Publications by authors named "Balint-Kurti P"

78 Publications

The Genetics of Leaf Flecking in Maize and Its Relationship to Plant Defense and Disease Resistance.

Plant Physiol 2016 11 26;172(3):1787-1803. Epub 2016 Sep 26.

Department of Plant Pathology, North Carolina State University, Raleigh, North Carolina 27695-7616 (B.A.O., P.J.B.-K.);

Physiological leaf spotting, or flecking, is a mild-lesion phenotype observed on the leaves of several commonly used maize (Zea mays) inbred lines and has been anecdotally linked to enhanced broad-spectrum disease resistance. Flecking was assessed in the maize nested association mapping (NAM) population, comprising 4,998 recombinant inbred lines from 25 biparental families, and in an association population, comprising 279 diverse maize inbreds. Joint family linkage analysis was conducted with 7,386 markers in the NAM population. Genome-wide association tests were performed with 26.5 million single-nucleotide polymorphisms (SNPs) in the NAM population and with 246,497 SNPs in the association population, resulting in the identification of 18 and three loci associated with variation in flecking, respectively. Many of the candidate genes colocalizing with associated SNPs are similar to genes that function in plant defense response via cell wall modification, salicylic acid- and jasmonic acid-dependent pathways, redox homeostasis, stress response, and vesicle trafficking/remodeling. Significant positive correlations were found between increased flecking, stronger defense response, increased disease resistance, and increased pest resistance. A nonlinear relationship with total kernel weight also was observed whereby lines with relatively high levels of flecking had, on average, lower total kernel weight. We present evidence suggesting that mild flecking could be used as a selection criterion for breeding programs trying to incorporate broad-spectrum disease resistance.
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http://dx.doi.org/10.1104/pp.15.01870DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100796PMC
November 2016

Semiautomated confocal imaging of fungal pathogenesis on plants: Microscopic analysis of macroscopic specimens.

Microsc Res Tech 2018 Feb 25;81(2):141-152. Epub 2016 Jun 25.

Department of Biological Sciences, University of Delaware, Newark, Delaware, 19716.

The study of phenotypic variation in plant pathogenesis provides fundamental information about the nature of disease resistance. Cellular mechanisms that alter pathogenesis can be elucidated with confocal microscopy; however, systematic phenotyping platforms-from sample processing to image analysis-to investigate this do not exist. We have developed a platform for 3D phenotyping of cellular features underlying variation in disease development by fluorescence-specific resolution of host and pathogen interactions across time (4D). A confocal microscopy phenotyping platform compatible with different maize-fungal pathosystems (fungi: Setosphaeria turcica, Cochliobolus heterostrophus, and Cercospora zeae-maydis) was developed. Protocols and techniques were standardized for sample fixation, optical clearing, species-specific combinatorial fluorescence staining, multisample imaging, and image processing for investigation at the macroscale. The sample preparation methods presented here overcome challenges to fluorescence imaging such as specimen thickness and topography as well as physiological characteristics of the samples such as tissue autofluorescence and presence of cuticle. The resulting imaging techniques provide interesting qualitative and quantitative information not possible with conventional light or electron 2D imaging. Microsc. Res. Tech., 81:141-152, 2018. © 2016 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/jemt.22709DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5329141PMC
February 2018

Maize Homologs of CCoAOMT and HCT, Two Key Enzymes in Lignin Biosynthesis, Form Complexes with the NLR Rp1 Protein to Modulate the Defense Response.

Plant Physiol 2016 07 10;171(3):2166-77. Epub 2016 May 10.

Department of Plant Pathology, North Carolina State University, Raleigh, North Carolina 27695 (G.-F.W., P.J.B.-K.)Key Laboratory of Plant Cell Engineering and Germplasm Innovation, Ministry of Education, School of Life Sciences, Shandong University, Jinan, Shandong 250100, P.R. China (G.-F.W.); U.S. Department of Agriculture-Agricultural Research Service, Plant Science Research Unit, Raleigh, North Carolina 27695 (P.J.B.-K.).

Disease resistance (R) genes encode nucleotide binding Leu-rich-repeat (NLR) proteins that confer resistance to specific pathogens. Upon pathogen recognition they trigger a defense response that usually includes a so-called hypersensitive response (HR), a rapid localized cell death at the site of pathogen infection. Intragenic recombination between two maize (Zea mays) NLRs, Rp1-D and Rp1-dp2, resulted in the formation of a hybrid NLR, Rp1-D21, which confers an autoactive HR in the absence of pathogen infection. From a previous quantitative trait loci and genome-wide association study, we identified genes encoding two key enzymes in lignin biosynthesis, hydroxycinnamoyltransferase (HCT) and caffeoyl CoA O-methyltransferase (CCoAOMT), adjacent to the nucleotide polymorphisms that were highly associated with variation in the severity of Rp1-D21-induced HR We have previously shown that the two maize HCT homologs suppress the HR conferred by Rp1-D21 in a heterologous system, very likely through physical interaction. Here, we show, similarly, that CCoAOMT2 suppresses the HR induced by either the full-length or by the N-terminal coiled-coil domain of Rp1-D21 also likely via physical interaction and that the metabolic activity of CCoAOMT2 is unlikely to be necessary for its role in suppressing HR. We also demonstrate that CCoAOMT2, HCTs, and Rp1 proteins can form in the same complexes. A model is derived to explain the roles of CCoAOMT and HCT in Rp1-mediated defense resistance.
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http://dx.doi.org/10.1104/pp.16.00224DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936554PMC
July 2016

A Genome-Wide Association Study for Partial Resistance to Maize Common Rust.

Phytopathology 2016 Jul 9;106(7):745-51. Epub 2016 May 9.

First author: Department of Plant Pathology and Department of Horticulture, North Carolina State University, Raleigh 27695; second and fourth authors: Department of Agronomy, University of Wisconsin-Madison, Madison 53706; third author: Department of Plant & Soil Sciences, University of Delaware, Newark 19716; and fifth author: Department of Plant Pathology, North Carolina State University, and United States Department of Agriculture-Agricultural Research Service Plant Science Research Unit, Raleigh, NC 27695.

Quantitative resistance to maize common rust (causal agent Puccinia sorghi) was assessed in an association mapping population of 274 diverse inbred lines. Resistance to common rust was found to be moderately correlated with resistance to three other diseases and with the severity of the hypersensitive defense response previously assessed in the same population. Using a mixed linear model accounting for the confounding effects of population structure and flowering time, genome-wide association tests were performed based at 246,497 single-nucleotide polymorphism loci. Three loci associated with maize common rust resistance were identified. Candidate genes at each locus had predicted roles, mainly in cell wall modification. Other candidate genes included a resistance gene and a gene with a predicted role in regulating accumulation of reactive oxygen species.
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http://dx.doi.org/10.1094/PHYTO-11-15-0305-RDOI Listing
July 2016

Maize Homologs of Hydroxycinnamoyltransferase, a Key Enzyme in Lignin Biosynthesis, Bind the Nucleotide Binding Leucine-Rich Repeat Rp1 Proteins to Modulate the Defense Response.

Plant Physiol 2015 Nov 15;169(3):2230-43. Epub 2015 Sep 15.

Departments of Plant Pathology (G.-F.W., Y.H., B.A.O., P.J.B.-K.),Plant and Microbial Biology (R.S., X.L.), andBiological Sciences (D.N.), North Carolina State University, Raleigh, North Carolina 27695;Plants for Human Health Institute, North Carolina State University, Kannapolis, North Carolina 28081 (R.S., X.L.); andPlant Science Research Unit, United States Department of Agriculture-Agricultural Research Service, Raleigh, North Carolina 27695 (P.J.B.-K.)

In plants, most disease resistance genes encode nucleotide binding Leu-rich repeat (NLR) proteins that trigger a rapid localized cell death called a hypersensitive response (HR) upon pathogen recognition. The maize (Zea mays) NLR protein Rp1-D21 derives from an intragenic recombination between two NLRs, Rp1-D and Rp1-dp2, and confers an autoactive HR in the absence of pathogen infection. From a previous quantitative trait loci and genome-wide association study, we identified a single-nucleotide polymorphism locus highly associated with variation in the severity of Rp1-D21-induced HR. Two maize genes encoding hydroxycinnamoyltransferase (HCT; a key enzyme involved in lignin biosynthesis) homologs, termed HCT1806 and HCT4918, were adjacent to this single-nucleotide polymorphism. Here, we show that both HCT1806 and HCT4918 physically interact with and suppress the HR conferred by Rp1-D21 but not other autoactive NLRs when transiently coexpressed in Nicotiana benthamiana. Other maize HCT homologs are unable to confer the same level of suppression on Rp1-D21-induced HR. The metabolic activity of HCT1806 and HCT4918 is unlikely to be necessary for their role in suppressing HR. We show that the lignin pathway is activated by Rp1-D21 at both the transcriptional and metabolic levels. We derive a model to explain the roles of HCT1806 and HCT4918 in Rp1-mediated disease resistance.
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http://dx.doi.org/10.1104/pp.15.00703DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634058PMC
November 2015

The genetic basis of flecking and its relationship to disease resistance in the IBM maize mapping population.

Theor Appl Genet 2015 Nov 4;128(11):2331-9. Epub 2015 Aug 4.

Department of Plant Pathology, NC State University, 2574 Thomas Hall, Raleigh, NC, 27695-7616, USA.

Key Message: In this paper, we determine the genetic architecture controlling leaf flecking in maize and investigate its relationship to disease resistance and the defense response. Flecking is defined as a mild, often environmentally dependent lesion phenotype observed on the leaves of several commonly used maize inbred lines. Anecdotal evidence suggests a link between flecking and enhanced broad-spectrum disease resistance. Neither the genetic basis underlying flecking nor its possible relationship to disease resistance has been systematically evaluated. The commonly used maize inbred Mo17 has a mild flecking phenotype. The IBM-advanced intercross mapping population, derived from a cross between Mo17 and another commonly used inbred B73, has been used for mapping a number of traits in maize including several related to disease resistance. In this study, flecking was assessed in the IBM population over 6 environments. Several quantitative trait loci for flecking were identified, with the strongest one located on chromosome 6. Low but moderately significant correlations were observed between stronger flecking and higher disease resistance with respect to two diseases, southern leaf blight and northern leaf blight and between stronger flecking and a stronger defense response.
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http://dx.doi.org/10.1007/s00122-015-2588-8DOI Listing
November 2015

Cytoplasmic and Nuclear Localizations Are Important for the Hypersensitive Response Conferred by Maize Autoactive Rp1-D21 Protein.

Mol Plant Microbe Interact 2015 Sep 25;28(9):1023-31. Epub 2015 Aug 25.

1 Dept. of Plant Pathology, North Carolina State University, Raleigh, NC 27695, U.S.A.;

Disease resistance (R) genes have been isolated from many plant species. Most encode nucleotide binding leucine-rich repeat (NLR) proteins that trigger a rapid localized programmed cell death called the hypersensitive response (HR) upon pathogen recognition. Despite their structural similarities, different NLR are distributed in a range of subcellular locations, and analogous domains play diverse functional roles. The autoactive maize NLR gene Rp1-D21 derives from an intragenic recombination between two NLR genes, Rp1-D and Rp1-dp2, and confers a HR independent of the presence of a pathogen. Rp1-D21 and its N-terminal coiled coil (CC) domain (CCD21) confer autoactive HR when transiently expressed in Nicotiana benthamiana. Rp1-D21 was predominantly localized in cytoplasm with a small amount in the nucleus, while CCD21 was localized in both nucleus and cytoplasm. Targeting of Rp1-D21 or CCD21 predominantly to either the nucleus or the cytoplasm abolished HR-inducing activity. Coexpression of Rp1-D21 or CCD21 constructs confined, respectively, to the nucleus and cytoplasm did not rescue full activity, suggesting nucleocytoplasmic movement was important for HR induction. This work emphasizes the diverse structural and subcellular localization requirements for activity found among plant NLR R genes.
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http://dx.doi.org/10.1094/MPMI-01-15-0014-RDOI Listing
September 2015

QTL mapping using high-throughput sequencing.

Methods Mol Biol 2015 ;1284:257-85

Department of Crop Science, North Carolina State University, Raleigh, NC, 27695-7620, USA.

Quantitative trait locus (QTL) mapping in plants dates to the 1980s (Stuber et al. Crop Sci 27: 639-648, 1987; Paterson et al. Nature 335: 721-726, 1988), but earlier studies were often hindered by the expense and time required to identify large numbers of polymorphic genetic markers that differentiated the parental genotypes and then to genotype them on large segregating mapping populations. High-throughput sequencing has provided an efficient means to discover single nucleotide polymorphisms (SNPs) that can then be assayed rapidly on large populations with array-based techniques (Gupta et al. Heredity 101: 5-18, 2008). Alternatively, high-throughput sequencing methods such as restriction site-associated DNA sequencing (RAD-Seq) (Davey et al. Nat Rev Genet 12: 499-510, 2011; Baird et al. PloS ONE 3: e3376, 2008) and genotyping-by-sequencing (GBS) (Elshire et al. PLoS One 6: 2011; Glaubitz et al. PLoS One 9: e90346, 2014) can be used to identify and genotype polymorphic markers directly. Linkage disequilibrium (LD) between markers and causal variants is needed to detect QTL. The earliest QTL mapping methods used backcross and F2 generations of crosses between inbred lines, which have high levels of linkage disequilibrium (dependent entirely on the recombination frequency between chromosomal positions), to ensure that QTL would have sufficiently high linkage disequilibrium with one or more markers on sparse genetic linkage maps. The downside of this approach is that resolution of QTL positions is poor. The sequencing technology revolution, by facilitating genotyping of vastly more markers than was previously feasible, has allowed researchers to map QTL in situations of lower linkage disequilibrium, and consequently, at higher resolution. We provide a review of methods to identify QTL with higher precision than was previously possible. We discuss modifications of the traditional biparental mapping population that provide higher resolution of QTL positions, QTL fine-mapping procedures, and genome-wide association studies, all of which are greatly facilitated by high-throughput sequencing methods. Each of these procedures has many variants, and consequently many details to consider; we focus our chapter on the consequences of practical decisions that researchers make when designing QTL mapping studies and when analyzing the resulting data. The ultimate goal of many of these studies is to resolve a QTL to its causal sequence variation.
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http://dx.doi.org/10.1007/978-1-4939-2444-8_13DOI Listing
November 2015

Molecular and functional analyses of a maize autoactive NB-LRR protein identify precise structural requirements for activity.

PLoS Pathog 2015 Feb 26;11(2):e1004674. Epub 2015 Feb 26.

Department of Plant Pathology, North Carolina State University, Raleigh, North Carolina, United States of America; USDA-ARS Plant Science Research Unit, Raleigh, North Carolina, United States of America.

Plant disease resistance is often mediated by nucleotide binding-leucine rich repeat (NLR) proteins which remain auto-inhibited until recognition of specific pathogen-derived molecules causes their activation, triggering a rapid, localized cell death called a hypersensitive response (HR). Three domains are recognized in one of the major classes of NLR proteins: a coiled-coil (CC), a nucleotide binding (NB-ARC) and a leucine rich repeat (LRR) domains. The maize NLR gene Rp1-D21 derives from an intergenic recombination event between two NLR genes, Rp1-D and Rp1-dp2 and confers an autoactive HR. We report systematic structural and functional analyses of Rp1 proteins in maize and N. benthamiana to characterize the molecular mechanism of NLR activation/auto-inhibition. We derive a model comprising the following three main features: Rp1 proteins appear to self-associate to become competent for activity. The CC domain is signaling-competent and is sufficient to induce HR. This can be suppressed by the NB-ARC domain through direct interaction. In autoactive proteins, the interaction of the LRR domain with the NB-ARC domain causes de-repression and thus disrupts the inhibition of HR. Further, we identify specific amino acids and combinations thereof that are important for the auto-inhibition/activity of Rp1 proteins. We also provide evidence for the function of MHD2, a previously uncharacterized, though widely conserved NLR motif. This work reports several novel insights into the precise structural requirement for NLR function and informs efforts towards utilizing these proteins for engineering disease resistance.
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http://dx.doi.org/10.1371/journal.ppat.1004674DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4342346PMC
February 2015

New insight into a complex plant-fungal pathogen interaction.

Nat Genet 2015 Feb;47(2):101-3

Plant Science Research Unit, US Department of Agriculture-Agricultural Research Service (USDA-ARS) and the Department of Crop Science, North Carolina State University, Raleigh, North Carolina, USA.

The coevolution of plants and microbes has shaped plant mechanisms that detect and repel pathogens. A newly identified plant gene confers partial resistance to a fungal pathogen not by preventing initial infection but by limiting its spread through the plant.
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http://dx.doi.org/10.1038/ng.3203DOI Listing
February 2015

Limits on the reproducibility of marker associations with southern leaf blight resistance in the maize nested association mapping population.

BMC Genomics 2014 Dec 5;15:1068. Epub 2014 Dec 5.

Department of Crop Science, North Carolina State University, Raleigh, NC 27695, USA.

Background: A previous study reported a comprehensive quantitative trait locus (QTL) and genome wide association study (GWAS) of southern leaf blight (SLB) resistance in the maize Nested Association Mapping (NAM) panel. Since that time, the genomic resources available for such analyses have improved substantially. An updated NAM genetic linkage map has a nearly six-fold greater marker density than the previous map and the combined SNPs and read-depth variants (RDVs) from maize HapMaps 1 and 2 provided 28.5 M genomic variants for association analysis, 17 fold more than HapMap 1. In addition, phenotypic values of the NAM RILs were re-estimated to account for environment-specific flowering time covariates and a small proportion of lines were dropped due to genotypic data quality problems. Comparisons of original and updated QTL and GWAS results confound the effects of linkage map density, GWAS marker density, population sample size, and phenotype estimates. Therefore, we evaluated the effects of changing each of these parameters individually and in combination to determine their relative impact on marker-trait associations in original and updated analyses.

Results: Of the four parameters varied, map density caused the largest changes in QTL and GWAS results. The updated QTL model had better cross-validation prediction accuracy than the previous model. Whereas joint linkage QTL positions were relatively stable to input changes, the residual values derived from those QTL models (used as inputs to GWAS) were more sensitive, resulting in substantial differences between GWAS results. The updated NAM GWAS identified several candidate genes consistent with previous QTL fine-mapping results.

Conclusions: The highly polygenic nature of resistance to SLB complicates the identification of causal genes. Joint linkage QTL are relatively stable to perturbations of data inputs, but their resolution is generally on the order of tens or more Mbp. GWAS associations have higher resolution, but lower power due to stringent thresholds designed to minimize false positive associations, resulting in variability of detection across studies. The updated higher density linkage map improves QTL estimation and, along with a much denser SNP HapMap, greatly increases the likelihood of detecting SNPs in linkage with causal variants. We recommend use of the updated genetic resources and results but emphasize the limited repeatability of small-effect associations.
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http://dx.doi.org/10.1186/1471-2164-15-1068DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300987PMC
December 2014

Southern leaf blight disease severity is correlated with decreased maize leaf epiphytic bacterial species richness and the phyllosphere bacterial diversity decline is enhanced by nitrogen fertilization.

Front Plant Sci 2014 15;5:403. Epub 2014 Aug 15.

Department of Biology and Marine Biology, University of North Carolina Wilmington Wilmington, NC, USA.

Plant leaves are inhabited by a diverse group of microorganisms that are important contributors to optimal growth. Biotic and abiotic effects on plant growth are usually studied in controlled settings examining response to variation in single factors and in field settings with large numbers of variables. Multi-factor experiments with combinations of stresses bridge this gap, increasing our understanding of the genotype-environment-phenotype functional map for the host plant and the affiliated epiphytic community. The maize inbred B73 was exposed to single and combination abiotic and the biotic stress treatments: low nitrogen fertilizer and high levels of infection with southern leaf blight (causal agent Cochliobolus heterostrophus). Microbial epiphyte samples were collected at the vegetative early-season phase and species composition was determined using 16S ribosomal intergenic spacer analysis. Plant traits and level of southern leaf blight disease were measured late-season. Bacterial diversity was different among stress treatment groups (P < 0.001). Lower species richness-alpha diversity-was correlated with increased severity of southern leaf blight disease when disease pressure was high. Nitrogen fertilization intensified the decline in bacterial alpha diversity. While no single bacterial ribotype was consistently associated with disease severity, small sets of ribotypes were good predictors of disease levels. Difference in leaf bacterial-epiphyte diversity early in the season were correlated with plant disease severity, supporting further tests of microbial epiphyte-disease correlations for use in predicting disease progression.
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http://dx.doi.org/10.3389/fpls.2014.00403DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4133650PMC
September 2014

A genome-wide association study of the maize hypersensitive defense response identifies genes that cluster in related pathways.

PLoS Genet 2014 Aug 28;10(8):e1004562. Epub 2014 Aug 28.

Department of Botany and Plant Pathology, Purdue University, Lilly Hall, West Lafayette, Indiana, United States of America.

Much remains unknown of molecular events controlling the plant hypersensitive defense response (HR), a rapid localized cell death that limits pathogen spread and is mediated by resistance (R-) genes. Genetic control of the HR is hard to quantify due to its microscopic and rapid nature. Natural modifiers of the ectopic HR phenotype induced by an aberrant auto-active R-gene (Rp1-D21), were mapped in a population of 3,381 recombinant inbred lines from the maize nested association mapping population. Joint linkage analysis was conducted to identify 32 additive but no epistatic quantitative trait loci (QTL) using a linkage map based on more than 7000 single nucleotide polymorphisms (SNPs). Genome-wide association (GWA) analysis of 26.5 million SNPs was conducted after adjusting for background QTL. GWA identified associated SNPs that colocalized with 44 candidate genes. Thirty-six of these genes colocalized within 23 of the 32 QTL identified by joint linkage analysis. The candidate genes included genes predicted to be in involved programmed cell death, defense response, ubiquitination, redox homeostasis, autophagy, calcium signalling, lignin biosynthesis and cell wall modification. Twelve of the candidate genes showed significant differential expression between isogenic lines differing for the presence of Rp1-D21. Low but significant correlations between HR-related traits and several previously-measured disease resistance traits suggested that the genetic control of these traits was substantially, though not entirely, independent. This study provides the first system-wide analysis of natural variation that modulates the HR response in plants.
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http://dx.doi.org/10.1371/journal.pgen.1004562DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4148229PMC
August 2014

Characterization of temperature and light effects on the defense response phenotypes associated with the maize Rp1-D21 autoactive resistance gene.

BMC Plant Biol 2013 Jul 26;13:106. Epub 2013 Jul 26.

Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA.

Background: Rp1 is a complex locus of maize, which carries a set of genes controlling race-specific resistance to the common rust fungus, Puccinia sorghi. The resistance response includes the "Hypersensitive response" (HR), a rapid response triggered by a pathogen recognition event that includes localized cell death at the point of pathogen penetration and the induction of pathogenesis associated genes. The Rp1-D21gene is an autoactive allelic variant at the Rp1 locus, causing spontaneous activation of the HR response, in the absence of pathogenesis. Previously we have shown that the severity of the phenotype conferred by Rp1-D21 is highly dependent on genetic background.

Results: In this study we show that the phenotype conferred by Rp1-D21 is highly dependent on temperature, with lower temperatures favoring the expression of the HR lesion phenotype. This temperature effect was observed in all the 14 genetic backgrounds tested. Significant interactions between the temperature effects and genetic background were observed. When plants were grown at temperatures above 30°C, the spontaneous HR phenotype conferred by Rp1-D21 was entirely suppressed. Furthermore, this phenotype could be restored or suppressed by alternately reducing and increasing the temperature appropriately. Light was also required for the expression of this phenotype. By examining the expression of genes associated with the defense response we showed that, at temperatures above 30°C, the Rp1-D21 phenotype was suppressed at both the phenotypic and molecular level.

Conclusions: We have shown that the lesion phenotype conferred by maize autoactive resistance gene Rp1-D21 is temperature sensitive in a reversible manner, that the temperature-sensitivity phenotype interacts with genetic background and that the phenotype is light sensitive. This is the first detailed demonstration of this phenomenon in monocots and also the first demonstration of the interaction of this effect with genetic background. The use of temperature shifts to induce a massive and synchronous HR in plants carrying the Rp1-D21 genes will be valuable in identifying components of the defense response pathway.
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http://dx.doi.org/10.1186/1471-2229-13-106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733612PMC
July 2013

A connected set of genes associated with programmed cell death implicated in controlling the hypersensitive response in maize.

Genetics 2013 Feb 5;193(2):609-20. Epub 2012 Dec 5.

Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695-7616, USA.

Rp1-D21 is a maize auto-active resistance gene conferring a spontaneous hypersensitive response (HR) of variable severity depending on genetic background. We report an association mapping strategy based on the Mutant Assisted Gene Identification and Characterization approach to identify naturally occurring allelic variants associated with phenotypic variation in HR. Each member of a collection of 231 diverse inbred lines of maize constituting a high-resolution association mapping panel were crossed to a parental stock heterozygous for Rp1-D21, and the segregating F(1) generation testcrosses were evaluated for phenotypes associated with lesion severity for 2 years at two locations. A genome-wide scan for associations with HR was conducted with 47,445 SNPs using a linear mixed model that controlled for spurious associations due to population structure. Since the ability to identify candidate genes and the resolution of association mapping are highly influenced by linkage disequilibrium (LD), we examined the extent of genome-wide LD. On average, marker pairs separated by >10 kbp had an r(2) value of <0.1. Genomic regions surrounding SNPs significantly associated with HR traits were locally saturated with additional SNP markers to establish local LD structure and precisely identify candidate genes. Six significantly associated SNPs at five loci were detected. At each locus, the associated SNP was located within or immediately adjacent to candidate causative genes predicted to play significant roles in the control of programmed cell death and especially in ubiquitin pathway-related processes.
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http://dx.doi.org/10.1534/genetics.112.147595DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3567748PMC
February 2013

PhenoPhyte: a flexible affordable method to quantify 2D phenotypes from imagery.

Plant Methods 2012 Nov 6;8(1):45. Epub 2012 Nov 6.

Division of Plant Sciences, University of Missouri, Columbia, MO, 65211, USA.

Unlabelled:

Background: Accurate characterization of complex plant phenotypes is critical to assigning biological functions to genes through forward or reverse genetics. It can also be vital in determining the effect of a treatment, genotype, or environmental condition on plant growth or susceptibility to insects or pathogens. Although techniques for characterizing complex phenotypes have been developed, most are not cost effective or are too imprecise or subjective to reliably differentiate subtler differences in complex traits like growth, color change, or disease resistance.

Results: We designed an inexpensive imaging protocol that facilitates automatic quantification of two-dimensional visual phenotypes using computer vision and image processing algorithms applied to standard digital images. The protocol allows for non-destructive imaging of plants in the laboratory and field and can be used in suboptimal imaging conditions due to automated color and scale normalization. We designed the web-based tool PhenoPhyte for processing images adhering to this protocol and demonstrate its ability to measure a variety of two-dimensional traits (such as growth, leaf area, and herbivory) using images from several species (Arabidopsis thaliana and Brassica rapa). We then provide a more complicated example for measuring disease resistance of Zea mays to Southern Leaf Blight.

Conclusions: PhenoPhyte is a new cost-effective web-application for semi-automated quantification of two-dimensional traits from digital imagery using an easy imaging protocol. This tool's usefulness is demonstrated for a variety of traits in multiple species. We show that digital phenotyping can reduce human subjectivity in trait quantification, thereby increasing accuracy and improving precision, which are crucial for differentiating and quantifying subtle phenotypic variation and understanding gene function and/or treatment effects.
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http://dx.doi.org/10.1186/1746-4811-8-45DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546069PMC
November 2012

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing plant disease resistance.

Phytopathology 2012 Nov;102(11):1016-25

Department of Plant and Soil Sciences, University of Delaware, Newark 19716, USA.

ABSTRACT The mixed linear model (MLM) is an advanced statistical technique applicable to many fields of science. The multivariate MLM can be used to model longitudinal data, such as repeated ratings of disease resistance taken across time. In this study, using an example data set from a multi-environment trial of northern leaf blight disease on 290 maize lines with diverse levels of resistance, multivariate MLM analysis was performed and its utility was examined. In the population and environments tested, genotypic effects were highly correlated across disease ratings and followed an autoregressive pattern of correlation decay. Because longitudinal data are often converted to the univariate measure of area under the disease progress curve (AUDPC), comparisons between univariate MLM analysis of AUDPC and multivariate MLM analysis of longitudinal data were made. Univariate analysis had the advantage of simplicity and reduced computational demand, whereas multivariate analysis enabled a comprehensive perspective on disease development, providing the opportunity for unique insights into disease resistance. To aid in the application of multivariate MLM analysis of longitudinal data on disease resistance, annotated program syntax for model fitting is provided for the software ASReml.
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http://dx.doi.org/10.1094/PHYTO-10-11-0268DOI Listing
November 2012

Analysis of quantitative disease resistance to southern leaf blight and of multiple disease resistance in maize, using near-isogenic lines.

Theor Appl Genet 2012 Feb 14;124(3):433-45. Epub 2011 Oct 14.

Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695-7616, USA.

Maize inbred lines NC292 and NC330 were derived by repeated backcrossing of an elite source of southern leaf blight (SLB) resistance (NC250P) to the SLB-susceptible line B73, with selection for SLB resistance among and within backcross families at each generation. Consequently, while B73 is very SLB susceptible, its sister lines NC292 and NC330 are both SLB resistant. Previously, we identified the 12 introgressions from NC250P that differentiate NC292 and NC330 from B73. The goals of this study were to determine the effects of each introgression on resistance to SLB and to two other foliar fungal diseases of maize, northern leaf blight and gray leaf spot. This was achieved by generating and testing a set of near isogenic lines carry single or combinations of just two or three introgressions in a B73 background. Introgressions 3B, 6A, and 9B (bins 3.03-3.04, 6.01, and 9.02-9.03) all conferred significant levels of SLB resistance in the field. Introgression 6A was the only introgression that had a significant effect on juvenile plant resistance to SLB. Introgressions 6A and 9B conferred resistance to multiple diseases.
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http://dx.doi.org/10.1007/s00122-011-1718-1DOI Listing
February 2012

Use of Mutant-Assisted Gene Identification and Characterization (MAGIC) to identify novel genetic loci that modify the maize hypersensitive response.

Theor Appl Genet 2011 Oct 27;123(6):985-97. Epub 2011 Jul 27.

Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA.

The partially dominant, autoactive maize disease resistance gene Rp1-D21 causes hypersensitive response (HR) lesions to form spontaneously on leaves and stems in the absence of pathogen recognition. The maize nested association mapping (NAM) population consists of 25 200-line subpopulations each derived from a cross between the maize line B73 and one of 25 diverse inbred lines. By crossing a line carrying the Rp1-D21 gene with lines from three of these subpopulations and assessing the F(1) progeny, we were able to map several novel loci that modify the maize HR, using both single-population quantitative trait locus (QTL) and joint analysis of all three populations. Joint analysis detected QTL in greater number and with greater confidence and precision than did single population analysis. In particular, QTL were detected in bins 1.02, 4.04, 9.03, and 10.03. We have previously termed this technique, in which a mutant phenotype is used as a "reporter" for a trait of interest, Mutant-Assisted Gene Identification and Characterization (MAGIC).
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http://dx.doi.org/10.1007/s00122-011-1641-5DOI Listing
October 2011

Targeted discovery of quantitative trait loci for resistance to northern leaf blight and other diseases of maize.

Theor Appl Genet 2011 Jul 28;123(2):307-26. Epub 2011 Apr 28.

Department of Plant Pathology and Plant-Microbe Biology, Cornell University, Ithaca, NY14853, USA.

To capture diverse alleles at a set of loci associated with disease resistance in maize, heterogeneous inbred family (HIF) analysis was applied for targeted QTL mapping and near-isogenic line (NIL) development. Tropical maize lines CML52 and DK888 were chosen as donors of alleles based on their known resistance to multiple diseases. Chromosomal regions ("bins"; n = 39) associated with multiple disease resistance (MDR) were targeted based on a consensus map of disease QTLs in maize. We generated HIFs segregating for the targeted loci but isogenic at ~97% of the genome. To test the hypothesis that CML52 and DK888 alleles at MDR hotspots condition broad-spectrum resistance, HIFs and derived NILs were tested for resistance to northern leaf blight (NLB), southern leaf blight (SLB), gray leaf spot (GLS), anthracnose leaf blight (ALB), anthracnose stalk rot (ASR), common rust, common smut, and Stewart's wilt. Four NLB QTLs, two ASR QTLs, and one Stewart's wilt QTL were identified. In parallel, a population of 196 recombinant inbred lines (RILs) derived from B73 × CML52 was evaluated for resistance to NLB, GLS, SLB, and ASR. The QTLs mapped (four for NLB, five for SLB, two for GLS, and two for ASR) mostly corresponded to those found using the NILs. Combining HIF- and RIL-based analyses, we discovered two disease QTLs at which CML52 alleles were favorable for more than one disease. A QTL in bin 1.06-1.07 conferred resistance to NLB and Stewart's wilt, and a QTL in 6.05 conferred resistance to NLB and ASR.
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http://dx.doi.org/10.1007/s00122-011-1585-9DOI Listing
July 2011

Multivariate analysis of maize disease resistances suggests a pleiotropic genetic basis and implicates a GST gene.

Proc Natl Acad Sci U S A 2011 May 13;108(18):7339-44. Epub 2011 Apr 13.

Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716-1304, USA.

Plants are attacked by pathogens representing diverse taxonomic groups, such that genes providing multiple disease resistance (MDR) are expected to be under positive selection pressure. To address the hypothesis that naturally occurring allelic variation conditions MDR, we extended the framework of structured association mapping to allow for the analysis of correlated complex traits and the identification of pleiotropic genes. The multivariate analytical approach used here is directly applicable to any species and set of traits exhibiting correlation. From our analysis of a diverse panel of maize inbred lines, we discovered high positive genetic correlations between resistances to three globally threatening fungal diseases. The maize panel studied exhibits rapidly decaying linkage disequilibrium that generally occurs within 1 or 2 kb, which is less than the average length of a maize gene. The positive correlations therefore suggested that functional allelic variation at specific genes for MDR exists in maize. Using a multivariate test statistic, a glutathione S-transferase (GST) gene was found to be associated with modest levels of resistance to all three diseases. Resequencing analysis pinpointed the association to a histidine (basic amino acid) for aspartic acid (acidic amino acid) substitution in the encoded protein domain that defines GST substrate specificity and biochemical activity. The known functions of GSTs suggested that variability in detoxification pathways underlie natural variation in maize MDR.
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http://dx.doi.org/10.1073/pnas.1011739108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3088610PMC
May 2011

Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population.

Nat Genet 2011 Feb 9;43(2):163-8. Epub 2011 Jan 9.

Department of Crop Science, North Carolina State University, Raleigh, North Carolina, USA.

Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions.
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http://dx.doi.org/10.1038/ng.747DOI Listing
February 2011

Resistance loci affecting distinct stages of fungal pathogenesis: use of introgression lines for QTL mapping and characterization in the maize--Setosphaeria turcica pathosystem.

BMC Plant Biol 2010 Jun 8;10:103. Epub 2010 Jun 8.

Dept. of Plant Pathology and Plant-Microbe Biology, Cornell University, Ithaca, NY 14853, USA.

Background: Studies on host-pathogen interactions in a range of pathosystems have revealed an array of mechanisms by which plants reduce the efficiency of pathogenesis. While R-gene mediated resistance confers highly effective defense responses against pathogen invasion, quantitative resistance is associated with intermediate levels of resistance that reduces disease progress. To test the hypothesis that specific loci affect distinct stages of fungal pathogenesis, a set of maize introgression lines was used for mapping and characterization of quantitative trait loci (QTL) conditioning resistance to Setosphaeria turcica, the causal agent of northern leaf blight (NLB). To better understand the nature of quantitative resistance, the identified QTL were further tested for three secondary hypotheses: (1) that disease QTL differ by host developmental stage; (2) that their performance changes across environments; and (3) that they condition broad-spectrum resistance.

Results: Among a set of 82 introgression lines, seven lines were confirmed as more resistant or susceptible than B73. Two NLB QTL were validated in BC4F2 segregating populations and advanced introgression lines. These loci, designated qNLB1.02 and qNLB1.06, were investigated in detail by comparing the introgression lines with B73 for a series of macroscopic and microscopic disease components targeting different stages of NLB development. Repeated greenhouse and field trials revealed that qNLB1.06(Tx303) (the Tx303 allele at bin 1.06) reduces the efficiency of fungal penetration, while qNLB1.02(B73) (the B73 allele at bin 1.02) enhances the accumulation of callose and phenolics surrounding infection sites, reduces hyphal growth into the vascular bundle and impairs the subsequent necrotrophic colonization in the leaves. The QTL were equally effective in both juvenile and adult plants; qNLB1.06(Tx303) showed greater effectiveness in the field than in the greenhouse. In addition to NLB resistance, qNLB1.02(B73) was associated with resistance to Stewart's wilt and common rust, while qNLB1.06(Tx303) conferred resistance to Stewart's wilt. The non-specific resistance may be attributed to pleiotropy or linkage.

Conclusions: Our research has led to successful identification of two reliably-expressed QTL that can potentially be utilized to protect maize from S. turcica in different environments. This approach to identifying and dissecting quantitative resistance in plants will facilitate the application of quantitative resistance in crop protection.
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http://dx.doi.org/10.1186/1471-2229-10-103DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3017769PMC
June 2010

Maize leaf epiphytic bacteria diversity patterns are genetically correlated with resistance to fungal pathogen infection.

Mol Plant Microbe Interact 2010 Apr;23(4):473-84

United States Department of Agriculture-Agricultural Research Service and Department of Plant Pathology, North Carolina State University, Raleigh, NC, USA.

Plant leaves host a specific set of microbial epiphytes. Plant genetic and solar UV-B radiation effects on the diversity of the phyllosphere were examined by measuring epiphytic bacterial ribosomal DNA diversity in a maize recombinant inbred (RI) mapping population. Several chromosomal quantitative trait loci (QTL) with significant effects on bacterial diversity were identified, some of which had effects only in the presence of UV-B radiation and others that had effects both with and without UV-B. Candidate genes with allele-specific effects were mapped to the bacterial diversity chromosomal regions. A glutamate decarboxylase candidate gene was located at a UV-B-specific chromosomal locus, and in a comparison between two RI lines with contrasting bacterial diversity phenotypes, high bacterial diversity was associated with high levels of glutamate decarboxylase enzyme activity, a component of the gamma-aminobutyric acid (GABA) pathway. The bacterial diversity loci exhibited a significant overlap with loci connected with Southern leaf blight (SLB) susceptibility in the field. A SLB-resistant inbred genotype had less beta bacterial diversity, and antibiotic treatment of inbreds increased this diversity. These results suggest that the GABA pathway is genetically associated with phyllosphere bacterial diversity. Furthermore, the colocalization of QTL between low bacterial diversity and fungal blight-resistance and the increase in beta diversity in antibiotic-treated leaves suggest that occupation of leaf habitats by a particular set of suppressive bacteria may restrict phyllosphere bacterial variability and increase resistance to fungal infection.
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http://dx.doi.org/10.1094/MPMI-23-4-0473DOI Listing
April 2010

Identification of a maize locus that modulates the hypersensitive defense response, using mutant-assisted gene identification and characterization.

Genetics 2010 Mar 22;184(3):813-25. Epub 2010 Feb 22.

Department of Botany and Plant Pathology, Purdue University, West Lafayette, Indiana 47907-2054, USA.

Potentially useful naturally occurring genetic variation is often difficult to identify as the effects of individual genes are subtle and difficult to observe. In this study, a novel genetic technique called Mutant-Assisted Gene Identification and Characterization is used to identify naturally occurring loci modulating the hypersensitive defense response (HR) in maize. Mutant-Assisted Gene Identification and Characterization facilitates the identification of naturally occurring alleles underlying phenotypic variation from diverse germplasm, using a mutant phenotype as a "reporter." In this study the reporter phenotype was caused by a partially dominant autoactive disease resistance gene, Rp1-D21, which caused HR lesions to form spontaneously all over the plant. Here it is demonstrated that the Rp1-D21 phenotype is profoundly affected by genetic background. By crossing the Rp1-D21 gene into the IBM mapping population, it was possible to map and identify Hrml1 on chromosome 10, a locus responsible for modulating the HR phenotype conferred by Rp1-D21. Other loci with smaller effects were identified on chromosomes 1 and 9. These results demonstrate that Mutant-Assisted Gene Identification and Characterization is a viable approach for identifying naturally occurring useful genetic variation.
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http://dx.doi.org/10.1534/genetics.109.111880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2845348PMC
March 2010

Genetic control of photoperiod sensitivity in maize revealed by joint multiple population analysis.

Genetics 2010 Mar 14;184(3):799-812. Epub 2009 Dec 14.

Department of Crop Science, North Carolina State University, Raleigh, North Carolina 27695, USA.

Variation in maize for response to photoperiod is related to geographical adaptation in the species. Maize possesses homologs of many genes identified as regulators of flowering time in other species, but their relation to the natural variation for photoperiod response in maize is unknown. Candidate gene sequences were mapped in four populations created by crossing two temperate inbred lines to two photoperiod-sensitive tropical inbreds. Whole-genome scans were conducted by high-density genotyping of the populations, which were phenotyped over 3 years in both short- and long-day environments. Joint multiple population analysis identified genomic regions controlling photoperiod responses in flowering time, plant height, and total leaf number. Four key genome regions controlling photoperiod response across populations were identified, referred to as ZmPR1-4. Functional allelic differences within these regions among phenotypically similar founders suggest distinct evolutionary trajectories for photoperiod adaptation in maize. These regions encompass candidate genes CCA/LHY, CONZ1, CRY2, ELF4, GHD7, VGT1, HY1/SE5, TOC1/PRR7/PPD-1, PIF3, ZCN8, and ZCN19.
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http://dx.doi.org/10.1534/genetics.109.110304DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2845347PMC
March 2010

Mapping resistance quantitative trait Loci for three foliar diseases in a maize recombinant inbred line population-evidence for multiple disease resistance?

Phytopathology 2010 Jan;100(1):72-9

Department of Plant Pathology, North Carolona State University, Raleigh, NC 27695, USA.

Southern leaf blight (SLB), gray leaf spot (GLS), and northern leaf blight (NLB) are all important foliar diseases impacting maize production. The objectives of this study were to identify quantitative trait loci (QTL) for resistance to these diseases in a maize recombinant inbred line (RIL) population derived from a cross between maize lines Ki14 and B73, and to evaluate the evidence for the presence genes or loci conferring multiple disease resistance (MDR). Each disease was scored in multiple separate trials. Highly significant correlations between the resistances and the three diseases were found. The highest correlation was identified between SLB and GLS resistance (r = 0.62). Correlations between resistance to each of the diseases and time to flowering were also highly significant. Nine, eight, and six QTL were identified for SLB, GLS, and NLB resistance, respectively. QTL for all three diseases colocalized in bin 1.06, while QTL colocalizing for two of the three diseases were identified in bins 1.08 to 1.09, 2.02/2.03, 3.04/3.05, 8.05, and 10.05. QTL for time to flowering were also identified at four of these six loci (bins 1.06, 3.04/3.05, 8.05, and 10.05). No disease resistance QTL was identified at the largest-effect QTL for flowering time in bin 10.03.
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http://dx.doi.org/10.1094/PHYTO-100-1-0072DOI Listing
January 2010

Use of selection with recurrent backcrossing and QTL mapping to identify loci contributing to southern leaf blight resistance in a highly resistant maize line.

Theor Appl Genet 2009 Mar 8;118(5):911-25. Epub 2009 Jan 8.

Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695-7616, USA.

B73 is a historically important maize line with excellent yield potential but high susceptibility to the foliar disease southern leaf blight (SLB). NC292 and NC330 are B73 near-isogenic lines (NILs) that are highly resistant to SLB. They were derived by repeated backcrossing of an elite source of SLB resistance (NC250P) to B73, with selection for SLB resistance among and within backcross families. The goal of this paper was to characterize the loci responsible for the increased SLB resistance of NC292 and NC330 and to determine how many of the SLB disease resistance quantitative trait loci (dQTL) were selected for in the development of NC292 and NC330. Genomic regions that differentiated NC292 and NC330 from B73 and which may contribute to NC292 and NC330s enhanced SLB resistance were identified. Ten NC250P-derived introgressions were identified in both the NC292 and NC330 genomes of which eight were shared between genomes. dQTL were mapped in two F(2:3) populations derived from lines very closely related to the original parents of NC292 and NC330--(B73rhm1 x NC250A and NC250A x B73). Nine SLB dQTL were mapped in the combined populations using combined SLB disease data over all locations (SLB AllLocs). Of these, four dQTL precisely colocalized with NC250P introgressions in bins 2.05-2.06, 3.03, 6.01, and 9.02 and three were identified near NC250P introgressions in bins 1.09, 5.05-5.06, and 10.03. Therefore the breeding program used to develop NC292 and NC330 was highly effective in selecting for multiple SLB resistance alleles.
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http://dx.doi.org/10.1007/s00122-008-0949-2DOI Listing
March 2009

Shades of gray: the world of quantitative disease resistance.

Trends Plant Sci 2009 Jan 4;14(1):21-9. Epub 2008 Dec 4.

Department of Plant Breeding & Genetics, Cornell University, Ithaca, NY 14853, USA.

A thorough understanding of quantitative disease resistance (QDR) would contribute to the design and deployment of durably resistant crop cultivars. However, the molecular mechanisms that control QDR remain poorly understood, largely due to the incomplete and inconsistent nature of the resistance phenotype, which is usually conditioned by many loci of small effect. Here, we discuss recent advances in research on QDR. Based on inferences from analyses of the defense response and from the few isolated QDR genes, we suggest several plausible hypotheses for a range of mechanisms underlying QDR. We propose that a new generation of genetic resources, complemented by careful phenotypic analysis, will produce a deeper understanding of plant defense and more effective utilization of natural resistance alleles.
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http://dx.doi.org/10.1016/j.tplants.2008.10.006DOI Listing
January 2009