Photosynthetic parameters of switchgrass (Panicum virgatum) under low radiation: Influence of stable overexpression of Miscanthus×giganteus PPDK on responses to light and CO2 under warm and cool growing conditions

Halter, Mathew; Mitchell, Jackson; Mann, David G. J.; Muthukumar, B.; Stewart, C. Neal; Nilsen, Erik T.

doi:10.1016/j.neps.2015.08.001

Cited by 4 publications

(2 citation statements)

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“…Another important enzyme identified here was pyruvate orthophosphate dikinase (PPDK) and it was only expressed significantly in VS16 but not in AP13. An increase in PPDK has been reported in cold tolerant species of sugar cane indicating the ability of PPDK content as a factor for cold tolerance (Halther et al 2015). VS16 is able to tolerate cold temperatures better than AP13 and this may be the reason for the significant increase of PPDK in VS16 compared to AP13.…”

Section: Discussionmentioning

confidence: 96%

Comparative transcriptome profiling of upland (VS16) and lowland (AP13) ecotypes of switchgrass

et al. 2016

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Key message Transcriptomes of two switchgrass genotypes representing the upland and lowland ecotypes will be key tools in switchgrass genome annotation and biotic and abiotic stress functional genomics. AbstractSwitchgrass (Panicum virgatum L.) is an important bioenergy feedstock for cellulosic ethanol production. We report genome-wide transcriptome profiling of two contrasting tetraploid switchgrass genotypes, VS16 and AP13, representing the upland and lowland ecotypes, respectively. A total of 268 million Illumina short reads (50 nt) were generated, of which, 133 million were obtained in AP13 and the rest 135 million in VS16. More than 90% of these reads were mapped to the switchgrass reference genome (V1.1). We identified 6619 and 5369 differentially expressed genes in VS16 and AP13, respectively. Gene ontology and KEGG pathway analysis identified key genes that regulate important pathways including C4 photosynthesis, photorespiration and phenylpropanoid metabolism. A series of genes (33) involved in photosynthetic pathway were up-regulated in AP13 but only two genes showed higher expression in VS16. We identified three dicarboxylate transporter homologs that were highly expressed in AP13. Additionally, genes that mediate drought, heat, and salinity tolerance were also identified. Vesicular transport proteins, syntaxin and signal recognition particles were seen to be up-regulated in VS16. Analyses of selected genes involved in biosynthesis of secondary metabolites, plant–pathogen interaction, membrane transporters, heat, drought and salinity stress responses confirmed significant variation in the relative expression reflected in RNA-Seq data between VS16 and AP13 genotypes. The phenylpropanoid pathway genes identified here are potential targets for biofuel conversion.Electronic supplementary materialThe online version of this article (doi:10.1007/s00299-016-2065-0) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 96%

Comparative transcriptome profiling of upland (VS16) and lowland (AP13) ecotypes of switchgrass

et al. 2016

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“…Nitrogen use efficiency (NUE) is another important sustainability trait given the high cost of fertilization [3,4]. Low NUE and little fertilizer would decrease switchgrass biomass production [5][6][7][8][9][10]. Lignin is a secondary metabolite found in the cell walls of plants and a major contributor to the cell wall recalcitrance as it inhibits the accessibility of cellulose to enzymatic breakdown into fermentable sugars for biofuel production [11].…”

Section: Introductionmentioning

confidence: 99%

Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

Shrestha

Piasecki

et al. 2021

Plants

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Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this study, we used UAV-based remote sensing for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. Using vegetation indices calculated from a UAV-based multispectral camera, statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potentials for multiple traits associated with sustainable production of switchgrass, and one statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait. Also, for the first time, lignin content was estimated in switchgrass shoots via UAV-based multispectral image analysis and statistical analysis. The UAV-based models were verified by ground-truthing via correlation analysis between the traits measured manually on the ground-based with UAV-based data. The normalized difference red edge (NDRE) vegetation index outperformed the normalized difference vegetation index (NDVI) for rust disease and nitrogen content, while NDVI performed better than NDRE for chlorophyll and lignin content. Overall, linear models were sufficient for rust disease and chlorophyll analysis, but for nitrogen and lignin contents, nonlinear models achieved better results. As the first comprehensive study to model switchgrass sustainability traits from UAV-based remote sensing, these results suggest that this methodology can be utilized for switchgrass high-throughput phenotyping in the field.

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Tweaking Crassulacean Acid Metabolism (CAM)‐Cycling Plants for Crop Productivity Improvement in View of a Bioenergy Crop,Jatropha curcasLinn

Govender

Dorairaj

Mohamed‐Hussein

et al. 2021

Annual Plant Reviews Online

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Crassulacean acid metabolism (CAM)‐cycling plants display both the C3and CAM photosynthetic pathways at various extents in response to environmental and plant physiological conditions. Evolved from the C3metabolism, CAM is a photosynthetic adaptation specialised to improve plant water‐use efficiency by shifting/extending the CO2uptake from the day to the night. Obligate CAM plants such as the Agave species, pineapples, orchids, and prickly pears are highly productive and respond favourably to extreme heat and drought, and water‐limited environments. In comparison to the C3and C4plants, agricultural CAM crops can thrive in semi‐arid and arid lands, making them an ideal and sustainable commercial crop for food and energy. Very few plants exhibit the CAM‐cycling pathway, while the fairly well‐known examples includeMesembryanthemum crystallinum(ice plant) andJatropha curcas(physic nut). In such plants bestowed with the ability to interchange different photosynthetic metabolisms, little is known on how each unique photosynthetic metabolism is likely to contribute to overall plant growth and development. This article explores the utilisation of CAM for biomass and yield improvement in a bioenergy crop (J. curcas) conferred with CAM‐cycling photosynthetic machinery. TheJ. curcasphotosynthetic‐associated parameters, yield components in relation to transcriptomic data analyses from previous studies are described and discussed to benefit plant breeding programs targeted for productivity enhancement.

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Photosynthetic parameters of switchgrass (Panicum virgatum) under low radiation: Influence of stable overexpression of Miscanthus×giganteus PPDK on responses to light and CO2 under warm and cool growing conditions

Cited by 4 publications

References 38 publications

Comparative transcriptome profiling of upland (VS16) and lowland (AP13) ecotypes of switchgrass

Comparative transcriptome profiling of upland (VS16) and lowland (AP13) ecotypes of switchgrass

Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

Tweaking Crassulacean Acid Metabolism (CAM)‐Cycling Plants for Crop Productivity Improvement in View of a Bioenergy Crop,Jatropha curcasLinn

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