7673591
Deciphering the genetic architecture of a multivariate phenotype.
A heritable multivariate quantitative phenotype comprises several correlated component phenotypes that are usually pleiotropically controlled by a set of major loci and environmental factors. One approach to decipher the genetic architecture of a multivariate phenotype, in particular to map the underlying loci, is to reduce the dimensionality of the data by means of a data reduction technique, such as principal component analysis. The extracted principal components are then analyzed in conjunction with marker data to map the underlying loci. We have examined the efficiency of this approach with and without taking into account the correlation structure of the multivariate phenotype when extracting principal components. We have assumed that genome-wide scan data on sibpairs are available for low-density (widely spaced) and high-density markers. Using extensive simulations, based on three models of the multivariate phenotype, we have shown that although ignoring the correlation structure of the multivariate phenotype does not have any serious impact on the efficiency of mapping the underlying trait loci in wide marker intervals, there is a significant adverse effect of this practice for fine-mapping. We, therefore, recommend that the correlation structure of the multivariate phenotype be carefully examined to decide on the strategy of extracting principal components for deciphering the genetic architecture of the multivariate phenotype.
29577210
Integrating sibship data for mapping quantitative trait loci.
Sibship methods have been shown to be more powerful than traditional sib-pair methods in mapping quantative trait loci. We propose a statistical procedure which integrates data on sibships into a so-called 'contrast function', a natural extension of the classical squared sib-pair trait difference proposed by Haseman & Elston (1972). We also develop a combined mean and contrast function which provides more information on linkage compared to the contrast function. Our method is extended to multiple, epistatically interacting trait loci. Monte-Carlo simulations are included to compare the efficiencies of the proposed procedures with some currently used methods. An application of our proposed method is presented using data on alcohol dependence.
20152806
Association Analysis of Population-Based Quantitative Trait Data: An Assessment of ANOVA
The classical analysis of variance (ANOVA) compares the means of different groups under the assumption that the variances within each of the groups are equal. However, for genetic studies of complex disorders, it is not reasonable to assume that variance of a quantitative trait within each genotype at the trait locus will be equal. Thus, the use of ANOVA may lead to misleading association inferences. In this article, we perform a simulation-based study to assess the rate of false positives and the power of ANOVA under various probability distributions of the quantitative trait and different genetic parameters such as allele frequencies and coefficient of linkage disequilibrium.
195690549
Linkage mapping of quantitative trait loci in humans: an overview.
In this article, we provide an overview of the different statistical procedures that have been developed for linkage mapping of quantitative trait loci. We outline the model assumptions, the data requirements and the underlying tests for linkage for the different methods.
11618662
Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
BackgroundCompared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression method and the "contrast function"- based regression method to analyze total cholesterol level in the younger cohort (the offspring generation) of the Genetic Analysis Workshop 13 simulated data set.ResultsWe obtained significant evidence of linkage near four of the six non-sex-specific genes in at least 30% of the replicates.ConclusionsThe proposed nonparametric method seems to be a powerful robust alternative to distribution-based methods.
343855
Identifying rare variants from exome scans: the GAW17 experience
Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.
25372281
Progress in development of vaccine against Hyalomma anatolicum anatolicum-Indian scenario.
Hyalomma anatolicum anatolicum, a three host tick vector transmitting the causative agent of bovine tropical theileriosis, is widely distributed throughout India. As a component of integrated control measures against the tick vector, attempts have been made to identify candidate protein molecules for development of an anti-tick vaccine in the different stages of this tick species. By strategic methods of isolation of the targeted molecules using affinity purification of proteins showing reactivity with immunoglobulins of animals previously immunized with different sources of tick antigen, six proteins were isolated in a significantly pure form. The recovery percentage of the candidate proteins was very low in the range of 1.8-8.0%. The protective potentiality of the antigens was tested in immunization and challenge trials and maximum potential was observed in the proteins isolated from total larval extracts, nymphal extracts and in larval glycoprotein. One of the antigens with a molecular weight of 37kDa isolated from larvae of H. a. anatolicum was found to have some adverse effect on development of Theileria annulata in the vector tick. The progress in the development of immunoprophylactic measures against H. a. anatolicum is discussed.
1958962
Whole-genomic analysis of a human G1P[9] rotavirus strain reveals intergenogroup-reassortment events.
Group A rotavirus (RVA) strain K8 (RVA/Human-tc/JPN/K8/1977/G1P[9]) was found to have Wa-like VP7 and NSP1 genes and AU-1-like VP4 and NSP5 genes. To determine the exact origin and overall genetic makeup of this unusual RVA strain, the remaining genes (VP1-VP3, VP6 and NSP2-NSP4) of K8 were analysed in this study. Strain K8 exhibited a G1-P[9]-I1-R3-C3-M3-A1-N1-T3-E3-H3 genotype constellation, not reported previously. The VP6 and NSP2 genes of strain K8 were related closely to those of common human Wa-like G1P[8] and/or G3P[8] strains, whilst its VP1-VP3, NSP3 and NSP4 genes were related more closely to those of AU-1-like RVAs and/or AU-1-like genes of multi-reassortant strains than to those of other RVAs. Therefore, strain K8 might have originated from intergenogroup-reassortment events involving acquisition of four Wa-like genes, possibly from G1P[8] RVAs, by an AU-1-like P[9] strain. Whole-genomic analysis of strain K8 has provided important insights into the complex genetic diversity of RVAs.
12243541
Cell density-dependent transcriptional activation of endocrine-related genes in human adipose tissue-derived stem cells.
Adipose tissue is recognized as an endocrine organ that plays an important role in human diseases such as type II diabetes and cancer. Human adipose tissue-derived stem cells (ASCs), a distinct cell population in adipose tissue, are capable of differentiating into multiple lineages including adipogenesis. When cultured in vitro under a confluent condition, ASCs reach a commitment stage for adipogenesis, which can be further induced into terminally differentiated adipocytes by a cocktail of adipogenic factors. Here we report that the confluent state of ASCs triggers transcriptional activation cascades for genes that are responsible for the endocrine function of adipose tissue. These include insulin-like growth factor 1 (IGF-1) and aromatase (Cyp19), a key enzyme in estrogen biosynthesis. Despite similar adipogenic potentials, ASCs from different individuals display huge variations in activation of these endocrine-related genes. Bioinformatics and experimental data suggest that transcription factor Foxo1 controls a large number of "early" confluency-response genes, which subsequently induce "late" response genes. Furthermore, siRNA-mediated knockdown of Foxo1 substantially compromises the ability of committed ASCs to stimulate tumor cell migration in vitro. Thus, our work suggests that cell density is an important determinant of the endocrine potential of ASCs.
13636170
Accuracy of Quadratic Versus Linear Interpolation in Noninvasive Electrocardiographic Imaging (ECGI)
Electrocardiographic Imaging (ECGI) is a cardiac functional imaging modality, noninvasively reconstructing epicardial potentials, electrograms and isochrones (activation maps) from multi-channel body surface potential recordings. The procedure involves solving Laplace’s equation in the source-free volume conductor between torso and epicardial surfaces, using Boundary Element Method (BEM). Previously, linear interpolation (LI) on three-noded triangular surface elements was used in the BEM formulation. Here, we use quadratic interpolation (QI) for potentials over six-noded linear triangles. The performance of LI and QI in ECGI is evaluated through direct comparison with measured data from an isolated canine heart suspended in a human-torso-shaped electrolyte tank. QI enhances the accuracy and resolution of ECGI reconstructions for two different inverse methods, Tikhonov regularization and Generalized Minimal Residual (GMRes) method, with the QI-GMRes combination providing the highest accuracy and resolution. QI reduces the average relative error (RE) between reconstructed and measured epicardial potentials by 25%. It preserves the amplitude (average RE reduced by 48%) and morphology of electrograms better (average correlation coefficient for QI ∼ 0.97, LI ∼ 0.92). We also applied QI to ECGI reconstructions in human subjects during cardiac pacing, where QI locates ventricular pacing sites with higher accuracy (≤ 10 mm) than LI (≤ 18 mm).
12219567
Application of rbcL based molecular diversity analysis to algae in wastewater treatment plants.
The molecular diversity of algae in the final clarifier or denitrification filter outfall from three wastewater treatment plants (WWTPs) with activated sludge based treatment was analyzed using the rbcL gene as a phylogenetic marker. The rbcL gene encodes the large subunit of the CO(2) fixing enzyme RuBisCO. Among algae identified at the WWTPs were diatoms, green algae, cyanobacteria, Eustigmatophyceae, and unknown heterokonts. A high level of diversity was observed within WWTPs with 19-24 unique rbcL sequences detected at each plant. Algae composition also varied between treatment plants. Our results show that the rbcL gene can be used as a phylogenetic marker for algae diversity analysis in a wastewater treatment context.