Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize

QTL mapping for plant-height traits has not been hitherto reported in high-oil maize. A high-oil maize inbred ‘GY220’ was crossed with two dent maize inbreds (‘8984’ and ‘8622’) to generate two connected F_2:3 populations. Four plant-height traits were evaluated in 284 and 265 F_2:3 families. Single-trait QTL mapping and multiple-trait joint QTL mapping was used to detect QTLs for the traits and the genetic relationship between plant height (PH) and two other plant-height traits. A total of 28 QTLs and 12 pairs of digenic interactions among detected QTLs for four traits were detected in the two F_2:3 families. Only one marker was shared between the two populations. Joint analysis of PH with ear height (EH) and PH with top height (TH) detected 32 additional QTLs. Our results showed that QTL detection for PH was dependent on the genetic background of dent corn inbreds. Multiple-trait joint QTL analysis could increase the number of detected QTLs.     

Combined linkage and association mapping of flowering time in Sunflower (Helianthus annuus L.)

Association mapping and linkage mapping were used to identify quantitative trait loci (QTL) and/or causative mutations involved in the control of flowering time in cultivated sunflower Helianthus annuus. A panel of 384 inbred lines was phenotyped through testcrosses with two tester inbred lines across 15 location × year combinations. A recombinant inbred line (RIL) population comprising 273 lines was phenotyped both per se and through testcrosses with one or two testers in 16 location × year combinations. In the association mapping approach, kinship estimation using 5,923 single nucleotide polymorphisms was found to be the best covariate to correct for effects of panel structure. Linkage disequilibrium decay ranged from 0.08 to 0.26 cM for a threshold of 0.20, after correcting for structure effects, depending on the linkage group (LG) and the ancestry of inbred lines. A possible hitchhiking effect is hypothesized for LG10 and LG08. A total of 11 regions across 10 LGs were found to be associated with flowering time, and QTLs were mapped on 11 LGs in the RIL population. Whereas eight regions were demonstrated to be common between the two approaches, the linkage disequilibrium approach did not detect a documented QTL that was confirmed using the linkage mapping approach.     

Re-evaluation of the prospects of marker-assisted selection for improving insect resistance against Diatraea spp. in tropical maize by cross validation and independent validation

Cross validation (CV) and validation with an independent sample (IV) are new biometric approaches in QTL analysis to obtain unbiased estimates of QTL effects and the proportion of the genetic variance explained by the detected marker-QTL association (p). Our objective with these methods was to obtain a realistic picture on the prospects of marker-assisted selection (MAS) for improving the resistance of maize against the tropical stem borer species Diatraea grandiosella (SWCB) and Diatraea saccharalis (SCB). Published QTL mapping studies on leaf-damage ratings (LDR) with populations of F_2:3 lines and recombinant inbred lines (RIL) from crosses CML131×CML67 and Ki3× CML139 of tropical maize inbreds were re-analyzed with CV and IV. With CV, the reduction in p for LDR compared to p obtained with the whole data set varied between 41.0 and 79.6% in the populations of F_2:3 lines and between 30.1 and 65.2% in the two populations of RIL. Estimates of p for SCB LDR were similar for CV and IV. For SWCB LDR, p estimates obtained with IV were larger than those obtained with CV in CML131× CML67. The reverse was observed for Ki3×CML139. Under the assumption of identical selection intensities, and based on the re-estimates of p, MAS using only molecular marker information is less-efficient than conventional phenotypic selection (CPS). MAS combining marker and phenotypic data increases the relative efficiency by only 4% in comparison to CPS. In conclusion, MAS for improving SWCB and SCB LDR seems not-promising unless additional QTLs with proven large effects are available or the costs of marker assays are considerably reduced. Received: 7 December 2000 / Accepted: 5 February 2001     

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.     

Genetic mapping shows intraspecific variation and transgressive segregation for caterpillar‐induced aphid resistance in maize

Plants in nature have inducible defences that sometimes lead to targeted resistance against particular herbivores, but susceptibility to others. The metabolic diversity and genetic resources available for maize (Zea mays) make this a suitable system for a mechanistic study of within‐species variation in such plant‐mediated interactions between herbivores. Beet armyworms (Spodoptera exigua) and corn leaf aphids (Rhopalosiphum maidis) are two naturally occurring maize herbivores with different feeding habits. Whereas chewing herbivore‐induced methylation of 2,4‐dihydroxy‐7‐methoxy‐1,4‐benzoxazin‐3‐one glucoside (DIMBOA‐Glc) to form 2‐hydroxy‐4,7‐dimethoxy‐1,4‐benzoxazin‐3‐one glucoside (HDMBOA‐Glc) promotes caterpillar resistance, lower DIMBOA‐Glc levels favour aphid reproduction. Thus, caterpillar‐induced DIMBOA‐Glc methyltransferase activity in maize is predicted to promote aphid growth. To test this hypothesis, the impact of S. exigua feeding on R. maidis progeny production was assessed using seventeen genetically diverse maize inbred lines. Whereas aphid progeny production was increased by prior caterpillar feeding on lines B73, Ki11, Ki3 and Tx303, it decreased on lines Ky21, CML103, Mo18W and W22. Genetic mapping of this trait in a population of B73 × Ky21 recombinant inbred lines identified significant quantitative trait loci on maize chromosomes 1, 7 and 10. There is a transgressive segregation for aphid resistance, with the Ky21 alleles on chromosomes 1 and 7 and the B73 allele on chromosome 10 increasing aphid progeny production. The chromosome 1 QTL coincides with a cluster of three maize genes encoding benzoxazinoid O‐methyltransferases that convert DIMBOA‐Glc to HDMBOA‐Glc. Gene expression studies and benzoxazinoid measurements indicate that S. exigua ‐induced responses in this pathway differentially affect R. maidis resistance in B73 and Ky21.     

Identification of trait-improving quantitative trait loci for grain yield components from a dent corn inbred line in an advanced backcross BC<Subscript>2</Subscript>F<Subscript>2</Subscript> population and comparison with its F<Subscript>2:3</Subscript> population in popcorn

Normal maize germplasm could be used to improve the grain yield of popcorn inbreds. Our first objective was to locate genetic factors associated with trait variation and make first assessment on the efficiency of advanced backcross quantitative trait locus (AB-QTL) analysis for the identification and transfer of favorable QTL alleles for grain yield components from the dent corn inbred. A second objective was to compare the detection of QTL in the BC₂F₂ population with results using F_2:3 lines of the same parents. Two hundred and twenty selected BC₂F₂ families developed from a cross between Dan232 and an elite popcorn inbred N04 were evaluated for six grain yield components under two environments, and genotyped by means of 170 SSR markers. Using composite interval mapping (CIM), a total of 19 significant QTL were detected. Eighteen QTL had favorable alleles contributed by the dent corn parent Dan232. Sixteen of these favorable QTL alleles were not in the same or near marker intervals with QTL for popping characteristics. Six QTL were also detected in the F_2:3 population. Improved N04 could be developed from 210 and 208 families with higher grain weight per plant and/or 100-grain weight, respectively, and 35 families with the same or higher popping expansion volume than N04. In addition, near isogenic lines containing detected QTL (QTL-NILs) for grain weight per plant and/or 100-grain weight could be obtained from 12 families. Our study demonstrated that the AB-QTL method can be applied to identify and manipulate favorable QTL alleles from normal corn inbreds and combine QTL detection and popcorn breeding efficiently.     

Genetic relationships between resistance to stalk-tunneling by the European corn borer and cell-wall components in maize population B73×B52

The objective of this study was to assess the relationships among quantitative trait loci (QTL) detected for European corn borer (ECB) tunneling and cell-wall components (CWC) neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL) content in leaf-sheath and stalk tissues in a maize recombinant inbred line population derived from inbred lines B73 and B52. Most of the QTL for ECB resistance (10/13) were at QTL positions for one or more CWC. Of the 12 QTL for NDF and ADF in leaf-sheaths, five for each trait were at or near QTL for ECB tunneling. Four of these five QTL for NDF and ADF mapped to common locations. Four of the eight leaf-sheath ADL QTL were detected in the same genomic regions as ECB QTL. For stalk tissue, four regions contained common/overlapping QTL for ECB tunneling, NDF, and ADF. Six such regions were observed for stalk ADL and ECB tunneling. Seven of the ten QTL associated with both CWC and ECB tunneling contributed to the negative correlations observed between these traits, while relatively few QTL effects were positively correlated. This suggests that while CWC contribute to ECB resistance in this population, other mechanisms and other genes also are involved. Several QTL contributing to the negative correlations between ECB tunneling and CWC in the leaf-sheaths mapped to similar positions as QTL detected in tropical maize populations for resistance to leaf-feeding by Diatraea grandiosella Dyar and Diatraea saccharalis Fabricus. These regions may contain genes involved in the synthesis of cellulose, hemicellulose, and lignin in the leaf-blades and leaf-sheaths of maize.     

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum

Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole‐genome resequencing and genotyping by sequencing (GBS) were used to construct high‐density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum‐clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co‐located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS‐GWAS represent a powerful combined approach for the identification of loci controlling complex traits.     

Optimum allocation of resources for QTL detection using a nested association mapping strategy in maize

In quantitative trait locus (QTL) mapping studies, it is mandatory that the available financial resources are spent in such a way that the power for detection of QTL is maximized. The objective of this study was to optimize for three different fixed budgets the power of QTL detection 1 − β* in recombinant inbred line (RIL) populations derived from a nested design by varying (1) the genetic complexity of the trait, (2) the costs for developing, genotyping, and phenotyping RILs, (3) the total number of RILs, and (4) the number of environments and replications per environment used for phenotyping. Our computer simulations were based on empirical data of 653 single nucleotide polymorphism markers of 26 diverse maize inbred lines which were selected on the basis of 100 simple sequence repeat markers out of a worldwide sample of 260 maize inbreds to capture the maximum genetic diversity. For the standard scenario of costs, the optimum number of test environments (E _opt) ranged across the examined total budgets from 7 to 19 in the scenarios with 25 QTL. In comparison, the E _opt values observed for the scenarios with 50 and 100 QTL were slightly higher. Our finding of differences in 1 − β* estimates between experiments with optimally and sub-optimally allocated resources illustrated the potential to improve the power for QTL detection without increasing the total resources necessary for a QTL mapping experiment. Furthermore, the results of our study indicated that also in studies using the latest genomics tools to dissect quantitative traits, it is required to evaluate the individuals of the mapping population in a high number of environments with a high number of replications per environment.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

The Genetic Architecture of Maize Stalk Strength

Stalk strength is an important trait in maize (Zea mays L.). Strong stalks reduce lodging and maximize harvestable yield. Studies show rind penetrometer resistance (RPR), or the force required to pierce a stalk rind with a spike, is a valid approximation of strength. We measured RPR across 4,692 recombinant inbreds (RILs) comprising the maize nested association mapping (NAM) panel derived from crosses of diverse inbreds to the inbred, B73. An intermated B73×Mo17 family (IBM) of 196 RILs and a panel of 2,453 diverse inbreds from the North Central Regional Plant Introduction Station (NCRPIS) were also evaluated. We measured RPR in three environments. Family-nested QTL were identified by joint-linkage mapping in the NAM panel. We also performed a genome-wide association study (GWAS) and genomic best linear unbiased prediction (GBLUP) in each panel. Broad sense heritability computed on a line means basis was low for RPR. Only 8 of 26 families had a heritability above 0.20. The NCRPIS diversity panel had a heritability of 0.54. Across NAM and IBM families, 18 family-nested QTL and 141 significant GWAS associations were identified for RPR. Numerous weak associations were also found in the NCRPIS diversity panel. However, few were linked to loci involved in phenylpropanoid and cellulose synthesis or vegetative phase transition. Using an identity-by-state (IBS) relationship matrix estimated from 1.6 million single nucleotide polymorphisms (SNPs) and RPR measures from 20% of the NAM panel, genomic prediction by GBLUP explained 64±2% of variation in the remaining RILs. In the NCRPIS diversity panel, an IBS matrix estimated from 681,257 SNPs and RPR measures from 20% of the panel explained 33±3% of variation in the remaining inbreds. These results indicate the high genetic complexity of stalk strength and the potential for genomic prediction to hasten its improvement.     

Mapping of QTL for downy mildew resistance in maize

Quantitative trait loci (QTLs) of maize involved in mediating resistance to Peronosclerospora sorghi, the causative agent of sorghum downy mildew (SDM), were detected in a population of recombinant inbred lines (RILs) derived from the Zea mays L. cross between resistant (G62) and susceptible (G58) inbred lines. Field tests of 94 RILs were conducted over two growing seasons using artificial inoculation. Heritability of the disease reaction was high (around 70%). The mapping population of the RILs was also scored for restriction fragment length polymorphic (RFLP) markers. One hundred and six polymorphic RFLP markers were assigned to ten chromosomes covering 1648 cM. Three QTLs were detected that significantly affected resistance to SDM combined across seasons. Two of these mapped quite close together on chromosome 1, while the third one was on chromosome 9. The percentage of phenotypic variance explained by each QTL ranged from 12.4% to 23.8%. Collectively, the three QTLs identified in this study explained 53.6% of the phenotypic variation in susceptibility to the infection. The three resistant QTLs appeared to have additive effects. Increased susceptibility was contributed by the alleles of the susceptible parent. The detection of more than one QTL supports the hypothesis that several qualitative and quantitative genes control resistance to P. sorghi.     

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short‐day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome‐wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co‐located with a QTL mapped in the RIL population.     

QTL mapping of resistance to Sporisorium reiliana in maize

We mapped and characterized quantitative trait loci (QTL) for resistance to Sporisorium reiliana. A population of 220 F₃ families produced from the cross of two European elite inbreds (D32, D145) was evaluated with two replications at a French location with high natural incidence of S. reiliana and at a Chinese location employing artificial inoculation. The 220 F₃ families were genotyped with 87 RFLP and seven SSR markers. Using composite interval mapping, we identified two different sets of 3 and 8 QTL for the French and the Chinese locations explaining 13% and 44% of respectively. Individual QTL explained up to 14% of σ^² _p. The 11 QTL mapped to eight maize chromosomes and displayed mostly additive or partial dominant gene action. Significant digenic epistatic interactions were detected for one pair of these QTL. Only a few QTL for S. reiliana were in common with QTL for resistance to Ustilago maydis and Puccinia sorghi, identified at a German location for the same population. Consequently, in our materials resistance to these three fungal pathogens of maize seems to be inherited independently. Received: 14. December 1998 / Accepted: 30 January 1999     

A new test for family-based association mapping with inbred lines from plant breeding programs

Association mapping holds great promise for the detection of quantitative trait loci (QTL) in plant breeding populations. The main objectives of this study were to (1) adapt the quantitative pedigree disequilibrium test to typical pedigrees of inbred lines produced in plant breeding programs, (2) compare the newly developed quantitative inbred pedigree disequilibrium test (QIPDT) with the commonly employed logistic regression ratio test (LRRT), with respect to the power and type I error rate of QTL detection, and (3) demonstrate the use of the QIPDT by applying it to flowering data of European elite maize inbreds. QIPDT and LRRT were compared based on computer simulations modeling 55 years of hybrid maize breeding in Central Europe. Furthermore, we applied QIPDT to a cross-section of 49 European elite maize inbred lines genotyped with 722 amplified fragment length polymorphism markers and phenotyped in four environments for days to anthesis. Compared to LRRT, the power to detect QTL was higher with QIPDT when using data collected routinely in plant breeding programs. Application of QIPDT to the 49 European maize inbreds resulted in a significant (P < 0.05) association located at a position for which a consensus QTL was detected in a previous study. The results of our study suggested that QIPDT is a promising QTL detection method for data collected routinely in plant breeding programs.     

Genetic dissection of sorghum grain quality traits using diverse and segregating populations

Key message

Coordinated association and linkage mapping identified 25 grain quality QTLs in multiple environments, and fine mapping of the Wx locus supports the use of high-density genetic markers in linkage mapping.

Abstract

There is a wide range of end-use products made from cereal grains, and these products often demand different grain characteristics. Fortunately, cereal crop species including sorghum [Sorghum bicolor (L.) Moench] contain high phenotypic variation for traits influencing grain quality. Identifying genetic variants underlying this phenotypic variation allows plant breeders to develop genotypes with grain attributes optimized for their intended usage. Multiple sorghum mapping populations were rigorously phenotyped across two environments (SC Coastal Plain and Central TX) in 2 years for five major grain quality traits: amylose, starch, crude protein, crude fat, and gross energy. Coordinated association and linkage mapping revealed several robust QTLs that make prime targets to improve grain quality for food, feed, and fuel products. Although the amylose QTL interval spanned many megabases, the marker with greatest significance was located just 12 kb from waxy (Wx), the primary gene regulating amylose production in cereal grains. This suggests higher resolution mapping in recombinant inbred line (RIL) populations can be obtained when genotyped at a high marker density. The major QTL for crude fat content, identified in both a RIL population and grain sorghum diversity panel, encompassed the DGAT1 locus, a critical gene involved in maize lipid biosynthesis. Another QTL on chromosome 1 was consistently mapped in both RIL populations for multiple grain quality traits including starch, crude protein, and gross energy. Collectively, these genetic regions offer excellent opportunities to manipulate grain composition and set up future studies for gene validation.

     

Locating QTLs controlling several adult root traits in an elite Chinese hybrid rice

This study aimed to elucidate the genetics of the adult root system in elite Chinese hybrid rice. Several adult root traits in a recombinant inbred line (RIL) population of Xieyou 9308 and two backcross F₁ (BCF₁) populations derived from the RILs were phenotyped under hydroponic culture at heading stage for quantitative trait locus (QTL) mapping and other statistical analysis. There a total of eight QTLs detected for the root traits. Among of them, a pleiotropic QTL was repeatedly flanked by RM180 and RM5436 on the short arm of chromosome 7 for multiple traits across RILs and its BCF₁ populations, accounting for 6.88% to 25.26% of the phenotypic variances. Only additive/dominant QTLs were detected for the root traits. These results can serve as a foundation for facilitating future cloning and molecular breeding.     

The Identification of Two Head Smut Resistance-Related QTL in Maize by the Joint Approach of Linkage Mapping and Association Analysis

Head smut, caused by the fungus Sphacelotheca reiliana (Kühn) Clint, is a devastating threat to maize production. In this study, QTL mapping of head smut resistance was performed using a recombinant inbred line (RIL) population from a cross between a resistant line “QI319” and a susceptible line “Huangzaosi” (HZS) with a genetic map constructed from genotyping-by-sequencing (GBS) data and composed of 1638 bin markers. Two head smut resistance QTL were identified, located on Chromosome 2 (q2.09HR) and Chromosome 5 (q5.03HR), q2.09HR is co-localized with a previously reported QTL for head smut resistance, and the effect of q5.03HR has been validated in backcross populations. It was also observed that pyramiding the resistant alleles of both QTL enhanced the level of resistance to head smut. A genome-wide association study (GWAS) using 277 diverse inbred lines was processed to validate the mapped QTL and to identify additional head smut resistance associations. A total of 58 associated SNPs were detected, which were distributed in 31 independent regions. SNPs with significant association to head smut resistance were detected within the q2.09HR and q5.03HR regions, confirming the linkage mapping results. It was also observed that both additive and epistastic effects determine the genetic architecture of head smut resistance in maize. As shown in this study, the combined strategy of linkage mapping and association analysis is a powerful approach in QTL dissection for disease resistance in maize.     

Identification of quantitative trait loci for yield and yield components in an advanced backcross population derived from the<Emphasis Type="Italic"> Oryza sativa</Emphasis> variety IR64 and the wild relative<Emphasis Type="Italic"> O. rufipogon</Emphasis>

A BC₂F₂ population developed from an interspecific cross between Oryza sativa (cv IR64) and O. rufipogon (IRGC 105491) was used in an advanced backcross QTL analysis to identify and introduce agronomically useful genes from this wild relative into the cultivated gene pool. The objectives of this study were: (1) to identify putative yield and yield component QTLs that can be useful to improve the elite cultivar IR64; (2) to compare the QTLs within this study with previously reported QTLs in rice as the basis for identifying QTLs that are stable across different environments and genetic backgrounds; and (3) to compare the identified QTLs with previously reported QTLs from maize to examine the degree of QTL conservation across the grass family. Two hundred eighty-five families were evaluated in two field environments in Indonesia, with two replications each, for 12 agronomic traits. A total of 165 markers consisting of 131 SSRs and 34 RFLPs were used to construct the genetic linkage map. By employing interval mapping and composite interval mapping, 42 QTLs were identified. Despite its inferior performance, 33% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield and yield components in the IR64 background. Twenty-two QTLs (53.4%) were located in similar regions as previously reported rice QTLs, suggesting the existence of stable QTLs across genetic backgrounds and environments. Twenty QTLs (47.6%) were exclusively detected in this study, uncovering potentially novel alleles from the wild, some of which might improve the performance of the tropical indica variety IR64. Additionally, several QTLs for plant height, grain weight, and flowering time detected in this study corresponded to homeologous regions in maize containing previously detected maize QTLs for these traits.