Abstract
The phytohormone abscisic acid (ABA) is a central regulator of acclimation to environmental stress; however, its contribution to differences in stress tolerance between species is unclear. To establish a comparative framework for understanding how stress hormone signalling pathways diverge across species, we studied the growth response of four Brassicaceae species to ABA treatment and generated transcriptomic and DNA affinity purification and sequencing datasets to construct a cross-species gene regulatory network (GRN) for ABA. Comparison of genes bound directly by ABA-responsive element binding factors suggests that cis-factors are most important for determining the target loci represented in the ABA GRN of a particular species. Using this GRN, we reveal how rewiring of growth hormone subnetworks contributes to stark differences in the response to ABA in the extremophyte Schrenkiella parvula. Our study provides a model for understanding how divergence in gene regulation can lead to species-specific physiological outcomes in response to hormonal cues.
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Data availability
All data are available in the manuscript, in the Supplementary material or in the following databases: high-throughput sequencing data sets are available through the National Center for Biotechnology Information Sequence Read Archive (NCBI SRA) under BioProject ID PRJNA682697. The Sisymbrium irio gene models are deposited in the CoGe database (https://genomevolution.org/) with the Genome ID 57216. Supplementary data are available on FigShare (https://doi.org/10.6084/m9.figshare.14033822). Genome browser view of data can be found on Jbrowse: http://jbrowsedap.s3-website-us-west-1.amazonaws.com
Code availability
The custom scripts developed in this study are publicly available in the GitHub repository at https://github.com/dinnenylab/BrassicaceaeGRN.
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Acknowledgements
We acknowledge M. Galli and M.C. Yee for advice on experimental design; Carnegie Institution for Science, Department of Plant Biology and G. Huntress for providing access to computing resources and data management; undergraduates R. Gates and J. Pulido for their summer engagements with this study; and C. Pires for Sisymbrium irio seeds. D.-H.O. and M.D. also acknowledge the Louisiana State University High Performance Computing services (HPC@LSU) for providing computational resources needed for data analyses. US Department of Energy’s Biological and Environmental Research program (Grant DE-SC0020358, to J.R.D., D.-H.O and M.D.), Carnegie Institution for Science endowment (to J.R.D.), National Science Foundation (MCB-1616827 and NSF-IOS-EDGE-1923589, to D.-H.O. and M.D.) Rural Development Administration (RDA), South Korea (Next-Generation BioGreen21 program PJ01317301 to D.-H.O. and M.D.), National Science Foundation Graduate Research Fellowship (to Y.S.), and HHMI-Simons Faculty Scholar (to J.R.D.).
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Y.S., L.D. and P.R. performed the experiments. Y.S., D.-H.O., P.R., A.R., A.B., K.-N.T., G.W. and J.R.D. analysed the data. Y.S., D.-H.O. and J.R.D. wrote the manuscript. L.D., P.R. and M.D. contributed to the manuscript preparation.
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Supplementary Information
Supplementary Text 1 and 2, Figs. 1–10 and Tables 1–4.
Supplementary Data 1
RNA- and DAP-Seq results for all 1-to-1 orthologous groups (OGs).
Supplementary Data 2
RNA- and DAP-Seq results for all genes organized as OrthNets.
Supplementary Data 3
GO enrichment among ABA-responsive DEGs and overlaps between salt and ABA responses.
Supplementary Data 4
Results of PiP analyses.
Supplementary Data 5
JASPAR motifs enriched among promoters of ABA-induced and repressed DEGs.
Supplementary Data 6
All DAP-Seq peak coordinates with annotations.
Supplementary Data 7
Conserved GRN.
Supplementary Data 8
ABA, auxin, and ethylene GRNs.
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Sun, Y., Oh, DH., Duan, L. et al. Divergence in the ABA gene regulatory network underlies differential growth control. Nat. Plants 8, 549–560 (2022). https://doi.org/10.1038/s41477-022-01139-5
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DOI: https://doi.org/10.1038/s41477-022-01139-5