Identification of novel QTL contributing resistance to aflatoxin accumulation in maize

The toxic metabolic product aflatoxin produced by the opportunistic fungus Aspergillus flavus (Link:Fr) in maize (Zea mays L.) can cause disease and economic harm when levels exceed very minute quantities. The selection of resistant germplasm has great potential to reduce the problem, but the highly quantitative nature of the trait makes this a difficult endeavor. The identification of aflatoxin accumulation resistance quantitative trait loci (QTL) from resistant donor lines and the discovery of linked markers could speed this task. To identify marker–trait associations for marker-assisted breeding, a genetic mapping population of F_2:3 families was developed from Mp715, a maize inbred line resistant to aflatoxin accumulation, and T173, a susceptible, southern-adapted maize inbred line. QTL, some with large phenotypic effects, were identified in multiple years on chromosomes 1, 3, 5, and 10, and smaller QTL identified in only 1 year were found on chromosomes 4 and 9. The phenotypic effect of each QTL ranged from 2.7 to 18.5%, and models created with multiple QTL could explain up to 45.7% of the phenotypic variation across years, indicating that the variation associated with the trait can be manipulated using molecular markers.     

Mapping QTL for Grain Yield and Plant Traits in a Tropical Maize Population

The vast majority of reported QTL mapping for maize (Zea mays L.) traits are from temperate germplasm and, also, QTL by environment interaction (QTL × E) has not been thoroughly evaluated and analyzed in most of these papers. The maize growing areas in tropical regions are more prone to environmental variability than in temperate areas, and, therefore, genotype by environment interaction is of great concern for maize breeders. The objectives of this study were to map QTL and to test their interaction with environments for several traits in a tropical maize population. Two-hundred and fifty-six F_2:3 families evaluated in five environments, a genetic map with 139 microsatellites markers, and the multiple-environment joint analysis (mCIM) were used to map QTL and to test QTL × E interaction. Sixteen, eight, six, six, nine, and two QTL were mapped for grain yield, ears per plant, plant lodging, plant height, ear height, and number of leaves, respectively. Most of these QTL interacted significantly with environments, most of them displayed overdominance for all traits, and genetic correlated traits had a low number of QTL mapped in the same genomic regions. Few of the QTL mapped had already been reported in both temperate and tropical germplasm. The low number of stable QTL across environments imposes additional challenges to design marker-assisted selection in tropical areas, unless the breeding programs could be directed towards specific target areas.     

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.     

Construction of high-density linkage map and identification of QTLs for resistance to sorghum downy mildew in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Sorghum downy mildew (SDM), caused by obligate biotrophic fungi Peronosclerospora sorghi, is an economically important disease of maize. The genetics of resistance was reported to be polygenic thereby necessitating identification of QTLs for resistance to SDM to initiate effective marker-assisted selection programs. During post-rainy and winter season of 2012, 645 F_2:3 progeny families from the cross CML153 (susceptible) × CML226 (resistant) were screened for their reaction to SDM. Characterization of QTLs affecting resistance to SDM was undertaken using the genetic linkage map with 319 polymorphic SSR and SNP marker loci and the phenotypic data of F_2:3 families. Three QTLs conferring resistance to SDM were consistently identified on chromosomes 2, 3 and 6 in both seasons. The resistant parent CML226 contributed all the QTL alleles conferring resistance to SDM. The major QTL located on chromosome 2 explained 38.68% of total phenotypic variation in the combined analysis with a LOD score of 9.12. All the three QTL showed partially dominant gene effects in combined analysis. The detection of more than one QTL supports the hypothesis that quantitative genes control resistance to P. sorghi. The generation was advanced to F₆ using markers linked to major QTLs on chromosomes 2 and 3 to derive 33 SDM resistant maize inbred lines.     

Identification of quantitative trait loci controlling resistance to maize chlorotic dwarf virus

Ineffective screening methods and low levels of disease resistance have hampered genetic analysis of maize (Zea mays L.) resistance to disease caused by maize chlorotic dwarf virus (MCDV). Progeny from a cross between the highly resistant maize inbred line Oh1VI and the susceptible inbred line Va35 were evaluated for MCDV symptoms after multiple virus inoculations, using the viral vector Graminella nigrifrons. Symptom severity scores from three rating dates were used to calculate area under the disease progress curve (AUDPC) scores for vein banding, leaf twist and tear, and whorl chlorosis. AUDPC scores for the F₂ population indicated that MCDV resistance was quantitatively inherited. Genotypic and phenotypic analyses of 314 F₂ individuals were compared using composite interval mapping (CIM) and analysis of variance. CIM identified two major quantitative trait loci (QTL) on chromosomes 3 and 10 and two minor QTL on chromosomes 4 and 6. Resistance was additive, with alleles from Oh1VI at the loci on chromosomes 3 and 10 contributing equally to resistance.     

Genetic analysis of resistance to six virus diseases in a multiple virus-resistant maize inbred line

Key message

Novel and previously known resistance loci for six phylogenetically diverse viruses were tightly clustered on chromosomes 2, 3, 6 and 10 in the multiply virus-resistant maize inbred line, Oh1VI.

Abstract

Virus diseases in maize can cause severe yield reductions that threaten crop production and food supplies in some regions of the world. Genetic resistance to different viruses has been characterized in maize populations in diverse environments using different screening techniques, and resistance loci have been mapped to all maize chromosomes. The maize inbred line, Oh1VI, is resistant to at least ten viruses, including viruses in five different families. To determine the genes and inheritance mechanisms responsible for the multiple virus resistance in this line, F₁ hybrids, F₂ progeny and a recombinant inbred line (RIL) population derived from a cross of Oh1VI and the virus-susceptible inbred line Oh28 were evaluated. Progeny were screened for their responses to Maize dwarf mosaic virus, Sugarcane mosaic virus, Wheat streak mosaic virus, Maize chlorotic dwarf virus, Maize fine streak virus, and Maize mosaic virus. Depending on the virus, dominant, recessive, or additive gene effects were responsible for the resistance observed in F₁ plants. One to three gene models explained the observed segregation of resistance in the F₂ generation for all six viruses. Composite interval mapping in the RIL population identified 17 resistance QTLs associated with the six viruses. Of these, 15 were clustered in specific regions of chr. 2, 3, 6, and 10. It is unknown whether these QTL clusters contain single or multiple virus resistance genes, but the coupling phase linkage of genes conferring resistance to multiple virus diseases in this population could facilitate breeding efforts to develop multi-virus resistant crops.     

Quantitative trait loci mapping of leaf angle and leaf orientation value in maize (Zea mays L.)

A major limiting factor for high productivity of maize (Zea mays L.) in dense planting is light penetration through the canopy. Plant architecture with a narrower leaf angle (LA) and an optimum leaf orientation value (LOV) is desirable to increase light capture for photosynthesis and production per unit area. However, the genetic control of the plant architecture traits remains poorly understood in maize. In this study, QTL for LA, LOV, and related traits were mapped using a set of 229 F_2:3 families derived from the cross between compact and expanded inbred lines, evaluated in three environments. Twenty-five QTL were detected in total. Three of the QTL explained 37.4% and five of the QTL explained 53.9% of the phenotypic variance for LA and LOV, respectively. Two key genome regions controlling leaf angle and leaf orientation were identified. qLA1 and qLOV1 at nearest marker umc2226 on chromosome 1.02 accounted for 20.4 and 23.2% of the phenotypic variance, respectively; qLA5 and qLOV5 at nearest bnlg1287 on chromosome 5 accounted for 9.7 and 9.8% of the phenotypic variance, respectively. These QTL could provide useful information for marker-assisted selection in improving performance of plant architecture with regard to leaf angle and orientation.     

Mapping Fusarium wilt race 1 resistance genes in cotton by inheritance,QTL and sequencing composition

Knowledge of the inheritance of disease resistance and genomic regions housing resistance (R) genes is essential to prevent expanding pathogen threats such as Fusarium wilt [Fusarium oxysporum f.sp. vasinfectum (FOV) Atk. Sny & Hans] in cotton (Gossypium spp.). We conducted a comprehensive study combining conventional inheritance, genetic and quantitative trait loci (QTL) mapping, QTL marker-sequence composition, and genome sequencing to examine the distribution, structure and organization of disease R genes to race 1 of FOV in the cotton genome. Molecular markers were applied to F₂ and recombinant inbred line (RIL) interspecific mapping populations from the crosses Pima-S7 (G. barbadense L.) × ‘Acala NemX’ (G. hirsutum L.) and Upland TM-1 (G. hirsutum) × Pima 3-79 (G. barbadense), respectively. Three greenhouse tests and one field test were used to obtain sequential estimates of severity index (DSI) of leaves, and vascular stem and root staining (VRS). A single resistance gene model was observed for the F₂ population based on inheritance of phenotypes. However, additional inheritance analyses and QTL mapping indicated gene interactions and inheritance from nine cotton chromosomes, with major QTLs detected on five chromosomes [Fov1-C06, Fov1-C08, (Fov1-C11 ₁ and Fov1-C11 ₂₎ , Fov1-C16 and Fov1-C19 loci], explaining 8–31% of the DSI or VRS variation. The Fov1-C16 QTL locus identified in the F₂ and in the RIL populations had a significant role in conferring FOV race 1 resistance in different cotton backgrounds. Identified molecular markers may have important potential for breeding effective FOV race 1 resistance into elite cultivars by marker-assisted selection. Reconciliation between genetic and physical mapping of gene annotations from marker-DNA and new DNA sequences of BAC clones tagged with the resistance-associated QTLs revealed defenses genes induced upon pathogen infection and gene regions rich in disease-response elements, respectively. These offer candidate gene targets for Fusarium wilt resistance response in cotton and other host plants.     

Mapping quantitative trait loci using naturally occurring genetic variance among commercial inbred lines of maize (Zea mays L.)

Many commercial inbred lines are available in crops. A large amount of genetic variation is preserved among these lines. The genealogical history of the inbred lines is usually well documented. However, quantitative trait loci (QTL) responsible for the genetic variances among the lines are largely unexplored due to lack of statistical methods. In this study, we show that the pedigree information of the lines along with the trait values and marker information can be used to map QTL without the need of further crossing experiments. We develop a Monte Carlo method to estimate locus-specific identity-by-descent (IBD) matrices. These IBD matrices are further incorporated into a mixed-model equation for variance component analysis. QTL variance is estimated and tested at every putative position of the genome. The actual QTL are detected by scanning the entire genome. Applying this new method to a well-documented pedigree of maize (Zea mays L.) that consists of 404 inbred lines, we mapped eight QTL for the maize male flowering trait, growing degree day heat units to pollen shedding (GDUSHD). These detected QTL contributed >80% of the variance observed among the inbred lines. The QTL were then used to evaluate all the inbred lines using the best linear unbiased prediction (BLUP) technique. Superior lines were selected according to the estimated QTL allelic values, a technique called marker-assisted selection (MAS). The MAS procedure implemented via BLUP may be routinely used by breeders to select superior lines and line combinations for development of new cultivars.     

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     

QTL mapping of <Emphasis Type="Italic">Sclerotinia</Emphasis> midstalk-rot resistance in sunflower

In many sunflower-growing regions of the world, Sclerotinia sclerotiorum (Lib.) de Bary is the major disease of sunflower (Helianthus annuus L.). In this study, we mapped and characterized quantitative trait loci (QTL) involved in resistance to S. sclerotiorum midstalk rot and two morphological traits. A total of 351 F₃ families developed from a cross between a resistant inbred line from the germplasm pool NDBLOS and the susceptible line CM625 were assayed for their parental F₂ genotype at 117 codominant simple sequence repeat markers. Disease resistance of the F₃ families was screened under artificial infection in field experiments across two sowing times in 1999. For the three resistance traits (leaf lesion, stem lesion, and speed of fungal growth) and the two morphological traits, genotypic variances were highly significant. Heritabilities were moderate to high (h²=0.55–0.89). Genotypic correlations between resistance traits were highly significant (P<0.01) but moderate. QTL were detected for all three resistance traits, but estimated effects at most QTL were small. Simultaneously, they explained between 24.4% and 33.7% of the genotypic variance for resistance against S. sclerotiorum. Five of the 15 genomic regions carrying a QTL for either of the three resistance traits also carried a QTL for one of the two morphological traits. The prospects of marker-assisted selection (MAS) for resistance to S. sclerotiorum are limited due to the complex genetic architecture of the trait. MAS can be superior to classical phenotypic selection only with low marker costs and fast selection cycles.     

The inheritance of resistance to Verticillium wilt caused by race 1 isolates of <Emphasis Type="Italic">Verticillium dahliae</Emphasis> in the lettuce cultivar La Brillante

Verticillium wilt of lettuce caused by Verticillium dahliae can cause severe economic damage to lettuce producers. Complete resistance to race 1 isolates is available in Lactuca sativa cultivar (cv.) La Brillante and understanding the genetic basis of this resistance will aid development of new resistant cultivars. F₁ and F₂ families from crosses between La Brillante and three iceberg cultivars as well as a recombinant inbred line population derived from L. sativa cv. Salinas 88 × La Brillante were evaluated for disease incidence and disease severity in replicated greenhouse and field experiments. One hundred and six molecular markers were used to generate a genetic map from Salinas 88 × La Brillante and for detection of quantitative trait loci. Segregation was consistent with a single dominant gene of major effect which we are naming Verticillium resistance 1 (Vr1). The gene described large portions of the phenotypic variance (R ² = 0.49–0.68) and was mapped to linkage group 9 coincident with an expressed sequence tag marker (QGD8I16.yg.ab1) that has sequence similarity with the Ve gene that confers resistance to V. dahliae race 1 in tomato. The simple inheritance of resistance indicates that breeding procedures designed for single genes will be applicable for developing resistant cultivars. QGD8I16.yg.ab1 is a good candidate for functional analysis and development of markers suitable for marker-assisted selection.     

Identification of a major quantitative trait locus for resistance to maize rough dwarf virus in a Chinese maize inbred line X178 using a linkage map based on 514 gene-derived single nucleotide polymorphisms

Maize rough dwarf disease (MRDD) is a worldwide viral disease and causes significant yield losses in maize (Zea mays L.) production. In this study, we mapped and characterized quantitative trait loci (QTL) conferring resistance to MRDD using 89 F8 recombinant inbred lines derived from a cross between X178 (resistant parent) and B73 (susceptible). The population was evaluated for MRDD resistance in Baoding, Hebei Province, China (a hot spot of MRDD incidence) under natural infection in 2008 and 2009 and artificial inoculation in 2010. Genotypic variances for disease severity index (DSI) were highly significant in the population. Heritability estimates for DSI evaluation were 0.472 and 0.467 in 2008 and 2009, respectively. The linkage map was constructed using 514 gene-derived single nucleotide polymorphisms (SNPs) and 72 simple sequence repeat markers, spanning a genetic distance of 1,059.72?cM with an average interval of 1.8?cM between adjacent markers. Multiple-QTL model mapping detected a major QTL for MRDD resistance on chromosome 8, explaining 24.6?C37.3% of the phenotypic variation across three environments. In 2010, an additional QTL was detected on chromosome 10, explaining 15.8% of the phenotypic variation. The major QTL on chromosome 8 and the SNP markers (SNP31, SNP548, and SNP284) co-located with the QTL peak have potential for further functional genomic analysis and use in molecular marker-assisted selection for MRDD resistance in maize.     

QTL mapping for bacterial wilt resistance in peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

Bacterial wilt (BW) caused by Ralstonia solanacearum is a serious, global, disease of peanut (Arachis hypogaea L.), but it is especially destructive in China. Identification of DNA markers linked to the resistance to this disease will help peanut breeders efficiently develop resistant cultivars through molecular breeding. A F₂ population, from a cross between disease-resistant and disease-susceptible cultivars, was used to detect quantitative trait loci (QTL) associated with the resistance to this disease in the cultivated peanut. Genome-wide SNPs were identified from restriction-site-associated DNA sequencing tags using next-generation DNA sequencing technology. SNPs linked to disease resistance were determined in two bulks of 30 resistant and 30 susceptible plants along with two parental plants using bulk segregant analysis. Polymorphic SSR and SNP markers were utilized for construction of a linkage map and for performing the QTL analysis, and a moderately dense linkage map was constructed in the F₂ population. Two QTL (qBW-1 and qBW-2) detected for resistance to BW disease were located in the linkage groups LG1 and LG10 and account for 21 and 12 % of the bacterial wilt phenotypic variance. To confirm these QTL, the F₈ RIL population with 223 plants was utilized for genotyping and phenotyping plants by year and location as compared to the F₂ population. The QTL qBW-1 was consistent in the location of LG1 in the F₈ population though the QTL qBW-2 could not be clarified due to fewer markers used and mapped in LG10. The QTL qBW-1, including four linked SNP markers and one SSR marker within 14.4-cM interval in the F₈, was closely related to a disease resistance gene homolog and was considered as a candidate gene for resistance to BW. QTL identified in this study would be useful to conduct marker-assisted selection and may permit cloning of resistance genes. Our study shows that bulk segregant analysis of genome-wide SNPs is a useful approach to expedite the identification of genetic markers linked to disease resistance traits in the allotetraploidy species peanut.     

Detection and integration of quantitative trait loci for grain yield components and oil content in two connected recombinant inbred line populations of high-oil maize

Improvement in grain yield is an important objective in high-oil maize breeding. In this study, one high-oil maize inbred was crossed with two normal maize inbreds to produce two connected recombinant inbred line (RIL) populations with 282 and 263 F_7:8 families, respectively. The field experiments were conducted under four environments, and eight grain yield components and grain oil content were evaluated. Two genetic linkage maps were constructed using 216 and 208 polymorphic SSR markers. Quantitative trait loci (QTL) were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL in both populations. A total of 199 QTL were detected, 122 in population 1 and 87 in population 2. Seven, 11 and 19 QTL showed consistency across five environments, across two RIL populations and with respective F_2:3 generations, respectively. 183 QTL were integrated in 28 meta-QTL (mQTL). QTL with contributions over 15% were consistently detected in 3–4 cases and integrated in mQTL. Each mQTL included 3–19 QTL related to 1–4 traits, reflecting remarkable QTL co-location for grain yield components and oil content. Further research and marker-assisted selection (MAS) should be concentrated on 37 consistent QTL and four genetic regions of mQTL with more than 10 QTL at bins 3.04–3.05, 7.02, 8.04–8.05 and 9.04–9.05. Near-isogenic lines for 100-grain-weight QTL at bin 7.02–7.03, for ear-length QTL at bin 7.02–7.03 and for rows-per-ear QTL at bin 3.08 are now in construction using MAS. Co-located candidate genes could facilitate the identification of candidate genes for grain yield in maize.     

QTL involved in the partial restoration of male fertility of C-type cytoplasmic male sterility in maize

Partial restoration of male fertility limits the use of C-type cytoplasmic male sterility (C-CMS) for the production of hybrid seeds in maize. Nevertheless, the genetic basis of the trait is still unknown. Therefore, the aim to this study was to identify genomic regions that govern partial restoration by means of a QTL analysis carried out in an F₂ population (n = 180). This population was derived from the Corn Belt inbred lines B37C and K55. F₂BC₁ progenies were phenotyped at three locations in Switzerland. Male fertility was rated according to the quality and number of anthers as well as the anthesis-silking interval. A weak effect of environment on the expression of partial restoration was reflected by high heritabilities of all fertility-related traits. Partial restoration was inherited like an oligogenic trait. Three major QTL regions were found consistently across environments in the chromosomal bins 2.09, 3.06 and 7.03. Therefore, a marker-assisted counter-selection of partial restoration is promising. Minor QTL regions were found on chromosomes 3, 4, 5, 6 and 8. A combination of partial restorer alleles at different QTL can lead to full restoration of fertility. The maternal parent was clearly involved in the partial restoration, because the restorer alleles at QTL in bins 2.09, 6.04 and 7.03 originated from B37. The three major QTL regions collocated with other restorer genes of maize, a phenomenon, which seems to be typical for restorer genes. Therefore, a study of the clusters of restorer genes in maize could lead to a better understanding of their evolution and function. In this respect, the long arm of chromosome 2 is particularly interesting, because it harbors restorer genes for the three major CMS systems (C, T and S) of maize.     

Development of SRAP, SRAP-RGA, RAPD and SCAR markers linked with a Fusarium wilt resistance gene in eggplant

Fusarium wilt (Fusarium oxysporum Schlecht. f. sp. melongenae) is a vascular disease of eggplant (Solanum melongena L.). The objectives of this work were (1) to confirm the monogenic inheritance of fusarium wilt resistance in eggplant, (2) to identify molecular markers linked to this resistance, and (3) to develop SCAR markers from most informative markers. We report the tagging of the gene for resistance to fusarium wilt (FOM) in eggplant using SRAP, RGA, SRAP-RGA and RAPD markers. Analysis of segregation data confirmed the monogenic inheritance of resistance. DNA from F₂ and BC₁ populations of eggplant segregating for fusarium wilt resistance was screened with 2,316 primer combinations to detect polymorphism. Three markers were linked within 2.6 cM of the gene. The codominant SRAP marker Me8/Em5 and dominant SRAP-RGA marker Em12/GLPL2 were tightly linked to each other and mapped 1.2 cM from the resistance gene, whereas RAPD marker H12 mapped 2.6 cM from the gene and on the same side as the other two markers. The SRAP marker was converted into two dominant SCAR markers that were confirmed to be linked to the resistance gene in the F_2, BC₁ and F₂ of BC₃ generations of the same cross. These markers provide a starting point for mapping the eggplant FOM resistance gene in eggplant and for exploring the synteny between solanaceous crops for fusarium wilt resistance genes. The SCAR markers will be useful for identifying fusarium wilt-resistant genotypes in marker-assisted selection breeding programs using segregating progenies of the resistant eggplant progenitor used in this study.     

Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length

Deep-seeding tolerant seeds can emerge from deep soil where the moisture is suitable for seed germination. Breeding deep-seeding tolerant cultivars is becoming increasingly important in arid and semi-arid regions. To dissect the quantitative trait loci (QTL) controlling deep-seeding tolerance traits, we selected a tolerant maize inbred line 3681-4 and crossed it with the elite inbred line-X178 to generate an F₂ population and the derivative F_2:3 families. A molecular linkage map composed of 179 molecular markers was constructed, and 25 QTL were detected including 10 QTL for sowing at 10 cm depth and 15 QTL for sowing at 20 cm depth. The QTL analysis results confirmed that deep-seeding tolerance was mainly caused by mesocotyl elongation and also revealed considerable overlap among QTL for different traits. To confirm a major QTL on chromosome 10 for mesocotyl length measured at 20 cm depth, we selected and self-pollinated a BC₃F₂ plant that was heterozygous at the markers around the target QTL and homozygous at other QTL to generate a BC₃F₃ population. We found that this QTL explained more phenotypic variance in the BC₃F₃ population than that in the F₂ population, which laid the foundation for fine mapping and NIL (near-isogenic line) construction.     

Mapping quantitative trait loci for downy mildew resistance in pearl millet

Quantitative trait loci (QTLs) for resistance to pathogen populations of Scelerospora graminicola from India, Nigeria, Niger and Senegal were mapped using a resistant x susceptible pearl millet cross. An RFLP map constructed using F₂ plants was used to map QTLs for traits scored on F₄ families. QTL analysis was carried out using the interval mapping programme Mapmaker/QTL. Independent inheritance of resistance to pathogen populations from India, Senegal, and populations from Niger and Nigeria was shown. These results demonstrate the existence of differing virulences in the pathogen populations from within Africa and between Africa and India. QTLs of large effect, contributing towards a large porportion of the variation in resistance, were consistently detected in repeated screens. QTLs of smaller and more variable effect were also detected. There was no QTLs that were effective against all four pathogen populations, demonstrating that pathotype-specific resistance is a major mechanism of downy mildew resistance in this cross. For all but one of the QTLs, resistance was inherited from the resistant parent and the inheritance of resistance tended to be the result of dominance or over-dominance. The implications of this research for pearl millet breeding are discussed.     

Novel quantitative trait loci for broad-based resistance to soybean cyst nematode (Heterodera glycines Ichinohe) in soybean PI 567516C

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is the most destructive pest of soybean worldwide. Host plant resistance is an effective approach to control this pest. Plant introduction PI 567516C has been reported to be highly resistant to multiple-HG types of SCN. The objectives of this study were to identify and map novel quantitative trait loci (QTL) for SCN resistance to six HG types (also known as races 1, 2, 3, 5, 14, and LY1). Mapping was conducted using 250 F_2:3 progeny derived from a Magellan (susceptible) × PI 567516C (resistant) cross. F_6:7 recombinant inbred lines (RILs) developed from the F_2:3 progeny were employed to confirm the putative QTL identified. A total of 927 polymorphic simple sequence repeats (SSR) and single nucleotide polymorphism (SNP) markers were genotyped. Following the genetic linkage analysis, permutation tests and composite interval mapping were performed to identify and map QTL. Four QTL were associated with resistance to either multiple- or single-SCN HG types. Two QTL for resistance to multiple-SCN HG types were mapped to Chromosomes 10 and 18 and have not been reported in other SCN resistance sources. New QTL were confirmed by analysis of 250 F_6:7 RILs from the same population. SSR and SNP markers closely associated with these QTL can be useful for the development of near-isogenic lines for fine-mapping and positional cloning of candidate genes for SCN resistance.