Abstract Detail

Phytochemical

Mahood, Elizabeth [1], Kruse, Lars [2], Bennett, Alexandra [3], Bravo, Armando [4], Ishka, Maryam [4], Kelkar, Chinmaey [5], Jiang, Yulin [6], Harrison, Maria [4], Vatamaniuk, Olean [7], Moghe, Gaurav [8].

Leveraging Integrative Omics Analyses for Stress-Responsive Metabolic Pathway Elucidation in Brachypodium.

Specialized metabolic pathways produce organ-specific or lineage-specific metabolites that are frequently important for survival under stress and proper ecological interactions. The biosynthesis of specialized metabolic genes has historically been difficult to elucidate, as they often belong to large gene families that undergo frequent gene duplication. In my talk, I will describe the results of an integrated transcriptomics and metabolomics experiment in the model C3 species Brachypodium distachyon, designed to elucidate metabolic functions of genes. B. distachyon plants were grown under different conditions (heat, Copper [Cu] deficiency, combined heat-Cu deficiency stress, low Phosphate [P], and Arbuscular Mycorrhizal Symbiosis [AMS]). Transcripts and metabolites were simultaneously extracted from leaves and roots, and RNA-seq and untargeted metabolomics was performed.
After an exploratory analysis of the data, metabolic genes contributing to specialized metabolite production were identified through a combination of correlation and phylogenetic approaches. Principal Components Analysis of the metabolomic data generated an expected clustering of metabolomic datasets by organs and growing conditions. Information theoretic analysis further revealed that while leaves had the most complex metabolite profiles, root metabolomes were more inducible and produced more condition-specific metabolites, especially under heat stress and AMS. Our results also suggest that Cu deficiency conditions the roots, better preparing them for subsequently applied heat stress – a finding of particular significance to improving crop resilience. Differential analysis of metabolite levels coupled with deep learning techniques helped identify broadly stress-responsive metabolite types such as sphingolipids, glycerolipids and phospholipids. Many condition-specific metabolites – such as blumenols (C13 apocarotenoids) – that can potentially serve as stress biomarkers were also found.
After metabolite structural annotation and gene expression quantification, we identified genes with conserved expression under AMS and with structurally similar, highly correlated metabolites as candidates of biosynthetic pathways. This workflow successfully identified multiple metabolic genes of known importance in AMS as well as identified new candidate genes regulating plant metabolism under AMS in B. distachyon. Validation of these genes and elucidation of their function in AMS is underway.
Associating stress-induced genes with metabolic pathways may provide an efficient method of gene function prediction in understudied species, as well as yield breeding targets for the creation of more stress-tolerant plants.

1 - Cornell University, Plant Biology, 266 Emerson Hall, 306 Tower Rd., Ithaca, NY, 14850, USA
2 - University of British Columbia, Michael Smith Laboratories, Vancouver, BC, V6T 1Z4, Canada
3 - University of Natural Resources and Life Sciences, Institute for Analytical Chemistry, 18 Muthgasse, Vienna, Austria
4 - Boyce Thompson Institute, 533 Tower Rd., Ithaca, NY, 14850, USA
5 - Cornell University, Data Science and Statistics, 266 Emerson Hall, 306 Tower Rd., Ithaca, NY, 14850, USA
6 - Sichuan Agricultural University, Triticeae Research Institute, Wenjiang 611130, Sichuan, China
7 - Cornell University, Soil and Crop Sciences, 608 Bradfield Hall, 306 Tower Rd., Ithaca, NY, 14850, USA
8 - Cornell University, Plant Biology, 306 Tower Road, 260 Emerson Hall, Ithaca, NY, 14853, United States

Keywords:
Integrative omics
Brachypodium
abiotic stress
arbuscular mycorrhiza
specialized metabolism
Gene function prediction.

Presentation Type: Oral Paper
Session: PHYT1, Phytochemistry I
Location: /
Date: Tuesday, July 20th, 2021
Time: 10:45 AM(EDT)
Number: PHYT1004
Abstract ID:949
Candidate for Awards:Phytochemical Best Oral Presentation Award