Enabling Epigenetics Research

ATAC-Seq Spike-In Control
Catalog No. 53154(Version A1)

Copyright 2024 Active Motif, Inc.

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ContentsOverview  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Kit Components and Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2Workflow  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3ATAC-Seq Spike-In Reaction Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  4
ATAC-Seq Normalization Guidelines  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  7
Technical Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  8activemotif.com

Overview
Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATACSeq) has emerged as a powerful method for investigating open or accessible chromatin
across the genome. However, the identification of differences between data sets can bechallenging when global modification changes occur, such as in the case of studying theeffects of chromatin modifying enzyme inhibitors. Additionally inaccurate quantification ofstarting material or technical variation during processing results in variation across sample
data. Currently available bioinformatic-based normalization methods are not applicable inthese 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 andCUT&Tag, and has now introduced a similar approach for ATAC-Seq.
Active Motif’s strategy for ATAC-Seq normalization is to Spike-In cryopreserved Drosophilacell nuclei into samples prior to nuclei prep and tagmention. During tagmentation both thetest cells and the Drosophila nuclei are tagged at open chromatin consistently across allsamples. A normalization factor is then created based on the Drosophila signal and applied
to the test genome.
The ATAC-Seq Spike-In Control kit works with the ATAC-Seq Assay Kit (Catalog No. 53150).
ProductFormat

Catalog No.

ATAC-Seq Spike-In Control

16 rxns

53154

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

Quantity

Storage

ATAC-Seq Spike-In Nuclei

4 x 80 µL-80°C

ATAC-Seq Spike-In Nuclei are provided as four 80 µL vials of nuclei at a concentration of500 nuclei/µL.
We recommend using 10,000 ATAC-Seq Spike-In Nuclei per 50,000 to 100,000 cells used in
an ATAC-Seq Assay Kit reaction. For less than 50,000 cells, 10,000 ATAC-Seq Spike-in Nuclei
can be used but will amount to more than 5% of sequencing reads.
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
ATAC-Seq
Spike-In Nuclei

Cells

ATAC-Seq

Sequencing

Map to experimental
genome

Map to Drosophila
genomeNormalize Drosophila
tag counts across samples

Normalize experimental
sample tag counts
by same ratio

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ATAC-Seq Spike-In Reaction Guidelines

Figure 1: K562 Starting Cell Numbers for ATAC-Seq
This experiment used 10,000 drosophila nuclei as a spike in for a mock treatment. The mocktreatment was a cell titration performed in duplicate from 200,000 cryopreserved K562 cells down
to 10,000 cryopreserved K562 cells. The actual cell numbers are 200,000, 100,000, 50,000, 20,000
and 10,000 cells. This figure is all of the normalized tracks for the titration in duplicates.

Figure 2: K562 Starting Cell Numbers for ATAC-Seq with and without Spike-In Normalization
This experiment used 10,000 drosophila nuclei as a spike in for a mock treatment. The mocktreatment was a cell titration performed in duplicate from 200,000 cryopreserved K562 cells down
to 10,000 cryopreserved K562 cells. The actual cell numbers are 200,000, 100,000, 50,000, 20,000
and 10,000 cells. This figure is both the spike-in normalized and unnormalized tracks for one of theduplicates in the titration.

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Figure 3: K562 Paired Alignments with and without Normalization
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 cell inputs.

Figure 4: K562 Paired Alignments After Normalization to Drosophila Paired Alignments
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. (numbers are multiplied by 10 toincrease scale).

activemotif.com|5The amount of cryopreserved Drosophila nuclei used per ATAC-Seq reaction may need
to be optimized with the goal of having Drosophila reads make up only 2-10% of the total
sequencing reads. However, when using 50,000-100,000 cells we recommend using 10,000
Drosophila nuclei. For samples that have less than 50,000 cells, 10,000 nuclei can be used,
but will account for more than 5% of total reads. This can be optimized by titrating thenumber of Drosophila nuclei.
To demonstrate the utility of this approach, chromatin accessibility differences weremimicked by setting up ATAC-Seq reactions with different amounts of starting cell numbers(Figure 1). Various numbers of cryopreserved human K562 cells (10,000, 20,000, 50,000,100,000, and 200,000) were combined with 10,000 of cryopreserved Drosophila nuclei foreach experiment.
Libraries were quantified and sequenced to a depth of 40-50 million reads per sample.
However, sequencing to equal read depth for each sample masks the differences instarting 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 (Figure 3) was used to generate normalization factors acrosssamples, which were then applied to down-sample the human read counts for each sample
accordingly (Figure 4). After obtaining normalized human read counts, a standard ATAC-Seq
pipeline was used for peak calling generation of bigWigs.

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ATAC-Seq Normalization Guidelines
1.

Perform ATAC-Seq by combining the ATAC-Seq Spike-In Nuclei with the experimental
sample cells to be used in ATAC-Seq prior to wash and lysis steps. Perform ATACSeq as per the instructions provide in Active Motif’s ATAC-Seq Assay kit (Catalog No.
53150). Use the guidelines provided for the number of Spike-In nuclei that should
added to the experimental sample based on cell number.

2.

Sequence the ATAC-Seq libraries using an NGS platform.

3.

Map the ATAC-Seq data to the test reference genome (e.g. human, mouse, or other).

4.

Map ATAC-Seq 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 Drosophilatag 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 ATAC-Seq 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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8Technical Services

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