DOE OSTI · 1850002
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Ko, Dae Kwan, Brandizzi, Federica. 2020-08-28. Network-based approaches for understanding gene regulation and function in plants. https://doi.org/10.1111/tpj.14940
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Identifying upstream regulators of key genes is essential for understanding gene regulatory mechanisms and translating these insights into functional targets. Here, we present a protocol for applying the network-enabled gene discovery pipeline (NEEDLE) to non-model plant species. We describe steps for environment setup, data preparation, computational analysis, expected outputs, and parameter considerations. NEEDLE integrates RNA sequencing (RNA-seq) processing, weighted gene co-expression analysis (WGCNA), Gene Network Inference with Ensemble of trees (GENIE3), and promoter conservation analysis to prioritize candidate transcriptional regulators.
Abstract In leaves, major CO₂ fluxes alternate between fixation by the Calvin-Benson-Bassham (CBB) cycle during light and release by the tricarboxylic acid (TCA) cycle in darkness. The speed at which leaf metabolism transitions between these pathways likely influences plant tolerance to fluctuating light conditions. To investigate these rapid metabolic shifts, we exposed leaves to ¹³CO₂ for 20 min to establish a quasi-steady state before abruptly turning off the light while maintaining ¹³CO₂ feeding. Within 10 s of dark transition, 3-phosphoglycerate levels rose significantly while most other CBB cycle intermediates decreased by more than 90%. Simultaneously, carbon accumulated in alanine, likely via pyruvate. Over the subsequent 10 min, six- and five-carbon TCA cycle intermediates steadily increased. In contrast, four-carbon TCA intermediates peaked at one minute, declined at three minutes, and rose again at 10 min, a pattern mirrored by most measured amino acids. These results reveal an exceptionally rapid metabolic reconfiguration from CO₂ fixation by the CBB cycle in light to TCA cycle activation for energy production in darkness, accompanied by substantial changes in amino acid metabolism.
While controlled environments are desirable for growing and measuring plants, growth chambers and greenhouses typically have microclimates that impact plant growth, development, and stress responses. Furthermore, opening and closing the doors of a controlled environment introduces variation in the environment, especially at temperature extremes, affecting both the measurements and the organisms within. Using multiple temperature data loggers to normalize results can be cost-prohibitive and rarely offers real-time feedback on temperature status. We used low-cost single-board computers, cameras, and temperature sensors to manage and capture growth chamber temperatures while acquiring plant image data. Detailed here are methods to document microclimates within a growth chamber so that data can be normalized to measured temperature information. This protocol describes a low-cost method for automated temperature monitoring, which enables both high-throughput measurements of temperature along with plant growth and stress responses via plant imaging.