Award Abstract #0211863
Dissecting Phytophthora Resistance In Soybean Using Expression Profiling and Analysis of Quantitative Trait Loci.

NSF Org:	IOS Division of Integrative Organismal Systems
Initial Amendment Date:	September 23, 2002
Latest Amendment Date:	August 2, 2007
Award Number:	0211863
Award Instrument:	Cooperative Agreement
Program Manager:	Diane Jofuku Okamuro IOS Division of Integrative Organismal Systems BIO Directorate for Biological Sciences
Start Date:	October 1, 2002
Expires:	September 30, 2008 (Estimated)
Awarded Amount to Date:	$6764462
Investigator(s):	Brett Tyler bmtyler@vt.edu (Principal Investigator) M Saghai Maroof (Co-Principal Investigator) Anne Dorrance (Co-Principal Investigator)
Sponsor:	Virginia Polytechnic Institute and State University 1880 Pratt Drive BLACKSBURG, VA 24060 540/231-5281
NSF Program(s):	PLANT GENOME RESEARCH PROJECT
Field Application(s):
Program Reference Code(s):	BIOT, 9109, 1329
Program Element Code(s):	1329

ABSTRACT

Some plant disease resistance genes (major resistance genes) confer high levels of resistance against particular pathogens. These genes have been well studied over the past decade. Major resistance genes, however, are generally effective only against specific strains of a pathogen, and so become ineffective in the field when new pathogens strains appear. In contrast, partial or quantitative resistance is effective against all strains of a pathogen, albeit providing a lower level of protection. Multiple genes confer partial resistance, each making minor contributions, complicating the study of these genes. As a result, less is known about how they operate.

The goal of this project is to understand the mechanisms of quantitative resistance of soybean against the oomycete pathogen Phytophthora sojae, which is one of the most damaging soybean diseases. Oomycetes are fungus-like organisms that are actually most closely related to brown algae such as kelp and diatoms. Phytophthora pathogens attack thousands of plant species, including many important crops.

Two approaches will be combined to identify and characterize quantitative resistance genes. First, genetic crosses between soybean cultivars differing in their quantitative resistance to Phytophthora will be analyzed to identify genetic loci (called quantitative trait loci or QTL) in soybean that contribute to resistance. Second, the expression levels of thousands of soybean and Phytophthora genes during infection will be assayed using hybridization microarrays to determine the mechanisms of resistance contributed by different quantitative resistance loci. Pathogen gene expression patterns will be analyzed to determine the impact of plant defense mechanisms on the pathogen. Overall, it is anticipated that this research will result in new insights into plant defense mechanisms, new genetic and genomic resources for soybean researchers and breeders, and new statistical tools for analysis of gene expression data.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Bao L. and I. Hoeschele. "Quality Assessment for Short Oligonucleotide Microarray Data: Comment.," Technometrics, v.50, 2008, p. 268.

Bing, N., Hoeschele, I., Ye, K., and Eilertsen, K. J.. "Finite mixture model analysis of microarray expression data on samples of uncertain biological type with application to reproductive efficiency," Veterinary Immunology and Immunopathology, v.105, 2005, p. 187-196.

De la Fuente, A., N. Bing, I. Hoeschele and P. Mendes. "Discovery of topologically meaningful associations in genomic data using partial correlation coefficients," Bioinformatics, v.20, 2004, p. 3565-3574.

Hoeschele, I., and Li, H.. "A note on joint versus gene-specific mixed model analysis of microarray gene expression data," Biostatistics, v.6, 2005, p. 183-186.

Liu, B., de la Fuente, A., and Hoeschele, I.. "Gene network inference via structural equation modeling in genetical genomics experiments," Genetics, v.178, 2008, p. 1763.

Trudy A. Torto-Alalibo, Sucheta Tripathy, Brian M. Smith, Felipe D. Arredondo, Lecong Zhou, Hua Li, Marcus C. Chibucos, Dinah Qutob, Mark Gijzen, Chunhong Mao, Bruno W.S. Sobral, Mark E. Waugh, Thomas K. Mitchell, Ralph A. Dean and Brett M. Tyler. "Expressed sequence tags from Phytophthora sojae reveal genes specific to development and infection," Molec. Plant-Microbe Interactions, 2007, p. 781-7.

Please report errors in award information by writing to: awardsearch@nsf.gov.