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1.  Novel quantitative trait loci for partial resistance to Phytophthora sojae in soybean PI 398841 
Phytophthora root and stem rot caused by Phytophthora sojae Kaufmann and Gerdemann is one of the most severe soybean [Glycine max (L.) Merr] diseases in the USA. Partial resistance is as effective in managing this disease as single-gene (Rps gene)-mediated resistance and is more durable. The objective of this study was to identify quantitative trait loci (QTL) associated with partial resistance to P. sojae in PI 398841, which originated from South Korea. A population of 305 F7:8 recombinant inbred lines derived from a cross of OX20-8 × PI 398841 was used to evaluate partial resistance against P. sojae isolate C2S1 using a tray test. Composite interval mapping using a genome-wide logarithm of odd (LOD) threshold detected three QTL on chromosomes 1, 13, and 18, which individually explained 4–16 % of the phenotypic variance. Seven additional QTL, accounting for 2–3 % of phenotypic variance each, were identified using chromosome-wide LOD thresholds. Seven of the ten QTL for resistance to P. sojae were contributed by PI 398841. Seven QTL co-localized with known Rps genes and previously reported QTL for soil-borne root pathogens, isoflavone, and seed oil. Three QTL on chromosomes 3, 13, and 18 co-localized with known Rps genes, but PI 398841 did not exhibit an Rps gene-mediated resistance response following inoculation with 48 different isolates of P. sojae. PI 398841 is potentially a source of novel genes for improving soybean cultivars for partial resistance to P. sojae.
Electronic supplementary material
The online version of this article (doi:10.1007/s00122-013-2040-x) contains supplementary material, which is available to authorized users.
doi:10.1007/s00122-013-2040-x
PMCID: PMC3607739  PMID: 23354974
2.  Novel Phakopsora pachyrhizi Extracellular Proteins Are Ideal Targets for Immunological Diagnostic Assays 
Applied and Environmental Microbiology  2012;78(11):3890-3895.
Phakopsora pachyrhizi, the causal agent of Asian soybean rust (ASR), continues to spread across the southeast and midsouth regions of the United States, necessitating the use of fungicides by producers. Our objective in this research was to identify ASR proteins expressed early during infection for the development of immunodiagnostic assays. We have identified and partially characterized a small gene family encoding extracellular proteins in the P. pachyrhizi urediniospore wall, termed PHEPs (for Phakopsora extracellular protein). Two highly expressed protein family members, PHEP 107 and PHEP 369, were selected as ideal immunodiagnostic targets for antibody development, after we detected PHEPs in plants as early as 3 days postinfection (dpi). Monoclonal antibodies (MAbs; 2E8E5-1 and 3G6H7-3) generated against recombinant PHEP 369 were tested for sensitivity against the recombinant protein and extracts from ASR-infected plants and for specificity against a set of common soybean pathogens. These antibodies should prove applicable in immunodiagnostic assays to detect infected soybeans and to identify ASR spores from sentinel surveillance plots.
doi:10.1128/AEM.07079-11
PMCID: PMC3346385  PMID: 22447596
3.  Dissection of two soybean QTL conferring partial resistance to Phytophthora sojae through sequence and gene expression analysis 
BMC Genomics  2012;13:428.
Background
Phytophthora sojae is the primary pathogen of soybeans that are grown on poorly drained soils. Race-specific resistance to P. sojae in soybean is gene-for-gene, although in many areas of the US and worldwide there are populations that have adapted to the most commonly deployed resistance to P. sojae ( Rps) genes. Hence, this system has received increased attention towards identifying mechanisms and molecular markers associated with partial resistance to this pathogen. Several quantitative trait loci (QTL) have been identified in the soybean cultivar ‘Conrad’ that contributes to the expression of partial resistance to multiple P. sojae isolates.
Results
In this study, two of the Conrad QTL on chromosome 19 were dissected through sequence and expression analysis of genes in both resistant (Conrad) and susceptible (‘Sloan’) genotypes. There were 1025 single nucleotide polymorphisms (SNPs) in 87 of 153 genes sequenced from Conrad and Sloan. There were 304 SNPs in 54 genes sequenced from Conrad compared to those from both Sloan and Williams 82, of which 11 genes had SNPs unique to Conrad. Eleven of 19 genes in these regions analyzed with qRT-PCR had significant differences in fold change of transcript abundance in response to infection with P. sojae in lines with QTL haplotype from the resistant parent compared to those with the susceptible parent haplotype. From these, 8 of the 11 genes had SNPs in the upstream, untranslated region, exon, intron, and/or downstream region. These 11 candidate genes encode proteins potentially involved in signal transduction, hormone-mediated pathways, plant cell structural modification, ubiquitination, and basal resistance.
Conclusions
These findings may indicate a complex defense network with multiple mechanisms underlying these two soybean QTL conferring resistance to P. sojae. SNP markers derived from these candidate genes can contribute to fine mapping of QTL and marker assisted breeding for resistance to P. sojae.
doi:10.1186/1471-2164-13-428
PMCID: PMC3443417  PMID: 22925529
QTL; Gene expression; Sequencing; SNP; Soybean; P. sojae; qRT-PCR
4.  Comparison of three microsatellite analysis methods for detecting genetic diversity in Phytophthora sojae (Stramenopila: Oomycete) 
Biotechnology Letters  2011;33(11):2217-2223.
Analysis of an organism’s genetic diversity requires a method that gives reliable, reproducible results. Microsatellites are robust markers, however, detection of allele sizes can be difficult with some systems as well as consistency among laboratories. In this study, our two laboratories used 219 isolates of Phytophthora sojae to compare three microsatellite methods. Two capillary electrophoresis methods, the Applied Biosystems 3730 Genetic Analyzer and the CEQ 8000 Genetic Analysis system, detected an average of 2.4-fold more alleles compared to gel electrophoresis with a mean of 8.8 and 3.6 alleles per locus using capillary and gel methods, respectively. The two capillary methods were comparable, although allele sizes differed consistently by an average of 3.2 bp across isolates. Differences between capillary methods could be overcome if reference standard DNA genotypes are shared between collaborating laboratories.
Electronic supplementary material
The online version of this article (doi:10.1007/s10529-011-0682-9) contains supplementary material, which is available to authorized users.
doi:10.1007/s10529-011-0682-9
PMCID: PMC3181407  PMID: 21744147
Alleles; Capillary electrophoresis; Microsatellites; Pathogenic diversity; Phytophora sojae
5.  Easy and efficient protocol for oomycete DNA extraction suitable for population genetic analysis 
Biotechnology Letters  2010;33(4):715-720.
Purpose of work
A simple and rapid DNA extraction protocol capable of obtaining high-quality and quantity DNA from a large number of individuals is essential for assaying population and phylogenetic studies of plant pathogens. Most DNA extraction protocols used with oomycetes are relatively lengthy and cumbersome for high throughput analysis. Commercial kits are widely used, but low quantities of DNA are usually obtained, and with large scale analysis multiple isolations are required.
A protocol for DNA isolation from Phytophthora and Pythium suitable for the evaluation of a large set of molecular markers was modified from one previously developed for soybean seed. There was a one to three fold increase in the amount of DNA that was extracted using the modified protocol compared to a commercial kit. The DNA obtained using the modified protocol was suitable for the amplification of microsatellite markers as well as the ITS region. This protocol is inexpensive, easy, quick, and efficient in terms of the volume of reagents and the number of steps involved in the procedure. The method may be applicable to other oomycetes and effectively implemented in other laboratories.
doi:10.1007/s10529-010-0478-3
PMCID: PMC3061009  PMID: 21107649
Phytophthora sojae; Phytophthora sansomeana; Pythium heterothallicum; ITS region; Microsatellites; PCR; DNA isolation
6.  Infection and genotype remodel the entire soybean transcriptome 
BMC Genomics  2009;10:49.
Background
High throughput methods, such as high density oligonucleotide microarray measurements of mRNA levels, are popular and critical to genome scale analysis and systems biology. However understanding the results of these analyses and in particular understanding the very wide range of levels of transcriptional changes observed is still a significant challenge. Many researchers still use an arbitrary cut off such as two-fold in order to identify changes that may be biologically significant. We have used a very large-scale microarray experiment involving 72 biological replicates to analyze the response of soybean plants to infection by the pathogen Phytophthora sojae and to analyze transcriptional modulation as a result of genotypic variation.
Results
With the unprecedented level of statistical sensitivity provided by the high degree of replication, we show unambiguously that almost the entire plant genome (97 to 99% of all detectable genes) undergoes transcriptional modulation in response to infection and genetic variation. The majority of the transcriptional differences are less than two-fold in magnitude. We show that low amplitude modulation of gene expression (less than two-fold changes) is highly statistically significant and consistent across biological replicates, even for modulations of less than 20%. Our results are consistent through two different normalization methods and two different statistical analysis procedures.
Conclusion
Our findings demonstrate that the entire plant genome undergoes transcriptional modulation in response to infection and genetic variation. The pervasive low-magnitude remodeling of the transcriptome may be an integral component of physiological adaptation in soybean, and in all eukaryotes.
doi:10.1186/1471-2164-10-49
PMCID: PMC2662884  PMID: 19171053

Results 1-6 (6)