Gene Expression Networks and their Regulators in a Model Perennial Plant
Principal Investigator: Matias Kirst
Agency: National Science Foundation - Genes and Genome System Cluster
Duration: 08/2008 – 08/2009
Gene expression networks may be defined as the organization and relationships of elements that control transcription of functionally related genes. Previous studies have established the feasibility of characterizing the genetic architecture of gene expression regulation based on full genome sequence and transcriptome profiling of segregating populations. However, few studies have attempted to utilize this information to describe transcription networks of genes and their regulators, and define the mechanisms of this regulation. The architecture and relationship of the entire ensemble of genes and their transcription regulators represents the first level of information required to link genome and genotype to phenotype. Describing these networks and their diversity also provides insight into the role of transcription regulation in the evolution of higher plants and the genetic basis of phenotypic diversity.
A comprehensive description of the genetic regulation of gene expression will be generated for the perennial model plant Populus trichocarpa, defining the contribution of specific and interacting genetic loci to transcript abundance variation. Gene expression networks will be identified and genetic models for their control will be generated for different plant tissues, creating the first description of their ontogeny, diversity and conservation. Network regulators and the mechanisms by which they control downstream network elements will also be pursued. To achieve these objectives, whole-genome microarrays will be analyzed in combination with the P. trichocarpa genome sequence. QTL for gene transcript abundance variation (eQTL) will be mapped, defining number and location of eQTL, additive and epistatic effects, and the proportion of the phenotypic variation explained by each locus. Comparison of the location of gene sequence and its corresponding eQTL will define cis or trans-acting regulation, and candidate regulatory genes. Gene expression networks will be defined based on coordinated regulation of functionally related genes and shared eQTLs (eQTL hotspots). Poplar is an ideal model plant for such analysis because the genome of P. trichocarpa has been sequenced, detailed genetic maps with ample microsatellite coverage have been constructed, and whole-genome microarrays are publicly available. Large, genetically variable and widely segregating populations, which are essential for QTL identification, are also readily available and can be clonally replicated easily. More important, extensive preliminary data that supports the study proposed here has been created. This data includes whole-genome transcript profiles for a large progeny (200 individuals) of Populus, in three developmentally distinct plant organs: differentiating secondary xylem, whole roots and mature leaves. The feasibility of mapping QTL for gene expression in woody plants, and the application of this approach for defining the genetic mechanism of transcript regulation of genes and networks has been established by the PI Kirst (Plant Physiol. (2004) 135:2368; Genetics (2005) 169: 2295-2303).
The proposed project will provide training and support for two graduate students using innovative approaches that integrate quantitative genetics and genomics. It will also create opportunities for high-school students from underrepresented groups to participate in research at the University of Florida during the last two years of the project. For the plant scientific community, this research will establish a framework for comparisons with the architecture of transcript regulation in monocots, other dicots, and gymnosperms. The models of genetic regulation of individual genes and metabolic and regulatory networks will provide support for the analysis and modification of pathway products for improvement of phenotypes and metabolic engineering. The population that will be used in this study has been extensively phenotyped for growth, plant architecture, wood quality, leaf and root phenotype, pest resistance, water-use efficiency and phenology traits – QTLs for most traits have been documented. Over 250 metabolites have also been measured in the differentiating secondary xylem of this population, using pyrolysis-MBMS. This phenotypic information, in combination with the research proposed, will be used to accelerate plant breeding and identify genes associated with quantitative variation of commercially important traits for the agricultural and forestry industry, using the model established in our previous studies (Plant Physiol. (2004) 135:2368). All the primary data will be deposited in microarray databases (NCBI-GEO), and integrated with genome sequence, genetic maps, and the Gene Ontology / Kegg functional annotation based on a visual, searchable tool.