An RFLP linkage map for loblolly pine based on a three-generation outbred pedigree

A genetic linkage map for loblolly pine (Pinus taeda L.) was constructed using segregation data from a three-generation outbred pedigree consisting of four grandparents, two parents, and 95 F₂ progeny. The map was based predominantly on restriction fragment length polymorphism (RFLP) loci detected by cDNA probes. Sixty-five cDNA and three genomic DNA probes revealed 90 RFLP loci. Six polymorphic isozyme loci were also scored. One-fourth (24%) of the cDNA probes detected more than 1 segregating locus, an indication that multigene families are common in pines. As many as six alleles were observed at a single segregating locus among grandparents and it was not unusual for the progeny to segregate for three or four alleles per locus. Multipoint linkage analysis placed 73 RFLP and 2 isozyme loci into 20 linkage groups; the remaining 17 RFLP and 4 isozyme loci were unlinked. The mapped RFLP probes provide a new set of codominant markers for genetic analyses in loblolly pine.     

Quantitative trait locus analysis of a recombinant inbred line population derived from a Lycopersicon esculentum x Lycopersicon cheesmanii cross

Quantitative trait loci influencing fruit traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato, Lycopersicon esculentum with a related wild species Lycopersicon cheesmanii. One hundred thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 F₈ RIL families. Fruit weight and soluble solids were measured in replicated trials during 1991 and 1992. Seed weight was measured in 1992. Significant (P<0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. A total of 73 significant marker locus-trait associations were detected for the three traits measured. Fifty-three of these associations were for fruit weight and soluble solids, many of which involved marker loci signficantly associated with both traits. QTL with large effects on all three traits were detected on chromosome 6. Greater homozygosity at many loci in the RIL population as compared to F₂ populations and greater genomic coverage resulted in increased precision in the estimation of QTL effects, and large proportions of the total phenotypic variance were explained by marker class variation at significant marker loci for many traits. The RIL population was effective in detecting and discriminating among QTL for these traits previously identified in other investigations despite skewed segregation ratios at many marker loci. Large additive effects were measured at significant marker loci. Lower fruit weight, higher soluble solids, and lower seed weight were generally associated with RFLP alleles from theL. cheesmanii parent.     

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain-Large White backcross

Knowing the large difference in daily feed intake (DFI) between Large White (LW) and Piétrain (PI) growing pigs, a backcross (BC) population has been set up to map QTL that could be used in marker assisted selection strategies. LW × PI boars were mated with sows from two LW lines to produce 16 sire families. A total of 717 BC progeny were fed ad libitum from 30 to 108 kg BW using single-place electronic feeders. A genome scan was conducted using genotypes for the halothane gene and 118 microsatellite markers spread on the 18 porcine autosomes. Interval mapping analyses were carried out, assuming different QTL alleles between sire families to account for within breed variability using the QTLMap software. The effects of the halothane genotype and of the dam line on the QTL effect estimates were tested. One QTL for DFI (P < 0.05 at the chromosome-wide (CW) level) and one QTL for feed conversion ratio (P < 0.01 at the CW level) were mapped to chromosomes SSC6 - probably due to the halothane alleles - and SSC7, respectively. Three putative QTL for feed intake traits were detected (P < 0.06 at the CW level) on SSC2, SSC7 and SSC9. QTL on feeding traits had effects in the range of 0.20 phenotypic s.d. The relatively low number of QTL detected for these traits suggests a large QTL allele variability within breeds and/or low effects of individual loci. Significant QTL were detected for traits related to carcass composition on chromosomes SSC6, SSC15 and SSC17, and to meat quality on chromosome SSC6 (P < 0.01 at the genome-wide level). QTL effects for body composition on SSC13 and SSC17 differed according to the LW dam line, which confirmed that QTL alleles were segregating in the LW breed. An epistatic effect involving the halothane locus and a QTL for loin weight on SSC7 was identified, the estimated substitution effects for the QTL differing by 200 g between Nn and NN individuals. The interactions between QTL alleles and genetic background or particular genes suggest further work to validate QTL segregations in the populations where marker assisted selection for the QTL would be applied.     

Multiple marker mapping of quantitative trait loci in an outbred pedigree of loblolly pine

A multiple marker least squares approach is presented for the analysis of a single three-generation pedigree for quantitative trait locus (QTL) characterisation. It is an extension of the approach by Haley et?al. (1994) to the situation where grandparents cannot be assumed to be homozygous at QTLs for the trait of interest. The method is applied to the analysis of wood specific gravity in loblolly pine (Pinus taeda L.). Within a similar framework, a series of preliminary analyses are carried out, followed by a more detailed search of the genome for one or more QTLs. The preliminary analyses provide information about whether the contribution from each linkage group appears to be polygenic, localised to a small region (e.g. a single QTL) or oligogenic (i.e. several QTLs). Significance levels are obtained using a permutation test that uses the observed phenotypes and marker genotypes. The conclusion of these analyses is that in this pedigree single QTLs with very large effect on wood specific gravity do not appear to be segregating, although there is evidence for QTLs with small effect. Finally, in order to assess the potential power of this pedigree, we simulated QTLs within the framework of the actual marker data. As expected, QTL effects would need to be large to be reliably detected in this study, and the power to detect QTLs varies at different positions in the genome depending on the level of information in the local markers.     

Mapping quantitative trait loci using molecular marker linkage maps

Summary High-density restriction fragment length polymorphism (RFLP) and allozyme linkage maps have been developed in several plant species. These maps make it technically feasible to map quantitative trait loci (QTL) using methods based on flanking marker genetic models. In this paper, we describe flanking marker models for doubled haploid (DH), recombinant inbred (RI), backcross (BC), F₁ testcross (F₁TC), DH testcross (DHTC), recombinant inbred testcross (RITC), F₂, and F₃ progeny. These models are functions of the means of quantitative trait locus genotypes and recombination frequencies between marker and quantitative trait loci. In addition to the genetic models, we describe maximum likelihood methods for estimating these parameters using linear, nonlinear, and univariate or multivariate normal distribution mixture models. We defined recombination frequency estimators for backcross and F₂ progeny group genetic models using the parameters of linear models. In addition, we found a genetically unbiased estimator of the QTL heterozygote mean using a linear function of marker means. In nonlinear models, recombination frequencies are estimated less efficiently than the means of quantitative trait locus genotypes. Recombination frequency estimation efficiency decreases as the distance between markers decreases, because the number of progeny in recombinant marker classes decreases. Mean estimation efficiency is nearly equal for these methods.     

A Random Model Approach to Interval Mapping of Quantitative Trait Loci

Mapping quantitative trait loci in outbred populations is important because many populations of organisms are noninbred. Unfortunately, information about the genetic architecture of the trait may not be available in outbred populations. Thus, the allelic effects of genes can not be estimated with ease. In addition, under linkage equilibrium, marker genotypes provide no information about the genotype of a QTL (our terminology for a single quantitative trait locus is QTL while multiple loci are referred to as QTLs). To circumvent this problem, an interval mapping procedure based on a random model approach is described. Under a random model, instead of estimating the effects, segregating variances of QTLs are estimated by a maximum likelihood method. Estimation of the variance component of a QTL depends on the proportion of genes identical-by-descent (IBD) shared by relatives at the locus, which is predicted by the IBD of two markers flanking the QTL. The marker IBD shared by two relatives are inferred from the observed marker genotypes. The procedure offers an advantage over the regression interval mapping in terms of high power and small estimation errors and provides flexibility for large sibships, irregular pedigree relationships and incorporation of common environmental and fixed effects.     

QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses

Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.     

Power analysis of QTL detection in half-sib families using selective DNA pooling

Individual loci of economic importance (QTL) can be detected by comparing the inheritance of a trait and the inheritance of loci with alleles readily identifiable by laboratory methods (genetic markers). Data on allele segregation at the individual level are costly and alternatives have been proposed that make use of allele frequencies among progeny, rather than individual genotypes. Among the factors that may affect the power of the set up, the most important are those intrinsic to the QTL: the additive effect of the QTL, and its dominance, and distance between markers and QTL. Other factors are relative to the choice of animals and markers, such as the frequency of the QTL and marker alleles among dams and sires. Data collection may affect the detection power through the size of half-sib families, selection rate within families, and the technical error incurred when estimating genetic frequencies. We present results for a sensitivity analysis for QTL detection using pools of DNA from selected half-sibs. Simulations showed that conclusive detection may be achieved with families of at least 500 half-sibs if sires are chosen on the criteria that most of their marker alleles are either both missing, or one is fixed, among dams.     

Fruit size QTL identification and the prediction of parental QTL genotypes and breeding values in multiple pedigreed populations of sweet cherry

Large fruit size is a critical trait for any new sweet cherry (Prunus avium L.) cultivar, as it is directly related to grower profitability. Therefore, determining the genetic control of fruit size in relevant breeding germplasm is a high priority. The objectives of this study were (1) to determine the number and positions of quantitative trait loci (QTL) for sweet cherry fruit size utilizing data simultaneously from multiple families and their pedigreed ancestors, and (2) to estimate fruit size QTL genotype probabilities and genomic breeding values for the plant materials. The sweet cherry material used was a five-generation pedigree consisting of 23 founders and parents and 424 progeny individuals from four full-sib families, which were phenotyped for fruit size and genotyped with 78 RosCOS single nucleotide polymorphism and 86 simple sequence repeat markers. These data were analyzed by a Bayesian approach implemented in FlexQTL? software. Six QTL were identified: three on linkage group (G) 2 with one each on groups 1, 3, and 6. Of these QTL, the second G2 QTL and the G6 QTL were previously discovered while other QTL were novel. The predicted QTL genotypes show that some QTL were segregating in all families while other QTL were segregating in a subset of the families. The progeny varied for breeding value, with some progeny having higher breeding values than their parents. The results illustrate the use of multiple pedigree-linked families for integrated QTL mapping in an outbred crop to discover novel QTL and predict QTL genotypes and breeding values.     

Allele-specific amplification of polymorphic sites for the detection of powdery mildew resistance loci in cereals

Primers for the polymerase chain reaction (PCR) were tailored to selectively amplify RFLP marker alleles associated with resistance and susceptibility for powdery mildew in cereals. The differentiation between marker alleles for susceptible and resistant genotypes is based on the discrimination of a single nucleotide by using allele-specific oligonucleotides as PCR primers. The PCR assays developed are diagnostic for RFLP alleles at the loci MWG097 in the barley genome and Whs350 in the wheat genome. The first marker locus is closely linked to MlLa resistance in barley, while the latter is linked to Pm2 resistance locus in wheat. PCR analysis of 31 barley and 30 wheat cultivars, with some exceptions, verified the presence or absence of the resistance loci investigated. These rapid PCR-based approaches are proposed as an efficient alternative to conventional procedures for selecting powdery mildew-resistant genotypes in breeding programs.     

Quantitative trait loci influencing protein and starch concentration in the Illinois Long Term Selection maize strains

A study was initiated to determine the number, chromosomal location, and magnitude of effect of QTL (quantitative trait loci or locus depending on context) controlling protein and starch concentration in the maize (Zea mays L.) kernel. Restriction fragment length polymorphism (RFLP) analysis was performed on 100 F₃ families derived from a cross of two strains, Illinois High Protein (IHP), X Illinois Low Protein (ILP), which had been divergently selected for protein concentration for 76 generations as part of the Illinois Long Term Selection Experiment. These families were analyzed for kernel protein and starch in replicated field trials during 1990 and 1991. A series of 90 genomic and cDNA clones distributed throughout the maize genome were chosen for their ability to detect RFLP between IHP and ILP. These clones were hybridized with DNA extracted from the 100 F₃ families, revealing 100 polymorphic loci. Single factor analysis of variance revealed significant QTL associations of many loci with both protein and starch concentration (P < 0.05 level). Twenty-two loci distributed on 10 chromosome arms were significantly associated with protein concentration, 19 loci on 9 chromosome arms were significantly associated with starch concentration. Sixteen of these loci were significant for both protein and starch concentration. Clusters of 3 or more significant loci were detected on chromosome arms 3L, 5S, and 7L for protein concentration, suggesting the presence of QTL with large effects at these locations. A QTL with large additive effects on protein and starch concentration was detected on chromosome arm 3L. RFLP alleles at this QTL were found to be linked with RFLP alleles at the Shrunken-2 (Sh2) locus, a structural gene encoding the major subunit of the starch synthetic enzyme ADP-glucose pyrophosphorylase. A multiple linear regression model consisting of 6 significant RFLP loci on different chromosomes explained over 64 % of the total variation for kernel protein concentration. Similar results were detected for starch concentration. Thus, several chromosomal regions with large effects may be responsible for a significant portion of the changes in kernel protein and starch concentration in the Illinois Long Term Selection Experiment.     

Derivation of single-locus relationship coefficients conditional on marker information

The coefficient of relationship is defined as the correlation between the additive genetic values of two individuals. This coefficient can be defined specifically for a single quantitative trait locus (QTL) and may deviate considerably from the overall expectation if it is taken conditional on information from linked marker loci. Conditional halfsib correlations are derived under a simple genetic model with a biallelic QTL linked to a biallelic marker locus. The conditional relationship coefficients are shown to depend on the recombination rate between the marker and the QTL and the population frequency of the marker alleles, but not on parameters of the QTL, i.e. number and frequency of QTL alleles, degree of dominance etc., nor on the (usually unknown) QTL genotype of the sire. Extensions to less simplified cases (multiple alleles at the marker locus and the QTL, two marker loci flanking the QTL) are given. For arbitrary pedigrees, conditional relationship coefficients can also be derived from the conditional gametic covariance matrix suggested by Fernando and Grossman (1989). The connection of these two approaches is discussed. The conditional relationship coefficient can be used for marker-assisted genetic evaluation as well as for the detection of QTL and the estimation of their effects.     

Using molecular markers to map multiple quantitative trait loci: models for backcross,recombinant inbred,and doubled haploid progeny

Summary To maximize parameter estimation efficiency and statistical power and to estimate epistasis, the parameters of multiple quantitative trait loci (QTLs) must be simultaneously estimated. If multiple QTL affect a trait, then estimates of means of QTL genotypes from individual locus models are statistically biased. In this paper, I describe methods for estimating means of QTL genotypes and recombination frequencies between marker and quantitative trait loci using multilocus backcross, doubled haploid, recombinant inbred, and testcross progeny models. Expected values of marker genotype means were defined using no double or multiple crossover frequencies and flanking markers for linked and unlinked quantitative trait loci. The expected values for a particular model comprise a system of nonlinear equations that can be solved using an interative algorithm, e.g., the Gauss-Newton algorithm. The solutions are maximum likelihood estimates when the errors are normally distributed. A linear model for estimating the parameters of unlinked quantitative trait loci was found by transforming the nonlinear model. Recombination frequency estimators were defined using this linear model. Certain means of linked QTLs are less efficiently estimated than means of unlinked QTLs.     

Assessment of genetic variation and differentiation of hop genotypes by microsatellite and AFLP markers.

Microsatellites have many desirable marker properties and have been increasingly used in crop plants in genetic diversity studies. Here we report on the characterisation of microsatellite markers and on their use for the determination of genetic identities and the assessment of genetic variability among accessions from a germplasm collection of hop. Thirty-two polymorphic alleles were found in the 55 diploid genotypes, with an average number of eight alleles (3.4 effective alleles) for four microsatellite loci. Calculated polymorphic information content values classified three loci as informative markers and two loci as suitable for mapping. The average observed heterozygosity was 0.7 and the common probability of identical genotypes was 3.271 x 10(-4). An additional locus, amplified by one primer pair, was confirmed by segregation analysis of two crosses. The locus discovered was heterozygous, with a null allele in the segregating population. The same range of alleles was detected in nine triploid and five tetraploid hop genotypes. Cultivar heterozygosity varied among all 69 accessions, with only one cultivar being homozygous at four loci. Microsatellite allele polymorphisms distinguished 81% of all genotypes; the same allelic profile was found mainly in clonally selected cultivars. Cultivar-specific alleles were found in some genotypes, as well as a specific distribution of alleles in geographically distinct hop germplasms. The genetic relationship among 41 hop accessions was compared on the basis of microsatellite and AFLP polymorphisms. Genetic similarity dendrograms showed low correlation between the two marker systems. The microsatellite dendrogram grouped genetically related accessions reasonably well, while the AFLP dendrogram showed good clustering of closely related accessions and, additionally, separated two geographically distinct hop germplasms. The results of microsatellite and AFLP analysis are discussed from the point of view of the applicability of the two marker systems for different aspects of germplasm evaluation.     

Genetic and physical mapping of barley telomeres

Barley (Hordeum vulgare L.) telomeres were investigated by means of pulsed field gel electrophoresis (PFGE) and in situ hybridization. In situ hybridization showed that a tandemly repeated satellite sequence has a subtelomeric location, and is present at thirteen of the fourteen chromosome ends. PFGE revealed that this satellite sequence is physically close to the telomeric repeat. Pulsed field gel electrophoresis was then used for segregation analysis and linkage mapping of several telomeric and satellite loci in a segregating doubled-haploid population. The telomeric repeat displayed a hypervariable segregation pattern with new alleles occurring in the progeny. Eight satellite and telomeric sites were mapped on an restriction fragment length polymorphism (RFLP)-map of barley, defining the ends of chromosome arms 1L, 2S, 3L, 4S, 4L, 5S and 6. One satellite locus mapped to an interstitial site on the long arm of chromosome 3. The pyhsical location of this locus was confirmed by in situ hybridization to wheat/barley addition line 3.     

A Bayesian Approach to Detect Quantitative Trait Loci Using Markov Chain Monte Carlo

Markov chain Monte Carlo (MCMC) techniques are applied to simultaneously identify multiple quantitative trait loci (QTL) and the magnitude of their effects. Using a Bayesian approach a multi-locus model is fit to quantitative trait and molecular marker data, instead of fitting one locus at a time. The phenotypic trait is modeled as a linear function of the additive and dominance effects of the unknown QTL genotypes. Inference summaries for the locations of the QTL and their effects are derived from the corresponding marginal posterior densities obtained by integrating the likelihood, rather than by optimizing the joint likelihood surface. This is done using MCMC by treating the unknown QTL genotypes, and any missing marker genotypes, as augmented data and then by including these unknowns in the Markov chain cycle along with the unknown parameters. Parameter estimates are obtained as means of the corresponding marginal posterior densities. High posterior density regions of the marginal densities are obtained as confidence regions. We examine flowering time data from double haploid progeny of Brassica napus to illustrate the proposed method.     

QTL analysis of potato tuber dormancy

The potential loss of chemical sprout inhibitors because of public concern over the use of pesticides underscores the desirability of breeding for long dormancy of potato (Solanum tuberosum L.) tubers. Quantitative trait locus (QTL) analyses were performed in reciprocal backcrosses between S. tuberosum and S. berthaultii toward defining the complexity of dormancy. S. berthaultii is a wild Bolivian species characterized by a short-day requirement for tuberization, long tuber dormancy, and resistance to several insect pests. RFLP alleles segregating from the recurrent parents as well as from the interspecific hybrid were monitored in two segregating progenies. We detected QTLs on nine chromosomes that affected tuber dormancy, either alone or through epistatic interactions. Alleles from the wild parent promoted dormancy, with the largest effect at a QTL on chromosome 2. Long dormancy appeared to be recessive in the backcross to S. berthaultii (BCB). In BCB the additive effects of dormancy QTLs accounted for 48% of the measured phenotypic variance, and adding epistatic effects to the model explained only 4% more. In contrast, additive effects explained only 16% of the variance in the backcross to S. tuberosum (BCT), and an additional 24% was explained by the inclusion of epistatic effects. In BCB variation at all QTLs detected was associated with RFLP alleles segregating from the hybrid parent; in BCT all QTLs except for two found through epistasis were detected through RFLP alleles segregating from the recurrent parent. At least three dormancy QTLs mapped to markers previously found to be associated with tuberization in these crosses.Paper number 55 of the Department of Fruit and Vegetable Science, Cornell University     

An AFLP linkage map for Douglas-fir based upon multiple full-sib families

An amplified fragment length polymorphism (AFLP) linkage map for coastal Douglas-fir (Pseudotsuga menziesii) was constructed from eight full-sib families each consisting of 40 progeny. These families were part of the British Columbia Ministry of Forests second-generation progeny test program and represent typical family sizes used in progeny trials. For map construction, ten primer pairs using EcoRI+3 and MseI+4 were employed to identify and assay AFLP loci that segregated in backcross configurations. A new technique was used to obtain a single recombination rate for each pair of marker loci: for each locus pair, a recombination rate and log-odd value were estimated across all segregating families using a joint maximum likelihood function that considered the full dataset of segregating genotypes. The resulting matrix of recombination rates between all pairs of loci was used to construct an integrated linkage map using JoinMap. The final map consisted of 19 linkage groups spanning 938.6 cM at an average distance of 9.3 cM between markers. The simultaneous integration of data from multiple families may provide an effective way to construct a linkage map, using the genetic resources inherent in most tree improvement programs, where progeny tests of small size are conducted. The statistical property of number of families used is briefly discussed. For our data, at least three to four families greatly increased the chance of obtaining an informative locus in at least one family. Families as small as ten are adequate for closely linked loci (<10 cM), while the size used in our study (40) is adequate for loci within 30 cM.     

Inheritance of Restriction Fragment Length Polymorphisms in Agaricus Brunnescens

The cultivated mushroom, Agaricus brunnescens, is secondarily homothallic; most basidia produce only two basidiospores, each of which receives two of the four post meiotic nuclei. The segregation of restriction fragment length polymorphisms (RFLPs) detected by four plasmid probes carrying single-copy nuclear DNA of Agaricus was followed in seven parental strains including commercial, wild-collected, and artificially synthesized heterokaryons. Of a total of 367 single-spore progeny examined, 351 (95.6%) were heteroallelic at all RFLP loci heteroallelic in the respective parents. Of the 16 segregant isolates, ten (2.7% of the total) were homoallelic at all segregating loci assayed, suggesting that these isolates were most probably derived from rare spores that had received only a single postmeiotic nucleus. Some of these ten isolates had recombinant genotypes. Only five isolates (1.4% of the total) showed homoallelism at one of the loci heteroallelic in the parent, while remaining heteroallelic at other loci. These five genotypes suggest that a crossover had occurred between a marker locus and its respective centromere. Taken together, the results suggest that meiosis in A. brunnescens is accompanied by low levels of recombination and that nonsister nuclei are preferentially incorporated into basidiospores after meiosis II.     

Identification of quantitative trait loci for wood quality and growth across eight full-sib coastal Douglas-fir families

Typical linkage and quantitative trait locus (QTL) analyses in forest trees have been conducted in single pedigrees with sex-averaged linkage maps. The results of a QTL analysis for wood quality and growth traits of coastal Douglas-fir using eight full-sib families, each consisting of 40 progeny, replicated on four sites are presented. The resulting map of segregating genetic markers consisted of 120 amplified fragment length polymorphism (AFLP) loci distributed across 19 linkage groups. The wood quality traits represent the widest suite of traits yet examined for QTL analysis in a tree species in a single study. Wood fiber traits showed the lowest number of QTLs (3) with relatively small effect (ca. 4%); wood density traits also showed just three QTLs but with slightly larger effect; wood chemistry traits showed more QTLs (7), while ring density traits showed many QTLs with large numbers of QTLs (78) and interesting patterns of temporal variation. Growth traits gave just five QTLs but of major effect (10–16%). Trees, with their long generation times, provide a rich resource for studies of temporal variation of QTL expression.