ISU Plant Sciences Institute

PSI Faculty Scholars

 


Madan Bhattacharyya, Ph.D. 

Dr. Bhattacharyya’s PSI project focuses on identifying genes for adapting crop plants to extreme weather conditions that may arise following climate change.

Ludovico Cademartiri, Ph.D. 

Dr. Cademartiri’s PSI project focuses on creating a set of integrated tools to allow the scientific community to create completely customizable environments for conducting plant biology and plant ecology experiments with complete phenotyping of shoot and root.  

Hui-Hsien Chou, Ph.D. 

Dr. Chou’s PSI project focuses on further development of his Mango tool for heterogeneous BIG DATA analyses.

Carolyn Lawrence-Dill, Ph.D. 

Dr. Lawrence-Dill’s predictive plant phenomics project focuses on three areas...


Liang Dong, Ph.D. 

Dr. Dong’s PSI project focuses on developing and deploying inexpensive microscale sensors and biochips for direct measurement of important chemical and physical signals related to plant responses to various environmental stresses


Baskar Ganapathysubramanian, Ph.D. 

Dr. Ganapathysubramanian’s PSI project focuses on high-throughput algorithms for image processing, data dimensionality reduction, as well as mechanistic models of plant growth. 


Stephen Howell, Ph.D. 

Dr. Howell’s PSI project is a two-pronged approach...


Thomas Lübberstedt, Ph.D. 

Dr. Lübberstedt ‘s PSI research project addresses the fundamental question of why and how plants with only a single genome (haploids) differ from perfect isogenic genotypes with two identical genomes (isogenic doubled haploids).


Allen Miller, Ph.D. 

Dr. Miller’s PSI project focuses on developing a new technology called ribosome profiling to monitor global gene expression at the level of protein synthesis.


Dan Nettleton, Ph.D.

Dr. Nettleton’s PSI project has established a statistical research group consisting of faculty and graduate students in the department of statistics who are developing statistical methods for predicting phenotypes from genotypic and environmental data.

 

Maria Salas Fernandez, Ph.D.

Dr. Salas Fernandez’s PSI project includes designing and developing high-yielding sorghum ideotypes through operations research...

 

Patrick Schnable, Ph.D.  

Dr. Schnable's scientific investigations of the maize genome have been wide-ranging and he has developed and/or deployed a number of important genomic tools and resources.


Lie Tang. Ph.D. 

Dr. Tang’s PSI project encompasses a broad range of robotic systems including...


Lizhi Wang, Ph.D. 

Dr. Wang’s PSI project includes two focus areas...


Steven Whitham, Ph.D.  

Dr. Whitham’s PSI project stems from his lab’s work to develop virus-based tools for functional genomics in plants.

 


Yanhai Yin, Ph.D. 
Dr. Yin’s PSI project is a collaboration with several research groups in developing new phenotyping tools that can be used to study the functions of a large number of genes in Gene Regulatory Networks (GRNs).


Jianming Yu, Ph.D.

Dr. Yu’s PSI project focuses on establishing an integrated modeling approach for performance prediction.

 

 

Madan Bhattacharyya, Ph.D. 

Madan Bhattacharyya is a professor in the department of agronomy. He manages a research program studying the sudden death syndrome (SDS) in soybean, an emerging disease caused by the fungal pathogen, Fusarium virguliforme. The Bhattacharyya group is also involved in understanding the non-host resistance mechanism of Arabidopsis against the soybean pathogen, P. sojae
 
Dr. Bhattacharyya’s PSI project focuses on identifying genes for adapting crop plants to extreme weather conditions that may arise following climate change. To accomplish his goal, Bhattacharyya is evaluating the responses of over 1,000 Arabidopsis ecotypes to extreme growing conditions through objective phenotyping and conducting  genome-wide association studies to identify candidate adaptation genes. 
 

Ludovico Cademartiri, Ph.D. 

Ludovico Cademartiri is an assistant professor in the department of materials science engineering. While biology has made great strides in the implementation of sophisticated methods for the characterization of the various -omics, less has been done to improve and standardize the tools available for the growing of plants in controlled environments. Dr. Cademartiri’s research group is dedicated to developing simple and controllable model systems to understand the role of the abiotic and biotic environment on the development of plants and ecosystems to test hypotheses.
 
Dr. Cademartiri’s PSI project focuses on creating a set of integrated tools to allow the scientific community to create completely customizable environments for conducting plant biology and plant ecology experiments with complete phenotyping of shoot and root.  
 

Hui-Hsien Chou, Ph.D. 

Hui-Hsien Chou is an associate professor in the department of genetics, development and cell biology. His research interest is the development of sophisticated computer algorithms and their implementations to efficiently solve large-scale biological research problems, e.g., a heterogeneous network analysis and visualization tool (Mango, with an embedded Graph Exploration Language, Gel). His software tools generally employ novel approaches to computing, provide convenient graphical user interfaces for end-users, and run efficiently across all major computing platforms. 
 
Dr. Chou’s PSI project focuses on further development of his Mango tool for heterogeneous BIG DATA analyses. Mango can load all the pathways of a species at once, merge them into a single combined large network, then superimpose additional information such as transcription data, protein-protein interactions or ontology networks on the combined network to facilitate biological discoveries. 
 

Carolyn Lawrence-Dill, Ph.D. 

Carolyn Lawrence-Dill is an associate professor in the department of genetics, development and cell biology.  Her research program is devoted to developing computational systems that support the plant research community.  Her lab’s work enables the use of existing and emerging knowledge to establish common standards and methods for data collection, integration, and sharing. 
 
Dr. Lawrence-Dill’s predictive plant phenomics project focuses on three areas:  
Developing standards that democratize data access and analysis and enable community development of systems that interoperate; creating examples of successful phenotypic prediction enabled by developed standards, a proof of concept, and to advance novel concepts for downstream broad implementation; and developing a coordinated network of research groups to develop and deploy data standards relevant to genotypic diversity, environmental documentation, and phenotypic prediction.
 

Liang Dong, Ph.D. 

Liang Dong is an associate professor in the department of computer and electrical engineering. His research interests include Micro/Nano-Electro-Mechanical Systems (MEMS/NEMS); lab on a chip; microfluidics, optics and smart materials and structures and their applications in sustainable agriculture; biomedicine, renewable energy; and information technology. As an engineer in the area of Micro-Electro-Mechanical Systems, Dr. Dong develops small-scale devices with critical dimensions ranging from micrometers to millimeters through inexpensive fabrication processes. He also integrates these devices into sensor networks for large-scale, high-throughput, in-field measurements.
 
Dr. Dong’s PSI project focuses on developing and deploying inexpensive microscale sensors and biochips for direct measurement of important chemical and physical signals related to plant responses to various environmental stresses. 
 

Baskar Ganapathysubramanian, Ph.D. 

Baskar Ganapathysubramanian is an associate professor in the department of mechanical engineering. His research interests are in the areas of computational mechanics, physics and scientific computing. His lab leverages advances in applied mathematics and high-performance computing to model, design and control real-world physical phenomena. From the application point-of-view, his lab is particularly interested in energy and environment-related phenomena. They develop mathematical techniques and computational tools — model reduction, multi-scale frameworks, multi-physics simulators, control algorithms, data-driven methods — to efficiently model these systems. Whenever possible, they validate the techniques using the expertise of their experimental collaborators.
 
Dr. Ganapathysubramanian’s PSI project focuses on high-throughput algorithms for image processing, data dimensionality reduction, as well as mechanistic models of plant growth.
 

Stephen Howell, Ph.D. 

Stephen Howell is a distinguished professor in the department of genetics, development and cell biology. His research focuses on abiotic stresses, such as heat, drought, flooding and salt stress, the major causes of crop losses worldwide. Stress tolerance has become an even more important trait as we face the prospects of climate change. His lab studies how plants perceive and respond to environmental stresses through a mechanism called the Unfolded Protein Response (UPR).  
 
Dr. Howell’s PSI project is a two-pronged approach – the first is to identify genetic determinants in plant populations that confer stress tolerance and the second is to modulate the expression of genes encoding known components on the UPR signaling pathway.  This involves defining the UPR signaling network composed of genes that are upregulated or downregulated by stress and characterizing the stress tolerance in UPR mutants during vegetative and reproductive development. This information will help scientists predict gene edits that might best contribute to stress tolerance phenotypes.
 

Thomas Lübberstedt, Ph.D. 

Thomas Lübberstedt is a professor in the department of agronomy and the K.J. Frey Chair in Agronomy. His general research area is the application/development of tools and methods provided by genome analysis to understand the composition of complex traits and phenomena, using this knowledge to determine and exploit genetic diversity in elite and exotic germplasm, and then applying this knowledge to plant breeding. Crop focus is on maize and perennial grasses. Current activities focus on accelerating plant breeding by establishing and improving doubled haploid technologies in maize and other species.
 
Dr. Lübberstedt ‘s PSI research project addresses the fundamental question of why and how plants with only a single genome (haploids) differ from perfect isogenic genotypes with two identical genomes (isogenic doubled haploids). This information will ultimately be used to establish high-throughput procedures to select for haploid plantlets or cells in vitro. His research group is utilizing “germplasm enhancement in maize” (GEM) DH lines, which were established in collaboration with the USDA to incorporate exotic germplasm into elite germplasm. These GEM-DH lines are currently used in genome-wide association studies of agronomic as well as root and phytohormone-related traits in collaboration with engineers to identify valuable exotic alleles.
 

Allen Miller, Ph.D. 

Allen Miller is a professor in the departments of plant pathology & microbiology and biochemistry, biophysics & molecular biology. His research program employs plant viruses as easy-to-use model systems to provide the basic understanding of how viruses express genes and replicate. Because of similarities across kingdoms, this knowledge may be relevant to major human viruses. The lab focuses on viral RNA structures that recruit host translation factors in novel ways, providing a better understanding of how the genetic code can be decoded. In addition to revealing targets for engineered virus resistance in crop plants, this knowledge may allow modification of viral sequences to regulate viral and host gene expression in beneficial ways.  
 
Dr. Miller’s PSI project focuses on developing a new technology called ribosome profiling to monitor global gene expression at the level of protein synthesis. The lab is performing RNAseq on every segment of mRNA being translated by a ribosome. This provides a more reliable measure of gene expression than traditional RNAseq, which simply sequences all the mRNAs. Ribosome profiling indicates how much each of those mRNAs is actually being translated into protein, the ultimate step in gene expression that leads from genotype to phenotype. It also reveals new genes, not known previously because they lack conventional signals in their sequences, a common occurrence in viruses. The lab will apply this tool to understand how virus infection, which is heavily controlled at the level of translation, affects translation of the host transcriptome. This will provide valuable insight into how the virus hijacks cellular gene expression to its own advantage, which may ultimately suggest virus resistance strategies that disrupt virus-host interactions.
 

Dan Nettleton, Ph.D. 

Dan Nettleton is a distinguished professor in the department of statistics and the Laurence H. Baker Endowed Chair and director of the Laurence H. Baker Center for Bioinformatics and Biological Statistics. His research interests include statistical design and analysis of high-throughput experiments in biology and the development of statistical learning methods for prediction.  
 
Dr. Nettleton’s PSI project has established a statistical research group consisting of faculty and graduate students in the department of statistics who are developing statistical methods for predicting phenotypes from genotypic and environmental data. Specific projects include the prediction of yield for a given variety in a given environment using historical yield trial results and weather information as training data; the prediction of multiple plant traits from DNA marker data and spatial locations of plants in a field; the prediction of plant phenotypes from DNA marker data combined with transcriptomic data; and improvement of the random forest methodology for general prediction problems.
 

Maria Salas Fernandez, Ph.D. 

Maria Salas Fernandez is an associate professor in the department of agronomy. Her research program is devoted to developing superior sorghum lines to be used as lignocellulosic feedstock for biofuel production and to discovering genes/alleles associated with traits that confer superior biomass yield through the use of molecular and genomic technologies. The genetic knowledge generated in her research program will be applied to sorghum but could also be utilized for the genetic improvement of other crops. Sorghum was selected as the crop focus based on the genotypic and phenotypic variation of the species, and its potential as a biofuel source. Sorghum can be used to produce ethanol from grain, stover, sugars accumulated in the stems (sweet sorghums) or as a dedicated lignocellulosic biomass crop (particularly photoperiod-sensitive types). 
 
Dr. Salas Fernandez’s PSI project includes designing and developing high-yielding sorghum ideotypes through operations research; determining the relationship between photosynthesis and biomass accumulation under drought assessed by high-throughput image analysis; and utilizing natural variation in photosynthetic capacity to model sorghum biomass production and adaption using a mechanistic framework.
 

Patrick Schnable, Ph.D.  

Patrick Schnable is a distinguished professor in the department of agronomy and Iowa Corn Endowed chair in genetics. He manages a research program that emphasizes interdisciplinary approaches to understanding plant biology. His own expertise is in the areas of genetics, molecular biology, genomics, bioinformatics, and high-throughput phenotyping but he collaborates with researchers in diverse fields, including agricultural and computer engineering, plant breeding, statistics and soil science.  He is the director of the Plant Sciences Institute, and under his direction, the Plant Sciences Institute’s Faculty Scholars are pursuing unique interdisciplinary approaches to the field of predictive plant phenomics.  
 
Dr. Schnable's scientific investigations of the maize genome have been wide-ranging and he has developed and/or deployed a number of important genomic tools and resources. However, the focus of his PSI project is on constructing and deploying new sensors and robots to facilitate the automated collection of the large volumes of phenotypic data at multiple locations needed to develop an understanding of GxE interactions. For example, networked systems of hundreds of computer-controlled cameras that enable high-throughput, high-resolution, field-based time-lapse photography for studying maize growth/development and responses to environmental stresses have been deployed at multiple locations over multiple years.
 

Lie Tang. Ph.D. 

Lie Tang is an associate professor in the department of agricultural & biosystems engineering. He is an expert in developing various automation and robotic systems for agricultural and biological applications.   
 
Dr. Tang’s PSI project encompasses a broad range of robotic systems including high-throughput robotic phenotyping; robotic weed control; autonomous field robot navigation control and operational path optimization; and machine vision algorithms for plant and animal monitoring and characterization. 
 

Lizhi Wang, Ph.D. 

Lizhi Wang is an associate professor in the department of industrial manufacturing systems engineering. His research interests include bilevel optimization algorithm design; plant breeding; power systems modeling and analysis; manufacturing supply chain; and transportation system resiliency assessment and enhancement.
 
Dr. Wang’s PSI project includes two focus areas. The first is designing new genomic selection strategies using operations research. The objective is to optimize a set of phenotypes, e.g., high yield with herbicide resistance, within a certain number of breeding generations subject to a budget constraint. The second is the detection of epistatic effects. Integer programming models are being developed to detect epistatic effects from genotype and phenotype data sets.
 

Steven Whitham, Ph.D. 

Steven Whitham is a professor in the department of plant pathology & microbiology.  His research focuses on the molecular mechanisms that underlie plant interactions with viruses and fungi. Projects in his lab involve studies on the major row crop plants, soybean and corn, as well as utilizing model host plants such as Arabidopsis thaliana and Nicotiana benthamiana. The lab uses functional genomics approaches to study the molecular changes that occur in susceptible and resistant genotypes of crop and model plant species. The plant and pathogen genes identified in these studies are providing insight into the ways successful pathogens interact with and manipulate their hosts and by which plants deploy defense mechanisms. 
 
Dr. Whitham’s PSI project stems from his lab’s work to develop virus-based tools for functional genomics in plants. Using a technology known as virus-induced gene silencing, the researchers can program viruses to turn off any plant gene to study the functions of that gene in plant processes. They are interested in using virus-induced gene silencing in large-scale screens designed to identify plants genes that mediate defense against pathogens and the trade-offs between plant defenses versus growth. The large-scale screens they envision will be enabled by automated systems for collecting and analyzing image and spectral data that will enhance their ability to associate plant genes with phenotypes of interest.
 

Yanhai Yin, Ph.D. 

Yanhai Yin is a professor in the department of genetics, development and cell biology. His research is focused on understanding the molecular mechanisms and gene regulatory networks through which the plant steroid hormone, Brassinosteroid (BRs), regulates plant growth and stress responses. His lab uses a combination of genetics, genomics, computational modeling and predictive phenomic approaches and the model plant Arabidopsis thaliana in the research. The long-term goal is to apply the knowledge generated from model systems to improve crop production under adverse climate conditions. 
 
Dr. Yin’s PSI project is a collaboration with several research groups in developing new phenotyping tools that can be used to study the functions of a large number of genes in Gene Regulatory Networks (GRNs). These include developing a platform to phenotype plant growth under drought conditions and using the platform to study the functions of hundreds of genes identified by computational modeling and quantitative genetics. The goal is to establish relationship between GRNs generated from predictive modeling and plant performance under various stress conditions. 
 

Jianming Yu, Ph.D. 

Jianming Yu is an associate professor in the department of agronomy and Pioneer Distinguished Chair in Maize Breeding.

The focus of his research is to address significant questions in plant breeding by combining cutting-edge genomic technologies and quantitative genetics theories. His research integrates knowledge in plant breeding, quantitative genetics, genomics, molecular genetics and statistics, and has the ultimate goal of developing and implementing new strategies and methods in trait dissection and crop improvement. 
 
Dr. Yu’s PSI project focuses on establishing an integrated modeling approach for performance prediction. Three major areas of research can be identified as the key elements to establish an Integrated Modeling Approach for Performance Prediction (IMAPP): quantitative and population genetics framework and associated developments; crop physiological modeling and agriculture production system; and systems biology. All three areas have their advantages and disadvantages in modeling and performance prediction at different levels, e.g., number of genotypes, context of performance, and input and output. In this project, the objectives are to assess a diverse set of performance prediction modeling approaches in plant breeding and genetics, crop modeling, and gene regulatory network, and to develop an integrated modeling framework for performance prediction under varied conditions.
 

 

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