Location: Plant Genetics Research2013 Annual Report
1a. Objectives (from AD-416):
Objective 1: Determine functions of genes previously identified through systems approaches of molecular, bioinformatics and genomics, and assess how they function as a network to control or regulate seed oil quality traits in plantae. Sub-Objective 1A: Determine functions of transcription factor genes in oil production and transcriptional regulatory networks by altering their expression in transgenic plants. Sub-Objective 1B: Determine functions of miRNA genes in defining oil production and their underlying regulatory networks by altering their activities in transgenic plants. Sub-Objective 1C: Determine functions of soybean genes in oil composition and content by exploring conservation of soybean and Arabidopsis. We have predicted a large number of transcription factor genes and microRNA genes potentially controlling oil quality traits in soybean seeds, and modeled their underlying gene regulatory networks. In this plan, we will select a minimum of two transcription factor genes and microRNA genes, and validate their functions in Sub-Objective 1A and 1B respectively through altering their activities in soybean transgenic seeds. It is time consuming to evaluate gene functions using a transgenic approach in soybean so we have decided to use a bioinformatics approach to improve the prediction of gene function in the proposed research. This approach will entail a genomic and evolutionary based comparison of expression profiles of protein coding sequences and miRNAs in soybean and Arabidopsis seeds over the course of seed maturation in Sub-Objective 1C. This will also enable us to translate knowledge and resources from model plant research into soybean oil quality improvement.
1b. Approach (from AD-416):
To determine the function of transcription factor genes and regulatory networks in soybean oil production a bioinformatic approach will be used to refine a selection of previously identified target genes. The resultant candidate genes will be functionally characterized in situ using an RNAi approach to impair the natural expression of the native gene in transgenic soybean lines. Functionality will be assessed by assessment of the seed oil composition in the transgenic lines. MicroRNA species that regulate oil production pathways in soybean seeds will be validated bioinformatically and by direct testing using standard molecular technologies. Transgenic approaches will be used to determine the functions of the miRNAs in regulating oil content and composition in seeds and their underlying gene regulatory networks by overexpressing or suppressing activity of the selected miRNAs in soybean. The functions of selected soybean genes in the control of oil composition and content will be explored by comparative bioinformatics approaches using Arabidopsis as a model seed. The soybean/Arabidopsis orthologous genes encoding candidate seed specific transcription factors will be preferentially selected for functional validation. The functional significance and equivalence of the paired Arabidopsis and soybean genes will be validated by selecting a minimum of two pairs of Arabidopsis/soybean genes, examine the oil and transcriptomic phenotypes of mutants that can be identified in Arabidopsis, use complementation transgenic strategies to determine if the soybean genes can functionally complement the phenotypes of the Arabidopsis mutants. The soybean genes that exhibit functions in oil composition and content will then be directly tested in soybean transgenic plants.
3. Progress Report:
Production of storage oil in seeds requires concerted activities of many genes and biological pathways over the course of seed maturation. However, lack of knowledge on the intricate biological network and the availability of its key regulatory components has been a bottleneck in the effective application of both breeding and biotechnological approaches for soybean oil quality improvement. Previously, ARS scientists in St. Louis, MO inferred a set of transcription factor regulatory networks underlying soybean seed maturation, and in a related project, identified a set of genes potentially regulating soybean oil quality traits by examining nine soybean germplasm varying in oil content and composition. We also identified and characterized 243 miRNA genes expressed in soybean cotyledon. To further select key regulatory gene candidates with the highest confidence in regulation of oil content and composition to validate their regulatory functions and underlying regulatory networks, we inferred miRNA gene regulatory networks, and characterized their topology. In addition, we determined the RNA degradome and constructed cDNA libraries in soybean cotyledon for RNA-seq. We are integrating the miRNA regulatory networks with transcription factor regulatory networks and the oil quality related genes identified in 9 soybean germplasm to select the genes regulating oil content and composition through a variety of data mining strategies.