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EXPLICIT-Kinase: a gene expression predictor for dissecting the functions of the Arabidopsis kinome

Yuming Peng, Wanzhu Zuo, Yue Qin, Shisong Ma
doi: https://doi.org/10.1101/2021.09.15.460437
Yuming Peng
1Hefei National Laboratory for Physical Sciences at the Microscale, MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Innovation Academy for Seed Design, Chinese Academy of Sciences, Hefei, China
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Wanzhu Zuo
1Hefei National Laboratory for Physical Sciences at the Microscale, MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Innovation Academy for Seed Design, Chinese Academy of Sciences, Hefei, China
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Yue Qin
1Hefei National Laboratory for Physical Sciences at the Microscale, MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Innovation Academy for Seed Design, Chinese Academy of Sciences, Hefei, China
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Shisong Ma
1Hefei National Laboratory for Physical Sciences at the Microscale, MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Innovation Academy for Seed Design, Chinese Academy of Sciences, Hefei, China
2School of Data Science, University of Science and Technology of China, Hefei, China
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  • For correspondence: sma@ustc.edu.cn
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ABSTRACT

Protein kinases regulate virtually all cellular processes, but it remains challenging to determine the functions of all protein kinases, collectively called the kinome, in any species. We developed an approach called EXPLICIT-Kinase to predict the functions of the Arabidopsis kinome. Because the activities of many kinases can be regulated transcriptionally, their gene expression patterns provide clues to their functions. A universal gene expression predictor for Arabidopsis was constructed to predict the expression of 30,172 non-kinase genes based on the expression of 994 protein kinase genes. The model reconstituted highly accurate transcriptomes for diverse Arabidopsis samples. It identified the significant kinases as predictor kinases for predicting the expression of Arabidopsis genes and pathways. Strikingly, these predictor kinases were often known regulators of the related pathways, as exemplified by those involved in cytokinesis, tissue development, and stress responses. Comparative analyses have revealed that portions of these predictor kinases, including the novel ones, are shared and conserved between Arabidopsis and maize. The conservation between species provide additional evidence to support the novel predictor kinases as bona fide regulators of the pathways involved. Thus our approach enables the systematic dissection of the functions of the Arabidopsis kinome.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
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 September 17, 2021.
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EXPLICIT-Kinase: a gene expression predictor for dissecting the functions of the Arabidopsis kinome
Yuming Peng, Wanzhu Zuo, Yue Qin, Shisong Ma
bioRxiv 2021.09.15.460437; doi: https://doi.org/10.1101/2021.09.15.460437
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EXPLICIT-Kinase: a gene expression predictor for dissecting the functions of the Arabidopsis kinome
Yuming Peng, Wanzhu Zuo, Yue Qin, Shisong Ma
bioRxiv 2021.09.15.460437; doi: https://doi.org/10.1101/2021.09.15.460437

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