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Quantitative trait loci influence renal disease progression in a mouse model of Alport syndrome.

Alport syndrome is a human hereditary glomerulonephritis which results in end-stage renal failure (ESRF) in most cases. It is caused by mutations in any one of the collagen alpha3(IV), alpha4(IV), or alpha5(IV) chain genes (COL4A3-COL4A5). Patients carrying identical mutations can exhibit very different disease courses, suggesting that other genes or the environment influence disease progression. We previously generated a knockout mouse model of Alport syndrome by mutating Col4a3. Here, we show that genetic background strongly influences the timing of onset of disease and rate of progression to ESRF in these mice. On the 129X1/SvJ background, Col4a3 -/- mice reached ESRF at approximately 66 days of age, while on the C57BL/6J background, the mean age at ESRF was 194 days of age. This suggests the existence of modifier genes that influence disease progression. A detailed histopathological analysis revealed that glomerular basement membrane lesions typical of Alport syndrome were significantly more frequent in homozygotes on the 129X1/SvJ background than on the C57BL/6J background as early as two weeks of age, suggesting that modifier genes act by influencing glomerular basement membrane structure. Additional data indicated that differential physiological responses to basement membrane splitting also underlie the differences in disease progression. We attempted to map the modifier genes as quantitative trait loci (QTLs) using age at ESRF as the quantitative trait. Genome scans were performed on mice at the two extremes in a cohort of mutant F1 x C57BL/6J backcross mice. Analysis with Map Manager QT revealed QTLs linked to markers on chromosomes 9 and 16. A more detailed understanding of how these QTLs act could lead to new approaches for therapy in diverse renal diseases.

Age Factors↗

Aspartate kinase 2. A candidate gene of a quantitative trait locus influencing free amino acid content in maize endosperm.

The maize (Zea mays) Oh545o2 inbred accumulates an exceptionally high level of free amino acids, especially lysine (Lys), threonine (Thr), methionine, and iso-leucine. In a cross between Oh545o2 and Oh51Ao2, we identified several quantitative trait loci linked with this phenotype. One of these is on the long arm of chromosome 2 and is linked with loci encoding aspartate (Asp) kinase 2 and Asp kinase (AK)-homoserine dehydrogenase (HSDH) 2. To investigate whether these enzymes can contribute to the high levels of Asp family amino acids, we measured their specific activity and feedback inhibition properties, as well as activities of several other key enzymes involved in Lys metabolism. We did not find a significant difference in total activity of dihydrodipicolinate synthase, HSDH, and Lys ketoglutarate reductase between these inbreds, and the feedback inhibition properties of HSDH and dihyrodipicolinate synthase by Lys and/or Thr were similar. The most significant difference we found between Oh545o2 and Oh51Ao2 is feedback inhibition of AK by Lys but not Thr. AK activity in Oh545o2 is less sensitive to Lys inhibition than that in Oh51Ao2, with a Lys I50 twice that of Oh51Ao2. AK activity in Oh545o2 endosperm is also higher than in Oh51Ao2 at 15 d after pollination, but not 20 d after pollination. The results indicate that the Lys-sensitive Asp kinase 2, rather than the Thr-sensitive AK-HSDH2, is the best candidate gene for the quantitative trait locus affecting free amino acid content in Oh545o2.

Abscisic Acid↗

Mapping segregation distortion loci and quantitative trait loci for spikelet sterility in rice ( Oryza sativa L.).

Markers with segregation ratio distortion are commonly observed in data sets used for quantitative trait locus (QTL) mapping. In this study, a multipoint method of maximum likelihood (ML) was newly developed to estimate the positions and effects of the segregation distortion loci (SDLs) in two F2 populations of rice (Oryza sativa L.), i.e. Taichung65/Bhadua (TB; japonica-indica cross) and CPSLO17/W207-2 (CW; japonica-japonica). Of the four parents, W207-2 and Bhadua were found to be spikelet semi-sterile and stably inherited through selfing, and spikelet fertility segregated in the two populations. Therefore, recombination frequencies were recalculated after mapping the SDLs by using the multipoint method, and the molecular linkage maps of the two F2 populations were constructed to detect QTLs underlying spikelet fertility. As a result, five SDLs in the TB population were mapped on chromosomes 1, 3, 8 and 9, respectively. Two major QTLs underlying spikelet fertility, namely qSS-6a and qSS-8a, were detected on chromosomes 6 and 8, respectively. In the CW population, a total of 12 SDLs were detected on all 12 chromosomes except 1, 5, 7 and 11. Three QTLs underlying spikelet sterility, namely qSS-2, qSS-6b and qSS-8b on chromosomes 2, 6 and 8, were determined on the whole genome scale. Interestingly, both qSS-6a and qSS-6b, detected in the two F2 populations respectively, were located on a similar position as the S5 gene on chromosome 6; while qSS-8a and qSS-8b were also simultaneously detected on similar positions of the short arm of chromosome 8 in the two populations, which should be a new sterility gene showing the same type of zygotic selection.

Chromosome Mapping↗

A score test for the linkage analysis of qualitative and quantitative traits based on identity by descent data from sib-pairs.

We propose a general likelihood-based approach to the linkage analysis of qualitative and quantitative traits using identity by descent (IBD) data from sib-pairs. We consider the likelihood of IBD data conditional on phenotypes and test the null hypothesis of no linkage between a marker locus and a gene influencing the trait using a score test in the recombination fraction theta between the two loci. This method unifies the linkage analysis of qualitative and quantitative traits into a single inferential framework, yielding a simple and intuitive test statistic. Conditioning on phenotypes avoids unrealistic random sampling assumptions and allows sib-pairs from differing ascertainment mechanisms to be incorporated into a single likelihood analysis. In particular, it allows the selection of sib-pairs based on their trait values and the analysis of only those pairs having the most informative phenotypes. The score test is based on the full likelihood, i.e. the likelihood based on all phenotype data rather than just differences of sib-pair phenotypes. Considering only phenotype differences, as in Haseman and Elston (1972) and Kruglyak and Lander (1995), may result in important losses in power. The linkage score test is derived under general genetic models for the trait, which may include multiple unlinked genes. Population genetic assumptions, such as random mating or linkage equilibrium at the trait loci, are not required. This score test is thus particularly promising for the analysis of complex human traits. The score statistic readily extends to accommodate incomplete IBD data at the test locus, by using the hidden Markov model implemented in the programs MAPMAKER/SIBS and GENEHUNTER (Kruglyak and Lander, 1995; Kruglyak et al., 1996). Preliminary simulation studies indicate that the linkage score test generally matches or outperforms the Haseman-Elston test, the largest gains in power being for selected samples of sib-pairs with extreme phenotypes.

Journal Article↗

[The effectiveness of selection for the DNA markers of quantitative trait loci in maize populations].

DNA-markers of some agronomically valuable quantitative trait loci were detected by SSR- and ISSR-PCR. Method of genetic improvement of initial population for polygenic trait complex is proposed basing on direct selection of plants according to their genotype marker profiles. Experimental modelling of marker selection within populations (gamma K26 x Mo17) F3-F4 has been carried out. Requirements of marker combination in test systems and criteria of marker informativity have been grounded. Significant effectiveness of marker selection in comparison with traditional methods of selection in maize breeding has been demonstrated.

Crosses, Genetic↗

A genome-wide linkage scan for quantitative trait loci underlying obesity related phenotypes in 434 Caucasian families.

To identify quantitative trait loci (QTLs) that contribute to obesity, we performed a large-scale whole genome linkage scan (WGS) involving 4,102 individuals from 434 Caucasian families. The most pronounced linkage evidence was found at the genomic region 20p11-12 for fat mass (LOD = 3.31) and percentage fat mass (PFM) (LOD = 2.92). We also identified several regions showing suggestive linkage signals (threshold LOD = 1.9) for obesity phenotypes, including 5q35, 8q13, 10p12, and 17q11.

Family↗

Mapping and analysis of quantitative trait loci in experimental populations.

Simple statistical methods for the study of quantitative trait loci (QTL), such as analysis of variance, have given way to methods that involve several markers and high-resolution genetic maps. As a result, the mapping community has been provided with statistical and computational tools that have much greater power than ever before for studying and locating multiple and interacting QTL. Apart from their immediate practical applications, the lessons learnt from this evolution of QTL methodology might also be generally relevant to other types of functional genomics approach that are aimed at the dissection of complex phenotypes, such as microarray assessment of gene expression.

Algorithms↗

Natural variation in neuron number in mice is linked to a major quantitative trait locus on Chr 11.

Common genetic polymorphisms-as opposed to rare mutations-generate almost all heritable differences in the size and structure of the CNS. Surprisingly, these normal variants have not previously been mapped or cloned in any vertebrate species. In a recent paper (), we suggested that much of the variation in retinal ganglion cell number in mice, and the striking bimodality of strain averages, are caused by one or two quantitative trait loci (QTLs). To test this idea, and to map genes linked to this variable and highly heritable quantitative trait, we have counted ganglion cells in 38 recombinant inbred strains (BXD and BXH) derived from parental strains that have high and low cell numbers. A genome-wide search using simple and composite interval-mapping techniques revealed a major QTL on chromosome (Chr) 11 in a 3 cM interval between Hoxb and Krt1 (LOD = 6.8; genome-wide p = 0.001) and possible subsidiary QTLs on Chr 2 and Chr 8. The Chr 11 locus, neuron number control 1 (Nnc1), accounts for one third of the genetic variance among BXH strains and more than half of that among BXD strains, but Nnc1 has no known effects on brain weight, eye weight, or total retinal cell number. Three strong candidate genes have been mapped previously to the same region as Nnc1. These genes-Rara, Thra, and Erbb2- encode receptors for retinoic acid, thyroxine, and neuregulin, respectively. Each receptor is expressed in the retina during development, and their ligands affect the proliferation or survival of retinal cells.

Animals↗

High-resolution mapping of quantitative trait loci for sternopleural bristle number in Drosophila melanogaster.

We have mapped quantitative trait loci (QTL) harboring naturally occurring allelic variation for Drosophila bristle number. Lines with high (H) and low (L) sternopleural bristle number were derived by artificial selection from a large base population. Isogenic H and L sublines were extracted from the selection lines, and populations of X and third chromosome H/L recombinant isogenic lines were constructed in the homozygous low line background. The polymorphic cytological locations of roo transposable elements provided a dense molecular marker map with an average intermarker distance of 4.5 cM. Two X chromosome and six chromosome 3 QTL affecting response to selection for sternopleural bristle number and three X chromosome and three chromosome 3 QTL affecting correlated response in abdominal bristle number were detected using a composite interval mapping method. The average effects of bristle number QTL were moderately large, and some had sex-specific effects. Epistasis between QTL affecting sternopleural bristle number was common, and interaction effects were large. Many of the intervals containing bristle number QTL coincided with those mapped in previous studies. However, resolution of bristle number QTL to the level of genetic loci is not trivial, because the genomic regions containing bristle number QTL often did not contain obvious candidate loci, and results of quantitative complementation tests to mutations at candidate loci affecting adult bristle number were ambiguous.

Alleles↗

Functional mapping for quantitative trait loci governing growth rates: a parametric model.

Are there-specific quantitative trait loci (QTL) governing growth rates in biology? This is emerging as an exciting but challenging question for contemporary developmental biology, evolutionary biology, and plant and animal breeding. In this article, we present a new statistical model for mapping QTL underlying age-specific growth rates. This model is based on the mechanistic relationship between growth rates and ages established by a variety of mathematical functions. A maximum likelihood approach, implemented with the EM algorithm, is developed to provide the estimates of QTL position, growth parameters characterized by QTL effects, and residual variances and covariances. Based on our model, a number of biologically important hypotheses can be formulated concerning the genetic basis of growth. We use forest trees as an example to demonstrate the power of our model, in which a QTL for stem growth diameter growth rates is successfully mapped to a linkage group constructed from polymorphic markers. The implications of the new model are discussed.

Age Factors↗

Mapping temporally varying quantitative trait loci in time-to-failure experiments.

Existing methods for mapping quantitative trait loci (QTL) in time-to-failure experiments assume that the QTL effect is constant over the course of the study. This assumption may be violated when the gene(s) underlying the QTL are up- or downregulated on a biologically meaningful timescale. In such situations, models that assume a constant effect can fail to detect QTL in a whole-genome scan. To investigate this possibility, we utilize an extension of the Cox model (EC model) within an interval-mapping framework. In its simplest form, this model assumes that the QTL effect changes at some time point t0 and follows a linear function before and after this change point. The approximate time point at which this change occurs is estimated. Using simulated and real data, we compare the mapping performance of the EC model to the Cox proportional hazards (CPH) model, which explicitly assumes a constant effect. The results show that the EC model detects time-dependent QTL, which the CPH model fails to detect. At the same time, the EC model recovers all of the QTL the CPH model detects. We conclude that potentially important QTL may be missed if their time-dependent effects are not accounted for.

Chromosome Mapping↗

A multilocus analysis of intraspecific competition and stabilizing selection on a quantitative trait.

The equilibrium structure of an additive, diallelic multilocus model of a quantitative trait under frequency- and density-dependent selection is derived. The trait is under stabilizing selection and mediates intraspecific competition as induced, for instance, by differential resource utilization. It is assumed that stabilizing selection is weak, but the strength of competition may be arbitrary relative to it. Density dependence is caused by population regulation, which may be of a very general kind. The number and effects of loci are arbitrary, and stabilizing selection is not necessarily symmetric with respect to the range of phenotypic values. All previously studied models of intraspecific competition for a continuum of resources known to the author reduce to a special case of the present model if overall selection is weak. Therefore, in this case our results are applicable as approximations to all these models. Our central result is the (nearly) complete characterization of the equilibrium and stability structure in terms of all parameters. It is derived under the sole assumption that selection is weak enough relative to recombination to ignore linkage disequilibrium. In particular, necessary and sufficient conditions on the strength of competition relative to stabilizing selection are found that ensure the maintenance of multilocus polymorphism and the occurrence of disruptive selection. In this case, explicit formulas for the number of polymorphic loci at equilibrium, the allele frequencies, the genetic variance, and the strength of disruptive selection are obtained. For two loci, the effects of linkage are investigated analytically; for several loci, they are studied numerically.

Alleles↗

An empirical Bayes method for updating inferences in analysis of quantitative trait loci using information from related genome scans.

Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective-intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator.

Chromosome Mapping↗

Linkage analysis of 2q14-q23 and 5q32 with blood pressure quantitative traits in Chinese sib pairs.

OBJECTIVES: Several genome-wide scans recently accomplished in the ethnic Chinese revealed a number of candidate loci possibly contributing to essential hypertension, and some appeared to be replicable in 2q14-q23 and 5q32. The current study aimed to examine the linkage of qualitative and blood pressure quantitative traits in essential hypertension with these genomic regions in a large sample of Chinese hypertensive families. METHODS: We performed a genetic analysis on 148 randomly ascertained families containing 328 affected sib pairs, grouped into two geographically distinct subsets. Five highly informative microsatellite markers (D2S151, D2S142, D5S2090, D5S413 and D5S2013) were genotyped, and linkage analyses were performed with different genetic models. RESULTS: We did not observe consistent evidence for excess allele sharing identity by descent in either of the qualitative or the quantitative test. However, higher LOD scores were found at D5S2013 in North Group subset with Haseman-Elston and maximum likelihood (ML) variance (no dominance variance, NDV) algorithms. With the ML (NDV) algorithm, the LOD was 1.410 for diastolic blood pressure at this locus, although this was not statistically significant. CONCLUSIONS: These findings provide no evidence to support a significant linkage of 2q14-q23 or 5q32 with essential hypertension or blood pressure quantitative traits in the ethnic Chinese, and indicate the aetiologic diversity and complexity of hypertension. Previous reports implied 2q14-q23 or beta 2- adrenergic receptor gene potentially linked to essential hypertension in the ethnic Chinese. To replicate these results and perform quantitative linkage analysis, we genotyped members of 148 hypertensive families with five highly informative microsatellite markers. We observed no evidence of excess allele sharing identity by descent in sib pairs, revealing a lack of linkage between 2q14-q23 or 5q32 (chromosome region harboring the gene encoding beta 2 adrenergic receptor) and hypertension in our study sample.

Adult↗

Quantitative trait loci for apolipoprotein B, cholesterol, and triglycerides in familial combined hyperlipidemia pedigrees.

OBJECTIVE: Familial combined hyperlipidemia (FCHL) is a genetically complex lipid disorder that is diagnosed in families by combinations of increased cholesterol, triglycerides, and/or apolipoprotein B (apoB) levels in patients and their first-degree relatives. Identifying the predisposing genes promises to reveal the primary risk factors and susceptibility pathways and suggest methods of prevention and treatment. As with most genetically complex disorders, a clinical definition of disease may not be the most useful phenotype for finding the complement of predisposing genes, and the quantitative traits used to define the disorder can provide important information. This is a report of a quantitative trait loci (QTL) analysis of FCHL. METHODS AND RESULTS: A full genome scan of 377 multi-allelic markers genotyped at approximately 10 centimorgan (cM) intervals was conducted in 150 sibling pairs from 22 nuclear families in FCHL pedigrees. These data were analyzed by 2 multipoint QTL linkage methods using the nonparametric and Haseman-Elston procedures of the Genehunter software. Using a criterion of P<0.001 by the nonparametric analysis, we found evidence of 2 apoB QTL at 1p21-31 (P<0.000009) and 17p11-q21 (P<0.000009), a total serum cholesterol QTL at 12p13 (P<0.0001), and a serum triglycerides QTL at 4p15-16 (P<0.0002). Using the criterion of P<0.03 for at least 2 traits at the same locus, additional evidence for cholesterol (P<0.01) and a triglycerides P<0.02) was observed at 17p11-21, as well as suggestive evidence for apoB (P<0.02) and triglycerides (P<0.01) at 4q34-35, and cholesterol (P<0.01) and triglycerides (P<0.02) and a binary FCHL trait (lod=1.5) at 16p12-13. CONCLUSIONS: QTL analyses of the traits that define FCHL are effective for localizing disease-predisposing genes.

Apolipoproteins B↗

Quantitative trait loci for yield and related traits in the wheat population Ning7840 x Clark.

Grain yield and associated agronomic traits are important factors in wheat (Triticum aestivum L.) improvement. Knowledge regarding the number, genomic location, and effect of quantitative trait loci (QTL) would facilitate marker-assisted selection and the development of cultivars with desirable characteristics. Our objectives were to identify QTLs directly and indirectly affecting grain yield expression. A population of 132 F12 recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese facultative wheat Ning7840 and the US soft red winter wheat Clark. Phenotypic data were collected for 15 yield and other agronomic traits in the RILs and parental lines from three locations in Oklahoma from 2001 to 2003. Twenty-nine linkage groups, consisting of 363 AFLP and 47 SSR markers, were identified. Using composite interval mapping (CIM) analysis, 10, 16, 30, and 14 QTLs were detected for yield, yield components, plant adaptation (shattering and lodging resistance, heading date, and plant height), and spike morphology traits, respectively. The QTL effects ranged from 7 to 23%. Marker alleles from Clark were associated with a positive effect for the majority of QTLs for yield and yield components, but gene dispersion was the rule rather than the exception for this RIL population. Often, QTLs were detected in proximal positions for different traits. Consistent, co-localized QTLs were identified in linkage groups 1AL, 1B, 4B, 5A, 6A, and 7A, and less consistent but unique QTLs were identified on 2BL, 2BS, 2DL, and 6B. Results of this study provide a benchmark for future efforts on QTL identification for yield traits.

Chromosome Mapping↗

Predicting response to selection on a quantitative trait: a comparison between models for mixed-mating populations.

Two different theoretical frameworks have been developed to predict response to selection in a mixed mating population (in which reproduction occurs by a mixture of outcrossing and self-fertilization). The genotypic covariance model (GCM) and the structured linear model (SLM) rely on the same assumptions regarding quantitative trait inheritance, but use different genetic summary statistics. Here, we demonstrate the algebraic relationships between the various genetic metrics used in each theory. This is accomplished by reformulating the GCM in terms of the Wright-Kempthorne equation. We use stochastic simulations to investigate the relative accuracy of each theory for a range of selfing rates. The SLM is generally more accurate than the GCM, the most pronounced differences emerging in simulations with inbreeding depression for fitness. In fact, with strong inbreeding depression and high selfing rates, evolution can occur opposite the direction predicted by the GCM. The simulations also indicate that direct application of random mating models to partially selfing populations can produce very inaccurate predictions if quantitative trait loci exhibit dominance.

Animals↗

Linkage analysis of anorexia and bulimia nervosa cohorts using selected behavioral phenotypes as quantitative traits or covariates.

To increase the likelihood of finding genetic variation conferring liability to eating disorders, we measured over 100 attributes thought to be related to liability to eating disorders on affected individuals from multiplex families and two cohorts: one recruited through a proband with anorexia nervosa (AN; AN cohort); the other recruited through a proband with bulimia nervosa (BN; BN cohort). By a multilayer decision process based on expert evaluation and statistical analysis, six traits were selected for linkage analysis (1): obsessionality (OBS), age at menarche (MENAR), and anxiety (ANX) for quantitative trait locus (QTL) linkage analysis; and lifetime minimum body mass index (BMI), concern over mistakes (CM), and food-related obsessions (OBF) for covariate-based linkage analysis. The BN cohort produced the largest linkage signals: for QTL linkage analysis, four suggestive signals: (for MENAR, at 10p13; for ANX, at 1q31.1, 4q35.2, and 8q13.1); for covariate-based linkage analyses, both significant and suggestive linkages (for BMI, one significant [4q21.1] and three suggestive [3p23, 10p13, 5p15.3]; for CM, two significant [16p13.3, 14q21.1] and three suggestive [4p15.33, 8q11.23, 10p11.21]; and for OBF, one significant [14q21.1] and five suggestive [4p16.1, 10p13.1, 8q11.23, 16p13.3, 18p11.31]). Results from the AN cohort were far less compelling: for QTL linkage analysis, two suggestive signals (for OBS at 6q21 and for ANX at 9p21.3); for covariate-based linkage analysis, five suggestive signals (for BMI at 4q13.1, for CM at 11p11.2 and 17q25.1, and for OBF at 17q25.1 and 15q26.2). Overlap between the two cohorts was minimal for substantial linkage signals.

Anorexia Nervosa↗