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PubMed2001

Mapping quantitative trait loci in oligogenic models.

We discuss strategies for mapping quantitative trait loci with emphasis on certain issues of study design that have recently received attention: e.g. genotyping only selected pedigrees and the comparative value of large pedigrees versus sib pairs. We use a standard variance components model and a parametrization of the genetic effects in which the 'segregation' parameters are locally orthogonal to the 'linkage' parameters. This permits simple explicit expressions for the expectation of the score statistic, which we use to compare the power of different strategies. We also discuss robustness of the score statistic.

Journal Article↗

PubMed1994

Precision mapping of quantitative trait loci.

Adequate separation of effects of possible multiple linked quantitative trait loci (QTLs) on mapping QTLs is the key to increasing the precision of QTL mapping. A new method of QTL mapping is proposed and analyzed in this paper by combining interval mapping with multiple regression. The basis of the proposed method is an interval test in which the test statistic on a marker interval is made to be unaffected by QTLs located outside a defined interval. This is achieved by fitting other genetic markers in the statistical model as a control when performing interval mapping. Compared with the current QTL mapping method (i.e., the interval mapping method which uses a pair or two pairs of markers for mapping QTLs), this method has several advantages. (1) By confining the test to one region at a time, it reduces a multiple dimensional search problem (for multiple QTLs) to a one dimensional search problem. (2) By conditioning linked markers in the test, the sensitivity of the test statistic to the position of individual QTLs is increased, and the precision of QTL mapping can be improved. (3) By selectively and simultaneously using other markers in the analysis, the efficiency of QTL mapping can be also improved. The behavior of the test statistic under the null hypothesis and appropriate critical value of the test statistic for an overall test in a genome are discussed and analyzed. A simulation study of QTL mapping is also presented which illustrates the utility, properties, advantages and disadvantages of the method.

Chromosome Mapping↗

PubMedDate not supplied

Trade-off between sibship size and sampling scheme for detecting quantitative trait loci.

There is general consensus that linkage with a quantitative trait locus cannot be detected with a reasonable number of sibpairs unless that trait has a very high heritability or the pairs are highly selected. However, the latter may require the screening of a very large number of pairs before a relatively small number of highly informative pairs is attained. At the same time, it is known that, for the same number of typed individuals, larger sibships tend to provide more linkage information than do independent sibpairs. We thus compared the efficiency of two sampling schemes, (1) random and (2) single ascertainment via an individual with an extreme phenotype, for sibship sizes ranging from two to five. The results demonstrate the clear trade-off between sibship size and the stringency of the ascertainment scheme.

Genes, Recessive↗

PubMed2003

Quantitative trait locus analysis of plasma cholesterol and triglyceride levels in KK x 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.

Alleles↗

PubMed2005

A powerful and robust method for mapping quantitative trait loci in general pedigrees.

The variance-components model is the method of choice for mapping quantitative trait loci in general human pedigrees. This model assumes normally distributed trait values and includes a major gene effect, random polygenic and environmental effects, and covariate effects. Violation of the normality assumption has detrimental effects on the type I error and power. One possible way of achieving normality is to transform trait values. The true transformation is unknown in practice, and different transformations may yield conflicting results. In addition, the commonly used transformations are ineffective in dealing with outlying trait values. We propose a novel extension of the variance-components model that allows the true transformation function to be completely unspecified. We present efficient likelihood-based procedures to estimate variance components and to test for genetic linkage. Simulation studies demonstrated that the new method is as powerful as the existing variance-components methods when the normality assumption holds; when the normality assumption fails, the new method still provides accurate control of type I error and is substantially more powerful than the existing methods. We performed a genomewide scan of monoamine oxidase B for the Collaborative Study on the Genetics of Alcoholism. In that study, the results that are based on the existing variance-components method changed dramatically when three outlying trait values were excluded from the analysis, whereas our method yielded essentially the same answers with or without those three outliers. The computer program that implements the new method is freely available.

Chromosome Mapping↗

PubMed2006

A quantitative trait locus analysis of natural genetic variation for Drosophila melanogaster oxidative stress survival.

Little is known about natural genetic variation for survival under oxidative stress conditions or whether genetic variation for oxidative stress survival is associated with that for life-history traits. We have investigated survival in a high-oxygen environment at 2 adult densities using a set of recombinant inbred lines (RILs) isolated from a natural population of Drosophila melanogaster. Female and male oxidative stress survival was highly correlated. Quantitative trait loci (QTLs) for oxidative stress survival were identified on both autosomes. These QTLs were sometimes sex or density specific but were most often not. QTLs were identified that colocalize to the same region of the genome as longevity in other studies using the same set of RILs. We also determined early-age egg production and found QTLs for this trait, but there was no support for an association between oxidative stress survival and egg production.

Age Factors↗

PubMed2004

Quantitative trait Loci specifying the response of body temperature to dietary restriction.

Dietary restriction (DR) retards aging and mortality across a variety of taxa. In homeotherms, one of the hallmarks of DR is lower mean body temperature (T(b)), which might be directly responsible for some aspects of DR-mediated life extension. We conducted a quantitative trait locus (QTL) analysis of the response of T(b) to DR in mice using a panel of 22 LSXSS recombinant inbred strains, tested in two cohorts. T(b) in response to DR had a significant genetic component, explaining approximately 35% of the phenotypic variation. We mapped a statistically significant QTL to chromosome 9 and a provisional QTL to chromosome 17, which together accounted for about two thirds of the genetic variation. Such QTLs could be used to critically test whether the response of T(b) to DR also affects the response of life extension. In addition, this study demonstrates the feasibility of trying to map QTLs that affect other physiological responses to DR, including the life extension response. Importantly, the genes underlying such QTLs would be causal factors affecting these responses and could be identified by positional cloning.

Aging↗

PubMed2003

Rank-based statistical methodologies for quantitative trait locus mapping.

This article addresses the identification of genetic loci (QTL and elsewhere) that influence nonnormal quantitative traits with focus on experimental crosses. QTL mapping is typically based on the assumption that the traits follow normal distributions, which may not be true in practice. Model-free tests have been proposed. However, nonparametric estimation of genetic effects has not been studied. We propose an estimation procedure based on the linear rank test statistics. The properties of the new procedure are compared with those of traditional likelihood-based interval mapping and regression interval mapping via simulations and a real data example. The results indicate that the nonparametric method is a competitive alternative to the existing parametric methodologies.

Crosses, Genetic↗

PubMed2001

The power of transmission disequilibrium tests for quantitative traits.

We develop a score statistic to test for linkage in the presence of linkage disequilibrium for quantitative traits. We then extend this method to analyze multiple tightly linked markers. One potential limitation with the use of many genetic markers is the large number of degrees of freedom involved that may reduce the overall power to detect linkage. To overcome this limitation, we propose to group haplotypes on the basis of haplotype similarity before performing transmission disequilibrium tests. Finally, we apply these methods to the Genetic Analysis Workshop 12 simulated data and compare their power.

Adult↗

PubMed2006

Quantitative trait loci for IQ and other complex traits: single-nucleotide polymorphism genotyping using pooled DNA and microarrays.

Similar to other complex traits, it is likely that many DNA polymorphisms of small effect size [quantitative trait loci (QTLs)] are responsible for the high heritability of intelligence, in addition to many rare monogenic disorders known to contribute to lowered intelligence. We review the current status of approaches to identify QTLs associations for intelligence employing genome-wide strategies using pooled DNA from many individuals and evaluate the innovative approach of microarray analysis to genotype DNA pools for large numbers of single nucleotide polymorphisms.

DNA↗

PubMed2001

Quantitative trait loci mapping associated with plant regeneration ability from seed derived calli in rice (Oryza sativa L.).

Quantitative trait loci (QTLs), which are associated with the ability of plant regeneration from seed derived calli, were detected using a recombinant inbred (RI) population from a cross between 'Milyang 23 (toingil)' and 'Gihobyeo (japonica)' in rice (Oryza sativa L.). A tongil type cultivar, 'Milyang 23', has a lower frequency of callus induction and plant regeneration than those of japonica 'Gihobyeo'. Transgressive segregations were observed for the callus induction rate and plant regeneration ability from seed derived calli of the RI population. An interval mapping analysis was used to identify the QTL controlling the plant regeneration ability. Two QTLs for the callus induction rate were detected on chromosomes 1 and 2, explaining the 10.9% total phenotypic variation. Four QTLs that are associated with the plant regeneration ability were located on chromosomes 2, 3, and 11, accounting for 25.7% of the total phenotypic variation.

Chromosome Mapping↗

PubMed2002

Simultaneous detection and fine mapping of quantitative trait loci in mice using heterogeneous stocks.

We describe a method to simultaneously detect and fine map quantitative trait loci (QTL) that is especially suited to the mapping of modifier loci in mouse mutant models. The method exploits the high level of historical recombination present in a heterogeneous stock (HS), an outbred population of mice derived from known founder strains. The experimental design is an F(2) cross between the HS and a genetically distinct line, such as one carrying a knockout or transgene. QTL detection is performed by a standard genome scan with approximately 100 markers and fine mapping by typing the same animals using densely spaced markers over those candidate regions detected by the scan. The analysis uses an extension of the dynamic-programming technique employed previously to fine map QTL in HS mice. We show by simulation that a QTL accounting for 5% of the total variance can be detected and fine mapped with >50% probability to within 3 cM by genotyping approximately 1500 animals.

Animals↗

PubMed1998

Multipoint genetic mapping of quantitative trait loci using a variable number of sibs per family.

We present a multipoint algorithm to map quantitative trait loci (QTLs) using families from outbred populations with a variable number of sibs. The algorithm uses information from all markers on a chromosome simultaneously to extract information of QTL segregation. A previous multipoint method (Kruglyak & Lander (1995) American Journal of Human Genetics 57, 439-454) extracts information using a hidden Markov model. However, this method is restricted to small families (< 10 sibs). We present an approximate hidden Markov model approach that can handle large sibships while retaining similar efficiency to the previous method. Computer simulations support the notion that data sampled from a small number of large families provide more power than data obtained from a large number of small families, under the constraint that the total number of individuals for the two schemes is the same. This is further reflected in simulations with variable family sizes, where variance in family size improves the statistical power of QTL detection relative to a constant size control.

Chromosome Mapping↗

PubMed2002

Fine linkage mapping of the blood pressure quantitative trait locus region on rat chromosome 1.

To narrow the area known to contain the blood pressure quantitative trait locus (QTL) on rat chromosome 1, we constructed a fine linkage map covering the blood pressure OTL region on the chromosome using 22 genetic markers informative for stroke-prone spontaneously hypertensive rats of the Izumo colony (SHRSP/Izm) and Wistar-Kyoto rats of the Izumo colony (WKY/Izm). Linkage mapping was done by genotyping 626 backcrossed rats from matings between SHRSP/Izm and WKY/Izm. Nineteen genetic markers informative for the two strains were selected from public databases. Two markers were newly isolated by screening a rat genomic library. One marker was mapped using a restriction endonuclease polymorphism. The region between DlWox29 and D1Smu11 was covered with 22 informative markers placed every 0.6 cM on average. In addition, 6 physiological candidates for a hypertension gene were mapped in this region either by linkage or by radiation hybrid (RH) mapping. This information should be essential for the construction and analysis of congenic strains for this QTL region.

Animals↗

PubMed2002

Efficient score statistics for mapping quantitative trait loci with extended pedigrees.

The method of variance components is the method of choice for mapping quantitative trait loci (QTLs) with general pedigrees. Being a likelihood-based method, this method can be computation intensive even for nuclear families, and has excessive false positive rates under some situations. Here two efficient score statistics to detect QTLs are derived, one assumes that the candidate locus has no dominance effect, and the other one does not make such an assumption. These two score statistics are asymptotically equivalent to the method of variance components but they are easier to compute and more robust than the likelihood ratio statistic. The derivation of these score statistics is facilitated by separating the segregation parameters, the parameters that describe the distribution of the phenotypic value in the population, from the linkage parameters, the parameters that measure the effect of the candidate locus on the phenotypic value. Such a separation of the model parameters greatly reduces the number of parameters to be dealt with in the analysis of linkage. The asymptotic distributions of both score statistics are derived. Simulation studies indicate that, compared to the method of variance components, both score statistics have comparable or higher power, and their false-positive rates are closer to their respective nominal significance levels.

Chromosome Mapping↗

PubMed2005

Severe hypertension caused by alleles from normotensive Lewis for a quantitative trait locus on chromosome 2.

Pursuing fully a suggestion from linkage analysis that there might be a quantitative trait locus (QTL) for blood pressure (BP) in a chromosome (Chr) 2 region of the Dahl salt-sensitive rat (DSS), four congenic strains were made by replacing various fragments of DSS Chr 2 with those of Lewis (LEW). Consequently, a BP QTL was localized to a segment of around 3 cM or near 3 Mb on Chr 2 by comparative congenics. The BP-augmenting alleles of this QTL originated from the LEW rat, a normotensive strain compared with DSS. The dissection of a QTL with such a paradoxical effect illustrated the power of congenics in unearthing a gene hidden in the context of the whole animal system, presumably by interactions with other genes. The locus for the angiotensin II receptor AT-1B (Agtr1b) is not supported as a candidate gene for the QTL because a congenic strain harboring it did not have an effect on BP. There are approximately 19 known and unknown genes present in the QTL interval. Among them, no standout candidate genes are reputed to affect BP. Thus the QTL will likely represent a novel gene for BP regulation.

Alleles↗

PubMed2002

The genetic variance for multiple linked quantitative trait loci conditional on marker information in a crossed population.

In the prediction of genetic values and quantitative trait loci (QTLs) mapping via the mixed model method incorporating marker information in animal populations, it is important to model the genetic variance for individuals with an arbitrary pedigree structure. In this study, for a crossed population originated from different genetic groups such as breeds or outbred strains, the variance of additive genetic values for multiple linked QTLs that are contained in a chromosome segment, especially the segregation variance, is investigated assuming the use of marker data. The variance for a finite number of QTLs in one chromosomal segment is first examined for the crossed population with the general pedigree. Then, applying the concept of the expectation of identity-by-descent proportion, an approximation to the mean of the conditional probabilities for the linked QTLs over all loci is obtained, and using it an expression for the variance in the case of an infinite number of linked QTLs marked by flanking markers is derived. It appears that the approach presented can be useful in the segment mapping using, and in the genetic evaluation of, crosses with general pedigrees in the population of concern. The calculation of the segregation variance through the current approach is illustrated numerically, using a small data-set.

Genetic Linkage↗

PubMed2000

A general mixture model approach for mapping quantitative trait loci from diverse cross designs involving multiple inbred lines.

Most current statistical methods developed for mapping quantitative trait loci (QTL) based on inbred line designs apply to crosses from two inbred lines. Analysis of QTL in these crosses is restricted by the parental genetic differences between lines. Crosses from multiple inbred lines or multiple families are common in plant and animal breeding programmes, and can be used to increase the efficiency of a QTL mapping study. A general statistical method using mixture model procedures and the EM algorithm is developed for mapping QTL from various cross designs of multiple inbred lines. The general procedure features three cross design matrices, W, that define the contribution of parental lines to a particular cross and a genetic design matrix, D, that specifies the genetic model used in multiple line crosses. By appropriately specifying W matrices, the statistical method can be applied to various cross designs, such as diallel, factorial, cyclic, parallel or arbitrary-pattern cross designs with two or multiple parental lines. Also, with appropriate specification for the D matrix, the method can be used to analyse different kinds of cross populations, such as F2 backcross, four-way cross and mixed crosses (e.g. combining backcross and F2). Simulation studies were conducted to explore the properties of the method, and confirmed its applicability to diverse experimental designs.

Animals↗