Digital Commons Network^™

Dct4—A New Member Of The Dicarboxylate Transporter Family In C4 Grasse, Sarit Weissmann, Pu Huang, Madeline A. Wiechert, Koki Furuyama, Thomas P. Brutnell, Mitsutaka Taniguchi, James C. Schnable, Todd C. Mockler

Center for Plant Science Innovation: Faculty and Staff Publications

Malate transport shuttles atmospheric carbon into the Calvin–Benson cycle during NADP-ME C4 photosynthesis. Previous characterizations of several plant dicarboxylate transporters (DCT) showed that they efficiently exchange malate across membranes. Here, we identify and characterize a previously unknown member of the DCT family, DCT4, in Sorghum bicolor. We show that SbDCT4 exchangesmalateacrossmembranesanditsexpressionpatternisconsistentwitharoleinmalatetransportduringC4 photosynthesis. SbDCT4 is not syntenic to the characterized photosynthetic gene ZmDCT2, and an ortholog is not detectable in the maize reference genome. We found that the expression patterns of DCT family genes in the leaves of Zea mays, and S. bicolor varied by cell type. Our results suggest that …

Dynamic Transcriptomic And Phosphoproteomic Analysis During Cell Wall Stress In Aspergillus Nidulans, Cynthia Chelius, Walker Huso, Samantha Reese, Alexander Doan, Stephen Lincoln, Kelsi Lawson, Boa Tran, Raj Purohit, Trevor Glaros, Ranjan Srivastava, Steven D. Harris, Mark R. Marten

Center for Plant Science Innovation: Faculty and Staff Publications

The fungal cell-wall integrity signaling (CWIS) pathway regulates cellular response to environmental stress to enable wall repair and resumption of normal growth. This complex, interconnected, pathway has been only partially characterized in filamentous fungi. To better understand the dynamic cellular response to wall perturbation, a-glucan synthase inhibitor (micafungin) was added to a growing A. nidulans shake-flask culture. From this flask, transcriptomic and phosphoproteomic data were acquired over 10 and 120 min, respectively. To differentiate statistically-significant dynamic behavior from noise, a multivariate adaptive regression splines (MARS) model was applied to both data sets. Over 1800 genes were dynamically expressed and over …

Semantic Segmentation Of Sorghum Using Hyperspectral Data Identifies Genetic Associations, Chenyong Miao, Alejandro Pages, Zheng Xu, Eric Rodene, Jinliang Yang, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

This study describes the evaluation of a range of approaches to semantic segmentation of hyperspectral images of sorghum plants, classifying each pixel as either nonplant or belonging to one of the three organ types (leaf, stalk, panicle). While many current methods for segmentation focus on separating plant pixels from background, organ-specific segmentation makes it feasible to measure a wider range of plant properties. Manually scored training data for a set of hyperspectral images collected from a sorghum association population was used to train and evaluate a set of supervised classification models. Many algorithms show acceptable accuracy for this classification task. …

Advances In Plant Phenomics: From Data And Algorithms To Biological Insights, Sunil Kumar Kenchanmane Raju, Addie M. Thompson, James Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

The measurement of the characteristics of living organisms is referred to as phenotyping (Singh et al., 2016). While the use of phenotyping in plant biology and genetics can be traced back at least to Gregor Mendel sorting and counting peas by shape and pod color 160 years ago, addressing current questions in plant biology, genetics, and breeding often requires increasingly precise phenotyping of a wide range of traits. Accurate phenotyping has played a role in both novel discoveries about the fundamental biology of plants and the development of improved crop varieties around the world. With the advent of inexpensive genotyping …

Non-Homology-Based Prediction Of Gene Functions In Maize (Zea Mays Ssp. Mays), Xiuru Dai, Zheng Xu, Zhikai Liang, Xiaoyu Tu, Silin Zhong, James Schnable, Pinghua Li

Center for Plant Science Innovation: Faculty and Staff Publications

Advances in genome sequencing and annotation have eased the difficulty of identifying new gene sequences. Predicting the functions of these newly identified genes remains challenging. Genes descended from a common ancestral sequence are likely to have common functions.As a result, homology is widely used for gene function prediction. This means functional annotation errors also propagate from one species to another. Several approaches based on machine learning classification algorithms were evaluated for their ability to accurately predict gene function from non-homology gene features. Among the eight supervised classification algorithms evaluated, random forest-based prediction consistently provided the most accurate gene function prediction. …

Voxel Carving-Based 3d Reconstruction Of Sorghum Identifies Genetic Determinants Of Light Interception Efficiency, Mathieu Gaillard, Chenyong Miao, James C. Schnable, Bedrich Benes

Center for Plant Science Innovation: Faculty and Staff Publications

Changes in canopy architecture traits have been shown to contribute to yield in- creases. Optimizing both light interception and light interception efficiency of agri- cultural crop canopies will be essential to meeting the growing food needs. Canopy architecture is inherently three-dimensional (3D), but many approaches to measuring canopy architecture component traits treat the canopy as a two-dimensional (2D) structure to make large scale measurement, selective breeding, and gene identifi- cation logistically feasible. We develop a high throughput voxel carving strategy to reconstruct 3D representations of sorghum from a small number of RGB photos. Our approach builds on the voxel carving …

Compounds For Increasing Lipid Synthesis And Storage, Concetta Dirusso, Nishikant Wase

Center for Plant Science Innovation: Faculty and Staff Publications

This invention relates to methods for increasing lipid accumulation and lipid production in cells. Methods of producing biofuel from cells and preparing nutraceuticals comprising lipids produced according to a method provided herein are also provided.

Non-Homology-Based Prediction Of Gene Functions In Maize (Zea Mays Ssp. Mays), Xiuru Dai, Zheng Xu, Zhikai Liang, Xiaoyu Tu, Silin Zhong, James C. Schnable, Pinghua Li

Center for Plant Science Innovation: Faculty and Staff Publications

Advances in genome sequencing and annotation have eased the difficulty of identifying new gene sequences. Predicting the functions of these newly identified genes remains challenging. Genes descended from a common ancestral sequence are likely to have common functions. As a result, homology is widely used for gene function pre- diction. This means functional annotation errors also propagate from one species to another. Several approaches based on machine learning classification algorithms were evaluated for their ability to accurately predict gene function from non-homology gene features. Among the eight supervised classification algorithms evaluated, random- forest-based prediction consistently provided the most accurate gene …

Advances In Plant Phenomics: From Data And Algorithms To Biological Insights, Sunil K. Kenchanmane Raju, Addie M. Thompson, James Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

The measurement of the characteristics of living organisms is re- ferred to as phenotyping (Singh et al., 2016). While the use of phe- notyping in plant biology and genetics can be traced back at least to Gregor Mendel sorting and counting peas by shape and pod color 160 years ago, addressing current questions in plant biology, genet- ics, and breeding often requires increasingly precise phenotyping of a wide range of traits. Accurate phenotyping has played a role in both novel discoveries about the fundamental biology of plants and the development of improved crop varieties around the world. With the advent …

Metabolic Profiles Of Six African Cultivars Of Cassava (Manihot Esculenta Crantz) Highlight Bottlenecks Of Root Yield, Toshihiro Obata, Patrick A.W. Klemens, Laise Rosado-Souza, Armin Schlereth, Andreas Gisel, Livia Stavolone, Wolfgang Zierer, Nicolas Morales, Lukas A. Mueller, Samuel C. Zeeman, Frank Ludewig, Mark State, Uwe Sonnewald, H. Ekkehard Neuhaus, Alisdair R. Femie

Center for Plant Science Innovation: Faculty and Staff Publications

Cassava is an important staple crop in sub-Saharan Africa, due to its high productivity even on nutrient poor soils. The metabolic characteristics underlying this high productivity are poorly understood including the mode of photosynthesis, reasons for the high rate of photosynthesis, the extent of source/sink limitation, the impact of environment, and the extent of variation between cultivars. Six commercial African cassava cultivars were grown in a greenhouse in Erlangen, Germany, and in the field in Ibadan, Nigeria. Source leaves, sink leaves, stems and storage roots were harvested during storage root bulking and analyzed for sugars, organic acids, amino acids, phosphorylated …

Increased Power And Accuracy Of Causal Locus Identification In Time Series Genome-Wide Association In Sorghum1[Open], Chenyong Miao, Yuhang Xu, Sanzhen Liu, Patrick S. Schnable, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

The phenotypes of plants develop over time and change in response to the environment. New engineering and computer vision technologies track these phenotypic changes. Identifying the genetic loci regulating differences in the pattern of phenotypic change remains challenging. This study used functional principal component analysis (FPCA) to achieve this aim. Time series phenotype data were collected from a sorghum (Sorghum bicolor) diversity panel using a number of technologies including conventional color photography and hyperspectral imaging. This imaging lasted for 37 d and centered on reproductive transition. A new higher density marker set was generated for the same population. Several genes …

Leaf Angle Extractor: A High-Throughput Image Processing Framework For Leaf Angle Measurements In Maize And Sorghum, Sunil Kumar Kenchanmane Raju, Miles Adkins, Alex Enersen, Daniel Santana De Carvalho, Anthony J. Studer, Baskar Ganapathysubramanian, Patrick S. Schnable, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

PREMISE: Maize yields have significantly increased over the past half-century owing to advances in breeding and agronomic practices. Plants have been grown in increasingly higher densities due to changes in plant architecture resulting in plants with more upright leaves, which allows more efficient light interception for photosynthesis. Natural variation for leaf angle has been identified in maize and sorghum using multiple mapping populations. However, conventional phenotyping techniques for leaf angle are low throughput and labor intensive, and therefore hinder a mechanistic understanding of how the leaf angle of individual leaves changes over time in response to the environment.

METHODS …

Plant Segmentation By Supervised Machine Learning Methods, Jason Adams, Yumou Qiu, Yuhang Xu, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

High-throughput phenotyping systems provide abundant data for statistical analysis through plant imaging. Before usable data can be obtained, image processing must take place. In this study, we used supervised learning methods to segment plants from the background in such images and compared them with commonly used thresholding methods. Because obtaining accurate training data is a major obstacle to using supervised learning methods for segmentation, a novel approach to producing accurate labels was developed. We demonstrated that, with careful selection of training data through such an approach, supervised learning methods, and neural networks in particular, can outperform thresholding methods at segmentation.

Interspecific Analysis Of Diurnal Gene Regulation In Panicoid Grasses Identifies Known And Novel Regulatory Motifs, Xianjun Lai, Claire Bendix, Lang Yan, Yang Zhang, James C. Schnable, Frank G. Harmon

Center for Plant Science Innovation: Faculty and Staff Publications

Background: The circadian clock drives endogenous 24-h rhythms that allow organisms to adapt and prepare for predictable and repeated changes in their environment throughout the day-night (diurnal) cycle. Many components of the circadian clock in Arabidopsis thaliana have been functionally characterized, but comparatively little is known about circadian clocks in grass species including major crops like maize and sorghum.

Results: Comparative research based on protein homology and diurnal gene expression patterns suggests the function of some predicted clock components in grasses is conserved with their Arabidopsis counterparts, while others have diverged in function. Our analysis of diurnal gene expression in …

Leaf Angle Extractor: A High-Throughput Image Processing Framework For Leaf Angle Measurements In Maize And Sorghum, Sunil Kumar Kenchanmane Raju, Miles Adkins, Alex Enersen, Daniel Santana De Carvalho, Anthony J. Studer, Baskar Ganapathysubramanian, Patrick Schnable, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

PREMISE: Maize yields have significantly increased over the past half-century owing to advances in breeding and agronomic practices. Plants have been grown in increasingly higher densities due to changes in plant architecture resulting in plants with more upright leaves, which allows more efficient light interception for photosynthesis. Natural variation for leaf angle has been identified in maize and sorghum using multiple mapping populations. However, conventional phenotyping techniques for leaf angle are low throughput and labor intensive, and therefore hinder a mechanistic understanding of how the leaf angle of individual leaves changes over time in response to the environment.

METHODS: High-throughput …

Isoseq Transcriptome Assembly Of C3 Panicoid Grasses Provides Tools To Study Evolutionary Change In The Panicoideae, Daniel S. Carvalho, Aime V. Nishimwe, James C. Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

The number of plant species with genomic and transcriptomic data has been increasing rapidly. The grasses—Poaceae—have been well represented among species with published reference genomes. However, as a result the genomes of wild grasses are less frequently targeted by sequencing efforts. Sequence data from wild relatives of crop species in the grasses can aid the study of domestication, gene discovery for breeding and crop improvement, and improve our understanding of the evolution of C₄ photosynthesis. Here, we used long-read sequencing technology to characterize the transcriptomes of three C₃ panicoid grass species: Dichanthelium oligosanthes, Chasmanthium laxum, and …

Oxidosqualene Cyclases Involved In The Biosynthesis Of Triterpenoids In Quercus Suber Cork, Lucas Busta, Olga Serra, Ok Tae Kim, Marisa Molinas, Irene Peré-Fossoul, Mercè Figueras, Reinhard Jetter

Center for Plant Science Innovation: Faculty and Staff Publications

Cork is a water-impermeable, suberin-based material harboring lignin, (hemi)cellulose, and extractable small molecules (primarily triterpenoids). Extractables strongly influence the properties of suberin-based materials. Though these previous findings suggest a key role for triterpenoids in cork material quality, directly testing this idea is hindered in part because it is not known which genes control cork triterpenoid biosynthesis. Here, we used gas chromatography and mass spectrometry to determine that the majority (>85%) of non-polar extractables from cork were pentacyclic triterpenoids, primarily betulinic acid, friedelin, and hydroxy-friedelin. In other plants, triterpenoids are generated by oxidosqualene cyclases (OSCs). Accordingly, we mined Quercus suber …

Methods And Compositions For Obtaining Useful Plant Traits, Sally Mackenzie, Michael Fromm, Kamaldeep Viridi, Yashitola Wamboldt

Center for Plant Science Innovation: Faculty and Staff Publications

The present invention provides methods for obtaining plants that exhibit useful traits by perturbation of plastid function in plant rootstocks and grafting the rootstocks to scions. Methods for identifying genetic loci that provide for useful traits in plants and plants produced with those loci are also provided. In addition, plants that exhibit the useful traits, parts of the plants including seeds, and products of the plants are provided as well as methods of using the plants. Recombinant DNA vectors and transgenic plants comprising those vectors that provide for plastid perturbation are also provided.

A High-Throughput Phenotyping Pipeline For Image Processing And Functional Growth Curve Analysis, Ronghao Wang, Yumuo Qiu, Yuzhen Zhou, Zhikai Liang, James Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

High-throughput phenotyping system has become more and more popular in plant science research. The data analysis for such a system typically involves two steps: plant feature extraction through image processing and statistical analysis for the extracted features. The current approach is to perform those two steps on different platforms. We develop the package “implant” in R for both robust feature extraction and functional data analysis. For image processing, the “implant” package provides methods including thresholding, hidden Markov random field model, and morphological operations. For statistical analysis, this package can produce nonparametric curve fitting with its confidence region for plant growth. …