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The cis-regulatory codes of response to combined heat and drought stress in Arabidopsis thaliana

View ORCID ProfileChristina B. Azodi, View ORCID ProfileJohn P. Lloyd, Shin-Han Shiu
doi: https://doi.org/10.1101/2020.02.28.969261
Christina B. Azodi
1Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
2The DOE Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI 48824, USA
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  • ORCID record for Christina B. Azodi
John P. Lloyd
3Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
4Department of Internal Medicine, University of Michigan, Ann Arbor, MI, 48109, USA
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Shin-Han Shiu
1Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
2The DOE Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI 48824, USA
5Department of Computational, Mathematics, Science, and Engineering, Michigan State University, East Lansing, MI, 48824, USA
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  • For correspondence: shius@msu.edu
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ABSTRACT

Plants respond to their environment by dynamically modulating gene expression. A powerful approach for understanding how these responses are regulated is to integrate information about cis-regulatory elements (CREs) into models called cis-regulatory codes. Transcriptional response to combined stress is typically not the sum of the responses to the individual stresses. However, cis-regulatory codes underlying combined stress response have not been established. Here we modeled transcriptional response to single and combined heat and drought stress in Arabidopsis thaliana. We grouped genes by their pattern of response (independent, antagonistic, synergistic) and trained machine learning models to predict their response using putative CREs (pCREs) as features (median F-measure = 0.64). We then developed a deep learning approach to integrate additional omics information (sequence conservation, chromatin accessibility, histone modification) into our models, improving performance by 6.2%. While pCREs important for predicting independent and antagonistic responses tended to resemble binding motifs of transcription factors associated with heat and/or drought stress, important synergistic pCREs resembled binding motifs of transcription factors not known to be associated with stress. These findings demonstrate how in silico approaches can improve our understanding of the complex codes regulating response to combined stress and help us identify prime targets for future characterization.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 29, 2020.
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The cis-regulatory codes of response to combined heat and drought stress in Arabidopsis thaliana
Christina B. Azodi, John P. Lloyd, Shin-Han Shiu
bioRxiv 2020.02.28.969261; doi: https://doi.org/10.1101/2020.02.28.969261
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The cis-regulatory codes of response to combined heat and drought stress in Arabidopsis thaliana
Christina B. Azodi, John P. Lloyd, Shin-Han Shiu
bioRxiv 2020.02.28.969261; doi: https://doi.org/10.1101/2020.02.28.969261

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