DOI: 10.5061/dryad.547d7wmgr
title: Reprogramming feedback strength in gibberellin biosynthesis highlights conditional regulation by the circadian clock and carbon dioxide

description: The phytohormone gibberellin (GA) is an important regulator of plant
 morphology and reproduction, and the biosynthesis and distribution of
 GA in planta is agriculturally relevant to past and
 current breeding efforts. Tools like biosensors, extensive molecular
 genetic resources in reference plants and mathematical models have greatly
 contributed to current understanding of GA homeostasis; however, these
 tools are difficult to tune or repurpose for engineering crop plants.
 Previously, we showed that a GA-regulated Hormone Activated CAS9-based
 Repressor (GAHACR) functions in planta (Khakhar et al.,
 2018). Here, we use GAHACRs to modulate the strength of feedback on
 endemic GA regulated genes, and to directly test the importance of
 transcriptional feedback in GA signaling. We first adapted
 existing mathematical models to predict the impact of targeting a GAHACR
 to different nodes in the GA biosynthesis pathway, and then implemented a
 perturbation predicted by the model to lower GA levels. Specifically, we
 individually targeted either the biosynthetic gene GA20 oxidase (GA20ox)
 or the GA receptor GID1, and characterized primary root length, flowering
 time and the transcriptome of these transgenic lines. Using this approach,
 we identified a strong connection between GA signaling status and the
 circadian clock, which can be largely attenuated by elevated carbon
 dioxide levels. Our results identify a node in the GA signaling pathway
 that can be engineered to modulate plant size and flowering time. Our
 results also raise concerns that rising atmospheric CO2 concentration are
 likely to reverse many of the gains of Green Revolution crops.
description: <strong>RNA-Seq</strong> For
 ambient carbon dioxide concentrations, T4 seedlings were cultured on
 plates for 4 days without drug selection, and then transplanted to LS0
 plates without drug for 10 days in either ambient or carbon
 dioxide-supplemented Conviron (Pembina, North Dakota) growth chambers. RNA
 was extracted using the Illustra RNAspin Mini Kit from GE, and RNA-Seq was
 performed by Amaryllis Nucleics (Oakland CA). In brief, RNA was checked
 for quality and quantity on a Bioanalyzer, and poly(A) mRNA was purified
 from total RNA. The library was constructed using the Amaryllis
 proprietary construction kit, followed by QC by E-gel &
 Bioanalyzer. Libraries were pooled and run on an Illumina NextSeq 500
 SR75, with a target of approximately 20 million reads per sample. Read
 preprocessing, mapping, and differential gene expression were performed by
 Amaryllis, in addition to independent differential gene expression
 analysis in-house using EdgeR and DESeq2. Network analysis was performed
 in cytoscape. GO terminology enrichment was calculated using g:profiler
 (biit.cs.ut.ee/gprofiler/gost) and plotted in R using ggplot2 (see code
 deposited at https://github.com/achillobator/GAHACR).
description: # Reprogramming feedback strength in gibberellin biosynthesis highlights
 conditional regulation by the circadian clock and carbon dioxide
 [https://doi.org/10.5061/dryad.547d7wmgr](https://doi.org/10.5061/dryad.547d7wmgr) ## Description of the data and file structure **Dataset overview:** Counts tables for differential gene expression performed in the analysis of 'reprogramming feedback strength in gibberellin biosynthesis highlights conditional regulation by the circadian clock and carbon dioxide' are provided for RNA-Seq experiments performed on Arabidopsis seedlings. We performed these at both Ambient and elevated (750ppm) carbon dioxide levels, with and without the GAHACR genetic perturbation, using GAHACRs to modulate the strength of feedback on endemic GA regulated genes, and to directly test the importance of transcriptional feedback in GA signaling. In order to facilitate future researchers to most easily incorporate our RNA-seq results, we have shared the count tables generated from our experiments.  ### Files and variables #### Description of the data and file structure ###### *Files and Folders* In general, all genotypes within these files will follow the same naming convention, where the parental GAHACR lacking any additional guide RNA is referenced as its plant number: 3943. This is used as the baseline for control in all experiments. The two lines carrying the four guide RNAs to retarget the dCAS9-TPLN repressor are labeled as 4578 and 4582. Individual biological replicates of the experiments are denoted with an underscore and a number, such as "_1", etc. Therefore, the three biological replicates for the parental are denoted as: "3943_1, 3943_2, 3943_3".  * **counts_ambient_GAHACR.txt** This file contains the raw counts from the HTSeq (htseq-count) function mapped to the *Arabidopsis* TAIR10 genome annotation. These samples were grown at ambient carbon dioxide levels (400-450ppm depending on fluctuations). The file has the following columns: AGI, 3943_1, 3943_2, 3943_3, 4578_1, 4578_2, 4578_3, 4582_1, 4582_2, 4582_3. The AGI term refers to the TAIR10 gene name. The columns are as described above, with three biological replicates for each of the genotypes.  * **counts_750ppm_GAHACR.txt** This file contains the raw counts from the HTSeq (htseq-count) function mapped to the *Arabidopsis* TAIR10 genome annotation. These samples were grown at elevated carbon dioxide levels (750ppm supplemented into the chamber). The file has the following columns: AGI, 3943_1, 3943_2, 3943_3, 4578_1, 4578_2, 4578_3, 4582_1, 4582_2, 4582_3. The AGI term refers to the TAIR10 gene name. The columns are as described above, with three biological replicates for each of the genotypes.  ## Code/software No specific code or software is required; these data files can be used to perform differential gene expression analysis in your program of choice, such as DESeq2 or EdgeR-type differential expression callers.  ## Access information Other publicly accessible locations of the data: * All code utilized to analyze this data is made publicly available at GitHub: [https://github.com/achillobator/GAHACR](https://github.com/achillobator/GAHACR) Data was derived from the following sources: * All sequencing was performed at Amaryllis Nucleics by Mike Covington, and count tables were generated by their in-house pipeline.