Effects of missing marker and segregation distortion on QTL mapping in F2 populations

Missing marker and segregation distortion are commonly encountered in actual quantitative trait locus (QTL) mapping populations. Our objective in this study was to investigate the impact of the two factors on QTL mapping through computer simulations. Results indicate that detection power decreases with increasing levels of missing markers, and the false discovery rate increases. Missing markers have greater effects on smaller effect QTL and smaller size populations. The effect of missing markers can be quantified by a population with a reduced size similar to the marker missing rate. As for segregation distortion, if the distorted marker is not closely linked with any QTL, it will not have significant impact on QTL mapping; otherwise, the impact of the distortion will depend on the degree of dominance of QTL, frequencies of the three marker types, the linkage distance between the distorted marker and QTL, and the mapping population size. Sometimes, the distortion can result in a higher genetic variance than that of non-distortion, and therefore benefits the detection of linked QTL. A formula of the ratio of genetic variance explained by QTL under distortion and non-distortion was given in this study, so as to easily determine whether the segregation distortion marker (SDM) increases or decreases the QTL detection power. The effect of SDM decreases rapidly as its linkage relationship with QTL becomes looser. In general, distorted markers will not have a great effect on the position and effect estimations of QTL, and their effects can be ignored in large-size mapping populations.     

Maximum Likelihood Mapping of Quantitative Trait Loci Using Full-Sib Families

A maximum likelihood method is presented for the detection of quantitative trait loci (QTL) using flanking markers in full-sib families. This method incorporates a random component for common family effects due to additional QTL or the environment. Simulated data have been used to investigate this method. With a fixed total number of full sibs power of detection decreased substantially with decreasing family size. Increasing the number of alleles at the marker loci (i.e., polymorphism information content) and decreasing the interval size about the QTL increased power. Flanking markers were more powerful than single markers. In testing for a linked QTL the test must be made against a model which allows for between family variation (i.e., including an unlinked QTL or a between family variance component) or the test statistic may be grossly inflated. Mean parameter estimates were close to the simulated values in all situations when fitting the full model (including a linked QTL and common family effect). If the common family component was omitted the QTL effect was overestimated in data in which additional genetic variance was simulated and when compared with an unlinked QTL model there was reduced power. The test statistic curves, reflecting the likelihood of the QTL at each position along the chromosome, have discontinuities at the markers caused by adjacent pairs of markers providing different amounts of information. This must be accounted for when using flanking markers to search for a QTL in an outbred population.     

Multi-QTL mapping for quantitative traits using distorted markers

Marker segregation distortion is a common natural phenomenon. However, relatively little is known about utilizing distorted markers for detecting quantitative trait loci (QTL). Therefore, in this study we proposed a multi-QTL mapping approach that uses distorted markers. First, the information from all markers, including distorted markers, was used to detect segregation distortion loci (SDL). Second, the information from the detected SDL was used to correct the conditional probabilities of the QTL genotypes conditional on marker information, and these corrected probabilities were then incorporated into a multi-QTL mapping methodology. Finally, the proposed approach was validated by both Monte Carlo simulation studies and real data analysis. The results from the simulation studies show that as long as one or two SDL are placed around the simulated QTL, there are no differences between the new method and the ordinary interval mapping method in terms of the power of QTL detection or the estimates of the position and dominant effects of the QTL. However, the power of QTL detection is higher under the dominant genetic model of SDL than under the additive genetic model, and the estimate for the additive effect of QTL using the new method is significantly different from the estimate obtained using ordinary interval mapping. The above results were further confirmed by the detection of QTL for dried soymilk in 222 F_2:4 families in soybean.     

Detection of linkage for heterogeneous disorders by using multipoint linkage analysis.

We have compared the efficiency of the lod score test which assumes heterogeneity (lod2) to the standard lod score test which assumes homogeneity (lod1) when three-point linkage analysis is used in successive map intervals. If it is assumed that a gene located midway between two linked marker loci is responsible for a proportion of disease cases, then the lod1 test loses power relative to the lod2 test, as the proportion of linked families decreases, as the flanking markers are more closely linked, and as more map intervals are tested. Moreover, when multipoint analysis is used, linkage for a disease gene is more likely to be incorrectly excluded from a complete and dense linkage map if true genetic heterogeneity is ignored. We thus conclude that, in general, the lod2 linkage test is more efficient for detecting a true linkage when a complete genetic marker map is screened for a heterogeneous disorder.     

Detecting parent of origin and dominant QTL in a two-generation commercial poultry pedigree using variance component methodology

Introduction

Variance component QTL methodology was used to analyse three candidate regions on chicken chromosomes 1, 4 and 5 for dominant and parent-of-origin QTL effects. Data were available for bodyweight and conformation score measured at 40 days from a two-generation commercial broiler dam line. One hundred dams were nested in 46 sires with phenotypes and genotypes on 2708 offspring. Linear models were constructed to simultaneously estimate fixed, polygenic and QTL effects. Different genetic models were compared using likelihood ratio test statistics derived from the comparison of full with reduced or null models. Empirical thresholds were derived by permutation analysis.

Results

Dominant QTL were found for bodyweight on chicken chromosome 4 and for bodyweight and conformation score on chicken chromosome 5. Suggestive evidence for a maternally expressed QTL for bodyweight and conformation score was found on chromosome 1 in a region corresponding to orthologous imprinted regions in the human and mouse.

Conclusion

Initial results suggest that variance component analysis can be applied within commercial populations for the direct detection of segregating dominant and parent of origin effects.     

Two-locus models of disease: comparison of likelihood and nonparametric linkage methods.

The power to detect linkage for likelihood and nonparametric (Haseman-Elston, affected-sib-pair, and affected-pedigree-member) methods is compared for the case of a common, dichotomous trait resulting from the segregation of two loci. Pedigree data for several two-locus epistatic and heterogeneity models have been simulated, with one of the loci linked to a marker locus. Replicate samples of 20 three-generation pedigrees (16 individuals/pedigree) were simulated and then ascertained for having at least 6 affected individuals. The power of linkage detection calculated under the correct two-locus model is only slightly higher than that under a single locus model with reduced penetrance. As expected, the nonparametric linkage methods have somewhat lower power than does the lod-score method, the difference depending on the mode of transmission of the linked locus. Thus, for many pedigree linkage studies, the lod-score method will have the best power. However, this conclusion depends on how many times the lod score will be calculated for a given marker. The Haseman-Elston method would likely be preferable to calculating lod scores under a large number of genetic models (i.e., varying both the mode of transmission and the penetrances), since such an analysis requires an increase in the critical value of the lod criterion. The power of the affected-pedigree-member method is lower than the other methods, which can be shown to be largely due to the fact that marker genotypes for unaffected individuals are not used.     

Quantitative Trait Locus Analysis of Plasma Cholesterol and Triglyceride Levels in KK × RR F2 Mice

A previous quantitative trait locus (QTL) study on hyperlipidemia in C57BL/6J x KK-Ay/a F2 mice identified three significant cholesterol QTLs (Cq1 and Cq2 on chromosome 1, and Cq3 on chromosome 3), and a suggestive triglyceride QTL on chromosome 9. An alternative analysis of this study identified a novel cholesterol QTL on chromosome 9 (Cq4), and a significant triglyceride QTL on chromosome 9 (Tgq1). In the present study, QTL analysis was performed on KK x RR F2 mice. A significant cholesterol QTL (Cq5, lod score 5.6) was identified on chromosome 9, and a significant triglyceride QTL (Tgq2, lod score 4.7) was identified on chromosome 8. The Cq5 locus was mapped to a region similar to the Cq4 locus. On the other hand, the Tgq2 locus overlapped with the QTL region responsible for glucose intolerance (Giq1) that was identified in a previous study. The results suggest that a different combination of QTLs is involved in the trait when a different counterpart strain is used. Identification of distinct, but related traits in an identical chromosomal region will facilitate revealing the responsible gene.     

A genome scan for Loci associated with aerobic running capacity in rats

Aerobic capacity is a complex trait that defines the efficiency to use atmospheric oxygen as an electron acceptor in energy transfer. Copenhagen (COP) and DA inbred rat strains show a wide difference in a test for aerobic treadmill running and serve as contrasting genetic models for aerobic capacity. A genome scan was carried out on an F(2)(COP x DA) segregating population (n=224) to detect quantitative trait loci (QTLs) associated with aerobic running capacity. Linkage analysis revealed a significant QTL on chromosome 16 (lod score, 4.0). A suggestive linkage was found near the p-terminus of chromosome 3 (lod score, 2.2) with evidence of an interaction with another QTL on chromosome 16 (lod score, 2.9). All three QTLs showed a dominant mode of inheritance in which the presence of at least one DA allele was associated with a greater distance run. These results represent the first aerobic capacity QTLs identified in genetic models.     

Use of maternal information for QTL detection in a (grand)daughter design

In a (grand)daughter design, maternal information is often neglected because the number of progeny per dam is limited. The number of dams per maternal grandsire (MGS), however, could be large enough to contribute to QTL detection. But dams and MGS usually are not genotyped, there are two recombination opportunities between the MGS and the progeny, and at a given location, only half the progeny receive a MGS chromosomal segment. A 3-step procedure was developed to estimate: (1) the marker phenotypes probabilities of the MGS; (2) the probability of each possible MGS haplotype; (3) the probabilities that the progeny receives either the first, or second MGS segment, or a maternal grandam segment. These probabilities were used for QTL detection in a linear model including the effects of sire, MGS, paternal QTL, MGS QTL and maternal grandam QTL. Including the grandam QTL effect makes it possible to detect QTL in the grandam population, even when MGS are not informative. The detection power, studied by simulation, was rather high, provided that MGS family size was greater than 50. Using maternal information in the French dairy cattle granddaughter design made it possible to detect 23 additional QTL genomewise significant.     

Genomic screen for QTLs underlying alcohol consumption in the P and NP rat lines

Selective breeding for voluntary alcohol consumption was utilized to establish the alcohol-preferring (P) and alcohol-nonpreferring (NP) rat lines. Inbreeding was initiated after 30 generations of selection and, after 19 generations of inbreeding, 384 F₂ intercross progeny were created to identify quantitative trait loci (QTLs) influencing alcohol consumption. We had reported previously a QTL on Chromosome (Chr) 4; additional markers genotyped on Chr 4 have increased the maximum lod score from 8.6 to 9.2. This QTL acts in an additive fashion and continues to account for approximately 11% of the phenotypic variability. The 95% confidence interval is 12.5 cM and includes the candidate gene, neuropeptide Y. Subsequent to the identification of the QTL on Chr 4, a genome scan was completed to identify additional QTLs influencing alcohol consumption. A lod score of 2.5 was obtained on Chr 3, syntenic to a region previously reported for alcohol preference in mice. Analysis of Chr 8 produced a lod score of 2.2 near the dopamine D2 and serotonin 1b receptors, which have been previously reported as candidate genes for alcohol preference. Evidence for linkage to alcohol consumption was not found on any other chromosome. It therefore appears likely that, in addition to the QTL on Chr 4, multiple loci of small to moderate effect, such as those on Chrs 3 and 8, underlie the difference in alcohol consumption in the P/NP lines. Received: 15 September 1998 / Accepted: 8 October 1998     

Gender-influenced obesity QTLs identified in a cross involving the KK type II diabetes-prone mouse strain

The inheritance of adiposity and related traits has been investigated in the obese, diabetes-prone KK/HlLt (KK) and the lean, normoglycemic C57BL/6J (B6) mouse strains, their F₁ hybrids, and a large intercross generation. Adiposity index (AI) was defined as the sum of four fat depot weights divided by body weight. Both male and female KK mice were obese, but AI values averaged twofold higher in females than in males. In contrast, B6 females were slightly more lean than males. A genome-wide search revealed several qualitative trait loci (QTLs) affecting AI. The proximal region of Chromosome (Chr) 9 has a large effect on AI, with a much stronger effect in females (lod = 6.3) than in males (lod = 2.7). The data for females fit a model in which a dominant allele from KK increases AI by 30%, with the lod score peak falling between markers D9Mit66 and D9Mit328. This QTL has large effects on inguinal and mesenteric fat pad weights, with smaller effects on gonadal and retroperitoneal fat pads. The region of Chr 9 containing this QTL has extensive homology to human Chr 11q. An X-linked QTL affecting AI was evident in males (lod = 3.77), but not females (lod = 0.7). Exclusion of mesenteric fat from male AI resulted in an increased lod score (lod = 5.0) at 8 cM distal to DXMit166. A suggestive AI QTL (lod = 4.2), differentially affecting males, was localized to Chr 18 near the glucocorticoid receptor locus. A region of Chr 7 had a strong effect on body weight (lod = 6.9), a significant effect on inguinal fat% (lod = 4.4), and a suggestive effect on AI in females (lod = 4.1). Plasma leptin levels were associated with genotypes on Chr 9 (lod = 5.9) and Chr 7 (lod = 4.2). A region of Chr 1 had a suggestive effect on fasted blood glucose (lod = 3.6). Received: 23 March 1999 / Accepted: 2 June 1999     

Advances in Statistical Methods to Map Quantitative Trait Loci in Outbred Populations

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.     

Genome scanning for linkage: an overview.

Several different methods for linkage analysis are shown to arise from a single likelihood function L for the observed allele-sharing data at multiple markers in a chromosomal region. These include classical parametric lod score methods, nonparametric or "model-free" affected pedigree-member (APM) methods, and the Gaussian process method. Setting the methods in the context of the likelihood function L clarifies their underlying assumptions. A test statistic derived from L, the efficient score statistic, is introduced. It is asymptotically equivalent to the lod score, but it can be easier to compute when the penetrances and frequencies of alleles of the trait gene are not known. APM test statistics and the Gaussian lod score are shown to be special cases of efficient score statistics. This unified framework facilitates exploration of a range of models for the effects of a putative trait-predisposing gene, and it facilitates sensitivity analyses to examine the consequences of model misspecification.     

植物QTL定位方法的研究进展

本文系统地介绍了QTL定位的单一标记分析法、区间作图法以及复合区间作图法、混合显性模型的分析方法,概述了一些主要定位方法的分析原理、存在的主要优缺点。单一标记分析法可以采用方差分析、回归分析或似然比检验的方法分析。区间作图法和复合区间作图法是基于两个相邻标记的QTL定位方法,可采用回归分析或最大似然法分析。复合区间作图法在模型中包括了与其他QTL连锁的标记,可以提高作图的精度和效率。混合线性模型的QTL定位方法可以包括复杂的遗传效应及QTL与环境的互作效应,具有更广阔的应用前景。 Abstract:QTL mapping methods are reviewed for single-marker mapping,interval mapping,composite interval mapping,and mixed-model based method.Statistical approaches along with their properties are discussed for the mapping methods.ANOVA,regression method and likelihood ratio test can be applied in single-marker mapping.Interval mapping and composite interval mapping can be conducted,based on two interval markers,by regression method and maximum likelihood method.Since markers linked with other QTLs are include in the model,composite interval mapping is more precision and powerful.Mapping QTL by mixed-model approaches is more applicable when complicated QTL effects as well as QTL by environment interaction are analyzed.     

Congenic strain confirms putative quantitative trait locus for body weight in the rat

Quantitative trait loci (QTLs) affecting body weight were investigated in the backcross population derived from nondiabetic BB/OK and spontaneously hypertensive rat (SHR) strains. The F₁ hybrids were backcrossed onto SHR rats, and QTL analysis was performed separately with the resulting backcross populations for each sex on Chromosomes (Chrs) 1, 3, 4, 10, 13, and 18. The body weight was determined at the age of 14 weeks, and the statistical analysis was performed with MAPMAKER/QTL 1.1b computer program. According to the stringent threshold for a lod score of 3.0, markers on Chr 1 were found to be linked with body weight. The QTL with a peak lod score (5.1) on Chr 1 for a male population was located within markers Igf2 and D1Mgh12. In contrast, in the female population the body weight affecting QTL (lod = 5.7) on Chr 1 was located between the D1Mit3 and Lsn markers. The existence of QTLs on Chr 1 affecting body weight in the male population was confirmed by congenic BB.Sa rats, carrying chromosomal region of SHR (Sa-Igf2) on the genetic background of BB rat. Received: 14 July 1997 / Accepted: 22 December 1997     

A quantitative trait locus mixture model that avoids spurious LOD score peaks

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.     

利用回交B1和B2及F2群体鉴定数量性状两对主基因+多基因混合遗传模型

ＱＴＬ作图和主基因＋多基因混合遗传分析表明：拓展两对基基因＋多基因混合遗传模型十分必要。本文利用混合分布理论,ＡＩＣ准则在回交Ｂ１和Ｂ２群体或Ｆ２群体中鉴定两对主基因的存在,当主基因存在时估计其遗传参数;同时还改进了利用亲本,Ｆ１和回交Ｂ１和Ｂ２群体,或亲本,Ｆ１和Ｆ２群体鉴定多基因存在的方法,分布参数的估计采用ＩＥＣＭ算法,以水稻株高性状为例说明该方法的应用。     

Segregation and linkage studies of plasma dopamine-beta-hydroxylase (DBH), erythrocyte catechol-O-methyltransferase (COMT), and platelet monoamine oxidase (MAO): possible linkage between the ABO locus and a gene controlling DBH activity.

Measurements of dopamine-beta-hydroxylase (DBH), catechol-O-methyltransferase (COMT), and monoamine oxidase (MAO) along with 27 polymorphic marker phenotypes were available for 162 patients with major affective disorders and 1,125 of their relatives. Levels of enzymes were previously found not to be associated with illness. Pedigree analysis methods for quantitative traits are used to test single-gene hypotheses for segregation of DBH in 32 families with 411 individuals. COMT in 30 families with 351 individuals, and MAO in 50 families with 309 individuals. The familial distribution of both DBH and COMT are consistent with two codominant alleles at the same locus that account for 56% and 59% of the total variance, respectively. MAO activity cannot be shown to be segregating as a single major gene, but a purely nongenetic hypothesis is also rejected. A possible linkage of a locus for DBH to the ABO locus is indicated by a maximum lod score of 1.82 at 0% and 10% recombination fractions for males and females, respectively. A lod score of 0.61 at 0% recombination for a similar analysis in a single large pedigree was reported by Elston et al., making the combined lod score for the two studies equal to 2.32 at 0% recombination.     

Linkage disequilibrium fine mapping of quantitative trait loci: A simulation study

Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on single-marker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance.