin size 100 bp, this extracted data have 81 bins, and the center bin corresponds to the TSS.</li>
		<li>For the gene on the antisense strand, flip the extracted region from left to right so that upstream bins are always placed on the left with the perl script.</li>
		<li>Further split the TSS &#177;4 kb region into three sub regions: Left, upstream 4 kb to upstream 2 kb; Middle, up and downstream 2 kb; Right, downstream 2 kb to 4 kb.</li>
		<li>For each sample, divide the count of reads in each bin by the total number of combined mapped reads calculated in 3.3.3. The normalization will eliminate the sample specific read differences and allows to compare the reads across different samples.</li>
	</ol>
	</li>
	<li>Run the bash script (as indicated in the script file) to perform statistical test on the normalized reads obtained from the left region, to detect differential methylation between normal and case group in the regions described as in the flank region. 
	Note: See the supplementary coding file for the bash script. Based on the regions that are differentially methylated, there are seven combinations: 
	Whole region: differential methylation throughout the TSS &#177;4 kb region 
	MiddleLeft: differential methylation in both middle and left region 
	MiddleRight: differential methylation in both middle and right region 
	Flank: differential methylation in both left and right region 
	Left: differential methylation in left region only 
	Right: differential methylation in right region only 
	Middle: differential methylation in middle region only</li>
	<li>Use the same bash script to visualize the differential methylation in a tornado plot. Plot the hyper and hypo methylated genes on a separate panel, and sort in the order of the region combination as described in 3.4, respectively.</li>
</ol>

<ol>
	<li>Trimarchi, M. P., Mouangsavanh, M., Huang, T. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer+epigenetics:+a+perspective+on+the+role+of+DNA+methylation+in+acquired+endocrine.">Cancer epigenetics: a perspective on the role of DNA methylation in acquired endocrine.</a> Chin. J. Cancer. 30, 749-756 (2011).</li><li>Nair, S. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+methyl-DNA+immunoprecipitation+(MeDIP)+and+methyl-CpG+binding+domain+(MBD)+protein+capture+for+genome-wide+DNA+methylation+analysis+reveal+CpG+sequence+coverage+bias.">Comparison of methyl-DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain (MBD) protein capture for genome-wide DNA methylation analysis reveal CpG sequence coverage bias.</a> Epigenetics. 6, 34-44 (2011).</li><li>Zuo, T., Tycko, B., Liu, T. M., Lin, J. J., Huang, T. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+in+DNA+methylation+profiling.">Methods in DNA methylation profiling.</a> Epigenomics. 1, 331-345 (2009).</li><li>Clark, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparison+of+the+whole+genome+approach+of+MeDIP-seq+to+the+targeted+approach+of+the+Infinium+HumanMethylation450+BeadChip((R))+for+methylome+profiling.">A comparison of the whole genome approach of MeDIP-seq to the targeted approach of the Infinium HumanMethylation450 BeadChip((R)) for methylome profiling.</a> PLoS One. 7, e50233 (2012).</li><li>Walker, D. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+methylation+profiling:+comparison+of+genome-wide+sequencing+methods+and+the+Infinium+Human+Methylation+450+Bead+Chip.">DNA methylation profiling: comparison of genome-wide sequencing methods and the Infinium Human Methylation 450 Bead Chip.</a> Epigenomics. , 1-16 (2015).</li><li>Huang, Y. W., Huang, T. H., Wang, L. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Profiling+DNA+methylomes+from+microarray+to+genome-scale+sequencing.">Profiling DNA methylomes from microarray to genome-scale sequencing.</a> Technol. Cancer Res. Treat. 9, 139-147 (2010).</li><li>Serre, D., Lee, B. H., Ting, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MBD-isolated+Genome+Sequencing+provides+a+high-throughput+and+comprehensive+survey+of+DNA+methylation+in+the+human+genome.">MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome.</a> Nucleic Acids Res. 38, 391-399 (2010).</li><li>Brinkman, A. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole-genome+DNA+methylation+profiling+using+MethylCap-seq.">Whole-genome DNA methylation profiling using MethylCap-seq.</a> Methods. 52, 232-236 (2010).</li><li>Wang, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LOcating+non-unique+matched+tags+(LONUT)+to+improve+the+detection+of+the+enriched+regions+for+ChIP-seq+data.">LOcating non-unique matched tags (LONUT) to improve the detection of the enriched regions for ChIP-seq data.</a> PLoS One. 8, e67788 (2013).</li><li>Gu, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CMS:+a+web-based+system+for+visualization+and+analysis+of+genome-wide+methylation+data+of+human+cancers.">CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers.</a> PLoS One. 8, e60980 (2013).</li><li>Lan, X., Bonneville, R., Apostolos, J., Wu, W., Jin, V. X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=W-ChIPeaks:+a+comprehensive+web+application+tool+for+processing+ChIP-chip+and+ChIP-seq+data.">W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data.</a> Bioinformatics. 27, 428-430 (2011).</li><li>Jadhav, R. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+DNA+methylation+analysis+reveals+estrogen-mediated+epigenetic+repression+of+metallothionein-1+gene+cluster+in+breast+cancer.">Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.</a> Clin. Epigenetics. 7, 13 (2015).</li><li>Hsu, Y. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Promoter+hypomethylation+of+EpCAM-regulated+bone+morphogenetic+protein+gene+family+in+recurrent+endometrial+cancer.">Promoter hypomethylation of EpCAM-regulated bone morphogenetic protein gene family in recurrent endometrial cancer.</a> Clin. Cancer Res. 19, 6272-6285 (2013).</li><li>Wang, Y. V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Roles+of+Distal+and+Genic+Methylation+in+the+Development+of+Prostate+Tumorigenesis+Revealed+by+Genome-wide+DNA+Methylation+Analysis.">Roles of Distal and Genic Methylation in the Development of Prostate Tumorigenesis Revealed by Genome-wide DNA Methylation Analysis.</a> Sci. Rep. , (2015).</li><li>Plongthongkum, N., Diep, D. H., Zhang, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+the+profiling+of+DNA+modifications:+cytosine+methylation+and+beyond.">Advances in the profiling of DNA modifications: cytosine methylation and beyond.</a> Nat Rev Gen. 15, 647-661 (2014).</li><li>Riebler, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BayMeth:+improved+DNA+methylation+quantification+for+affinity+capture+sequencing+data+using+a+flexible+Bayesian+approach.">BayMeth: improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach.</a> Genome Biol. 15, R35 (2014).</li></ol>

This protocol is developed in the laboratories of Dr. Tim Huang and Dr. Victor Jin at the University of Texas Health Science Center at San Antonio.

The MBDCap-seq technique is an affinity enrichment approach3, considered as a cost effective alternative when investigating cohorts with a large number of patients15. The pipeline presented here describes a comprehensive approach from sample procurement to data analysis and interpretation. One of the most important steps is setting up a PCR amplification procedure to improve the PCR efficiency of the GC enriched regions in the genome as this is where DNA methylation occurs. Also, it is essential to ensure that after seq...

Epigenetic regulation of genes through DNA methylation is one of the essential mechanisms required to determine the cell fate by stable differentiation of different tissue types in the body1. Dysregulation of this process has been known to cause various diseases including cancer2.
This process mainly involves the addition of methyl groups on the cytosine residue in the CpG dinucleotides of DNA3. There are a few different techniques currently used to investigate this mechanism, each having their own advantages as outlined in many studies2-8. Here we will discuss one of these techniques called Methyl-Binding DNA Capture&#160;sequencing (MBDCap-seq), where we use an affinity enrichment technique to identify methylated regions of the DNA. This technique builds upon the methyl-binding ability of the MBD2 protein to enrich for the genomic DNA fragments containing methylated CpG sites. We utilize a commercial methylated DNA enrichment kit for the isolation of these methylated regions. Our laboratory has screened hundreds of patient samples using this technique and here we provide a comprehensive optimized protocol, which can be used to investigate large patient cohorts.
As evident with any next-generation sequencing technology, MBDCap-seq also requires a specific bioinformatics approach in order to accurately quantify the levels of methylation across the samples. There have been many recent studies in an effort to optimize the normalization and analysis process of the sequencing data9,10. In this protocol, we demonstrate one of these methods implementing a unique read recovery approach &#8212; LONUT &#8212; followed by linear normalization of each sample in order to enable unbiased comparisons across large number of patient samples.

<table><tbody><tr><td>Methylminer DNA enrichment Kit</td><td>Invitrogen</td><td>ME10025</td><td></td></tr><tr><td>Dynabeads M-280 Streptavidin</td><td>Invitrogen</td><td>112-05D</td><td></td></tr><tr><td>Bioruptor Plus Sonication Device</td><td>diagenode</td><td>B01020001</td><td></td></tr><tr><td>3 M sodium acetate, pH 5.2</td><td>Sigma</td><td>S7899</td><td>100 mL</td></tr><tr><td>SPRIworks Fragment Library System I</td><td>Beckman Coulter</td><td>A50100</td><td>Fully automated library construction system</td></tr><tr><td>Adapter Primers</td><td>Bioo Scientific</td><td>514104</td><td>PCR primer mix</td></tr><tr><td>Qubit</td><td>Invitrogen</td><td>Q32854</td><td>Fluorometric Quantitation System</td></tr><tr><td>PCR master mix</td><td>KAPA scientific</td><td>KK2621</td><td>PCR master mix</td></tr><tr><td>AMPure XP</td><td>Beckman Coulter</td><td>A63881</td><td>PCR Purification beads</td></tr><tr><td>EB Buffer</td><td>Qiagen</td><td>19086</td><td></td></tr><tr><td>HiSeq 2000 Sequencing System</td><td>Illumina</td><td></td><td></td></tr></tbody></table>

methyl-binding dna capture sequencing for patient tissues

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable development and differentiation of different tissue types. Dysregulation of this process is often the hallmark of various diseases like cancer. Here, we outline one of the recent sequencing techniques, Methyl-Binding DNA Capture sequencing (MBDCap-seq), used to quantify methylation in various normal and disease tissues for large patient cohorts. We describe a detailed protocol of this affinity enrichment approach along with a bioinformatics pipeline to achieve optimal quantification. This technique has been used to sequence hundreds of patients across various cancer types as a part of the 1,000 methylome project (Cancer Methylome System).

We have used MBDCap-seq to study DNA methylation alterations in a large number of patients from diverse cancer types including breast12, endometrial13, prostate14, and liver cancers among others. Here we demonstrate some information from the breast cancer study published recently12. In this instance, we used the whole genome sequencing approach to identify CpG islands that are differentially methylated in tumor with respect to normal across different genomic regions. The investigation revealed that...

Watch this Scientific Journal Video about Methyl-binding DNA capture Sequencing for Patient Tissues at JoVE.com

Methyl-binding DNA capture Sequencing for Patient Tissues

Here we present a protocol to investigate genome wide DNA methylation in large scale clinical patient screening studies using the Methyl-Binding DNA Capture sequencing (MBDCap-seq or MBD-seq) technology and the subsequent bioinformatics analysis pipeline.

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable ...

methyl-binding-dna-capture-sequencing-for-patient-tissues

Research

JoVE Journal

Genetics

8.6K Views.  University of Texas Health Science Center at San Antonio.  Hier presenteren we een protocol om het gehele genoom DNA-methylatie in grootschalige klinische patiënt screening studies met behulp van de Methyl-bindende DNA Capture sequencing (MBDCap-seq of MBD-volgende) technologie en de daaropvolgende bioinformatica analyse pijplijn te onderzoeken. 

Video: Methyl-binding DNA capture Sequencing for Patient Tissues

Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients

The role of long noncoding RNAs (lncRNAs) in cancer is coming to the forefront due to growing interest in understanding their mechanistic functions during cancer development and progression. Despite this, the global epigenetic regulation of lncRNAs and repetitive sequences in cancer has not been well investigated, particularly in chronic lymphocytic leukemia (CLL). This study focuses on a unique approach: the immunoprecipitation-based capture of double-stranded, methylated DNA fragments using methyl-binding domain (MBD) proteins, followed by next-generation sequencing (MBD-seq). CLL patient samples belonging to two prognostic subgroups (5 IGVH mutated samples + 5 IGVH unmutated samples) were used in this study. Analysis revealed 5,800 hypermethylated and 12,570 hypomethylated CLL-specific differentially methylated genes (cllDMGs) compared to normal healthy controls. Importantly, these results identified several CLL-specific, differentially methylated lncRNAs, repetitive elements, and protein-coding genes with potential prognostic value. This work outlines a detailed protocol for an MBD-seq and bioinformatics pipeline developed for the comprehensive analysis of global methylation profiles in highly CpG-rich regions using CLL patient samples. Finally, a protein-coding gene and an lncRNA were validated using pyrosequencing, which is a highly quantitative method to analyze CpG methylation levels to further corroborate the findings from the MBD-seq protocol.

This work describes an optimized methyl-CpG-binding domain (MBD) sequencing protocol and a computational pipeline to identify differentially methylated CpG-rich regions in chronic lymphocytic leukemia (CLL) patients.

The role of long noncoding RNAs (lncRNAs) in cancer is coming to the forefront due to growing interest in understanding their mechanistic functions during ...

Methodology for Accurate Detection of Mitochondrial DNA Methylation

Quantification of DNA methylation can be achieved using bisulfite sequencing, which takes advantage of the property of sodium bisulfite to convert unmethylated cytosine into uracil, in a single-stranded DNA context. Bisulfite sequencing can be targeted (using PCR) or performed on the whole genome and provides absolute quantification of cytosine methylation at the single base-resolution. Given the distinct nature of nuclear- and mitochondrial DNA, notably in the secondary structure, adaptions of bisulfite sequencing methods for investigating cytosine methylation in mtDNA should be made. Secondary and tertiary structure of mtDNA can indeed lead to bisulfite sequencing artifacts leading to false-positives due to incomplete denaturation poor access of bisulfite to single-stranded DNA. Here, we describe a protocol using an enzymatic digestion of DNA with BamHI coupled with bioinformatic analysis pipeline to allow accurate quantification of cytosine methylation levels in mtDNA. In addition, we provide guidelines for designing the bisulfite sequencing primers specific to mtDNA, in order to avoid targeting undesirable NUclear MiTochondrial segments (NUMTs) inserted into the nuclear genome.

Here, we present a protocol to allow accurate quantification of mitochondrial DNA (mtDNA) methylation. In this protocol, we describe an enzymatic digestion of DNA with BamHI coupled with a bioinformatic analysis pipeline which can be used to avoid overestimation of mtDNA methylation levels caused by the secondary structure of mtDNA.

Quantification of DNA methylation can be achieved using bisulfite sequencing, which takes advantage of the property of sodium bisulfite to convert ...

Methylated DNA Immunoprecipitation

The identification of DNA methylation patterns is a common procedure in the study of epigenetics, as methylation is known to have significant effects on gene expression, and is involved with normal development as well as disease 1-4. Thus, the ability to discriminate between methylated DNA and non-methylated DNA is essential for generating methylation profiles for such studies. Methylated DNA immunoprecipitation (MeDIP) is an efficient technique for the extraction of methylated DNA from a sample of interest 5-7. A sample of as little as 200 ng of DNA is sufficient for the antibody, or immunoprecipitation (IP), reaction. DNA is sonicated into fragments ranging in size from 300-1000 bp, and is divided into immunoprecipitated (IP) and input (IN) portions. IP DNA is subsequently heat denatured and then incubated with anti-5'mC, allowing the monoclonal antibody to bind methylated DNA. After this, magnetic beads containing a secondary antibody with affinity for the primary antibody are added, and incubated. These bead-linked antibodies will bind the monoclonal antibody used in the first step. DNA bound to the antibody complex (methylated DNA) is separated from the rest of the DNA by using a magnet to pull the complexes out of solution. Several washes using IP buffer are then performed to remove the unbound, non-methylated DNA. The methylated DNA/antibody complexes are then digested with Proteinase K to digest the antibodies leaving only the methylated DNA intact. The enriched DNA is purified by phenol:chloroform extraction to remove the protein matter and then precipitated and resuspended in water for later use. PCR techniques can be used to validate the efficiency of the MeDIP procedure by analyzing the amplification products of IP and IN DNA for regions known to lack and known to contain methylated sequences. The purified methylated DNA can then be used for locus-specific (PCR) or genome-wide (microarray and sequencing) methylation studies, and is particularly useful when applied in conjunction with other research tools such as gene expression profiling and array comparative genome hybridization (CGH) 8. Further investigation into DNA methylation will lead to the discovery of new epigenetic targets, which in turn, may be useful in developing new therapeutic or prognostic research tools for diseases such as cancer that are characterized by aberrantly methylated DNA 2, 4, 9-11.

This video demonstrates the protocol for methylated DNA immunoprecipitation (MeDIP). MeDIP is a two day procedure that selectively extracts methylated DNA fragments from a genomic DNA sample using antibodies with specificity for 5 -methylcytosine (anti-5 mC).

The identification of DNA methylation patterns is a common procedure in the study of epigenetics, as methylation is known to have significant effects on ...

Biology

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Exposure to diet, drugs and early life adversity during sensitive windows of life 1,2 can lead to lasting changes in gene expression that contribute to the display of physiological and behavioural phenotypes. Such environmental programming is likely to increase the susceptibility to metabolic, cardiovascular and mental diseases 3,4.
DNA methylation and histone modifications are considered key processes in the mediation of the gene-environment dialogue and appear also to underlay environmental programming 5. In mammals, DNA methylation typically comprises the covalent addition of a methyl group at the 5-position of cytosine within the context of CpG dinucleotides.
CpG methylation occurs in a highly tissue- and cell-specific manner making it a challenge to study discrete, small regions of the brain where cellular heterogeneity is high and tissue quantity limited. Moreover, because gene expression and methylation are closely linked events, increased value can be gained by comparing both parameters in the same sample.
Here, a step-by-step protocol (Figure 1) for the investigation of epigenetic programming in the brain is presented using the 'maternal separation' paradigm of early life adversity for illustrative purposes. The protocol describes the preparation of micropunches from differentially-aged mouse brains from which DNA and RNA can be simultaneously isolated, thus allowing DNA methylation and gene expression analyses in the same sample.

A streamlined workflow to study DNA methylation and gene expression changes upon early-life stress is shown. Starting from maternal separation of newborn mice and isolation of discrete brain tissues, we represent a protocol to simultaneously isolate DNA and RNA from brain tissue punches for subsequent bisulfite sequencing and RT-PCR analysis.

Exposure to diet, drugs and early life adversity during sensitive windows of life 1,2 can lead to lasting changes in gene expression that contribute to ...

Neuroscience

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

DNA methylation is an important epigenetic change that is biologically meaningful and a frequent focus of cancer research. Genome-wide DNA methylation is a useful measure to provide an accurate analysis of the methylation status of gastrointestinal (GI) malignancies. Given the multiple potential translational uses of DNA methylation analysis, practicing clinicians and others new to DNA methylation studies need to be able to understand step by step how these genome-wide analyses are performed. The goal of this protocol is to provide a detailed description of how this method is used for the biomarker identification in GI malignancies. Importantly, we describe three critical steps that are needed to obtain accurate results during genome-wide analysis. Clearly and concisely written, these three methods are often lacking and not noticeable to those new to epigenetic studies. We used 48 samples of a GI malignancy (gastric cancer) to highlight practically how genome-wide DNA methylation analysis can be performed for GI malignancies.

Herein, we describe a procedure for genome-wide analysis of DNA methylation in gastrointestinal cancers. The procedure is of relevance to studies that investigate relationships between methylation patterns of genes and factors contributing to carcinogenesis in gastrointestinal cancers.

DNA methylation is an important epigenetic change that is biologically meaningful and a frequent focus of cancer research. Genome-wide DNA methylation is ...

Cancer Research

DNA Methylation: Bisulphite Modification and Analysis

Epigenetics describes the heritable changes in gene function that occur independently to the DNA sequence. The molecular basis of epigenetic gene regulation is complex, but essentially involves modifications to the DNA itself or the proteins with which DNA associates. The predominant epigenetic modification of DNA in mammalian genomes is methylation of cytosine nucleotides (5-MeC). DNA methylation provides instruction to gene expression machinery as to where and when the gene should be expressed. The primary target sequence for DNA methylation in mammals is 5'-CpG-3' dinucleotides (Figure 1). CpG dinucleotides are not uniformly distributed throughout the genome, but are concentrated in regions of repetitive genomic sequences and CpG "islands" commonly associated with gene promoters (Figure 1). DNA methylation patterns are established early in development, modulated during tissue specific differentiation and disrupted in many disease states including cancer. To understand the biological role of DNA methylation and its role in human disease, precise, efficient and reproducible methods are required to detect and quantify individual 5-MeCs.
This protocol for bisulphite conversion is the "gold standard" for DNA methylation analysis and facilitates identification and quantification of DNA methylation at single nucleotide resolution. The chemistry of cytosine deamination by sodium bisulphite involves three steps (Figure 2). (1) Sulphonation: The addition of bisulphite to the 5-6 double bond of cytosine (2) Hydrolic Deamination: hydrolytic deamination of the resulting cytosine-bisulphite derivative to give a uracil-bisulphite derivative (3) Alkali Desulphonation: Removal of the sulphonate group by an alkali treatment, to give uracil. Bisulphite preferentially deaminates cytosine to uracil in single stranded DNA, whereas 5-MeC, is refractory to bisulphite-mediated deamination. Upon PCR amplification, uracil is amplified as thymine while 5-MeC residues remain as cytosines, allowing methylated CpGs to be distinguished from unmethylated CpGs by presence of a cytosine "C" versus thymine "T" residue during sequencing.
DNA modification by bisulphite conversion is a well-established protocol that can be exploited for many methods of DNA methylation analysis. Since the detection of 5-MeC by bisulphite conversion was first demonstrated by Frommer et al.1 and Clark et al.2, methods based around bisulphite conversion of genomic DNA account for the majority of new data on DNA methylation. Different methods of post PCR analysis may be utilized, depending on the degree of specificity and resolution of methylation required. Cloning and sequencing is still the most readily available method that can give single nucleotide resolution for methylation across the DNA molecule.

The gold standard for DNA methylation analysis is genomic sequencing of bisulphite converted DNA. This method takes advantage of the increased sensitivity of cytosine compared with 5-methylcytosine (5-MeC) to bisulphite deamination under acidic conditions. Unmethylated cytosines can be distinguished from methylated cytosines after PCR amplification of the target genomic DNA.

Epigenetics describes the heritable changes in gene function that occur independently to the DNA sequence. The molecular basis of epigenetic gene ...

Selective Capture of 5-hydroxymethylcytosine from Genomic DNA

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene expression, maintenance of genome integrity, parental imprinting, X-chromosome inactivation, regulation of development, aging, and cancer1. Recently, the presence of an oxidized 5-mC, 5-hydroxymethylcytosine (5-hmC), was discovered in mammalian cells, in particular in embryonic stem (ES) cells and neuronal cells2-4. 5-hmC is generated by oxidation of 5-mC catalyzed by TET family iron (II)/&alpha;-ketoglutarate-dependent dioxygenases2, 3. 5-hmC is proposed to be involved in the maintenance of embryonic stem (mES) cell, normal hematopoiesis and malignancies, and zygote development2, 5-10. To better understand the function of 5-hmC, a reliable and straightforward sequencing system is essential. Traditional bisulfite sequencing cannot distinguish 5-hmC from 5-mC11. To unravel the biology of 5-hmC, we have developed a highly efficient and selective chemical approach to label and capture 5-hmC, taking advantage of a bacteriophage enzyme that adds a glucose moiety to 5-hmC specifically12.
Here we describe a straightforward two-step procedure for selective chemical labeling of 5-hmC. In the first labeling step, 5-hmC in genomic DNA is labeled with a 6-azide-glucose catalyzed by &beta;-GT, a glucosyltransferase from T4 bacteriophage, in a way that transfers the 6-azide-glucose to 5-hmC from the modified cofactor, UDP-6-N3-Glc (6-N3UDPG). In the second step, biotinylation, a disulfide biotin linker is attached to the azide group by click chemistry. Both steps are highly specific and efficient, leading to complete labeling regardless of the abundance of 5-hmC in genomic regions and giving extremely low background. Following biotinylation of 5-hmC, the 5-hmC-containing DNA fragments are then selectively captured using streptavidin beads in a density-independent manner. The resulting 5-hmC-enriched DNA fragments could be used for downstream analyses, including next-generation sequencing.
Our selective labeling and capture protocol confers high sensitivity, applicable to any source of genomic DNA with variable/diverse 5-hmC abundances. Although the main purpose of this protocol is its downstream application (i.e., next-generation sequencing to map out the 5-hmC distribution in genome), it is compatible with single-molecule, real-time SMRT (DNA) sequencing, which is capable of delivering single-base resolution sequencing of 5-hmC.

Described is a two-step labeling process using &beta;-glucosyltransferase (&beta;-GT) to transfer an azide-glucose to 5-hmC, followed by click chemistry to transfer a biotin linker for easy and density-independent enrichment. This efficient and specific labeling method enables enrichment of 5-hmC with extremely low background and high-throughput epigenomic mapping via next-generation sequencing.

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene ...

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

Gene inactivation is instrumental to study gene function and represents a promising strategy for the treatment of a broad range of diseases. Among traditional technologies, RNA interference suffers from partial target abrogation and the requirement for life-long treatments. In contrast, artificial nucleases can impose stable gene inactivation through induction of a DNA double strand break (DSB), but recent studies are questioning the safety of this approach. Targeted epigenetic editing via engineered transcriptional repressors (ETRs) may represent a solution, as a single administration of specific ETR combinations can lead to durable silencing without inducing DNA breaks.
ETRs are proteins containing a programmable DNA-binding domain (DBD) and effectors from naturally occurring transcriptional repressors. Specifically, a combination of three ETRs equipped with the KRAB domain of human ZNF10, the catalytic domain of human DNMT3A and human DNMT3L, was shown to induce heritable repressive epigenetic states on the ETR-target gene. The hit-and-run nature of this platform, the lack of impact on the DNA sequence of the target, and the possibility to revert to the repressive state by DNA demethylation on demand, make epigenetic silencing a game-changing tool. A critical step is the identification of the proper ETRs&#39; position on the target gene to maximize on-target and minimize off-target silencing. Performing this step in the final ex vivo or in vivo preclinical setting can be cumbersome.
Taking the CRISPR/catalytically dead Cas9 system as a paradigmatic DBD for ETRs, this paper describes a protocol consisting of the in vitro screen of guide RNAs (gRNAs) coupled to the triple-ETR combination for efficient on-target silencing, followed by evaluation of the genome-wide specificity profile of top hits. This allows for reduction of the initial repertoire of candidate gRNAs to a short list of promising ones, whose complexity is suitable for their final&#160;evaluation in the therapeutically relevant setting of interest.

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

Here, we present a protocol for the in vitro selection of engineered transcriptional repressors (ETRs) with high, long-term, stable, on-target silencing efficiency and low genome-wide, off-target activity. This workflow allows for reducing an initial, complex repertoire of candidate ETRs to a short list, suitable for further evaluation in therapeutically relevant settings.

Gene inactivation is instrumental to study gene function and represents a promising strategy for the treatment of a broad range of diseases. Among ...

Bioengineering

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine methylation patterns in cells. Reduced representation of whole genome bisulfite sequencing was developed to detect quantitative base pair resolution cytosine methylation patterns at GC-rich genomic loci. This is accomplished by combining the use of a restriction enzyme followed by bisulfite conversion. Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) increases the biologically relevant genomic loci covered and has been used to profile cytosine methylation in DNA from human, mouse and other organisms. ERRBS initiates with restriction enzyme digestion of DNA to generate low molecular weight fragments for use in library preparation. These fragments are subjected to standard library construction for next generation sequencing. Bisulfite conversion of unmethylated cytosines prior to the final amplification step allows for quantitative base resolution of cytosine methylation levels in covered genomic loci. The protocol can be completed within four days. Despite low complexity in the first three bases sequenced, ERRBS libraries yield high quality data when using a designated sequencing control lane. Mapping and bioinformatics analysis is then performed and yields data that can be easily integrated with a variety of genome-wide platforms. ERRBS can utilize small input material quantities making it feasible to process human clinical samples and applicable in a range of research applications. The video produced demonstrates critical steps of the ERRBS protocol.

Enhanced Reduced Representation Bisulfite Sequencing is a method for the preparation of sequencing libraries for DNA methylation analysis based on restriction enzyme digestion combined with cytosine bisulfite conversion. This protocol requires 50 ng of starting material and yields base pair resolution data at GC-rich genomic regions.

DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine ...

Targeted DNA Methylation Analysis by Next-generation Sequencing

The role of epigenetic processes in the control of gene expression has been known for a number of years. DNA methylation at cytosine residues is of particular interest for epigenetic studies as it has been demonstrated to be both a long lasting and a dynamic regulator of gene expression. Efforts to examine epigenetic changes in health and disease have been hindered by the lack of high-throughput, quantitatively accurate methods. With the advent and popularization of next-generation sequencing (NGS) technologies, these tools are now being applied to epigenomics in addition to existing genomic and transcriptomic methodologies. For epigenetic investigations of cytosine methylation where regions of interest, such as specific gene promoters or CpG islands, have been identified and there is a need to examine significant numbers of samples with high quantitative accuracy, we have developed a method called Bisulfite Amplicon Sequencing (BSAS). This method combines bisulfite conversion with targeted amplification of regions of interest, transposome-mediated library construction and benchtop NGS. BSAS offers a rapid and efficient method for analysis of up to 10 kb of targeted regions in up to 96 samples at a time that can be performed by most research groups with basic molecular biology skills. The results provide absolute quantitation of cytosine methylation with base specificity. BSAS can be applied to any genomic region from any DNA source. This method is useful for hypothesis testing studies of target regions of interest as well as confirmation of regions identified in genome-wide methylation analyses such as whole genome bisulfite sequencing, reduced representation bisulfite sequencing, and methylated DNA immunoprecipitation sequencing.

Bisulfite amplicon sequencing (BSAS) is a method for quantifying cytosine methylation in targeted genomic regions of interest. This method uses bisulfite conversion paired with PCR amplification of target regions prior to next-generation sequencing to produce absolute quantitation of DNA methylation at a base-specific level.

The role of epigenetic processes in the control of gene expression has been known for a number of years. DNA methylation at cytosine residues is of ...

Methyl-binding DNA capture Sequencing for Patient Tissues

Samenvatting

Meer video's verkennen