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PubMed2003

Molecular and quantitative trait variation within and among populations of the intertidal copepod Tigriopus californicus.

While molecular and quantitative trait variation may be theoretically correlated, empirical studies using both approaches frequently reveal discordant patterns, and these discrepancies can contribute to our understanding of evolutionary processes. Here, we assessed genetic variation in six populations of the copepod Tigriopus californicus. Molecular variation was estimated using five polymorphic microsatellite loci, and quantitative variation was measured using 22-life history and morphometric characters. Within populations, no correlation was found between the levels of molecular variation (heterozygosity) and quantitative variation (heritability). Between populations, quantitative subdivision (Q(ST)) was correlated with molecular subdivision when measured as F(ST) but not when measured as R(ST). Unlike most taxa studied to date, the overall level of molecular subdivision exceeded the level of quantitative subdivision (F(ST) = 0.80, R(ST) = 0.89, Q(ST) = 0.30). Factors that could contribute to this pattern include stabilizing or fluctuating selection on quantitative traits or accelerated rates of molecular evolution.

Animals↗
PubMedDate not supplied

A sib-pair regression model of linkage disequilibrium for quantitative traits.

A multiple-regression model is described for the detection of linkage disequilibrium in quantitative trait loci. The model is developed for application to large numbers of single nucleotide polymorphism (SNP) markers genotyped on small nuclear families. Parental data are not required by the method, although it provides a direct means to test quantitative trait locus-marker allele association and to determine whether any such association is attributable to linkage disequilibrium or population admixture. Analytical expectations for the regression coefficients are derived, allowing direct interpretation of the parameter estimates. Simulation studies indicate a substantial improvement in power over classical linkage studies of sibling pairs and show the effects of population admixture on the model outcomes.

Humans↗
PubMed1999

Quantitative trait loci for blood pressure exist near the IGF-1, the Liddle syndrome, the angiotensin II-receptor gene and the renin loci in man.

Blood pressure (BP) is heritable and finding quantitative trait loci that influence BP is an important step in identifying genes responsible for BP regulation. Sixty-six pairs of dizygotic (DZ) twin subjects and their parents were used in a sib-pair analysis to look for linkage of selected candidate genes to the quantitative trait BP. Microsatellite markers were tested in the vicinity of the gene loci for insulin-like growth factor-1 (IGF-1), Liddle syndrome, autosomal-dominant hypertension with brachydactyly, angiotensinogen, angiotensin II type 1 receptor, angiotensin-converting enzyme, renin, and lipoprotein lipase. BP was measured in a standardized manner. Heart size was determined echocardiographically. Significant linkage was found at the IGF-1, Liddle syndrome, and AT1 receptor gene for systolic BP. Linkage for diastolic BP was found at the autosomal-dominant hypertension with brachydactyly locus. Both systolic and diastolic BP were linked to the renin gene locus. The linkage was most consistent for the IGF-1 gene locus and systolic BP. Linkage was also found between the IGF-1 gene locus and posterior cardiac wall thickness, septal thickness, and left ventricular mass index. It is suggested that these quantitative trait loci may be important for the subsequent detection of allelic variants for elevated BP. Furthermore, these results linking the IGF-1 gene locus to both BP and cardiac dimensions underscore the importance of the IGF-1 gene as a candidate gene for cardiovascular disease.

Adult↗
PubMed2004

Genetic and functional confirmation of the causality of the DGAT1 K232A quantitative trait nucleotide in affecting milk yield and composition.

We recently used a positional cloning approach to identify a nonconservative lysine to alanine substitution (K232A) in the bovine DGAT1 gene that was proposed to be the causative quantitative trait nucleotide underlying a quantitative trait locus (QTL) affecting milk fat composition, previously mapped to the centromeric end of bovine chromosome 14. We herein generate genetic and functional data that confirm the causality of the DGAT1 K232A mutation. We have constructed a high-density single-nucleotide polymorphism map of the 3.8-centimorgan BULGE30-BULGE9 interval containing the QTL and show that the association with milk fat percentage maximizes at the DGAT1 gene. We provide evidence that the K allele has undergone a selective sweep. By using a baculovirus expression system, we have expressed both DGAT1 alleles in Sf9 cells and show that the K allele, causing an increase in milk fat percentage in the live animal, is characterized by a higher Vmax in producing triglycerides than the A allele.

Acyltransferases↗
PubMed2005

Quantitative trait nucleotide analysis using Bayesian model selection.

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Bayes Theorem↗
PubMed2004

Mapping quantitative trait Loci interactions from the maternal and offspring genomes.

The expression of most developmental or behavioral traits involves complex interactions between quantitative trait loci (QTL) from the maternal and offspring genomes. The maternal-offspring interactions play a pivotal role in shaping the direction and rate of evolution in terms of their substantial contribution to quantitative genetic (co)variation. To study the genetics and evolution of maternal-offspring interactions, a unifying statistical framework that embraces both the direct and indirect genetic effects of maternal and offspring QTL on any complex trait is developed. This model is derived for a simple backcross design within the maximum-likelihood context, implemented with the EM algorithm. Results from extensive simulations suggest that this model can provide reasonable estimation of additive and dominant effects of the QTL at different generations and their interaction effects derived from the maternal and offspring genomes. Although our model is framed to characterize the actions and interactions of maternal and offspring QTL affecting offspring traits, the idea can be readily extended to decipher the genetic machinery of maternal traits, such as maternal care. Our model provides a powerful means for studying the evolutionary significance of indirect genetic effects in any sexually reproductive organisms.

Animals↗
PubMed2002

Vanaso is a candidate quantitative trait gene for Drosophila olfactory behavior.

Most animals depend on olfaction for survival and procreation. Odor-guided behavior is a quantitative trait, with phenotypic variation due to multiple segregating quantitative trait loci (QTL). Despite its profound biological importance, the genetic basis of naturally occurring variation in olfactory behavior remains unexplored. Here, we mapped a single Drosophila QTL affecting variation in avoidance response to benzaldehyde, using a population of recombinant inbred lines. Deficiency complementation mapping resolved this region into one female- and one male-specific QTL. Subsequent quantitative complementation tests to all available mutations of positional candidate genes showed that the female-specific QTL failed to complement a P-element insertional mutation, l(3)04276. The P-element insertion was in the intron of a novel gene, Vanaso, which contains a putative guanylate binding protein domain, is highly polymorphic, and is expressed in the third antennal segment, the major olfactory organ of Drosophila. No expression was detected in the fly brain, suggesting that Vanaso plays a role in peripheral chemosensory processes rather than in central integration of olfactory information. QTL mapping followed by quantitative complementation tests to deficiencies and mutations is an effective strategy for gene discovery that allows characterization of effects of recessive lethal genes on adult phenotypes and here enabled identification of a candidate gene that contributes to sex-specific quantitative variation in olfactory behavior.

Amino Acid Sequence↗
PubMed2005

A new method of linkage analysis using LOD scores for quantitative traits supports linkage of monoamine oxidase activity to D17S250 in the Collaborative Study on the Genetics of Alcoholism pedigrees.

OBJECTIVE: Although LOD score methods have been applied to diseases with complex modes of inheritance, linkage analysis of quantitative traits has tended to rely on non-parametric methods based on regression or variance components analysis. Here, we describe a new method for LOD score analysis of quantitative traits which does not require specification of a mode of inheritance. METHODS: The technique is derived from the MFLINK method for dichotomous traits. A range of plausible transmission models is constructed, constrained to yield the correct population mean and variance for the trait but differing with respect to the contribution to the variance due to the locus under consideration. Maximized LOD scores under homogeneity and admixture are calculated, as is a model-free LOD score which compares the maximized likelihoods under admixture assuming linkage and no linkage. These LOD scores have known asymptotic distributions and hence can be used to provide a statistical test for linkage. The method has been implemented in a program called QMFLINK. It was applied to data sets simulated using a variety of transmission models and to a measure of monoamine oxidase activity in 105 pedigrees from the Collaborative Study on the Genetics of Alcoholism. RESULTS: With the simulated data, the results showed that the new method could detect linkage well if the true allele frequency for the trait was close to that specified. However, it performed poorly on models in which the true allele frequency was much rarer. For the Collaborative Study on the Genetics of Alcoholism data set only a modest overlap was observed between the results obtained from the new method and those obtained when the same data were analysed previously using regression and variance components analysis. Of interest is that D17S250 produced a maximized LOD score under homogeneity and admixture of 2.6 but did not indicate linkage using the previous methods. However, this region did produce evidence for linkage in a separate data set, suggesting that QMFLINK may have been able to detect a true linkage which was not picked up by the other methods. CONCLUSION: The application of model-free LOD score analysis to quantitative traits is novel and deserves further evaluation of its merits and disadvantages relative to other methods.

Alcoholism↗
PubMed2005

A computational method to detect epistatic effects contributing to a quantitative trait.

We develop a new computational method to detect epistatic effects that contribute to a complex quantitative trait. Rather than looking for epistatic effects that show statistical significance when considered in isolation, we search for a close approximation to the quantitative trait by a sum of epistatic effects. Our search algorithm consists of a sequence of random walks around the space of sums of epistatic effects. An important feature of our approach is that there is learning between random walks, i.e. the control mechanism that chooses steps in our random walks adapts to the experiences of earlier random walks. We test the effectiveness of our algorithms by applying them to synthetic datasets where the phenotype is a sum of epistatic effects plus normally distributed noise. Our test statistic is the rate of success that our methods achieve in identifying the underlying epistatic effects. We report on the effectiveness of our methods as we vary parameters that are intrinsic to the computation (length of random walks and degree of learning) as well as parameters that are extrinsic to the computation (number of markers, number of individuals, noise level, architecture of the epistatic effects).

Algorithms↗
PubMed1993

Evaluating linkage between DNA fingerprint bands and quantitative traits in chickens: interactions.

This study assessed the influence of background genome on expression of genes linked to DNA fingerprint (DFP) bands in chickens. Two experimental lines of White Plymouth Rocks previously selected for high or low 8-wk body weight were crossed to produce two F1 males that served as heads of two sire families. Each of these sires was mated to three hens from an unrelated White Leghorn population to produce progeny in which quantitative traits of 4-, 8-, and 12-wk body weight and shank length at 12 wk were measured. The DFP patterns were produced for all individuals in the study. For the 12 sire-specific DFP bands (common to both F1 sires but not found in the dams), each offspring was classified as having or not having each band. Then, an analysis of variance was conducted for each DFP sire band with sex, hatch, dam family, and presence or absence of the sire band as main effects. Interactions between dam family and presence or absence of sire band were also tested. Of 48 possible analyses of variance (12 sire bands by 4 quantitative traits), 3 resulted in significant effects due to sire band, and 2 indicated significant interactions. Thus, associations of a DFP band and a gene coding for a quantitative trait were present, but, in some cases, the expression of the trait differed, depending on the dam family in which it occurred. These data suggest that associations between DFP bands and quantitative traits may not be consistent in different genetic backgrounds.

Animals↗
PubMed2006

A population-based latent variable approach for association mapping of quantitative trait loci.

A population-based latent variable approach is proposed for association mapping of quantitative trait loci (QTL), using multiple closely linked genetic markers within a small candidate region in the genome. By incorporating QTL as latent variables into a penetrance model, the QTL are flexible to characterize either alleles at putative trait loci or potential risk haplotypes/sub-haplotypes of the markers. Under a general likelihood framework, we develop an EM-based algorithm to estimate genetic effects of the QTL and haplotype frequencies of the QTL and markers jointly. Closed form solutions derived in the maximization step of the EM procedure for updating the joint haplotype frequencies of QTL and markers can effectively reduce the computational intensity. Various association measures between QTL and markers can then be derived from the haplotype frequencies of markers and used to infer QTL positions. The likelihood ratio statistic also provides a joint test for association between a quantitative trait and marker genotypes without requiring adjustment for the multiple testing. Extensive simulation studies are performed to evaluate the approach.

Algorithms↗
PubMed2006

Substitution mapping of dth1.1, a flowering-time quantitative trait locus (QTL) associated with transgressive variation in rice, reveals multiple sub-QTL.

A quantitative trait locus (QTL), dth1.1, was associated with transgressive variation for days to heading in an advanced backcross population derived from the Oryza sativa variety Jefferson and an accession of the wild rice relative Oryza rufipogon. A series of near-isogenic lines (NILs) containing different O. rufipogon introgressions across the target region were constructed to dissect dth1.1 using substitution mapping. In contrast to the late-flowering O. rufipogon parent, O. rufipogon alleles in the substitution lines caused early flowering under both short- and long-day lengths and provided evidence for at least two distinct sub-QTL: dth1.1a and dth1.1b. Potential candidate genes underlying these sub-QTL include genes with sequence similarity to Arabidopsis GI, FT, SOC1, and EMF1, and Pharbitis nil PNZIP. Evidence from families with nontarget O. rufipogon introgressions in combination with dth1.1 alleles also detected an early flowering QTL on chromosome 4 and a late-flowering QTL on chromosome 6 and provided evidence for additional sub-QTL in the dth1.1 region. The availability of a series of near-isogenic lines with alleles introgressed from a wild relative of rice provides an opportunity to better understand the molecular basis of transgressive variation in a quantitative trait.

Alleles↗
PubMed1998

Least squares interval mapping of quantitative trait loci under the infinitesimal genetic model in outbred populations.

Genetic marker and phenotypic data for a quantitative trait were simulated on 20 paternal half-sib families with 100 progeny to investigate properties of within-family-regression interval mapping of a postulated single quantitative trait locus (QTL) in a marker interval under the infinitesimal genetic model, which has been the basis of the application of quantitative genetics to genetic improvement programs, and to investigate use of the infinitesimal model as null hypothesis in testing for presence of a major QTL. Genetic effects on the marked chromosome were generated based on a major gene model, which simulated a central biallelic QTL, or based on 101 biallelic QTL of equal effect, which approximated the infinitesimal model. The marked chromosome contained 0, 3.3%, 13.3%, or 33.3% of genetic variance and heritability was 0.25 or 0.70. Under the polygenic model with 3.3% of genetic variance on the marked chromosome, which corresponds to the infinitesimal model for the bovine, significant QTL effects were found for individual families. Correlations between estimates of QTL effects and true chromosome substitution effects were 0.29 and 0.47 for heritabilities of 0.25 and 0.70 but up to 0.85 with 33.3% of polygenic variance on the marked chromosome. These results illustrate the potential of marker-assisted selection even under the infinitesimal genetic model. Power of tests for presence of QTL was substantially reduced when the polygenic model with 3.3% of genetic variance on the chromosome was used as a null hypothesis. The ability to determine whether genetic variance on a chromosome was contributed by a single QTL of major effect or a large number of QTL with minor effects, corresponding to the infinitesimal model, was limited.

Chromosome Mapping↗
PubMed2006

Quantitative trait loci associated with parasitic infection in Scottish blackface sheep.

This study aimed to identify quantitative trait loci associated with endoparasitic infection in Scottish Blackface sheep. Data were collected from 789 animals over a 3-year period. All of the animals were continually exposed to a mixed nematode infection by grazing. Faecal samples were collected in August, September and October each year at ca. 16, 20 and 24 weeks of age; Nematodirus spp. eggs were counted separately from the other species of nematodes. Blood samples were collected in October from which immunoglobulin A (IgA) activity was measured and DNA was extracted for genotyping. In total, 139 Microsatellite markers were genotyped across eight chromosomal regions (chromosomes 1, 2, 3, 5, 14, 18, 20 and 21) in the sires and progeny were genotyped for the markers that were polymorphic in their sire. Evidence was found for quantitative trait loci (QTL) on chromosomes 2, 3, 14 and 20. QTL associated with specific IgA activity were identified in chromosomes 3 and 20, in regions close to IFNG (chromosome 3) and the MHC (chromosome 20). QTL associated with Nematodirus FEC were identified on chromosomes 2, 3 and 14. Lastly, QTL associated with non-Nematodirus Strongyle FEC were identified on chromosomes 3 and 20. This study has shown that some aspects of host resistance to gastrointestinal parasites are under strong genetic control, therefore these QTL could be utilised in a marker-assisted selection scheme to increase host resistance to gastrointestinal parasites.

Animals↗
PubMed2005

Quantitative trait locus analysis of aggressive behaviours in mice.

Quantitative trait locus (QTL) analysis is a forward genetic strategy (phenotype to gene) that enables an investigator to start with a phenotype of interest (e.g. aggressive behaviours), and then identify chromosomal regions (QTLs) and, ultimately, specific gene variants (alleles) within those regions, that influence quantitative variation in the phenotype. QTL analysis is an important complement to reverse genetic strategies (gene to phenotype), such as the generation of knockout and transgenic mice. Although a propensity for aggressive behaviours is partially heritable in mice and other mammals, very few aggression QTLs have been mapped. This slow progress is likely due, in part, to the complexity of aggressive behaviours as phenotypes, which are affected by many nongenetic (environmental and random) factors and gene-environment interactions. This paper reviews the general principles of QTL analysis, as well as the non-genetic factors that can confound aggression QTL studies. Some examples of successfully mapped intermale mouse aggression QTLs are presented, such as QTLs on chromosomes 10 and X. Strategies for fine mapping these loci are discussed, and candidate genes are considered. Finally, newly available mouse genetic resources that may facilitate QTL analysis of aggressive behaviours are suggested, such as consomic mouse strains.

Aggression↗
PubMed2002

Does natural selection promote population divergence? A comparative analysis of population structure using amplified fragment length polymorphism markers and quantitative traits.

Divergent natural selection is considered an important force in plant evolution leading to phenotypic differentiation between populations exploiting different environments. Extending an earlier greenhouse study of population differentiation in the selfing annual plant Senecio vulgaris, we estimated the degree of population divergence in several quantitative traits related to growth and life history and compared these estimates with those based on presumably neutral molecular markers (amplified fragment length polymorphisms; AFLPs). This approach allowed us to disentangle the effects of divergent selection from that of other evolutionary forces (e.g. genetic drift). Five populations were examined from each of two habitat types (ruderal and agricultural habitats). We found a high proportion of total genetic variance to be among populations, both for AFLP markers (phiST = 0.49) and for quantitative traits (range of QST: 0.26-0.77). There was a strong correlation between molecular and quantitative genetic differentiation between pairs of populations (Mantel's r = 0.59). However, estimates of population differentiation in several quantitative traits exceeded the neutral expectation (estimated from AFLP data), suggesting that divergent selection contributed to phenotypic differentiation, especially between populations from ruderal and agricultural habitats. Estimates of within-population variation in AFLP markers and quantitative genetic were poorly correlated, indicating that molecular marker data may be of limited value to predict the evolutionary potential of populations of S. vulgaris.

DNA, Plant↗
PubMed1998

Minimum distance estimation of mutational parameters for quantitative traits.

Individual spontaneous mutations affecting the expression of quantitative traits cannot be systematically identified and, therefore, their effect on the trait cannot be measured. Thus, the rate of occurrence of such mutations and the moments of the probability distribution of the corresponding effects, which are important in evolutionary studies, remain unknown. Here we propose a method to estimate those mutational properties from the observed distribution of the trait mean in a set of independent inbred lines (all derived from the same homozygous base population) in which mutations had been allowed to accumulate randomly. It is based on the use of the well-known minimum distance method, i.e., on the minimization of a distance between the observed distribution and that expected on the basis of a genetic model. We analyze data for three morphological traits (wing length and abdominal and sternopleural bristle number) in Drosophila melanogaster. The method appears to be powerful, giving evolutionary coherent estimates of relevant mutational properties that had not been estimated previously. For all traits, mutational rates were low (smaller than 0.05). Most mutations affecting wing length or abdominal bristle number and negative effect, while almost half of those affecting sternopleural bristle number had positive effect. For each trait, results obtained from data on different generations are in qualitative agreement, although mutational effects seem to depend on generation-specific environmental factors. The method detected between-trait differences in the kurtosis coefficient of the distribution of mutational effects, which varied from values close to that of the normal distribution (wing length) to relatively high values (sternopleural bristle number). It reveals that an important proportion of the mutational input variance of each trait is due to mutations with absolute effect smaller than 0.5 environmental standard deviation units. For morphological traits undergoing weak direct selection, this suggests that large amounts of genetic variance due to genes segregating at intermediate frequencies can be present at the equilibrium.

Animals↗
PubMed2005

Cis-acting expression quantitative trait loci in mice.

We previously reported the analysis of genome-wide expression profiles and various diabetes-related traits in a segregating cross between inbred mouse strains C57BL/6J (B6) and DBA/2J (DBA). By considering transcript levels as quantitative traits, we identified several thousand expression quantitative trait loci (eQTL) with LOD score >4.3. We now experimentally address the problem of multiple comparisons by estimating the fraction of false-positive eQTL that are under cis-acting regulation. For this, we have utilized a classic cis-trans test with (B6 x DBA)F(1) mice to determine the relative levels of transcripts from the B6 and DBA alleles. The results suggest that at least 64% of cis-acting eQTL with LOD >4.3 are true positives, while the remaining 36% could not be confirmed as truly cis-acting. Moreover, we find that >96% of apparent cis-acting eQTL occur in regions that do not share SNP haplotypes. Cis-acting eQTL serve as an important new resource for the identification of positional candidates in QTL studies in mice. Also, we use the analysis of the correlation structures between genotypes, gene expression traits, and phenotypic traits to further characterize genes expressed in liver that are under cis-acting control, and highlight the advantages and disadvantages of integrating genetics and gene expression data in segregating populations.

Alleles↗