Does dong quai have estrogenic effects in postmenopausal women? A double-blind, placebo-controlled trial

The simulated extended pedigree data of the Genetic Analysis Workshop 10 were used to examine the relationship between several quantitative traits (Q1-Q5), an environmental factor, age and sex and to identify genes contributing to the quantitative traits. A forward selection procedure was used to identify regression models for each trait. Residuals from these regression models were used as quantitative traits in linkage analysis. Two-point sib-pair analysis was performed on Replicate 1 of the data set using SIBPAL. Sixteen regions on 8 chromosomes yielded two-point p-values < 0.005 in Replicate 1. Two strategies for utilizing a second data set were evaluated. In a two-stage approach, only those regions with p-value < 0.005 in Replicate 1 were followed up in the second data set. Nine of these regions had p-values < 0.05 in Replicate 2; four were associated with major genes included in the generating model and the remaining five regions were false positives. An alternative strategy was to perform a repeat genome wide screen in the second data set. This strategy resulted in the identification of 20 regions with p-values < 0.05 in both replicates; five of which included major genes included in the generating model. Although the false positive rate increased when a complete genome screen was performed on both data sets, the two-stage screen, with a more stringent initial criterion for identifying suggestive linkages, had a higher rate of false negatives. For some studies, conducting two complete genome screens in a split-sample design may be worthwhile.     

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.     

Molecular dissection of developmental behavior of plant height in rice (Oryza sativa L.)

A doubled haploid population of 123 lines from IR64/Azucena was used to dissect the developmental behavior and genotype by environment interaction for plant height by conditional and unconditional quantitative trait loci (QTL) mapping methods in rice. It was shown that the number of QTL detected was different at various measuring stages. Some QTL could be detected at all stages and some only at one or several stages. More QTL could be found on the basis of time-dependent measures of different stages. By conditional QTL mapping of time-dependent measures, it is possible to reveal dynamic gene expression for quantitative traits. Mapping QTL for genetic main effects and GE interaction effects could help us in understanding the nature of QTL x environment interaction for the development of quantitative traits.     

Quantitative trait loci affecting differences in floral morphology between two species of monkeyflower (Mimulus)

Conspicuous differences in floral morphology are partly responsible for reproductive isolation between two sympatric species of monkeyflower because of their effect on visitation of the flowers by different pollinators. Mimulus lewisii flowers are visited primarily by bumblebees, whereas M. cardinalis flowers are visited mostly by hummingbirds. The genetic control of 12 morphological differences between the flowers of M. lewisii and M. cardinalis was explored in a large linkage mapping population of F2 plants n = 465 to provide an accurate estimate of the number and magnitude of effect of quantitative trait loci (QTLs) governing each character. Between one and six QTLs were identified for each trait. Most (9/12) traits appear to be controlled in part by at least one major QTL explaining >/=25% of the total phenotypic variance. This implies that either single genes of individually large effect or linked clusters of genes with a large cumulative effect can play a role in the evolution of reproductive isolation and speciation.     

Quantitative trait loci and metabolic pathways

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for "channeling" of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits.     

Genetic dissection of obesity in polygenic animal models

In contrast to diseases caused by single-gene defects, many of the most common human maladies such as obesity, atherosclerosis, diabetes, and hypertension exhibit continuous phenotypic variation and a predominantly multifactorial and polygenic basis. Genes with roles in energy balance, nutrient partitioning, lipid and insulin metabolism, and a variety of behavioral traits are likely interacting with environmental stimuli to regulate obesity phenotypes. With the current proliferation of highly polymorphic genetic markers and the refinement of experimental approaches, it is now possible to screen thoroughly the genomes of model organisms for the individual genes or quantitative trait loci (QTL) that control measurable polygenic traits such as obesity. With the growing wealth of comparative mapping, it will be possible to predict the location of a homologous locus in the human after first mapping it in the mouse. Many experiments have been conducted in mice, rats, and pigs to estimate the number, location, and effect of QTL controlling obesity and related traits. This review describes the design and strategies of such studies and summarizes the results and their implications toward understanding the complex nature of obesity in humans.     

Estimation of effects of quantitative trait loci in large complex pedigrees

A method was derived to estimate effects of quantitative trait loci (QTL) using incomplete genotype information in large outbreeding populations with complex pedigrees. The method accounts for background genes by estimating polygenic effects. The basic equations used are very similar to the usual linear mixed model equations for polygenic models, and segregation analysis was used to estimate the probabilities of the QTL genotypes for each animal. Method R was used to estimate the polygenic heritability simultaneously with the QTL effects. Also, initial allele frequencies were estimated. The method was tested in a simulated data set of 10,000 animals evenly distributed over 10 generations, where 0, 400 or 10,000 animals were genotyped for a candidate gene. In the absence of selection, the bias of the QTL estimates was < 2%. Selection biased the estimate of the Aa genotype slightly, when zero animals were genotyped. Estimates of the polygenic heritability were 0.251 and 0.257, in absence and presence of selection, respectively, while the simulated value was 0.25. Although not tested in this study, marker information could be accommodated by adjusting the transmission probabilities of the genotypes from parent to offspring according to the marker information. This renders a QTL mapping study in large multi-generation pedigrees possible.     

Selection with recurrent backcrossing to develop congenic lines for quantitative trait loci analysis

SEWALL WRIGHT suggested that genes of large effect on a quantitative trait could be isolated by recurrent backcrossing with selection on the trait. Loci [quantitative trait loci (QTL)] at which the recurrent and nonrecurrent lines have genes of different large effect on the trait would remain segregating, while other loci would become fixed for the gene carried by the recurrent parent. If the recurrent line is inbred and the backcrossing and selection is conducted in a series of replicate lines, in each of which only one backcross parent is selected for each generation, the lines will become congenic to the recurrent parent except for the QTL of large effect and closely linked regions of the genome, and these regions can be identified using a dense set of markers that differ between the parental lines. Such lines would be particularly valuable for subsequent fine-scale mapping and gene cloning; but by chance, even QTL of large effect will be lost from some lines. The probability that QTL of specified effect remain segregating is computed as a function of its effect on the trait, the intensity of selection, and the number of generations of backcrossing. Analytical formulas are given for one or two loci, and simulation is used for more. It is shown that the method could have substantial discriminating ability and thus potential practical value.     

Personality genetics

Although 30-60% of the variance in many personality traits is inherited, until recently little was known about the responsible genes. Preliminary studies of family history in bipolar disorder and of X-linkage of personality traits in color-blindness suggested a "quantitative trait locus" (QTL) approach to the genetics of normal personality. In methodically similar but independent studies of 124 Israeli and 315 American normal volunteers we showed an association between the dopamine D4 receptor gene (D4DR) and the personality trait of novelty seeking. In the Israeli sample we also found an interaction between the D4DR gene and the serotonin 2C receptor gene (5-HT2C) with a marked effect on the trait of reward dependence. Further investigation of genes for personality traits may suggest links between normal personality and psychiatric illness.     

Genes on mouse chromosomes 2 and 9 determine variation in ethanol consumption

Quantitative trait locus (QTL) mapping efforts in alcohol (ethanol) research are beginning to generate promising data that may ultimately lead to the identification of genes influencing alcohol addiction. Rodents have been extensively utilized to study ethanol's rewarding and aversive effects, and to demonstrate the existence of genetic influences on traits such as free-choice ethanol-consumption, ethanol-conditioned place preference and ethanol-conditioned taste aversion. The purpose of the current investigation was to verify or eliminate from further consideration putative QTLs for free-choice ethanol consumption originally identified in BXD Recombinant Inbred (RI) strains and other informative genetic crosses. B6D2F2 mice were utilized in a verification testing strategy to evaluate the viability of putative ethanol consumption QTLs. When data were combined from BXD RI, B6D2F2 and short-term selected line (STSL) mapping studies, verification was obtained for two QTLs, one on Chromosome (Chr) 9 (proximal-mid) and another on Chr 2 (distal), and suggestive verification was obtained for QTLs on Chrs 2 (proximal), 3, 4, 7, and 15. In addition, the possible genetic association of ethanol consumption with conditioned place preference was evaluated. Genetic correlations were estimated from BXD RI strain means, and QTL maps for these traits were compared to evaluate the possibility of a genetic association. The correlational analysis yielded a trend (r = 0.34, p = 0.09), but no statistically significant results. However, comparisons of QTL mapping results between phenotypes suggested some possible genetic overlap for these traits, both putative measures of ethanol reward. These data suggest that the determinants of these two measures are genetically diverse, but may share some common genetic elements.     

A nonparametric bootstrap method for testing close linkage vs. pleiotropy of coincident quantitative trait loci

A novel method using the nonparametric bootstrap is proposed for testing whether a quantitative trait locus (QTL) at one chromosomal position could explain effects on two separate traits. If the single-QTL hypothesis is accepted, pleiotropy could explain the effect on two traits. If it is rejected, then the effects on two traits are due to linked QTLs. The method can be used in conjunction with several QTL mapping methods as long as they provide a straightforward estimate of the number of QTLs detectable from the data set. A selection step was introduced in the bootstrap procedure to reduce the conservativeness of the test of close linkage vs. pleiotropy, so that the erroneous rejection of the null hypothesis of pleiotropy only happens at a frequency equal to the nominal type I error risk specified by the user. The approach was assessed using computer simulations and proved to be relatively unbiased and robust over the range of genetic situations tested. An example of its application on a real data set from a saline stress experiment performed on a recombinant population of wheat (Triticum aestivum L. ) doubled haploid lines is also provided.     

Negative regulation of transcription by anti-sigma factors

The identification, mapping and eventual cloning of genes which determine or influence important epidemiological traits in parasites can have great benefits for the control of parasitic disease. In this review, strategies are outlined for identifying genetic markers for complex, quantitative traits. A genetic marker is a variable DNA sequence which co-occurs with a variable quantitative trait. Candidate markers are chosen because they are thought to directly influence the trait whereas random markers are expected to be linked to another DNA sequence which influences the trait. Association studies compare the value of a quantitative trait between different marker genotype classes in a population, without regard to family structure. Linkage studies compare the value of a quantitative trait between marker genotype classes within families or within a population (usually derived from a cross between inbred lines) which is segregating for both marker and quantitative trait loci. The most commonly used analytical methods for determining the significance of association or linkage between marker and quantitative trait loci, and for estimating parameters such as recombination rate and quantitative gene action, are least-squares and maximum likelihood. Both methods may be used to test either single markers or the interval between flanking markers, and both suffer from the need to minimize type I and type II error rates with multiple tests.     

Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects

The efficiency of marker-assisted selection (MAS) depends on the power of quantitative trait locus (QTL) detection and unbiased estimation of QTL effects. Two independent samples N = 344 and 107 of F2 plants were genotyped for 89 RFLP markers. For each sample, testcross (TC) progenies of the corresponding F3 lines with two testers were evaluated in four environments. QTL for grain yield and other agronomically important traits were mapped in both samples. QTL effects were estimated from the same data as used for detection and mapping of QTL (calibration) and, based on QTL positions from calibration, from the second, independent sample (validation). For all traits and both testers we detected a total of 107 QTL with N = 344, and 39 QTL with N = 107, of which only 20 were in common. Consistency of QTL effects across testers was in agreement with corresponding genotypic correlations between the two TC series. Most QTL displayed no significant QTL x environment nor epistatic interactions. Estimates of the proportion of the phenotypic and genetic variance explained by QTL were considerably reduced when derived from the independent validation sample as opposed to estimates from the calibration sample. We conclude that, unless QTL effects are estimated from an independent sample, they can be inflated, resulting in an overly optimistic assessment of the efficiency of MAS.     

Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine

We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.). QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (> 2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among alleles at QTL (deviation from additive gene action). Restriction fragment length polymorphism (RFLP) marker genotypes and wood specific gravity phenotypes were determined for 177 progeny. Two RFLP linkage maps were constructed, representing maternal and paternal parent gamete segregations as inferred from diploid progeny RFLP genotypes. RFLP loci segregating for multiple alleles were vital for aligning the two maps. Each RFLP locus was assayed for cosegregation with WSG QTL using analysis of variance (ANOVA). Five regions of the genome contained one or more RFLP loci showing differences in mean WSG at or below the P = 0.05 level for progeny as grouped by RFLP genotype. One region contained a marker locus (S6a) whose QTL-associated effects were highly significant (P > 0.0002). Marker S6a segregated for multiple alleles, a prerequisite for determining the number of alleles segregating at the linked QTL and analyzing the interactions among QTL alleles. The QTL associated with marker S6a appeared to be segregating for multiple alleles which interacted with each other and with environments. No evidence for digenic epistasis was found among the five QTL.     

Murine susceptibility to radiation-induced pulmonary fibrosis is influenced by a genetic factor implicated in susceptibility to bleomycin-induced pulmonary fibrosis

From evidence of interpatient variability in normal tissue sensitivity to radiotherapy and from radiation studies using inbred mouse strains, it is hypothesized that individual variation in susceptibility to radiation-induced pulmonary fibrosis is genetically controlled. A genetic model has been developed from the fibrosis-prone C57BL/6J and the fibrosis-resistant C3Hf/Kam mouse strains. Inheritance of the fibrotic phenotype was characterized in F1 and F2 (F1 intercross) generations derived from the parental strains. Genetic mapping was used to determine whether the quantitative trait loci (QTL), which influence susceptibility to bleomycin-induced lung fibrosis in these progenitor strains, could be implicated in susceptibility to radiation-induced lung fibrosis. Mice were treated with 14 or 16 Gy (60Co) to the whole thorax. The doses were selected to investigate the response at the LD50 and LD100 of C3Hf/Kam mice. The animals were sacrificed 33 weeks after treatment or when moribund. The percentage of lung with fibrosis for each mouse was quantified with image analysis of a histological section of the lung. For both the 14- and 16-Gy data sets, heritability was estimated at 38 +/- 11%, and the number of genetic factors influencing susceptibility to pulmonary fibrosis was estimated to be one or two. Two hundred fifty-five F2 intercross mice were genotyped with markers at the bleomycin loci on chromosomes 11 and 17 (chromosome 17 marker is at the major histocompatibility complex). Genetic linkage was established for the marker on chromosome 17 (P = 3.0 x 10(-6)), which accounts for 6.6% of the F2 phenotypic variance but not for the markers surrounding the QTL on chromosome 11 (P = 0.37). The inheritance data suggested that susceptibility to radiation-induced pulmonary fibrosis is a heritable trait controlled by two genetic loci, and through genomic mapping, a QTL on chromosome 17 was identified as one of the loci.     

Mapping a quantitative trait locus involved in melanotic encapsulation of foreign bodies in the malaria vector, Anopheles gambiae

A Plasmodium-refractory strain of Anopheles gambiae melanotically encapsulates many species of Plasmodium, whereas wild-type mosquitoes are usually susceptible. This encapsulation trait can also be observed by studying the response of refractory and susceptible strains to intrathoracically injected CM-Sephadex beads. We report the results of broad-scale quantitative trait locus (QTL) mapping of the encapsulation trait using the bead model system. Interval mapping using the method of maximum likelihood identified one major QTL, Pen1. The 13.7-cM interval containing Pen1 was defined by marker AGH157 at 8E and AGH46 at 7A on 2R. Pen1 was associated with a maximum LOD score of 9.0 and accounted for 44% of the phenotypic variance in the distribution of phenotypes in the backcross. To test if this QTL is important for encapsulation of Plasmodium berghei, F2 progeny were infected with P. berghei and evaluated for degree of parasite encapsulation. For each of the two markers that define the interval containing Pen1, a significant difference of encapsulation was seen in progeny with at least one refractory allele in contrast with homozygous susceptible progeny. These results suggest that Pen1 is important for melanotic encapsulation of Plasmodium as well as beads.     

Mapping quantitative trait loci for carcass and meat quality traits in a wild boar x Large White intercross

An intercross between wild boar and a domestic Large White pig population was used to map quantitative trait loci (QTL) for body proportions, weight of internal organs, carcass composition, and meat quality. The results concerning growth traits and fat deposition traits have been reported elsewhere. In the present study, all 200 F2 animals, their parents, and their grandparents were genotyped for 236 markers. The marker genotypes were used to calculate the additive and dominance coefficients at fixed positions in the genome of each F2 animal, and the trait values were regressed onto these coefficients in intervals of 1 cM. In addition, the effect of proportion of wild boar alleles was tested for each chromosome. Significant QTL effects were found for percentage lean meat and percentage lean meat plus bone in various cuts, proportion of bone in relation to lean meat in ham, muscle area, and carcass length. The significant QTL were located on chromosomes 2, 3, 4, and 8. Each QTL explained 9 to 16% of the residual variance of the traits. Gene action for most QTL was largely additive. For meat quality traits, there were no QTL that reached the significance threshold. However, the average proportion of wild boar alleles across the genome had highly significant effects on reflectance and drip loss. The results show that there are several chromosome regions with a considerable effect on carcass traits in pigs.     

Genetic analysis of the corticosterone response to ethanol in BXD recombinant inbred mice.

The genetic control over the corticosterone response to ethanol (EtOH) and its possible relationship to other EtOH-related traits was examined using BXD recombinant inbred (RI) strains derived from an F2 cross of C57BL/6J (B6) and DBA/2J (D2) progenitor strains. Quantitative trait locus (QTL) analysis of corticosterone levels 1 hr following EtOH suggested the influence of a single major gene on this trait. Two loci were predicted to account for 47% of the genetic variance in plasma corticosterone levels 6 hr following EtOH, whereas 3 loci were predicted to account for 78% of the genetic variance in corticosterone levels 7 hrs following EtOH. Markers associated with corticosterone levels 7 hrs following EtOH and corrected corticosterone levels 6 hrs post-EtOH overlapped with ones found to influence acute and chronic EtOH withdrawal severity, suggesting some degree of common genetic determination between these traits. Overall these results indicate that gene action significantly influences stress responsiveness and suggest possible chromosomal locations of these genes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Linkage of a gene causing high bone mass to human chromosome 11 (11q12-13)

The purpose of this paper is to report the linkage of a genetic locus (designated "HBM") in the human genome to a phenotype of very high spinal bone density, using a single extended pedigree. We measured spinal bone-mineral density, spinal Z(BMD), and collected blood from 22 members of this kindred. DNA was genotyped on an Applied Biosystems model 377 (ABI PRISM Linkage Mapping Sets; Perkin Elmer Applied Biosystems), by use of fluorescence-based marker sets that included 345 markers. Both two-point and multipoint linkage analyses were performed, by use of affected/unaffected and quantitative-trait models. Spinal Z(BMD) for affected individuals (N = 12) of the kindred was 5.54 +/- 1.40; and for unaffected individuals (N = 16) it was 0.41 +/- 0.81. The trait was present in affected individuals 18-86 years of age, suggesting that HBM influences peak bone mass. The only region of linkage was to a series of markers on chromosome 11 (11q12-13). The highest LOD score (5.21) obtained in two-point analysis, when a quantitative-trait model was used, was at D11S987. Multipoint analysis using a quantitative-trait model confirmed the linkage, with a LOD score of 5.74 near marker D11S987. HBM demonstrates the utility of spinal Z(BMD) as a quantitative bone phenotype that can be used for linkage analysis. Osteoporosis pseudoglioma syndrome also has been mapped to this region of chromosome 11. Identification of the causal gene for both traits will be required for determination of whether a single gene with different alleles that determine a wide range of peak bone densities exists in this region.