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PubMed2005

Fine mapping of Lvm1: a quantitative trait locus controlling heart size independently of blood pressure.

We have previously reported a quantitative trait locus (QTL) on rat chromosome 2 that influences heart size independently of blood pressure (Left Ventricular Mass Locus 1; Lvm1). The recent release of the rat genome sequence allowed us to retest and refine this relatively broad QTL with a view to identifying within it candidate genes worthy of structural investigation. We sought to achieve this 'fine mapping' by increasing the marker density within the interval and undertaking a linkage analysis in a previously defined population of F2 hybrids generated from inbred spontaneously hypertensive rats (SHR) of the Okamoto strain and Fischer rat (F344) progenitors. We were able to reconfirm and resolve Lvm1 from its original width of approximately 45 to 15 cM. By reference to the ENSEBL rat genome data bank, we identified within Lvm1 27 known genes, 109 predicted genes and 7 pseudogenes. Of the known genes, candidates include potential regulators of cardiac growth, a sodium channel and calcium channel as well as the fibroblast growth factor 2 gene. Located nearby the Lvm1 locus was the gene for the angiotensin Type 1B receptor. Given the evidence that the ligand for the angiotensin Type 1B receptor-angiotensin II-is a potent cardiotroph, we also consider this gene a potential candidate. The identification of the precise allelic variant(s) within Lvm1 involved in the control of pressure-independent cardiac growth awaits further molecular studies.

Animals↗
PubMed2001

Quantitative trait locus mapping of loci influencing elongation factor 1alpha content in maize endosperm.

The nutritional value of maize (Zea mays) seed is most limited by its protein quality because its storage proteins are devoid of the essential amino acid lysine (Lys). The Lys content of the kernel can be significantly increased by the opaque-2 mutation, which reduces zein synthesis and increases accumulation of proteins that contain Lys. Elongation factor 1alpha (eEF1A) is one of these proteins, and its concentration is highly correlated with the Lys content of the endosperm. We investigated the genetic regulation of eEF1A and the basis for its relationship with other Lys-containing proteins by analyzing the progeny of a cross between a high (Oh51Ao2) and a low (Oh545o2) eEF1A maize inbred. We identified 83 simple sequence repeat loci that are polymorphic between these inbreds; the markers are broadly distributed over the genome (1,402 cM) with an average interval of 17 cM. Genotypic analysis of the F(2) progeny revealed two significant quantitative trait loci that account for 25% of the variance for eEF1A content. One of these is on the short arm of chromosome 4 and is linked with a cluster of 22-kD alpha-zein coding sequences; the other quantitative trait locus is on the long arm of chromosome 7. The content of alpha-zein and gamma-zein was measured in pools of high- and low-eEF1A individuals obtained from this cross, and a higher level of alpha-zein was found to cosegregate with high eEF1A content. Allelic variation at the 22-kD alpha-zein locus may contribute to the difference of eEF1A content between Oh51Ao2 and Oh545o2 by increasing the surface area of protein bodies in the endosperm and creating a more extensive network of cytoskeletal proteins.

Chromosome Mapping↗
PubMed2003

Power of linkage disequilibrium mapping to detect a quantitative trait locus (QTL) in selected samples of unrelated individuals.

We considered a strategy to map quantitative trait loci (QTLs) using linkage disequilibrium (LD) when the QTL and marker locus were multiallelic. The strategy involved phenotyping a large number of unrelated individuals and genotyping only selected individuals from the two tails of the trait distribution. Power to detect trait-marker association was assessed as a function of the number of QTL and marker alleles. Two patterns of LD were used to study their influence on power. When the frequency of the QTL allele with the largest effect and that of the marker allele linked in coupling were equal, power was maximum. In this case, increasing the number of QTL alleles reduced the power. The maximum difference in power between the two LD patterns studied was approximately 30%. For low QTL heritabilities (h2QTL<0.1) and single trait studies we recommend selecting around 5% of the upper and lower tails of the trait distribution.

Chromosome Mapping↗
PubMed1997

General formulas for obtaining the MLEs and the asymptotic variance-covariance matrix in mapping quantitative trait loci when using the EM algorithm.

We present in this paper general formulas for deriving the maximum likelihood estimates and the asymptotic variance-covariance matrix of the positions and effects of quantitative trait loci (QTLs) in a finite normal mixture model when the EM algorithm is used for mapping QTLs. The general formulas are based on two matrices D and Q, where D is the genetic design matrix, characterizing the genetic effects of the QTLs, and Q is the conditional probability matrix of QTL genotypes given flanking marker genotypes, containing the information on QTL positions. With the general formulas, it is relatively easy to extend QTL mapping analysis to using multiple marker intervals simultaneously for mapping multiple QTLs, for analyzing QTL epistasis, and for estimating the heritability of quantitative traits. Simulations were performed to evaluate the performance of the estimates of the asymptotic variances of QTL positions and effects.

Algorithms↗
PubMed2005

Combining data from multiple inbred line crosses improves the power and resolution of quantitative trait loci mapping.

Rodent inbred line crosses are widely used to map genetic loci associated with complex traits. This approach has proven to be powerful for detecting quantitative trait loci (QTL); however, the resolution of QTL locations, typically approximately 20 cM, means that hundreds of genes are implicated as potential candidates. We describe analytical methods based on linear models to combine information available in two or more inbred line crosses. Our strategy is motivated by the hypothesis that common inbred strains of the laboratory mouse are derived from a limited ancestral gene pool and thus QTL detected in multiple crosses are likely to represent shared ancestral polymorphisms. We demonstrate that the combined-cross analysis can improve the power to detect weak QTL, can narrow support intervals for QTL regions, and can be used to separate multiple QTL that colocalize by chance. Moreover, combined-cross analysis can establish the allelic states of a QTL among a set of parental lines, thus providing critical information for narrowing QTL regions by haplotype analysis.

Cholesterol, HDL↗
PubMed1998

Identification of quantitative trait loci affecting carcass composition in swine: II. Muscling and wholesale product yield traits.

A genomic scan was conducted on 540 reciprocal backcross Meishan x White composite pigs for hot carcass weight (HCWT); loin eye area (LOIN); carcass length (CRCL); belly weight (BELLY); and weight of trimmed ham, loin, picnic, and Boston butt adjusted to a constant live (TWPLWT) or carcass (TWPCWT) weight. Genetic markers spanned the entire porcine linkage map and were spaced at approximately 20-cM intervals. Grandparental breed of origin for all chromosomal segments was determined using multipoint linkage procedures, and a least squares regression analysis was conducted. Nominal P-values were converted to a genome-wide level of significance to adjust for the number of tests actually conducted. Seven associations were significant at the genome-wide level relating to chromosomes 1 (SSC 1), 7 (SSC 7), and X (SSC X). The SSC 1 region affected LOIN, TWPLWT, and TWPCWT; SSC 7 affected HWCT and CRCL; and SSC X affected TWPLWT and TWPCWT. Twelve associations relating to seven chromosomal regions (including SSC 1 and X) presented suggestive evidence for quantitative trait loci (QTL), and many of these regions are likely to contain QTL. Chromosomes 8 and 14 had two and three traits with suggestive evidence for QTL, respectively. Many pleiotropic effects were detected for regions on SSC 1, 7, 14, and X in this study and a companion study looking for fat deposition QTL in the same population. In addition, SSC 4 was nearly significant for CRCL in the same region identified as affecting backfat in a wild boar x Large White population. These results expand our knowledge of the inheritance of quantitative traits and are directly relevant to composite populations containing Meishan germplasm.

Alleles↗
PubMed2005

Atherosclerosis quantitative trait loci are sex- and lineage-dependent in an intercross of C57BL/6 and FVB/N low-density lipoprotein receptor-/- mice.

Atherosclerosis is a complex disease that is affected by environmental as well as genetic factors. The aim of the present study was to identify loci of atherosclerosis susceptibility in a cross of atherosclerosis-susceptible C57BL/6 and atherosclerosis-resistant FVB/N mice on the low-density lipoprotein (LDL) receptor (LDLR)-deficient background (LDLR(-/-)) and to test whether these loci are affected by lineage. A total of 459 F(2)s were generated in two ways: In cross "mB6xfFVB," male B6.LDLR(-/-) mice were crossed to female FVB.LDLR(-/-) mice to generate 107 female and 112 male F(2)s. In cross "mFVBxfB6," male FVB.LDLR(-/-) mice were crossed to female B6.LDLR(-/-) mice to generate 120 female and 120 male F(2)s. Animals were phenotyped for cross-sectional atherosclerotic lesion area at the aortic root, and a genome scan was carried out with 192 microsatellite markers. Quantitative trait locus mapping revealed significant loci of atherosclerosis susceptibility on chromosomes 3, 10, and 12. On chromosome 10 maximal logarithm of odds (LOD) scores of 13.1 (D10Mit16, 16 cM) and 5.7 (D10Mit168, 9 cM) were found in female and male mice, respectively. On chromosome 3, a maximal LOD score of 5.1 (D3Mit45, 79 cM) was detected only in females. On proximal chromosome 12 significant LOD scores were lineage-dependent, with maximal LOD scores of 3.9 (D12Mit82, 3 cM) and 4.8 (D12Mit189, 24 cM) present only in female mice of cross mB6xfFVB and male mice of cross mFVBxfB6, respectively. We conclude that, in this intercross, loci of atherosclerosis susceptibility are in part sex- and lineage-dependent. Awareness of these complexities may have major consequences for the identification of atherosclerosis susceptibility genes by quantitative trait locus mapping.

Animals↗
PubMed1981

Estimation of environmental and genetic components of quantitative traits with application to serum cholesterol levels.

A mixed model of environmental, polygenic, and major locus effects is developed, allowing for environmental correlations between first-degree relatives and spouses. Maximum-likelihood techniques are used to determine the relative contributions of each of these effects to a quantitative trait. Inclusion of a nuclear family in the sample is assumed to depend on the value of the quantitative trait of one member of the family, so conditional distributions are used. Application of the method to serum cholesterol data from the general population shows that the addition of a polygenic effect to a model that assumes only an environmental effect makes a significant improvement. A completely dominant single gene is also found to be influencing serum cholesterol levels. Although cholesterol levels have been adjusted for a range of factors, such as age, sex, weight/height, and marital status, environmental factors still account for about half the variability in the residual values.

Adult↗
PubMed2001

Methods for linkage analysis of quantitative trait loci in humans.

This paper reviews linkage analysis methods for detecting loci associated with quantitative traits in humans. All such methods are based on the underlying principle that family members who have similar trait values should have higher than expected levels of sharing of genetic material (identity by descent) near the genes that influence those traits. A number of different statistical methods for testing that association between shared trait values and shared identity by descent have been developed over the past 30 or more years. These different types of tests are reviewed here, with emphasis on their theory and derivations. Robustness and power are also discussed.

Bayes Theorem↗
PubMed2004

[The effect of heterosis on inheritance of quantitative traits in silkworm exposed to electromagnetic irradiation].

The effect of heterosis was studied in several quantitative traits of clone breed and interbreed silkworm hybrids exposed to electromagnetic irradiation (lambda = 1.6 cm, power density 700 microW/cm2) during postdiapause embryonic development. The influence of the type of reproduction on the manifestation of irradiation effects in the next generation was also examined. In hybrids, the resistance to low-intensity high-frequency irradiation was higher than in the parental forms. Unlike the latter, the hybrids showed no significant modification of the traits after the exposure to electromagnetic irradiation. In the second generation, the modifying effect of irradiation is retained in the case of parthenogenetic silkworm development but not after mating.

Animals↗
PubMed2000

Bayesian mapping of quantitative trait loci for complex binary traits.

A complex binary trait is a character that has a dichotomous expression but with a polygenic genetic background. Mapping quantitative trait loci (QTL) for such traits is difficult because of the discrete nature and the reduced variation in the phenotypic distribution. Bayesian statistics are proved to be a powerful tool for solving complicated genetic problems, such as multiple QTL with nonadditive effects, and have been successfully applied to QTL mapping for continuous traits. In this study, we show that Bayesian statistics are particularly useful for mapping QTL for complex binary traits. We model the binary trait under the classical threshold model of quantitative genetics. The Bayesian mapping statistics are developed on the basis of the idea of data augmentation. This treatment allows an easy way to generate the value of a hypothetical underlying variable (called the liability) and a threshold, which in turn allow the use of existing Bayesian statistics. The reversible jump Markov chain Monte Carlo algorithm is used to simulate the posterior samples of all unknowns, including the number of QTL, the locations and effects of identified QTL, genotypes of each individual at both the QTL and markers, and eventually the liability of each individual. The Bayesian mapping ends with an estimation of the joint posterior distribution of the number of QTL and the locations and effects of the identified QTL. Utilities of the method are demonstrated using a simulated outbred full-sib family. A computer program written in FORTRAN language is freely available on request.

Algorithms↗
PubMed2005

Gene networks in hexaploid wheat: interacting quantitative trait loci for grain protein content.

In hexaploid wheat, single-locus and two-locus quantitative trait loci (QTL) analyses for grain protein content (GPC) were conducted using two different mapping populations (PI and PII). Main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL x environment interactions (QE, QQE) were detected using two-locus analyses in both the populations. Only a few QTLs were common in both the analyses, and the QTLs and the interactions detected in the two populations differed, suggesting the superiority of two-locus analysis and the need for using several mapping populations for QTL analysis. A sizable proportion of genetic variation for GPC was due to interactions (28.59% and 54.03%), rather than to M-QTL effects (7.24% and 7.22%), which are the only genetic effects often detected in the majority of QTL studies. Even E-QTLs made a marginal contribution to genetic variation (2.68% and 6.04%), thus suggesting that the major part of genetic variation is due to changes in gene networks rather than the presence or absence of specific genes. This is in sharp contrast to the genetic dissection of pre-harvest sprouting tolerance conducted by us earlier, where interaction effects were not substantial, suggesting that the nature of genetic variation also depends on the nature of the trait.

Plant Proteins↗
PubMed2003

Score tests for epistasis models on quantitative traits using general pedigree data.

Efficient score tests for a two-locus model for quantitative traits are proposed for general pedigrees. Two search strategies, simultaneous search and conditional search, are considered. These tests are attractive alternatives to the likelihood ratio test for their asymptotic equivalency to their respective likelihood ratio tests and efficiency in computation. The finite-sample properties of these tests are investigated through simulations. Extensions to more complicated models and to other search strategies are discussed.

Epistasis, Genetic↗
PubMed1998

Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree.

Quantitative trait loci (QTL) affecting milk production and health of dairy cattle were mapped in a very large Holstein granddaughter design. The analysis included 1794 sons of 14 sires and 206 genetic markers distributed across all 29 autosomes and flanking an estimated 2497 autosomal cM using Kosambi's mapping function. All families were analyzed jointly with least-squares (LS) and variance components (VC) methods. A total of 6 QTL exceeding approximate experiment-wise significance thresholds, 24 QTL exceeding suggestive thresholds, and 34 QTL exceeding chromosome-wise thresholds were identified. Significance thresholds were determined via data permutation (for LS analysis) and chi-square distribution (for VC analysis). The average bootstrap confidence interval for the experiment-wise significant QTL was 48 cM. Some chromosomes harbored QTL affecting several traits, and these were always in coupling phase, defined by consistency with genetic correlations among traits. Chromosome 17 likely harbors 2 QTL affecting milk yield, and some other chromosomes showed some evidence for 2 linked QTL affecting the same trait. In each of these cases, the 2 QTL were in repulsion phase in those families appearing to be heterozygous for both QTL, a finding which supports the build-up of linkage disequilibrium due to selection.

Analysis of Variance↗
PubMed2005

Regression-based quantitative trait loci mapping: robust, efficient and effective.

Regression has always been an important tool for quantitative geneticists. The use of maximum likelihood (ML) has been advocated for the detection of quantitative trait loci (QTL) through linkage with molecular markers, and this approach can be very effective. However, linear regression models have also been proposed which perform similarly to ML, while retaining the many beneficial features of regression and, hence, can be more tractable and versatile than ML in some circumstances. Here, the use of linear regression to detect QTL in structured outbred populations is reviewed and its perceived shortfalls are revisited. It is argued that the approach is valuable now and will remain so in the future.

Genetics, Population↗
PubMed1999

Combined linkage and association sib-pair analysis for quantitative traits.

An extension to current maximum-likelihood variance-components procedures for mapping quantitative-trait loci in sib pairs that allows a simultaneous test of allelic association is proposed. The method involves modeling of the allelic means for a test of association, with simultaneous modeling of the sib-pair covariance structure for a test of linkage. By partitioning of the mean effect of a locus into between- and within-sibship components, the method controls for spurious associations due to population stratification and admixture. The power and efficacy of the method are illustrated through simulation of various models of both real and spurious association.

Genetic Linkage↗
PubMed1999

Multipoint genetic mapping of quantitative trait loci with dominant markers in outbred populations.

We present a multipoint algorithm for mapping quantitative trait loci (QTLs) using dominant markers. The algorithm is designed for outbred populations and is particularly suited for large families. The algorithm works with either codominant or dominant markers, either of which may be interspersed within the same linkage map. Concurrently, the algorithm also partitions dominance variance at the QTL. Computer simulations show that with large families, QTL mapping with dominant markers can be almost as powerful as with bi-allelic, codominant markers. Yet despite this, other situations show a large standard deviation in the estimate of the QTL position, thus making QTL mapping with dominant markers in outbred populations a useful detection tool, albeit limited in its resolution.

Algorithms↗
PubMed2004

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.

Genetic Techniques↗