Diverse motif ensembles specify non-redundant DNA binding activities of AP-1 family members in macrophages

Gregory J. Fonseca, Jenhan Tao, Emma M. Westin, Sascha H. Duttke, Nathanael J. Spann, Tobias Strid, Zeyang Shen, Joshua D. Stender, Mashito Sakai, Verena M. Link, Christopher Benner and Christopher K. Glass ()
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Gregory J. Fonseca: University of California San Diego
Jenhan Tao: University of California San Diego
Emma M. Westin: University of California San Diego
Sascha H. Duttke: University of California San Diego
Nathanael J. Spann: University of California San Diego
Tobias Strid: University of California San Diego
Zeyang Shen: University of California San Diego
Joshua D. Stender: University of California San Diego
Mashito Sakai: University of California San Diego
Verena M. Link: Ludwig-Maximilian University of Munich
Christopher Benner: University of California San Diego
Christopher K. Glass: University of California San Diego

Nature Communications, 2019, vol. 10, issue 1, 1-16

Abstract: Abstract Mechanisms by which members of the AP-1 family of transcription factors play non-redundant biological roles despite recognizing the same DNA sequence remain poorly understood. To address this question, here we investigate the molecular functions and genome-wide DNA binding patterns of AP-1 family members in primary and immortalized mouse macrophages. ChIP-sequencing shows overlapping and distinct binding profiles for each factor that were remodeled following TLR4 ligation. Development of a machine learning approach that jointly weighs hundreds of DNA recognition elements yields dozens of motifs predicted to drive factor-specific binding profiles. Machine learning-based predictions are confirmed by analysis of the effects of mutations in genetically diverse mice and by loss of function experiments. These findings provide evidence that non-redundant genomic locations of different AP-1 family members in macrophages largely result from collaborative interactions with diverse, locus-specific ensembles of transcription factors and suggest a general mechanism for encoding functional specificities of their common recognition motif.

Date: 2019
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DOI: 10.1038/s41467-018-08236-0

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