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At least 1,189 records · Page 66Linked to original sources
PubMed2004

Inversion frequencies in Drosophila serrata along an eastern Australian transect.

Clinal patterns over broad geographic regions provide a way of identifying characteristics of species under selection and are increasingly being used in quantitative trait locus mapping of adaptive genetic variation in Drosophila. However, interpretations of clinal patterns can be complicated by inversions that also vary clinally and reduce recombination in some parts of the genome. Drosophila serrata (Malloch) is an Australian endemic species being used to investigate the genetic basis of geographic variation in climatic adaptation and mate recognition. Here we describe inversions in D. serrata populations from the east coast of Australia, covering tropical and temperate regions. Seven autosomal paracentric inversions and 1 apparently complex X chromosome arrangement were identified from these populations. All inverted arrangements were relatively more common in tropical populations; 2 common inversions showed clinal patterns over part of the range of D. serrata. Inversion polymorphism was relatively higher in tropical populations and almost absent in populations near the cooler southern border, in agreement with findings on other Drosophila species. While these patterns will complicate mapping of adaptive variation in D. serrata, they suggest that this species will be useful in investigatingthe dynamics of inversion-trait associations in natural populations.

Animals↗
PubMed2005

Quantitative trait analysis in the investigation of function and aging of hematopoietic stem cells.

Extensive genetically determined quantitative variation exists in the number and function of hematopoietic stem cells in inbred mouse strains. Furthermore, aging of hematopoietic stem cells is genetically determined. Gene identification of quantitative trait loci involved in the regulation and aging of hematopoietic stem cells would provide novel insights into regulatory mechanisms that are relevant in vivo and may be clinically important. Here we describe strategies for mapping and gene identification of quantitative trait loci applied to traits contributing to the regulation of hematopoietic stem cells.

Aging↗
PubMed1992

Detection of genetic heterogeneity for complex quantitative phenotypes.

Statistically characterizing factors responsible for quantitative phenotype expression (e.g., polygenes, major genes, shared household factors, etc.) through model selection strategies is a difficult task. A great deal of effort has been expended on refining mathematical and computational aspects of various segregation models used to characterize unique expressions of quantitative phenotypes in an effort to make these models easier to implement and evaluate for a given set of data. In this paper a slightly different angle is emphasized: namely, the explicit modeling of the potentially numerous heterogeneous genetic and environmental processes (i.e., segregation patterns, household aggregations, etiologic processes, etc.) that could contribute to the overall variation of a quantitative trait. As such, this paper describes tools for detecting quantitative trait heterogeneity that are meant to answer such questions as "are there pedigrees among a great many that show a pattern consistent with a possibly very specific single locus segregation pattern while the rest show compatibility with a polygenic or purely environmental pattern?" Methods for determining the significance of such heterogeneity are also discussed, as are the results of numerous examples and simulation studies carried out in an effort to validate and further elaborate aspects of the proposed techniques.

Genetic Linkage↗
PubMed1980

Ultraviolet light induction of diphtheria toxin-resistant mutations in normal and DNA repair-deficient human and Chinese hamster fibroblasts.

The role of unrepaired DNA lesions in the production of mutations is suspected of contributing to the initiation phase of carcinogenesis. Since the molecular basis of mutagenesis is not understood in eukaryotic cells, development of new genetic markers for quantitative in vitro measurement of mutations for mammalian cells is needed. Furthermore, mammalian cells, genetically deficient for various DNA repair enzymes, will be needed to study the role of unrepaired DNA lesions in mutagenesis. The results in this report relate to preliminary attempts (1) to characterize the diphtheria toxin resistance marker as a useful quantitative genetic marker in human cells and (2) to isolate and characterize various DNA repair-deficient Chinese hamster cells.

Animals↗
PubMed2000

Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships.

Quantitative structure-activity relationship (QSAR) studies based on chemometric techniques are reviewed. Partial least squares (PLS) is introduced as a novel robust method to replace classical methods such as multiple linear regression (MLR). Advantages of PLS compared to MLR are illustrated with typical applications. Genetic algorithm (GA) is a novel optimization technique which can be used as a search engine in variable selection. A novel hybrid approach comprising GA and PLS for variable selection developed in our group (GAPLS) is described. The more advanced method for comparative molecular field analysis (CoMFA) modeling called GA-based region selection (GARGS) is described as well. Applications of GAPLS and GARGS to QSAR and 3D-QSAR problems are shown with some representative examples. GA can be hybridized with nonlinear modeling methods such as artificial neural networks (ANN) for providing useful tools in chemometric and QSAR.

Algorithms↗
PubMed2026

Pervasive context-dependent effects in the genetic architecture of complex and quantitative traits revealed by a powerful multiparent mapping population in yeast.

The genetic dissection of complex traits remains a major challenge in basic and biomedical research, but is essential for understanding the molecular pathways that shape phenotypic variation and for developing predictive models of trait and disease susceptibility. Here, we leverage a novel multiparent mapping population of budding yeast, CYClones, comprising 9,344 haploid strains derived from eight genetically diverse founders (~270,000 SNVs, ~ 1 per 44 bp, capturing 56% of common variants and 32% of all variants with a minor allele frequency greater than 0.005 in the global population), to identify quantitative trait loci (QTL) and systematically investigate the genetic architecture of growth rates across ten environmental conditions. In total, we identified 349 QTL (ranging from 18 to 49 QTL per growth condition) that explained between 60% and 100% of narrow sense heritability across traits. The high power and resolution of CYClones revealed that growth traits exhibited distinct, condition-specific genetic architectures with extensive allelic heterogeneity, where a QTL was the result of multiple tightly linked causal variants. We also observed pleiotropy among QTL with complex, trait-dependent allele effects that are also consistent with allelic heterogeneity. Genetic complexity varied widely, with some traits showing nearly Mendelian architectures, while others were highly polygenic. Introgressed loci played a prominent role in the landscape of growth rate QTL, including a QTL localized to a 2.4 kb interval in the PCA1 cadmium transporter that explains 72% of variation in cadmium resistance and is largely driven by an introgression, and a non-additive interaction between the GAL3 regulator and introgressed GAL1/7/10 alleles, extending a previously described three-locus GAL-pathway incompatibility to a four-locus interaction. In both cadmium and galactose conditions, we show that allelic variation at a small number of loci stratifies the population into regulatory or physiological subgroups, each with distinct genetic architectures, a specific manifestation of epistasis we term allele-dependent stratification. Collectively, our results provide novel insights into the genetics of growth rates in budding yeast, the architectural features of genetic complexity, and demonstrate that CYClones is a powerful platform for revealing the molecular basis of complex trait variation.

Quantitative Trait Loci↗
PubMed1980

The preparation of transforming DNA from Mycoplasma hominis strain Sprott tetr and quantitative studies of the factors affecting the genetic transformation of Mycoplasma salivarium strain S9 tets to tetracycline resistance.

DNA extracted by a standard method from Mycoplasma hominis Sprott, resistant to 100 micrograms tetracycline, permitted the quantitative genetic transformation of tetracycline-sensitive Mycoplasma salivarium to resistance. The yield was 1 microgram DNA/10(9) cells. This DNA enabled determination of the optimum conditions for making M. Salivarium competent with CaCl2 and for studying some factors affecting transformation. Mycoplasma salivarium was transformed to resistance to 10, 20, and 30 micrograms tetracycline but not to 40 micrograms. The optimum DNA concentration for transforming resistance to 10, 20, and 30 micrograms tetracycline was the same, i.e., 50 micrograms DNA/10(8) viable cells. Treatment with DNase indicated that DNA uptake took 30 min. Competition between transforming DNA and DNA from calf thymus and M. salivarium tets inhibited transformation.

Calcium Chloride↗
PubMed1985

Genetic distances based on quantitative traits.

Morphological data showing continuous distributions, polygenically controlled, may be particularly useful in intergroup classification below the species level; an appropriate distance analysis based on these traits is an important tool in evolutionary biology and in plant and animal breeding.--The interpretation of morphological distances in genetic terms is not easy because simple phenotypic data may lead to biased estimates of genetic distances. Convenient estimates can be obtained whenever it is possible to breed populations according to a suitable crossing design and to derive information from genetic parameters.--A general method for determining genetic distances is proposed. The procedure of multivariate analysis of variance is extended to estimate appropriate genetic parameters (genetic effects). Not only are optimal statistical estimates of parameters obtained but also the procedure allows the measurement of genetic distances between populations as linear functions of the estimated parameters, providing an appropriate distance matrix that can be defined in terms of these parameters. The use of the T2 statistic, defined in terms of the vector of contrasts specifying the distance, permits the testing of the significance of any distance between any pair of populations that may be of interest from a genetic point of view.--A numerical example from maize diallel data is reported in order to illustrate the procedure. In particular, heterosis effects are used as the basis for estimates of genetic divergence between populations.

Analysis of Variance↗
PubMed2006

Efficient quantitative morphological phenotyping of genetically altered organisms using stereology.

Genetically modified organisms present the challenge of quantifying structures and functions in organs, tissues and cells. Morphological investigation is greatly facilitated by taking sections in MRI, CAT scanning, histological preparations or EM, and powerful unbiased quantitative tools called stereology can use these sections in a sampling based approach to measure volume, number surface and length. Stereological tools have become methods of choice in the fields of neurobiology, nephrology and cell biology and allow accurate unbiased description of intact organs, tissues, cells and organelles. Stereology has yet to be applied widely in the field of transgenics. Here I provide an overview of stereological methods and explain how they represent a powerful addition to the transgenic biologists armoury of techniques.

Animals↗
PubMed2002

Novel linkage mapping approach using DNA pooling in human and animal genetics. II. Detection of quantitative traits loci in dairy cattle.

Selective DNA pooling is an advanced methodology for linkage mapping of quantitative trait loci (QTL) in farm animals. The principle is based on densitometric estimates of marker allele frequency in pooled DNA samples of phenotypically extreme individuals from half-sib, backcross and F(2) experimental designs in farm animals. This methodology provides a rapid and efficient analysis of a large number of individuals with short tandem repeat markers that are essential to detect QTL through the genome - wide searching approach. Several strategies involving whole genome scanning with a high statistical power have been developed for systematic search to detect the quantitative traits loci and linked loci of complex traits. In recent studies, greater success has been achieved in mapping several QTLs in Israel-Holstein cattle using selective DNA pooling. This paper outlines the currently emerged novel strategies of linkage mapping to identify QTL based on selective DNA pooling with more emphasis on its theoretical pre-requisite to detect linked QTLs, applications, a general theory for experimental half-sib designs, the power of statistics and its feasibility to identify genetic markers linked QTL in dairy cattle. The study reveals that the application of selective DNA pooling in dairy cattle can be best exploited in the genome-wide detection of linked loci with small and large QTL effects and applied to a moderately sized half-sib family of about 500 animals.

Animals↗
PubMed2004

Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice.

Here we present a strategy to determine the genetic basis of variance in complex phenotypes that arise from natural, as opposed to induced, genetic variation in mice. We show that a commercially available strain of outbred mice, MF1, can be treated as an ultrafine mosaic of standard inbred strains and accordingly used to dissect a known quantitative trait locus influencing anxiety. We also show that this locus can be subdivided into three regions, one of which contains Rgs2, which encodes a regulator of G protein signaling. We then use quantitative complementation to show that Rgs2 is a quantitative trait gene. This combined genetic and functional approach should be applicable to the analysis of any quantitative trait.

Animals↗
PubMed1999

Methods to estimate genetic components of variance for quantitative traits in family studies.

The aim of this paper was to compare several methods of estimating the genetic components of a quantitative trait in familial data. The Expectation and Maximization (E-M) algorithm, the Newton-Raphson method, and the scoring method were compared for estimating polygenic and environmental effects on nuclear families. We also compared scoring and quasilikelihood (QL) methods when a linked genetic marker was available to estimate effects from a major gene. Generally, all procedures performed similarly in estimating polygenic and environmental variance components. The E-M algorithm yielded more precise estimators when heritability was low. The scoring method was much faster than the other methods and yielded slightly more precise estimates of mean effects but slightly less precise estimates of the variance components. Estimates of major gene effects were not affected by the number of alleles at the trait locus. For these relatively large sample sizes, QL and scoring had similar precision, but QL took 32 times longer than scoring. Finally, we compared the results of applying these methods to data from the Bogalusa Heart Study. Results showed larger imprecision when the QL method was applied, consistent with earlier studies that showed decreased precision of quasilikelihood compared with maximum likelihood in moderately small sample sizes.

Algorithms↗
PubMedDate not supplied

McQSAR: a multiconformational quantitative structure-activity relationship engine driven by genetic algorithms.

The generation of quantitative structure-activity relationships (QSARs) under the supervision of a genetic algorithm (GA) is a QSAR modeling approach used for more than a decade. In this paper we present McQSAR, an extension to the traditional GA approach to derive QSARs. McQSAR is able to use descriptors for multiple representations per compound, such as different conformers, tautomers, or protonation forms. Test runs show that the algorithm converges to a set of representations that describe the binding mode of the set of input molecules to a reasonable resolution provided that suitable descriptors-based on the three-dimensional structure-are used. Furthermore, the frequency of chance correlation was measured during multiple runs on a real-life data set using simulated linear relationship functions. The observed frequency of chance correlation, on average 0.3 +/- 0.5%, was found independent of the size of the calibration set and the number of terms in the underlying relationship function.

Algorithms↗