Personnel

To view CVs, click on the highlighted names.

Most often cited for his discovery of bias in estimates of genetic effects in QTL analyses of populations with poor power (the "Beavis Effect"), Dr. William Beavis gained extensive experience in the application of statistical genetic methods during his twelve years at Pioneer Hi-Bred. Subsequent to his career at Pioneer, Bill was the CSO and COO at the National Center for Genome Resources, a private bioinformatics research institute. While at NCGR Dr. Beavis was the principal investigator for a variety of bioinformatics projects including the Legume Information System, and the GeneX and GeneX-Lite gene expression systems. Dr. Beavis joined the faculty at Iowa State University as the G.F. Sprague Chair of Crop Genomics in September 2007. His academic appointment is 75% research and 25% teaching. Bill’s research interests are to understand the limitations to Marker Assisted Breeding. These limitations can be technical, e.g., statistical bias in predicted breeding values, or biological, e.g., insufficient useful genetic diversity in the breeding population. By bringing these technical and scientific research questions together through the application of genomics and population, quantitative and statistical genetics, he intends to assure that the full genetic potential of domesticated crop species can be realized. Bill’s teaching interests are in graduate student education. Specifically, he teaches Advanced Plant Breeding through a traditional venue, applied statistics through a distance education (online) venue and is working with Dr. Thomas Lubberstedt to develop a new course in molecular plant breeding. He also advises undergraduates in Agronomy.

Kendra Meade is a Ph.D. candidate in plant breeding and laboratory manager for the group. She is working on the genetic analysis of biomass and moisture accumulation in maize kernels. The purpose of the experiment is to determine if rates of accumulation of moisture and dry-matter content in maize kernels can be associated with segregating genomic regions. She is interested in the intersection of physiology and genetics, and how genetics and environment affect physiological traits. As lab manager she carries out experiments related to Dr. Beavis' research, maintains the group website, and assists in teaching an online applied statistics course.

Mark Newell completed his Ph.D. in plant breeding in December of 2011. For his research he is applying association analysis to identify QTL in oats associated with increased beta-glucan biosynthesis. At the same time, he is exploring streamlined methods for beta-glucan evaluation, which could potentially decrease time and money for the evaluation process. Lastly, he is evaluating the structure of linkage disequilibrium across the oat genome, with emphasis on how it relates to association analysis to identify QTL controlling complex traits.

Franco Asoro is a Ph.D. student in Plant Breeding since Fall 2008. He completed his B.S. in Agriculture and M.S. in Plant Breeding at the University of the Philippines Los Banos. Currently in his last year, Franco is working with Dr. William Beavis, Dr. Paul Scott and Dr. Jean-Luc Jannink. The focus of his research is the use of molecular markers for association mapping and genomic selection. Parts of this project are the following:  association analysis for beta-glucan content in elite North American oats;  assessment of accuracy of genomic selection; and empirical comparison of phenotypic, marker-assisted selection and genomic selection methods.

Shreyartha Mukherjee is a Ph.D. student in Bioinformatics and Computational Biology from India. He has a B.TECH degree in Information Technology from the Institute of Engineering and Management, Kolkata, India. Currently he is studying Nitrogen use efficiency in terms of genetic mapping. In this project, Shrey wishes to discover specific genes associated with Nitrogen uptake and assimilation in maize by integrating genetic mapping of quantitative trait loci (QTL) controlling maize NUE, mRNA expression profiling, homology modeling and protein structural information. A fundamental and unsolved problem in computational molecular biology is to predict the structure of a protein, given its sequence information. Several protein structure prediction algorithms have been in use in the commercial and the academic world trying to picture biologically feasible conformation of proteins. But none of these algorithms have been so far able to predict structures with satisfactory accuracy. The discriminatory functions of these algorithms often confer high scores to incorrect conformations, thus it is imperative to improve these discriminatory functions to advance the accuracy of protein structure prediction. One method to test these algorithms would be to generate incorrect conformations, very close to the native protein structure and then let the discriminatory function distinguish between correct and incorrect conformations. These structures, better known as protein decoys would help develop better protein modeling tools and high resolution decoys can help us solve structures of binding sites, interaction sites etc. A reduced representation protein modeling tool CABS is extensively used in this project to generate the decoys. The scope of this approach goes beyond generating high-resolution decoys. The applications of this method include ab-initio structure prediction, comparative modeling and loop modeling.

Reka Howard is currently working on her Ph.D. in Statistics and Plant Breeding. She has a M.S. in Statistics and a B.S. in Statistics and Mathematics. She is working with Dr. Beavis, learning about genetic interactions among genes that are important for complex traits. Complex traits are features whose properties are controlled by many genes and whose inheritance does not follow the simple rules of Mendelian genetics. She will be developing statistical methods to estimate these interactions and use simulation techniques to evaluate the methods. In her research, Empirical Bayes Shrinkage methods for random effects will be used. Results from her research will advance the paper "Bayesian Model Selection for Genome-Wide Epistatic Quantitative Trait Loci Analysis" by Yi, Yandell, Churchill, Allison, Eisen and Pomp.

 

Jenna Woody is currently working on her Ph.D. in Genetics with an emphasis in statistics with Dr. Bill Beavis and Dr. Randy Shoemaker. She completed her B.A. in English from the University of Iowa in 2007. Currently starting her second year, she is focusing on the computational side of primarily soybean research. She is focused on the evolutionary demands and interactions between expression characteristics and structural genetics. Her first project focused on the relationship between expression breadth and level and the size of the individual gene. Her current project is characterizing soybean LHGRs (isochore and isochore-like regions) with the plan to extend the methods created while characterizing soybeans into other plant species.

Chris Meyer is a junior in Agronomy - Plant Breeding. He is also working with Dr. Beavis to maintain and care for Brassica rapa and Mimulus plants. Chris’s duties currently include updating the G.F.S. Population Genetics group website and working to create a successful number of genetically pure inbreds of both Brassica rapa and Mimulus to begin experimentation. Chris is an active member in the Agronomy Club and in his spare time enjoys physical activity.

Lynn Veenstra is a senior in Agronomy and Genetics. She is working on her honors research project with Dr. Beavis. Lynn’s project will focus on the trends of Beta-Glucan levels in crosses of wild and adapted oats. She is also the president of WISE (Women in Science and Engineering) and an avid swimmer.

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