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PubMed2000

A method for fine mapping quantitative trait loci in outbred animal stocks.

High-resolution mapping of quantitative trait loci (QTL) in animals has proved to be difficult because the large effect sizes detected in crosses between inbred strains are often caused by numerous linked QTLs, each of small effect. In a study of fearfulness in mice, we have shown it is possible to fine map small-effect QTLs in a genetically heterogeneous stock (HS). This strategy is a powerful general method of fine mapping QTLs, provided QTLs detected in crosses between inbred strains that formed the HS can be reliably detected in the HS. We show here that single-marker association analysis identifies only two of five QTLs expected to be segregating in the HS and apparently limits the strategy's usefulness for fine mapping. We solve this problem with a multipoint analysis that assigns the probability that an allele descends from each progenitor in the HS. The analysis does not use pedigrees but instead requires information about the HS founder haplotypes. With this method we mapped all three previously undetected loci [chromosome (Chr.) 1 logP 4.9, Chr. 10 logP 6.0, Chr. 15 logP 4.0]. We show that the reason for the failure of single-marker association to detect QTLs is its inability to distinguish opposing phenotypic effects when they occur on the same marker allele. We have developed a robust method of fine mapping QTLs in genetically heterogeneous animals and suggest it is now cost effective to undertake genomewide high-resolution analysis of complex traits in parallel on the same set of mice.

Animals↗
PubMed1998

Two-locus developments of the weighted pairwise correlation method for linkage analysis.

Different studies of complex traits assumed to be influenced by two unliked loci found that two-locus linkage analysis is more powerful than the classical one-locus strategy. The Weighted Pairwise Correlation (WPC) approach is a nonparametric method for linkage analysis that has the advantage to analyze any kind of phenotypes and to consider extended pairs of relatives. In this report, we propose different two-locus extensions of the WPC method based on an additive or a multiplicative effect of two unlinked marker loci on the phenotype. Both methods and their corresponding statistics are easily derived from the classical WPC approach. Compared to the additive model, the multiplicative approach, which can be understood as a statistical interaction effect of the two markers, does not need to specify any additional parameter and allows one to test both the global effect of the two markers (T(AB)test) and the effect of one marker, e.g., B, taking into account the effect of the other, A (T(AB/A) test). When compared to classical one-locus tests by means of simulations, two-locus tests have comparable 0.05 type I error and are more powerful. In particular, tests based on the multiplicative approach appear to be quite interesting in addition to single locus tests to detect the combined role of two markers (T(AB)), or to investigate the role of a marker taking into account a known linked marker (T(AB/A)), especially when these markers have complex effects on the phenotype (e.g., statistical interaction).

Alleles↗
PubMed2001

Large upward bias in estimation of locus-specific effects from genomewide scans.

The primary goal of a genomewide scan is to estimate the genomic locations of genes influencing a trait of interest. It is sometimes said that a secondary goal is to estimate the phenotypic effects of each identified locus. Here, it is shown that these two objectives cannot be met reliably by use of a single data set of a currently realistic size. Simulation and analytical results, based on variance-components linkage analysis as an example, demonstrate that estimates of locus-specific effect size at genomewide LOD score peaks tend to be grossly inflated and can even be virtually independent of the true effect size, even for studies on large samples when the true effect size is small. However, the bias diminishes asymptotically. The explanation for the bias is that the LOD score is a function of the locus-specific effect-size estimate, such that there is a high correlation between the observed statistical significance and the effect-size estimate. When the LOD score is maximized over the many pointwise tests being conducted throughout the genome, the locus-specific effect-size estimate is therefore effectively maximized as well. We argue that attempts at bias correction give unsatisfactory results, and that pointwise estimation in an independent data set may be the only way of obtaining reliable estimates of locus-specific effect-and then only if one does not condition on statistical significance being obtained. We further show that the same factors causing this bias are responsible for frequent failures to replicate initial claims of linkage or association for complex traits, even when the initial localization is, in fact, correct. The findings of this study have wide-ranging implications, as they apply to all statistical methods of gene localization. It is hoped that, by keeping this bias in mind, we will more realistically interpret and extrapolate from the results of genomewide scans.

Bias↗
PubMed1993

Evidence for linkage of the apolipoprotein A-II locus to plasma apolipoprotein A-II and free fatty acid levels in mice and humans.

Although it has been hypothesized that the synteny between mouse and human genes provides an approach to the localization of genes that determine quantitative traits in humans, this has yet to be demonstrated. We tested this approach with two quantitative traits, plasma apolipoprotein A-II (apoAII) and free fatty acid (FFA) levels. ApoAII is the second most abundant protein of high density lipoprotein particles, but its function remains largely unknown. We now show that, in a backcross between strains Mus spretus and C57BL/6J, apoAII levels correlate with plasma FFA concentrations on both chow (P < 0.0001) and high-fat (P < 0.0003) diets and that apoAII levels are linked to the apoAII gene (P < 0.0002). To test whether variations of the apoAII gene influence plasma lipid metabolism in humans, we studied 306 individuals in 25 families enriched for coronary artery disease. The segregation of the apoAII gene was followed by using an informative simple sequence repeat in the second intron of the gene and two nearby genetic markers. Robust sib-pair linkage analysis was performed on members of these families using the SAGE linkage programs. The results suggest linkage between the human apoAII gene and a gene controlling plasma apoAII levels (P = 0.03). Plasma apoAII levels were also significantly correlated with plasma FFA levels (P = 0.007). Moreover, the apoAII gene exhibited linkage with a gene controlling FFA levels (P = 0.003). Evidence for nonrandom segregation was seen with markers as far as 6-12 centimorgans from the apoAII structural locus. These data provide evidence, in two species, that the apoAII gene is linked to a gene that controls plasma apoAII levels and that apoAII influences, by an unknown mechanism, plasma FFA levels. The results illustrate the utility of animal studies for analysis of complex traits.

Animals↗
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

Genetics and differential expression of NADH:ubiquinone oxidoreductase B8 subunit in brains of genetic strains of mice differing in voluntary alcohol consumption.

Inbred strains of mice remain a valuable resource for genetic dissection of complex traits including responses to drugs and chemicals, particularly alcohol. As a novel source of candidate genes for further analysis, we have used mRNA differential displays to identify genes with differential expression in the brains of ethanol-preferring (C57BL/6J) vs. ethanol-avoiding (A/J, BALB/c, and DBA/2J) strains, with and without ethanol i.p. treatments (4 g/kg). We report on one such gene, NADH:ubiquinone oxidoreductase B8 subunit, that has a higher expression in the C57BL/6J. Further, its expression also increases following ethanol treatment as compared to the three alcohol-avoiding strains. This regulatory feature follows three single nucleotide polymorphisms (SNPs) in the promoter region across the four strains studied. The four strains represent only two haplotypes, one C57BL/6J-specific and the other found in the three alcohol-avoiding strains. Interestingly, one of the observed SNPs (-687 A/G) is located in the putative TFIID binding site with potential to regulate the expression of this gene and contribute to genotype-specific alcohol responses and effects involving reactive oxygen species (ROS).

Alcohol Drinking↗
PubMed2004

Genetic basis of pre-harvest sprouting tolerance using single-locus and two-locus QTL analyses in bread wheat.

Quantitative trait loci (QTL) analysis for pre-harvest sprouting tolerance (PHST) in bread wheat was conducted following single-locus and two-locus analyses, using data on a set of 110 recombinant inbred lines (RILs) of the International Triticeae Mapping Initiative population grown in four different environments. Single-locus analysis following composite interval mapping (CIM) resolved a total of five QTLs with one to four QTLs in each of the four individual environments. Four of these five QTLs were also detected following two-locus analysis, which resolved a total of 14 QTLs including 8 main effect QTLs (M-QTLs), 8 epistatic QTLs (E-QTLs) and 5 QTLs involved in QTL x environment (QE) or QTL x QTL x environment (QQE) interactions, some of these QTLs being common. The analysis revealed that a major fraction (76.68%) of the total phenotypic variation explained for PHST is due to M-QTLs (47.95%) and E-QTLs (28.73%), and that only a very small fraction of variation (3.24%) is due to QE and QQE interactions. Thus, more than three-quarters of the genetic variation for PHST is fixable and would contribute directly to gains under selection. Two QTLs that were detected in more than one environment and at LOD scores above the threshold values were located on 3BL and 3DL presumably in the vicinity of the dormancy gene TaVp1. Another QTL was found to be located on 3B, perhaps in close proximity to the R gene for red grain colour. However, these associations of QTLs for PHST with genes for dormancy and grain colour are only suggestive. The results obtained in the present study suggest that PHST is a complex trait controlled by large number of QTLs, some of them interacting among themselves or with the environment. These QTLs can be brought together through marker-aided selection, leading to enhanced PHST.

Chromosome Mapping↗
PubMed2005

Comparative microsatellite linkage analysis and genetic structure of two populations of F6 lines derived from Lycopersicon pimpinellifolium and L. cheesmanii.

A population of recombinant inbred lines (RILs) has several advantages over its F2 population counterpart with respect to quantitative trait loci (QTLs) and genomic studies. The objective of the investigation reported here was the comparative characterization by simple sequence repeat (SSR) and sequence characterized amplified region (SCAR) markers of two populations of F6 lines derived from Lycopersicon pimpinellifolium (P population, consisting of 142 lines) and L. cheesmanii (C population, consisting of 115 lines) and sharing the female parent, L. esculentum var. cerasiforme. Almost the same percentage of polymorphic markers was found for each population although a different set of markers was involved. The proportion of SSR primer pairs (93 in total) that resulted in polymorphism for the main band was larger (55-56%) than for SCAR ones (13-16%). The C population showed the largest proportion of markers with zygotic and gametic segregation distortion, which is in agreement with the larger genetic distance reported between L. esculentum and L. cheesmanii than with the former and L. pimpinellifolium. Zygotic distortion corresponded primarily to an excess of heterozygotes in both populations, suggesting that the increment of homozygosity was the main factor limiting viability/self-fertility of the lines. Despite both populations sharing the female parent, P alleles were slightly favored in the P population while E alleles were the most frequently fixed in the C population. A linkage map for each population was obtained, with the average distances between consecutive markers being 3.8 cM or 3.4 cM depending on the population. Discrepancy between the maps for the location of only four markers on chromosomes 3, 6 and 10 was observed. Two possible causes of this discrepancy were investigated and can not be discarded: (1) the presence of duplicated markers and (2) segregation distortion caused by the selective advantage of gametes carrying one of the two alleles. This marker characterization of both populations will continue and will enable the comparative QTLs and candidate gene analysis of complex traits towards a more efficient utilization of genetic resources and breeding strategies.

Chromosome Mapping↗
PubMed1996

A full genome search in multiple sclerosis.

The aetiology of multiple sclerosis (MS) is uncertain. There is strong circumstantial evidence to indicate it is an autoimmune complex trait. Risks for first degree relatives are increased some 20 fold over the general population. Twin studies have shown monozygotic concordance rates of 25-30% compared to 4% for dizygotic twins and siblings. Studies of adoptees and half sibs show that familial risk is determined by genes, but environmental factors strongly influence observed geographic differences. Studies of candidate genes have been largely unrewarding. We report a genome search using 257 microsatellite markers with average spacing of 15.2 cM in 100 sibling pairs (Table 1, data set 1 - DS1). A locus of lambda>3 was excluded from 88% of the genome. Five loci with maximum lod scores (MLS) of >1 were identified on chromosomes 2, 3, 5, 11 and X. Two additional data sets containing 44 (Table 1, DS2) and 78 sib pairs (Table 1, DS3) respectively, were used to further evaluate the HLA region on 6p21 and a locus on chromosome 5 with an MLS of 4.24. Markers within 6p21 gave MLS of 0.65 (non-significant, NS). However, D6S461, just outside the HLA region, showed significant evidence for linkage disequilibrium by the transmission disequilibrium test (TDT), in all three data sets (for DS1 chi2 = 10.8, adjusted P < 0.01)(DS2 and DS3 chi2 = 10.9, P < 0.0005), suggesting a modest susceptibility locus in this region. On chromosome 5p results from all three data sets (222 sib pairs) yielded a multipoint MLS of 1.6. The results support genetic epidemiological evidence that several genes interact epistatically to determine heritable susceptibility.

Chromosome Mapping↗
PubMed2007

Confirmation of linkage to ocular refraction on chromosome 22q and identification of a novel linkage region on 1q.

OBJECTIVE: To localize genes influencing ocular refraction in subjects in the Beaver Dam Eye Study. Previous studies establish that myopia clusters within families and linkage to myopia has been demonstrated on 2q, 4q, 12q, 17q, 18q, 22q, and Xq. Few studies have examined genetic effects across the entire range of refraction, though linkages to 1p, 3q, 4q, 8p, and 11p have been reported, and our previous analysis of the Beaver Dam Eye Study demonstrated substantial heritability for refraction (68%). METHODS: We conducted nonparametric sibling-pair and genome-wide linkage analyses on spherical equivalent adjusting for age, education, and nuclear sclerosis, in 834 sibling pairs in 486 extended pedigrees. RESULTS: We identified a novel region of suggestive linkage on 1q (multipoint, P<.00019) and replicated the 22q region (multipoint, P = .0033) previously linked to myopia. Additionally, there was some evidence of linkage to 7p (multipoint, P = .0023). CONCLUSION: Refraction is a complex trait influenced by both genes and environment. Our work confirms a previously reported linkage region on 22q and identifies 2 novel regions of linkage on 1q and 7p. CLINICAL RELEVANCE: Further, genetic research is needed to finemap this trait to identify the causative gene. Modifying the actions of such a gene might lead to a reduction in the risk of refractive error.

Adult↗
PubMed1996

Analysis of the recurrence patterns for nonsyndromic cleft lip with or without cleft palate in the families of 3,073 Danish probands.

The identification of several putative susceptibility loci for nonsyndromic cleft lip with or without cleft palate (CL +/- P) has sparked a renewed interest in the genetics of this condition. However, prior to undertaking linkage studies for complex traits such as CL +/- P it is desirable to have some understanding of the number and nature of the loci involved in disease susceptibility. The ability to obtain valid estimates of these parameters is contingent on the availability of family data which are unbiased by factors that distort the true familial recurrence pattern. In an effort to obtain such data, 2 centralized data repositories (the Danish Central Person Registry and the Danish Facial Cleft Database), were linked and used to estimate the risks to first, second, and third-degree relatives of 3,073 CL +/- P probands born in Denmark from 1952 to 1987. Analyses of these data excluded single locus and additive multilocus inheritance of CL +/- P, and provided evidence that CL +/- P is most likely determined by the effects of multiple interacting loci. Under a multiplicative model, no single locus can account for more than a threefold increase in the risk to first-degree relatives of CL +/- P probands. These data provide further evidence that nonparametric linkage methods (ex. affected relative pair studies) are likely to represent a more realistic approach for identifying CL +/- P susceptibility loci, than are traditional pedigree-based methods. However, at least 100 and more realistically several hundred (300-500) affected sib pairs are likely to be required to detect linkage to CL +/- P susceptibility loci.

Cleft Lip↗
PubMed1999

Analysis of select folate pathway genes, PAX3, and human T in a Midwestern neural tube defect population.

Neural tube defects (NTDs) are a common birth defect, seen in approximately 1/1,000 births in the United States. NTDs are considered a complex trait where several genes, interacting with environmental factors, create the phenotype. Using a Midwestern NTD population consisting of probands, parents, and siblings from Iowa, Minnesota, and Nebraska, we analyzed a range of candidate genes, including 5,10-methylenetetrahydrofolate reductase (MTHFR), folate receptors-alpha (FOLR1; hereafter abbreviated "FR-alpha") and -beta (FOLR2; hereafter, "FR-beta"), methionine synthase (hereinafter, "MS"), T, the human homolog of the murine Brachyury gene, and the paired-box homeotic gene 3 (PAX3), for association with NTDs. We were unable to demonstrate an association using a previously described Ala-->Val mutation in MTHFR and the majority of our NTD populations. However, we discovered a silent polymorphism in exon 6 of MTHFR which conserved a serine residue and which showed significant association with NTDs in our Iowa population. Analysis of exon 7 of MTHFR then demonstrated an Ala-->Glu mutation which was significantly associated with our Iowa NTD population; however, we could not replicate this result either in a combined Minnesota/ Nebraska or in a California NTD population. Using polymorphic markers for MS, FR-beta, T, and PAX3, we were unable to demonstrate linkage disequilibrium with our NTD populations. A mutation search of FR-alpha revealed one proband with a de novo silent mutation of the stop codon. This work provides a new panel of genetic variants for studies of folate metabolism and supports, in some NTD populations, an association between MTHFR and NTDs.

5,10-Methylenetetrahydrofolate Reductase (FADH2)↗
PubMed1996

Random effects model for meta-analysis of multiple quantitative sibpair linkage studies.

The growing interest in detection of genetic effects for complex traits along with molecular revolution has stimulated many linkage studies. Multiple replication studies tend to produce different results. In such situations, rigorous meta-analysis methods can be useful for assessing the overall evidence for linkage. We propose here a random effects model for combining results from independent quantitative sibpair linkage studies. The model can be used to assess the aggregate evidence for linkage by combing the regression coefficients to the Haseman and Elston [(1972) Behav Genet 2:3-19] sibpair method as well as to assess heterogeneity among the multiple studies.

Genetic Linkage↗
PubMed1996

General score tests for associations of genetic markers with disease using cases and their parents.

Association studies of genetic markers with disease play a critical role in the dissection of genetically complex traits because they are relatively easy to conduct and are useful for fine-scale mapping of genetic traits. The advantage of family-based controls has recently received much attention because spurious associations caused by population structure can be controlled for, and marker genotype information on diseased cases and their parents can be used to test the compound hypothesis of both linkage and linkage disequilibrium. However, debate still exists regarding the statistical methods of analysis. Herein are presented statistical methods to test for linkage (in the presence of linkage disequilibrium) between multiallelic genetic markers and disease when diseased subjects (cases) and their parents are sampled. Theoretical considerations for the development of general statistical tests are presented as well as asymptotic formulas to compute their power when planning a study. Furthermore, simulation results for nine specific statistics are used to contrast the power of these methods under different genetic mechanisms leading to disease (dominant vs. recessive, one vs. two high-risk alleles). These results demonstrate substantial gains in power for specific statistical tests designed to detect specified genetic mechanisms. However, without a priori knowledge of the likely genetic mechanism, it is desirable to rely on a fairly robust statistical method, robust so that power is not drastically lost when either dominant or recessive mechanisms are acting, and when either one or more than one marker alleles are associated with disease. Based on both theoretical and simulation results, a general score statistic, which generalizes the transmission/disequilibrium test, tends to offer sufficient power for a variety of genetic mechanisms, so that it is worth considering for broad use in studies which use genetic marker information from both diseased cases and their parents.

Adult↗
PubMed1997

Empirical genomewide significance levels established by whole genome simulations.

The advent of high-resolution genetic maps and semiautomated genotyping technology has opened the way for genome screening in genetically complex traits. Many such screens are now under way, or completed, most using multipoint nonparametric linkage analysis of affected sibling pairs. This type of linkage analysis uses all the available genotype information to calculate the maximum lod score (MLS) value at each point in the genome, and thereby generates MLS profiles along each chromosome. Any positive MLS values indicate potential linkage, but the peaks in these profiles, which may be referred to as "hits," identify the most likely locations of disease susceptibility genes. However, such analysis presents serious problems of multiple testing, and the assessment of the statistical significance of hits has become a contentious issue [Lander and Kruglyak (1995) Nat Genet 11:241-247; Curtis (1996) Nat Genet 12:356-357; Witte et al. (1996) Nat Genet 12:355-356]. Having recently completed a genome screen in multiple sclerosis, we decided to investigate the statistical properties of our study by simulation. We report here in detail the results of this simulation study. Our main conclusion is that, for the particular set of families and markers used in our screen, an MLS of 3.2 carries a genome-wide significance of 5% (that is, there is a 5% probability of observing at least one false hit, above this threshold in a complete genome screen). This value is closer to the familiar limit of 3.0, originally suggested by Morton [1955; Am J Hum Genet 7:277-318] than to the more stringent limit of 4.0 recently proposed by Lander and Kruglyak [1995; Nat Genet 11:241-247]. This is somewhat reassuring, in view of the very large sample sizes that would be necessary to achieve adequate power to detect linkage at the more stringent threshold.

Female↗
PubMed1998

CAT scans, PET scans, and genomic scans.

As we begin the long march toward genetic dissection of complex traits, it becomes necessary to develop optimum study designs and retool ourselves to face the emerging new challenges. Key issues pertaining to the design of genomic scans are reviewed, including: sampling unit, definition and refinement of phenotype, genotyping issues, one-stage vs. two-stage strategies, sample size and power, and cost and feasibility. It is emphasized that false positives should not be minimized in isolation from the issue of false negatives. Striking a practical balance between the two error rates is suggested. In terms of future directions to pursue, three areas are suggested: meta-analysis for pooling linkage results from multiple scans, rapid multivariate screening methods for increased power to detect quantitative trait loci (QTLs), and classification and regression trees (CART) methodology for handling heterogeneity and interactions. Finally, three recommendations are proposed for genomic scans. First, so as to minimize false negatives for a fixed sample size, it is recommended that we tolerate/accept a reasonable rate of false positives, on average, one false positive per individual scan. Second, so as to enable the use of relatively strict significance levels for interpreting the results from a genomic scan, it is highly recommended that the sample size be derived based on a significance level of at most 0.01 (and not 0.05) and 90% power (and not 80%). Third, it is recommended that the stringent significance levels suggested by Lander and Kruglyak be used when pooling evidence from multiple genomic scans (and not at the level of individual scans).

Alzheimer Disease↗
PubMed2000

Clustering methods applied to allele sharing data.

Here we focus on using clustering methods to disentangle the interacting factors that lead to the presentation of complex diseases. Relative pairs are placed in discrete subgroups, or classes, based upon their pattern of allele sharing at a sequence of markers and on concomitant risk factors. The relationship between the locus information and the affectation status of the relative pairs within each subgroup then can be assessed. Cluster analysis (CLA) and latent class analysis (LCA) were applied to sibling allele sharing data from GAW11 simulated data, and to an existing Alzheimer's disease (AD) dataset. Both methods were able to identify markers linked to all 3 disease loci in the GAW11 data. LCA and CLA also replicated regions of chromosomes identified in an analysis of the AD data using affected-sib-pair methods. These analyses indicate that classification tools may be useful for detecting susceptibility genes for complex traits.

Aged↗
PubMed2000

Impulsivity, aggression, and serotonin: a molecular psychobiological perspective.

The expression of aggressiveness, which constitutes many facets of behavior, is influenced by a complex interaction of biologic, psychologic, and social variables. Even though individual differences in impulsivity and the behavioral consequences, such as aggression, addiction, and suicidality, are substantially heritable, they ultimately result from an interplay between genetic variations and environmental factors. While formation and integration of multiple neural networks is dependent on the actions of neurotransmitters, such as serotonin (5HT), converging lines of evidence indicate that genetically determined variability in serotonergic gene expression influences complex traits including that of inappropriately aggressive behavior. This contribution reviews studies of major gene effects in inbred and knockout strains of mice with increased aggression-related behavior and discusses the relevance of several serotonergic gene variations in humans which include high aggressiveness as part of the phenotype. Although special emphasis is given to the molecular psychobiology of 5HT in aggression-related behavior in rodents, nonhuman primates, and humans, relevant conceptual and methodological issues in the search for candidate genes for impulsivity and aggressiveness and for the development of mouse models of aggressive and antisocial behavior in humans are also considered.

Aggression↗