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Genetic mapping of quantitative trait loci controlling growth and wood quality traits in Eucalyptus grandis using a maternal half-sib family and RAPD markers.

Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping, BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding.

Chromosome Mapping↗

Estimation of effects of quantitative trait loci in large complex pedigrees.

A method was derived to estimate effects of quantitative trait loci (QTL) using incomplete genotype information in large outbreeding populations with complex pedigrees. The method accounts for background genes by estimating polygenic effects. The basic equations used are very similar to the usual linear mixed model equations for polygenic models, and segregation analysis was used to estimate the probabilities of the QTL genotypes for each animal. Method R was used to estimate the polygenic heritability simultaneously with the QTL effects. Also, initial allele frequencies were estimated. The method was tested in a simulated data set of 10,000 animals evenly distributed over 10 generations, where 0, 400 or 10,000 animals were genotyped for a candidate gene. In the absence of selection, the bias of the QTL estimates was < 2%. Selection biased the estimate of the Aa genotype slightly, when zero animals were genotyped. Estimates of the polygenic heritability were 0.251 and 0.257, in absence and presence of selection, respectively, while the simulated value was 0.25. Although not tested in this study, marker information could be accommodated by adjusting the transmission probabilities of the genotypes from parent to offspring according to the marker information. This renders a QTL mapping study in large multi-generation pedigrees possible.

Animals↗

Use of DNA fingerprints for the detection of major genes for quantitative traits in domestic species.

The detection of marker loci linked to major genes or quantitative trait loci (QTL) of large effect in farm animal populations is of great potential value, both because it allows the easy manipulation of the major genes and because it provides a possible route to their ultimate isolation. At present the number of markers available is limited in farm animals. DNA fingerprints provide a promising source of informative marker loci and have the advantage that several loci can be detected on a single Southern hybridization. The disadvantage of DNA fingerprints is the difficulty in determining allelism of DNA fingerprint bands in different pedigrees and the fact that not all potentially resolvable loci can be resolved in a single pedigree. With probes capable of detecting 50 randomly distributed loci, about 50% of the genome of a typical domestic mammal might be expected to be closely linked to a marker (at a distance of 0.2 Morgans or less). If a proportion of DNA fingerprint loci prove to be clustered near chromosomal telomeres or elsewhere in the genome, coverage will be less. In order to detect linkage to a major gene, sires known or suspected to be heterozygous are used to produce large half-sibships, all animals in the pedigree are DNA fingerprinted and the phenotypes of the offspring are recorded. Where several heterozygous sires are available, sires can be selected in an attempt to maximize the number of marker loci resolved. The optimum number of sires needed to produce pedigrees will depend upon the size of the major gene, the number of DNA fingerprint probes available and the characteristics of the DNA fingerprints produced, but often one or two pedigrees will be optimum. Monte Carlo simulation was used to explore the power of detection of linkage between a major gene and a marker locus in a backcross. Maximum likelihood and analysis of variance of mean differences between marker genotypes were of similar power, but maximum likelihood provided reasonable estimates of the major gene effect and its linkage to the marker under some circumstances. One hundred offspring informative for the segregation of a marker would provide reasonable power for the detection of a gene causing a difference between the heterozygote and the homozygote of at least one within-sire, within-genotype standard deviation when linkage was very close (0.05 or less).(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

[Marker analysis of quantitative traits in maize by ISSR-PCR].

The segregating maize population (GK26 x Mo17)F2 has been used for identification of ISSR markers able to reveal a significant difference between alleles by a quantitative index. Confidence ranges have been determined for variation in 17 quantitative traits. Variations in the traits under study correlate with the inheritance of 16 marker loci have been found. The nature of these correlations and the possibility of chromosomal mapping of genetic markers are discussed.

Crosses, Genetic↗

Domestication quantitative trait loci in Triticum dicoccoides, the progenitor of wheat.

Wild emmer wheat, Triticum dicoccoides, is the progenitor of modern tetraploid and hexaploid cultivated wheats. Our objective was to map domestication-related quantitative trait loci (QTL) in T. dicoccoides. The studied traits include brittle rachis, heading date, plant height, grain size, yield, and yield components. Our mapping population was derived from a cross between T. dicoccoides and Triticum durum. Approximately 70 domestication QTL effects were detected, nonrandomly distributed among and along chromosomes. Seven domestication syndrome factors were proposed, each affecting 5-11 traits. We showed: (i) clustering and strong effects of some QTLs; (ii) remarkable genomic association of strong domestication-related QTLs with gene-rich regions; and (iii) unexpected predominance of QTL effects in the A genome. The A genome of wheat may have played a more important role than the B genome during domestication evolution. The cryptic beneficial alleles at specific QTLs derived from T. dicoccoides may contribute to wheat and cereal improvement.

Alleles↗

Quantitative trait loci for growth trajectories in Populus.

Growth trajectories are a biological process important to plant and animal breeding, and to evolutionary genetic studies. In this article, we report the detection of quantitative trait loci (QTLs) responsible for growth trajectories in poplars that are used as a model system for the study of forest biology. These QTLs were localized on a genetic linkage map of polymorphic markers using a statistical mapping method incorporating growth-curve models. The effects of the QTLs on growth are described as a function of age, so that age-specific changes in QTL effects can be readily projected throughout the entire growth process. The QTLs identified display increased effects on growth when trees age, yet the timing of QTL activation is earlier for stem height than diameter, which is consistent with the ecological viewpoint of canopy competition. The implications of the results for breeding and silviculture are discussed.

Genetic Linkage↗

Detection of quantitative trait loci for resistance/susceptibility to pseudorabies virus in swine.

This study describes genetic differences in resistance/susceptibility to pseudorabies virus (PrV) between European Large White and Chinese Meishan pigs, with a mapping of quantitative trait loci (QTL) obtained from a genome-wide scan in F(2) animals. Eighty-nine F(2) pigs were challenged intranasally at 12 weeks with 10(5) p.f.u. of the wild-type PrV strain NIA-3. For QTL analysis, 85 microsatellite markers, evenly spaced on the 18 porcine autosomes and on the pseudoautosomal region of the X chromosome, were genotyped. All pigs developed clinical signs, i.e. fever, from 3 to 7 days p.i. The pure-bred Large White pigs, the F(1) and three-quarters of the F(2) animals, but none of the Meishan pigs, developed neurological symptoms and died or were euthanized. QTLs for appearance/non-appearance of neurological symptoms were found on chromosomes 9, 5, 6 and 13. They explained 10.6-17.9% of F(2) phenotypic variance. QTL effects for rectal temperature after PrV challenge were found on chromosomes 2, 4, 8, 10, 11 and 16. Effects on chromosomes 9, 10 and 11 were significant on a genome-wide level. The results present chromosomal regions that are associated with presence/absence of neurological symptoms as well as temperature course after intranasal challenge with NIA-3. The QTLs are in proximity to important candidate genes that are assumed to play crucial roles in host defence against PrV.

Animals↗

Tagging quantitative trait loci for maturity-corrected late blight resistance in tetraploid potato with PCR-based candidate gene markers.

Late blight caused by the oomycete Phytophthora infestans is the economically most important and destructive disease in potato cultivation. Quantitative resistance to late blight available in tetraploid cultivars is correlated with late maturity in temperate climates, which is an undesirable characteristic. A total of 30 DNA-based markers known to be linked to loci for pathogen resistance in diploid potato were selected and tested as polymerase chain reaction-based markers for linkage with quantitative trait loci (QTL) for late blight resistance and plant maturity in two half-sib families of tetraploid potatoes. Most markers originated from within or were physically closely linked to candidate genes for quantitative resistance factors. The families were repeatedly evaluated in the field for quantitative resistance to late blight and maturity. Resistance was corrected for the maturity effect. Nine of eleven different map segments tagged by the markers harbored QTL affecting maturity-corrected resistance. Interactions were found between unlinked resistance QTL, providing testable strategies for marker-assisted selection in tetraploid potato. Based on the linkage observed between QTL for resistance and plant maturity and based on the genetic interactions observed between candidate genes tagging resistance QTL, we discuss models for the molecular basis of quantitative resistance and maturity.

Alleles↗

A two-stage variable-stringency semiparametric method for mapping quantitative-trait loci with the use of genomewide-scan data on sib pairs.

Genomewide scans for mapping loci have proved to be extremely powerful and popular. We present a semiparametric method of mapping a quantitative-trait locus (QTL) or QTLs with the use of sib-pair data generated from a two-stage genomic scan. In a two-stage genomic scan, either the entire genome or a large portion of the genome is saturated with low-density markers at the first stage. At the second stage, the intervals that are identified as probable locations of the trait loci, by means of analysis of data from the first stage, are then saturated with higher-density markers. These data are then analyzed for fine mapping of the loci. Our statistical strategy for analysis of data from the first stage is a low-stringency method based on the rank correlation of squared trait-difference values of the sib pairs and the estimated identity-by-descent scores at the marker loci. We suggest the use of a low-stringency method at the first stage, to save on computational time and to avoid missing any marker interval that may contain the trait loci. For analysis of data from the second stage, we have developed a high-stringency nonparametric-regression approach, using the kernel-smoothing technique. Through extensive simulations, we show that this approach is more powerful than is a currently used method for mapping QTLs by use of sib pairs, particularly in the presence of dominance and epistatic effects at the trait loci.

Alleles↗

Effects of misspecification of allele frequencies on the power of Haseman-Elston sib-pair linkage method for quantitative traits.

It is well known that the Haseman-Elston (H-E) sib-pair linkage method does not assume that the genetic model underlying the trait phenotype is known without error, although this assumption is made for marker loci. However, misspecification of allele frequencies at the marker locus decreases power when some or all parental genotypes are unknown. In this study, the power of the H-E sib-pair method was compared for different types of traits when some or all parental data were missing and allele frequencies at the marker loci were misspecified. Data were generated for a quantitative trait and marker loci in nuclear families using G.A.S.P. (V3.3). Three types of traits were simulated with two equifrequent alleles with a random environmental effect (10%, 30%, and 50%). The simulated data were analyzed using (i) one of the parent's marker data, and (ii) no parental marker data, with both correct and incorrect marker allele frequencies. This test is found to be robust in most of the situations considered except for a slight decrease in power when sample size is small and when the marker locus is not very polymorphic.

Chromosome Mapping↗

Quantitative trait loci affecting fatness in the chicken.

An F2 chicken population of 442 individuals from 30 families, obtained by crossing a broiler line with a layer line, was used for detecting and mapping Quantitative Trait Loci (QTL) affecting abdominal fat weight, skin fat weight and fat distribution. Within-family regression analyses using 102 microsatellite markers in 27 linkage groups were carried out with genome-wide significance thresholds. The QTL for abdominal fat weight were found on chromosomes 3, 7, 15 and 28; abdominal fat weight adjusted for carcass weight on chromosomes 1, 5, 7 and 28; skin and subcutaneous fat on chromosomes 3, 7 and 13; skin fat weight adjusted for carcass weight on chromosomes 3 and 28; and skin fat weight adjusted for abdominal fat weight on chromosomes 5, 7 and 15. Interactions of the QTL with sex or family were unimportant and, for each trait, there was no evidence for imprinting or of multiple QTL on any chromosome. Significant dominance effects were obtained for all but one of the significant locations for QTL affecting the weight of abdominal fat, none for skin fat and one of the three QTL affecting fat distribution. The magnitude of each QTL ranged from 3.0 to 5.2% of the residual phenotypic variation or 0.2-0.8 phenotypic standard deviations. The largest additive QTL (on chromosome 7) accounted for more than 20% of the mean weight of abdominal fat. Significant positive and negative QTL were identified from both lines.

Abdomen↗

Genetic and molecular dissection of quantitative traits in rice.

Recent progress in the generation of a molecular genetic map and markers for rice has made possible a new phase of mapping individual genes associated with complex traits. This type of analysis is often referred to as quantitative trait locus (QTL) analysis. Increasing numbers of QTL analyses are providing enormous amounts of information about QTLs, such as the numbers of loci involved, their chromosomal locations and gene effects. Clarification of genetic bases of complex traits has a big impact not only on fundamental research on rice plant development, but it also has practical benefits for rice breeding. In this review, we summarize recent progress of QTL analysis of several complex traits in rice. A strategy for positional cloning of genes at QTLs is also discussed.

Chromosome Mapping↗

Exponential mapping of quantitative trait loci governing allometric relationships in organisms.

Allometric scaling relationships or quarter-power rules, as a universal biological law, can be viewed as having some genetic component, and the particular genes (or quantitative trait loci, QTL) underlying these allometric relationships can be mapped using molecular markers. We develop a mathematical and statistical model for mapping allometric QTL on the basis of nonlinear power functions using Taylor's approximation theory. Simulation studies indicate that the QTL position and effect can be estimated using our model, but the estimation precision can be improved from the higher- over lower-order approximation when the sample size used and gene effects are small. The application of our approach in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship between 3rd-year stem height and 3rd-year stem biomass. It is expected that our model will have broad implications for genetic, evolutionary, biomedical and breeding research.

Algorithms↗

Mapping quantitative trait loci in plants: uses and caveats for evolutionary biology.

Gregor Mendel was either clever or lucky enough to study traits of simple inheritance in his pea plants; however, many plant characters of interest to modern geneticists are decidedly complex. Understanding the genetic basis of such complex, or quantitative, traits requires a combination of modern molecular genetic techniques and powerful statistical methods. These approaches have begun to give us insight into understanding the evolution of complex traits both in crops and in wild plants.

Genome, Plant↗

Quantitative trait loci (QTLs) associated with resistance/susceptibility to infectious pancreatic necrosis virus (IPNV) in rainbow trout (Oncorhynchus mykiss).

Infectious pancreatic necrosis (IPN) is a well-known acute viral disease of salmonid species. We have identified quantitative trait loci (QTLs) associated with resistance to this disease in rainbow trout. We searched for linkage among 51 microsatellite markers used to construct a framework linkage map in backcross families of rainbow trout (Oncorhynchus mykiss), produced by crossing IPN-resistant (YN-RT201) and -susceptible (YK-RT101) strains. Two putative QTLs affecting disease resistance were detected on chromosomes A (IPN R S-1) and C (IPN R/S-2), respectively, suggesting that this is a polygenic trait in rainbow trout. These markers have great potential for use in marker-assisted selection (MAS) for IPN resistance and provide the basis for cloning of IPN resistance genes. Clarification of the genetic bases of complex traits has broad implications for fundamental research, but will also be of practical benefit to fish breeding.

Animals↗

Confirmation of correlations and common quantitative trait loci between neurotensin receptor density and hypnotic sensitivity to ethanol.

BACKGROUND: In previous studies, genetic correlations were observed between hypnotic sensitivity to ethanol and high-affinity neurotensin receptor (NTS1) binding. Provisional quantitative trait loci (QTLs) were identified for these traits, and some of these QTLs were found on common chromosomal regions. In continued efforts to examine the relationship between NTS1 binding capacity and hypnotic sensitivity to ethanol, studies were designed to confirm correlations between NTS1 densities in the brain, duration of ethanol-induced loss of righting reflex (LORR), and blood ethanol concentrations at regain of righting reflex (BECRR). Another purpose of the study was to confirm QTLs for these traits. METHODS: ILS X ISS F2 mice and HAS X LAS F2 rats as well as the progenitors were tested for LORR, BECRR, and NTS1 densities. Phenotypic correlations were calculated between LORR and BECRR and between these measures and NTS1 densities in striatum from both mice and rats. The F2 mice were genotyped by using polymorphic markers for five previously reported QTLs for LORR to confirm QTLs for BECRR and NTS1 densities in striatum, ventral midbrain, and frontal cortex. RESULTS: Phenotypic correlations were found between LORR and BECRR (r = -0.66 to -0.74, p < 10(-9)) and between these measures and NTS1 densities in striatum (r = 0.28-0.38, p < 10(-2)) from both mice and rats. QTLs for LORR and BECRR (lod score = 2-6) were found in common regions of chromosomes 1, 2, and 15. By using the combined results from a previous LSXSS RI study and the current results, a suggestive QTL (lod score = 3.1) for striatal NTS1 receptor densities was found on chromosome 15 at approximately 60 cM, in the same region as the chromosome 15 LORR/BECRR QTL. CONCLUSIONS: The results are in agreement with previously reported correlations and QTLs for NTS1 receptor densities and measures of hypnotic sensitivity to ethanol in mice and extend those correlations to another species, the rat. These findings support a role for NTS1 in genetically mediated differences in hypnotic sensitivity to ethanol.

Animals↗

Sex-specific quantitative trait loci contribute to normal variation in bone structure at the proximal femur in men.

Bone structure is an important determinant of osteoporotic fracture. In women, bone structure is highly heritable, and several quantitative trait loci (QTL) have been reported. There are few comparable data in men. This study in men aimed at establishing the heritability of bone structure at the proximal femur, identifying QTL contributing to normal variation in bone structure, and determining which QTL might be sex-specific. Bone structure at the proximal femur was measured in 205 pairs of brothers age 18-61. Heritability was calculated, and linkage analysis performed on phenotypes at the proximal femur. Heritability estimates ranged from 0.99 to 0.39. A genome wide scan identified suggestive QTL (LOD>2.2) for femoral shaft width on chromosome 14q (LOD=2.69 at position 99 cM), calcar femorale at chromosome 2p (LOD=3.97 at position 194 cM) and at the X chromosome (LOD=3.01 at position 77 cM), femoral neck width on chromosome 5p (LOD=2.28 at position 0 cM), femoral head width on chromosome 11q (LOD=2.30 at position 131 cM) and 15q (LOD=3.11 at position 90 cM), and pelvic axis length on chromosome 4q (LOD=4.16 at position 99 cM) and 17q (LOD=2.80 at position 112 cM). Comparison with published data in 437 pairs of premenopausal sisters from the same geographical region suggested that 3 of the 7 autosomal QTL were male-specific. This study demonstrates that bone structure at the proximal femur in healthy men is highly heritable. The occurrence of sex-specific genes in humans for bone structure has important implications for the pathogenesis and treatment of osteoporosis.

Adult↗

Independent genome-wide scans identify a chromosome 18 quantitative-trait locus influencing dyslexia.

Developmental dyslexia is defined as a specific and significant impairment in reading ability that cannot be explained by deficits in intelligence, learning opportunity, motivation or sensory acuity. It is one of the most frequently diagnosed disorders in childhood, representing a major educational and social problem. It is well established that dyslexia is a significantly heritable trait with a neurobiological basis. The etiological mechanisms remain elusive, however, despite being the focus of intensive multidisciplinary research. All attempts to map quantitative-trait loci (QTLs) influencing dyslexia susceptibility have targeted specific chromosomal regions, so that inferences regarding genetic etiology have been made on the basis of very limited information. Here we present the first two complete QTL-based genome-wide scans for this trait, in large samples of families from the United Kingdom and United States. Using single-point analysis, linkage to marker D18S53 was independently identified as being one of the most significant results of the genome in each scan (P< or =0.0004 for single word-reading ability in each family sample). Multipoint analysis gave increased evidence of 18p11.2 linkage for single-word reading, yielding top empirical P values of 0.00001 (UK) and 0.0004 (US). Measures related to phonological and orthographic processing also showed linkage at this locus. We replicated linkage to 18p11.2 in a third independent sample of families (from the UK), in which the strongest evidence came from a phoneme-awareness measure (most significant P value=0.00004). A combined analysis of all UK families confirmed that this newly discovered 18p QTL is probably a general risk factor for dyslexia, influencing several reading-related processes. This is the first report of QTL-based genome-wide scanning for a human cognitive trait.

Child↗