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PubMed2005

A comparison of regression interval mapping and multiple interval mapping for linked QTL.

Regression interval mapping and multiple interval mapping are compared with regard to mapping linked quantitative trait loci (QTL) in inbred-line cross experiments. For that purpose, a simulation study was performed using genetic models with two linked QTL. Data were simulated for F(2) populations of different sizes and with all QTL and marker alleles fixed for alternative alleles in the parental lines. The criteria for comparison are power of QTL identification and the accuracy of the QTL position and effect estimates. Further, the estimates of the relative QTL variance are assessed. There are distinct differences in the QTL position estimates between the two methods. Multiple interval mapping tends to be more powerful as compared to regression interval mapping. Multiple interval mapping further leads to more accurate QTL position and QTL effect estimates. The superiority increased with wider marker intervals and larger population sizes. If QTL are in repulsion, the differences between the two methods are very pronounced. For both methods, the reduction of the marker interval size from 10 to 5 cM increases power and greatly improves QTL parameter estimates. This contrasts with findings in the literature for single QTL scenarios, where a marker density of 10 cM is generally considered as sufficient. The use of standard (asymptotic) statistical theory for the computation of the standard errors of the QTL position and effect estimates proves to give much too optimistic standard errors for regression interval mapping as well as for multiple interval mapping.

Chromosome Mapping↗
PubMed1991

A population genetic study in Finland: comparison of the Finnish- and Swedish-speaking populations.

In Finland there is a substantial but geographically limited Swedish-speaking minority (in 1980 6.3% of the total population) which originates mainly from Swedish immigrants during the years 1100-1300 AD. The admixture of this population with the neighbouring Finns was studied using more than 20 blood marker loci. The reference populations, Swedes and Finns, in spite of being part of the genetically rather uniform European populations, differ from each other genetically. These quantitative and also qualitative differences in gene frequencies are mostly due to the Finnish population possessing a number of genetic markers absent or rare in the rest of Europe. The results based on a sample of 620 individuals from the Swedish-speaking population in Finland showed a rather high degree of Finnish admixture, which was estimated to about 60%. This admixture most probably occurred at an early stage since it has reached such a high and geographically homogeneous degree.

Autoantigens↗
PubMed1978

[Study of the Gc protein in several French population samples : genetic polymorphism by isoelectrofocusing and quantitative results].

The authors describe the results obtained in an examination by isoelectrofocusing of more than 1,000 serum samples from various regions in France. The autochthonous populations of the north side of the Pyrénées are characterized by a high frequency of the gene Gc2 and a very low frequency of the Gc1F gene. This distinguishes them from the other groups studied (southwestern, northwestern and eastern France). The quantitative analysis of the data emphasizes the difference. These results can only be explained by the interdependance of the genetic and metabolic factors.

Adult↗
PubMed2005

Evaluation of candidate gene effects for beef backfat via Bayesian model selection.

Candidate gene approaches provide tools for exploring and localizing causative genes affecting quantitative traits and the underlying variation may be better understood by determining the relative magnitudes of effects of their polymorphisms. Diacyglycerol O-acyltransferase 1 (DGAT1), fatty acid binding protein (heart) 3 (FABP3), growth hormone 1 (GH1), leptin (LEP) and thyroglobulin (TG) have been previously identified as genes contributing to genetic control of subcutaneous fat thickness (SFT) in beef cattle. In the present research, Bayesian model selection was used to evaluate effects of these five candidate genes by comparing competing non-nested models and treating candidate gene effects as either random or fixed. The analyses were implemented in SAS to simplify the programming and computation. Phenotypic data were gathered from a F(2) population of Wagyu x Limousin cattle. The five candidate genes had significant but varied effects on SFT in this population. Bayesian model selection identified the DGAT1 model as the one with the greatest model probability, whether candidate gene effects were considered random or fixed, and DGAT1 had the greatest additive effect on SFT. The SAS codes developed in the study are freely available and can be downloaded at: http://www.ansci.wsu.edu/programs/.

Adiposity↗
PubMedDate not supplied

First-stage autosomal genome screen in extended pedigrees suggests genes predisposing to low bone mineral density on chromosomes 1p, 2p and 4q.

Osteoporosis is characterized by low bone density, and osteopenia is responsible for 1.5 million fractures in the United States annually. In order to identify regions of the genome which are likely to contain genes predisposing to osteopenia, we genotyped 149 members of seven large pedigrees having recurrence of low bone mineral density (BMD) with 330 DNA markers spread throughout the autosomal genome. Linkage analysis for this quantitative trait was carried out using spine and hip BMD values by the classical lod-score method using a genetic model with parameters estimated from the seven families. In addition, non-parametric analysis was performed using the traditional Haseman-Elston approach in 74 independent sib pairs from the same pedigrees. The maximum lod score obtained by parametric analysis in all families combined was +2.08 (theta = 0.05) for the marker CD3D on chromosome 11q. All other combined lod scores from the parametric analysis were less than +1.90, the threshold for suggestive linkage. Non-parametric analysis suggested linkage of low BMD to chromosomes 1p36 (Zmax = +3.51 for D1S450) and 2p23-24 (Zmax = +2.07 for D2S149). Maximum multi-point lod scores for these regions were +2.29 and +2.25, respectively. A third region with associated lod scores above the threshold of suggestive linkage in both single-point and multi-point non-parametric analysis was on chromosome 4qter (Zmax = +2.95 for D4S1539 and Zmax = +2.48 for D4S1554). Our data suggest the existence of multiple genes involved in controlling spine and hip BMD, and indicate several candidate regions for further screening in this and other independent samples.

Bone Density↗
PubMed2003

Evolutionary dynamics of an Arabidopsis insect resistance quantitative trait locus.

Glucosinolate profiles differ among Arabidopsis thaliana ecotypes, caused by the composition of alleles at several glucosinolate biosynthetic loci. One of these, GS-Elong, harbors a family of methylthioalkylmalate synthase (MAM) genes that determine the side chain length of aliphatic glucosinolate structures. Fine mapping reveals that GS-Elong constitutes an insect resistance quantitative trait locus, caused by variation in glucosinolate profiles conferred by polymorphism of MAM alleles in this region. A sequence survey of randomly chosen ecotypes indicates that GS-Elong is highly variable among A. thaliana ecotypes: indel polymorphisms are frequent, as well as gene conversion events between gene copies arranged in tandem. Furthermore, statistical methods of molecular population genetics suggest that one of the genes, MAM2, is subject to balancing selection. This may be caused by ecological tradeoffs, i.e., by contrasting physiological effects of glucosinolates on generalist vs. specialist insects.

Animals↗
PubMed2003

Effects of marker-assisted selection under different initial frequency of QTL favorable allele.

A ten-generation continuous selection experiment on a single trait in a closed population was carried out by stochastic simulation. It assumed that the trait was controlled by polygenes and a single autosomal bi-allelic marked quantitative trait locus (QTL). Individual breeding values were estimated through animal model marker-assisted best linear unbiased prediction (MB-LUP), and breeding animals were selected according to their breeding values. The effects of three levels initial frequencies of QTL favorable allele on marker-assisted selection (MAS) were studied. The results showed that it would gain higher genetic response when implementing MAS on those traits with lower initial frequency of QTL favorable allele. When the initial frequency of QTL favorable allele was low, although the generation number required for fixing QTL favorable allele in the population would be lengthened, its frequency would be increased faster. However, the initial frequency of QTL favorable allele had little effects on the inbreeding rates.

Algorithms↗
PubMed2006

[Advance in quantitative traits from phenotypic variation to gene discovery].

With the rapid development of molecular biotechnology, many improved approaches have been provided for studying on the genetic bases of quantitative traits. Many studies paid attention to dissect the genetic bases using different emendatory approaches from phenotypic variation to gene discovery, mainly containing QTL mapping, chemical mutagenesis etc. Especially, QTL analysis was executed for a lot of important quantitative traits. This paper summarizes the development of quantitative genetics, the recent progress on QTL mapping populations and methods, the status of QTL locating and QTG identification, positional cloning, and QTL application in breeding.

Animals↗
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↗
PubMed2000

Gene interactions from maternal effects.

Theoretical analyses have demonstrated a potential role for epistasis in many of the most important processes in evolution. These analyses generally assume that an individual's genes map directly to its phenotype and epistasis results from interactions among loci that contribute to the same biochemical or developmental pathways (termed physiological, or within-genotype, epistasis). For many characters, particularly those expressed early in life, an individual's phenotype may also be affected by genes expressed by its parents. The presence of these parental effects allows for interactions between the genes present in the parental and offspring genomes. When the phenotypic effect of a locus in the offspring depends on the alleles possessed by its parents, genotype-by-genotype, or among-genotype, epistasis occurs. The among-genotype epistasis resulting from parental effects may contribute to ruggedness of adaptive landscapes because early mortality often accounts for much of the variance in fitness in populations. To demonstrate how parent-offspring interactions can result in among-genotype epistasis, I use a two-locus model, with one maternal effect locus and one direct effect locus, each with two alleles. Dynamical equations are presented for the two-locus model and are directly contrasted with the dynamical equations derived for a model for physiological epistasis. The relationship between the evolutionary dynamics resulting from these two forms of epistasis is discussed. Three scenarios are presented to illustrate systems in which maternal-offspring, genotype-by-genotype epistasis may occur. The implications of maternal-offspring epistasis for quantitative-trait-loci studies are also discussed.

Animals↗
PubMed1997

[Preparation of new microsatellite markers of rat chromosome 10 in the region, containing genes regulating blood pressure level].

Primer walking is a simple and efficient technique to find new microsatellites in the regions adjacent to known sequences. The method was applied to obtaining new microsatellite markers for rat chromosome 10 in the region of a blood pressure quantitative trait locus. Eight microsatellites were found, five of them were polymorphic in at least one population used for mapping. Improved genetic maps of this region for F2(SxMNS) and F2(SxLEW) populatons were constructed.

Animals↗
PubMed2004

Quantitative trait locus mapping of genetic modifiers of metabolic syndrome and atherosclerosis in low-density lipoprotein receptor-deficient mice: identification of a locus for metabolic syndrome and increased atherosclerosis on chromosome 4.

OBJECTIVE: The purpose of this study was to examine genetic factors responsible for metabolic syndrome and atherosclerosis in a setting of low-density lipoprotein (LDL) receptor deficiency in a cross between C57BL/6J (B6) and PERA/Ei (PERA) inbred mouse strains. METHODS AND RESULTS: Comparison of metabolic phenotypes in B6 and PERA strains revealed the PERA genetic background to be dramatically more susceptible to hyperleptinemia, hyperglycemia, hypertriglyceridemia, elevated insulin levels, and body fat increase than the B6 background. To facilitate genetic analysis, metabolic syndrome-related traits and atherosclerotic lesion area were measured in 167 [(PERAxB6.129S7-Ldlr(tm1Her))xB6.129S7-Ldlr(tm1Her)]N2 male and female backcross mice that were homozygous for the Ldlr null allele. Quantitative trait locus analysis was performed using 153 polymorphic microsatellite markers spanning the genome. On chromosome 4, we identified a locus influencing plasma triglyceride, insulin, and leptin concentrations, body weight, and atherosclerosis. Several other genetic loci were identified with separate effects on plasma insulin, body weight, high-density lipoprotein cholesterol, and atherosclerosis. CONCLUSIONS: The PERA strain is highly susceptible to the development of metabolic syndrome after feeding a Western-type diet. This susceptibility is due, in part, to a locus on murine chromosome 4 in which PERA alleles predispose to adiposity, increased insulin, and accelerated atherogenesis in the absence of marked hyperlipidemia.

Animals↗
PubMed2003

Covariation of larval gene expression and adult body size in natural populations of Drosophila melanogaster.

Understanding adaptive phenotypic variation is one of the most fundamental problems in evolutionary biology. Genes involved in adaptation are most likely those that affect traits most intimately connected to fitness: life-history traits. The genetics of quantitative trait variation (including life histories) is still poorly understood, but several studies suggest that (1) quantitative variation might be the result of variation in gene expression, rather than protein evolution, and (2) natural variation in gene expression underlies adaptation. The next step in studying the genetics of adaptive phenotypic variation is therefore an analysis of naturally occuring covariation of global gene expression and a life-history trait. Here, we report a microarray study addressing the covariation in larval gene expression and adult body weight, a life-history trait involved in adaptation. Natural populations of Drosophila melanogaster show adaptive geographic variation in adult body size, with larger animals at higher latitudes. Conditions during larval development also affect adult size with larger flies emerging at lower temperatures. We found statistically significant differences in normalized larval gene expression between geographic populations at one temperature (genetic variation) and within geographic populations between temperatures (developmental plasticity). Moreover, larval gene expression correlated highly with adult weight, explaining 81% of its natural variation. Of the genes that show a correlation of gene expression with adult weight, most are involved in cell growth or cell maintenance or are associated with growth pathways.

Animals↗
PubMed2004

Genetic variation in BEACON influences quantitative variation in metabolic syndrome-related phenotypes.

The BEACON gene (also known as UBL5) was identified as differentially expressed between lean and obese Psammomys obesus, a polygenic animal model of obesity, type 2 diabetes, and dyslipidemia. The human homologue of BEACON is located on chromosome 19p, a region likely to contain genes affecting metabolic syndrome-related quantitative traits as established by linkage studies. To assess whether the human BEACON gene may be involved in influencing these traits, we exhaustively analyzed the complete gene for genetic variation in 40 unrelated individuals and identified four variants (three novel). The two more common variants were tested for association with a number of quantitative metabolic syndrome-related traits in two large cohorts of unrelated individuals. Significant associations were found between these variants and fat mass (P = 0.026), percentage of fat (P = 0.001), and waist-to-hip ratio (P = 0.031). The same variants were also associated with total cholesterol (P = 0.024), LDL cholesterol (P = 0.019), triglycerides (P = 0.006), and postglucose load insulin levels (P = 0.018). Multivariate analysis of these correlated phenotypes also yielded a highly significant association (P = 0.0004), suggesting that BEACON may influence phenotypic variation in metabolic syndrome-related traits.

Adult↗
PubMed2003

A method for marker-assisted selection based on QTLs with epistatic effects.

A method for marker-assisted selection (MAS) based on quantitative trait loci (QTLs) with epistatic effects is proposed. The efficiency of such method is investigated by simulations under a wide range of situations. In the presence of epistasis, MAS generally yields longer persistence response than that based exclusively on additive or additive and dominance. Neglecting epistasis could result in considerable loss in response, and more pronounced at later generations. In addition to population size and trait heritability, genetic variance configurations play an important role in determining both the short- and long-term efficiencies of MAS. MAS using breeding values not only achieves higher response, but also tends to have smaller standard error than other methods in most cases. Errors in QTL detection cause distinct reductions in responses to MAS in most cases. It is thus concluded that verifications of putative QTL and its magnitude of effect and accurate map chromosome location are imperative to realize the potentials of MAS.

Epistasis, Genetic↗
PubMed2005

Genetical genomics analysis of a yeast segregant population for transcription network inference.

Genetic analysis of gene expression in a segregating population, which is expression profiled and genotyped at DNA markers throughout the genome, can reveal regulatory networks of polymorphic genes. We propose an analysis strategy with several steps: (1) genome-wide QTL analysis of all expression profiles to identify eQTL confidence regions, followed by fine mapping of identified eQTL; (2) identification of regulatory candidate genes in each eQTL region; (3) correlation analysis of the expression profiles of the candidates in any eQTL region with the gene affected by the eQTL to reduce the number of candidates; (4) drawing directional links from retained regulatory candidate genes to genes affected by the eQTL and joining links to form networks; and (5) statistical validation and refinement of the inferred network structure. Here, we apply an initial implementation of this strategy to a segregating yeast population. In 65, 7, and 28% of the identified eQTL regions, a single candidate regulatory gene, no gene, or more than one gene was retained in step 3, respectively. Overall, 768 putative regulatory links were retained, 331 of which are the strongest candidate links, as they were retained in the expression correlation analysis and were located within or near an eQTL subregion identified by a multimarker analysis separating multiple linked QTL. One or several biological processes were statistically significantly overrepresented in independent network structures or in highly interconnected subnetworks. Most of the transcription factors found in the inferred network had a putative regulatory link to only one other gene or exhibited cis-regulation.

DNA↗
PubMed1998

Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data.

Evolutionary biologists have long sought a way to determine whether a phenotypic difference between two taxa was caused by natural selection or random genetic drift. Here I argue that data from quantitative trait locus (QTL) analyses can be used to test the null hypothesis of neutral phenotypic evolution. I propose a sign test that compares the observed number of plus and minus alleles in the "high line" with that expected under neutrality, conditioning on the known phenotypic difference between the taxa. Rejection of the null hypothesis implies a role for directional natural selection. This test is applicable to any character in any organism in which QTL analysis can be performed.

Alleles↗
PubMed2006

Expression profiling identifies novel candidate genes for ethanol sensitivity QTLs.

The Inbred Long Sleep (ILS) and Inbred Short Sleep (ISS) mouse strains have a 16-fold difference in duration of loss of the righting response (LORR) following administration of a sedative dose of ethanol. Four quantitative trait loci (QTLs) have been mapped in these strains for this trait. Underlying each of these QTLs must be one or more genetic differences (polymorphisms in either gene coding or regulatory regions) influencing ethanol sensitivity. Because prior studies have tended to focus on differences in coding regions, genome-wide expression profiling in cerebellum was used here to identify candidate genes for regulatory region differences in these two strains. Fifteen differentially expressed genes were found that map to the QTL regions and polymorphisms were identified in the promoter regions of four of these genes by direct sequencing of ILS and ISS genomic DNA. Polymorphisms in the promoters of three of these genes, Slc22a4, Rassf2, and Tax1bp3, disrupt putative transcription factor binding sites. Slc22a4 and another candidate, Xrcc5, have human orthologs that map to genomic regions associated with human ethanol sensitivity in genetic linkage studies. These genes represent novel candidates for the LORR phenotype and provide new targets for future studies into the neuronal processes underlying ethanol sensitivity.

Animals↗