Quantitative trait loci (QTLs) for pollen thermotolerance detected in maize

Pollen thermotolerance is an important component of the adaptability of crops to high temperature stress. The tolerance level of the different genotypes in a population of 45 maize recombinant inbred lines was determined as the degree of injury caused by high temperature to pollen germinability (IPGG) and pollen tube growth (IPTG) in an in vitro assay. Both traits revealed quantitative variability and high heritability. The traits were genetically dissected by the analysis of molecular markers using 184 mapped restriction fragment length polymorphisms (RFLPs). Significant genetic correlation between the markers and the trait allowed us to identify a minimum number of five quatitative trait loci (QTLs) for IPGG and six QTLs for IPTG. Their chromosomal localization indicated that the two characters are controlled by different sets of genes. In addition, IPGG and IPTG were shown to be basically independent of the pollen germination ability and pollen tube growth rate under non-stress conditions. These results are discussed in relation to their possible utilization in a breeding strategy for the improvement of thermotolerance in maize.     

Accuracy of mapping quantitative trait loci in autogamous species

Summary The development of linkage maps with large numbers of molecular markers has stimulated the search for methods to map genes involved in quantitative traits (QTLs). A promising method, proposed by Lander and Botstein (1989), employs pairs of neighbouring markers to obtain maximum linkage information about the presence of a QTL within the enclosed chromosomal segment. In this paper the accuracy of this method was investigated by computer simulation. The results show that there is a reasonable probability of detecting QTLs that explain at least 5% of the total variance. For this purpose a minimum population of 200 backcross or F₂ individuals is necessary. Both the number of individuals and the relative size of the genotypic effect of the QTL are important factors determining the mapping precision. On the average, a QTL with 5% or 10% explained variance is mapped on an interval of 40 or 20 centiMorgans, respectively. Of course, QTLs with a larger genotypic effect will be located more precisely. It must be noted, however, that the interval length is rather variable.     

Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker-assisted selection strategies

In most maize-growing areas yield reductions due to drought have been observed. Drought at flowering time is, in some cases, the most damaging. In the experiment reported here, trials with F₃ families, derived from a segregating F₂ population, were conducted in the field under well-watered conditions (WW) and two other water-stress regimes affecting flowering (intermediate stress, IS, and severe stress, SS). Several yield components were measured on equal numbers of plants per family: grain yield (GY), ear number (ENO), kernel number (KNO), and 100-kernel weight (HKWT). Correlation analysis of these traits showed that they were not independent of each other. Drought resulted in a 60% decrease of GY under SS conditions. By comparing yield under WW and SS conditions, the families that performed best under WW conditions were found to be proportionately more affected by stress, and the yield reductions due to SS conditions were inversely proportional to the performance under drought. Moreover, no positive correlation was observed between a drought-tolerance index (DTI) and yield under WW conditions. The correlation between GY under WW and SS conditions was 0.31. Therefore, in this experiment, selection for yield improvement under WW conditions only, would not be very effective for yield improvement under drought. Quantitative trait loci (QTLs) were identified for GY, ENO and KNO using composite interval mapping (CIM). No major QTLs, expressing more then 13% of the phenotypic variance, were detected for any of these traits, and there were inconsistencies in their genomic positions across water regimes. The use of CIM allowed the evaluation of QTL-by-environment interactions (Q×E) and could thus identify “stable” QTLs CIMMYT, Apartado Postal 6-641, 06600 Mexico D.F., Mexico across drought environments. Two such QTLs for GY, on chromosomes 1 and 10, coincided with two stable QTLs for KNO. Moreover, four genomic regions were identified for the expression of both GY and the anthesis-silking interval (ASI). In three of these, the allelic contributions were for short ASI and GY increase, while for that on chromosome 10 the allelic contribution for short ASI corresponded to a yield reduction. From these results, we hypothesize that to improve yield under drought, marker-assisted selection (MAS) using only the QTLs involved in the expression of yield components appears not to be the best strategy, and neither does MAS using only QTLs involved in the expression of ASI. We would therefore favour a MAS strategy that takes into account a combination of the “best QTLs” for different traits. These QTLs should be stable across target environments, represent the largest percentage possible of the phenotypic variance, and, though not involved directly in the expression of yield, should be involved in the expression of traits significantly correlated with yield, such as ASI.     

Sequential sampling in determining linkage between marker loci and quantitative trait loci

Summary As compared to classical, fixed sample size techniques, simulation studies showed that a proposed sequential sampling procedure can provide a substantial decrease (up to 50%, in some cases) in the mean sample size required for the detection of linkage between marker loci and quantitative trait loci. Sequential sampling with truncation set at the required sample size for the non-sequential test, produced a modest further decrease in mean sample size, accompanied by a modest increase in error probabilities. Sequential sampling with observations taken in groups produced a noticeable increase in mean sample size, with a considerable decrease in error probabilities, as compared to straightforward sequential sampling. It is concluded that sequential sampling has a particularly useful application to experiments aimed at investigating the genetics of differences between lines or strains that differ in some single outstanding trait.     

Identification of quantitative trait loci controlling rice mature seed culturability using chromosomal segment substitution lines

The genetic transformation efficiency of a rice variety is largely determined by its tissue culturability. Establishment of a highly efficient tissue-culture system has greatly accelerated the wide spread application of transgenic japonica varieties. However, such process for indica rice was hampered because this type of variety is recalcitrant to in vitro culture. This study aimed to map the quantitative trait loci (QTLs) for mature seed culturability using a chromosomal segment substitution lines (CSSL) population derived from a cross between an indica variety “Zhenshan 97B” and a japonica variety “Nipponbare”. The CSSLs consist of 139 lines each containing a single or a few introgression segments, and together covering the whole “Nipponbare” genome. Every CSSL was tested by culturing on the two medium systems developed for the respective indica and japonica parental varieties. The performance of culturability was evaluated by four indices: frequency of callus induction (CIF), callus subculture capability (CSC), frequency of plant regeneration (PRF) and the mean plantlet number per regenerated callus (MNR). All four traits displayed continuous variation among the CSSLs. With the culture system for japonica rice, three CIF QTLs, three CSC QTLs, three PRF QTLs and three MNR QTLs were detected. With the culture system for indica variety, six CIF QTLs, two CSC QTLs, three PRF QTLs and six MNR QTLs were identified, and these QTLs distributed on nine rice chromosomes. Two QTLs of CIF and two QTLs of MNR were detected in both the japonica and indica rice culture system. The correlation coefficients of all the four traits varied depending on the culture systems. These results provide the possibilities of enhancing the culturability of indica rice by marker-assisted breeding with those desirable alleles from the japonica. Lina Zhao and Hongju Zhou have contributed equally to this work.     

Power of different sampling strategies to detect quantitative trait loci variance effects

Summary Many studies have shown that segregating quantitative trait loci (QTL) can be detected via linkage to genetic markers. Power to detect a QTL effect on the trait mean as a function of the number of individuals genotyped for the marker is increased by selectively genotyping individuals with extreme values for the quantitative trait. Computer simulations were employed to study the effect of various sampling strategies on the statistical power to detect QTL variance effects. If only individuals with extreme phenotypes for the quantitative trait are selected for genotyping, then power to detect a variance effect is less than by random sampling. If 0.2 of the total number of individuals genotyped are selected from the center of the distribution, then power to detect a variance effect is equal to that obtained with random selection. Power to detect a variance effect was maximum when 0.2 to 0.5 of the individuals selected for genotyping were selected from the tails of the distribution and the remainder from the center.     

Genetic dissection of tocopherol content and composition in maize grain using quantitative trait loci analysis and the candidate gene approach

Tocopherols are essential micronutrients for humans and animals, with several beneficial effects in plants. Among cereals, only maize grains contain high concentrations of tocopherols. In this investigation we analyzed, during 2004 and 2005, by high-performance liquid chromatography (HPLC), a population of 233 recombinant inbred lines (RIL) which were derived from two diverse parents and had extremely variable tocopherol content and composition. A genetic map was constructed using 208 polymorphic molecular markers including gene-targeted markers based on six candidate genes of the tocopherol biosynthesis pathway (HPPD, VTE1, VTE3, VTE4, P3VTE5, and P4VTE5). Thirty-one quantitative trait loci (QTL) associated with quantitative variation of tocopherol content and composition were identified by composite interval mapping (CIM); these were located on sixteen genomic regions covering all the chromosomes except chromosome 4. Most (65%) QTL were co-located, suggesting that in some cases the same QTL predominantly affected the amounts of more than one tocopherol. Two candidate genes, HPPD and VTE4 showed co-localization with major QTL for tocopherol content and composition whereas only one interval (umc1075–umc1304) on chromosome eight exhibited a QTL for α, δ, γ, and total tocopherols with high LOD and PVE values. The candidate genes associated with tocopherol content and with composition, especially VTE4 and HPPD, could be precisely used for alteration of the tocopherol content and composition of maize grains by development of functional markers. Other identified major QTL especially those on chromosomes 8, 1, and 2 (near candidate gene VTE5) can also be used for improvement of maize grain quality by marker-assisted selection.     

Quantitative trait loci associated with traits determining grain and stover yield in pearl millet under terminal drought-stress conditions

Drought stress during the reproductive stage is one of the most important environmental factors reducing the grain yield and yield stability of pearl millet. A QTL mapping approach has been used in this study to understand the genetic and physiological basis of drought tolerance in pearl millet and to provide a more-targeted approach to improving the drought tolerance and yield of this crop in water-limited environments. The aim was to identify specific genomic regions associated with the enhanced tolerance of pearl millet to drought stress during the flowering and grain-filling stages. Testcrosses of a set of mapping-population progenies, derived from a cross of two inbred pollinators that differed in their response to drought, were evaluated in a range of managed terminal drought-stress environments. A number of genomic regions were associated with drought tolerance in terms of both grain yield and its components. For example, a QTL associated with grain yield per se and for the drought tolerance of grain yield mapped on linkage group 2 and explained up to 23% of the phenotypic variation. Some of these QTLs were common across stress environments whereas others were specific to only a particular stress environment. All the QTLs that contributed to increased drought tolerance did so either through better than average maintenance (compared to non-stress environments) of harvest index, or harvest index and biomass productivity. It is concluded that there is considerable potential for marker-assisted backcross transfer of selected QTLs to the elite parent of the mapping population and for their general use in the improvement of pearl millet productivity in water-limited environments. Received: 15 November 2000 / Accepted: 12 April 2001     

Genetic mapping of maize streak virus resistance from the Mascarene source. II. Resistance in line CIRAD390 and stability across germplasm

The streak disease has a major effect on maize in sub-Saharan Africa. Various genetic factors for resistance to the virus have been identified and mapped in several populations; these factors derive from different sources of resistance. We have focused on the Réunion island source and have recently identified several factors in the D211 line. A second very resistant line, CIRAD390, was crossed to the same susceptible parent, B73. The linkage map comprised 124 RFLP markers, of which 79 were common with the D211×B73 map. A row-column design was used to evaluate the resistance to maize streak virus (MSV) of 191 F_2:3 families under artificial infestation at two locations: Harare (Zimbabwe) and in Réunion island. Weekly ratings of resistance were taken and disease incidence and severity calculated. QTL analyses were conducted for each scoring date and for the integration over time of the disease scores, of incidence, and of severity. Heritability estimates (71–98%) were as high as for the D211×B73 population. Eight QTLs were detected on chromosomes 1, 2, 3, 5 (two QTLs), 6, 8, and 10. The chr1-QTL explained the highest proportion of phenotypic variation, about 45%. The QTLs on chromosomes 1, 2, and 10 were located in the same chromosomal bin as QTLs for MSV resistance in the D211×B73 population. In a simultaneous fit, QTLs explained together 43–67% of the phenotypic variation. The QTLs on chromosomes 3, 5, and 6 appeared to be specific for one or the other component of the resistance. For the chr3-QTL, resistance was contributed by the susceptible parent. There were significant QTL × environment interactions for some of the variables studied, but QTLs were stable in the two environments. They also appeared to be stable over time. Global gene action ranged from partial dominance to overdominance, except for disease severity. Some additional putative QTLs were also detected. The major QTL on chromosome 1 seemed to be common to the other sources of resistance, namely Tzi4, a tolerant line from IITA, and CML202 from CIMMYT. However, the distribution of the other QTLs within the genome revealed differences in Réunion germplasm and across these other resistance sources. This diversity is of great importance when considering the durability of the resistance. Received: 15 June 1998 / Accepted: 30 January 1999     

Identification of quantitative trait loci for growth and carcass composition in cattle

A genomic screening to detect quantitative trait loci (QTL) affecting growth, carcass composition and meat quality traits was pursued. Two hundred nineteen microsatellite markers were genotyped on 176 of 620 (28%) progeny from a Brahman x Angus sire mated to mostly MARC III dams. Selective genotyping, based on retail product yield (%) and fat yield (%), was used to select individuals to be genotyped. Traits included in the study were birth weight (kg), hot carcass weight (kg), retail product yield, fat yield, marbling score (400 = slight00 and 500 = small00), USDA yield grade, and estimated kidney, heart and pelvic fat (%). The QTL were classified as significant when the expected number of false positives (ENFP) was less than 0.05 (F-statistic greater than 17.3), and suggestive when the ENFP was <1 (F-statistic between 10.2 and 17.3). A significant QTL (F = 19; ENFP = 0.02) was detected for marbling score at centimorgan (cM) 54 on chromosome 2. Suggestive QTL were detected for fat yield at 50 cM, for retail product yield at 53 cM, and for USDA yield grade at 63 cM on chromosome 1, for marbling score at 56 cM, for retail product yield at 70 cM, and for estimated kidney, heart and pelvic fat at 79 cM on chromosome 3, for marbling score at 44 cM, for hot carcass weight at 49 cM, and for estimated kidney, heart and pelvic fat at 62 cM on chromosome 16, and for fat yield at 35 cM on chromosome 17. Two suggestive QTL for birth weight were identified, one at 12 cM on chromosome 20 and the other at 56 cM on chromosome 21. An additional suggestive QTL was detected for retail product yield, for fat yield, and for USDA yield grade at 26 cM on chromosome 26. Results presented here represent the initial search for quantitative trait loci in this family. Validation of detected QTL in other populations will be necessary.     

Genetic mapping of maize streak virus resistance from the Mascarene source. I. Resistance in line D211 and stability against different virus clones

Maize streak virus (MSV) disease may cause significant grain yield reductions in maize in Africa. Réunion island maize germplasm is a proven source of strong resistance. Its genetic control was investigated using 123 RFLP markers in an F₂ population of D211 (resistant) × B73 (susceptible). This population of 165 F_2:3 families was carefully evaluated in Harare (Zimbabwe) and in Réunion. Artificial infestation was done with viruliferous leafhoppers. Each plant was rated weekly six times after infestation on a 1–9 scale previously adjusted by image analysis. QTL analyses were conducted for each scoring date, and for the areas under the disease, incidence and severity progress curves. The composite interval mapping method used allowed the estimation of the additive and dominance effects and QTL × environment interactions. Heritabilities ranged from 73% to 98%, increasing with time after infestation. Resistance to streak virus in D211 was provided by one region on chromosome 1, with a major effect, and four other regions on chromosomes 2, 3 (two regions) and 10, with moderate or minor effects. Overall, they explained 48–62% of the phenotypic variation for the different variables. On chromosome 3, one of the two regions seemed to be more involved in early resistance, whereas the second was detected at the latest scoring date. Other QTLs were found to be stable over time and across environments. Mild QTL × environment interactions were detected. Global gene action appeared to be partially dominant, in favor of resistance, except at the earliest scoring dates, where it was additive. From this population, 32 families were chosen, representing the whole range of susceptibility to MSV. They were tested in Réunion against three MSV clones, along with a co-inoculation of two of them. Virulence differences between clones were significant. There were genotype × clone interactions, and these were more marked for disease incidence than for severity. Although these interactions were not significant for the mean disease scores, it is suggested that breeders should select for completely resistant genotypes. Received: 15 June 1998 / Accepted: 30 January 1999     

RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.)

 Abscisic acid (ABA) concentration in leaves of drought-stressed plants is a quantitatively inherited trait. In order to identify quantitative trait loci (QTLs) controlling leaf ABA concentration (L-ABA) in maize, leaf samples were collected from 80 F_3:4 families of the cross Os420 (high L-ABA)×IABO78 (low L-ABA) tested under drought conditions in field trials conducted over 2 years. In each year, leaf samples were collected at stem elongation and near anthesis. The genetic map obtained with 106 restriction fragment length polymorphism (RFLP) loci covered 1370 cM, which represented approximately 85% of the UMC maize map. Sixteen different QTLs with a LOD>2.0 were revealed in at least one sampling. Across samplings, only four QTLs significantly influenced L-ABA, accounting for 66% of the phenotypic variation and 76% of the genetic variation among families. At these QTLs, the alleles which increased L-ABA were contributed by Os420. The two most important QTLs were mapped on chromosome 2 near csu133 and csu109a. The effects associated with the QTL near csu133 were more pronounced near anthesis. The support intervals of the four primary QTLs for L-ABA did not overlap the presumed map position of mutants impaired in ABA biosynthesis. Received: 27 January 1998 / Accepted: 22 April 1998     

Efficiency of direct selection on quantitative trait loci for a two-trait breeding objective

Selection on known loci affecting quantitative traits (DSQ) was compared to phenotypic selection index for a single and a two-trait selection objective. Two situations were simulated; a single known quantitative locus, and ten identified loci accounting for all the additive genetic variance. Selection efficiency of DSQ relative to traitbased selection was higher for two-trait selection, than was selection on a single trait with the same heritability. The advantage of DSQ was greater when the traits were negatively correlated. Relative selection efficiency (RSE) for a single locus responsible for 0.1 of the genetic variance was 1.11 with heritabilities of 0.45 and 0.2 and zero genetic and phenotypic correlations between the traits. RSE of DSQ for ten known loci was 1.5 to 1.8 in the first 3 generations of selection, but declined in each subsequent generation. With DSQ most loci reached fixation after 7 generations. Response to trait-based selection continued through generation 15 and approached the response obtained with DSQ after 10 generations. The cumulative genetic response after 10 generations of DSQ was only 93% to 97% of the economically optimum genotype because the less favorable allele reached fixation for some loci, generally those with effects in opposite directions on the two traits.     

Bayesian point estimation of quantitative trait loci

In this article, we consider the problem of the estimation of quantitative trait loci (QTL), those chromosomal regions at which genetic information affecting some quantitative trait is encoded. Generally the number of such encoding sites is unknown, and associations between neutral molecular marker genotypes and observed trait phenotypes are sought to locate them. We consider a Bayesian model for simple experimental designs, and discuss the existing approaches to inference for this problem. In particular, we focus on locating positions of the best candidate markers segregating for the trait, a situation which is of primary interest in comparative mapping. We introduce a loss function for estimating both the number of QTL and their location, and we illustrate its application via simulated and real data.     

Identification and fine mapping of quantitative trait loci for the number of vascular bundle in maize stem

Studies that investigated the genetic basis of source and sink related traits have been widely conducted. However, the vascular system that links source and sink received much less attention. When maize was domesticated from its wild ancestor, teosinte, the external morphology has changed dramatically; however, less is known for the internal anatomy changes. In this study, using a large maize‐teosinte experimental population, we performed a high‐resolution quantitative trait locus (QTL) mapping for the number of vascular bundle in the uppermost internode of maize stem. The results showed that vascular bundle number is dominated by a large number of small‐effect QTLs, in which a total of 16 QTLs that jointly accounts for 52.2% of phenotypic variation were detected, with no single QTL explaining more than 6% of variation. Different from QTLs for typical domestication traits, QTLs for vascular bundle number might not be under directional selection following domestication. Using Near Isogenic Lines (NILs) developed from heterogeneous inbred family (HIF), we further validated the effect of one QTL qVb9‐2 on chromosome 9 and fine mapped the QTL to a 1.8‐Mb physical region. This study provides important insights for the genetic architecture of vascular bundle number in maize stem and sets basis for cloning of qVb9‐2.     

Bayesian analysis of linkage between genetic markers and quantitative trait loci. I. Prior knowledge

Summary Prior information on gene effects at individual quantitative trait loci (QTL) and on recombination rates between marker loci and QTL is derived. The prior distribution of QTL gene effects is assumed to be exponential with major effects less likely than minor ones. The prior probability of linkage between a marker and another single locus is a function of the number and length of chromosomes, and of the map function relating recombination rate to genetic distance among loci. The prior probability of linkage between a marker locus and a quantitative trait depends additionally on the number of detectable QTL, which may be determined from total additive genetic variance and minimum detectable QTL effect. The use of this prior information should improve linkage tests and estimates of QTL effects.     

Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment

Effects of individual quantitative trait loci (QTLs) can be isolated with the aid of linked genetic markers. Most studies have analyzed each marker or pair of linked markers separately for each trait included in the analysis. Thus, the number of contrasts tested can be quite large. The experimentwise type-I error can be readily derived from the nominal type-I error if all contrasts are statistically independent, but different traits are generally correlated. A new set of uncorrelated traits can be derived by application of a canonical transformation. The total number of effective traits will generally be less than the original set. An example is presented for DNA microsatellite D21S4, which is used as a marker for milk production traits of Israeli dairy cattle. This locus had significant effects on milk and protein production but not on fat. It had a significant effect on only one of the canonical variables that was highly correlated with both milk and protein, and this variable explained 82% of the total variance. Thus, it can be concluded that a single QTL is affecting both traits. The effects on the original traits could be derived by a reverse transformation of the effects on the canonical variable.     

Detection of quantitative trait loci on chromosome 5R of rye (Secale cereale L.)

 Progenies of an F₂ mapping population were analyzed for quantitative traits to detect QTLs by using marker information from F₂ plants for chromosome 5R. The mapping population was segregating for the major dwarfing gene Ddw1 and the gene Hp1 for hairy peduncle. The only QTL determining plant height was located between HP1 and Ddw1 on the distal part of chromosome 5RL. At the same position a QTL for peduncle length was found, and this trait was closely related to plant height (r=0.895). Since Hp1 and Ddw1 are dominant marker loci, no dominance effect could be estimated. The QTLs for spike length and the number of florets were located near the centromere on 5RL. These two traits were correlated with r=0.824 and showed partial dominance, but these traits were not correlated to plant height and peduncle length. Homoeologous relationships between the QTLs mapped for the first time in rye and those mapped in other Triticeae members are discussed. Received: 8 June 1998 / Accepted: 8 October 1998     

Identification of quantitative trait loci for nitrogen use efficiency in maize

Intensively managed crop systems are normally dependent on nitrogen input to maximize yield potential. Improvements in nitrogen- use efficiency (NUE) in crop plants may support the development of cropping systems that are more economically efficient and environment friendly. The objective of this study was to map and characterize quantitative trait loci (QTL) for NUE in a maize population. In preliminary experiments, inbred lines contrasting for NUE were identified and were used to generate populations of F2:3 families for genetic study. A total of 214 F2:3 families were evaluated in replicated trials under high nitrogen (280 kg/ha) and low nitrogen (30 kg/ha) conditions in 1996 and 1997. Analysis of ear-leaf area, plant height, grain yield, ears per plant, kernels number per ear, and kernel weight indicated significant genetic variation among F2:3 families. The heritability of these traits was found to be high (h2=0.57–0.81). The mapping population were genotyped using a set of 99 restriction fragment length polymorphism (RFLP) markers. A linkage map of these markers was developed and used to identify QTL. Between two and six loci were found to be associated with each trait. The correspondence of several genomic regions with traits measured under nitrogen limited conditions suggests the presence of QTL associated with NUE. QTLs will help breeders to improve their maize ideotype of a low-nitrogen efficiency by identifying those constitutive and adaptive traits involved in the expression of traits significantly correlated with yield, such as ear leaf area and number of ears per plant. This revised version was published online in June 2006 with corrections to the Cover Date.     

Mixture generalized linear models for multiple interval mapping of quantitative trait Loci in experimental crosses

Summary .  Quantitative trait loci mapping in experimental organisms is of great scientific and economic importance. There has been a rapid advancement in statistical methods for quantitative trait loci mapping. Various methods for normally distributed traits have been well established. Some of them have also been adapted for other types of traits such as binary, count, and categorical traits. In this article, we consider a unified mixture generalized linear model (GLIM) for multiple interval mapping in experimental crosses. The multiple interval mapping approach was proposed by Kao, Zeng, and Teasdale (1999, Genetics 152, 1203–1216) for normally distributed traits. However, its application to nonnormally distributed traits has been hindered largely by the lack of an efficient computation algorithm and an appropriate mapping procedure. In this article, an effective expectation–maximization algorithm for the computation of the mixture GLIM and an epistasis-effect-adjusted multiple interval mapping procedure is developed. A real data set, Radiata Pine data, is analyzed and the data structure is used in simulation studies to demonstrate the desirable features of the developed method.