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Trait Analysis (trait + analysis)
Kinds of Trait Analysis Selected AbstractsStudies of associations between the Arg389Gly polymorphism of the ,1 -adrenergic receptor gene (ADRB1) and hypertension and obesity in 7677 Danish white subjectsDIABETIC MEDICINE, Issue 4 2007A. P. Gjesing Abstract Aims, Activation of the ,1 -adrenergic receptor (ADRB1) causes increased lipolysis in adipose tissue and enhances cardiac output. Analysis of the association of the functional ADRB1 Arg389Gly variant with obesity and hypertension has given ambiguous results. To clarify the potential impact of this variant on obesity and hypertension in the general population, we examined the Arg389Gly variant in a relatively large-scale population-based study. Methods, Case-control studies and quantitative trait analyses were carried out in 7677 Danish Caucasians who were genotyped for the Arg389Gly variant (dbSNP rs1801253) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Results, A weak association between the Gly allele of the Arg389Gly variant and obesity was observed when comparing cases (n = 1540) defined as body mass index (BMI) > 30 kg/m2 with control subjects (n = 6108) defined as BMI , 30 kg/m2 for both allele frequencies (P = 0.05) and genotype distribution (P = 0.05). Case-control studies (cases n = 2518; control n = 3981) examining the effect on hypertension showed no association with allele frequencies (P = 0.3) or genotype distribution (P = 0.5); however, in the quantitative trait analyses, individuals carrying the Gly allele had slightly but significantly lower diastolic (Arg/Arg = 81.9 mmHg vs. Gly-allele carriers = 81.5 mmHg) and systolic (Arg/Arg = 129.4 mmHg vs. Gly-allele carriers = 128.8 mmHg) blood pressure as well as a lower mean arterial blood pressure. Conclusion, Our results suggest that the Arg389Gly polymorphism does not have any clinically important impact on the pathogenesis of obesity in Danish white subjects. Furthermore, despite the observed minor influence on blood pressure, this variant is most likely not to be a major contributor to the development of hypertension. [source] Cattle MHC genes DOA and DOB: sequence polymorphisms and assignments to the class IIb regionINTERNATIONAL JOURNAL OF IMMUNOGENETICS, Issue 3 2001A. Gelhaus Summary In a study of the genetic polymorphism of the second exons of the cattle DOA and DOB genes, two and four allelic variants were detected, respectively. In the predicted amino acid sequence, the DOA polymorphism corresponded to variation at the respective residue position, whereas the nucleotide substitutions in the DOB gene were non-informative. PCR-RFLP assays were developed for DOA and DOB typing, and both loci were genetically mapped to the BoLA class IIb region by linkage analysis in the International Bovine Reference Panel. The single nucleotide polymorphisms detected in the BoLA-DOA and - DOB genes enable these loci to be used as markers in genetic trait analyses. [source] Genetic correlations among and between wool, growth and reproduction traits in Merino sheepJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 2 2007E. Safari Summary Data from seven research resource flocks across Australia were combined to provide accurate estimates of genetic correlations among production traits in Merino sheep. The flocks represented contemporary Australian Merino fine, medium and broad wool strains over the past 30 years. Over 110 000 records were available for analysis for each of the major wool traits, and 50 000 records for reproduction and growth traits with over 2700 sires and 25 000 dams. Individual models developed from the single trait analyses were extended to the various combinations of two-trait models to obtain genetic correlations among six wool traits [clean fleece weight (CFW), greasy fleece weight, fibre diameter (FD), yield, coefficient of variation of fibre diameter and standard deviation of fibre diameter], four growth traits [birth weight, weaning weight, yearling weight (YWT), and hogget weight] and four reproduction traits [fertility, litter size, lambs born per ewe joined, lambs weaned per ewe joined (LW/EJ)]. This study has provided for the first time a comprehensive matrix of genetic correlations among these 14 wool, growth and reproduction traits. The large size of the data set has also provided estimates with very low standard errors. A moderate positive genetic correlation was observed between CFW and FD (0.29 ± 0.02). YWT was positively correlated with CFW (0.23 ± 0.04), FD (0.17 ± 0.04) and LWEJ (0.58 ± 0.06), while LW/EJ was negatively correlated with CFW (,0.26 ± 0.05) and positively correlated with FD (0.06 ± 0.04) and LS (0.68 ± 0.04). These genetic correlations, together with the estimates of heritability and other parameters provide the basis for more accurate prediction of outcomes in complex sheep-breeding programmes designed to improve several traits. [source] Variable selection method for quantitative trait analysis based on parallel genetic algorithmANNALS OF HUMAN GENETICS, Issue 1 2010Siuli Mukhopadhyay Summary Selection of important genetic and environmental factors is of strong interest in quantitative trait analyses. In this study, we use parallel genetic algorithm (PGA) to identify genetic and environmental factors in genetic association studies of complex human diseases. Our method can take account of both multiple markers across the genome and environmental factors, and also can be used to do fine mapping based on the results of haplotype analysis to select the markers that are associated with the quantitative traits. Using both simulated and real examples, we show that PGA is able to choose the variables correctly and is also an easy-to-use variable selection tool. [source] Using evidence for population stratification bias in combined individual- and family-level genetic association analyses of quantitative traitsGENETIC EPIDEMIOLOGY, Issue 5 2010Lucia Mirea Abstract Genetic association studies are generally performed either by examining differences in the genotype distribution between individuals or by testing for preferential allele transmission within families. In the absence of population stratification bias (PSB), integrated analyses of individual and family data can increase power to identify susceptibility loci [Abecasis et al., 2000. Am. J. Hum. Genet. 66:279,292; Chen and Lin, 2008. Genet. Epidemiol. 32:520,527; Epstein et al., 2005. Am. J. Hum. Genet. 76:592,608]. In existing methods, the presence of PSB is initially assessed by comparing results from between-individual and within-family analyses, and then combined analyses are performed only if no significant PSB is detected. However, this strategy requires specification of an arbitrary testing level ,PSB, typically 5%, to declare PSB significance. As a novel alternative, we propose to directly use the PSB evidence in weights that combine results from between-individual and within-family analyses. The weighted approach generalizes previous methods by using a continuous weighting function that depends only on the observed P -value instead of a binary weight that depends on ,PSB. Using simulations, we demonstrate that for quantitative trait analysis, the weighted approach provides a good compromise between type I error control and power to detect association in studies with few genotyped markers and limited information regarding population structure. Genet. Epidemiol. 34: 502,511, 2010. © 2010 Wiley-Liss, Inc. [source] Combining spatial and phylogenetic eigenvector filtering in trait analysisGLOBAL ECOLOGY, Issue 6 2009Ingolf Kühn ABSTRACT Aim, To analyse the effects of simultaneously using spatial and phylogenetic information in removing spatial autocorrelation of residuals within a multiple regression framework of trait analysis. Location, Switzerland, Europe. Methods, We used an eigenvector filtering approach to analyse the relationship between spatial distribution of a trait (flowering phenology) and environmental covariates in a multiple regression framework. Eigenvector filters were calculated from ordinations of distance matrices. Distance matrices were either based on pure spatial information, pure phylogenetic information or spatially structured phylogenetic information. In the multiple regression, those filters were selected which best reduced Moran's I coefficient of residual autocorrelation. These were added as covariates to a regression model of environmental variables explaining trait distribution. Results, The simultaneous provision of spatial and phylogenetic information was effectively able to remove residual autocorrelation in the analysis. Adding phylogenetic information was superior to adding purely spatial information. Applying filters showed altered results, i.e. different environmental predictors were seen to be significant. Nevertheless, mean annual temperature and calcareous substrate remained the most important predictors to explain the onset of flowering in Switzerland; namely, the warmer the temperature and the more calcareous the substrate, the earlier the onset of flowering. A sequential approach, i.e. first removing the phylogenetic signal from traits and then applying a spatial analysis, did not provide more information or yield less autocorrelation than simple or purely spatial models. Main conclusions, The combination of spatial and spatio-phylogenetic information is recommended in the analysis of trait distribution data in a multiple regression framework. This approach is an efficient means for reducing residual autocorrelation and for testing the robustness of results, including the indication of incomplete parameterizations, and can facilitate ecological interpretation. [source] Ecometrics: The traits that bind the past and present togetherINTEGRATIVE ZOOLOGY (ELECTRONIC), Issue 2 2010Jussi T. ERONEN Abstract We outline here an approach for understanding the biology of climate change, one that integrates data at multiple spatial and temporal scales. Taxon-free trait analysis, or "ecometrics," is based on the idea that the distribution in a community of ecomorphological traits such as tooth structure, limb proportions, body mass, leaf shape, incubation temperature, claw shape, any aspect of anatomy or physiology can be measured across some subset of the organisms in a community. Regardless of temporal or spatial scale, traits are the means by which organisms interact with their environment, biotic and abiotic. Ecometrics measures these interactions by focusing on traits which are easily measurable, whose structure is closely related to their function, and whose function interacts directly with local environment. Ecometric trait distributions are thus a comparatively universal metric for exploring systems dynamics at all scales. The main challenge now is to move beyond investigating how future climate change will affect the distribution of organisms and how it will impact ecosystem services and to shift the perspective to ask how biotic systems interact with changing climate in general, and how climate change affects the interactions within and between the components of the whole biotic-physical system. We believe that it is possible to provide believable, quantitative answers to these questions. Because of this we have initiated an IUBS program iCCB (integrative Climate Change Biology). [source] The evolving typology of neuropsychiatric complications of Alzheimer's disease: the use of latent trait analysisINTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY, Issue 11 2001Barnett S. Meyers No abstract is available for this article. [source] Estimates of genetic parameters for Boran, Friesian, and crosses of Friesian and Jersey with the Boran cattle in the tropical highlands of Ethiopia: milk production traits and cow weightJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 3 2004S. Demeke Summary Breed additive and non-additive effects plus heritabilities and repeatabilities for milk yield per lactation (LMY), milk yield per day (DMY), lactation length (LL), annual milk yield (AMY), annual milk yield per metabolic body weight (AMYBW) and cow weight at calving (BW) were estimated for 5464 lactation records collected from purebred Boran (B), Friesian (F), and crosses of Friesian and Jersey (J) breeds with the Boran breed raised in the tropical highlands of Ethiopia. Single trait analysis was carried out by using two equivalent repeatability animal models. In the first model the genotype was fitted as a fixed group effect, while in the second model the genotype was substituted by breed additive, heterotic and recombination effects fitted as fixed covariates. Both the F and J breed additive effects, measured as a deviation from the B breed were significant (p < 0.01) for all traits, except for BW of the J. The F and J additive contributions were 2774 ± 81 and 1473 ± 362 kg for LMY, 7.1 ± 0.2 and 4.8 ± 0.8 kg for DMY, 152 ± 7 and 146 ± 31 days for LL, 2345 ± 71 and 1238 ± 319 kg for AMY, 20.6 ± 0.9 and 18.9 ± 4.3 kg for AMYBW, and 140 ± 4 and ,21 ± 22 kg (p > 0.05) for BW. The heterotic contributions to the crossbred performance were also positive and significant (p < 0.01) for all traits. The F1 heterosis expressed as a deviation from the mid-parent values were 22 and 66% for LMY, 11 and 20% for DMY, 29 and 29% for LL, 21 and 64% for AMY, 42 and 42% for AMYBW, and 2% (p < 0.05) and 11% for BW for the F × B and J × B crosses, respectively. The recombination effect estimated for the F × B crosses was negative and significant for LMY (,526 ± 192 kg, p < 0.01), DMY (,3.0 ± 0.4 kg, p < 0.001), AMY (,349 ± 174 kg, p < 0.05) and BW (,68 ± 11 kg, p < 0.001). For the J × B crosses the recombination loss was significant and negative only for DMY (,2.2 ± 0.7 kg, p < 0.05) and BW (,33 ± 17 kg, p < 0.05). The direct heritabilities (h2) estimated for LMY, DMY, LL, AMY and AMYBW were 0.24 ± 0.04, 0.19 ± 0.03, 0.13 ± 0.03, 0.23 ± 0.04 and 0.17 ± 0.05, respectively. Based on the genetic parameters estimated, the best breeding strategy to increased milk production under highland Ethiopian conditions is to apply selection on purebred base populations (Boran and Friesian) and then crossing them to produce F1 dairy cows. However, for breeding decision based on total dairy merit, further investigations are needed for traits such as milk quality, reproduction, longevity and survival. Zusammenfassung Additive Rasseneffekte, nicht additive Effekte, Heritabilitäten und Wiederholbarkeiten für Milchmenge pro Laktation (LMY), Milchmenge pro Tag (DMY), Laktationsdauer (LL), jährliche Milchmenge (AMY), jährliche Milchmenge pro metabolischem Körpergewicht (AMYBW) und Kuhgewichte zur Kalbung (BW) wurden anhand von 5464 Laktationsdatensätzen von reinrassigen Boran (B), Friesian (F) und Kreuzungen der Rassen Friesian und Jersey (J) mit der Rasse Boran, die im tropischen Hochland von Äthiopien groß gezogen wurden, geschätzt. Einmerkmalsmodelle wurden mit zwei äquivalenten Wiederholbarkeits-Tiermodellen durchgeführt. Im ersten Modell wurde der Genotyp als fixer Gruppeneffekt berücksichtigt, während im zweiten Modell der Genotyp durch additive Rasseneffekte, Heterosis und Rekombinationseffekte als Kovariable ersetzt wurde. Die additiven Rasseneffekte von F und J, gemessen als Abweichung von der Rasse B, waren für alle Merkmale signifikant (p < 0,01), ausgenommen BW für die Rasse J. Die additiven Rasseneffekte von F und J betrugen 2774 ± 81 und 1473 ± 362 kg für LMY, 7,1 ± 0,2 und 4,8 ± 0,8 kg für DMY, 152 ± 7 und 146 ± 31 Tage für LL, 2345 ± 71 und 1238 ± 319 kg für AMY, 20,6 ± 0,9 und 18,9 ± 4,3 kg für AMYBW und 140 ± 4 und ,21 ± 22 kg (p > 0,05) für BW. Die Heterosis bei den Kreuzungstieren war positiv und signifikant für alle Merkmale (p < 0,01). Die Heterosis der F1 -Tiere, ausgedrückt als Abweichung vom Mittel der beiden Eltern, betrug 22 und 66% für LMY, 11 und 20% für DMY, 29 und 29% für LL, 21 und 64% für AMY, 42% und 42% für AMYBW und 2% (p < 0,05) und 11% für BW für die F × B und J × B Kreuzungen. Der geschätzte Rekombinationseffekt für die F × B Kreuzungen war negativ und signifikant für LMY (,526 ± 192 kg, p < 0,01), DMY (,3,0 ± 0,4 kg, p < 0,001), AMY (,349 ± 174, p < 0,05) und BW (,68 ± 11 kg, p < 0,001). Für die J × B Kreuzungen war der Rekombinationsverlust signifikant und negativ nur für DMY (,2,2 ± 0,7 kg, p < 0,05) und BW (,33 ± 17, p < 0,05). Die geschätzten Heritabilitäten (h2) betrugen für LMY, DMY, LL, AMY und AMYBW 0,24 ± 0,04, 0,19 ± 0,03, 0,13 ± 0,03, 0,23 ± 0,04 und 0,17 ± 0,05. Basierend auf den geschätzten genetischen Parametern erscheint Selektion in den Reinzuchtpopulationen B und F und anschließ end Kreuzung dieser Tiere zur Erstellung von F1 -Milchkühen als günstigste Zuchtstrategie, um die Milchproduktion unter äthiopischen Hochlandbedingungen zu steigern. Für Zuchtentscheidungen, die die gesamte Milchproduktion berücksichtigen, sind weitere Untersuchungen notwendig für Merkmale wie Milchqualität, Reproduktion, Persistenz und Langlebigkeit. [source] Mapping Quantitative Trait Loci for Vertebral Trabecular Bone Volume Fraction and Microarchitecture in Mice,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 4 2004Mary L Bouxsein Abstract BMD, which reflects both cortical and cancellous bone, has been shown to be highly heritable; however, little is known about the specific genetic factors regulating trabecular bone. Genome-wide linkage analysis of vertebral trabecular bone traits in 914 adult female mice from the F2 intercross of C57BL/6J and C3H/HeJ inbred strains revealed a pattern of genetic regulation derived from 13 autosomes, with 5,13 QTLs associated with each of the traits. Ultimately, identification of genes that regulate trabecular bone traits may yield important information regarding mechanisms that regulate mechanical integrity of the skeleton. Introduction: Both cortical and cancellous bone influence the mechanical integrity of the skeleton, with the relative contribution of each varying with skeletal site. Whereas areal BMD, which reflects both cortical and cancellous bone, has been shown to be highly heritable, little is known about the genetic determinants of trabecular bone density and architecture. Materials and Methods: To identify heritable determinants of vertebral trabecular bone traits, we evaluated the fifth lumbar vertebra from 914 adult female mice from the F2 intercross of C57BL/6J (B6) and C3H/HeJ (C3H) progenitor strains. High-resolution ,CT was used to assess total volume (TV), bone volume (BV), bone volume fraction (BV/TV), trabecular thickness (Tb.Th), separation (Tb.Sp), and number (Tb.N) of the trabecular bone in the vertebral body in the progenitors (n = 8/strain) and female B6C3H-F2 progeny (n = 914). Genomic DNA from F2 progeny was screened for 118 PCR-based markers discriminating B6 and C3H alleles on all 19 autosomes. Results and Conclusions: Despite having a slightly larger trabecular bone compartment, C3H progenitors had dramatically lower vertebral trabecular BV/TV (,53%) and Tb.N (,40%) and higher Tb.Sp (71%) compared with B6 progenitors (p < 0.001 for all). Genome-wide quantitative trait analysis revealed a pattern of genetic regulation derived from 13 autosomes, with 5,13 quantitative trait loci (QTLs) associated with each of the vertebral trabecular bone traits, exhibiting adjusted LOD scores ranging from 3.1 to 14.4. The variance explained in the F2 population by each of the individual QTL after adjusting for contributions from other QTLs ranged from 0.8% to 5.9%. Taken together, the QTLs explained 22,33% of the variance of the vertebral traits in the F2 population. In conclusion, we observed a complex pattern of genetic regulation for vertebral trabecular bone volume fraction and microarchitecture using the F2 intercross of the C57BL/6J and C3H/HeJ inbred mouse strains and identified a number of QTLs, some of which are distinct from those that were previously identified for total femoral and vertebral BMD. Identification of genes that regulate trabecular bone traits may ultimately yield important information regarding the mechanisms that regulate the acquisition and maintenance of mechanical integrity of the skeleton. [source] Genetic Diversity and Association Analysis for Salinity Tolerance, Heading Date and Plant Height of Barley Germplasm Using Simple Sequence Repeat MarkersJOURNAL OF INTEGRATIVE PLANT BIOLOGY, Issue 8 2008Lilia Eleuch Abstract The objective of this study was to investigate the genetic diversity of barley accessions. Additionally, association trait analysis was conducted for grain yield under salinity, heading date and plant height. For this purpose, 48 barley genotypes were analyzed with 22 microsatellite simple sequence repeat (SSR) markers. Four of the 22 markers (Bmac316, scssr03907, HVM67 and Bmag770) were able to differentiate all barley genotypes. Cluster and principal coordinate analysis allowed a clear grouping between countries from the same region. The genotypes used in this study have been evaluated for agronomic performance in different environments. Conducting association analysis for grain yield under salinity conditions using TASSEL software revealed a close association of the marker Bmag749 (2H, bin 13) in two different environments with common significant alleles (175, 177), whereas the HVHOTR1 marker (2H, bin 3) was only significant in Sakhar_Egypt with alleles size being 158 and 161. Heading date also showed an association with scssr03907 through the common significant specific allele 111 and EBmac0415 markers in three different agro climatic locations, whereas HVCMA, scssr00103 and HVM67 were linked to heading date in the Egyptian environment only. The plant height association analysis revealed significant markers Bmag770 via the significant allele 152 and scssr09398. [source] Variable selection method for quantitative trait analysis based on parallel genetic algorithmANNALS OF HUMAN GENETICS, Issue 1 2010Siuli Mukhopadhyay Summary Selection of important genetic and environmental factors is of strong interest in quantitative trait analyses. In this study, we use parallel genetic algorithm (PGA) to identify genetic and environmental factors in genetic association studies of complex human diseases. Our method can take account of both multiple markers across the genome and environmental factors, and also can be used to do fine mapping based on the results of haplotype analysis to select the markers that are associated with the quantitative traits. Using both simulated and real examples, we show that PGA is able to choose the variables correctly and is also an easy-to-use variable selection tool. [source] Robust Quantitative Trait Association Tests in the Parent-Offspring Triad Design: Conditional Likelihood-Based ApproachesANNALS OF HUMAN GENETICS, Issue 2 2009J.-Y. Wang Summary Association studies, based on either population data or familial data, have been widely applied to mapping of genes underlying complex diseases. In family-based association studies, using case-parent triad families, the popularly used transmission/disequilibrium test (TDT) was proposed for avoidance of spurious association results caused by other confounders such as population stratification. Originally, the TDT was developed for analysis of binary disease data. Extending it to allow for quantitative trait analysis of complex diseases and for robust analysis of binary diseases against the uncertainty of mode of inheritance has been thoroughly discussed. Nevertheless, studies on robust analysis of quantitative traits for complex diseases received relatively less attention. In this paper, we use parent-offspring triad families to demonstrate the feasibility of establishment of the robust candidate-gene association tests for quantitative traits. We first introduce the score statistics from the conditional likelihoods based on parent-offspring triad data under various genetic models. By applying two existing robust procedures we then construct the robust association tests for analysis of quantitative traits. Simulations are conducted to evaluate empirical type I error rates and powers of the proposed robust tests. The results show that these robust association tests do exhibit robustness against the effect of misspecification of the underlying genetic model on testing powers. [source] | |||||||||||||