bioRxiv Science⌕ Search

bioRxiv · 10.1101/2020.06.03.130179

VipariNama: RNA vectors to rapidly reprogram plant morphology and metabolism

Abstract

Synthetic transcription factors have great promise as tools to explore biological processes. By allowing precise alterations in gene expression, they can help elucidate relationships between gene expression and plant morphology or metabolism. However, the years-long timescales, high cost, and technical skill associated with plant transformation have dramatically slowed their use. In this work, we developed a new platform technology called VipariNama (ViN) in which RNA vectors are used to rapidly deploy synthetic transcription factors and reprogram gene expression in planta. We demonstrate how ViN vectors can direct activation or repression of multiple genes, systemically and persistently over several weeks, and in multiple plant species. We also show how this transcriptional reprogramming can create predictable changes to metabolic and morphological phenotypes in the model plants Nicotiana benthamiana and Arabidopsis thaliana in a matter of weeks. Finally, we show how a model of gibberellin signaling can guide ViN vector-based reprogramming to rapidly engineer plant size in both model species as well as the crop Solanum lycopersicum (tomato). In summary, using VipariNama accelerates the timeline for generating phenotypes from over a year to just a few weeks, providing an attractive alternative to transgenesis for synthetic transcription factor-enabled hypothesis testing and crop engineering.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Khakhar, A., Wang, C., Swanson, R., Stokke, S., Rizvi, F., Sarup, S., Hobbs, J., Voytas, D. F.. 2020-06-04. VipariNama: RNA vectors to rapidly reprogram plant morphology and metabolism. https://doi.org/10.1101/2020.06.03.130179

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

In-cell structural analysis reveals a distinctive chloroplast ribosome in Chlamydomonas reinhardtii

Chloroplast ribosomes synthesize plastid-encoded components of photosynthetic machinery, yet their structure and organization remain poorly understood. We combined cryo-focused ion beam milling, cryo-electron tomography and subtomogram averaging to determine native chloroplast ribosomes in Chlamydomonas reinhardtii. The 4.4-4.9 [A] structure revealed a large arch-like extension on the small subunit (SSU). Comparisons with bacterial and plant chloroplast ribosomes, supported by proteomics, AlphaFold3 predictions and a recent atomic model, indicate that the arch is formed by insertions and extensions in SSU proteins. Classification resolved active, thylakoid-associated ribosomes with density adjacent to the nascent peptide exit and an arch-moved state enriched among thylakoid-associated particles, with coordinated displacement of the arch and beak. Phylogenetic analysis revealed an evolutionary mosaic: the uS3c insertion is broadly distributed across Chlorophyceae, whereas the uS2c insertion, uS5c and PSRP7 are concentrated in Chlamydomonadales, with PSRP7 also in Sphaeropleales. Nuclear-encoded components were recruited stepwise onto a plastid-encoded scaffold, with all four under comparable purifying selection. These findings link a lineage-specific SSU extension to ribosome dynamics, thylakoid association and evolution, highlighting the value of in-cell structural analysis.

plant biology↗

Implementation and calibration of the Vaganov-Shashkin model in the virtualRings R package

Process-based tree growth models provide a mechanistic framework for investigating how climate conditions regulate tree growth across daily to annual time scales. Yet, their broader application across species and environments is constrained by the limited accessibility in open-source environments and the difficulty of estimating physiological parameters that are rarely measured directly. Here, we present virtualRings, a new R package integrating the Vaganov-Shashkin model (VSM) and the RINGS3 models, and focus on the implementation and calibration of VSM. Using tree-ring width observations from seven Northern Hemisphere sites across various environmental conditions, we compared the traditional bootstrap-based calibration approach with the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). CMA-ES improved agreement between simulated and observed radial tree growth and provided an efficient approach for model parameter estimation. We further evaluated practical CMA-ES settings to balance computational cost and performance and discussed its potential limitations. The virtualRings package provides an open and reproducible platform for tree growth simulation, facilitating the application of important process-based models across species and environments and the investigation of how temperature and moisture constraints regulate daily tree-ring formation across spatial and temporal scales.

plant biology↗

Timing of transient darkness shapes carbon-nitrogen metabolism and sugar signaling in sugarcane

Fluctuating light is common in field environments. Yet, the mechanisms by which C4 crops coordinate carbon and nitrogen metabolism during short-term carbon deprivation remain poorly understood. Here, we imposed transient darkness at different phases of the diel cycle to assess how the timing of light loss affects photosynthesis, carbohydrate turnover, amino acid dynamics, and sugar-sensing pathways in commercial sugarcane leaves. Early-day darkness significantly impaired photosynthetic induction and revealed a temporal disconnect between stomatal and metabolic limitations, whereas midday and late-day treatments caused temporary, time-specific disruptions in carbon assimilation. These shifts altered the balance between sucrose preservation and catabolic mobilization, leading to treatment-dependent changes in starch reserves and free amino acids. Core circadian components largely maintained their phase relationships, but their amplitudes varied across treatments, consistent with partial decoupling from carbon status. Darkness also reorganized energy signaling, with SnRK1 and DIN6 responses associated with greater declines in sucrose. Notably, trehalose-pathway transcripts showed marked changes in network connectivity, with ScTPSIIG consistently emerging as a highly connected candidate associated with photosynthetic performance, water-use traits, sugar sensing, and amino acid metabolism. Overall, these results indicate that the timing of carbon limitation and residual sucrose availability shape distinct metabolic responses, while trehalose metabolism provides a candidate regulatory layer coordinating carbon-nitrogen adjustment during the diel cycle, highlighting class II TPS proteins as targets for functional investigation of metabolic resilience in sugarcane.

plant biology↗