Location: Plant Gene Expression Center
Project Number: 2030-21000-042-00-D
Project Type: Appropriated
Start Date: Jun 14, 2013
End Date: Jun 13, 2018
The long-term goal of this program is to define the cellular, molecular and biochemical mechanisms by which light-activated phytochrome (phy) molecules transduce environmentally-generated signaling information to the genes they regulate. The specific objectives of this project plan are: Objective 1: Define the functional roles of phytochrome (phy) interacting transcription factors (PIFs) in regulating plant growth and developmental responses to light using mutant analysis. [NP 301, C3, PS 3A] Objective 2: Identify phy-PIF-pathway-regulated genes through high-throughput RNAseq analysis. [NP 301, C3, PS 3A] Objective 3: Define the primary phy-PIF-regulated transcriptional network using ChIPseq (chromatin immunoprecipitation sequence) analysis to identify direct targets of the PIFs among the rapidly light-regulated gene-set. [NP 301, C3, PS 3A] Objective 4: Define the functional roles and downstream targets of the transcription-factor-encoding (TFE) genes in this primary network using CHIPseq analysis and RNAseq-based transcript profiling of mutants at these loci. [NP 301, C3, PS 3A]
Objective 1: Hypothesis: Phytochrome (phy) interacting transcription factors (PIFs) in addition to PIFs 1,3,4 and 5 have functional roles in regulating plant growth and developmental responses to light. Approach: We will obtain higher order combinations of mutants with the PIF mutants and with mutants in other components of the light signaling pathway in order to determine the phenotypes. We will screen for mutants starting with quadruple mutants in the PIF genes. Contingencies: Although we plan to use high-throughput sequencing to identify mutants of interest, if this proves to be problematic, we will consider including more traditional map-based procedures that have previously provided numerous mutants for our program over many years. Objective 2: Hypothesis: Genes identified by RNAseq analysis of wild-type and various pif- mutant combinations will identify genes that include potential direct targets of PIF-regulated transcription genome-wide. Approach: We will analyze the expression profiles of selected combinations of the PIF mutants by RNAseq. Objective 3: Hypothesis: ChlPseq analysis will identify the promoter sites to which the PIF proteins bind physically in vivo, data which, when integrated with the RNAseq transcriptome data, will identify direct targets of PIF transcriptional regulation. Approach: We will carry out chromatin immunoprecipitation in dark grown wild type or PIF:MYC fusion protein plants. A subset of these genes will be selected for validation and reproducibility of the observed PIF binding by qPCR. For a further subset, we will generate promoter-fusion constructs with the LUC reporter gene. Initially we will use these constructs in a transient transfection assay that we developed for examining transcriptional activity in etiolated Arabidopsis seedlings using particle bombardment. Objective 4: Hypothesis: Integration of ChlPseq and RNAseq analyses of the downstream targets of PIF-targeted TFE genes will define the landscape and predicted functional trajectory of the various branches of the transcriptional cascade presumed to emanate from the primary transcriptional network. Approach: We will use the ChIP-seq strategy to screen for promoters that bind selected members of the transcription factors identified encoded by direct PIF-target genes. T-DNA-insertional mutants in these selected TFE genes will be identified and used for RNA-seq analysis to define the downstream transcriptional network they regulate. Contingencies - Objectives 2, 3 and 4 Most aspects of the proposed technology are already operative in this laboratory, and our preliminary data indicate that the assays and analysis are working successfully. However, should we encounter difficulties with the RNAseq or ChlPseq experiments, we will consider refined or alternative strategies. For example, should the RNAseq strategy not provide interpretable data, we will revert to the use of the now available Affymetrix tiling array platform for full genome transcriptome coverage, a technology with which we have extensive experience in the ATH1 format (Tepperman et al., 2001; 2004; 2006; Monte et al., 2004; Leivar et al.,2009; 2012a).