Selection mapping of loci for quantitative disease resistance in a diverse maize population

Mapping quantitative trait loci for seminal root angle in a selected durum wheat population

Seminal root angle (SRA) is an important root architectural trait associated with drought adaptation in cereal crops. To date, all attempts to dissect the genetic architecture of SRA in durum wheat (Triticum durum Desf.) have used large association panels or structured mapping populations. Identifying changes in allele frequency generated by selection provides an alternative genetic mapping approach that can increase the power and precision of QTL detection. This study aimed to map quantitative trait loci (QTL) for SRA by genotyping durum lines created through divergent selection using a combination of marker-assisted selection (MAS) for the major SRA QTL (qSRA-6A) and phenotypic selection for SRA over multiple generations. The created 11 lines (BC1F2:5) were genotyped with genome-wide single-nucleotide polymorphism (SNP) markers to map QTL by identifying markers that displayed segregation distortion significantly different from the Mendelian expectation. QTL regions were further assessed in an independent validation population to confirm their associations with SRA. The experiment revealed 14 genomic regions under selection, 12 of which have not previously been reported for SRA. Five regions, including qSRA-6A, were confirmed in the validation population. The genomic regions identified in this study indicate that the genetic control of SRA is more complex than previously anticipated. Our study demonstrates that selection mapping is a powerful approach to complement genome-wide association studies for QTL detection. Moreover, the verification of qSRA-6A in an elite genetic background highlights the potential for MAS, although it is necessary to combine additional QTL to develop new cultivars with extreme SRA phenotypes.

Mapping QTL associated with resistance to Pseudomonas syringae pv. actinidiae in kiwifruit (Actinidia chinensis var. chinensis)

Pseudomonas syringae pv. actinidiae (Psa) is a bacterial pathogen of kiwifruit. This pathogen causes leaf-spotting, cane dieback, wilting, cankers (lesions), and in severe cases, plant death. Families of diploid A. chinensis seedlings grown in the field show a range of susceptibilities to the disease with up to 100% of seedlings in some families succumbing to Psa. But the effect of selection for field resistance to Psa on the alleles that remain in surviving seedlings has not been assessed. The objective of this work was to analyse, the effect of plant removal from Psa on the allele frequency of an incomplete-factorial-cross population. This population was founded using a range of genotypically distinct diploid A. chinensis var. chinensis parents to make 28 F1 families. However, because of the diversity of these families, low numbers of surviving individuals, and a lack of samples from dead individuals, standard QTL mapping approaches were unlikely to yield good results. Instead, a modified bulk segregant analysis (BSA) overcame these drawbacks while reducing the costs of sampling and sample processing, and the complexity of data analysis. Because the method was modified, part one of this work was used to determine the signal strength required for a QTL to be detected with BSA. Once QTL detection accuracy was known, part two of this work analysed the 28 families from the incomplete-factorial-cross population that had multiple individuals removed due to Psa infection. Each family was assigned to one of eight bulks based on a single parent that contributed to the families. DNA was extracted in bulk by grinding sampled leaf discs together before DNA extraction. Each sample bulk was compared against a bulk made up of WGS data from the parents contributing to the sample bulk. The deviation in allele frequency from the expected allele frequency within surviving populations using the modified BSA method was able to identify 11 QTLs for Psa that were present in at least two analyses. The identification of these Psa resistance QTL will enable marker development to selectively breed for resistance to Psa in future kiwifruit breeding programs.

A genomic analysis of the University of Nebraska Replicated Recurrent Selection program

The inbred-hybrid system of maize breeding closely resembles a reciprocal full-sib (RFS) selection program. Studying changes in genetic variation as a result of RFS selection can help illuminate long-standing questions regarding the relative roles of selection and genetic drift and help understand the nature of adaptation occurring in selection programs. The University of Nebraska-Lincoln Replicated Recurrent Selection (UNL-RpRS) program underwent eight cycles of replicated RFS and S1-progeny selection, making it a powerful system to study genomic changes accompanying selection for inter-population performance. The objectives of this study were to identify regions of the genome under selection after eight cycles of selection and evaluate the effect eight cycles of selection for inter-population full-sib performance had in expanding genome-wide and localized population structure. We address these questions with a large set of individuals sampled from the UNL-RpRS program with dense genotyping-by-sequence data. We found evidence of parallel selection signatures in the UNL-RpRS program, with a region on chromosome 7 being implicated in three of the four selection systems studied. Regions that displayed selection signatures across independently run selection programs represent regions likely to be capitalizing on standing genetic variation and support a soft sweep model of adaptation. We did not find selection to be a strong force in diverging populations undergoing RFS. This could be due to the nature of adaptation occurring in these populations, underlying gene action, or a result of unstable genetic topographies.

Brown midrib mutant and genome-wide association analysis uncover lignin genes for disease resistance in maize

Brown midrib (BMR) maize (Zea mays L.) harbors mutations that result in lower lignin levels and higher feed digestibility, making it a desirable silage market class for ruminant nutrition. Northern leaf blight (NLB) epidemics in upstate New York highlighted the disease susceptibility of commercially grown BMR maize hybrids. We found the bm1, bm2, bm3, and bm4 mutants in a W64A genetic background to be more susceptible to foliar fungal (NLB, gray leaf spot [GLS], and anthracnose leaf blight [ALB]) and bacterial (Stewart's wilt) diseases. The bm1, bm2, and bm3 mutants showed enhanced susceptibility to anthracnose stalk rot (ASR), and the bm1 and bm3 mutants were more susceptible to Gibberella ear rot (GER). Colocalization of quantitative trait loci (QTL) and correlations between stalk strength and disease traits in recombinant inbred line families suggest possible pleiotropies. The role of lignin in plant defense was explored using high-resolution, genome-wide association analysis for resistance to NLB in the Goodman diversity panel. Association analysis identified 100 single and clustered single-nucleotide polymorphism (SNP) associations for resistance to NLB but did not implicate natural functional variation at bm1-bm5. Strong associations implicated a suite of diverse candidate genes including lignin-related genes such as a β-glucosidase gene cluster, hct11, knox1, knox2, zim36, lbd35, CASP-like protein 8, and xat3. The candidate genes are targets for breeding quantitative resistance to NLB in maize for use in silage and nonsilage purposes.

The recent evolutionary rescue of a staple crop depended on over half a century of global germplasm exchange

Rapid environmental change can lead to population extinction or evolutionary rescue. The global staple crop sorghum (Sorghum bicolor) has recently been threatened by a global outbreak of an aggressive new biotype of sugarcane aphid (SCA; Melanaphis sacchari). We characterized genomic signatures of adaptation in a Haitian breeding population that had rapidly adapted to SCA infestation, conducting evolutionary population genomics analyses on 296 Haitian lines versus 767 global accessions. Genome scans and geographic analyses suggest that SCA adaptation has been conferred by a globally rare East African allele of RMES1, which spread to breeding programs in Africa, Asia, and the Americas. De novo genome sequencing revealed potential causative variants at RMES1. Markers developed from the RMES1 sweep predicted resistance in eight independent commercial and public breeding programs. These findings demonstrate the value of evolutionary genomics to develop adaptive trait technology and highlight the benefits of global germplasm exchange to facilitate evolutionary rescue.

Identifying adaptive alleles in the human genome: from selection mapping to functional validation

The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.

A Simple Test Identifies Selection on Complex Traits

Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome-wide association studies and selection-mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique uses additive-effects estimates from all available markers, and relates these estimates to allele-frequency change over time. Using this information, we generate a composite statistic, denoted [Formula: see text] which can be used to test for significant evidence of selection on a trait. Our test requires pre- and postselection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that [Formula: see text] is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection.

Selection Mapping Identifies Loci Underpinning Autumn Dormancy in Alfalfa (Medicago sativa)

Autumn dormancy in alfalfa (Medicago sativa) is associated with agronomically important traits including regrowth rate, maturity, and winter survival. Historical recurrent selection experiments have been able to manipulate the dormancy response. We hypothesized that artificial selection for dormancy phenotypes in these experiments had altered allele frequencies of dormancy-related genes. Here, we follow this hypothesis and analyze allele frequency changes using genome-wide polymorphisms in the pre- and postselection populations from one historical selection experiment. We screened the nondormant cultivar CUF 101 and populations developed by three cycles of recurrent phenotypic selection for taller and shorter plants in autumn with markers derived from genotyping-by-sequencing (GBS). We validated the robustness of our GBS-derived allele frequency estimates using an empirical approach. Our results suggest that selection mapping is a powerful means of identifying genomic regions associated with traits, and that it can be exploited to provide regions on which to focus further mapping and cloning projects.

Whole-Genome Analysis of Candidate genes Associated with Seed Size and Weight in Sorghum bicolor Reveals Signatures of Artificial Selection and Insights into Parallel Domestication in Cereal Crops

Seed size and seed weight are major quality attributes and important determinants of yield that have been strongly selected for during crop domestication. Limited information is available about the genetic control and genes associated with seed size and weight in sorghum. This study identified sorghum orthologs of genes with proven effects on seed size and weight in other plant species and searched for evidence of selection during domestication by utilizing resequencing data from a diversity panel. In total, 114 seed size candidate genes were identified in sorghum, 63 of which exhibited signals of purifying selection during domestication. A significant number of these genes also had domestication signatures in maize and rice, consistent with the parallel domestication of seed size in cereals. Seed size candidate genes that exhibited differentially high expression levels in seed were also found more likely to be under selection during domestication, supporting the hypothesis that modification to seed size during domestication preferentially targeted genes for intrinsic seed size rather than genes associated with physiological factors involved in the carbohydrate supply and transport. Our results provide improved understanding of the complex genetic control of seed size and weight and the impact of domestication on these genes.

Whole-Genome Analysis of Candidate genes Associated with Seed Size and Weight in Sorghum bicolor Reveals Signatures of Artificial Selection and Insights into Parallel Domestication in Cereal Crops

Seed size and seed weight are major quality attributes and important determinants of yield that have been strongly selected for during crop domestication. Limited information is available about the genetic control and genes associated with seed size and weight in sorghum. This study identified sorghum orthologs of genes with proven effects on seed size and weight in other plant species and searched for evidence of selection during domestication by utilizing resequencing data from a diversity panel. In total, 114 seed size candidate genes were identified in sorghum, 63 of which exhibited signals of purifying selection during domestication. A significant number of these genes also had domestication signatures in maize and rice, consistent with the parallel domestication of seed size in cereals. Seed size candidate genes that exhibited differentially high expression levels in seed were also found more likely to be under selection during domestication, supporting the hypothesis that modification to seed size during domestication preferentially targeted genes for intrinsic seed size rather than genes associated with physiological factors involved in the carbohydrate supply and transport. Our results provide improved understanding of the complex genetic control of seed size and weight and the impact of domestication on these genes.

Selection Signatures in Four Lignin Genes from Switchgrass Populations Divergently Selected for In Vitro Dry Matter Digestibility

Switchgrass is undergoing development as a dedicated cellulosic bioenergy crop. Fermentation of lignocellulosic biomass to ethanol in a bioenergy system or to volatile fatty acids in a livestock production system is strongly and negatively influenced by lignification of cell walls. This study detects specific loci that exhibit selection signatures across switchgrass breeding populations that differ in in vitro dry matter digestibility (IVDMD), ethanol yield, and lignin concentration. Allele frequency changes in candidate genes were used to detect loci under selection. Out of the 183 polymorphisms identified in the four candidate genes, twenty-five loci in the intron regions and four loci in coding regions were found to display a selection signature. All loci in the coding regions are synonymous substitutions. Selection in both directions were observed on polymorphisms that appeared to be under selection. Genetic diversity and linkage disequilibrium within the candidate genes were low. The recurrent divergent selection caused excessive moderate allele frequencies in the cycle 3 reduced lignin population as compared to the base population. This study provides valuable insight on genetic changes occurring in short-term selection in the polyploid populations, and discovered potential markers for breeding switchgrass with improved biomass quality.

Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens

A whole-genome scan for identifying selection acting on pairs of linked loci is proposed and implemented. The scan is based on , one of Ohta's 1982 measures of between-population linkage disequilibrium (LD). An approximate empirical null distribution for the statistic is suggested. Although the partitioning of LD into between-population components was originally used to investigate epistatic selection, we demonstrate that values of may also be influenced by single-locus selective sweeps with linkage but no epistasis. The proposed scan is implemented in a diverse panel of chickens including 72 distinct breeds genotyped at 538 298 single-nucleotide polymorphisms. In all, 1723 locus pairs are identified as putatively corresponding to a selective sweep or epistatic selection. These pairs of loci generally cluster to form overlapping or neighboring signals of selection. Known variants that were expected to have been under selection in the panel are identified, as well as an assortment of novel regions that have putatively been under selection in chickens. Notably, a promising pair of genes located 8 MB apart on chromosome 9 are identified based on as demonstrating strong evidence of dispersive epistatic selection between populations.

Selection for silage yield and composition did not affect genomic diversity within the Wisconsin Quality Synthetic maize population

Maize silage is forage of high quality and yield, and represents the second most important use of maize in the United States. The Wisconsin Quality Synthetic (WQS) maize population has undergone five cycles of recurrent selection for silage yield and composition, resulting in a genetically improved population. The application of high-density molecular markers allows breeders and geneticists to identify important loci through association analysis and selection mapping, as well as to monitor changes in the distribution of genetic diversity across the genome. The objectives of this study were to identify loci controlling variation for maize silage traits through association analysis and the assessment of selection signatures and to describe changes in the genomic distribution of gene diversity through selection and genetic drift in the WQS recurrent selection program. We failed to find any significant marker-trait associations using the historical phenotypic data from WQS breeding trials combined with 17,719 high-quality, informative single nucleotide polymorphisms. Likewise, no strong genomic signatures were left by selection on silage yield and quality in the WQS despite genetic gain for these traits. These results could be due to the genetic complexity underlying these traits, or the role of selection on standing genetic variation. Variation in loss of diversity through drift was observed across the genome. Some large regions experienced much greater loss in diversity than what is expected, suggesting limited recombination combined with small populations in recurrent selection programs could easily lead to fixation of large swaths of the genome.

Two distinct classes of QTL determine rust resistance in sorghum

BACKGROUND

Agriculture is facing enormous challenges to feed a growing population in the face of rapidly evolving pests and pathogens. The rusts, in particular, are a major pathogen of cereal crops with the potential to cause large reductions in yield. Improving stable disease resistance is an on-going major and challenging focus for many plant breeding programs, due to the rapidly evolving nature of the pathogen. Sorghum is a major summer cereal crop that is also a host for a rust pathogen Puccinia purpurea, which occurs in almost all sorghum growing areas of the world, causing direct and indirect yield losses in sorghum worldwide, however knowledge about its genetic control is still limited. In order to further investigate this issue, QTL and association mapping methods were implemented to study rust resistance in three bi-parental populations and an association mapping set of elite breeding lines in different environments.

RESULTS

In total, 64 significant or highly significant QTL and 21 suggestive rust resistance QTL were identified representing 55 unique genomic regions. Comparisons across populations within the current study and with rust QTL identified previously in both sorghum and maize revealed a high degree of correspondence in QTL location. Negative phenotypic correlations were observed between rust, maturity and height, indicating a trend for both early maturing and shorter genotypes to be more susceptible to rust.

CONCLUSIONS

The significant amount of QTL co-location across traits, in addition to the consistency in the direction of QTL allele effects, has provided evidence to support pleiotropic QTL action across rust, height, maturity and stay-green, supporting the role of carbon stress in susceptibility to rust. Classical rust resistance QTL regions that did not co-locate with height, maturity or stay-green QTL were found to be significantly enriched for the defence-related NBS-encoding gene family, in contrast to the lack of defence-related gene enrichment in multi-trait effect rust resistance QTL. The distinction of disease resistance QTL hot-spots, enriched with defence-related gene families from QTL which impact on development and partitioning, provides plant breeders with knowledge which will allow for fast-tracking varieties with both durable pathogen resistance and appropriate adaptive traits.

Insights into the effects of long-term artificial selection on seed size in maize

Grain produced from cereal crops is a primary source of human food and animal feed worldwide. To understand the genetic basis of seed-size variation, a grain yield component, we conducted a genome-wide scan to detect evidence of selection in the maize Krug Yellow Dent long-term divergent seed-size selection experiment. Previous studies have documented significant phenotypic divergence between the populations. Allele frequency estimates for ∼3 million single nucleotide polymorphisms (SNPs) in the base population and selected populations were estimated from pooled whole-genome resequencing of 48 individuals per population. Using FST values across sliding windows, 94 divergent regions with a median of six genes per region were identified. Additionally, 2729 SNPs that reached fixation in both selected populations with opposing fixed alleles were identified, many of which clustered in two regions of the genome. Copy-number variation was highly prevalent between the selected populations, with 532 total regions identified on the basis of read-depth variation and comparative genome hybridization. Regions important for seed weight in natural variation were identified in the maize nested association mapping population. However, the number of regions that overlapped with the long-term selection experiment did not exceed that expected by chance, possibly indicating unique sources of variation between the two populations. The results of this study provide insights into the genetic elements underlying seed-size variation in maize and could also have applications for other cereal crops.

A genome-wide scan for evidence of selection in a maize population under long-term artificial selection for ear number

A genome-wide scan to detect evidence of selection was conducted in the Golden Glow maize long-term selection population. The population had been subjected to selection for increased number of ears per plant for 30 generations, with an empirically estimated effective population size ranging from 384 to 667 individuals and an increase of more than threefold in the number of ears per plant. Allele frequencies at >1.2 million single-nucleotide polymorphism loci were estimated from pooled whole-genome resequencing data, and FST values across sliding windows were employed to assess divergence between the population preselection and the population postselection. Twenty-eight highly divergent regions were identified, with half of these regions providing gene-level resolution on potentially selected variants. Approximately 93% of the divergent regions do not demonstrate a significant decrease in heterozygosity, which suggests that they are not approaching fixation. Also, most regions display a pattern consistent with a soft-sweep model as opposed to a hard-sweep model, suggesting that selection mostly operated on standing genetic variation. For at least 25% of the regions, results suggest that selection operated on variants located outside of currently annotated coding regions. These results provide insights into the underlying genetic effects of long-term artificial selection and identification of putative genetic elements underlying number of ears per plant in maize.

Identification of genomic loci associated with crown rust resistance in perennial ryegrass (Lolium perenne L.) divergently selected populations

The inheritance of crown rust resistance in perennial ryegrass is complex with both major and minor quantitative trait loci (QTL) being detected on all seven linkage groups. However, QTL mapping populations have only few segregating alleles, limiting the transferability of results to other materials. In this study, a synthetic population was developed from four crown rust resistant and susceptible parents as starting material for a divergent selection experiment of crown rust resistance to be closer to practice in plant breeding programs, and to identify genome regions relevant across a broader range of genotypes. Following three cycles of directional selection, perennial ryegrass populations were produced with a two-fold difference in average rust resistance. Divergently selected populations were genotyped at 7 resistance gene analog-derived expressed sequence tag (RGA-derived EST) as well as 15 simple sequence repeat (SSR) loci. A test for selective neutrality (Waples test), which tests the hypothesis of genetic drift versus selection, identified significant differences in allele frequencies for 7 loci (32%). The selection effect was bidirectional with the same loci showing significant response in both positively and negatively selected populations. A region under selection represented by markers LpSSR006 and EST13 on linkage group (LG) 4 was further confirmed by colocation with two separate QTL for crown rust resistance in a VrnA, a two-way pseudo-testcross mapping population. This suggests suitability of alleles identified for introgression into perennial ryegrass germplasm, where quantitative resistance to crown rust is desired.

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

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.

Information content in genome-wide scans: concordance between patterns of genetic differentiation and linkage mapping associations

BACKGROUND

Scanning the genome with high density SNP markers has become a standard approach for identifying regions of the genome showing substantial between-population genetic differentiation, and thus evidence of diversifying selection. Such regions may contain genes of large phenotypic effect. However, few studies have attempted to address the power or efficacy of such an approach.

RESULTS

In this study, the patterns of allele frequency differences between two cattle breeds based on the Bovine HapMap study were compared with statistical evidence for QTL based on a linkage mapping study of an experimental population formed by a cross between the same breeds. Concordance between the two datasets was seen for chromosomes carrying QTL with strong statistical support, such as BTA5 and BTA18, which carry genes associated with coat color. For these chromosomes, there was a correspondence between the strength of the QTL signal along the chromosome and the degree of genetic differentiation between breeds. However, such an association was not seen in a broader comparison that also included chromosomes carrying QTL with lower significance levels. In addition, other chromosomal regions with substantial QTL effects did not include markers showing extreme between-breed genetic differentiation. Furthermore, the overall consistency between the two studies was weak, with low genome-wide correlation between the statistical values obtained in the linkage mapping study and between-breed genetic differentiation from the HapMap study.

CONCLUSIONS

These results suggest that genomic diversity scans are capable of detecting regions associated with qualitative traits but may be limited in their power to detect regions associated with quantitative phenotypic differences between populations, which may depend on the marker resolution of the study and the level of LD in the populations under investigation.

Characterization and fine-mapping of a resistance locus for northern leaf blight in maize bin 8.06

As part of a larger effort to capture diverse alleles at a set of loci associated with disease resistance in maize, DK888, a hybrid known to possess resistance to multiple diseases, was used as a donor in constructing near-isogenic lines (NILs). A NIL pair contrasting for resistance to northern leaf blight (NLB), caused by Setosphaeria turcica, was identified and associated with bin 8.06. This region of the maize genome had been associated in previous studies with both qualitative and quantitative resistance to NLB. In addition, bins 8.05-8.06 had been associated with quantitative resistance to several other diseases, as well as resistance gene analogs and defense response gene homologs. To test the hypothesis that the DK888 allele at bin 8.06 (designated qNLB8.06 ( DK888 )) conditions the broad-spectrum quantitative resistance characteristic of the donor, the NILs were evaluated with a range of maize pathogens and different races of S. turcica. The results revealed that qNLB8.06 (DK888) confers race-specific resistance exclusively to NLB. Allelism analysis suggested that qNLB8.06 (DK888) is identical, allelic, or closely linked and functionally related to Ht2. The resistance conditioned by qNLB8.06 was incompletely dominant and varied in effectiveness depending upon allele and/or genetic background. High-resolution breakpoint analysis, using approximately 2,800 individuals in F(9)/F(10) heterogeneous inbred families and 98 F(10)/F(11) fixed lines carrying various recombinant events, delimited qNLB8.06 ( DK888 ) to a region of approximately 0.46 Mb, spanning 143.92-144.38 Mb on the B73 physical map. Three compelling candidate genes were identified in this region. Isolation of the gene(s) will contribute to better understanding of this complex locus.

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

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.

Quantitative disease resistance and quantitative resistance Loci in breeding

Quantitative disease resistance (QDR) has been observed within many crop plants but is not as well understood as qualitative (monogenic) disease resistance and has not been used as extensively in breeding. Mapping quantitative trait loci (QTLs) is a powerful tool for genetic dissection of QDR. DNA markers tightly linked to quantitative resistance loci (QRLs) controlling QDR can be used for marker-assisted selection (MAS) to incorporate these valuable traits. QDR confers a reduction, rather than lack, of disease and has diverse biological and molecular bases as revealed by cloning of QRLs and identification of the candidate gene(s) underlying QRLs. Increasing our biological knowledge of QDR and QRLs will enhance understanding of how QDR differs from qualitative resistance and provide the necessary information to better deploy these resources in breeding. Application of MAS for QRLs in breeding for QDR to diverse pathogens is illustrated by examples from wheat, barley, common bean, tomato, and pepper. Strategies for optimum deployment of QRLs require research to understand effects of QDR on pathogen populations over time.