Interpreting ATAC-SEQ motif enrichment output
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Entering edit mode
8 months ago
emalekos • 0

After aligning and peak calling ATAC SEQ data, I used the homer getDifferentialPeaks script to do pairwise comparisons between samples.
This produces a file that contains the peaks enriched in sample1 vs. sample2.
Then I used findMotifsGenome.pl (also homer) on the differential peaks file to try to determine which transcription factors might be more active in sample1 compared to sample2.
I am having trouble interpreting the results, in part because the motifs that have been found are highly conserved, yet the transcription factors associated with those motifs are different.
As you can see in the image, the first ten hits all have something like: TGA[CG]TCA
But all are associated with different TFs, albeit with some similarity (Fos/Fosl2, Fra1/Fra2, JunB/Jun-API).

Any help making sense of these results, or suggestions for further/different analyses would be appreciated!

enter image description here

ATAC-Seq ChIP-Seq • 364 views
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Entering edit mode
8 months ago
ATpoint 55k

These are all AP-1 motifs, that is a transcription factor family that all these members belong to (Fos, Jun, ATF...). They all share a similar motif, that is why they belong to the same family. Having similar or almost identical motifs is very common for transcription factors. It is then the experssion level, affinity of each transcription factor for the actual DNA target sequence and interaction with binding partners that determines whether a TF binds or not. Competition between members of the same family for the same binding sites have extensively been reported in the literature. Ratios of expression levels can be important regulatory mechanisms towards gene expression.

Motifs are just rough approximations towards the actual factors. You will need to take expression data of these factors, ideally also protein expression and binding data such as ChIP-seq into account. Once you have candidates you would need to make experiments, such as knockout and overexpression to prove your in silico results. That having said, motifs alone are probably not sufficient to make convincing claims.

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