Enabling Epigenetics ResearchCUT&Tag-IT® Spike-In Control, R-loop
Catalog No. 53173(Version A1)

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Contents
Overview  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Kit Components and Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2Workflow  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3CUT&Tag Spike-In Reaction Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  4CUT&Tag Normalization Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  7
Technical Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  8

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Overview
The Cleavage Under Targets and Tagmentation (CUT&Tag) technique has emerged as a
powerful method for investigating the genomic localization of histone modifications ofinterest. However, the identification of differences between data sets can be challenging
when global modification changes occur, such as in the case of studying the effects ofchromatin modifying enzyme inhibitors. Additionally inaccurate quantification of starting
material or technical variation during processing results in variation across sample data.
Currently available bioinformatic-based normalization methods are not applicable in these
instances, and the only reliable way to overcome bias and variation is to add a known
standard (spike-in) into all samples. Active Motif offers spike-in reagents for ChIP-Seq and has
now introduced a similar approach for CUT&Tag.
Active Motif’s strategy for CUT&Tag normalization is to spike-in cryopreserved Drosophilacell nuclei into samples prior to CUT&Tag. Then, during the primary antibody incubation step,a Drosophila H2Av antibody is added in addition to the antibody targeting the histone markof interest. This Drosophila H2Av antibody provides a mechanism to reliably tag Drosophila
histones in a consistent way across all samples. A normalization factor is then created basedon the Drosophila signal and applied to the test genome. This CUT&Tag Spike-in strategy
enables normalization of CUT&Tag data independent of the experimental antibody andwithout bias.
The CUT&Tag-IT® Spike-In Control, R-loop works with the CUT&Tag-IT® R-loop Assay Kit(Catalog No. 53167).
ProductFormat

Catalog No.

CUT&Tag-IT® Spike-In Control, R-loop

16 rxns

53174

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Kit Components and Storage
All components are guaranteed for 6 months after receipt when stored properly.
Kit Component

Quantity

Storage

CUT&Tag-IT® Spike-In Antibody, Mouse

16 µL

-20°C

CUT&Tag-IT Spike-In Nuclei, R-loop

4 x 440 µL

-80°C

®

CUT&Tag-IT Spike-in Nuclei, R-loop are provided as four 440 µL vials of nuclei at aconcentration of 500 nuclei/µL.
We recommend using 50,000 nuclei per 500,000 cells used in CUT&Tag-IT R-loop Assay
Kit reaction.
Note:

If more than 1 vial of nuclei are used across an experiment, pool the neededvials of nuclei together to ensure consistency in the amount of nuclei added
per reaction for spike-in.

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Workflow

Cells

CUT&Tag-IT®
Spike-In Nuclei

DNA-RNA Hybrid
Antibody

CUT&Tag-IT® Spike-In
Antibody, Mouse

CUT&Tag

Sequencing

Map to experimentalgenomeMap to Drosophila
genomeNormalize Drosophila
tag counts across samples

Normalize experimental
sample tag counts
by same ratio

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CUT&Tag-IT Spike-In Control, R-loop Reaction Guidelines
Active Motif’s CUT&Tag normalization strategy1 may be applied to any mammalian CUT&Tag
assay reaction due to the lack of cross-reactivity of the Spike-in antibody with mammaliansamples. The amount of cryopreserved Drosophila nuclei and antibody used per CUT&Tag
reaction may need to be optimized with the goal of having Drosophila reads make up only
2-10% of the total sequencing reads.
A spike-in:test sample ratio of 1:10 is recommended for CUT&Tag targeting R-loops.
To demonstrate the utility of this approach, DNA-RNA hybrid R-loop level differences were
mimicked by setting up CUT&Tag reactions with different amounts of starting cell numbers.
Various numbers of cryopreserved human K562 cells (500,000, 375,000, 250,000,and 125,000) were combined with 50,000 of cryopreserved Drosophila nuclei for eachexperiment (Figure 1).
DNA-RNA hybrids were evaluated in the CUT&Tag R-loop Spike-In assay, with biologicalduplicates included in each experiment. Libraries were quantified and sequenced to a depthof 40-50 million reads per sample. However, sequencing to equal read depth for eachsample masks the differences in starting amounts for each sample (Figure 2). Therefore
spike-in normalization is required to reveal the differences in starting material2.
For normalization, the sample with the lowest number of Drosophila reads was used
to generate normalization factors across samples, which were then applied to downsample the human read counts for each sample accordingly. After obtaining normalized
human read counts, a standard CUT&Tag pipeline was used for peak calling generation ofbigWigs. Normalized results correlate with input cell numbers, so that differences between
experimental samples can be revealed (Figure 3).

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Figure 1: K562 Cell Titration results for CUT&Tag-IT R-loop Assay without CUT&Tag-IT Spike-In
Control, R-loop normalization
This experiment used 50,000 drosophila nuclei as a spike-in for a mock treatment. The mocktreatment was a cell titration performed in duplicate from 500,000 cryopreserved K562 cells down
to 125,000 cryopreserved K562 cells. The actual cell numbers are 500,000, 375,000, 250,000, and125,000 cells. This figure is all of the non-normalized tracks for the titration in duplicates.

Figure 2: K562 Cell Titration results for CUT&Tag-IT R-loop Assay with CUT&Tag-IT Spike-In
Control, R-loop normalization
This experiment used 50,000 drosophila nuclei as a spike-in for a mock treatment. The mocktreatment was a cell titration performed in duplicate from 500,000 cryopreserved K562 cells down
to 125,000 cryopreserved K562 cells. The actual cell numbers are 500,000, 375,000, 250,000, and125,000 cells. This figure is all of the normalized tracks for the titration in duplicates.

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Figure 3: K562 Unique Alignments
This is the unique alignments (to human genome) for one of the duplicates, before (-) and after (+)
normalization with the spike in, for each of the 4 cell inputs.

Figure 4: Normalized Data Correlates with Experimental Cell Numbers
This is the ratio of input material. For the sample data (normalized and unnormalized) this wascalculated by dividing the number of unique fragments aligning to the human genome for eachsample by the number of unique alignments for the max input. For the expected sample – thenumber of cell input was divided by the max number of cell input.

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CUT&Tag-IT Spike-In Control, R-loop Normalization Guidelines
1.

Perform CUT&Tag by combining the CUT&Tag-IT® Spike-In Nuclei with theexperimental sample cells to be used in the CUT&Tag-IT R-loop Assay. Perform theCUT&Tag-IT R-loop Assay as per the instructions provided in the CUT&Tag-IT® R-loop
Assay Kit manual (Catalog No. 53167) and add 1 µL of CUT&Tag-IT® Spike-In Antibody,
Mouse in combination with the DNA-RNA Hybrid mAb (Clone S9.6) antibody, during
the primary antibody incubation step. Use the guidelines provided for nuclei andantibody quantities based on the antibody target.

2.

Sequence the CUT&Tag libraries using an NGS platform.

3.

Map the CUT&Tag data to the test reference genome (e.g. human, mouse, or other).

4.

Map CUT&Tag data to the Drosophila reference genome.

5.

Count uniquely aligning Drosophila sequence tags and identify the sample containing
the least number of tags.

6.

Divide the aligned Drosophila tag value from the sample with the lowest Drosophila
tag count by the Drosophila tag count value from all other samples to and generatea normalization factor for each sample. (Sample 1 with lowest tag count / Sample 2)= Normalization factor. The sample with the lowest drosophila tag count will have anormalization factor of 1.

7.

Generate the normalization factors for all samples using the strategy from step 6.

8.

Use the normalization factors to down-sample the read counts for each sample.

9.

After obtaining normalized human read counts, use a standard CUT&Tag pipeline
starting with the downsampled tag counts for each sample for peak calling andgeneration of bigWigs.

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References
1.

Egan, B. et al. (2016) PLoS ONE. 11(11): e0166438.

2.

Taruttis et al. (2017) Biotechniques 62:53-61

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