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PubMed1993

Determinants of interjudge agreement on personality traits: the big five domains, observability, evaluativeness, and the unique perspective of the self.

We examined several determinants of interjudge agreement on personality traits. The findings, which were cross-validated in two samples, suggest that agreement is a function of four factors: which Big Five content domain the trait represents, how observable relevant behaviors are, how evaluative the trait is, and whether the self is one of the judges. Agreement was highest for traits related to Extraversion and lowest for traits related to Agreeableness. More observable and less evaluative traits elicited higher interjudge agreement. On average, self-peer agreement was lower than peer-peer agreement. However, this effect was limited to evaluative traits; for neutral traits, self-peer agreement was as high as peer-peer agreement. These findings suggest that self- and peer perception proceed through similar processes for neutral traits but not for highly evaluative traits, raising the possibility that self-perceptions become distorted when the trait is affectively charged.

Evaluation Studies as Topic↗
PubMed1993

Schizophrenia-related and affective personality disorder traits in relatives of probands with schizophrenia and personality disorders.

OBJECTIVE: The possible heterogeneity of the schizophrenia-related personality disorder traits associated with DSM-III criteria for schizotypal personality disorder was investigated using the family history method. A familial relationship to schizophrenia was hypothesized for schizophrenia-related personality disorder traits without coexisting affective personality disorder traits, pure schizophrenia-related personality disorder traits. Alternatively, a familial relationship with borderline personality disorder was hypothesized for schizophrenia-related personality disorder traits with comorbid affective personality disorder traits. METHOD: Criteria for schizophrenia-related and affective personality disorder traits were used to assess the 588 nonpsychotic first-degree relatives of 55 chronic schizophrenic probands and 67 probands with personality disorders. The probands with one or more DSM-III personality disorders were categorized as having schizotypal personality disorder without borderline personality disorder (pure schizotypal personality disorder), borderline personality disorder without schizotypal personality disorder (pure borderline personality disorder), both disorders, or neither. RESULTS: The morbid risk of all cases of schizophrenia-related personality disorder traits was higher in relatives of probands with schizophrenia and pure schizotypal personality disorder than in relatives of probands with neither schizotypal nor borderline personality disorder; however, it differed only slightly from that observed in the relatives of probands with both schizotypal and borderline personality disorders and pure borderline personality disorder. In contrast, the risk of pure schizophrenia-related personality disorder traits was higher in relatives of probands with schizophrenia and pure schizotypal personality disorder, while the risk of coexisting schizophrenia-related and affective personality disorder traits was lower in both of these groups than among the relatives of probands with both schizotypal and borderline personality disorders and pure borderline personality disorder. CONCLUSIONS: These results offer preliminary indications that schizotypal personality disorder features present without comorbid affective personality disorder traits may more specifically characterize the personality characteristics familially related to schizophrenia. Furthermore, they indicate that schizotypal personality disorder features as currently defined are found in relatives of patients other than those with schizophrenia or schizotypal personality disorder.

Adult↗
PubMed2004

Developmental associations between traits: covariance and beyond.

Statistical associations between phenotypic traits often result from shared developmental processes and include both covariation between the trait values and more complex associations between higher moments of the joint distribution of traits. In this article, an analytical technique for calculating the covariance between traits is presented on the basis of (1). the distribution of underlying genetic and environmental variation that jointly influences the traits and (2). the mechanics of how these underlying factors influence the development of each trait. It is shown that epistasis can produce patterns of covariation between traits that are not seen in additive models. Applying this approach to a trait in parents and the same trait in their offspring allows us to study the consequences of epistasis for the evolution of additive genetic variance and heritability. This analysis is then extended to the study of more complicated associations between traits. It is shown that even traits that are not correlated may exhibit developmental associations that influence their joint evolution.

Biological Evolution↗
PubMed1997

The effect of adding further traits in index selection.

The effect on genetic and economic response of adding further traits in index selection was studied. This was done first using the true parameters and then using simulated parameter estimates and with "bending" to ensure consistent matrixes. The extra responses obtained in the full aggregate genotype were expressed as a percentage of the response before adding the trait. For simplicity the cases studied were limited to 2 to 4 traits, and to a range of simple parameter sets. The extra response from adding a further trait in index selection was very variable, but was often very large. As a simple rule, adding a trait with a high relative product (ah2) of the standardized economic weight (a) and heritability (h2) gave large extra response. Adding a trait with lower ah2 value gave less extra response. The extra responses were smaller if the correlations between the added trait and other traits with high relative ah2 were favorable and were larger if the correlations were unfavorable. With estimated parameters, the results from adding a further trait in index selection were more variable. For many cases the increase in the response was still large but for some cases the response was reduced. With poor parameter estimates the number of traits in index selection should be limited to those with the larger values of ah2. As the parameter estimates improve, more traits can be added without reducing overall genetic response. Even though some general tendencies have been discerned, there was much variation in the extra responses obtained.

Animals↗
PubMed2004

Genetic correlations between reproduction and production traits in swine.

Genetic correlations between reproduction and production traits were estimated in swine. Reproduction traits investigated were age at first service (AFS), number of live-born piglets in the first litter (NBA1), interval from weaning to first service after first litter (WTS1), number of live-born piglets in the second litter (NBA2), and interval from weaning to first service after the second litter (WTS2). Females generating the data were Norwegian Landrace born in nucleus herds between 1990 and 2000, and the number of records ranged from 13,792 to 56,932. Genetic correlations were estimated among the main production traits in the breeding goal: adjusted age at 100 kg live weight (A100), percentage of lean meat content (LMC), individual feed consumption from 25 to 100 kg (FC), and bacon side quality (BSQ). Average adjusted backfat thickness (BF) was included as a production trait. The A100 and BF traits were recorded on gilts on-farm with 190,454 records, whereas LMC, BSQ, and FC were recorded on-station with the number of records ranging from 12,487 to 12,992. Analyses were carried out with a multivariate animal model using average information restricted maximum likelihood procedures by first running each reproduction trait with A100 and BF, followed by each reproduction trait with LMC, BSQ, and FC. Average heritabilities for reproduction traits were as follows: AFS (0.38), NBA1 (0.11), WTS1 (0.06), NBA2 (0.12), and WTS2 (0.03); and for production traits: A100 (0.30), BF (0.44), FC (0.22), LMC (0.58), and BSQ (0.23). The highest genetic correlation was estimated between A100 and AFS (r(g)= 0.68), also resulting in a positive genetic correlation between FC and AFS. Growth (A100) was negatively (i.e., unfavorably) genetically correlated to NBA1 and NBA2 (r(g) = 0.60 and rg = 0.42 respectively), and so the genetic correlation to FC also became unfavorable (r(g)= 0.23 and r(g) = 0.20). Single-trait selection for enhanced LMC would also affect NBA1 and NBA2 unfavorably (r(g)= -0.12 and r(g)= -0.24). Correlations between BF at 100 kg live weight and reproduction traits were close to zero; however, a low genetic correlation between BF and WTS1 was obtained (r(g)= -0.12), indicating that selection toward reduced BF at 100 kg live weight may have an unfavorable impact on WTS1.

Animals↗
PubMed2004

Genetic associations of prolificacy with performance, carcass, meat quality, and leg conformation traits in the Finnish Landrace and Large White pig populations.

The objective of this study was to estimate genetic associations of prolificacy traits with other traits under selection in the Finnish Landrace and Large White populations. The prolificacy traits evaluated were total number of piglets born, number of stillborn piglets, piglet mortality during suckling, age at first farrowing, and first farrowing interval. Genetic correlations were estimated with two performance traits (ADG and feed:gain ratio), with two carcass traits (lean percent and fat percent), with four meat quality traits (pH and L* values in longissimus dorsi and semimembranosus muscles), and with two leg conformation traits (overall leg action and buck-kneed forelegs). The data contained prolificacy information on 12,525 and 10,511 sows in the Finnish litter recording scheme and station testing records on 10,372 and 9,838 pigs in Landrace and Large White breeds, respectively. The genetic correlations were estimated by the restricted maximum likelihood method. The most substantial correlations were found between age at first farrowing and lean percent (0.19 in Landrace and 0.27 in Large White), and fat percent (-0.26 in Landrace and -0.18 in Large White), and between number of stillborn piglets and ADG (-0.38 in Landrace and -0.25 in Large White) and feed:gain (0.27 in Landrace and 0.12 in Large White). The correlations are indicative of the benefits of superior growth for piglets already at birth. Similarly, the correlations indicate that age at first farrowing is increasing owing to selection for carcass lean content. There was also clear favorable correlation between performance traits and piglet mortality from birth to weaning in Large White (r(g) was -0.43 between piglet mortality and ADG, and 0.42 between piglet mortality and feed:gain), but not in Landrace (corresponding correlations were 0.26 and -0.22). There was a general tendency that prolificacy traits were favorably correlated with performance traits, and unfavorably with carcass lean and fat percents, whereas there were no clear associations between prolificacy and meat quality or leg conformation. In conclusion, accuracy of estimated breeding values may be improved by accounting for genetic associations between prolificacy, carcass, and performance traits in a multitrait analysis.

Adipose Tissue↗
PubMed2001

Bayesian inference for categorical traits with an application to variance component estimation.

We implemented statistical models of Bayesian inference that included direct and maternal genetic effects for genetic parameter estimation of categorical traits by Gibbs sampling. The estimation errors and variances of estimates of animal versus sire and maternal grandsire models, of linear versus threshold models, of single-trait versus multiple-trait models, and of treating herd-year-season as fixed versus random effects in the model were compared. The results indicated that linear models yielded biased estimates of genetic parameters for categorical traits. The animal model was improper for analysis of categorical traits using a threshold model and the Gibbs sampler. Moreover, linear versus threshold models and animal versus sire-maternal grandsire models resulted in larger Monte Carlo errors and increased auto-correlations among posterior samples. Treating herd-year-seasons as random effects in the threshold models decreased the Monte Carlo error, auto-correlations, and the variances of estimates. Efficiency of the single-trait threshold sire model, as measured by the variance of the estimates, was lower than for a multiple-trait model that included a correlated continuous trait, but both estimates were unbiased. Therefore, the threshold single-trait sire and maternal grandsire model is a feasible alternative to the multiple-trait model for analysis of variance components of categorical traits affected by direct and maternal genetic factors.

Animals↗
PubMed2005

Genetic variance and covariance for physiological traits in Lobelia: are there constraints on adaptive evolution?

Physiological traits that control the uptake of carbon dioxide and loss of water are key determinants of plant growth and reproduction. Variation in these traits is often correlated with environmental gradients of water, light, and nutrients, suggesting that natural selection is the primary evolutionary mechanism responsible for physiological diversification. Responses to selection, however, can be constrained by the amount of standing genetic variation for physiological traits and genetic correlations between these traits. To examine the potential for constraint on adaptive evolution, we estimated the quantitative genetic basis of physiological trait variation in one population of each of two closely related species (Lobelia siphilitica and L. cardinalis). Restricted maximum likelihood analyses of greenhouse-grown half-sib families were used to estimate genetic variances and covariances for seven traits associated with carbon and water relations. We detected significant genetic variation for all traits in L. siphilitica, suggesting that carbon-gain and water-use traits could evolve in response to natural selection in this population. In particular, narrow-sense heritabilities for photosynthetic rate (A), stomatal conductance (gs), and water-use efficiency (WUE) in our L. siphilitica population were high relative to previous studies in other species. Although there was significant narrow-sense heritability for A in L. cardinalis, we detected little genetic variation for traits associated with water use (gs and WUE), suggesting that our population of this species may be unable to adapt to drier environments. Despite being tightly linked functionally, the genetic correlation between A and gs was not strong and significant in either population. Therefore, our L. siphilitica population would not be genetically constrained from evolving high A (and thus fixing more carbon for growth and reproduction) while also decreasing gs to limit water loss. However, a significant negative genetic correlation existed between WUE and plant size in L. siphilitica, suggesting that high WUE may be negatively associated with high fecundity. In contrast, our results suggest that any constraints on the evolution of photosynthetic and stomatal traits of L. cardinalis are caused primarily by a lack of genetic variation, rather than by genetic correlations between these functionally related traits.

Adaptation, Physiological↗
PubMed1991

[Hematological data analysis in children with thalassemia trait or hemoglobin H disease in Taiwan].

In the past several years, we have collected 91 cases diagnosed as beta-thalassemia trait, 94 cases as alpha-thalassemia trait and 43 cases as hemoglobin H disease. The ages ranged from 6 months to 15 years. The hematological data were analyzed. We calculated the mean +/- SD for each item of the erythrocyte indices (RBC, Hgb, Hct, MCV, MCH, MCHC, +/- RDW) and the Hb electrophoretic results (Hb A, Hb A2, Hb F, Hb H & Bart's) in each group, and tabulated them. Then, comparisons were made between beta and alpha-thalassemia traits or between the thalassemia trait and hemoglobin H disease. We found that each of the mean values for Hgb, Hct, MCV and MCH for children with the beta-thalassemia trait was significantly lower than that for children with the alpha-thalassemia trait. The mean MCV value of the beta-thalassemia trait group was 60.7 +/- 3.4 fl, and 87% of the MCV values in this group ranged from 55 to 65 fl. The mean MCV value for the alpha-thalassemia trait group was 63.3 +/- 3.3 fl, and 56% of the MCV values in this group ranged from 60-65 fl. The MCV values for all of the 185 children studied with either the beta- or alpha-thalassemia trait ranged from 54 to 71 fl, and were far below the normal ranges for MCV values for each age-specific group. The mean percentage of deviation of MCV from normal was greater than that of Hgb in both the beta- and alpha-thalassemia trait groups. A comparison of those with beta-thalassemia trait 6 years old and under and those over 6 years showed that both the mean values of RBC and Hgb were higher in the older subgroup, while the mean MCV values did not show any significant differences between these 2 subgroups.(ABSTRACT TRUNCATED AT 250 WORDS)

Adolescent↗
PubMed2006

Protected polymorphism and evolutionary stability in pleiotropic models with trait-specific dominance.

When alleles have pleiotropic effects on a number of quantitative traits, the degree of dominance between a pair of alleles can be different for each trait. Such trait-specific dominance has been studied previously in models for the maintenance of genetic variation by antagonistic effects of an allele on two fitness components. By generalizing these models to an arbitrary number of fitness components or other phenotypic traits with different degrees of dominance, I show that genetic polymorphism is generally impossible without antagonistic fitness effects of different traits and without trait-specific dominance. I also investigate dominance and pleiotropy from a more long-term evolutionary perspective, allowing for the study of general ecological scenarios, and I discuss the effects of trait-specific dominance on evolutionary stability criteria. When selection is mainly directional and only trait-specific dominance and antagonism cause the emergence of polymorphism, then these polymorphisms can be overtaken by single mutants again, such that they are probably short-lived on an evolutionary time scale. Near evolutionarily singular points where directional selection is absent, trait-specific dominance and overdominance facilitate the emergence of polymorphism and cause evolutionary divergence in some cases. An important outcome of these models is that trait-specific dominance allows for the emergence of genetic polymorphisms without a selective disadvantage for heterozygotes. This removes the scope for the evolution of assortative mate choice and affects dominance modification. Sympatric speciation by disruptive ecological selection requires this heterozygote disadvantage in order to evolve, and therefore it becomes less plausible if the emergence of genetic polymorphism usually occurs via trait-specific dominance and antagonistic effects.

Biological Evolution↗
PubMed2005

Integrative genetic analysis of transcription modules: towards filling the gap between genetic loci and inherited traits.

Genetic loci that regulate inherited traits are routinely identified using quantitative trait locus (QTL) mapping methods. However, the genotype-phenotype associations do not provide information on the gene expression program through which the genetic loci regulate the traits. Transcription modules are 'self-consistent regulatory units' and are closely related to the modular components of gene regulatory network [Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Revealing modular organization in the yeast transcriptional network. Nat. Genet., 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet., 34, 166-176]. We used genome-wide genotype and gene expression data of a genetic reference population that consists of mice of 32 recombinant inbred strains to identify the transcription modules and the genetic loci regulating them. Twenty-nine transcription modules defined by genetic variations were identified. Statistically significant associations between the transcription modules and 18 classical physiological and behavioral traits were found. Genome-wide interval mapping showed that major QTLs regulating the transcription modules are often co-localized with the QTLs regulating the associated classical traits. The association and the possible co-regulation of the classical trait and transcription module indicate that the transcription module may be involved in the gene pathways connecting the QTL and the classical trait. Our results show that a transcription module may associate with multiple seemingly unrelated classical traits and a classical trait may associate with different modules. Literature mining results provided strong independent evidences for the relations among genes of the transcription modules, genes in the regions of the QTLs regulating the transcription modules and the keywords representing the classical traits.

Animals↗
PubMed2003

A QTL genome scan of the metabolic syndrome and its component traits.

BACKGROUND: Because high blood pressure, altered lipid levels, obesity, and diabetes so frequently occur together, they are sometimes collectively referred to as the metabolic syndrome. While there have been many studies of each metabolic syndrome trait separately, few studies have attempted to analyze them combined, i.e., as one composite variable, in quantitative trait linkage or association analysis. We used genotype and phenotype data from the Framingham Heart Study to perform a full-genome scan for quantitative trait loci underlying the metabolic syndrome. RESULTS: Heritability estimates for all of the covariate-adjusted and age- and gender-standardized individual traits, and the composite metabolic syndrome trait, were all fairly high (0.39-0.62), and the composite trait was among the highest at 0.61. The composite trait yielded no regions with suggestive linkage by Lander and Kruglyak's criteria, although there were several noteworthy regions for individual traits, some of which were also observed for the composite variable. CONCLUSION: Despite its high heritability, the composite metabolic syndrome trait variable did not increase the power to detect or localize linkage peaks in this sample. However, this strategy and related methods of combining correlated individual traits deserve further investigation, particularly in settings with complex causal pathways.

Adult↗
PubMed2005

Detection of genes for ordinal traits in nuclear families and a unified approach for association studies.

There is growing interest in genomewide association analysis using single-nucleotide polymorphisms (SNPs), because traditional linkage studies are not as powerful in identifying genes for common, complex diseases. Tests for linkage disequilibrium have been developed for binary and quantitative traits. However, since many human conditions and diseases are measured in an ordinal scale, methods need to be developed to investigate the association of genes and ordinal traits. Thus, in the current report we propose and derive a score test statistic that identifies genes that are associated with ordinal traits when gametic disequilibrium between a marker and trait loci exists. Through simulation, the performance of this new test is examined for both ordinal traits and quantitative traits. The proposed statistic not only accommodates and is more powerful for ordinal traits, but also has similar power to that of existing tests when the trait is quantitative. Therefore, our proposed statistic has the potential to serve as a unified approach to identifying genes that are associated with any trait, regardless of how the trait is measured. We further demonstrated the advantage of our test by revealing a significant association (P = 0.00067) between alcohol dependence and a SNP in the growth-associated protein 43.

Alcoholism↗
PubMed2003

Accuracy of marker-assisted selection with auxiliary traits.

Genetic information on molecular markers is increasingly being used in plant and animal improvement programmes particularly as indirect means to improve a metric trait by selection either on an individual basis or on the basis of an index incorporating such information. This paper examines the utility of an index of selection that not only combines phenotypic and molecular information on the trait under improvement but also combines similar information on one or more auxiliary traits. The accuracy of such a selection procedure has been theoretically studied for sufficiently large populations so that the effects of detected quantitative trait loci can be perfectly estimated. The theory is illustrated numerically by considering one auxiliary trait. It is shown that the use of an auxiliary trait improves the selection accuracy; and, hence, the relative efficiency of index selection compared to individual selection which is based on the same intensity of selection. This is particularly so for higher magnitudes of residual genetic correlation and environmental correlation having opposite signs, lower values of the proportion of genetic variation in the main trait associated with the markers, negligible proportion of genetic variation in the auxiliary trait associated with the markers, and lower values of the heritability of the main trait but higher values of the heritability of the auxiliary trait.

Animals↗
PubMed2002

Molecular dissection of the genetic relationships of source, sink and transport tissue with yield traits in rice.

Source, sink, and translocation capacity of assimilates play important roles during the formation of grain yield. The present study was conducted to characterize the genetic bases of traits representing source, sink and transport tissue, and their relationships with yield traits in rice, by analyzing QTLs for these traits and various ratios among them. The genetic materials were a recombinant inbred population derived from a cross between two indica cultivars Zhenshan 97 and Minghui 63, the parents of the most-widely grown hybrid rice in China. Using a linkage map that covers a total of 1,796 cM based on 221 molecular marker loci, a total of 81 QTLs were identified for the 15 traits studied (three leaf areas as the source, total spikelets per panicle as the sink, the number of large vascular bundles in the stem as transport tissue, three source to sink ratios, three transport tissue to source ratios, one transport tissue to sink ratio and three yield traits). The amount of variation explained by individual QTLs ranged from 1.12% to 24.14%. Five QTLs were identified to show interaction effects with the environment, which explained from 3.19% to 9.15% of the variation. The results showed that close linkage or pleiotropy is the genetic basis for the correlations of grain yield traits with source, sink, transport tissue and the various ratios among them. Of the 25 QTLs identified for source-sink-transport tissue trait, and 43 for various ratios, 8 and 22 QTLs, respectively, were mapped to the similar genomic blocks harboring QTLs for yield traits, especially for grain weight. Co-location of QTLs for yield traits with those for ratios among source, sink and transport tissue may provide a genetic explanation for the physiological expression of yield traits, and also suggest that improvement in ratios among source, sink and transport tissue may result in improvement in yield potential.

Chimera↗
PubMed2026

Multidimensional GWAS analyses on longitudinal phenotypes reveal candidate genes regulating multi-stage egg production traits in Wannan yellow chicken.

Egg production performance directly determines the economic viability of indigenous chicken breeding. However, the genetic regulation of multi-stage egg production traits remains difficult to characterize due to their complex and dynamic nature. Here, we integrated a multidimensional GWAS framework, including single-trait GWAS, multi-trait GWAS (MTAG), and longitudinal trajectory-based GWAS (TrajGWAS), to identify stage-specific and shared genetic effects underlying egg production traits in Wannan yellow chickens (WNY). Whole-genome sequencing of 354 WNY hens (10× depth) and quality control yielded 14,253,816 SNPs for analysis. Selective sweep analyses comparing red jungle fowl, commercial layers, and WNY identified a genomic region containing IGF1 under significant selection pressure. Single-trait GWAS identified SNPs 4_57990480 (BMPR1B) and 17_370912 (LOC112531479) associated with egg production across three laying stages (21-30, 31-40, and 21-40 weeks). MTAG further identified loci 8_4336468 (FASLG) and 21_654726 (CHD5) with shared effects across the laying period, whereas TrajGWAS revealed longitudinal associations involving PRKG1 and identified dynamic loci associated with clutch traits, including GRID1. For clutch traits, stage-specific loci were detected for average clutch size (ACS) and maximum clutch size (MCS), including SNP 8_8542036 at 21-30 weeks, PROK1 at 31-40 weeks, and CUL5, ALKBH8 across the entire laying period. These results demonstrate that integrating complementary GWAS strategies improves the resolution of genetic architecture underlying egg production traits by capturing trait-specific, shared, and stage-dependent genetic effects. The identified GWAS loci and selective-sweep candidate regions provide insights into the genetic architecture of egg production traits and breed differentiation.

Egg production↗
PubMed2004

Major growth QTLs in fowl are related to fearful behavior: possible genetic links between fear responses and production traits in a red junglefowl x white leghorn intercross.

The aim of this work was to study fear responses and their relation to production traits in red junglefowl ( Gallus gallus spp.), White Leghorn ( Gallus domesticus ), and their F2-progeny. Quantitative trait locus (QTL) analyses were performed for behavioral traits to gain information about possible genetic links between fear-related behaviors and production. Four behavioral tests were performed that induce different levels of acute fear (open field [OF], exposure to a novel object, tonic immobility, and restraint). Production traits, that is, egg production, sexual maturity (in females), food intake, and growth, were measured individually. A genome scan using 105 microsatellite markers was carried out to identify QTLs controlling the traits studied. In the OF and novel object tests (NO), Leghorns showed less fear behavior than junglefowl, whereas junglefowl behaved less fearfully in the tonic immobility test (TI) and were more active in the restraint test. In the F2 progeny, only weak phenotypic associations were found between production traits and fear behavior. A significant QTL for TI duration was found on chromosome 1 that coincided with a QTL for egg weight and growth in the same animals. Another QTL for NO in males coincided with another major growth QTL. These two known growth QTLs affected a wide range of reactions in different tests. Several other significant and suggestive QTLs for behavioral traits related to fear were found. These QTLs did not coincide with QTLs for production traits, indicating that these fear variables may not be genetically linked to the production traits we measured here. The results show that loci affecting important production traits are located in the same chromosomal region as loci affecting different fear-related behaviors.

Animals↗
PubMed1983

Falciparum malaria and beta-thalassaemia trait in northern Liberia.

In a study in northern Liberia of the malaria and beta-thalassaemia hypothesis, the frequencies of beta-thalassaemia and HbS traits were 9.1 and 3.4% in the Mano and 9.5 and 1.7% in the Gio tribal samples. HbC and HbN were present at low frequency. G6PD deficiency was found in 16% of males. An observed increase with age of beta-thalassaemia trait frequencies was consistent with the selection hypothesis. However, we could not entirely exclude that associated iron deficiency influenced the results in the six to 11 month age group. Malaria was holoendemic; Plasmodium falciparum predominated, P. malariae and P. ovale were also identified. Plasmodium falciparum prevalence rates were similar in normal and beta-thalassaemia trait children but parasite densities were consistently lower in the latter. Using the criterion of a falciparum parasite density of 1 x 10(9) 1(-1) or greater to indicate a potentially important infection, the relative risk in beta-thalassaemia traits one to four years old from the cross-sectional study was 0.45 (upper 95% confidence interval 0.79) and 0.41 (0.61) in two to nine year trait carriers from a longitudinal study. Plasmodium falciparum gametocyte rates were lower in beta-thalassaemia trait children (P less than 0.005). The geometric mean titre of P. falciparum antibodies was lower in beta-thalassaemia trait children from the one to four year group (P less than 0.05). Otherwise immunological studies showed little difference between the different Hb types. Parasitological findings were consistent with relative resistance of HbS trait carriers towards P. falciparum infection. We found no evidence for relative resistance of beta-thalassaemia traits towards P. malariae infection nor that G6PD deficient males were more resistant to P. falciparum than those with normal activity. We conclude that the results are consistent with relative resistance of beta-thalassaemia trait carriers to P. falciparum malaria.

Adolescent↗