Epigenetics application guide

Find out about the key areas of epigenetics including histone modifications, chromatin architecture, DNA and RNA modifications.

​​Why is epigenetics so important

​​Completion of the human genome project and advances in next-generation sequencing technologies have revealed that genomic DNA has much less control over biological processes and disease states than originally thought. Instead, epigenetic factors dictate how DNA is translated, tightly regulating DNA structure to control which genes are expressed at what times. 

Many of these epigenetic factors work together to orchestrate essential cellular programs, from developmental processes to cell death pathways. Dysfunction of any of these factors can upset genomic regulation, causing cellular processes to go awry and resulting in disease from cancers to autoimmune disorders, neurological diseases, infertility and everything in between.
​​
To thoroughly understand any aspect of biology or disease, it is therefore essential to examine epigenetic factors that may contribute. This guide provides an overview of epigenetic regulation, and how to study these critical players in health and disease. ​

How to study epigenetics

​Epigenetic regulation occurs on many interacting levels, and it is important to examine all of these levels in parallel to paint a complete picture of how epigenetics contributes to biological processes. Overlooking any of these aspects of epigenetic regulation can point to the wrong conclusions. Tackling epigenetic studies from many angles with redundancy is key to ensuring accurate results.

​Epigenetics is a very active field of research which is continually discovering new mechanisms and interactions of genomic regulation. Distinct sets of chromatin marks are associated with various regulatory outcomes and have been implicated as carriers of epigenetic identity, although precise mechanisms connecting these marks to functional consequences are only beginning to emerge.

​Currently, there are five essential aspects of epigenetic regulation that warrant examination.

1. Chromatin accessibility and architecture
​
The genome is efficiently packaged into the nucleus.  DNA is wrapped around histones to form a nucleosome, comprised of 147 base pairs of DNA and eight core histone proteins.  Nucleosomes are strung together like beads on a string and packaged into higher order chromatin architecture (Figure 1). 

remodeled​^{Figure 1: Chromatin structure. DNA winds around nucleosomes to form chromatin fiber and then chromosomes}

^​​DNA that is tightly bound in nucleosomes or compacted into higher order heterochromatin is inaccessible, preventing the binding of transcription factors, transcriptional machinery, and other DNA binding proteins, resulting in gene silencing.  Meanwhile “Linker” DNA and open euchromatin architecture is accessible to binding, allowing for active gene transcription.

Chromatin is actively and dynamically remodelled to alter gene expression and cellular programming, for example during different developmental states or in response to particular stimuli.  Large genomic regions may be silenced or activated, or nucleosomes may be unraveled to access specific genes and DNA sequences.

Examining chromatin structure and nucleosome positioning, and changes therein, at specific sites and across the genome can reveal epigenetic programs and mechanisms involved in specific cellular processes and disease states.

​Methods to study DNA accessibility

• Most established and practiced method
• DNase cutting bias is well-understood
• Can be adapted to inversely examine protected genomic regions, called DNase footprinting, to identify transcription factor and nucleosome binding sites. However, it is important to use naked DNA as a control for such experiments as DNase I cutting bias can lead to false conclusions
• Possible to adapt for single cell analysis

• Technically difficult to master, especially in optimizing digestion conditions for a given cell type/number
• Requires millions of cells, and may be challenging for analysis of rare patient samples

• Common and well established in many cell types of many species, from yeast to humans, with some standardization of digestion and data analysis
• Can be used in combinations with chromatin immunoprecipitation (ChIP-seq), to study regulatory factors that bind to nucleosomes
• Can be adapted to generate base-pair resolution mapping
• Can be adapted to examine nucleosome positioning and DNA methylation state in NOMe-seq

• Requires large numbers of cells: 10–20 million cells
• Sequence-specific bias in digestion of AT-rich regions (although most enzymes used in chromatin accessibility assays exhibit similar biases), but also unknown biases that may skew results
• Single cell analysis not possible yet

• Easiest method: no sonication, phenol-chloroform extraction, antibodies (ChIP-seq) or enzymatic digestion (DNase-seq, MNase-seq)
• Fastest method: < 3 hours compared to up to 4-day protocol
• Best signal-to-noise ratio
• Only 50,000 or fewer cells required (500-50,000 recommended)
• Single nucleotide resolution possible
• Single-cell analysis is possible with adapted protocols utilizing flow cytometry/microfluidics

• More expensive, requiring a kit from Illumina (Nextera DNA Library Preparation Kit).
• Least established method requires optimization of cell number and lysis conditions for specific cell types, tissues, and organisms to achieve ideal fragment distributions. Cell number defines the quality of data, with too few cells or too many cells resulting in over or under-transposition which can skew results.
  
  

Chromosome conformation techniques

​​Three-dimensional chromatin architecture can be assessed with chromatin contact mapping, which reveals physical interactions between distant genomic regions. This type of mapping is made possible by the advent of chromatin conformation capture (3C) and subsequent methods born out of that approach. Each of these approaches has particular strengths for certain applications; however, selecting a method for a specific purpose can be challenging due to the sheer variety of methodologies.​

• Choose the right restriction enzymes. More frequent cutters (ie four bp recognition sites) are better for local interactions between the region of interest and nearby sequences on the same chromosome (van der Werken et al., 2012).
• Find the appropriate crosslinking stringency for your experiment. Lower formaldehyde concentrations promote undesirable region-of-interest self-ligations, but also prevent DNA "hairballs" that hinder restriction enzyme cutting. Higher formaldehyde concentrations lower self-ligation events but increase hairballs. An optimal formaldehyde concentration should be chosen for the specific experimental situation to balance these considerations. 1% formaldehyde treatment for 10 min is a good starting point for most experiments (van der Werken et al., 2012).

• Select the right restriction enzyme. This is a much simpler task for 5C than 4C, since 5C does not need to consider the distribution of restriction sites around the region-of-interest. However, choosing an enzyme that functions efficiently under your specific experimental conditions is important. For example, BamHI is not recommended for most experiments due to inefficiency under 3C conditions (Dotsie et al., 2007).
• Optimize primer design. This is a key for 5C, and a little different to other 3C techniques. 5C uses two primers: a forward 5C primer that binds upstream of the ligation site, and a reverse primer that binds immediately downstream. Primer length should be adjusted so that the annealing temperature is about 65°C to allow primers to anneal exactly with their restriction fragments. Ensure that 5C primers are synthesized with a phosphate at the 5' end for ligation.
• Try to use a control template. This will control for differences in primer efficiency. A control library constructed from the entire genomic region under study is recommended. However, in a large-scale study, this may not be reasonable, and most researchers opt to skip it. If this library is not constructed, then researchers should be aware that interaction frequencies would be less precise.

• Overlap PET tags to reduce background. Like most 3C technologies, background noise is a big technical challenge. In ChIA-PET particularly, noise can make it difficult to find true long-range interactions with the locus of interest. A useful tip to overcome this is to require PETs to overlap at both ends of the region to be a true long-range interaction.

• Avoid non-native loops. The biggest issue encountered with ChIP-loop is the formation of non-native loops forming during DNA concentration before ligation occurs. A simple way to avoid this is to choose a protocol that performs the precipitation after the ligation step (Simons et al., 2007).
• Validate ChIP-loop interactions. Another challenge in ChIP-loop can be accurate quantitation of ligation products. Random interactions are often captured by 3C technologies, especially ChIP-loop. To combat this, consider performing a ChIP experiment in parallel and using it to validate the ChIP-loop interactions. If a DNA-protein-DNA interaction identified by ChIP-loop is indeed real, then both DNA-protein interactions should also appear in the ChIP data (Simons et al., 2007).

• Optimize library amplification. Hi-C library amplification must generate enough product for analysis while avoiding PCR artifacts. To do this, the PCR cycle number should be optimized (in the range of 9-15 cycles). If enough product can't be produced (50 ng of DNA), multiple PCR reactions should be pooled rather than the cycle number increased, five reactions are usually sufficient (Belton et al., 2012).
• Balance read lengths. As with any sequence experiment, high-quality reads are paramount. The read length must be optimal to balance the need for long reads to map interactions, but not too long as to pass through the ligation junction into the partner fragment. Therefore, 50 bp reads are optimal in most cases (Belton et al., 2012).
• Choose a proper bin size. This is critical for data analysis. Bin size should be inversely proportional to the number of expected interactions in a region. Use smaller bins for more frequent intra-chromosomal interactions and larger bins for less frequent inter-chromosomal interactions (Belton et al., 2012).

• Carefully choose probe positions. It's best to position probes close to the restriction enzyme sites, even overlapping when possible (Hughes et al., 2014).
• Keep libraries complex. Maintaining library complexity is the top priority. A complex library means more high-quality interactions in the output. For this reason, anything could decrease library complexity should be avoided, such as a Hi-C biotin capture (Hughes et al., 2014).
• Watch for false interaction in duplicated regions. The mapping process can stimulate strong interactions between these regions (such as pseudogenes) that are actually artifacts (Hughes et al., 2014).

Chromatin architecture, nucleosomal positioning and ultimately access to DNA for gene transcription, is controlled in large part by histone proteins. Each nucleosome is comprised of 8 core histone proteins: two subunits each of histones H2A, H2B, H3 and H4. Meanwhile, the H1 protein acts as the linker histone to stabilize internucleosomal DNA and does not form part of the nucleosome itself.

Histone proteins can be post-translational modified in different ways, impacting their interactions with DNA. Some modifications disrupt histone-DNA interactions, causing nucleosomes to unwind. In this open chromatin conformation, called euchromatin, DNA is accessible to binding of transcriptional machinery, resulting in gene activation.  In contrast, modifications that strengthen histone-DNA interactions create a tightly packed chromatin structure called heterochromatin. In this compact form, transcriptional machinery cannot access DNA, resulting in gene silencing. In this way, modification to histones by chromatin remodeling complexes changes chromatin architecture and gene activation.

At least nine different types of histone modifications have been discovered thus far. Acetylation, methylation, phosphorylation, and ubiquitylation are the most well-understood, while GlcNAcylation, citrullination, krotonilation, and isomerization are more recent discoveries that have yet to be thoroughly investigated. Each of these modifications are added or removed from specific amino acid residues of histone proteins by a specific set of enzymes.

Figure 2: The most common histone modifications. To find out more see our full histone modifications poster.

​Together, these histone modifications make up what is known as the histone code, which dictates the transcriptional state of the local genomic region. Examining histone modifications at a particular region, or across the genome, can reveal gene activation states, locations of promoters, enhancers, and other gene regulatory elements.

Histone modifications in detail

​Acetylation
​Acetylation is one of the most widely studied histone modifications, as one of the first discovered to influence transcriptional regulation. Acetylation adds a negative charge to lysine residues on N-terminal histone tails, which extend out from the nucleosome. This repels negatively charged DNA and results in a relaxed chromatin structure.  The open chromatin conformation allows transcription factor binding and significantly increases gene expression.

• Lysine:   SET  domain containing (histone tails)   
• Non-SET domain containing (histone cores)
• Arginine:  PRMT (protein arginine methyltransferases) family

• Lysine:   KDM1/LSD1 (lysine-specific demethylase 1)
• JmjC (Jumonji domain-containing)     
• Arginine:   PAD4/PADI4

• H2A:  polycomb group proteins  
• H2B:  Bre1 (yeast) and its homologs RNF20/RNF40 (mammals)

• H2A/H2AX K63:  RNF8/RNF168  

^{Figure 3: Histone modification ChIP. Antibodies bind directly to modified histone tails. Immunoprecipitation and DNA purification allows isolation and identification of the genomic regions the modifications occupy.}​

^​If the function of a specific histone modification is known, ChIP can identify specific genes and regions with this histone modification signature and corresponding function across the genome. These genes and regions can then be further examined for their role in the biological process of interest. For example, ChIP’ing against H3K4me1 will reveal the locations and sequences of active enhancers throughout the genome, pointing to genes and genetic programs of interest.

Alternatively, if the function of the histone modification is not known, ChIP can identify sequences, genes, and locations with this signature, which can then be used to infer the function of the modification.  This technique was pivotal in decoding much of the histone code and is still implemental in ascertaining the function of newly discovered modifications like ubiquitylation and other novel markings. Abcam offers fast and easy ChIP kits for histone modifications, designed and optimized for high quality, reproducible results, to accelerate your epigenetic research. 

You can find our native ChIP protocol recommended for the study of histone modifications, here. ​

​Figure 4. ChIP protocol workflow. Step by step approach to carrying out a ChIP experiment 

1. Cross-linking

• N-ChIP provides the highest resolution mapping, with enzymatic digestion generating fragments the size of a single nucleosome at 175 base pairs. 
• X-ChIP relies on sonication to generate ideal fragment sizes of 200-1000 base pairs.

​​

^{_​​Figure 5: Example of sonication time course experiment. U2OS cells were sonicated for 5, 10, 15 and 20 min. The cross-links were reversed and the purified DNA was resolved on a 1.5% agarose gel. The fragment size decreases during the time course. The optimal fragment size is observed at 15 min.}

Antibody concentration. It is important to titer the antibody to optimize the signal to noise ratio. Start with 3–5 µg of antibody for every 25–35 mg of pure monosomes. For quantitative ChIP, you may need to match the amount of chromatin with the same amount of antibody. ChIP typically requires a large amount of primary antibody (1-10 ug per ug of beads). As with many techniques, it is essential to optimize the amount of antibody at the beginning before you run your experiment.

Wash buffers. Determine the correct composition for appropriate stringency of wash steps, typically between 250–500 mM NaCl or LiCl. Higher concentrations of salt and detergent will give cleaner results. However, balance must be achieved between low background and detrimental effects on the target.  If the buffer is too stringent, it will destroy specific antibody interactions, resulting in low signal.  If the buffer is not stringent enough, non-specific interactions will remain, resulting in high background. NP-40 can be used as a detergent, while RIPA is commonly used for X-ChIP.

ChIP with low cell numbers

Standard ChIP workflows require a large number of cells. Approximately 10⁶ to 10⁷cells as starting material, below which the assay is hindered by high background binding, poor enrichment efficiencies and loss of enriched library complexity. However, these large sample sizes can be difficult to obtain, specifically when examining precious sample types like transgenic mouse tissues or clinical samples. To adjust for lower sample inputs, a number of strategies can be applied.

1. Improving enrichment efficiency and minimizing sample loss

Several adjustments to the ChIP workflow can increase enrichment efficiency and minimize sample loss for low input samples.

•          The quality and properties of the sample itself are important considerations. Specifically, in formalin-fixed paraffin embedded (FFPE) samples, over-cross-linking can cause problems. Methods to extract soluble chromatin from FFPE samples may help.

•          The kinetics of the immunoprecipitation with low concentrations of antigen can be optimized by modifying variables like buffer pH, ionic strength, and time of incubation.

•          Broad DNA fragment size distribution hinders analysis of low-input ChIP, which can be remedied by more limited sonication and/or MNase digestion for more uniform fragmentation.

•          While bacterial DNA is sometimes used as a blocking agent to reduce background for standard ChIP, it is not advised for low-input ChIP as it carries through the assay and confounds data analysis. Other blocking agents such as inert proteins or mRNA can reduce background binding in low-input ChIP, without contaminating the data.

•          Miniaturization of the assay into microwell formats facilitates automation and increases concentration of the antigen (target transcription factor) during the IP workflow –  this avoids the “dilution effect” of low antigen concentrations that favor dissociation of the antibody:antigen complex and decreases the efficiency of ChIP.

•          Maximize sample retention with single-tube assay formats and the use of magnetic bead purification rather than phenol-based extraction after each assay step.

•          The immobilization of antibody and washes to remove non-antibody bound material is often overlooked. Standard protocols use Protein A/G, but alternatives like epitope-tagged proteins may run the risk of over-expression and introduction of artifacts.

2. Readout and downstream data processing platforms

In addition to the assay itself, the choice and optimization of downstream processing (ie sequencing, array, or PCR) and bioinformatic analysis are also important.

•          The detection platform impacts assay sensitivity. ChIP-sequencing (ChIP-seq) is the gold standard platform for high sensitivity, with consistently lower noise than ChIP-on-chip.

•          The most common issues in low-input ChIP-seq are high numbers of unmappable reads, PCR duplicates, and poor library complexity. Therefore library preparation must be optimized for low input samples by optimization adapter ligation to avoid amplification-derived error and bias. Maximizing the efficiency of ChIP enrichment, as described above, can also help.

​•          Bioinformatic workflows should be adapted to take into account likely process-derived biases in the data.

ChIP from tissue

​​Examining epigenetic mechanisms in specific tissues can reveal essential elements of tissue-specific genetic programming, development, and biological processes. ChIP can be a valuable tool for examining roles and mechanisms of tissue-specific transcription factors, gene activation and other aspects of epigenetic regulation.  To perform ChIP from tissue samples requires specialized chromatin preparation protocols to ensure quality input material and reliable results.

For more information, you can find our ChIP from tissue samples protocol here. 

Troubleshooting

Even with optimization, your results may not be perfect on the first attempt.  Here you can find some common issues and solutions you can use to fix them.

High background in non-specific antibody control

Low signal

Note: Low signal may be real, with no antibody enrichment at the region of interest.

Include positive control antibody and locus to confirm ChIP is working. The antigen may be present, but not at the expected genomic loci.

Low resolution with high background across large regions

PCR amplification problems:

High signal in all samples after PCR including non-template control

No DNA amplification in samples

What other treatments might affect my ChIP results?

Some antibodies are affected by relatively low concentrations of SDS. TSA, butyrate or colcemid addition do not generally affect ChIP.

ChIP readout

​​Once pulled down DNA fragments have been immunoprecipitated and purified, they can be analyzed by a number of different methods.

qPCR

Utilizes gene or target-specific primers to amplify known target loci among pulldown DNA

Limitations:

• Must know the genome sequence of target regions to design primers for readout

ChIP-on-Chip

Employs microarrays to examine the presence of many loci of interest, specific domains, etc. across the genome. Pulldown and control samples are amplified and labeled with complementary fluorescent probes. Samples are combined and hybridized to microarray of interest. The ratio of fluorescent signals indicates enriched regions where proteins of interest have bound.

Limitations:

• Requires large cell numbers
• Not sensitive to repetitive elements
• Large number of arrays are necessary to cover the entire genome
• Susceptible to amplification bias after the ChIP procedure
• Lower resolution than ChIP-seq

ChIP-seq

Most commonly used method for genome-wide analysis with improved base pair resolution and none of the limitations of ChIP-on-Chip. Pulldown DNA and control samples are amplified, followed by high throughput sequencing of the fragments, which are then aligned to the genome. Overlapping fragments form a peak, indicating where the protein of interest was bound to the genome.

Data analysis

Data should always be normalized for the amount of starting material to eliminate errors introduced by uneven sample quantities. To normalize data, take the final amplicon value and divide it by the amplicon value of input material. For histone modifications, the immunoprecipitated material is usually normalized to the input amount and the amount of the relevant immunoprecipitated histone. For example, ChIP with an H3K4me3 antibody will be expressed relative to the input amount and the amount of H3 immunoprecipitated.

Measuring the amounts (and quality) of starting material is the key to interpreting your results effectively.

Tutorial for ChIP-seq data analysis using online software

While ChIP-seq data analysis can be complex, it is arguably the most important part of the experiment. Robust data analysis is key to accurate and reliable results. A combination of online tools makes data interpretation accessible to bioinformatics specialists and wet lab biologists alike. 

This step-by-step guide demonstrates how to extract reliable results from ChIP-seq data, and how to interpret data sets for successful ChIP-seq analysis. For more information, see Abcam’s data analysis webinar here. 

This webinar covers the following steps of ChIP data analysis:

1.         QC of sequencing reads (FastQC)

2.         Read alignment/mapping (Galaxy/bowtie)

3.         Peak calling (Galaxy/macs)

4.         Binding signal visualization (UCSC genome browser)

5.         De novo motif discovery (MEME-ChIP)

6.         Gene ontology of binding sites (GREAT)

7.         Heatmap representation of binding signals (seqMINER)

4. DNA methylation and demethylation

​

​​

​

^{Figure 6: Bisulfite conversion. Treatment of DNA with bisulfite (sulphonation) leads to the deamination of cytosine residues and converts them to uracil, while 5-methylcytosine residues remain the same}

Bisulfite-based applications

Bisulfite conversion has become the basis for several variations and applications designed for high throughput applications or the investigation of broader, whole genome-scale regions.
Here are so examples of bisulfite-based methods.

Genome-wide DNA methylation analysis:

Whole genome bisulfite sequencing (WGBS; Lister et al 2009) applies next-generation sequencing (NGS) techniques to bisulfite-converted input samples. WGBS produces single-base resolution DNA methylation maps that span the entire genome of an organism.

Reduced representation bisulfite sequencing (RRBS; Meissner et al., 2005) Combines the single-base resolution of bisulfite, and the genome-scale coverage of high throughput sequencing, with the use of methylation-sensitive restriction enzymes to enrich samples for high CpG content. This approach effectively limits sequencing to only the regions of high interest, where DNA methylation exists.

Targeted DNA methylation analysis:

Methylation-specific PCR (MS-PCR; Herman et al., 1996) applies PCR primers specific to bisulfite converted DNA templates that are either methylated or unmethylated. The differential PCR amplification indicates if DNA methylation modifications are present.

Pyrosequencing (Colella et al., 2003; Tost et al., 2007)also known as sequencing by synthesis and can interrogate bisulfite converted DNA at a specific region of interest. The level of 5-mC is determined by comparing the ratio of C and T bases at an individual locus.

High resolution melting (HRM) analysis (Wojdacz and Dobrovic, 2007)originally applied to SNP detection, but the process has also been adopted for DNA methylation. The real-time PCR-based protocol measures melting temperatures of PCR amplicons. The shift in melting temperatures, which vary on C-T content, corresponds to the level of DNA methylation in the sample.

Methylation-sensitive single-nucleotide primer extension (MS-SnuPE; Gonzalgo ​and Jones PA, 1997) queries a CpG of interest by targeting bisulfite specific primers to the sequence immediately preceding a CpG. DNA polymerase terminating dideoxynucleotides allow the primer to extend a single base, which then can be quantitatively measured to determine C-T content, determining its DNA methylation status.

Bisulfite conversion: technical considerations
Incomplete conversion. Bisulfite conversion is a very powerful method because it is relatively simple to perform, and it can deliver single-base resolution of DNA methylation status. However, the method does have some drawbacks, which should be considered by researchers. Incomplete conversion (or on occasion, over-conversion) can occur under sub-optimal reaction conditions leading to insufficient DNA denaturation, or when the DNA strands re-anneal before completion of the reaction.

Distinguishing 5hmC. DNA degradation is often a by-product of the harsh bisulfite conversion reaction conditions. This can make working with smaller samples challenging. Insufficient desulfonation of the reaction will leave behind residues that can inhibit DNA polymerases used in PCR. Recent evidence indicates that bisulfite conversion does not distinguish between 5-mC and 5-hmC Bisulfite conversion lowers the overall complexity of the DNA sequence by essentially reducing the number of bases present from four to three. This can complicate primer design for downstream PCR-based interrogation or introduce challenges when attempting to uniquely map sequencing reads to a reference genome.

DNA immunoprecipitation (DIP)

Another method commonly used to map the location of DNA methylation marks is DIP. DIP relies heavily on having antibodies capable of recognizing the DNA modifications in which you are interested. However, once you have this, DIP is a straightforward and effective method. It is also considerably cheaper and easier to analyze compared to WGBS sequencing which requires the whole genome to be sequenced. DIP only requires sequencing of the small sheared DNA regions pulled down in your IP step.

So far DIP has been successfully carried out for the most well-characterised DNA modifications; 5mC, 5hmC, 5fC, and 5caC (Pastor et al 2011, Shen et al 2013). It has been used in a range of samples including embryonic stem (ES) cells, brain tissue, and zebrafish fish embryos. The method is similar to ChIP, but your starting material is raw genomic DNA with no chromatin required. This genomic DNA will undergo shearing to approximately 150-300bp, and then this sheared DNA can undergo heat denaturation. This step is essential as the antibody will only be able to access the modifications within denatured (open) DNA.

After DNA denaturation the sheared DNA will incubate with the antibody recognizing your modification of interest, usually overnight, and then the samples can under an IP step to pull down all the DNA bound to the antibody and washing away any unbound DNA. We recommend using magnetic beads for this type of IP step. When you carry out DIP, it is important to treat your initial genomic DNA with RNase to remove any RNA from the samples.

DIP based applications

Genome-wide DIP analysis:

DIP-sequencing

• DIP is combined with NGS to map the location of DNA modifications across the whole genome.
• Due to the conservation of these chemical structures between species, it has been very easy for researchers to sequence their DNA modification of choice in any organism.
• The library prep and analysis of DIP-sequencing is very similar to that of ChIP-sequencing.
• The small DNA fragments pulled down in your IP are used in library prep, and these can be sequenced at a relatively low read depth compared to WGBS as you are more selective about what you sequence, ie only regions bound to your antibody.

Targeted DIP analysis:

DIP-PCR

• The pulldown DNA you obtain from your IP as described in the DIP-sequencing section above. However, this time instead of using the sheared DNA for library prep you can use it in a qPCR as template DNA.
• When you design primers for this type of DNA you have to consider that the template being genomic DNA will contain both exons and introns. This method can be very effective to determine levels of a modification across samples.
• It can be tricky to compare levels of different modifications as many factors including antibody affinity can affect this.

DIP: technical considerations
Shear your samples appropriately. Unlike WGBS, DIP is not single base resolution. When you are shearing your DNA samples, it is important to get these DNA fragments to a good size of between 150-300bp to try to improve the resolution of your DIP sequencing. Having larger fragments means you will inevitably pull down more DNA flanking your DNA modification of interest and not physically bound to it. This results in broad, unspecific peaks in your sequencing analysis.

Get good antibodies. Another problem with DIP is that you need to have an antibody specific for your modification of interest. You need to make sure there is minimal cross-reactivity with other similar modifications for example if your 5fC antibody also recognizes 5hmC, this is not ideal for mapping the location of 5fC throughout the genome. The use of antibodies for this type of sequencing also has many advantages. You are only limited by the antibodies available to you. If you wanted to investigate a modification not previously characterized in DNA, eg m6A (more commonly associated with RNA), you could provided you have a good m6A antibody. 

Alternative methods to capture 5hmC, 5fC, and 5caC

The biggest drawback of traditional bisulfite sequencing is that it is unable to distinguish the oxidized derivatives of 5mC and will profile only 5mC itself. Fortunately, there have been many variations on bisulfite sequencing and some entirely new approaches to tackling the problem of sequencing 5hmC, 5fC, and 5caC. Here we look at some of these new methods in more detail.

5hmC mapping

Tet-assisted bisulfite sequencing (TAB-seq; Yu et al 2012)

• This method relies on the conversion of 5hmC into 5gmC. The addition of glucose in this glucosylation reaction acts to protect the 5hmC.
• TET enzymes are then added to the genomic DNA to convert all 5mC and 5fC present into 5caC. After Bisulphite conversion 5hmC is read as C.
• 5caC and unmethylated cytosines are all read as T. This method gives a clear differentiation between 5mC and 5hmC.
• The problems with this method are that all the conversions to T can make it difficult to map the end sequences produced. It also requires very deep sequencing to get full coverage of the genome, so this can be more expensive than other methods.

Oxidative bisulfite sequencing (oxBS-seq; Booth et al 2012)

• This is another method for detecting 5hmC at single-base resolution. This method uses potassium perruthenate (KRuO₄) to chemically convert of 5hmC to 5fC.
• After this conversion, all 5mC remains unchanged. Subsequent bisulfite treatment and sequencing allows you to distinguish between 5mC and 5hmC sites by comparing the KRuO₄ treated and untreated samples.

hMe-Seal. (Song et al 2011)

• Similar to TAB-seq, hMe-Seal starts with the glucosylation of 5hmC to 5gmC.
• However, in this method, the added glucose molecule is engineered to contain an azide group which can be chemically modified with biotin.
• 5hmC can then be enriched within the genome using the tight binding between biotin and streptavidin to carry out a pull-down for 5hmC.

Selective chemical labeling with exonuclease (SCL-exo; Sérandour et al 2016)

• The initial steps for this are the same as hMe-Seal, azide-glucose glycosylation of 5hmC.
• Azide reaction with biotin allows for the 5hmC present to be linked to streptavidin however in this method the captured DNA undergoes exonuclease digestion which will stall at the biotin-5gmCs.

5fC/5caC mapping

M.SssI methylase-assisted bisulfite sequencing (MAB-seq; Wu et al 2014)

• This method can quantitatively measure 5fC and 5caC at single-base resolution. This is achieved using M.SssI methyltransferase on your DNA to convert all unmodified cytosine to 5mC.
• After bisulfite-treatment, all newly modified C’s, 5mC, and 5hmC will be read in the sequencing as C, but all the 5fC and 5caC in the genome will be read as T.
• If you compare this to sequencing carried out without M.SssI treatment you can determine where the 5fC and 5caC modifications are within the genome.
• The biggest problem with this method is that is doesn’t differentiate between 5fC and 5caC.

5fC chemically assisted bisulfite sequencing (fCAB-seq; Song et al 2013)

• This technique relies on the chemical protection of 5fC using O-ethylhydroxylamine (EtONH₂).
• This protection prevents bisulfite-mediated deamination of 5fC, and so this will appear as a C in the sequencing results (the same as 5mC and 5hmC).
• When this is compared to a sample not treated with EtONH₂ (where all 5fC modifications would be read as T), you can distinguish all the sites in the genome which have a 5fC.

5caC chemically assisted bisulfite sequencing (caCAB-seq; Lu et al 2013)

• caCAB-seq uses the modification of 5caC within the genome using 1-ethyl-3-[3-dimethylaminopropyl] carbodiimide hydrochloride (EDC) to catalyze the formation of amide bonds to 5caC.
• This chemical modification prevents deamination of 5caC after bisulfite conversion allowing for it to be distinguished from 5fC in the sequencing.

Chemical-labeling-enabled C-to-T conversion sequencing (CLEVER-seq; Zhu et al 2017)

• CLEVER-seq is not only single base resolution but can also be used on single cells. It is just for sequencing 5fC distribution and not 5caC.
• This method uses malononitrile to selectively label 5fC creating a 5fC-M adduct which is read as a T in the sequencing.

Comparison of DNA modification sequencing methods

It is important that you choose the best method for detecting DNA modifications that suit your needs. Consider things like whether you need single-base resolution if you need to be able to quantify the absolute levels of the modification, and how feasible the method will be to use in your model system or sample type. Below you can find a table where we have summarized these key features for some of the available methods for sequencing 5hmC, 5fC, and 5caC.

Table: DNA modification sequencing methods

Liquid chromatography tandem-mass spectrometry (LC/MS-MS)

If you have access to LC-MS/MS, then this is the best way quantify the amount of a DNA modification within total genomic DNA (Le et al 2011 and Fernandez et al 2018). Using absolute quantification methods, LC-MS/MS gives you parallel quantification of all the DNA modifications found in total DNA from any organism and cell type (Zhang et al 2012). For absolute quantification, you are only limited which isotopic standards you have available to use as a standard to measure your sample against.

Using this technique combined with DIP (DIP-MS) will allow you to determine if your DNA modification antibody is binding to your modification of interest and it will also allow you to see if it binds any other non-specific modifications. If you generate LC-MS/MS data of your DIP input and pull-down samples, you should see an enrichment of your modification of interest in the pulldown sample compared to the input. You can also then check other modifications with these same data to see if anything else came out as enriched in your samples to test for non-specific antibody binding. There is software being developed now that can even help you with this type of analysis. 

LC/MS-MS: technical considerations

Technically challenging. Mass spec equipment is costly and very specialized. The machine itself will require an enormous amount of maintenance and often requires its own technician to keep on top of things. Operating the machine is very complicated and requires specialized training so it may be difficult to obtain this type of mass spec data on your own. Consider obtaining this data through collaborations or paid services if it is not feasible for you to purchase your own LC/MS-MS equipment.

DNA modification IHC/ICC

It is also possible to carry out IHC/ICC for DNA modifications. This can be done with a few simple additions to your standard IHC/ICC protocol. The most significant difference you will need to consider is that antibodies against DNA modifications cannot access and bind to the modification if it sits within double-stranded DNA. This means that you will need to denature the DNA making it single-stranded and accessible by the antibodies.

The most common way to achieve this is to treat your samples with acid. This is usually 4N hydrochloric acid (HCL) applied directly to you IHC/ICC slides (Yamaguchi et al 2013 and Kaefer et al 2016). The best time to add this step to your protocol is before the addition of the primary antibody. Once you have permeabilized your cells or tissues with a detergent (eg PBS 0.1% Triton) you can wash and add 4N HCl to denature the DNA strands. It is important to thoroughly wash the acid off once the step is complete and neutralize the acid with an alkali (eg 100 µM NaOH in PBS). After the acid is washed and neutralized you can proceed with your usual IHC/ICC steps and add the primary antibody.

When carrying out an IHC/ICC for DNA modifications you should also be wary that your antibody may recognize very similar modifications on RNA (eg 5mC on DNA and m5C on RNA). To avoid this problem, you can treat your samples with an RNase step to remove all RNA present. Again, this step should be optimized as leaving your sample in RNase for too long can also cause damage to the DNA present.

DNA modification IHC/ICC: technical considerations

Time your acid step.

• It is crucial that you optimize the concentration and timings of the acid step before you start using your experimental samples.
• Too long in acid treatment will ruin the samples but the timing needs to be long enough to denature the DNA fully.
• Tissue samples will require the acid treatment for longer than cells used for ICC. You could try a range of timings from 10 minutes up to 40 minutes and see how your signal looks after this.
• ICC should only need 5–10 minutes maximum but again, it is important to test this first and optimize correctly.

Double IHC/ICC.

• It can be difficult to carry out double IHC/ICC with a DNA modification given the effects of the acid treatment step. The acid treatment may denature proteins present in the sample or degrade epitopes required for recognition by your second primary antibody.
• If you want to carry out such a double immuno it will require careful optimization. Try to minimize the amount of time your sample spends in the acid treatment step to reduce damage to other proteins. You could also consider doing the primary antibody steps sequentially.
• For example, after you have applied the first primary antibody fix this with a formaldehyde-based fixative before the acid treatment step and adding the second primary antibody (eg the DNA modification antibody).

Choose the right DNA stain.

• You may find that because of the acid treatment step you cannot use your standard DNA stain. For example, DAPI may not bind so well as this recognizes the adenine-thymine bases present within double-stranded DNA.
• A good alternative commonly found in most labs is propidium iodide (PI). PI will recognize both double-stranded and single-stranded nucleotide chains.
• This means it will also pick up any RNA in your samples, so watch out for this. You can also find many commercially available DNA stains which will recognize single-stranded DNA.
  
  

Methyl binding domain (MBD) proteins

5mC and its oxidized derivatives play an important role in gene silencing and promoting gene expression after DNA demethylation. It is now known that some of these DNA modifications can act as markers to recruit proteins to specific DNA sites, altering gene expression and acting as epigenetic marks. MBD3 and methyl CpG binding protein 2 (MECP2) have both been shown to bind 5hmC in addition to 5mC. Once bound to 5hmC they play a role in DNA accessibility and activation of transcription (Yildirim et al 2011 and Mellén et al 2012).

A common method to screen for binders of a DNA modification is to use a pull-down technique followed by mass spec to screen for any proteins pulled down. This method has been successfully used to find binders of 5mC, 5hmC, and 5fC (Iurlaro et al 2013 and Sprujit et al 2013). For this experiment, you need to create a synthetic DNA bait containing the modification you are interested in as well as baits containing other modifications and unmodified cytosine to act as controls. This DNA bait should be linked to a biotin molecule at one end that can be used to tether the bait to streptavidin-linked magnetic beads. Protein extract from your sample of interest can then be added to the tethered bait and flushed through with various wash steps to remove any non-specifically bound proteins. After this, you can elute the remaining proteins and carry out mass spec analysis to find out what your specific binders are.

MBDs: Technical considerations

DNA sequence.

• When you design your synthetic DNA sequence, you may need to consider that the sequence itself may affect which binders you pull-down.
• You may have a sequence in mind that you wish to use as bait, the promoter region of your gene of interest for example.
• Having a variety of sequences to use in your experiment will help to ensure that it is the modification which is the critical factor and not the DNA sequence.

The number of modifications.

• The number of DNA modifications you have within your sequence may also influence the proteins binding to your bait.
• You should consider having just one modification or multiple modifications in a sequence to see how this is influencing your result.

Washing.

• If you want to be sure that the proteins binding to your bait are true binders of your modification it is important to carry out very stringent washing.
• You can try high salt washes to ensure you are removing everything non-specifically bound. You also run the risk of removing everything, so you need to optimize this step to get the best results.

Novel DNA modifications

New DNA modifications could still be out there, just not discovered yet. It has been demonstrated that some modifications traditionally considered to be RNA modifications may also be present within DNA. One good example of this is N6-adenine methylation, known as m6A within RNA and 6mA within DNA. This modification is one of the most famous and abundant RNA modifications, but now it’s known to also reside within DNA. One of the first studies to show this was from John Gurdon’s lab in 2016 (Koziol et al 2016). They show that 6mA is within the Xenopus laevis, mouse, and the human genome. They achieve this using an antibody against 6mA to carry out DIP-seq.

Since this study, there have been several more claims that 6mA is present within DNA. Shortly after the paper from the Gurdon lab, there have been other studies showing 6mA present in the zebrafish and pig genomes (Liu et al 2016), within the mouse brain following environmental stress (Yao et al 2017), and within the Arabidopsis thaliana genome (Liang et al 2018). One study from 2018 took this one step further and uncovered the enzymes responsible for 6mA methylation and demethylation N6AMT1 and ALKBH1 respectively (Xiao et al 2018). The presence of enzymes actively adding and removing the DNA modification suggests that it has a real purpose to be there and potentially its own epigenetic function.

Novel DNA modifications: technical considerations

Antibody availability.

• Until single-base resolution methods are available for individual modifications, many studies rely heavily on the use of antibody-based pulldown (DIP-seq) to look for novel modifications within DNA.
• The biggest problem here is that you are then reliant on there being a specific, commercially available antibody for your modification which is quite often not the case. Many RNA modification antibodies will also recognize modifications within DNA, so this is one approach you could take.
• Treating your samples with RNase will help to ensure that you are targeting just DNA with your antibodies. 

5. RNA modifications

The field of epigenetics is branching down many new and exciting avenues. One of these avenues is the area of RNA modification research. Recent advancements in the development of RNA modification detection and sequencing methods eg miCLIP has meant that it is becoming easier and faster to discover new modifications and map them to different species of RNA within any cell type or model organism. The advancements in this technology lead to a boom in the number of known RNA modifications. Currently, there are over 100 known RNA chemical modifications. You find these on mRNA, tRNAs, rRNAs and other non-coding RNAs including miRNAs. Each of these modifications also has its own functions including RNA structure, export, stability, and mRNA splicing. The future is bright for this field of research; there is still much to uncover regarding the function of some of these new exciting modifications.

​​

^{Figure 7: The distribution of RNA modifications on mRNA and tRNAs. To find out more take a look at our RNA modifications poster here.}

^​​Of all the RNA species, tRNAs contain the most RNA modifications. Almost one in five nucleotides within tRNAs are thought to contain RNA modifications. The modifications on tRNA are incredibly diverse. Some modifications require step-by-step formation by multiple enzymes. You can commonly find modifications in the anticodon loop of the tRNA. These are found here help promote translation efficiency by aiding codon-anticodon interactions and preventing frameshifting.

The field of RNA modifications is relatively new but growing more and more every day. We know that working with these modifications can be tricky and that is why we are constantly adding to our RNA modifications range and providing new protocols and content to help you with your reseach. In this section, we will go through some of these protocols and offer a few tips and advice for working with RNA modifications. 

RNA modification antibodies

We know that working with RNA modifications can be tricky and that is why we are adding to our RNA modifications range all the time to get reagents for the newest and most exciting modifications before anyone else. We also know that getting antibodies truly specific to your RNA modification of choice can be difficult, so we use multiple applications to test the specificity of all our antibodies. Check out our RNA modification antibodies control page for more details on what you can do to check that your antibodies work in your model system.

You can get the best reagents for your RNA modification research right here. Our m6A antibody has been cited in several great publications including a Nature Methods paper which uses it for single-base resolution sequencing of m6A. This same m6A antibody also features in a Nature paper, looking at the role of m6A in mRNA stability. For a full list of our RNA modification antibodies go to www.abcam.com/RNAmods

RNA modification antibodies: technical considerations

Antibody specificity and consistency. It is important to be sure that the antibody you are using is specific for the modification you are interested by using the right controls and testing the antibody in your model system. Once you have a working antibody you should ensure that between batches you are still getting specificity. Recombinant RabMAb^® technology eliminates batch-to-batch variation by using the same immunogen for each round of antibody production. This gives you a consistent antibody and reproducible results throughout your project. Many of our RNA modification antibodies are RabMAb^® monoclonal antibodies including key targets such as m6A, m1A, Mettl3, m2,2G, and many more.

RNA immunoprecipitation (RIP)

RIP is an antibody-based technique used to map in vivo RNA-protein interactions. The RNA binding protein (RBP) of interest is immunoprecipitated together with its associated RNA for identification of bound transcripts (mRNAs, non-coding RNAs or viral RNAs). Transcripts are detected by real-time PCR, microarrays or sequencing.

The fields of epigenetics and RNA biology has recently seen a huge increase in the interest of different RNA roles and functions. Beyond transcription and subsequent translation, it has been observed that there is much more to the function of RNA. For example, RNA-protein interactions are able to modulate mRNA and noncoding RNA function. This new appreciation for the potential of RNA has lead to the development of novel methods allowing researchers to map RNA-protein interactions. RIP is one such protocol allowing the study of the physical association between individual proteins and RNA molecules.

Take a look at our full RIP protocol here. 

RIP: technical considerations

RNase contamination. Avoid contamination using RNase-free reagents such as RNase-free tips, tubes, and reagent bottles; also use ultrapure distilled, DNase-free, RNase-free water to prepare buffers and solutions.

Plan your controls carefully. One or more negative controls should be maintained throughout the experiment, eg no antibody sample or immunoprecipitation from knockout cells or tissue. Knockdown cells are not recommended for negative control experiments.

Downstream analysis. The RNA isolated from your pulldown can be analyzed using several techniques. Choose the best method based on the questions you want to answer and use multiple methods to confirm your results. For example, any novel results you obtain using RIP-seq should then be confirmed using RIP-qPCR.

CLIP

Interest in RNA-protein interactions is booming as we begin to appreciate the role of RNA, not just in well-established processes such as transcription, splicing, and translation, but also in newer fields such as RNA interference and gene regulation by non-coding RNAs.

CLIP is an antibody-based technique used to study RNA-protein interactions related to RNA immunoprecipitation (RIP) but differs from RIP in the use of UV radiation to cross-link RNA binding proteins to the RNA that they are bound to. This covalent bond is irreversible, allowing stringent purification conditions. Unlike RIP, CLIP provides information about the actual protein binding site on the RNA.

Different types of CLIP exist, high-throughput sequencing-CLIP (HITS-CLIP), photoactivatable-ribonucleoside enhanced CLIP (PAR-CLIP), and individual CLIP (iCLIP).

You can find our full CLIP protocol a summary of the iCLIP protocol adapted from Konig et al. J. Vis. Exp. 2011. “iCLIP -Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution” here. 

CLIP: technical considerations 

4-thiouridine pre-incubation. Optional 4-thiouridine pre-incubation and UV-A crosslinking may be necessary for certain proteins. 4-thiouridine enhances crosslinking of some proteins. Details for this can be found in the complete protocol.

Optimize antibody concentration. The amount of antibody required might need to be optimized before you start your experiment. A no-antibody sample is a good negative control. If your target of interest has not been studied using CLIP before you could start by using an antibody which is working in IP, this is a good indication that it will work in CLIP.

miCLIP

A well-known paper from the laboratory of Samie Jaffrey at Cornell University outlines a new approach for high-resolution localization of N6-methyladenosine in eukaryotic RNA, called m6A individual-nucleotide-resolution cross-linking and immunoprecipitation (miCLIP).

Although m6A is the most abundant modified base in eukaryotic mRNA, current methods to accurately study it have limitations. New approaches to high-resolution mapping of m6A will be essential for understanding this epigenetic RNA modification.

miCLIP allows for high-resolution detection of single m6A residues and m6A clustering across the entire RNA. Using miCLIP, the researchers were able to map m6A and the related dimethylated version m6Am (N6,2′-O-dimethyladenosine), at single-nucleotide resolution in human and mouse mRNA.

Additionally, the development of miCLIP lends new insight into the m6Am modification, occurring at the 5’ transcription start site. This facilitates research into the poorly understood function of this unique epigenetic signature in RNA.

miCLIP is applicable to smaller RNAs. The authors of this protocol discovered that m6A is present in small nucleolar RNAs (snoRNAs), a class of small non-coding RNAs. This was impossible to establish with previous applications due to lack of specificity and bioinformatic challenges.

You can find our full miCLIP protocol here. 

miCLIP: technical considerations 

Not 100% precise. The method is unable to identify the specific location of modified residues and only determines the general location of m6A sites

Bias in bioinformatic m6A calling. Data analysis uses assumptions based upon known consensus sequences that harbor m6A residues so modifications outside these motifs are missed.

Liquid chromatography tandem-mass spectrometry (LC/MS-MS)

​Similar to DNA modifications, if you have access to LC-MS/MS, then this is the best way quantify the amount of RNA modification within total genomic DNA. Also similar to measuring DNA modifications you can use absolute quantification methods limited only by which isotopic standards you have available to use as a standard to measure your sample against.

Using this technique combined with RIP (RIP-MS) will allow you to determine if your RNA modification antibody is binding to your modification of interest and it will also allow you to see if it binds any other non-specific modifications. If you generate LC-MS/MS data of your RIP input and pull-down samples, you should see an enrichment of your modification of interest in the pulldown sample compared to the input. You can also then check other modifications with these same data to see if anything else came out as enriched in your samples to test for non-specific antibody binding.

LC/MS-MS: technical considerations

Technically challenging. Mass spec equipment is costly and very specialized. The machine itself will require an enormous amount of maintenance and often requires its own technician to keep on top of things. Operating the machine is very complicated and requires specialized training so it may be difficult to obtain this type of mass spec data on your own. Consider obtaining this data through collaborations or paid services if it is not feasible for you to purchase your own LC/MS-MS equipment.

RNA modification control experiments

When you are working with RNA modification antibodies, it is essential to be sure that they are specific – only binding to the correct modification. Due to the nature of RNA modifications their chemical structures are often very similar. To make sure you are getting the most accurate results from your antibodies, you need to test them in your model system thoroughly. Controls for RNA modification antibodies can be done using a range of applications. See below for some of our advanced controls and tips to make your RNA modification research easy.

RNase treatment

Whether you are carrying out ICC/IHC or RIP-qPCR, it is essential to have an RNAse treated control alongside your experimental samples. For example, if you see a clear bright signal in your experimental IHC samples, but you get no signal in your RNAse treated control samples, you can be confident that the signal you are getting is within the RNA and is not background signal from a non-specific source. This suggests that the antibody is recognizing the modification within RNA and not the DNA.

• It is crucial to ensure that you are not picking up high levels of non-specific background signal from DNA when using RNA modification antibodies. You can quickly add an RNase treatment step to your normal RNA modification IHC or RIP protocol. It is important not to leave the samples in the RNase solution for too long, this can lead to degradation of the DNA, and this then makes it difficult to carry out counterstains such as DAPI.
• For each different sample type, you should test different concentrations of RNase and try leaving on your samples for varying lengths of time. For example, an IHC may need an RNAse time of up to an hour depending on the tissue type whereas an ICC will require much less time – try 10–30 mins as a starting point.

Whether you are carrying out ICC/IHC or dot blot, it is essential to have an RNAse-treated control alongside your experimental samples1 to ensure that you are not picking up non-specific background signal from DNA when using RNA modification antibodies. For example, if you see a clear, bright signal in your experimental IHC samples, but you get no signal in your RNAse-treated control samples, you can be confident that the signal you are getting is from the RNA and not background signal from a non-specific source. This suggests that the antibody is recognizing the modification within RNA and not the DNA. 

You can quickly add an RNase treatment step to your normal RNA modification IHC, RIP, or dot blot protocol.

• It is important not to leave the samples in the RNase solution for too long, as this can lead to degradation of the DNA, which makes it difficult to carry out counterstains such as DAPI.
• For each different sample type, you should test different concentrations of RNase and try leaving on your samples for varying lengths of time. For example, an IHC may need an RNAse time of up to an hour depending on the tissue type whereas an ICC will require much less time – try 10–30 mins as a starting point.

DNase treatment

In addition to RNase-treated controls, you should carry out DNAse-treated controls. If you are concerned that your RNA modification antibody is recognizing a similar modification within DNA, the best way to test for this is to treat your samples with DNAse. Many modifications are within both RNA and DNA, so this is a common problem. For example, 5mC within DNA has the same chemical modification as m5C within RNA.

• ​If you carry out IHC using an RNA modification antibody, it is a good idea to have a DNAse-treated control alongside your experimental samples. If you get a clear, strong signal from your experimental samples, but your DNAse-treated control has no signal, it suggests that your antibody is binding to a modification within DNA.
• For this type of control, it is also important to optimize the conditions. Leaving your samples in DNAse treatment for too long can lead to degradation of RNA, so be sure to test different DNAse concentrations and the duration of the treatment.

Competition assays

Another way to ensure the specificity of your RNA modification antibody is to use a competition assay. This assay uses a synthetic modification-containing oligonucleotide which can be pre-incubated with your antibody2. When you then use this pre-incubated antibody for your applications, eg ICC/IHC or dot blot, you should see a reduction in the signal obtained when compared a sample stained with the antibody alone. You can try adding the competitor oligonucleotide to your antibody solution at increasing concentrations. You will expect to see a decreasing gradient of the signal reflecting the amount of competitor you add to the antibody. For example try a gradient of 0 ng, 10 ng, 100 ng, and 1µg of the competitor oligonucleotide.

Dot blot

Carrying out a dot blot using RNA modification antibodies can be a quick and simple way to test for their specificity. A dot blot works like a simplified version of a western blot. For this technique, the sample is spotted directly on to the membrane, cross-linked, and then undergoes blotting. For more details take a look at our dot blot protocol here. If you have access to synthetic RNA molecules containing your modification of interest, this can act as the perfect positive control2. Similarly, loading an unmodified molecule or a molecule containing a different modification can serve as a negative control and help you to gauge any non-specific binding or cross-reactivity.

• For your experimental samples, it is possible to test whether your RNA modification antibody is specific by carrying out a dot blot with the right controls. For a negative control, use samples that contain a knockout (KO) for the enzyme responsible for producing your specific RNA modification, eg ALKBH5 for m6A3,4.
• If you load RNA from your wild-type and KO samples onto a membrane for dot blot, you should see a clear difference between the two samples. The wild-type sample will display a clear signal and the KO should appear blank when the membrane is stained using an antibody against your RNA modification of interest. 

RIP-MS

If you have access to liquid chromatography tandem-mass spectrometry (LC-MS/MS), then this is really the best way to test for RNA modification antibody specificity5. Using this technique combined with RIP (RIP-MS) will allow you to determine if your antibody is binding to your modification of interest and it will also allow you to see if it binds any other non-specific modifications. For more information on RIP take a look at our RIP protocol here. Or take a look at our miCLIP protocol, optimized for use with our m6A antibody6.

• Using either absolute or relative quantification methods, LC-MS/MS gives you parallel quantification of all the RNA modifications found in total RNA from any organism and cell type. If you generate LC-MS/MS data of your RIP input and pull-down samples you should see an enrichment of your modification of interest in the pulldown sample compared to the input.
• You can also then check other modifications with these same data to see if anything else came out as enriched in your samples to test for non-specific antibody binding. There is software being developed now that can even help you with this type of analysis. 

Use a well-established antibody

The distribution of abundant RNA modifications such as m6A is well characterized in many model systems. If the modification you are interested in is less well known, you could use a modification such as m6A as a positive control for many applications. For example, if you are carrying out RIP-qPCR and you want to be sure that technically the experiment has worked, you could carry out RIP-qPCR for m6A alongside your experimental samples and choose regions of the transcriptome previously shown to contain m6A as positive control regions. This will help to ensure that your buffers, other reagents, and method are all working fine before you try with a novel modification.

Part 1 references
^{Belton JM, McCord RP, Gibcus JH, Naumova N, Zhan Y and Dekker J (2012). Hi-C: a comprehensive technique to capture the conformation of genomes. Methods, 58, 268-76.
Dekker J, Rippe K, Dekker M and Kleckner N (2002). Capturing chromosome conformation. Science, 295, 1306-1311.
Dekker J. (2006). The three ‘C’ s of chromosome conformation capture: controls, controls, controls. Nat Methods, 3, 17-21.
Dostie J and Dekker J (2007). Mapping networks of physical interactions between genomic elements using 5C technology. Nat Protoc, 2, 988-1002.
Dostie J, Zhan Y and Dekker J (2007). Chromosome conformation capture carbon copy technology. Curr Protoc Mol Biol, Chapter 21, Unit 21.14.
Horike S, Cai S, Miyano M, Cheng JF and Kohwi-Shigematsu T (2005). Loss of silent-chromatin looping and impaired imprinting of DLX5 in Rett syndrome. Nat Genet, 37, 31-40.
Fullwood MJ, et al.  (2009). An oestrogen-receptor-alpha-bound human chromatin interactome. Nature, 462, 58-64.
Lieberman-Aiden E, et al. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326, 289-293.
Hughes JR (August 2014). Email interview.
Hughes JR, et al. (2014). Analysis of hundreds of cis-regulatory landscapes at high resolution in a single, high-throughput experiment. Nat Genet, 46, 205-212.
Simonis M, Kooren J and de Laat W (2007). An evaluation of 3C-based methods to capture DNA interactions. Nat Methods, 11, 895-901.
van de Werken H, de Vree PJ, Splinter E, Holwerda SJ, Klous P, de Wit E and de Laat W (2012). 4C technology: protocols and data analysis. Methods Enzymol, 513, 89-112}
​

Part 4 references

^{Booth, M. J., Branco, M. R., Ficz, G., Oxley, D., Krueger, F., Reik, W., & Balasubramanian, S. (2012). Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution. Science, 336(6083), 934–937. https://doi.org/10.1126/science.1220671}

^{Colella, S., Shen, L., Baggerly, K. A., Issa, J. P. J., & Krahe, R. (2003). Sensitive and quantitative universal PyrosequencingTM methylation analysis of CpG sites. BioTechniques, 35(1), 146–150. https://doi.org/10.2144/03351md01}

^{Fernandez, A. F., Valledor, L., Vallejo, F., Cañal, M. J., & Fraga, M. F. (2018). Quantification of Global DNA Methylation Levels by Mass Spectrometry. In J. Tost (Ed.), DNA Methylation Protocols (pp. 49–58). New York, NY: Springer New York. https://doi.org/10.1007/978-1-4939-7481-8_3}

^{ML., G., & PA., J. (1997). Rapid quantitation of methylation differences at specific sites using methylation-sensitive single nucleotide primer extension (Ms-SNuPE). Nucleic Acids Research, 25(12 PG-2529-31), 2529–2531.}

^{Herman, J. G., Graff, J. R., Myohanen, S., Nelkin, B. D., & Baylin, S. B. (1996). Methylation-specific PCR: A novel PCR assay for methylation status of CpG islands (DNA methylation/tumor suppressor genes/pl6/p15). Proceedings of the National Academy of Sciences of the United States of America, 93(September), 9821–9826. https://doi.org/10.1111/j.1442-200X.2011.03428.x}

^{Kafer, G. R., Li, X., Horii, T., Suetake, I., Tajima, S., Hatada, I., & Carlton, P. M. (2016). 5-Hydroxymethylcytosine Marks Sites of DNA Damage and Promotes Genome Stability. Cell Reports, 14(6), 1283–1292. https://doi.org/10.1016/j.celrep.2016.01.035}

^{Koziol, M. J., Bradshaw, C. R., Allen, G. E., Costa, A. S. H., Frezza, C., & Gurdon, J. B. (2016). Identification of methylated deoxyadenosines in vertebrates reveals diversity in DNA modifications. Nature Structural and Molecular Biology, 23(1), 24–30. https://doi.org/10.1038/nsmb.3145}

^{Le, T., Kim, K. P., Fan, G., & Faull, K. F. (2011). A sensitive mass spectrometry method for simultaneous quantification of DNA methylation and hydroxymethylation levels in biological samples. Analytical Biochemistry, 412(2), 203–209. https://doi.org/10.1016/j.ab.2011.01.026}

^{Liang, Z., Shen, L., Cui, X., Bao, S., Geng, Y., Yu, G., … Yu, H. (2018). DNA N6-Adenine Methylation in Arabidopsis thaliana. Developmental Cell, 45(3), 406–416.e3. https://doi.org/10.1016/j.devcel.2018.03.012}

^{Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., Tonti-filippini, J., … Ecker, J. R. (2009). Human DNA methylomes at base resolution show widespread epigenomic differences. Nature, 462(7271), 315–322. https://doi.org/10.1038/nature08514}

^{Liu, J., Zhu, Y., Luo, G. Z., Wang, X., Yue, Y., Wang, X., … He, C. (2016). Abundant DNA 6mA methylation during early embryogenesis of zebrafish and pig. Nature Communications, 7(866), 1–7. https://doi.org/10.1038/ncomms13052}

^{Lu, X., Song, C., Szulwach, K., Wang, Z., Weidenbacher, P., Jin, P., & He, C. (2013). Chemical Modi fi cation-Assisted Bisul fi te Sequencing ( CAB-Seq ) for 5 ‑ Carboxylcytosine Detection in DNA. J. Am. Chem. Soc., 135(25), 9315–9317. https://doi.org/10.1021/ja4044856}

^{Iurlaro, M., Ficz, G., Oxley, D., Raiber, E. A., Bachman, M., Booth, M. J., … Reik, W. (2013). A screen for hydroxymethylcytosine and formylcytosine binding proteins suggests functions in transcription and chromatin regulation. Genome Biology, 14(10), 1–11. https://doi.org/10.1186/gb-2013-14-10-r119}

^{Meissner, A., Gnirke, A., Bell, G. W., Ramsahoye, B., Lander, E. S., & Jaenisch, R. (2005). Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Research, 33(18), 5868–5877. https://doi.org/10.1093/nar/gki901}

^{Mellén, M., Ayata, P., Dewell, S., Kriaucionis, S., & Heintz, N. (2012). MeCP2 binds to 5hmC enriched within active genes and accessible chromatin in the nervous system. Cell, 151(7), 1417–1430. https://doi.org/10.1016/j.cell.2012.11.022}

^{Moore, L. D., Le, T., & Fan, G. (2013). DNA methylation and its basic function. Neuropsychopharmacology, 38(1), 23–38. https://doi.org/10.1038/npp.2012.112}

^{Okano, M., Bell, D. W., Haber, D. A., & Li, E. (1999). Cell 1999 Okano, 99, 1–11. https://doi.org/10.1016/S0092-8674(00)81656-6}

^{Pastor, W. A., Pape, U. J., Huang, Y., Henderson, H. R., Lister, R., Ko, M., … Rao, A. (2011). Genome-wide mapping of 5-hydroxymethylcytosine in embryonic stem cells. Nature, 473(7347), 394–397. https://doi.org/10.1038/nature10102}

^{Sérandour, A. A., Avner, S., Mahé, E. A., Madigou, T., Guibert, S., Weber, M., & Salbert, G. (2016). Single-CpG resolution mapping of 5-hydroxymethylcytosine by chemical labeling and exonuclease digestion identifies evolutionarily unconserved CpGs as TET targets. Genome Biology, 17(1), 1–12. https://doi.org/10.1186/s13059-016-0919-y}

^{Shen, L., Wu, H., Diep, D., Yamaguchi, S., D’Alessio, A. C., Fung, H. L., … Zhang, Y. (2013). Genome-wide analysis reveals TET- and TDG-dependent 5-methylcytosine oxidation dynamics. Cell, 153(3), 692–706. https://doi.org/10.1016/j.cell.2013.04.002}

^{Song, C. X., Szulwach, K. E., Fu, Y., Dai, Q., Yi, C., Li, X., … He, C. (2011). Selective chemical labeling reveals the genome-wide distribution of 5-hydroxymethylcytosine. Nature Biotechnology, 29(1), 68–75. https://doi.org/10.1038/nbt.1732}

^{Song, C. X., Szulwach, K. E., Dai, Q., Fu, Y., Mao, S. Q., Lin, L., … He, C. (2013). Genome-wide profiling of 5-formylcytosine reveals its roles in epigenetic priming. Cell, 153(3), 678–691. https://doi.org/10.1016/j.cell.2013.04.001}

^{Spruijt, C. G., Gnerlich, F., Smits, A. H., Pfaffeneder, T., Jansen, P. W. T. C., Bauer, C., … Vermeulen, M. (2013). Dynamic readers for 5-(Hydroxy)methylcytosine and its oxidized derivatives. Cell, 152(5), 1146–1159. https://doi.org/10.1016/j.cell.2013.02.004}

^{Vertino, P. M., Yen, R. W., Gao, J., & Baylin, S. B. (1996). De novo methylation of CpG island sequences in human fibroblasts overexpressing DNA (cytosine-5-)-methyltransferase. Molecular and Cellular Biology, 16(8), 4555–4565. https://doi.org/10.1128/MCB.16.8.4555}

^{Wu, H., Wu, X., Shen, L., & Zhang, Y. (2014). Single-base resolution analysis of active DNA demethylation using methylase-assisted bisulfite sequencing. Nature Biotechnology, 32(12), 1231–1240. https://doi.org/10.1038/nbt.3073}

^{Wu, X., & Zhang, Y. (2017). TET-mediated active DNA demethylation: Mechanism, function and beyond. Nature Reviews Genetics, 18(9), 517–534. https://doi.org/10.1038/nrg.2017.33}

^{Xiao, C. Le, Zhu, S., He, M., De Chen, D., Zhang, Q., Chen, Y., … Yan, G. R. (2018). N6-Methyladenine DNA Modification in the Human Genome. Molecular Cell, 1–13. https://doi.org/10.1016/j.molcel.2018.06.015}

^{Yamaguchi, S., Hong, K., Liu, R., Inoue, A., Shen, L., Zhang, K., & Zhang, Y. (2013). Dynamics of 5-methylcytosine and 5-hydroxymethylcytosine during germ cell reprogramming. Cell Research, 23(3), 329–339. https://doi.org/10.1038/cr.2013.22}

^{Yao, B., Cheng, Y., Wang, Z., Li, Y., Chen, L., Huang, L., … Jin, P. (2017). DNA N6-methyladenine is dynamically regulated in the mouse brain following environmental stress. Nature Communications, 8(1), 1–10. https://doi.org/10.1038/s41467-017-01195-y}

^{Yildirim, O., Li, R., Hung, J. H., Chen, P. B., Dong, X., Ee, L. S., … Fazzio, T. G. (2011). Mbd3/NURD complex regulates expression of 5-hydroxymethylcytosine marked genes in embryonic stem cells. Cell, 147(7), 1498–1510. https://doi.org/10.1016/j.cell.2011.11.054}

^{Yu, M., Hon, G. C., Szulwach, K. E., Song, C. X., Zhang, L., Kim, A., … He, C. (2012). Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell, 149(6), 1368–1380. https://doi.org/10.1016/j.cell.2012.04.027}

^{Zhang, L., Zhang, L., Zhou, K., Ye, X., Zhang, J., Xie, A., … Cai, C. (2012). Simultaneous determination of global DNA methylation and hydroxymethylation levels by hydrophilic interaction liquid chromatography-tandem mass spectrometry. Journal of Biomolecular Screening, 17(7), 877–884. https://doi.org/10.1177/1087057112447946}

^{Zhu, C., Gao, Y., Guo, H., Xia, B., Song, J., Wu, X., … Kee, K. (2017). Single-Cell 5-Formylcytosine Landscapes of Mammalian Early Embryos and ESCs at Single-Base Resource Single-Cell 5-Formylcytosine Landscapes of Mammalian Early Embryos and ESCs at Single-Base Resolution. Stem Cell, 1–12. https://doi.org/10.1016/j.stem.2017.02.013}

Part 5 references

^{Roundtree, I., Evans, M., Pan, T., & He, C. (2017) Dynamic RNA Modifications in Gene Expression Regulation. Cell, 1187-1200}

^{Xiao, W., Adhikari, S., Dahal, U., Chen, Y.S., Hao, Y.J., Sun, B.F., Sun, H.Y., Li, A., Ping, X.L., Lai, W.Y., et al. (2016). Nuclear m6A Reader YTHDC1 Regulates mRNA Splicing. Mol. Cell 61, 507–519.}

^{Liu, N., Dai, Q., Zheng, G., He, C., Parisien, M., and Pan, T. (2015). N6-methyladenosine-dependent RNA structural switches regulate RNA-protein interactions. Nature 518, 560–564.}

^{Du, H., Zhao, Y., He, J., Zhang, Y., Xi, H., Liu, M., Ma, J., and Wu, L. (2016). YTHDF2 destabilizes m6A-containing RNA through direct recruitment of the CCR4–NOT deadenylase complex. Nat. Commun. 7, 12626.}

^{Wang, X., Zhao, B.S., Roundtree, I.A., Lu, Z., Han, D., Ma, H., Weng, X., Chen, K., Shi, H., and He, C. (2015). N6-methyladenosine modulates messenger RNA translation efficiency. Cell 161, 1388–1399.}

^{Kirchner, S., and Ignatova, Z. (2015). Emerging roles of tRNA in adaptive translation, signalling dynamics and disease. Nat. Rev. Genet. 16, 98–112.}

^{Rubio, M.A.T., Gaston, K.W., McKenney, K.M., Fleming, I.M.C., Paris, Z., Limbach, P.A., and Alfonzo, J.D. (2017). Editing and methylation at a single site by functionally interdependent activities. Nature 542, 494–497.}

^{Stuart, J.W., Koshlap, K.M., Guenther, R., and Agris, P.F. (2003). Naturally occurring modification restricts the anticodon domain conformational space of tRNA (Phe). J. Mol. Biol. 334, 901–918.}

^{Linder B  et al. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat Methods 12:767-72 (2015).}

^{Mauer J  et al. Reversible methylation of m(6)Am in the 5' cap controls mRNA stability. Nature 541:371-375 (2017).}

^{​Arango et al. ​Acetylation of Cytidine in mRNA Promotes
Translation Efficiency. Cell 13;175(7):1872-1886 (2018).}

^{Khalila AM, Guttman M, Huarte M, Garbera M, Rajd A, Morales DR, Thomas K, Pressera A, Bernstein BE, Oudenaarden AV, Regeva A, Lander ES, and Rinn JL (2009). Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. PNAS 106, 11667–72.}

^{Hendrickson DG, Hogan DJ, McCullough HL, Myers JW, Herschlag D, Ferrell JE, and Brown PO (2009). Concordant Regulation of Translation and mRNA Abundance for Hundreds of Targets of a Human microRNA. PLoS Biology 7 (11), 2643.}

^{Hendrickson DG, Hogan DJ, Herschlag D, Ferrell JE, and Brown PO (2008). Systematic Identification of mRNAs Recruited to Argonaute 2 by Specific microRNAs and Corresponding Changes in Transcript Abundance. PLoS One 3 (5), 2126.}

^{Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA, Goodnough LH, Helms JA, Farnham PJ, Segal E, and Chang HY (2007). Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 129, 1311–1323.}

^{Konig et al. J. Vis. Exp. 2011. “iCLIP -Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution.”}

^{Huppertz et al. Methods. 2014. “iCLIP: Protein–RNA interactions at nucleotide resolution.”}

^{Dominissini, D. et al. (2012). Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 485, 201–206}

^{Liu, N. et al. (2015). N6-methyladenosine-dependent RNA structural switches regulate RNA–protein interactions. Nature 518, 560-564}

^{Narayan, P. and Rottman, F.M. (1988). An in vitro system for accurate methylation of internal adenosine residues in messenger RNA. Science 242, 1159–1162}

^{Meyer, K.D. and Jaffrey, S.R. (2014) The dynamic epitranscriptome: N6-methyladenosine and gene expression control. Nat Rev Mol Cell Biol 15, 313–326}

^{Sugimoto, Y. et al. (2012). Analysis of CLIP and iCLIP methods for nucleotide-resolution studies of protein-RNA interactions. Genome Biol. 13, R67}

^{Wang, X., Lu, Z., Gomez, A., Hon, G.C., Yue, Y., Han, D., Fu, Y., Parisien, M., Dai, Q., Jia, G., et al. (2014). N6-methyladenosine-dependent regulation of messenger RNA stability. Nature 505, 117–120}

​