Mapping quantitative trait loci associated with southern leaf blight resistance in maize (Zea mays L.)

Southern leaf blight (SLB) caused by the fungus Cochliobolus heterostrophus (Drechs.) Drechs. is a major foliar disease of maize worldwide. Our objectives were to identify quantitative trait loci (QTL) for resistance to SLB and flowering traits in recombinant inbred line (RIL) population derived from the cross of inbred lines LM5 (resistant) and CM140 (susceptible). A set of 207 RILs were phenotyped for resistance to SLB at three time intervals for two consecutive years. Four putative QTL for SLB resistance were detected on chromosomes 3, 8 and 9 that accounted for 54% of the total phenotypic variation. Days to silking and anthesis–silking interval (ASI) QTL were located on chromosomes 6, 7 and 9. A comparison of the obtained results with the published SLB resistance QTL studies suggested that the detected bins 9.03/02 and 8.03/8.02 are the hot spots for SLB resistance whereas novel QTL were identified in bins 3.08 and 8.01/8.04. The linked markers are being utilized for marker‐assisted mobilization of QTL conferring resistance to SLB in elite maize backgrounds. Fine mapping of identified QTL will facilitate identification of candidate genes underlying SLB resistance.     

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

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.     

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.     

Fine mapping of three quantitative trait loci for late blight resistance in tomato using near isogenic lines (NILs) and sub-NILs

An earlier study identified quantitative trait loci (QTLs) lb4, lb5b, and lb11b for quantitative resistance to Phytophthora infestans (late blight) in a backcross population derived from crossing susceptible cultivated tomato (Lycopersicon esculentum) with resistant L. hirsutum. The QTLs were located in intervals spanning 28–47 cM. Subsequently, near-isogenic lines (NILs) were developed for lb4, lb5b, and lb11b by marker-assisted backcrossing to L. esculentum. Sub-NILs containing overlapping L. hirsutum segments across each QTL region were selected and used to validate the QTL effects, fine-map QTLs, and evaluate potential linkage drag between resistance QTLs and QTLs for horticultural traits. The NILs and sub-NILs were evaluated for disease resistance and eight horticultural traits at three field locations. Resistance QTLs were detected in all three sets of NIL lines, confirming the BC₁ mapping results. Lb4 mapped near TG609, and between TG182 and CT194, on chromosome 4, a 6.9-cM interval; lb5b mapped to an 8.8-cM interval between TG69a and TG413 on chromosome 5, with the most likely position near TG23; and lb11b mapped to a 15.1-cM interval on chromosome 11 between TG194 and TG400, with the peak centered between CT182 and TG147. Most QTLs for horticultural traits were identified in intervals adjacent to those containing the late blight resistance QTLs. Fine mapping of these QTLs permits the use of marker-assisted selection for the precise introgression of L. hirsutum segments containing late blight resistance alleles separately from those containing deleterious alleles at horticulturally important QTLs.Electronic Supplementary Material Supplementary material is available in the online version of this article at Communicated by D.B. Neale     

Identification of quantitative trait loci controlling resistance to gray leaf spot disease in maize

Breeding maize for gray leaf spot (GLS) resistance has been hindered by the quantitative nature of the inheritance of GLS resistance and by the limitations of selection under less than optimumal disease pressure. In order to identify the quantitative trait loci (QTLs) controlling GLS resistance, a cross was made between B73 (susceptible) and Va14 (resistant) to generate a large F₂ population. Six GLS disease assessments were made throughout the disease season for over 1000 F₂ plants in 1989, and for 600 F₂-derived F₃ lines replicated in two blocks in 1990. RFLP analysis for78 marker loci representing all ten maize chromosomes was conducted in 239 F₂ individuals including those with the extreme GLS disease phenotypes. The GLS disease scores of the three field evaluations, each averaged over six ratings, were separately used for the interval mapping in order to determine the consistency of the QTL effects. The heavy GLS disease pressure, meticulous disease ratings, and large population size of this study afforded us the sensitivity for detecting QTL effects. QTLs located on three chromosomes (1, 4, and 8) had large effects on GLS resistance, each explaining 35.0–56.0%, 8.8–14.3%, and 7.7–11.0% of the variance, respectively. These three QTL effects were remarkably consistent across three disease evaluations over 2 years and two generations. Smaller QTL effects were also found on chromosomes 2 and 5, but the chromosome-5 effect might be a false positive because it was not repeatable even in the same location. The chromosome-1 QTLs had the largest effect or highest R² reported for any quantitative trait to-date. Except for the chromosome-4 gene, which was from the susceptible parent B73, the resistance alleles at all QTL were derived from Va14. The resistance QTLs on chromosomes 1 and 2 appear to have additive effects, but those on chromosomes 4 and 8 are dominant and recessive, respectively. Significant interaction between the QTLs on chromosomes 1 and 4 was detected in all three evaluations. Cumulatively, the four QTLs identified in this study explained 44, 60, and 68% of the variance in F₂, and in F₃ replications 1 and 2, respectively.     

Mapping quantitative trait loci in chickpea associated with time to flowering and resistance to Didymella rabiei the causal agent of Ascochyta blight

Drought is the major constraint to chickpea (Cicer arietinum L.) productivity worldwide. Utilizing early-flowering genotypes and advancing sowing from spring to autumn have been suggested as strategies for drought avoidance. However, Ascochyta blight (causal agent: Didymella rabiei (Kov.) v. Arx.) is a major limitation for chickpea winter cultivation. Most efforts to introgress resistance to the pathogen into Kabuli germplasm resulted in relatively late flowering germplasm. With the aim to explore the feasibility of combining earliness and resistance, RILs derived from a cross between a Kabuli cultivar and a Desi accession were evaluated under field conditions and genotyped with SSR markers. Three quantitative trait loci (QTLs) with significant effects on resistance were identified: two linked loci located on LG4 in epistatic interaction and a third locus on LG8. Two QTLs were detected for time to flowering: one in LG1 and another on LG2. When resistance and time to flowering were analyzed together, the significance of the resistance estimates obtained for the LG8 locus increased and the locus effect on days to flowering, previously undetected, was significantly different from zero. The identification of a locus linked both to resistance and time to flowering may account for the correlation observed between these traits in this and other breeding attempts.     

Syntenic quantitative trait loci and genomic divergence for Sclerotinia resistance and flowering time in Brassica napus

Oilseed rape (Brassica napus) is an allotetraploid with two subgenomes descended from a common ancestor. Accordingly, its genome contains syntenic regions with many duplicate genes, some of which may have retained their original functions, whereas others may have diverged. Here, we mapped quantitative trait loci (QTL) for stem rot resistance (SRR), a disease caused by the fungus Sclerotinia sclerotiorum, and flowering time (FT) in a recombinant inbred line population. The population was genotyped using B. napus 60K single nucleotide polymorphism arrays and phenotyped in six (FT) and nine (SSR) experimental conditions or environments. In total, we detected 30 SRR QTL and 22 FT QTL and show that some of the major QTL associated with these two traits were co-localized, suggesting a genetic linkage between them. Two SRR QTL on chromosome A2 and two on chromosome C2 were shown to be syntenic, suggesting the functional conservation of these regions. We used the syntenic properties of the genomic regions to exclude genes for selection candidates responsible for QTL-associated traits. For example, 152 of the 185 genes could be excluded from a syntenic A2-C2 region. These findings will help to elucidate polyploid genomics in future studies, in addition to providing useful information for B. napus breeding programs.     

Fine mapping of quantitative trait loci for acid phosphatase activity in maize leaf under low phosphorus stress

Acid phosphatase (APase) is very important in phosphorus (P) scavenging and remobilization in plants. The aim of this study was the fine mapping of quantitative trait loci (QTL) for APase activity (APA) in maize (Zea mays L.) leaf. The QTL for APA were studied in the F2:3 population derived from the cross 082 × Ye107 under low P stress in two sites. A significant difference in APA was found between 082 (P-efficient genotype) and Ye107 (P-deficient genotype). Each environment was analyzed to identify the QTL. Six QTL for APA were found, comprising two QTL at Beibei (BB) and four QTL at Hechuan (HC), China. A QTL denoted as AP9 showed a stable expression under different environments on chromosome 9, and explained 10.21 and 16.81 % of phenotypic variation at BB and HC, respectively. For the fine mapping of this QTL, seven individuals selected via marker-assisted selection in the BC3F1 population were used to produce the BC3F2 lines by selfing and to allow recombination within the region containing the target QTL. High-resolution genetic and physical maps were further constructed for the fine mapping of AP9 using 12 simple sequence repeat markers and the BC3F2 population consisting of 1,441 individuals. As a result, the location of AP9 was narrowed down to a 546-kb fragment on chromosome 9.     

Precision and high-resolution mapping of quantitative trait loci by use of recurrent selection,backcross or intercross schemes

Dissecting quantitative genetic variation into genes at the molecular level has been recognized as the greatest challenge facing geneticists in the twenty-first century. Tremendous efforts in the last two decades were invested to map a wide spectrum of quantitative genetic variation in nearly all important organisms onto their genome regions that may contain genes underlying the variation, but the candidate regions predicted so far are too coarse for accurate gene targeting. In this article, the recurrent selection and backcross (RSB) schemes were investigated theoretically and by simulation for their potential in mapping quantitative trait loci (QTL). In the RSB schemes, selection plays the role of maintaining the recipient genome in the vicinity of the QTL, which, at the same time, are rapidly narrowed down over multiple generations of backcrossing. With a high-density linkage map of DNA polymorphisms, the RSB approach has the potential of dissecting the complex genetic architecture of quantitative traits and enabling the underlying QTL to be mapped with the precision and resolution needed for their map-based cloning to be attempted. The factors affecting efficiency of the mapping method were investigated, suggesting guidelines under which experimental designs of the RSB schemes can be optimized. Comparison was made between the RSB schemes and the two popular QTL mapping methods, interval mapping and composite interval mapping, and showed that the scenario of genomic distribution of QTL that was unlocked by the RSB-based mapping method is qualitatively distinguished from those unlocked by the interval mapping-based methods.     

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

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 × NC250A and NC250A × 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. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genetic mapping of quantitative trait loci for resistance to Haemonchus contortus in sheep

This paper presents results from a mapping experiment to detect quantitative trait loci (QTL) for resistance to Haemonchus contortus infestation in merino sheep. The primary trait analysed was faecal worm egg count in response to artificial challenge at 6 months of age. In the first stage of the experiment, whole genome linkage analysis was used for broad-scale mapping. The animal resource used was a designed flock comprising 571 individuals from four half-sib families. The average marker spacing was about 20 cM. For the primary trait, 11 QTL (as chromosomal/family combinations) were significant at the 5% chromosome-wide level, with allelic substitution effects of between 0.19 and 0.38 phenotypic standard deviation units. In general, these QTL did not have a significant effect on faecal worm egg count recorded at 13 months of age. In the second stage of the experiment, three promising regions (located on chromosomes 1, 3 and 4) were fine-mapped. This involved typing more closely spaced markers on individuals from the designed flock as well as an additional 495 individuals selected from a related population with a deeper pedigree. Analysis was performed using a linkage disequilibrium–linkage approach, under additive, dominant and multiple QTL models. Of these, the multiple QTL model resulted in the most refined QTL positions, with resolutions of <10 cM achieved for two regions. Because of the moderate size of effect of the QTL, and the apparent age and/or immune status specificity of the QTL, it is suggested that a panel of QTL will be required for significant genetic gains to be achieved within industry via marker-assisted selection.     

Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize.

Recombinant inbred (RI) lines offer several advantages for detecting quantitative trait loci (QTLs), including increased precision of trait measurements, power for detection of additive effects, and resolution of linked QTLs. This study was conducted to detect and characterize QTLs in maize for flowering and plant height and to compare QTL detection in an early (F2:3) generation of the same population. One hundred and eighty-six RIs from a cross between inbred lines Mo17 and H99 were evaluated in a replicated field experiment and analyzed at 101 loci detected by restriction fragment length polymorphisms. QTLs were identified by single-factor analysis of variance. A total of 59 QTLs were detected for plant height, ear height, top height, anthesis, silk emergence, and anthesis to silk interval. Individual QTLs explained 2.2-15.4% of trait variation, and multiple models including all QTLs detected for a trait explained up to 52.5% of the phenotypic variation. Comparison of QTLs detected with 150 F2:3 lines from the same population indicated that 16 (70%) of the 23 F2:3 QTLs were also observed in the F6:7 generation. Parental effects were consistent across generations. At 14 of the 16 QTLs detected in both generations, genetic effects were smaller in the F6:7. Also, some QTLs detected in the F2:3 were resolved into multiple linked QTLs in the F6:7, indicating the additional power of RI populations for mapping, with important implications for marker-assisted selection as well as map-based cloning of QTLs. Key words : Zea mays, RFLP, plant breeding, genetics, recombination.     

A general mixture model for mapping quantitative trait loci by using molecular markers

Summary In a segregating population a quantitative trait may be considered to follow a mixture of (normal) distributions, the mixing proportions being based on Mendelian segregation rules. A general and flexible mixture model is proposed for mapping quantitative trait loci (QTLs) by using molecular markers. A method is discribed to fit the model to data. The model makes it possible to (1) analyse non-normally distributed traits such as lifetimes, counts or percentages in addition to normally distributed traits, (2) reduce environmental variation by taking into account the effects of experimental design factors and interaction between genotype and environment, (3) reduce genotypic variation by taking into account the effects of two or more QTLs simultaneously, (4) carry out a (combined) analysis of different population types, (5) estimate recombination frequencies between markers or use known marker distances, (6) cope with missing marker observations, (7) use markers as covariables in detection and mapping of QTLs, and finally to (8) implement the mapping in standard statistical packages.     

Interval mapping of genes for quantitative resistance of maize to Setosphaeria turcica,cause of northern leaf blight,in a tropical environment

Quantitative trait loci (QTL) involved in the resistance of maize to Setosphaeria turcica, the causal agent of northern leaf blight, were located by interval mapping analysis of 121 F_2:3 lines derived from a cross between Mo17 (moderately resistant) and B52 (susceptible). A linkage map spanning 112 RFLP loci with 15 cM mean interval length was constructed, based on marker data recorded in a previous study. Field tests with artificial inoculation were conducted at three sites in tropical mid- to high-altitude regions of Kenya, East Africa. Host-plant response was measured in terms of incubation period, disease severity (five scoring dates), and the area under the disease progress curve (AUDPC). Heritability of all traits was high (around 0.75). QTL associated with the incubation period were located on chromosomes 2S and 8L. For disease severity and AUDPC, significant QTL were detected in the putative centromeric region of chromosome 1 and on 2S, 3L, 5S, 6L, 7L, 8L and 9S. On 2S the same marker interval which carried a gene enhancing latent period was also associated with reduced disease severity of juvenile plants. QTL on chromosomes 3L, 5S, 7L and 8L were significant across environments but all other QTL were affected by a large genotype x environment interaction. Partially dominant gene action for resistance as well as for susceptibility was prevailing. Single QTL explained 10 to 38% of the phenotypic variation of the traits. All but the QTL on chromosomes 1, 6 and 9 were contributed by the resistant parent Mo17. On chromosome 8L a QTL mapped to the same region as the major race-specific gene Ht2, supporting the hypothesis that some qualitative and quantitative resistance genes may be allelic.Abbreviations AUDPC area under the disease progress curve - CIMMYT International Maize and Wheat Improvement Center - KARI Kenya Agricultural Research Institute - NCLB northern corn leaf blight - QTL quantitative trait locus/loci     

Genome-wide association mapping of flowering time and northern corn leaf blight (Setosphaeria turcica) resistance in a vast commercial maize germplasm set

ABSTRACT: BACKGROUND: Setosphaeria turcica is a fungal pathogen that causes northern corn leaf blight (NCLB) which is a serious foliar disease in maize. In order to unravel the genetic architecture of the resistance against this disease, a vast association mapping panel comprising 1487 European maize inbred lines was used to (i) identify chromosomal regions affecting flowering time (FT) and northern corn leaf blight (NCLB) resistance, (ii) examine the epistatic interactions of the identified chromosomal regions with the genetic background on an individual molecular marker basis, and (iii) dissect the correlation between NCLB resistance and FT. RESULTS: The single marker analyses performed for 8 244 single nucleotide polymorphism (SNP) markers revealed seven, four, and four SNP markers significantly (alpha D 0.05, amplicon wise Bonferroni correction) associated with FT, NCLB, and NCLB resistance corrected for FT, respectively. These markers explained individually between 0.36 and 14.29% of the genetic variance of the corresponding trait. DISCUSSION: The very well interpretable pattern of SNP associations observed for FT suggested that data from applied plant breeding programs can be used to dissect polygenic traits. This in turn indicates that the associations identified for NCLB resistance might be successfully used in marker-assisted selection programs. Furthermore, the associated genes are also of interest for further research concerning the mechanism of resistance to NCLB and plant diseases in general, because some of the associated genes have not been mentioned in this context so far.     

Molecular mapping of quantitative trait loci for three kernel-related traits in maize using a double haploid population

Kernel size and kernel weight are important factors possibly involved in the determination of grain yield in maize, so identifying the genetic basis of kernel-related traits provides insights into the breeding of high-yield maize varieties. Kernel length (KL), kernel width (KW) and hundred kernel weight (HKW) were evaluated in three various planting conditions for the 240 field-grown double haploid (DH) lines derived from the single-cross hybrid Xianyu335. Variations in KL, KW and HKW were observed among DH lines, and all three traits showed a broad sense heritability of 76%. A total of 964 single nucleotide polymorphisms (SNPs) from the MaizeSNP3072 chip was utilised to create a high-density genetic map of 1546.4 cM and to identify quantitative trait loci (QTLs). Using composite interval mapping, a total of five, seven and five QTLs have been mapped for KL, KW and HKW, respectively. qkl1-2 and qkl4-1 explained 17.8% and 14.2% of the phenotypic variation in KL, respectively, and the other three QTLs contributed 3.2–4.0%. The phenotypic variation explained (PVE) of seven QTLs responsible for KW ranged from 3.3 to 9.5%. Three QTLs for HKW, qhkw1, qhkw5 and qhkw10 each explained more than 10% of the phenotypic variation, and qhkw4 and qhkw9 accounted for 3.0% and 6.0%, respectively. Due to their detection in multiple planting environments, the loci mapped here appear to be potential targets for the improvement of maize grain yield.     

Detection and verification of quantitative trait loci for resistance to Fusarium ear rot in maize

Fusarium ear rot caused by Fusarium verticillioides is a prevalent disease in maize which can severely reduce grain yields and quality. Identification of stable quantitative trait loci (QTL) for resistance to Fusarium ear rot is a basic prerequisite for understanding the genetic mechanism of resistance and for the use of marker-assisted selection. In this study, two hundred and ten F _2:3 families were developed from a cross between resistant inbred line BT-1 and susceptible inbred line Xi502, and were genotyped with 178 simple sequence repeat markers. The resistance of each line was evaluated in two environments by artificial inoculation using the nail-punch method. The resistance QTL were detected using the composite interval mapping method. Three QTL were detected on chromosomes 4, 5 and 10. Of them, the QTL on chromosome 4 (bin 4.05/06) had the largest resistance to Fusarium ear rot, and could explain 17.95?% of the phenotypic variation. For further verification of the QTL effect, we developed near-isogenic lines (NILs) carrying the QTL region on chromosome 4 using parental line Xi502 as the recurrent parent. In the NIL background, this QTL can increase the resistance by 33.7?C35.2?% if the resistance region is homozygous, and by 17.8?C26.5?% if the resistance region contains the heterozygous allele. The stable and significant resistance effect of the QTL on chromosome 4 lays the foundation for further marker-assisted selection and map-based cloning in maize.     

Mapping quantitative trait loci (QTLs) for resistance to Gibberella zeae infection in maize

The basic prerequisite for an efficient breeding program to improve levels of resistance to pathogens in plants is the identification of genes controlling the resistance character. If the response to pathogens is under the control of a multilocus system, the utilization of molecular markers becomes essential. Stalk and ear rot caused by Gibberella zeae is a widespread disease of corn: resistance to G. zeae is quantitatively inherited. Our experimental approach to understanding the genetic basis of resistance to Gibberella is to estimate the genetic linkage between available molecular markers and the character, measured as the amount of diseased tissue 40 days after inoculation of a suspension of Fusarium graminearum, the conidial form of G. zeae, into the first stalk internode. Sensitive and resistant parental inbreds were crossed to obtain F₁ and F₂ populations: the analysis of the segregation of 95 RFLP (restriction fragment length polymorphism) clones and 10 RAPD (random amplified polymorphic DNA) markers was performed on a population of 150 F₂ individuals. Analysis of resistance was performed on the F₃ families obtained by selfing the F₂ plants. Quantitative trait loci (QTL) detection was based either on analysis of regression coefficients between family mean value and allele values in the F₂ population, or by means of interval mapping, using MAPMAKER-QTL. A linkage map of maize was obtained, in which four to five genomic regions are shown to carry factors involved in the resistance to G. zeae.     

Mapping of quantitative trait loci for field resistance to Fusarium head blight in an European winter wheat

Fusarium head blight (FHB) caused by Fusarium culmorum is an economically important disease of wheat that may cause serious yield and quality losses under favorable climate conditions. The development of disease-resistant cultivars is the most effective control strategy. Worldwide, there is heavy reliance on the resistance pool originating from Asian wheats, but excellent field resistance has also been observed among European winter wheats. The objective of this study was to map and characterize quantitative traits loci (QTL) of resistance to FHB among European winter wheats. A population of 194 recombinant inbred lines (RILs) was genotyped from a cross between two winter wheats Renan (resistant)/Récital (susceptible) with microsatellites, AFLP and RFLP markers. RILs were assessed under field conditions For 3 years in one location. Nine QTLs were detected, and together they explained 30-45% of the variance, depending on the year. Three of the QTLs were stable over the 3 years. One stable QTL, QFhs.inra.2b, was mapped to chromosome 2B and two QTLs QFhs.inra.5a2 and QFhs.inra5a3, to chromosome 5A; each of these QTLs explained 6.9-18.6% of the variance. Other QTLs were identified on chromosome 2A, 3A, 3B, 5D, and 6D, but these had a smaller effect on FHB resistance. One of the two QTLs on chromosome 5A was linked to gene B1 controlling the presence of awns. Overlapping QTLs for FHB resistance were those for plant height or/and flowering time. Our results confirm that wheat chromosomes 2A, 3A, 3B, and 5A carry FHB resistance genes, and new resistance factors were identified on chromosome arms 2BS and 5AL. Markers flanking these QTLs should be useful tools for combining the resistance to FHB of Asian and European wheats to increase the resistance level of cultivars.