Genomics of Bioenergy Grass Architecture
Investigator: Paterson, A. H.
Institution: University of Georgia
Non-Technical Summary: Variations in plant architecture (size, shape, and branching) are central to the yield potential of biomass crops under favorable conditions and are a key element of crop adaptation to marginal environments under which most cellulosic biomass production may occur. Optimal biomass productivity in temperate latitudes and/or under perennial production systems may require substantial changes to architecture of plants of tropical origin that have previously been adapted to annual cultivation. Sorghum is one of the few crops suited to all proposed approaches for renewable fuel production, i.e. from starch, sugar, and/or cellulose; and as a botanical model for functional genomics of many other bioenergy plants, particularly Saccharum (sugarcane) and Miscanthus. Its low water requirements and adaptability to production regimes that reduce soil erosion further increase its intrinsic merit as renewable fuel crop. We will increase knowledge of the genetic determinants of components of plant architecture that are important to the design of crop genotypes optimized for production of biomass from a range of environments, also characterizing allelic and haplotype variation in salient sorghum genes toward their deterministic utilization, and enabling new integrative queries of these and other results to accelerate their utilization in biomass crop improvement. This project is expected to contribute to advancing energy security, scientific discovery, and environmental responsibility. Substantial economies are realized by leveraging data and tools generated under prior public research investments, and the present work will further enhance the value of many existing resources while also adding new dimensions to scientific research capacity.
Objectives: The specific goals and expected outputs of the proposed research are: (a) Genetically-dissect components of plant architecture that are important to productivity of bioenergy grasses under annual or perennial production systems. Forward genetics in three populations that span the range of variation in eusorghums will provide baseline QTL data for components of plant architecture and related traits, also assessing inter-relationships with one another and perenniality. (b) Investigate levels and patterns of DNA sequence variation in positional and functional candidate genes for association with phenotypic variation in plant architecture and other traits. Phenotyping and resequencing of positional and/or functional candidate genes in a validated panel that broadly and deeply samples S. bicolor genetic diversity, will narrow the locations of QTLs, reveal haplotype diversity in trait-controlling regions, and perhaps even identify functional variants in some instances. (c) Enrich online resources for meta-analysis and deterministic utilization of variants in plant architecture. We will facilitate searches for positional candidate genes affecting plant architecture by supplementing a CMAP-based QTL resource being developed under current program funding for Miscanthus, with new QTLs as well as orthologs, paralogs or other homologs of major genes cited below (plus new additions and any inadvertent omissions) that qualitatively impact plant architecture. Further, we will facilitate integrative use of positional, diversity, and mutant information in discovery and utilization of genetic variation by using Gramene trait ontologies to interleave three well-characterized but to date isolated genetic resources as described below.
Approach: Forward genetics will employ three populations, each sharing as a common parent the elite reference genotype BTx623, with the other parents varying widely morphologically, indeed collectively sampling the breadth of variation in the eusorghums (species sexually compatible with S. bicolor). Flowering time will be measured as anthesis dates for the first 5 flowers in a 3 meter row of about 30 plants. Leaf number and morphology will be measured shortly after flowering, including length (cm), width (mm), and angle from the main stalk/stem (degrees) of the 4th leaf below the inflorescence. Plant branching at physiological maturity (of the primary inflorescence) For each of two representative plants per plot, the number of primary branches (tillers) emanating from the crown, secondary branches emanating from primary branches, and tertiary branches emanating from secondary branches will be counted. To assess physiological status, each branch will be classified as vegetative, immature inflorescence, or physiologically mature inflorescence. Main stalk dimension at physiological maturity – we will measure length (height, cm) from crown to flag leaf, and flag leaf to the base of the inflorescence, number of nodes on the main stalk; and stalk diameter (mm) at the crown, midpoint, and base of the inflorescence (of stalk stripped of leaves and leaf sheaths). Stalk diameter is an important element of biomass yield, and in standability of crops which is essential to harvest efficiency; Biomass yield and distribution — stem yield per unit area; leaf and grain weights and yields; and dry matter contents, are fundamental to crop productivity and to photosynthate allocation to major organs, consistent with how a plant is used (seed/grain crop, cellulosic biomass crop emphasizing stalks, turf or forage crop emphasizing leaves). QTL mapping is expected to reveal windows of 10-20 cM that are likely to contain genes responsible for variations in plant architecture. To narrow the windows further, we will employ a well-characterized diversity panel and an association genetics approach. Phenotyping will follow the design, traits and methods described above for the genetic mapping populations. Resequencing and association genetic analysis will benefit from many additional resources. TASSEL will be used to perform both linkage disequilibrium analysis and tests of association, employing population structure covariates and a kinship matrix for the germplasm panel. We are near completion of a resource to integrate QTL, phenotypic, and molecular diversity data for sorghum using standardized trait ontologies and data formats. Here, we seek to facilitate integrative application of this resource with a database describing phenotypes for M3 EMS-induced sorghum mutant lines and a web application to facilitate the selection and analysis of phenotype and genotype data for the 377-member sorghum diversity panel, incorporating pedigree and passport data on these lines from NPGS, in accelerating discovery and utilization of genetic variation, by using the common trait ontology as a foundation for seamless queries.
Name: Andrew Paterson