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Enhancing stress tolerance using a synthetic phase-dependent stress response.
Circadian biologists have associated large portions of the transcriptome with temporal regulation by the circadian clock. One consequence of this internal timekeeping in plants is time of day dependent responses to abiotic and biotic stress. Given the energy costs associated with mounting a defense response it is not surprising that plants restrict the response to the time when its effectiveness is maximal. Rather than thinking of stress response as simply on or off, we focus on fine-tuning the timing of the response in a more 'turn up or down' approach. Adjusting the amplitude of the response within the normal phase domain and maintaining the timing of essential growth processes has the potential to enhance stress tolerance without a reduction in fitness. 
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Predicting stress improvement targets using regulatory network guided pattern discovery.
Crop improvement relies on the identification of genetic markers that confer beneficial trait modifications. Identifying the gene and desired modification that will provide the desired trait improvement is a challenging task. Alterations to a single loci can have cascading effects on the larger transcriptional network leading to inadvertent effects like yield reduction under stress-free conditions. In the Greenham lab, we are building gene regulatory networks from time course abiotic stress experiments to associate transcriptomic patterns with metabolic profiles. Using machine learning approaches to uncover temporal patterns common among similar phenotypic measures will provide targets for trait improvement by genome editing techniques. Collaborators: Adrian Hegeman - UMN Cory Hirsch - UMN Tools Created: DiPALM - Differential Pattern Analysis via Linear Modeling Funding: JGI-CSP2019 |
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Investigating the role of nectar glucosinolates in pollinator attraction in Brassica crops
Improved understanding of plant-pollinator interactions have the potential to increase crop yield and support higher populations of native and managed pollinator species. Brassica fields promote pollinator diversity and abundance yet pollinator forage sources in the Upper Midwest have declined in recent years. Nectar provides essential calories and metabolites for pollinator growth and development. Glucosinolates (GSLs) are a class of specialized metabolites found in the Brassicaceae that are well known for their anti-herbivory properties. GSLs vary in abundance throughout the day in leaf tissue suggesting that they are under diel and/or circadian regulation. We are investigating the levels of GSLs in nectar and how they influence pollinator visitation. Collaborators:
Adrian Hegeman - UMN Clay Carter - UMN Rahul Roy - St. Catherine University Dan Cariveau - UMN |
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The role of the circadian clock during crop domestication.
The Brassicaceae is one of the most diverse plant families containing more than 3700 species, many of current and potential agronomic and economic value. Arabidopsis, a member of the Brassicaceae, continues to be a powerful model for plant growth, but how does this knowledge translate to crop systems? Arguably, the most important aspect of the Brassicaceae is morphological diversity. The Brassica genus supplies much of this diversity and contains crops with leaf, flower and root vegetables for consumption, food and fodder and oil production. The agricultural importance of Brassica crops is evident by the history of its early domestication in Europe and Asia. Most widely known are B. rapa (AA, 2n=20), B. oleracea (CC, 2n=18) and B. napus (AACC, 2n=38), the allopolyploid derived from B. rapa and B. oleracea. B. rapa includes a range of croptypes including turnip, Chinese cabbage, pak choi and oilseed. Their potential as model crops lies in their long history of domestication and local adaptation. We find extensive variation in circadian traits among croptypes suggesting diversity in circadian parameters have contributed to crop domestication and local adaptation. We are generating a pan-genome in B. rapa to assess genomic variation of the circadian network from diel transcriptomic and metabolomic profiling of abiotic stress response. Using morphotype-specific gene regulatory networks we can improve target predictions of traits that are unique to a morphotype. |
Nat Rev Genet. 2015 Nov;16(11):681
Transcript abundance profiles of the circadian clock gene TOC1 on chromosome A03 in four croptypes of Brassica rapa.
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