Prediction of conserved and variable heat and cold stress response in maize using cis-regulatory information

Author:

Zhou Peng1ORCID,Enders Tara A1ORCID,Myers Zachary A1ORCID,Magnusson Erika1ORCID,Crisp Peter A12ORCID,Noshay Jaclyn M1ORCID,Gomez-Cano Fabio3ORCID,Liang Zhikai1ORCID,Grotewold Erich3ORCID,Greenham Kathleen1ORCID,Springer Nathan M1ORCID

Affiliation:

1. Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota 55108, USA

2. School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia

3. Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, USA

Abstract

Abstract Changes in gene expression are important for responses to abiotic stress. Transcriptome profiling of heat- or cold-stressed maize genotypes identifies many changes in transcript abundance. We used comparisons of expression responses in multiple genotypes to identify alleles with variable responses to heat or cold stress and to distinguish examples of cis- or trans-regulatory variation for stress-responsive expression changes. We used motifs enriched near the transcription start sites (TSSs) for thermal stress-responsive genes to develop predictive models of gene expression responses. Prediction accuracies can be improved by focusing only on motifs within unmethylated regions near the TSS and vary for genes with different dynamic responses to stress. Models trained on expression responses in a single genotype and promoter sequences provided lower performance when applied to other genotypes but this could be improved by using models trained on data from all three genotypes tested. The analysis of genes with cis-regulatory variation provides evidence for structural variants that result in presence/absence of transcription factor binding sites in creating variable responses. This study provides insights into cis-regulatory motifs for heat- and cold-responsive gene expression and defines a framework for developing models to predict expression responses across multiple genotypes.

Funder

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Cell Biology,Plant Science

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