Location: Plant Physiology and Genetics Research
2019 Annual Report
Objectives
Objective 1: Characterize the molecular and physiological mechanisms governing crop response to heat and drought, including interactions, to use the information to identify and verify new genes and molecular markers useful for plant breeding.
Sub-objective 1A: Characterize the physiological and genetic mechanisms governing wax content and composition and heat shock proteins in cotton, under heat and drought conditions.
Sub-objective 1B: Characterize the physiological and genetic mechanisms governing wax content and composition and aquaporins in oilseeds, under heat and drought conditions.
Objective 2: Develop and validate field-based, high-throughput phenotyping strategies for rapid assessment of crop responses to heat and drought, including evaluation and validation of sensors, proximal sensing vehicles, and methods of data capture, storage, analysis, and interpretations.
Sub-objective 2A: Develop and deploy novel sensing platforms, sensor calibration devices, and sensor validation protocols for field-based high-throughput phenotyping.
Sub-objective 2B: Develop a database that can be queried, and a geospatial data processing pipeline for proximal sensing and imaging data collected from terrestrial platforms for field-based high-throughput phenotyping.
Objective 3: Characterize the molecular mechanisms of oil accumulation in agriculturally important plants under various inclement conditions, including heat and drought conditions, to identify and verify new genes and molecular markers to increase oil yields in both food and bioenergy crop plants.
Sub-objective 3A: Characterize the molecular and physiological mechanisms governing seed number, size, and weight for oilseeds and biofuel crops in response to heat and drought stress conditions.
Sub-objective 3B: Characterize the function of lipid droplet-associated proteins (LDAPs) and identify new genes involved in abiotic stress responses and oil production pathways in plants.
Sub-objective 3C: Use transgenic and gene-editing approaches to increase oil content and abiotic stress tolerance in crop plants.
Approach
A variety of experimental approaches including phenomics and associated “big data” management, field studies of cotton and camelina, genomics, and the molecular and biochemical studies of the model plant Arabidopsis, as well as camelina, Brassica napus, and cotton are involved.
Objective 1: To characterize the physiological and genetic mechanisms governing crop response to heat and drought, cotton and Brassica napus plants will be examined for genetic variability of these traits using conventional and high-throughput phenotyping approaches to determine canopy temperature, cuticular wax content and composition, and leaf chlorophyll content. A transcriptomics approach will be used to determine if known genes involved in wax or chlorophyll biosynthesis are underpinning the observed phenotypes, and ribonucleic acid (RNA) sequencing will be conducted with either PacBio or Illumina HiSeq technology.
Objective 2: To develop and validate field-based high-throughput phenotyping (FB-HTP) strategies for assessment of crop responses to heat and drought, novel platforms and sensor arrays, including carts, small robots and imagery, will be tested in cotton fields grown under high heat or drought stress. The FB-HTP collected traits will be assessed for accuracy and consistency using in-field calibration targets and ground truthing measurements. Semi-automated pipelines and databases will be developed to process and manage the data for statistical analysis of crop response to the environmental conditions.
Objective 3: To characterize the molecular and physiological mechanisms governing seed development and lipid-droplet-associated proteins (LDAPs) in biofuel crops, candidate gene-based and transgenic approaches will be used to examine the model system Arabidopsis and camelina. Gene function will be characterized using a combination of forward and reverse genetic approaches, coupled with cellular and biochemical studies of protein activity. Oil production in response to abiotic stress tolerance will be studied by examining the function of LDAPs and other lipid-related proteins in leaves and seeds of plants. Transgenic approaches will be used to increase oil content and abiotic stress tolerance in camelina.
Progress Report
This project has three main objectives that focus on crop improvement. The first objective is to characterize the molecular and physiological mechanisms that drive heat and drought tolerance in oilseeds and cotton. In support of Sub-objective 1A, a small greenhouse trial was conducted on six upland cotton lines and five Pima cotton lines to determine the content and composition of leaf wax and cutin monomers. Results showed significant differences between upland and Pima lines, where upland cotton produced more total wax and Pima produced more total cutin. Two of the upland cotton lines identified in this trial were crossed to develop a recombinant inbred line population. We intend to use this population to identify genomic regions associated with leaf wax and cutin development. These same lines were also included in the regional breeders testing network trials from 2016-2018. Fiber yield and quality were collected each year for this trial as well as canopy temperature and plant height at eight points throughout the growing season. Leaf tissue and fiber were collected in 2017 and assessed for wax content and composition. Results were similar to the greenhouse study showing significant differences between lines for both leaf wax and fiber wax. Analysis of plant height and canopy temperature are ongoing.
In support of Sub-objective 1B, two rapeseed genotypes with significant differences in wax content were selected to conduct a growth chamber experiment to study the effects of heat and drought stress on wax accumulation and other physiological traits. The results showed variations in total leaf wax content and composition among the selected genotypes within each stress treatment as well as between stress treatments. Chlorophyll content and photosynthetic efficiency were also estimated via leaf level fluorescence. Preliminary results indicate significant differences in these traits between the two genotypes and among stress treatments.
The second objective of the project is to develop and validate field-based, high-throughput phenotyping (HTP) platforms and data processing pipelines for rapid and accurate assessment of crops grown under high heat and drought conditions. The current high-clearance tractor and sensor package was evaluated to improve data quality and consistency. A cost-effective, light-weight sensor package was designed and equipped with a 3-band multispectral camera, an infrared thermometer array, and a Mini Light Detection and Ranging (LiDAR) sensor array to deliver phenotypic metrics of the spectral signature, temperature, and height of the plant canopy, respectively. Sensors and microcontrollers were surveyed for their performance and compatibility. A microcontroller was selected for its unique features of low power consumption and easy programming and interfaced with all sensors. An algorithm was developed to read a sequence of proximal sensor arrays and integrate with the camera control. A field-cart was also re-designed to minimize the frame weight, but still rigid enough to carry all sensors, controllers, and other wiring peripherals.
In support of Sub-objective 2A, two prototype calibration/validation panels were developed that can be interchanged on a custom-made height adjustable field-table. The first panel will be used to calibrate multi-spectral data collected from terrestrial-based platforms. The calibration data will be used in an interpolation model to correct for time-of-capture in the spectral data. The second panel will be used to calibrate the fluorescence images collected from the LemnaTec field scanner. The calibration data will be used to adjust the camera settings to the desired light settings to optimize fluorescence capture. In support of Sub-objective 2B, processing pipelines for each terrestrial platform were developed using the open source coding language Python. The pipelines process data by calculating the geospatial position of each data point captured using geospatial satellite positions, which enable users to associate captured data to each experimental plot for statistical analysis. The georeferenced data are then automatically transferred into a database for storage, curations, and subsequent analysis. The pipelines and database are currently being beta tested and minor adjustments will be made for the upcoming season.
The third objective is to characterize the molecular mechanisms of oil accumulation and increase oil yields in agricultural crops grown under high heat and drought conditions. In support of Sub-objective 3A, 250 genotypes from a Camelina sativa spring diversity panel, plus checks, were planted in Maricopa under well-irrigated and reduced irrigation regimes. At physiological maturity, plots were harvested to determine seed yield, seed weight, oil content, and fatty acid composition. Results showed significant variations in 1,000 seed weights, a trait indicative of seed size, among camelina genotypes within each irrigation treatment. Based on these results, two genotypes were selected with broadest seed size values for upcoming experiments.
In support of Sub-objectives 3B and 3C, we continued to study the molecular mechanisms of oil production in plants, with the goal of increasing oil content of oilseed crops and stabilizing oil yields when crops are challenged with environmental stresses such as heat and drought. We are currently focused on understanding how plant cells “package” oil into subcellular organelles called “lipid droplets”. Oil is synthesized in the endoplasmic reticulum (ER) of plant cells, then lipid droplets pinch off from the ER surface and become coated with various proteins. In collaboration with scientists from the University of Guelph and the University of North Texas, we previously described two key proteins that are involved in this process: SEIPIN, which acts at the surface of the ER to help facilitate the process of lipid droplet formation and budding, and lipid droplet associated proteins (LDAPs), which are abundant coat proteins that bind to the lipid droplet surface and stabilize the organelles in the cytoplasm. To identify additional proteins involved in lipid droplet formation and function, we used the LDAP coat proteins in an experiment to identify other interacting protein partners. One of these interacting proteins was called mycobacterial membrane protein large (MMPL), now called lipid droplet interacting proteins (LDIP), for LDAP-Interacting Protein. Notably, when the LDIP gene is disrupted, lipid droplets become much larger in both the leaves and seeds of plants, and there is a substantial increase in seed oil content. This finding was the subject of a recently filed patent application.
To determine how LDIP functions to regulate oil content in plants, we first asked whether LDIP might serve as an anchoring protein that allowed the LDAPs to bind to the lipid droplet surface. The hypothesis was that in the absence of LDIP, the abundant LDAP coat proteins would not be able to associate with lipid droplets, allowing them to grow much larger in size. However, when we expressed LDAPs in plant cells that were disrupted for LDIP, not only did the LDAPs still target to lipid droplets, but the droplets were much larger in size. Subsequent experiments further revealed that the LDAPs bind to lipid droplets first, then recruit LDIP to the lipid droplet surface. We then showed that LDIP also interacted with the SEIPIN protein in the endoplasmic reticulum (ER), indicating that LDIP is dual-localized, spending part of its time working together with SEIPIN in the ER, and part of its time on lipid droplets with LDAPs. The interaction of LDIP with SEIPIN was shown to be critical for regulating the number and size of lipid droplets produced in plant cells.
We are also exploring the role of lipid droplets and their associated proteins during stress response in plants. We recently showed that the abundance of lipid droplets increases dramatically in plant cells during heat or drought stress, but their roles in this adaptive response are unknown. We recently identified a new lipid droplet protein called ERD7 (Early Responsive to Dehydration 7) that is highly induced during a variety of stress responses, and when disrupted in plant cells, results in a significant increase in lipid droplet abundance in comparison to wild type. Our data suggests that ERD7 plays an important role in regulating lipid droplet abundance and function during stress response.
We have also extended our studies of LDAP and LDIP to the oilseed crop camelina and identified specific LDAP genes that are strongly induced during heat and drought stress. Our current work focuses on development of transgenic lines to determine whether, as in the model plant Arabidopsis, there is an increase in heat and drought stress tolerance when LDAPs are over-expressed. We are also creating camelina lines that suppress expression of LDIP, with the end-goal of increasing seed oil content. These lines will be tested first in the greenhouse before moving to the field.
Accomplishments
1. High-throughput phenotyping methods determine water use efficiency in cotton. Plant water use efficiency (WUE) is an important trait for crops grown under dry-land or limited irrigation production. WUE is a difficult trait to quantify, requiring information tools for quantifying how much water is used by the crop; and therefore, has rarely been applied to breeding trials. ARS researchers at Maricopa, Arizona, developed an approach to rapidly quantify crop water use for a large number of cotton breeding plots. The approach provided new and improved data that permitted selection of varieties that were more drought tolerant and used water more efficiently. This approach provides a valuable new tool for plant breeders and researchers aiming to use information technologies to quantify plant WUE.
2. High-throughput phenotyping methods determine plant height in cotton. Plant height is an important characteristic of plant growth that is a useful indicator of plant stress resulting from water and nutrient deficit. While this trait is relatively simple, it can be difficult to measure accurately in crops with complex canopy architectures, like cotton. Manual measurements of plant height can be time-consuming and expensive, especially in large breeding trials, and are prone to human error, reducing repeatability. ARS researchers and University collaborators at Maricopa, Arizona, have developed and validated two high-throughput phenotyping methods for determining plant height in cotton. One method utilizes terrestrial platforms and inexpensive ultrasonic transducers, and the other utilizes images captured with a small hobby drone. These methods provide valuable new tools for plant researchers to assess plant height accurately throughout the growing season to improve breeding and selection decisions.
Review Publications
Teresinski, H.J., Gidda, S.K., Nhuyen, T.N., Howard, M., Porter, B.K., Grimberg, N., Smith, M.D., Andrews, D.W., Dyer, J.M., Mullen, R.T. 2018. An RK/ST C-terminal motif is required for targeting of OEP7.2 and a subset of other Arabidopsis tail-anchored proteins to the plastid outer envelope membrane. Plant and Cell Physiology. 60:516-537. https://doi.org/10.1093/pcp/pcy234.
Vanhercke, T., Dyer, J.M., Mullen, R.T., Kilaru, A., Rahman, M.M., Petrie, J.R., Green, A.G., Yurchenko, O., Singh, S.P. 2019. Metabolic engineering for enhanced oil in biomass. Progress in Lipid Research. 74:103-129. https://doi.org/10.1016/j.plipres.2019.02.002.
Thompson, A.L., Thorp, K.R., Conley, M.M., French, A.N., Andrade-Sanchez, P., Pauli, D. 2019. Comparing nadir and multi-angle view sensor technologies for measuring in-field plant height of upland cotton. Remote Sensing of Environment. 11:700-719. https://doi.org/10.3390/rs11060700.
Luo, Z., Brock, J., Dyer, J.M., Kutchan, T., Augustin, M., Scachtman, D., Ge, Y., Fahlgren, N., Abdel-Haleem, H.A. 2019. Genetic diversity and population structure of a Camelina sativa spring panel. Frontiers in Plant Science. 10:184. https://doi.org/10.3389/fpls.2019.00184.
Thorp, K.R., Thompson, A.L., Harders, S.J., French, A.N., Ward, R.W. 2018. High-throughput phenotyping of crop water use efficiency via multispectral drone imagery and a daily soil water balance model. Remote Sensing. 10(11):1682. https://doi.org/10.3390/rs10111682.
Yurchenko, O., Kimberlin, A., Mehling, M.E., Koo, A.J., Chapman, K., Mullen, R.T., Dyer, J.M. 2018. Response of high leaf-oil Arabidopsis thaliana plant lines to biotic or abiotic stress. Plant Signaling and Behavior. 13(5):e1464361. https://doi.org/10.1080/15592324.2018.1464361.
