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Results for “QTL mapping”

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PubMed1999

Mapping genes that control hormone-induced ovulation rate in mice.

The present study mapped quantitative trait loci (QTL) that control 6-fold genetic differences in hormone-induced ovulation rate (HIOR) between C57BL/6J (B6) (HIOR = 54) and A/J strain mice (HIOR = 9). (The gene name is Ovulation Rate Induced [ORI] QTL and the gene symbol is Oriq.) QTL linkage analysis was conducted on 167 (B6xA)xA backcross mice at 165 loci. Suggestive B6 ORI QTL that control the number of eggs in cumulus mapped, as follows, near: Cyp19 and D9Mit4 on chromosome (Chr) 9 (Oriq1); D2Mit433 on Chr2 (Oriq2); D6Mit316 on Chr6 (Oriq3); DXMit22 on ChrX (Oriq4) and were associated with a 2.7, 2.7, 2.6, and 4.2 egg increases in HIOR, respectively. Oriq3 was significant (LOD = 3.45) based on composite interval mapping. QTL linkage analysis of the number of eggs matured by endogenous gonadotropins and ovulated by eCG mapped a significant Oriq5 to Chr 10 and suggestive Oriq to Chr 6, 7, and X. These data provide the first molecular genetic markers for reproductive QTL that control major differences in ovarian responsiveness to gonadotropins. These and closely linked syntenic molecular markers will enable a more accurate prediction of ovarian responsiveness to gonadotropins and provide selection criteria for improving reproductive performance in diverse mammalian species.

Animals↗

PubMed1993

Behavior genetic analyses of drug withdrawal.

Many studies with rodent models have illustrated the role of genetic factors in determining the severity of ethanol withdrawal. In studies using inbred mouse strains and mice selectively bred for drug sensitivity, a consistent finding has been that genotypes susceptible to alcohol withdrawal are also susceptible to withdrawal from other drugs with CNS depressant effects. A new method for rough genetic mapping of genes associated with withdrawal, quantitative trait loci (QTL) gene mapping, has recently been employed in the BXD RI recombinant inbred mouse series. Several QTLs are associated with alcohol withdrawal: One such QTL on Chromosome 1 is described. An area of Chromosome 2 contains a QTL marker for a gene affecting withdrawal from acute and chronic ethanol, nitrous oxide, and high-pressure neurological syndrome Type I clonic convulsions.

Animals↗

PubMed2003

Inferences regarding the numbers and locations of QTLs under multiple-QTL models using interval mapping and composite interval mapping.

This paper examines the properties of likelihood maps generated by interval mapping (IM) and composite interval mapping (CIM), two widely used methods for detecting quantitative trait loci (QTLs). We evaluate the usefulness of interpretations of entire maps, rather than only evaluating summary statistics that consider isolated features of maps. A simulation study was performed in which traits with varying genetic architectures, including 20-40 QTLs per chromosome, were examined with both IM and CIM under different marker densities and sample sizes. IM was found to be an unreliable tool for precise estimation of the number and locations of individual QTLs, although it has greater power for simply detecting the presence of QTLs than CIM. The ability of CIM to resolve the correct number of QTLs and to estimate their locations correctly is good if there are three or fewer QTLs per 100 centiMorgans, but can lead to erroneous inferences for more complex architectures. When the underlying genetic architecture of a trait consists of several QTLs with randomly distributed effects and locations likelihood profiles were often indicative of a few underlying genes of large effect. Studies that have detected more than a few QTLs per chromosome should be interpreted with caution.

Animals↗

PubMed2000

QTL influencing blood pressure maps to the region of PPH1 on chromosome 2q31-34 in Old Order Amish.

BACKGROUND: Hypertension is a major risk factor for coronary heart disease, stroke, congestive heart failure, renal insufficiency, and peripheral vascular disease. Although the genetic contribution to variation in blood pressure is well recognized, the specific genes involved are mostly unknown. We carried out a genome-wide scan to identify loci influencing blood pressure in the Old Order Amish population of Lancaster County, Pennsylvania. METHODS AND RESULTS: Blood pressures were measured in 694 adult participants from families recruited without regard to blood pressure. We performed a quantitative linkage analysis by using 357 microsatellite markers. In multipoint analysis, strong evidence for linkage was observed with both diastolic (lod=3.36; P=0.00004) and to a lesser extent systolic (lod=1.64; P=0.003) blood pressure in the region of chromosome 2q31-34. Peak evidence for linkage occurred at map positions 217 and 221 cM from pter for diastolic and systolic blood pressure, respectively. CONCLUSIONS: A gene linked to familial primary pulmonary hypertension has recently been mapped to this same region, suggesting the intriguing hypothesis that other (attenuated) mutations in this same gene may influence variation in systolic and diastolic blood pressure in this population.

Adult↗

PubMed2002

High-resolution genetic mapping of the ACE-linked QTL influencing circulating ACE activity.

Fine-mapping of trait loci through combined linkage and association analysis is an important component of strategies designed to identify causative gene variants, particularly in situations where the trait may be influenced by one or more of many polymorphisms within the same gene. Angiotensin-1 converting enzyme (ACE) provides one of the best models for developing and testing such methodologies, as a major fraction of the heritable variation in the activity of the angiotensin-1 converting enzyme (ACE) is tightly linked to the ACE gene. Moreover, ACE contains many frequent polymorphisms that are in strong linkage disequilibrium with each other. Although none of these variants induces a significant amino-acid change, one or more, either singly or in combination, are likely to have a strong effect on the quantitative phenotype. Here, we show that measured-haplotype analysis of SNP data from a large European family cohort can be used to localise the major ACE-linked genetic factors influencing the trait to a 16 kb interval within the gene, thus limiting the number of ACE variants that need to be considered in future studies designed to elucidate their biological effects. The approaches developed will be applicable to the fine-mapping of other quantitative trait loci in humans.

Amino Acid Substitution↗

PubMed2003

Efficient construction of high-density linkage map and its application to QTL analysis in barley.

Using a High Efficiency Genome Scanning (HEGS) system and recombinant inbred (RI) lines derived from the cross of Russia 6 and H.E.S. 4, a high-density genetic map was constructed in barley. The resulting 1,595.7-cM map encompassed 1,172 loci distributed on the seven linkage groups comprising 1,134 AFLP, 34 SSR, three STS and vrs1 (kernel row type) loci. Including PCR reactions, gel electrophoresis and data processing, 6 months of work by a single person was sufficient for the whole mapping procedure under a reasonable cost. To make an appraisal of the resolution of genetic analysis for the 95 RI lines based on the constructed linkage map, we measured three agronomic traits: plant height, spike exsertion length and 1,000-kernel weight, and the analyzed quantitative trait loci (QTLs) associated with these traits. The results were compared on the number of detected QTLs and their effects between a high-density map and a skeleton map constructed by selected AFLP and anchor markers. The composite interval mapping on the high-density map detected more QTLs than the other analyses. Closely linked markers with QTLs on the high-density map could be powerful tools for marker-assisted selection in barley breeding programs and further genetic analyses including an advanced backcross analysis or a map-based cloning of QTL.

Chromosome Mapping↗

PubMed1992

A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.

Animals↗

PubMed2000

Markov chain Monte Carlo for mapping a quantitative trait locus in outbred populations.

A Bayesian approach is presented for mapping a quantitative trait locus (QTL) using the 'Fernando and Grossman' multivariate Normal approximation to QTL inheritance. For this model, a Bayesian implementation that includes QTL position is problematic because standard Markov chain Monte Carlo (MCMC) algorithms do not mix, i.e. the QTL position gets stuck in one marker interval. This is because of the dependence of the covariance structure for the QTL effects on the adjacent markers and may be typical of the 'Fernando and Grossman' model. A relatively new MCMC technique, simulated tempering, allows mixing and so makes possible inferences about QTL position based on marginal posterior probabilities. The model was implemented for estimating variance ratios and QTL position using a continuous grid of allowed positions and was applied to simulated data of a standard granddaughter design. The results showed a smooth mixing of QTL position after implementation of the simulated tempering sampler. In this implementation, map distance between QTL and its flanking markers was artificially stretched to reduce the dependence of markers and covariance. The method generalizes easily to more complicated applications and can ultimately contribute to QTL mapping in complex, heterogeneous, human, animal or plant populations.

Animals↗

PubMed2004

Pleiotropic effects of the Arabidopsis cryptochrome 2 allelic variation underlie fruit trait-related QTL.

The previous molecular identification of a flowering time QTL segregating in the Arabidopsis L er x Cvi cross, demonstrated that natural allelic variation at the blue light photoreceptor CRY2 gene affects flowering time (El-Assal et al., 2001). In addition, previous works on the same cross have mapped several QTL affecting other unrelated life history traits in the CRY2 genomic region. In the present report, we have used a set of Arabidopsis L er transgenic plants carrying four different functional CRY2 transgenes for phenotypic analyses, with the aim of exploring the extent of pleiotropy of CRY2 allelic variation. It is concluded that previously identified QTL affecting fruit length, ovule number per fruit, and percentage of unfertilized ovules are caused by this same Ler/Cvi CRY2 allelic variation. In addition, dose effects of the CRY2-L er allele are detected for fruit length. A seed weight QTL at the map position of CRY2 could not be confirmed and also no effect on seed dormancy was observed. Thus, it is shown that transgenic plants carrying different alleles can be a useful tool to attribute QTL for different complex traits to a specific locus, even when the relationship among the traits has not been previously suggested.

Alleles↗

PubMed2001

Interval mapping of quantitative trait loci in autotetraploid species.

This article presents a method for QTL interval mapping in autotetraploid species for a full-sib family derived by crossing two parents. For each offspring, the marker information on each chromosome is used to identify possible configurations of chromosomes inherited from the two parents and the locations of crossovers on these chromosomes. A branch and bound algorithm is used to identify configurations with the minimum number of crossovers. From these configurations, the conditional probability of each possible QTL genotype for a series of positions along the chromosome can be estimated. An iterative weighted regression is then used to relate the trait values to the QTL genotype probabilities. A simulation study is performed to assess this approach and to investigate the effects of the proportion of codominant to dominant markers, the heritability, and the population size. We conclude that the method successfully locates QTL and estimates their parameters accurately, and we discuss different modes of action of the QTL that may be modeled.

Algorithms↗

PubMed2006

Development of congenic rat strains for alcohol consumption derived from the alcohol-preferring and nonpreferring rats.

A genome scan of the F2 generation from an inbred alcohol-preferring (iP) and inbred alcohol-nonpreferring (iNP) rat cross identified a significant quantitative trait locus (QTL) on chromosome 4 with a lod score of 9.2. To confirm this QTL and to create animals for fine mapping of the QTL region, chromosome 4 reciprocal congenic strains were developed by transferring the chromosome 4 QTL interval into the respective iP or iNP backgrounds. The iP strain was crossed with the iNP strain to create iPiNP F1 animals, which were backcrossed to either iNP or iP animals to produce the N2 generation. Using marker-assisted selection, 10 generations of backcrossing were performed. The selection was followed by an intercross between the N10 animals to produce homozygous animals (N10F1), resulting in the finished congenic strains. Congenic strains in which the iP chromosome 4 QTL interval was transferred to the iNP (NP.P) and the iNP chromosome 4 QTL was transferred to the iP (P.NP) exhibited the expected effect on alcohol consumption of the donor strain. Development of these congenic strains further indicates that the chromosome 4 QTL region is, in part, responsible for the disparate alcohol consumption observed between the iP and iNP rats. These congenic animals will be an invaluable resource for fine mapping the QTL region and for the identification of the gene(s) that influences the drinking behavior of the iP and iNP rats.

Alcohol Drinking↗

PubMed1999

Sequence polymorphisms in the chemokines Scya1 (TCA-3), Scya2 (monocyte chemoattractant protein (MCP)-1), and Scya12 (MCP-5) are candidates for eae7, a locus controlling susceptibility to monophasic remitting/nonrelapsing experimental allergic encephalomyelitis.

Experimental allergic encephalomyelitis (EAE), the principal animal model of multiple sclerosis, is genetically controlled. To date, 13 disease-modifying loci have been identified in the mouse by whole genome scanning using an F2 intercross between EAE-susceptible SJL/J and EAE-resistant B10.S/DvTe mice. Two quantitative trait loci (QTL), eae6 and eae7, on chromosome 11 were identified by classical marker-specific linkage analysis and interval mapping. Both QTL were reported to be associated with severity and duration of clinical signs. eae7 was subsequently shown to be a unique locus controlling the development of monophasic remitting/nonrelapsing EAE. In this study, composite interval mapping resolved eae6 into two linked QTL: eae6a at 0-13 cM is associated with disease severity, and eae6b at 19-28 cM associated with the duration of clinical signs. Additionally, composite interval mapping significantly refined the locations of eae6a, eae6b, and eae7, thereby facilitating systematic candidate gene screening by cDNA sequencing of SJL/J and B10.S/DvTe alleles. Sequence polymorphisms were not seen in Lif and IL12 beta, candidate genes for eae6a and eae6b, respectively. Similarly, cDNA sequence polymorphisms in Nos2, Scya3, Scya4, Scya5, Scya6, Scya7, Scya9, Scya10, and Scya11 were excluded as candidates for eae7. However, multiple sequence polymorphisms resulting in significant amino acid substitutions were identified in Scya1 (TCA-3), Scya2 (monocyte chemoattractant protein (MCP)-1), and Scya12 (MCP-5). Given the role of chemokines in EAE, these sequence polymorphisms are promising candidates for eae7, a locus associated with severity of clinical signs and susceptibility to the shorter, less severe monophasic remitting/nonrelapsing form of disease.

Amino Acid Sequence↗

PubMed2000

Quantitative trait loci and candidate gene mapping of bud set and bud flush in populus.

The genetic control of bud phenology in hybrid poplar was studied by mapping quantitative trait loci (QTL) affecting the timing of autumn bud set and spring bud flush. The founders of the mapping pedigree were collected from widely separated latitudes to maximize segregating variation for dormancy-related traits in the F(2) generation-the female Populus trichocarpa parent is from Washington State (48 degrees N) and the male P. deltoides parent is from Texas (31 degrees N). Bud set and bud flush timing were measured on the F(2) generation in a replicated clonal field trial. Using a linkage map constructed of AFLP and microsatellite markers, three QTL controlling bud set and six QTL controlling bud flush were detected. Additionally, five candidate genes believed to be involved in perception of photoperiod (PHYB1, PHYB2) or transduction of abscisic acid response signals (ABI1B, ABI1D, and ABI3) were placed on the QTL map. PHYB2 and ABI1B were found to be coincident with QTL affecting bud set and bud flush.

Base Sequence↗

PubMed1997

Mapping quantitative trait loci for fear-like behaviors in mice.

Two mouse models developed for screening anxiolytic drugs were selected for genetic analysis, namely "wall-seeking" tendency in an open field ("thigmotaxis") and the light-to-dark transition (LD) paradigm, a conflict test. These tests measure differences in naturalistic tendencies of mice to explore a novel environment and to avoid a bright light or the center of an open field. In an F2 intercross of two strains of mice (A/J and C57BL/6J) that differ markedly in these behaviors, we estimated a broad sense heritability ranging from 0.3 to 0.59. With this intercross (n = 518), we have mapped several quantitative trait loci (QTL) for these behaviors by performing a genome-wide search. A significant QTL on chromosome 10 (near D10Mit237; LOD of 9.3) that affects LD behavior was identified, and suggestive QTL (LOD > 2.8) were mapped to chromosomes 6, 15, 19, and X. For center time behaviors, QTL were identified on chromosome 1 (LOD of 7.7 and 4.0 for the initial 5-min epoch and the first trial average of the next two 5-min epochs, respectively), and suggestive QTL (LOD > 2.8) were mapped to chromosomes 6 and 14. These QTL individually explain from 2.3 to 8.4% of the phenotypic variance. Collectively, the multiple independent QTL explain from 3.5 to 26.5% of the F2 population's phenotypic variance, depending on the trait. The complexity and heterogeneity of the genetic factors underlying these fear-like behaviors are illustrated by the lack of shared QTL between paradigms and by mapping different QTL for repeated trials of behavior. The identification of QTL affecting individual differences in fear-like behavior may lead to the identification of new gene products and pathways that modulate behavior, providing targets for rational drug design.

Animals↗

PubMed2002

Linkage disequilibrium mapping of quantitative trait loci under truncation selection.

As a dense map of single nucleotide polymorphism (SNP) markers are available, population-based linkage disequilibrium (LD) mapping or association study is becoming one of the major tools for identifying quantitative trait loci (QTL) and for fine gene mapping. However, in many cases, LD between the marker and trait locus is not very strong. Approaches that maximize the potential of detecting LD will be essential for the success of LD mapping of QTL. In this paper, we propose two strategies for increasing the probability of detecting LD: (1) phenotypic selection and (2) haplotype LD mapping. To provide the foundations for LD mapping of QTL under selection, we develop analytic tools for assessing the impact of phenotypic selection on allele and haplotype frequencies, and LD under three trait models: single trait locus, two unlinked trait loci, and two linked trait loci with or without epistasis. In addition to a traditional chi(2) test, which compares the difference in allele or haplotype frequencies in the selected sample and population sample, we present multiple regression methods for LD mapping of QTL, and investigate which methods are effective in employing phenotypic selection for QTL mapping. We also develop a statistical framework for investigating and comparing the power of the single marker and multilocus haplotype test for LD mapping of QTL. Finally, the proposed methods are applied to mapping QTL influencing variation in systolic blood pressure in an isolated Chinese population.

Chi-Square Distribution↗

PubMed2001

Genetic analysis of collagen-induced arthritis in rats: a polygenic model for rheumatoid arthritis predicts a common framework of cross-species inflammatory/autoimmune disease loci.

Collagen-induced arthritis (CIA) is a useful model for dissecting the genetic patterns underlying susceptibility to rheumatoid arthritis (RA) and related chronic/inflammatory autoimmune diseases. CIA exhibits three phenotypes characteristic of autoimmune disease pathogenesis: abnormal levels of immune reactivity to self antigens; chronic inflammation of target organs expressing that specific autoantigen; activation and direct participation of invading mononuclear cells and resident tissue fibroblasts in organ damage. Over 25 different quantitative trait loci (QTL) regulating arthritis severity and autoantibody in rats with CIA are mapped. QTL-congenic strains show that certain CIA-QTLs can modulate arthritis independently These monogenic models are proving to be highly informative for fine mapping and function studies, revealing gender effects and evidence of gene clusters. Recent genome scans of RA populations identified RA-susceptibility loci in chromosome regions homologous to rat chromosomal segments housing CIA-QTLs. Also, CIA-QTLs frequently co-localize with susceptibility QTLs mapped in other rat arthritis models induced with non-immunogenic adjuvant oils and/or in rat autoimmune models of multiple sclerosis and diabetes. Common autoimmunity genes and inflammation genes important to several human diseases are likely being detected in the various rat disease models. Continued dissection of the genetic underpinnings of rat arthritis models should provide candidate genes for investigation in human patients and lead to a clearer understanding of the complex genetics of RA.

Animals↗

PubMed2003

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas fir. III. Quantitative trait loci-by-environment interactions.

Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring temperatures. A three-generation mapping population of 460 cloned progeny was used for genetic mapping and phenotypic evaluations. An all-marker interval mapping method was used for scanning the genome for the presence of QTL and single-factor ANOVA was used for estimating QTL-by-environment interactions. A modest number of QTL were detected per trait, with individual QTL explaining up to 9.5% of the phenotypic variation. Two QTL-by-treatment interactions were found for growth initiation, whereas several QTL-by-treatment interactions were detected among growth cessation traits. This is the first report of QTL interactions with specific environmental signals in forest trees and will assist in the identification of candidate genes controlling these important adaptive traits in perennial plants.

Genetic Linkage↗

PubMed2004

Quantitative trait loci (QTL) detection in multicross inbred designs: recovering QTL identical-by-descent status information from marker data.

Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the parameter estimates depend largely on the choice of the two parental lines. Thus, the QTL detected in such populations represent only a small part of the genetic architecture of the trait. In addition, the effects of only two alleles are characterized, which is of limited interest to the breeder, while common pedigree breeding material remains unexploited for QTL mapping. In this study, we extend QTL mapping methodology to a generalized framework, based on a two-step IBD variance component approach, applicable to any type of breeding population obtained from inbred parents. We then investigate with simulated data mimicking conventional breeding programs the influence of different estimates of the IBD values on the power of QTL detection. The proposed method would provide an alternative to the development of specifically designed recombinant populations, by utilizing the genetic variation actually managed by plant breeders. The use of these detected QTL in assisting breeding would thus be facilitated.

Computer Simulation↗