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Genomics-Enabled Plant Biology for Determination of Gene Function
The DOE SC program in Biological and Environmental Research (BER) hereby announces its interest in receiving applications for research within the Biological Systems Science Division’s (BSSD) Genomic Science Program (GSP) (http://genomicscience.energy.gov) mission-space. This FOA solicits applications for: a) understanding of regulatory elements that control plant gene expression; b) approaches to understand the biological mechanisms that lead to differential gene expression of different members of gene families; and c) dissection of multigene traits and understanding their component parts.
Crop plants developed to be productive on lands unsuitable for traditional agricultural crops have the potential to play a significant role in the emerging bioeconomy as an alternative source of renewable feedstocks for fuels and chemicals. Plant scientists and breeders recognize that potentially bigger gains in productivity and sustainability may be realized in such crops by leveraging multi-omics approaches, systems biology, and computational biology to better understand the regulation of critical plant processes at the molecular level. However, understanding molecular function remains a challenge in plants due to several unique features, such as segmental and whole genome duplications, differences in mode of reproduction, and domestication.
Advances in ‘omics technologies together with computational modeling and data analysis are enabling the gathering of information on critical and complex plant processes such as metabolism, development, and signaling. Although immense amounts of data can be generated by these methodologies, much of the functional information obtained from them is generated by correlation analysis and computational inference, lacking causal and verifiable knowledge. Experimental characterization of gene function continues to be a significant bottleneck, hampering our ability to fully exploit the potential of available ‘omics data. This in turn limits direct understanding of how genes regulate organismal function and ultimately the ability to accurately assign and validate gene function in non-model organisms. By elucidating complex regulatory processes at the molecular, cellular, and organismal levels, a better understanding of plants as a whole and a more accurate prediction of plant behavior under varying conditions can be achieved.
To overcome these obstacles, more efficient, high-throughput methods for interpreting experimental evidence need to be developed for accurate determination of gene function. While experimental approaches are unlikely to scale with advances in ‘omics technologies, concentrated development and application of new approaches are required to tackle this critical knowledge gap of genomics space. The overarching goal of this FOA is to address the challenges and opportunities in associating gene(s) to function (i.e., genotype to phenotype) in plant systems of relevance to the BER mission in energy and the environment.
Specifically, this FOA seeks applications that employ systems biology and high throughput approaches to elucidate and validate the functional roles of genes, gene families, and associated pathways related to physiological and metabolic processes such as CO2 sequestration and belowground storage; nutrient and water use efficiency; tolerance and/or resistance to abiotic stresses such as drought and temperature extremes; developmental processes critical to enhanced biomass yield and optimization or extension of growth range; and metabolism of oils and fatty acids for biofuels and bioproducts.
- Required Pre-Application: Jan. 14, 2022
- Full Application: March 25, 2022
Applicant institutions are limited to no more than one letter of intent, pre-application, or application for each PI at the applicant institution. DOE will consider the latest received submissions to be the institution’s intended submissions.
Ceiling $1,000,000 per year
Floor $250,000 per year
DOE anticipates making awards with a project period of 3 years.