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Predictive Models of Spatial Transcriptional Response to High Salinity
Sahra Uygun1, Alexander E Seddon1, Christina B Azodi1
1Genetics Program (S.U., S.-H.S.), Department of Plant Biology (A.E.S., C.B.A., S.-H.S.), and Ecology, Evolutionary Biology, and Behavior Program (S.-H.S.), Michigan State University, East Lansing, Michigan 48824.
Plant Physiology
|April 5, 2017
Summary
Researchers identified key DNA elements controlling plant salt stress responses. Computational models using these elements accurately predict gene regulation in plant roots and shoots, revealing the cis-regulatory code for environmental adaptation.
Area of Science:
- Plant molecular biology
- Genomics
- Environmental stress response
Background:
- Plants require precise gene expression regulation for environmental adaptation.
- Understanding spatial control of stress response genes, particularly transcription factors (TFs) and cis-regulatory elements (CREs), is crucial but incomplete.
- A genome-wide model for spatially specific stress response regulation is lacking.
Purpose of the Study:
- To identify cis-regulatory elements (CREs) involved in high-salinity stress response in Arabidopsis thaliana.
- To develop computational models for predicting salt-responsive genes in specific plant organs (root and shoot).
- To elucidate the genome-wide cis-regulatory code governing spatial transcriptional responses to environmental stress.
Main Methods:
- Identification of 1,894 putative cis-regulatory elements (pCREs) linked to salt-up-regulated genes in Arabidopsis roots or shoots.
- Development of computational models using pCREs to predict salt-up-regulated genes, comparing performance against models based on known TF binding motifs.
- Integration of TF binding sites, chromatin accessibility, evolutionary conservation, and pCRE combinations into machine learning models.
Main Results:
- pCRE-based models outperformed models using known TF binding motifs in predicting salt-up-regulated genes in both root and shoot.
- Machine learning models incorporating pCRE combinations significantly improved prediction performance for salt up-regulation.
- TF binding sites, chromatin accessibility, and evolutionary conservation alone did not enhance predictive accuracy.
Conclusions:
- A core set of pCREs regulates the plant organ transcriptional response to high salinity.
- Combinatorial interactions among pCREs are critical for accurate prediction of spatial transcriptional responses.
- This study provides a genome-wide perspective on the cis-regulatory code for plant environmental stress adaptation.
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