PCR-free quantitative detection of genetically modified organism from raw materials – A novel electrochemiluminescence-based bio-barcode method

PubMed Central

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R.

2018-01-01

Bio-barcode assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio-barcode assay requires lengthy experimental procedures including the preparation and release of barcode DNA probes from the target-nanoparticle complex, and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio-barcode assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2’2’-bipyridyl) ruthenium (TBR)-labele barcode DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products. PMID:18386909

Interlaboratory validation of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

PubMed

Takabatake, Reona; Koiwa, Tomohiro; Kasahara, Masaki; Takashima, Kaori; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Oguchi, Taichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2011-01-01

To reduce the cost and time required to routinely perform the genetically modified organism (GMO) test, we developed a duplex quantitative real-time PCR method for a screening analysis simultaneously targeting an event-specific segment for GA21 and Cauliflower Mosaic Virus 35S promoter (P35S) segment [Oguchi et al., J. Food Hyg. Soc. Japan, 50, 117-125 (2009)]. To confirm the validity of the method, an interlaboratory collaborative study was conducted. In the collaborative study, conversion factors (Cfs), which are required to calculate the GMO amount (%), were first determined for two real-time PCR instruments, the ABI PRISM 7900HT and the ABI PRISM 7500. A blind test was then conducted. The limit of quantitation for both GA21 and P35S was estimated to be 0.5% or less. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSD(R)). The determined bias and RSD(R) were each less than 25%. We believe the developed method would be useful for the practical screening analysis of GM maize.

Development of a screening method for genetically modified soybean by plasmid-based quantitative competitive polymerase chain reaction.

PubMed

Shimizu, Eri; Kato, Hisashi; Nakagawa, Yuki; Kodama, Takashi; Futo, Satoshi; Minegishi, Yasutaka; Watanabe, Takahiro; Akiyama, Hiroshi; Teshima, Reiko; Furui, Satoshi; Hino, Akihiro; Kitta, Kazumi

2008-07-23

A novel type of quantitative competitive polymerase chain reaction (QC-PCR) system for the detection and quantification of the Roundup Ready soybean (RRS) was developed. This system was designed based on the advantage of a fully validated real-time PCR method used for the quantification of RRS in Japan. A plasmid was constructed as a competitor plasmid for the detection and quantification of genetically modified soy, RRS. The plasmid contained the construct-specific sequence of RRS and the taxon-specific sequence of lectin1 (Le1), and both had 21 bp oligonucleotide insertion in the sequences. The plasmid DNA was used as a reference molecule instead of ground seeds, which enabled us to precisely and stably adjust the copy number of targets. The present study demonstrated that the novel plasmid-based QC-PCR method could be a simple and feasible alternative to the real-time PCR method used for the quantification of genetically modified organism contents.

Quantitative genetics of disease traits.

PubMed

Wray, N R; Visscher, P M

2015-04-01

John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics. © 2015 Blackwell Verlag GmbH.

Selection of Suitable DNA Extraction Methods for Genetically Modified Maize 3272, and Development and Evaluation of an Event-Specific Quantitative PCR Method for 3272.

PubMed

Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2016-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize, 3272. We first attempted to obtain genome DNA from this maize using a DNeasy Plant Maxi kit and a DNeasy Plant Mini kit, which have been widely utilized in our previous studies, but DNA extraction yields from 3272 were markedly lower than those from non-GM maize seeds. However, lowering of DNA extraction yields was not observed with GM quicker or Genomic-tip 20/G. We chose GM quicker for evaluation of the quantitative method. We prepared a standard plasmid for 3272 quantification. The conversion factor (Cf), which is required to calculate the amount of a genetically modified organism (GMO), was experimentally determined for two real-time PCR instruments, the Applied Biosystems 7900HT (the ABI 7900) and the Applied Biosystems 7500 (the ABI7500). The determined Cf values were 0.60 and 0.59 for the ABI 7900 and the ABI 7500, respectively. To evaluate the developed method, a blind test was conducted as part of an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSDr). The determined values were similar to those in our previous validation studies. The limit of quantitation for the method was estimated to be 0.5% or less, and we concluded that the developed method would be suitable and practical for detection and quantification of 3272.

Real-Time PCR-Based Quantitation Method for the Genetically Modified Soybean Line GTS 40-3-2.

PubMed

Kitta, Kazumi; Takabatake, Reona; Mano, Junichi

2016-01-01

This chapter describes a real-time PCR-based method for quantitation of the relative amount of genetically modified (GM) soybean line GTS 40-3-2 [Roundup Ready(®) soybean (RRS)] contained in a batch. The method targets a taxon-specific soybean gene (lectin gene, Le1) and the specific DNA construct junction region between the Petunia hybrida chloroplast transit peptide sequence and the Agrobacterium 5-enolpyruvylshikimate-3-phosphate synthase gene (epsps) sequence present in GTS 40-3-2. The method employs plasmid pMulSL2 as a reference material in order to quantify the relative amount of GTS 40-3-2 in soybean samples using a conversion factor (Cf) equal to the ratio of the RRS-specific DNA to the taxon-specific DNA in representative genuine GTS 40-3-2 seeds.

Genomic Quantitative Genetics to Study Evolution in the Wild.

PubMed

Gienapp, Phillip; Fior, Simone; Guillaume, Frédéric; Lasky, Jesse R; Sork, Victoria L; Csilléry, Katalin

2017-12-01

Quantitative genetic theory provides a means of estimating the evolutionary potential of natural populations. However, this approach was previously only feasible in systems where the genetic relatedness between individuals could be inferred from pedigrees or experimental crosses. The genomic revolution opened up the possibility of obtaining the realized proportion of genome shared among individuals in natural populations of virtually any species, which could promise (more) accurate estimates of quantitative genetic parameters in virtually any species. Such a 'genomic' quantitative genetics approach relies on fewer assumptions, offers a greater methodological flexibility, and is thus expected to greatly enhance our understanding of evolution in natural populations, for example, in the context of adaptation to environmental change, eco-evolutionary dynamics, and biodiversity conservation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Universality and predictability in molecular quantitative genetics.

PubMed

Nourmohammad, Armita; Held, Torsten; Lässig, Michael

2013-12-01

Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. Copyright © 2013. Published by Elsevier Ltd.

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus.

PubMed

Andrew, R L; Peakall, R; Wallis, I R; Wood, J T; Knight, E J; Foley, W J

2005-12-01

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.

Reinventing the ames test as a quantitative lab that connects classical and molecular genetics.

PubMed

Goodson-Gregg, Nathan; De Stasio, Elizabeth A

2009-01-01

While many institutions use a version of the Ames test in the undergraduate genetics laboratory, students typically are not exposed to techniques or procedures beyond qualitative analysis of phenotypic reversion, thereby seriously limiting the scope of learning. We have extended the Ames test to include both quantitative analysis of reversion frequency and molecular analysis of revertant gene sequences. By giving students a role in designing their quantitative methods and analyses, students practice and apply quantitative skills. To help students connect classical and molecular genetic concepts and techniques, we report here procedures for characterizing the molecular lesions that confer a revertant phenotype. We suggest undertaking reversion of both missense and frameshift mutants to allow a more sophisticated molecular genetic analysis. These modifications and additions broaden the educational content of the traditional Ames test teaching laboratory, while simultaneously enhancing students' skills in experimental design, quantitative analysis, and data interpretation.

The integration of quantitative genetics, paleontology, and neontology reveals genetic underpinnings of primate dental evolution.

PubMed

Hlusko, Leslea J; Schmitt, Christopher A; Monson, Tesla A; Brasil, Marianne F; Mahaney, Michael C

2016-08-16

Developmental genetics research on mice provides a relatively sound understanding of the genes necessary and sufficient to make mammalian teeth. However, mouse dentitions are highly derived compared with human dentitions, complicating the application of these insights to human biology. We used quantitative genetic analyses of data from living nonhuman primates and extensive osteological and paleontological collections to refine our assessment of dental phenotypes so that they better represent how the underlying genetic mechanisms actually influence anatomical variation. We identify ratios that better characterize the output of two dental genetic patterning mechanisms for primate dentitions. These two newly defined phenotypes are heritable with no measurable pleiotropic effects. When we consider how these two phenotypes vary across neontological and paleontological datasets, we find that the major Middle Miocene taxonomic shift in primate diversity is characterized by a shift in these two genetic outputs. Our results build on the mouse model by combining quantitative genetics and paleontology, and thereby elucidate how genetic mechanisms likely underlie major events in primate evolution.

EvolQG - An R package for evolutionary quantitative genetics

PubMed Central

Melo, Diogo; Garcia, Guilherme; Hubbe, Alex; Assis, Ana Paula; Marroig, Gabriel

2016-01-01

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \\textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification. PMID:27785352

Quantitative PCR for Detection and Enumeration of Genetic Markers of Bovine Fecal Pollution

EPA Science Inventory

Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described cow feces-spec...

Harnessing quantitative genetics and genomics for understanding and improving complex traits in crops

USDA-ARS?s Scientific Manuscript database

Classical quantitative genetics aids crop improvement by providing the means to estimate heritability, genetic correlations, and predicted responses to various selection schemes. Genomics has the potential to aid quantitative genetics and applied crop improvement programs via large-scale, high-thro...

Breeding and quantitative genetics advances in sunflower Sclerotinia research

USDA-ARS?s Scientific Manuscript database

Genetic research of the sunflower research unit, USDA-ARS, in Fargo, ND, was discussed in a presentation to a group of producers, industry representatives, and scientists. The need for sunflower quantitative genetics research to find and capture Sclerotinia resistance is increasing with every year t...

Development and in-house validation of the event-specific qualitative and quantitative PCR detection methods for genetically modified cotton MON15985.

PubMed

Jiang, Lingxi; Yang, Litao; Rao, Jun; Guo, Jinchao; Wang, Shu; Liu, Jia; Lee, Seonghun; Zhang, Dabing

2010-02-01

To implement genetically modified organism (GMO) labeling regulations, an event-specific analysis method based on the junction sequence between exogenous integration and host genomic DNA has become the preferential approach for GMO identification and quantification. In this study, specific primers and TaqMan probes based on the revealed 5'-end junction sequence of GM cotton MON15985 were designed, and qualitative and quantitative polymerase chain reaction (PCR) assays were established employing the designed primers and probes. In the qualitative PCR assay, the limit of detection (LOD) was 0.5 g kg(-1) in 100 ng total cotton genomic DNA, corresponding to about 17 copies of haploid cotton genomic DNA, and the LOD and limit of quantification (LOQ) for quantitative PCR assay were 10 and 17 copies of haploid cotton genomic DNA, respectively. Furthermore, the developed quantitative PCR assays were validated in-house by five different researchers. Also, five practical samples with known GM contents were quantified using the developed PCR assay in in-house validation, and the bias between the true and quantification values ranged from 2.06% to 12.59%. This study shows that the developed qualitative and quantitative PCR methods are applicable for the identification and quantification of GM cotton MON15985 and its derivates.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

PubMed

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait

Quantitative maps of genetic interactions in yeast - comparative evaluation and integrative analysis.

PubMed

Lindén, Rolf O; Eronen, Ville-Pekka; Aittokallio, Tero

2011-03-24

High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms. Using large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies. We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

QUANTITATIVE GENETIC ACTIVITY GRAPHICAL PROFILES FOR USE IN CHEMICAL EVALUATION

EPA Science Inventory

A graphic approach termed a Genetic Activity Profile (GAP) has been developed to display a matrix of data on the genetic and related effects of selected chemical agents. he profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each...

An event-specific method for the detection and quantification of ML01, a genetically modified Saccharomyces cerevisiae wine strain, using quantitative PCR.

PubMed

Vaudano, Enrico; Costantini, Antonella; Garcia-Moruno, Emilia

2016-10-03

The availability of genetically modified (GM) yeasts for winemaking and, in particular, transgenic strains based on the integration of genetic constructs deriving from other organisms into the genome of Saccharomyces cerevisiae, has been a reality for several years. Despite this, their use is only authorized in a few countries and limited to two strains: ML01, able to convert malic acid into lactic acid during alcoholic fermentation, and ECMo01 suitable for reducing the risk of carbamate production. In this work we propose a quali-quantitative culture-independent method for the detection of GM yeast ML01 in commercial preparations of ADY (Active Dry Yeast) consisting of efficient extraction of DNA and qPCR (quantitative PCR) analysis based on event-specific assay targeting MLC (malolactic cassette), and a taxon-specific S. cerevisiae assay detecting the MRP2 gene. The ADY DNA extraction methodology has been shown to provide good purity DNA suitable for subsequent qPCR. The MLC and MRP2 qPCR assay showed characteristics of specificity, dynamic range, limit of quantification (LOQ) limit of detection (LOD), precision and trueness, which were fully compliant with international reference guidelines. The method has been shown to reliably detect 0.005% (mass/mass) of GM ML01 S. cerevisiae in commercial preparations of ADY. Copyright © 2016 Elsevier B.V. All rights reserved.

Genetic Architectures of Quantitative Variation in RNA Editing Pathways

PubMed Central

Gu, Tongjun; Gatti, Daniel M.; Srivastava, Anuj; Snyder, Elizabeth M.; Raghupathy, Narayanan; Simecek, Petr; Svenson, Karen L.; Dotu, Ivan; Chuang, Jeffrey H.; Keller, Mark P.; Attie, Alan D.; Braun, Robert E.; Churchill, Gary A.

2016-01-01

RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing. PMID:26614740

Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

PubMed

Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

2009-11-01

The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

Albert, Réka; Collins, James J.; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

PubMed

Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

2015-10-01

Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.

Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait

PubMed Central

Hernández-Serrano, Ana; Verdú, Miguel; Santos-del-Blanco, Luís; Climent, José; González-Martínez, Santiago C.; Pausas, Juli G.

2014-01-01

Background and Aims Although it is well known that fire acts as a selective pressure shaping plant phenotypes, there are no quantitative estimates of the heritability of any trait related to plant persistence under recurrent fires, such as serotiny. In this study, the heritability of serotiny in Pinus halepensis is calculated, and an evaluation is made as to whether fire has left a selection signature on the level of serotiny among populations by comparing the genetic divergence of serotiny with the expected divergence of neutral molecular markers (QST–FST comparison). Methods A common garden of P. halepensis was used, located in inland Spain and composed of 145 open-pollinated families from 29 provenances covering the entire natural range of P. halepensis in the Iberian Peninsula and Balearic Islands. Narrow-sense heritability (h2) and quantitative genetic differentiation among populations for serotiny (QST) were estimated by means of an ‘animal model’ fitted by Bayesian inference. In order to determine whether genetic differentiation for serotiny is the result of differential natural selection, QST estimates for serotiny were compared with FST estimates obtained from allozyme data. Finally, a test was made of whether levels of serotiny in the different provenances were related to different fire regimes, using summer rainfall as a proxy for fire regime in each provenance. Key Results Serotiny showed a significant narrow-sense heritability (h2) of 0·20 (credible interval 0·09–0·40). Quantitative genetic differentiation among provenances for serotiny (QST = 0·44) was significantly higher than expected under a neutral process (FST = 0·12), suggesting adaptive differentiation. A significant negative relationship was found between the serotiny level of trees in the common garden and summer rainfall of their provenance sites. Conclusions Serotiny is a heritable trait in P. halepensis, and selection acts on it, giving rise to contrasting serotiny levels

Quantitative genetics of immunity and life history under different photoperiods.

PubMed

Hammerschmidt, K; Deines, P; Wilson, A J; Rolff, J

2012-05-01

Insects with complex life-cycles should optimize age and size at maturity during larval development. When inhabiting seasonal environments, organisms have limited reproductive periods and face fundamental decisions: individuals that reach maturity late in season have to either reproduce at a small size or increase their growth rates. Increasing growth rates is costly in insects because of higher juvenile mortality, decreased adult survival or increased susceptibility to parasitism by bacteria and viruses via compromised immune function. Environmental changes such as seasonality can also alter the quantitative genetic architecture. Here, we explore the quantitative genetics of life history and immunity traits under two experimentally induced seasonal environments in the cricket Gryllus bimaculatus. Seasonality affected the life history but not the immune phenotypes. Individuals under decreasing day length developed slower and grew to a bigger size. We found ample additive genetic variance and heritability for components of immunity (haemocyte densities, proPhenoloxidase activity, resistance against Serratia marcescens), and for the life history traits, age and size at maturity. Despite genetic covariance among traits, the structure of G was inconsistent with genetically based trade-off between life history and immune traits (for example, a strong positive genetic correlation between growth rate and haemocyte density was estimated). However, conditional evolvabilities support the idea that genetic covariance structure limits the capacity of individual traits to evolve independently. We found no evidence for G × E interactions arising from the experimentally induced seasonality.

Effects of functionally asexual reproduction on quantitative genetic variation in the evening primroses (Oenothera, Onagraceae).

PubMed

Godfrey, Ryan M; Johnson, Marc T J

2014-11-01

It has long been predicted that a loss of sexual reproduction leads to decreased heritable variation within populations and increased differentiation between populations. Despite an abundance of theory, there are few empirical tests of how sex affects genetic variation in phenotypic traits, especially for plants. Here we test whether repeated losses of two critical components of sex (recombination and segregation) in the evening primroses (Oenothera L., Onagraceae) affect quantitative genetic variation within and between populations. We sampled multiple genetic families from 3-5 populations from each of eight Oenothera species, which represented four independent transitions between sexual reproduction and a functionally asexual genetic system called "permanent translocation heterozygosity." We used quantitative genetics methods to partition genetic variation within and between populations for eight plant traits related to growth, leaf physiology, flowering, and resistance to herbivores. Heritability was, on average, 74% higher in sexual Oenothera populations than in functionally asexual populations, with plant growth rate, specific leaf area, and the percentage of leaf water content showing the strongest differences. By contrast, genetic differentiation among populations was 2.8× higher in functionally asexual vs. sexual Oenothera species. This difference was particularly strong for specific leaf area. Sexual populations tended to exhibit higher genetic correlations among traits, but this difference was weakly supported. These results support the prediction that sexual reproduction maintains higher genetic variation within populations, which may facilitate adaptive evolution. We also found partial support for the prediction that a loss of sex leads to greater population differentiation, which may elevate speciation rates. © 2014 Botanical Society of America, Inc.

[Development and validation of event-specific quantitative PCR method for genetically modified maize LY038].

PubMed

Mano, Junichi; Masubuchi, Tomoko; Hatano, Shuko; Futo, Satoshi; Koiwa, Tomohiro; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Akiyama, Hiroshi; Teshima, Reiko; Kurashima, Takeyo; Takabatake, Reona; Kitta, Kazumi

2013-01-01

In this article, we report a novel real-time PCR-based analytical method for quantitation of the GM maize event LY038. We designed LY038-specific and maize endogenous reference DNA-specific PCR amplifications. After confirming the specificity and linearity of the LY038-specific PCR amplification, we determined the conversion factor required to calculate the weight-based content of GM organism (GMO) in a multilaboratory evaluation. Finally, in order to validate the developed method, an interlaboratory collaborative trial according to the internationally harmonized guidelines was performed with blind DNA samples containing LY038 at the mixing levels of 0, 0.5, 1.0, 5.0 and 10.0%. The precision of the method was evaluated as the RSD of reproducibility (RSDR), and the values obtained were all less than 25%. The limit of quantitation of the method was judged to be 0.5% based on the definition of ISO 24276 guideline. The results from the collaborative trial suggested that the developed quantitative method would be suitable for practical testing of LY038 maize.

A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

PubMed

Korolev, Kirill S; Xavier, João B; Nelson, David R; Foster, Kevin R

2011-10-01

It is widely accepted that population-genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on- and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut microbe Escherichia coli and the opportunistic pathogen Pseudomonas aeruginosa, and show that spatiogenetic patterns in colony biofilms of both species are accurately described by an extension of the one-dimensional stepping-stone model. We use one empirical measure, genetic diversity at the colony periphery, to parameterize our models and show that we can then accurately predict another key variable: the degree of short-range cell migration along an edge. Moreover, the model allows us to estimate other key parameters, including effective population size (density) at the expansion frontier. While our experimental system is a simplification of natural microbial community, we argue that it constitutes proof of principle that the spatial models of population genetics can quantitatively capture organismal evolution.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Making Quantitative Genetics Relevant: Effectiveness of a Laboratory Investigation that Links Scientific Research, Commercial Applications, and Legal Issues

ERIC Educational Resources Information Center

Rutledge, Michael L.; Mathis, Philip M.; Seipelt, Rebecca L.

2005-01-01

As students apply their knowledge of scientific concepts and of science as a method of inquiry, learning becomes relevant. This laboratory exercise is designed to foster students' understanding of the genetics of quantitative traits and of the nature of science as a method of inquiry by engaging them in a real-world business scenario. During the…

Refining Intervention Targets in Family-Based Research: Lessons From Quantitative Behavioral Genetics

PubMed Central

Leve, Leslie D.; Harold, Gordon T.; Ge, Xiaojia; Neiderhiser, Jenae M.; Patterson, Gerald

2010-01-01

The results from a large body of family-based research studies indicate that modifying the environment (specifically dimensions of the social environment) through intervention is an effective mechanism for achieving positive outcomes. Parallel to this work is a growing body of evidence from genetically informed studies indicating that social environmental factors are central to enhancing or offsetting genetic influences. Increased precision in the understanding of the role of the social environment in offsetting genetic risk might provide new information about environmental mechanisms that could be applied to prevention science. However, at present, the multifaceted conceptualization of the environment in prevention science is mismatched with the more limited measurement of the environment in many genetically informed studies. A framework for translating quantitative behavioral genetic research to inform the development of preventive interventions is presented in this article. The measurement of environmental indices amenable to modification is discussed within the context of quantitative behavioral genetic studies. In particular, emphasis is placed on the necessary elements that lead to benefits in prevention science, specifically the development of evidence-based interventions. An example from an ongoing prospective adoption study is provided to illustrate the potential of this translational process to inform the selection of preventive intervention targets. PMID:21188273

Quantitative analysis of terahertz spectra for illicit drugs using adaptive-range micro-genetic algorithm

NASA Astrophysics Data System (ADS)

Chen, Yi; Ma, Yong; Lu, Zheng; Peng, Bei; Chen, Qin

2011-08-01

In the field of anti-illicit drug applications, many suspicious mixture samples might consist of various drug components—for example, a mixture of methamphetamine, heroin, and amoxicillin—which makes spectral identification very difficult. A terahertz spectroscopic quantitative analysis method using an adaptive range micro-genetic algorithm with a variable internal population (ARVIPɛμGA) has been proposed. Five mixture cases are discussed using ARVIPɛμGA driven quantitative terahertz spectroscopic analysis in this paper. The devised simulation results show agreement with the previous experimental results, which suggested that the proposed technique has potential applications for terahertz spectral identifications of drug mixture components. The results show agreement with the results obtained using other experimental and numerical techniques.

QUANTITATIVE CANCER RISK ASSESSMENT METHODOLOGY USING SHORT-TERM GENETIC BIOASSAYS: THE COMPARATIVE POTENCY METHOD

EPA Science Inventory

Quantitative risk assessment is fraught with many uncertainties. The validity of the assumptions underlying the methods employed are often difficult to test or validate. Cancer risk assessment has generally employed either human epidemiological data from relatively high occupatio...

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

2013-01-01

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

Quantitative Assessment of Eye Phenotypes for Functional Genetic Studies Using Drosophila melanogaster

PubMed Central

Iyer, Janani; Wang, Qingyu; Le, Thanh; Pizzo, Lucilla; Grönke, Sebastian; Ambegaokar, Surendra S.; Imai, Yuzuru; Srivastava, Ashutosh; Troisí, Beatriz Llamusí; Mardon, Graeme; Artero, Ruben; Jackson, George R.; Isaacs, Adrian M.; Partridge, Linda; Lu, Bingwei; Kumar, Justin P.; Girirajan, Santhosh

2016-01-01

About two-thirds of the vital genes in the Drosophila genome are involved in eye development, making the fly eye an excellent genetic system to study cellular function and development, neurodevelopment/degeneration, and complex diseases such as cancer and diabetes. We developed a novel computational method, implemented as Flynotyper software (http://flynotyper.sourceforge.net), to quantitatively assess the morphological defects in the Drosophila eye resulting from genetic alterations affecting basic cellular and developmental processes. Flynotyper utilizes a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. As a proof of principle, we tested our method by analyzing the defects due to eye-specific knockdown of Drosophila orthologs of 12 neurodevelopmental genes to accurately document differential sensitivities of these genes to dosage alteration. We also evaluated eye images from six independent studies assessing the effect of overexpression of repeats, candidates from peptide library screens, and modifiers of neurotoxicity and developmental processes on eye morphology, and show strong concordance with the original assessment. We further demonstrate the utility of this method by analyzing 16 modifiers of sine oculis obtained from two genome-wide deficiency screens of Drosophila and accurately quantifying the effect of its enhancers and suppressors during eye development. Our method will complement existing assays for eye phenotypes, and increase the accuracy of studies that use fly eyes for functional evaluation of genes and genetic interactions. PMID:26994292

Quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria by gas chromatography-mass spectrometry.

PubMed

Guan, Wenna; Zhao, Hui; Lu, Xuefeng; Wang, Cong; Yang, Menglong; Bai, Fali

2011-11-11

Simple and rapid quantitative determination of fatty-acid-based biofuels is greatly important for the study of genetic engineering progress for biofuels production by microalgae. Ideal biofuels produced from biological systems should be chemically similar to petroleum, like fatty-acid-based molecules including free fatty acids, fatty acid methyl esters, fatty acid ethyl esters, fatty alcohols and fatty alkanes. This study founded a gas chromatography-mass spectrometry (GC-MS) method for simultaneous quantification of seven free fatty acids, nine fatty acid methyl esters, five fatty acid ethyl esters, five fatty alcohols and three fatty alkanes produced by wild-type Synechocystis PCC 6803 and its genetically engineered strain. Data obtained from GC-MS analyses were quantified using internal standard peak area comparisons. The linearity, limit of detection (LOD) and precision (RSD) of the method were evaluated. The results demonstrated that fatty-acid-based biofuels can be directly determined by GC-MS without derivation. Therefore, rapid and reliable quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria can be achieved using the GC-MS method founded in this work. Copyright © 2011 Elsevier B.V. All rights reserved.

[Methods of quantitative proteomics].

PubMed

Kopylov, A T; Zgoda, V G

2007-01-01

In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and functional homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.

Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.

PubMed

Santure, Anna W; Spencer, Hamish G

2006-08-01

The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components.

Quantitative genetic analysis of injury liability in infants and toddlers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, K.; Matheny, A.P. Jr.

1995-02-27

A threshold model of latent liability was applied to infant and toddler twin data on total count of injuries sustained during the interval from birth to 36 months of age. A quantitative genetic analysis of estimated twin correlations in injury liability indicated strong genetic dominance effects, but no additive genetic variance was detected. Because interpretations involving overdominance have little research support, the results may be due to low order epistasis or other interaction effects. Boys had more injuries than girls, but this effect was found only for groups whose parents were prompted and questioned in detail about their children`s injuries.more » Activity and impulsivity are two behavioral predictors of childhood injury, and the results are discussed in relation to animal research on infant and adult activity levels, and impulsivity in adult humans. Genetic epidemiological approaches to childhood injury should aid in targeting higher risk children for preventive intervention. 30 refs., 4 figs., 3 tabs.« less

Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

PubMed

Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

2016-01-01

Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics

PubMed Central

Corwin, Jason A.; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J.

2016-01-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes. PMID:26866607

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

PubMed

Corwin, Jason A; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J

2016-02-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes.

Quantitative Genetic Interactions Reveal Layers of Biological Modularity

PubMed Central

Beltrao, Pedro; Cagney, Gerard; Krogan, Nevan J.

2010-01-01

In the past, biomedical research has embraced a reductionist approach, primarily focused on characterizing the individual components that comprise a system of interest. Recent technical developments have significantly increased the size and scope of data describing biological systems. At the same time, advances in the field of systems biology have evoked a broader view of how the underlying components are interconnected. In this essay, we discuss how quantitative genetic interaction mapping has enhanced our view of biological systems, allowing a deeper functional interrogation at different biological scales. PMID:20510918

[Progress in stable isotope labeled quantitative proteomics methods].

PubMed

Zhou, Yuan; Shan, Yichu; Zhang, Lihua; Zhang, Yukui

2013-06-01

Quantitative proteomics is an important research field in post-genomics era. There are two strategies for proteome quantification: label-free methods and stable isotope labeling methods which have become the most important strategy for quantitative proteomics at present. In the past few years, a number of quantitative methods have been developed, which support the fast development in biology research. In this work, we discuss the progress in the stable isotope labeling methods for quantitative proteomics including relative and absolute quantitative proteomics, and then give our opinions on the outlook of proteome quantification methods.

Qualitative versus quantitative methods in psychiatric research.

PubMed

Razafsha, Mahdi; Behforuzi, Hura; Azari, Hassan; Zhang, Zhiqun; Wang, Kevin K; Kobeissy, Firas H; Gold, Mark S

2012-01-01

Qualitative studies are gaining their credibility after a period of being misinterpreted as "not being quantitative." Qualitative method is a broad umbrella term for research methodologies that describe and explain individuals' experiences, behaviors, interactions, and social contexts. In-depth interview, focus groups, and participant observation are among the qualitative methods of inquiry commonly used in psychiatry. Researchers measure the frequency of occurring events using quantitative methods; however, qualitative methods provide a broader understanding and a more thorough reasoning behind the event. Hence, it is considered to be of special importance in psychiatry. Besides hypothesis generation in earlier phases of the research, qualitative methods can be employed in questionnaire design, diagnostic criteria establishment, feasibility studies, as well as studies of attitude and beliefs. Animal models are another area that qualitative methods can be employed, especially when naturalistic observation of animal behavior is important. However, since qualitative results can be researcher's own view, they need to be statistically confirmed, quantitative methods. The tendency to combine both qualitative and quantitative methods as complementary methods has emerged over recent years. By applying both methods of research, scientists can take advantage of interpretative characteristics of qualitative methods as well as experimental dimensions of quantitative methods.

Laboratory evolution of the migratory polymorphism in the sand cricket: combining physiology with quantitative genetics.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2007-01-01

Predicting evolutionary change is the central goal of evolutionary biology because it is the primary means by which we can test evolutionary hypotheses. In this article, we analyze the pattern of evolutionary change in a laboratory population of the wing-dimorphic sand cricket Gryllus firmus resulting from relaxation of selection favoring the migratory (long-winged) morph. Based on a well-characterized trade-off between fecundity and flight capability, we predict that evolution in the laboratory environment should result in a reduction in the proportion of long-winged morphs. We also predict increased fecundity and reduced functionality and weight of the major flight muscles in long-winged females but little change in short-winged (flightless) females. Based on quantitative genetic theory, we predict that the regression equation describing the trade-off between ovary weight and weight of the major flight muscles will show a change in its intercept but not in its slope. Comparisons across generations verify all of these predictions. Further, using values of genetic parameters estimated from previous studies, we show that a quantitative genetic simulation model can account for not only the qualitative changes but also the evolutionary trajectory. These results demonstrate the power of combining quantitative genetic and physiological approaches for understanding the evolution of complex traits.

Quantitative trait locus gene mapping: a new method for locating alcohol response genes.

PubMed

Crabbe, J C

1996-01-01

Alcoholism is a multigenic trait with important non-genetic determinants. Studies with genetic animal models of susceptibility to several of alcohol's effects suggest that several genes contributing modest effects on susceptibility (Quantitative Trait Loci, or QTLs) are important. A new technique of QTL gene mapping has allowed the identification of the location in mouse genome of several such QTLs. The method is described, and the locations of QTLs affecting the acute alcohol withdrawal reaction are described as an example of the method. Verification of these QTLs in ancillary studies is described and the strengths, limitations, and future directions to be pursued are discussed. QTL mapping is a promising method for identifying genes in rodents with the hope of directly extrapolating the results to the human genome. This review is based on a paper presented at the First International Congress of the Latin American Society for Biomedical Research on Alcoholism, Santiago, Chile, November 1994.

[The study of tomato fruit weight quantitative trait locus and its application in genetics teaching].

PubMed

Wang, Hai-yan

2015-08-01

The classical research cases, which have greatly promoted the development of genetics in history, can be combined with the content of courses in genetics teaching to train students' ability of scientific thinking and genetic analysis. The localization and clone of gene controlling tomato fruit weight is a pioneer work in quantitative trait locus (QTL) studies and represents a complete process of QTL research in plants. Application of this integrated case in genetics teaching, which showed a wonderful process of scientific discovery and the fascination of genetic research, has inspired students' interest in genetics and achieved a good teaching effect.

Composition and Quantitation of Microalgal Lipids by ERETIC 1H NMR Method

PubMed Central

Nuzzo, Genoveffa; Gallo, Carmela; d’Ippolito, Giuliana; Cutignano, Adele; Sardo, Angela; Fontana, Angelo

2013-01-01

Accurate characterization of biomass constituents is a crucial aspect of research in the biotechnological application of natural products. Here we report an efficient, fast and reproducible method for the identification and quantitation of fatty acids and complex lipids (triacylglycerols, glycolipids, phospholipids) in microalgae under investigation for the development of functional health products (probiotics, food ingredients, drugs, etc.) or third generation biofuels. The procedure consists of extraction of the biological matrix by modified Folch method and direct analysis of the resulting material by proton nuclear magnetic resonance (1H NMR). The protocol uses a reference electronic signal as external standard (ERETIC method) and allows assessment of total lipid content, saturation degree and class distribution in both high throughput screening of algal collection and metabolic analysis during genetic or culturing studies. As proof of concept, the methodology was applied to the analysis of three microalgal species (Thalassiosira weissflogii, Cyclotella cryptica and Nannochloropsis salina) which drastically differ for the qualitative and quantitative composition of their fatty acid-based lipids. PMID:24084790

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.

PubMed

Pollock, Samuel B; Hu, Amy; Mou, Yun; Martinko, Alexander J; Julien, Olivier; Hornsby, Michael; Ploder, Lynda; Adams, Jarrett J; Geng, Huimin; Müschen, Markus; Sidhu, Sachdev S; Moffat, Jason; Wells, James A

2018-03-13

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states. Copyright © 2018 the Author(s). Published by PNAS.

Uncovering the genetic signature of quantitative trait evolution with replicated time series data.

PubMed

Franssen, S U; Kofler, R; Schlötterer, C

2017-01-01

The genetic architecture of adaptation in natural populations has not yet been resolved: it is not clear to what extent the spread of beneficial mutations (selective sweeps) or the response of many quantitative trait loci drive adaptation to environmental changes. Although much attention has been given to the genomic footprint of selective sweeps, the importance of selection on quantitative traits is still not well studied, as the associated genomic signature is extremely difficult to detect. We propose 'Evolve and Resequence' as a promising tool, to study polygenic adaptation of quantitative traits in evolving populations. Simulating replicated time series data we show that adaptation to a new intermediate trait optimum has three characteristic phases that are reflected on the genomic level: (1) directional frequency changes towards the new trait optimum, (2) plateauing of allele frequencies when the new trait optimum has been reached and (3) subsequent divergence between replicated trajectories ultimately leading to the loss or fixation of alleles while the trait value does not change. We explore these 3 phase characteristics for relevant population genetic parameters to provide expectations for various experimental evolution designs. Remarkably, over a broad range of parameters the trajectories of selected alleles display a pattern across replicates, which differs both from neutrality and directional selection. We conclude that replicated time series data from experimental evolution studies provide a promising framework to study polygenic adaptation from whole-genome population genetics data.

Statistical genetics and evolution of quantitative traits

NASA Astrophysics Data System (ADS)

Neher, Richard A.; Shraiman, Boris I.

2011-10-01

The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach quasilinkage equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parametrized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. Key results of quantitative genetics such as the generalized Fisher’s “fundamental theorem,” along with Wright’s adaptive landscape, are shown to emerge within QLE from the dynamics of the genotype distribution. This is followed by a discussion under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest.

Model-Based Linkage Analysis of a Quantitative Trait.

PubMed

Song, Yeunjoo E; Song, Sunah; Schnell, Audrey H

2017-01-01

Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

Event-specific qualitative and quantitative detection of five genetically modified rice events using a single standard reference molecule.

PubMed

Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Shin, Min-Ki; Moon, Gui-Im; Hong, Jin-Hwan; Kim, Hae-Yeong

2017-07-01

One novel standard reference plasmid, namely pUC-RICE5, was constructed as a positive control and calibrator for event-specific qualitative and quantitative detection of genetically modified (GM) rice (Bt63, Kemingdao1, Kefeng6, Kefeng8, and LLRice62). pUC-RICE5 contained fragments of a rice-specific endogenous reference gene (sucrose phosphate synthase) as well as the five GM rice events. An existing qualitative PCR assay approach was modified using pUC-RICE5 to create a quantitative method with limits of detection correlating to approximately 1-10 copies of rice haploid genomes. In this quantitative PCR assay, the square regression coefficients ranged from 0.993 to 1.000. The standard deviation and relative standard deviation values for repeatability ranged from 0.02 to 0.22 and 0.10% to 0.67%, respectively. The Ministry of Food and Drug Safety (Korea) validated the method and the results suggest it could be used routinely to identify five GM rice events. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

2005-10-01

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Using multiple PCR and CE with chemiluminescence detection for simultaneous qualitative and quantitative analysis of genetically modified organism.

PubMed

Guo, Longhua; Qiu, Bin; Chi, Yuwu; Chen, Guonan

2008-09-01

In this paper, an ultrasensitive CE-CL detection system coupled with a novel double-on-column coaxial flow detection interface was developed for the detection of PCR products. A reliable procedure based on this system had been demonstrated for qualitative and quantitative analysis of genetically modified organism-the detection of Roundup Ready Soy (RRS) samples was presented as an example. The promoter, terminator, function and two reference genes of RRS were amplified with multiplex PCR simultaneously. After that, the multiplex PCR products were labeled with acridinium ester at the 5'-terminal through an amino modification and then analyzed by the proposed CE-CL system. Reproducibility of analysis times and peak heights for the CE-CL analysis were determined to be better than 0.91 and 3.07% (RSD, n=15), respectively, for three consecutive days. It was shown that this method could accurately and qualitatively detect RRS standards and the simulative samples. The evaluation in terms of quantitative analysis of RRS provided by this new method was confirmed by comparing our assay results with those of the standard real-time quantitative PCR (RT-QPCR) using SYBR Green I dyes. The results showed a good coherence between the two methods. This approach demonstrated the possibility for accurate qualitative and quantitative detection of GM plants in a single run.

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

PubMed Central

2012-01-01

Background Proanthocyanidins (PAs), or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL) analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs. Results Multiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1) showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel. Conclusions This study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA traits and different

A new method of linkage analysis using LOD scores for quantitative traits supports linkage of monoamine oxidase activity to D17S250 in the Collaborative Study on the Genetics of Alcoholism pedigrees.

PubMed

Curtis, David; Knight, Jo; Sham, Pak C

2005-09-01

Although LOD score methods have been applied to diseases with complex modes of inheritance, linkage analysis of quantitative traits has tended to rely on non-parametric methods based on regression or variance components analysis. Here, we describe a new method for LOD score analysis of quantitative traits which does not require specification of a mode of inheritance. The technique is derived from the MFLINK method for dichotomous traits. A range of plausible transmission models is constructed, constrained to yield the correct population mean and variance for the trait but differing with respect to the contribution to the variance due to the locus under consideration. Maximized LOD scores under homogeneity and admixture are calculated, as is a model-free LOD score which compares the maximized likelihoods under admixture assuming linkage and no linkage. These LOD scores have known asymptotic distributions and hence can be used to provide a statistical test for linkage. The method has been implemented in a program called QMFLINK. It was applied to data sets simulated using a variety of transmission models and to a measure of monoamine oxidase activity in 105 pedigrees from the Collaborative Study on the Genetics of Alcoholism. With the simulated data, the results showed that the new method could detect linkage well if the true allele frequency for the trait was close to that specified. However, it performed poorly on models in which the true allele frequency was much rarer. For the Collaborative Study on the Genetics of Alcoholism data set only a modest overlap was observed between the results obtained from the new method and those obtained when the same data were analysed previously using regression and variance components analysis. Of interest is that D17S250 produced a maximized LOD score under homogeneity and admixture of 2.6 but did not indicate linkage using the previous methods. However, this region did produce evidence for linkage in a separate data set

Methods for Quantitative Creatinine Determination.

PubMed

Moore, John F; Sharer, J Daniel

2017-04-06

Reliable measurement of creatinine is necessary to assess kidney function, and also to quantitate drug levels and diagnostic compounds in urine samples. The most commonly used methods are based on the Jaffe principal of alkaline creatinine-picric acid complex color formation. However, other compounds commonly found in serum and urine may interfere with Jaffe creatinine measurements. Therefore, many laboratories have made modifications to the basic method to remove or account for these interfering substances. This appendix will summarize the basic Jaffe method, as well as a modified, automated version. Also described is a high performance liquid chromatography (HPLC) method that separates creatinine from contaminants prior to direct quantification by UV absorption. Lastly, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method is described that uses stable isotope dilution to reliably quantify creatinine in any sample. This last approach has been recommended by experts in the field as a means to standardize all quantitative creatinine methods against an accepted reference. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium.

PubMed

Palmer, Nicholette D; Goodarzi, Mark O; Langefeld, Carl D; Wang, Nan; Guo, Xiuqing; Taylor, Kent D; Fingerlin, Tasha E; Norris, Jill M; Buchanan, Thomas A; Xiang, Anny H; Haritunians, Talin; Ziegler, Julie T; Williams, Adrienne H; Stefanovski, Darko; Cui, Jinrui; Mackay, Adrienne W; Henkin, Leora F; Bergman, Richard N; Gao, Xiaoyi; Gauderman, James; Varma, Rohit; Hanis, Craig L; Cox, Nancy J; Highland, Heather M; Below, Jennifer E; Williams, Amy L; Burtt, Noel P; Aguilar-Salinas, Carlos A; Huerta-Chagoya, Alicia; Gonzalez-Villalpando, Clicerio; Orozco, Lorena; Haiman, Christopher A; Tsai, Michael Y; Johnson, W Craig; Yao, Jie; Rasmussen-Torvik, Laura; Pankow, James; Snively, Beverly; Jackson, Rebecca D; Liu, Simin; Nadler, Jerry L; Kandeel, Fouad; Chen, Yii-Der I; Bowden, Donald W; Rich, Stephen S; Raffel, Leslie J; Rotter, Jerome I; Watanabe, Richard M; Wagenknecht, Lynne E

2015-05-01

Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

Quantitative Methods in Psychology: Inevitable and Useless

PubMed Central

Toomela, Aaro

2010-01-01

Science begins with the question, what do I want to know? Science becomes science, however, only when this question is justified and the appropriate methodology is chosen for answering the research question. Research question should precede the other questions; methods should be chosen according to the research question and not vice versa. Modern quantitative psychology has accepted method as primary; research questions are adjusted to the methods. For understanding thinking in modern quantitative psychology, two epistemologies should be distinguished: structural-systemic that is based on Aristotelian thinking, and associative-quantitative that is based on Cartesian–Humean thinking. The first aims at understanding the structure that underlies the studied processes; the second looks for identification of cause–effect relationships between the events with no possible access to the understanding of the structures that underlie the processes. Quantitative methodology in particular as well as mathematical psychology in general, is useless for answering questions about structures and processes that underlie observed behaviors. Nevertheless, quantitative science is almost inevitable in a situation where the systemic-structural basis of behavior is not well understood; all sorts of applied decisions can be made on the basis of quantitative studies. In order to proceed, psychology should study structures; methodologically, constructive experiments should be added to observations and analytic experiments. PMID:21833199

Quantitative methods in psychology: inevitable and useless.

PubMed

Toomela, Aaro

2010-01-01

Science begins with the question, what do I want to know? Science becomes science, however, only when this question is justified and the appropriate methodology is chosen for answering the research question. Research question should precede the other questions; methods should be chosen according to the research question and not vice versa. Modern quantitative psychology has accepted method as primary; research questions are adjusted to the methods. For understanding thinking in modern quantitative psychology, two epistemologies should be distinguished: structural-systemic that is based on Aristotelian thinking, and associative-quantitative that is based on Cartesian-Humean thinking. The first aims at understanding the structure that underlies the studied processes; the second looks for identification of cause-effect relationships between the events with no possible access to the understanding of the structures that underlie the processes. Quantitative methodology in particular as well as mathematical psychology in general, is useless for answering questions about structures and processes that underlie observed behaviors. Nevertheless, quantitative science is almost inevitable in a situation where the systemic-structural basis of behavior is not well understood; all sorts of applied decisions can be made on the basis of quantitative studies. In order to proceed, psychology should study structures; methodologically, constructive experiments should be added to observations and analytic experiments.

DENSITY-DEPENDENT SELECTION ON CONTINUOUS CHARACTERS: A QUANTITATIVE GENETIC MODEL.

PubMed

Tanaka, Yoshinari

1996-10-01

A quantitative genetic model of density-dependent selection is presented and analysed with parameter values obtained from laboratory selection experiments conducted by Mueller and his coworkers. The ecological concept of r- and K-selection is formulated in terms of selection gradients on underlying phenotypic characters that influence the density-dependent measure of fitness. Hence the selection gradients on traits are decomposed into two components, one that changes in the direction to increase r, and one that changes in the direction to increase K. The relative importance of the two components is determined by temporal fluctuations in population density. The evolutionary rate of r and K (per-generation changes in r and K due to the genetic responses of the underlying traits) is also formulated. Numerical simulation has shown that with moderate genetic variances of the underlying characters, r and K can evolve rapidly and the evolutionary rate is influenced by synergistic interaction between characters that contribute to r and K. But strong r-selection can occur only with severe and continuous disturbances of populations so that the population density is kept low enough to prevent K-selection. © 1996 The Society for the Study of Evolution.

Population size is weakly related to quantitative genetic variation and trait differentiation in a stream fish.

PubMed

Wood, Jacquelyn L A; Tezel, Defne; Joyal, Destin; Fraser, Dylan J

2015-09-01

How population size influences quantitative genetic variation and differentiation among natural, fragmented populations remains unresolved. Small, isolated populations might occupy poor quality habitats and lose genetic variation more rapidly due to genetic drift than large populations. Genetic drift might furthermore overcome selection as population size decreases. Collectively, this might result in directional changes in additive genetic variation (VA ) and trait differentiation (QST ) from small to large population size. Alternatively, small populations might exhibit larger variation in VA and QST if habitat fragmentation increases variability in habitat types. We explored these alternatives by investigating VA and QST using nine fragmented populations of brook trout varying 50-fold in census size N (179-8416) and 10-fold in effective number of breeders, Nb (18-135). Across 15 traits, no evidence was found for consistent differences in VA and QST with population size and almost no evidence for increased variability of VA or QST estimates at small population size. This suggests that (i) small populations of some species may retain adaptive potential according to commonly adopted quantitative genetic measures and (ii) populations of varying sizes experience a variety of environmental conditions in nature, however extremely large studies are likely required before any firm conclusions can be made. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

From themes to hypotheses: following up with quantitative methods.

PubMed

Morgan, David L

2015-06-01

One important category of mixed-methods research designs consists of quantitative studies that follow up on qualitative research. In this case, the themes that serve as the results from the qualitative methods generate hypotheses for testing through the quantitative methods. That process requires operationalization to translate the concepts from the qualitative themes into quantitative variables. This article illustrates these procedures with examples that range from simple operationalization to the evaluation of complex models. It concludes with an argument for not only following up qualitative work with quantitative studies but also the reverse, and doing so by going beyond integrating methods within single projects to include broader mutual attention from qualitative and quantitative researchers who work in the same field. © The Author(s) 2015.

Metabolite profiling and quantitative genetics of natural variation for flavonoids in Arabidopsis

PubMed Central

Routaboul, Jean-Marc; Dubos, Christian; Beck, Gilles; Marquis, Catherine; Bidzinski, Przemyslaw; Loudet, Olivier; Lepiniec, Loïc

2012-01-01

Little is known about the range and the genetic bases of naturally occurring variation for flavonoids. Using Arabidopsis thaliana seed as a model, the flavonoid content of 41 accessions and two recombinant inbred line (RIL) sets derived from divergent accessions (Cvi-0×Col-0 and Bay-0×Shahdara) were analysed. These accessions and RILs showed mainly quantitative rather than qualitative changes. To dissect the genetic architecture underlying these differences, a quantitative trait locus (QTL) analysis was performed on the two segregating populations. Twenty-two flavonoid QTLs were detected that accounted for 11–64% of the observed trait variations, only one QTL being common to both RIL sets. Sixteen of these QTLs were confirmed and coarsely mapped using heterogeneous inbred families (HIFs). Three genes, namely TRANSPARENT TESTA (TT)7, TT15, and MYB12, were proposed to underlie their variations since the corresponding mutants and QTLs displayed similar specific flavonoid changes. Interestingly, most loci did not co-localize with any gene known to be involved in flavonoid metabolism. This latter result shows that novel functions have yet to be characterized and paves the way for their isolation. PMID:22442426

A population genetic interpretation of GWAS findings for human quantitative traits

PubMed Central

Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

2018-01-01

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID

Quantitative imaging methods in osteoporosis.

PubMed

Oei, Ling; Koromani, Fjorda; Rivadeneira, Fernando; Zillikens, M Carola; Oei, Edwin H G

2016-12-01

Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are critical in the diagnosis and follow-up of treatment effects in osteoporosis. Prior radiographic vertebral fractures and bone mineral density (BMD) as a quantitative parameter derived from dual-energy X-ray absorptiometry (DXA) are among the strongest known predictors of future osteoporotic fractures. Therefore, current clinical decision making relies heavily on accurate assessment of these imaging features. Further, novel quantitative techniques are being developed to appraise additional characteristics of osteoporosis including three-dimensional bone architecture with quantitative computed tomography (QCT). Dedicated high-resolution (HR) CT equipment is available to enhance image quality. At the other end of the spectrum, by utilizing post-processing techniques such as the trabecular bone score (TBS) information on three-dimensional architecture can be derived from DXA images. Further developments in magnetic resonance imaging (MRI) seem promising to not only capture bone micro-architecture but also characterize processes at the molecular level. This review provides an overview of various quantitative imaging techniques based on different radiological modalities utilized in clinical osteoporosis care and research.

Determination of Mycotoxin Production of Fusarium Species in Genetically Modified Maize Varieties by Quantitative Flow Immunocytometry.

PubMed

Bánáti, Hajnalka; Darvas, Béla; Fehér-Tóth, Szilvia; Czéh, Árpád; Székács, András

2017-02-22

Levels of mycotoxins produced by Fusarium species in genetically modified (GM) and near-isogenic maize, were determined using multi-analyte, microbead-based flow immunocytometry with fluorescence detection, for the parallel quantitative determination of fumonisin B1, deoxynivalenol, zearalenone, T-2, ochratoxin A, and aflatoxin B1. Maize varieties included the genetic events MON 810 and DAS-59122-7 , and their isogenic counterparts. Cobs were artificially infested by F. verticillioides and F. proliferatum conidia, and contained F. graminearum and F. sporotrichoides natural infestation. The production of fumonisin B1 and deoxynivalenol was substantially affected in GM maize lines: F. verticillioides , with the addition of F. graminearum and F. sporotrichoides , produced significantly lower levels of fumonisin B1 (~300 mg·kg -1 ) in DAS-59122-7 than in its isogenic line (~580 mg·kg -1 ), while F. proliferatum , in addition to F. graminearum and F. sporotrichoides , produced significantly higher levels of deoxynivalenol (~18 mg·kg -1 ) in MON 810 than in its isogenic line (~5 mg·kg -1 ). Fusarium verticillioides , with F. graminearum and F. sporotrichoides , produced lower amounts of deoxynivalenol and zearalenone than F. proliferatum , with F. graminearum and F. sporotrichoides . T-2 toxin production remained unchanged when considering the maize variety. The results demonstrate the utility of the Fungi-Plex™ quantitative flow immunocytometry method, applied for the high throughput parallel determination of the target mycotoxins.

Filling the knowledge gap: Integrating quantitative genetics and genomics in graduate education and outreach

USDA-ARS?s Scientific Manuscript database

The genomics revolution provides vital tools to address global food security. Yet to be incorporated into livestock breeding, molecular techniques need to be integrated into a quantitative genetics framework. Within the U.S., with shrinking faculty numbers with the requisite skills, the capacity to ...

Comparison of genetic algorithms with conjugate gradient methods

NASA Technical Reports Server (NTRS)

Bosworth, J. L.; Foo, N. Y.; Zeigler, B. P.

1972-01-01

Genetic algorithms for mathematical function optimization are modeled on search strategies employed in natural adaptation. Comparisons of genetic algorithms with conjugate gradient methods, which were made on an IBM 1800 digital computer, show that genetic algorithms display superior performance over gradient methods for functions which are poorly behaved mathematically, for multimodal functions, and for functions obscured by additive random noise. Genetic methods offer performance comparable to gradient methods for many of the standard functions.

Quantitative Genetic Architecture at Latitudinal Range Boundaries: Reduced Variation but Higher Trait Independence.

PubMed

Paccard, Antoine; Van Buskirk, Josh; Willi, Yvonne

2016-05-01

Species distribution limits are hypothesized to be caused by small population size and limited genetic variation in ecologically relevant traits, but earlier studies have not evaluated genetic variation in multivariate phenotypes. We asked whether populations at the latitudinal edges of the distribution have altered quantitative genetic architecture of ecologically relevant traits compared with midlatitude populations. We calculated measures of evolutionary potential in nine Arabidopsis lyrata populations spanning the latitudinal range of the species in eastern and midwestern North America. Environments at the latitudinal extremes have reduced water availability, and therefore plants were assessed under wet and dry treatments. We estimated genetic variance-covariance (G-) matrices for 10 traits related to size, development, and water balance. Populations at southern and northern distribution edges had reduced levels of genetic variation across traits, but their G-matrices were more spherical; G-matrix orientation was unrelated to latitude. As a consequence, the predicted short-term response to selection was at least as strong in edge populations as in central populations. These results are consistent with genetic drift eroding variation and reducing the effectiveness of correlational selection at distribution margins. We conclude that genetic variation of isolated traits poorly predicts the capacity to evolve in response to multivariate selection and that the response to selection may frequently be greater than expected at species distribution margins because of genetic drift.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

Slater, Anthony T; Cogan, Noel O I; Hayes, Benjamin J; Schultz, Lee; Dale, M Finlay B; Bryan, Glenn J; Forster, John W

2014-11-01

Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

Classification of cassava genotypes based on qualitative and quantitative data.

PubMed

Oliveira, E J; Oliveira Filho, O S; Santos, V S

2015-02-02

We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

Quantitative genetic models of sexual conflict based on interacting phenotypes.

PubMed

Moore, Allen J; Pizzari, Tommaso

2005-05-01

Evolutionary conflict arises between reproductive partners when alternative reproductive opportunities are available. Sexual conflict can generate sexually antagonistic selection, which mediates sexual selection and intersexual coevolution. However, despite intense interest, the evolutionary implications of sexual conflict remain unresolved. We propose a novel theoretical approach to study the evolution of sexually antagonistic phenotypes based on quantitative genetics and the measure of social selection arising from male-female interactions. We consider the phenotype of one sex as both a genetically influenced evolving trait as well as the (evolving) social environment in which the phenotype of the opposite sex evolves. Several important points emerge from our analysis, including the relationship between direct selection on one sex and indirect effects through selection on the opposite sex. We suggest that the proposed approach may be a valuable tool to complement other theoretical approaches currently used to study sexual conflict. Most importantly, our approach highlights areas where additional empirical data can help clarify the role of sexual conflict in the evolutionary process.

Quantitative method of medication system interface evaluation.

PubMed

Pingenot, Alleene Anne; Shanteau, James; Pingenot, James D F

2007-01-01

The objective of this study was to develop a quantitative method of evaluating the user interface for medication system software. A detailed task analysis provided a description of user goals and essential activity. A structural fault analysis was used to develop a detailed description of the system interface. Nurses experienced with use of the system under evaluation provided estimates of failure rates for each point in this simplified fault tree. Means of estimated failure rates provided quantitative data for fault analysis. Authors note that, although failures of steps in the program were frequent, participants reported numerous methods of working around these failures so that overall system failure was rare. However, frequent process failure can affect the time required for processing medications, making a system inefficient. This method of interface analysis, called Software Efficiency Evaluation and Fault Identification Method, provides quantitative information with which prototypes can be compared and problems within an interface identified.

Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

PubMed Central

Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

2007-01-01

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. PMID:17319748

Chemoenzymatic method for glycomics: isolation, identification, and quantitation

PubMed Central

Yang, Shuang; Rubin, Abigail; Eshghi, Shadi Toghi; Zhang, Hui

2015-01-01

Over the past decade, considerable progress has been made with respect to the analytical methods for analysis of glycans from biological sources. Regardless of the specific methods that are used, glycan analysis includes isolation, identification, and quantitation. Derivatization is indispensable to increase their identification. Derivatization of glycans can be performed by permethylation or carbodiimide coupling / esterification. By introducing a fluorophore or chromophore at their reducing end, glycans can be separated by electrophoresis or chromatography. The fluorogenically labeled glycans can be quantitated using fluorescent detection. The recently developed approaches using solid-phase such as glycoprotein immobilization for glycan extraction and on-tissue glycan mass spectrometry imaging demonstrate advantages over methods performed in solution. Derivatization of sialic acids is favorably implemented on the solid support using carbodiimide coupling, and the released glycans can be further modified at the reducing end or permethylated for quantitative analysis. In this review, methods for glycan isolation, identification, and quantitation are discussed. PMID:26390280

Event specific qualitative and quantitative polymerase chain reaction detection of genetically modified MON863 maize based on the 5'-transgene integration sequence.

PubMed

Yang, Litao; Xu, Songci; Pan, Aihu; Yin, Changsong; Zhang, Kewei; Wang, Zhenying; Zhou, Zhigang; Zhang, Dabing

2005-11-30

Because of the genetically modified organisms (GMOs) labeling policies issued in many countries and areas, polymerase chain reaction (PCR) methods were developed for the execution of GMO labeling policies, such as screening, gene specific, construct specific, and event specific PCR detection methods, which have become a mainstay of GMOs detection. The event specific PCR detection method is the primary trend in GMOs detection because of its high specificity based on the flanking sequence of the exogenous integrant. This genetically modified maize, MON863, contains a Cry3Bb1 coding sequence that produces a protein with enhanced insecticidal activity against the coleopteran pest, corn rootworm. In this study, the 5'-integration junction sequence between the host plant DNA and the integrated gene construct of the genetically modified maize MON863 was revealed by means of thermal asymmetric interlaced-PCR, and the specific PCR primers and TaqMan probe were designed based upon the revealed 5'-integration junction sequence; the conventional qualitative PCR and quantitative TaqMan real-time PCR detection methods employing these primers and probes were successfully developed. In conventional qualitative PCR assay, the limit of detection (LOD) was 0.1% for MON863 in 100 ng of maize genomic DNA for one reaction. In the quantitative TaqMan real-time PCR assay, the LOD and the limit of quantification were eight and 80 haploid genome copies, respectively. In addition, three mixed maize samples with known MON863 contents were detected using the established real-time PCR systems, and the ideal results indicated that the established event specific real-time PCR detection systems were reliable, sensitive, and accurate.

High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

PubMed

Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

2017-07-14

Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

Quantitative and Comparative Profiling of Protease Substrates through a Genetically Encoded Multifunctional Photocrosslinker.

PubMed

He, Dan; Xie, Xiao; Yang, Fan; Zhang, Heng; Su, Haomiao; Ge, Yun; Song, Haiping; Chen, Peng R

2017-11-13

A genetically encoded, multifunctional photocrosslinker was developed for quantitative and comparative proteomics. By bearing a bioorthogonal handle and a releasable linker in addition to its photoaffinity warhead, this probe enables the enrichment of transient and low-abundance prey proteins after intracellular photocrosslinking and prey-bait separation, which can be subject to stable isotope dimethyl labeling and mass spectrometry analysis. This quantitative strategy (termed isoCAPP) allowed a comparative proteomic approach to be adopted to identify the proteolytic substrates of an E. coli protease-chaperone dual machinery DegP. Two newly identified substrates were subsequently confirmed by proteolysis experiments. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative genetic analysis of anxiety trait in bipolar disorder.

PubMed

Contreras, J; Hare, E; Chavarría, G; Raventós, H

2018-01-01

Bipolar disorder type I (BPI) affects approximately 1% of the world population. Although genetic influences on bipolar disorder are well established, identification of genes that predispose to the illness has been difficult. Most genetic studies are based on categorical diagnosis. One strategy to overcome this obstacle is the use of quantitative endophenotypes, as has been done for other medical disorders. We studied 619 individuals, 568 participants from 61 extended families and 51 unrelated healthy controls. The sample was 55% female and had a mean age of 43.25 (SD 13.90; range 18-78). Heritability and genetic correlation of the trait scale from the Anxiety State and Trait Inventory (STAI) was computed by using the general linear model (SOLAR package software). we observed that anxiety trait meets the following criteria for an endophenotype of bipolar disorder type I (BPI): 1) association with BPI (individuals with BPI showed the highest trait score (F = 15.20 [5,24], p = 0.009), 2) state-independence confirmed after conducting a test-retest in 321 subjects, 3) co-segregation within families 4) heritability of 0.70 (SE: 0.060), p = 2.33 × 10 -14 and 5) genetic correlation with BPI was 0.20, (SE = 0.17, p = 3.12 × 10 -5 ). Confounding factors such as comorbid disorders and pharmacological treatment could affect the clinical relationship between BPI and anxiety trait. Further research is needed to evaluate if anxiety traits are specially related to BPI in comparison with other traits such as anger, attention or response inhibition deficit, pathological impulsivity or low self-directedness. Anxiety trait is a heritable phenotype that follows a normal distribution when measured not only in subjects with BPI but also in unrelated healthy controls. It could be used as an endophenotype in BPI for the identification of genomic regions with susceptibility genes for this disorder. Published by Elsevier B.V.

Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.).

PubMed

Zhang, Zhen; Shang, Haihong; Shi, Yuzhen; Huang, Long; Li, Junwen; Ge, Qun; Gong, Juwu; Liu, Aiying; Chen, Tingting; Wang, Dan; Wang, Yanling; Palanga, Koffi Kibalou; Muhammad, Jamshed; Li, Weijie; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Song, Weiwu; Cai, Juan; Li, Pengtao; Rashid, Harun or; Gong, Wankui; Yuan, Youlu

2016-04-11

Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

Quantitative Genetic Modeling of the Parental Care Hypothesis for the Evolution of Endothermy

PubMed Central

Bacigalupe, Leonardo D.; Moore, Allen J.; Nespolo, Roberto F.; Rezende, Enrico L.; Bozinovic, Francisco

2017-01-01

There are two heuristic explanations proposed for the evolution of endothermy in vertebrates: a correlated response to selection for stable body temperatures, or as a correlated response to increased activity. Parental care has been suggested as a major driving force in this context given its impact on the parents' activity levels and energy budgets, and in the offspring's growth rates due to food provisioning and controlled incubation temperature. This results in a complex scenario involving multiple traits and transgenerational fitness benefits that can be hard to disentangle, quantify and ultimately test. Here we demonstrate how standard quantitative genetic models of maternal effects can be applied to study the evolution of endothermy, focusing on the interplay between daily energy expenditure (DEE) of the mother and growth rates of the offspring. Our model shows that maternal effects can dramatically exacerbate evolutionary responses to selection in comparison to regular univariate models (breeder's equation). This effect would emerge from indirect selection mediated by maternal effects concomitantly with a positive genetic covariance between DEE and growth rates. The multivariate nature of selection, which could favor a higher DEE, higher growth rates or both, might partly explain how high turnover rates were continuously favored in a self-reinforcing process. Overall, our quantitative genetic analysis provides support for the parental care hypothesis for the evolution of endothermy. We contend that much has to be gained from quantifying maternal and developmental effects on metabolic and thermoregulatory variation during adulthood. PMID:29311952

Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

PubMed

Tufto, Jarle

2015-08-01

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Quantitative genetic correlation between trait and preference supports a sexually selected sperm process

PubMed Central

Simmons, Leigh W.; Kotiaho, Janne S.

2007-01-01

Sperm show patterns of rapid and divergent evolution that are characteristic of sexual selection. Sperm competition has been proposed as an important selective agent in the evolution of sperm morphology. However, several comparative analyses have revealed evolutionary associations between sperm length and female reproductive tract morphology that suggest patterns of male–female coevolution. In the dung beetle Onthophagus taurus, males with short sperm have a fertilization advantage that depends on the size of the female's sperm storage organ, the spermatheca; large spermathecae select for short sperm. Sperm length is heritable and is genetically correlated with male condition. Here we report significant additive genetic variation and heritability for spermatheca size and genetic covariance between spermatheca size and sperm length predicted by both the “good-sperm” and “sexy-sperm” models of postcopulatory female preference. Our data thus provide quantitative genetic support for the role of a sexually selected sperm process in the evolutionary divergence of sperm morphology, in much the same manner as precopulatory female preferences drive the evolutionary divergence of male secondary sexual traits. PMID:17921254

IWGT report on quantitative approaches to genotoxicity risk ...

EPA Pesticide Factsheets

This is the second of two reports from the International Workshops on Genotoxicity Testing (IWGT) Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (the QWG). The first report summarized the discussions and recommendations of the QWG related to the need for quantitative dose–response analysis of genetic toxicology data, the existence and appropriate evaluation of threshold responses, and methods to analyze exposure-response relationships and derive points of departure (PoDs) from which acceptable exposure levels could be determined. This report summarizes the QWG discussions and recommendations regarding appropriate approaches to evaluate exposure-related risks of genotoxic damage, including extrapolation below identified PoDs and across test systems and species. Recommendations include the selection of appropriate genetic endpoints and target tissues, uncertainty factors and extrapolation methods to be considered, the importance and use of information on mode of action, toxicokinetics, metabolism, and exposure biomarkers when using quantitative exposure-response data to determine acceptable exposure levels in human populations or to assess the risk associated with known or anticipated exposures. The empirical relationship between genetic damage (mutation and chromosomal aberration) and cancer in animal models was also examined. It was concluded that there is a general correlation between cancer induction and mutagenic and/or clast

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings

PubMed Central

Sariaslan, A; Larsson, H; Fazel, S

2016-01-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8–10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h2=53–71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30–0.33) than bipolar disorder (r=0.23; 0.21–0.25), and large proportions (51–67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21% 20–22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings.

PubMed

Sariaslan, A; Larsson, H; Fazel, S

2016-09-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8-10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h(2)=53-71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30-0.33) than bipolar disorder (r=0.23; 0.21-0.25), and large proportions (51-67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21%; 20-22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and violence.

Mapcurves: a quantitative method for comparing categorical maps.

Treesearch

William W. Hargrove; M. Hoffman Forrest; Paul F. Hessburg

2006-01-01

We present Mapcurves, a quantitative goodness-of-fit (GOF) method that unambiguously shows the degree of spatial concordance between two or more categorical maps. Mapcurves graphically and quantitatively evaluate the degree of fit among any number of maps and quantify a GOF for each polygon, as well as the entire map. The Mapcurve method indicates a perfect fit even if...

Biology Undergraduates' Misconceptions about Genetic Drift

ERIC Educational Resources Information Center

Andrews, T. M.; Price, R. M.; Mead, L. S.; McElhinny, T. L.; Thanukos, A.; Perez, K. E.; Herreid, C. F.; Terry, D. R.; Lemons, P. P.

2012-01-01

This study explores biology undergraduates' misconceptions about genetic drift. We use qualitative and quantitative methods to describe students' definitions, identify common misconceptions, and examine differences before and after instruction on genetic drift. We identify and describe five overarching categories that include 16 distinct…

Uncertainty of quantitative microbiological methods of pharmaceutical analysis.

PubMed

Gunar, O V; Sakhno, N G

2015-12-30

The total uncertainty of quantitative microbiological methods, used in pharmaceutical analysis, consists of several components. The analysis of the most important sources of the quantitative microbiological methods variability demonstrated no effect of culture media and plate-count techniques in the estimation of microbial count while the highly significant effect of other factors (type of microorganism, pharmaceutical product and individual reading and interpreting errors) was established. The most appropriate method of statistical analysis of such data was ANOVA which enabled not only the effect of individual factors to be estimated but also their interactions. Considering all the elements of uncertainty and combining them mathematically the combined relative uncertainty of the test results was estimated both for method of quantitative examination of non-sterile pharmaceuticals and microbial count technique without any product. These data did not exceed 35%, appropriated for a traditional plate count methods. Copyright © 2015 Elsevier B.V. All rights reserved.

[Effect of non-genetically modified (non-GM) soy varieties on the measured value of GM soy by a quantitative PCR method].

PubMed

Watanabe, Takahiro; Sekino, Ayako; Shiramasa, Yuko; Matsuda, Rieko; Maitani, Tamio

2008-08-01

It is very important to examine the effect of non-genetically modified (non-GM) soy varieties, which constitute the matrix of the testing sample used to quantify GM soy (RRS), on the measured value of RRS by quantitative PCR methods. Therefore, we quantified the amount of RRS in powder-mixed samples containing 1 or 5% RRS prepared by using 10 different varieties of non-GM soy as the matrix. The results revealed that the measured values were not in agreement with the powder-mixing levels and that the extent of the difference depended on the variety of non-GM soy used as the matrix. The yields of DNA extracted differed among the soy varieties. On the other hand, analysis of DNA-mixed samples, that were prepared with the DNAs extracted from RRS and non-GM soy varieties, showed that the measured values of RRS were in agreement with the DNA-mixing levels. These results strongly suggest that the proportions of DNA derived from RRS and non-GM soy were not consistent with the powder-mixing ratio in the case of some non-GM soy varieties used as a matrix, resulting in the discrepancy between the measured values and the powder-mixing levels.

Hybrid wheat: quantitative genetic parameters and consequences for the design of breeding programs.

PubMed

Longin, Carl Friedrich Horst; Gowda, Manje; Mühleisen, Jonathan; Ebmeyer, Erhard; Kazman, Ebrahim; Schachschneider, Ralf; Schacht, Johannes; Kirchhoff, Martin; Zhao, Yusheng; Reif, Jochen Christoph

2013-11-01

Commercial heterosis for grain yield is present in hybrid wheat but long-term competiveness of hybrid versus line breeding depends on the development of heterotic groups to improve hybrid prediction. Detailed knowledge of the amount of heterosis and quantitative genetic parameters are of paramount importance to assess the potential of hybrid breeding. Our objectives were to (1) examine the extent of midparent, better-parent and commercial heterosis in a vast population of 1,604 wheat (Triticum aestivum L.) hybrids and their parental elite inbred lines and (2) discuss the consequences of relevant quantitative parameters for the design of hybrid wheat breeding programs. Fifteen male lines were crossed in a factorial mating design with 120 female lines, resulting in 1,604 of the 1,800 potential single-cross hybrid combinations. The hybrids, their parents, and ten commercial wheat varieties were evaluated in multi-location field experiments for grain yield, plant height, heading time and susceptibility to frost, lodging, septoria tritici blotch, yellow rust, leaf rust, and powdery mildew at up to five locations. We observed that hybrids were superior to the mean of their parents for grain yield (10.7 %) and susceptibility to frost (-7.2 %), leaf rust (-8.4 %) and septoria tritici blotch (-9.3 %). Moreover, 69 hybrids significantly (P < 0.05) outyielded the best commercial inbred line variety underlining the potential of hybrid wheat breeding. The estimated quantitative genetic parameters suggest that the establishment of reciprocal recurrent selection programs is pivotal for a successful long-term hybrid wheat breeding.

Quantitative genetic models of sexual selection by male choice.

PubMed

Nakahashi, Wataru

2008-09-01

There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

Development of an event-specific hydrolysis probe quantitative real-time polymerase chain reaction assay for Embrapa 5.1 genetically modified common bean (Phaseolus vulgaris).

PubMed

Treml, Diana; Venturelli, Gustavo L; Brod, Fábio C A; Faria, Josias C; Arisi, Ana C M

2014-12-10

A genetically modified (GM) common bean event, namely Embrapa 5.1, resistant to the bean golden mosaic virus (BGMV), was approved for commercialization in Brazil. Brazilian regulation for genetically modified organism (GMO) labeling requires that any food containing more than 1% GMO be labeled. The event-specific polymerase chain reaction (PCR) method has been the primary trend for GMO identification and quantitation because of its high specificity based on the flanking sequence. This work reports the development of an event-specific assay, named FGM, for Embrapa 5.1 detection and quantitation by use of SYBR Green or hydrolysis probe. The FGM assay specificity was tested for Embrapa 2.3 event (a noncommercial GM common bean also resistant to BGMV), 46 non-GM common bean varieties, and other crop species including maize, GM maize, soybean, and GM soybean. The FGM assay showed high specificity to detect the Embrapa 5.1 event. Standard curves for the FGM assay presented a mean efficiency of 95% and a limit of detection (LOD) of 100 genome copies in the presence of background DNA. The primers and probe developed are suitable for the detection and quantitation of Embrapa 5.1.

Targeted methods for quantitative analysis of protein glycosylation

PubMed Central

Goldman, Radoslav; Sanda, Miloslav

2018-01-01

Quantification of proteins by LC-MS/MS-MRM has become a standard method with broad projected clinical applicability. MRM quantification of protein modifications is, however, far less utilized, especially in the case of glycoproteins. This review summarizes current methods for quantitative analysis of protein glycosylation with a focus on MRM methods. We describe advantages of this quantitative approach, analytical parameters that need to be optimized to achieve reliable measurements, and point out the limitations. Differences between major classes of N- and O-glycopeptides are described and class-specific glycopeptide assays are demonstrated. PMID:25522218

Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships.

PubMed

Zhang, Qianqian; Guldbrandtsen, Bernt; Calus, Mario P L; Lund, Mogens Sandø; Sahana, Goutam

2016-08-17

There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment.

PubMed

Bourret, A; Garant, D

2017-03-01

Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

Development and application of SINE multilocus and quantitative genetic markers to study oilseed rape (Brassica napus L.) crops.

PubMed

Allnutt, T R; Roper, K; Henry, C

2008-01-23

A genetic marker system based on the S1 Short Interspersed Elements (SINEs) in the important commercial crop, oilseed rape ( Brassica napus L.) has been developed. SINEs provided a successful multilocus, dominant marker system that was capable of clearly delineating winter- and spring-type crop varieties. Sixteen of 20 varieties tested showed unique profiles from the 17 polymorphic SINE markers generated. The 3' or 5' flank region of nine SINE markers were cloned, and DNA was sequenced. In addition, one putative pre-transposition SINE allele was cloned and sequenced. Two SINE flanking sequences were used to design real-time PCR assays. These quantitative SINE assays were applied to study the genetic structure of eight fields of oilseed rape crops. Studied fields were more genetically diverse than expected for the chosen loci (mean H T = 0.23). The spatial distribution of SINE marker frequencies was highly structured in some fields, suggesting locations of volunteer impurities within the crop. In one case, the assay identified a mislabeling of the crop variety. SINE markers were a useful tool for crop genetics, phylogenetics, variety identification, and purity analysis. The use and further application of quantitative, real-time PCR markers are discussed.

DRIFTSEL: an R package for detecting signals of natural selection in quantitative traits.

PubMed

Karhunen, M; Merilä, J; Leinonen, T; Cano, J M; Ovaskainen, O

2013-07-01

Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (DRIFTSEL) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three-spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. DRIFTSEL can also be used to perform usual quantitative genetic analyses in common-garden study designs. © 2013 John Wiley & Sons Ltd.

Revisiting the Quantitative-Qualitative Debate: Implications for Mixed-Methods Research

PubMed Central

SALE, JOANNA E. M.; LOHFELD, LYNNE H.; BRAZIL, KEVIN

2015-01-01

Health care research includes many studies that combine quantitative and qualitative methods. In this paper, we revisit the quantitative-qualitative debate and review the arguments for and against using mixed-methods. In addition, we discuss the implications stemming from our view, that the paradigms upon which the methods are based have a different view of reality and therefore a different view of the phenomenon under study. Because the two paradigms do not study the same phenomena, quantitative and qualitative methods cannot be combined for cross-validation or triangulation purposes. However, they can be combined for complementary purposes. Future standards for mixed-methods research should clearly reflect this recommendation. PMID:26523073

An integrative view of phylogenetic comparative methods: connections to population genetics, community ecology, and paleobiology.

PubMed

Pennell, Matthew W; Harmon, Luke J

2013-06-01

Recent innovations in phylogenetic comparative methods (PCMs) have spurred a renaissance of research into the causes and consequences of large-scale patterns of biodiversity. In this paper, we review these advances. We also highlight the potential of comparative methods to integrate across fields and focus on three examples where such integration might be particularly valuable: quantitative genetics, community ecology, and paleobiology. We argue that PCMs will continue to be a key set of tools in evolutionary biology, shedding new light on how evolutionary processes have shaped patterns of biodiversity through deep time. © 2013 New York Academy of Sciences.

Mathematical modelling and quantitative methods.

PubMed

Edler, L; Poirier, K; Dourson, M; Kleiner, J; Mileson, B; Nordmann, H; Renwick, A; Slob, W; Walton, K; Würtzen, G

2002-01-01

The present review reports on the mathematical methods and statistical techniques presently available for hazard characterisation. The state of the art of mathematical modelling and quantitative methods used currently for regulatory decision-making in Europe and additional potential methods for risk assessment of chemicals in food and diet are described. Existing practices of JECFA, FDA, EPA, etc., are examined for their similarities and differences. A framework is established for the development of new and improved quantitative methodologies. Areas for refinement, improvement and increase of efficiency of each method are identified in a gap analysis. Based on this critical evaluation, needs for future research are defined. It is concluded from our work that mathematical modelling of the dose-response relationship would improve the risk assessment process. An adequate characterisation of the dose-response relationship by mathematical modelling clearly requires the use of a sufficient number of dose groups to achieve a range of different response levels. This need not necessarily lead to an increase in the total number of animals in the study if an appropriate design is used. Chemical-specific data relating to the mode or mechanism of action and/or the toxicokinetics of the chemical should be used for dose-response characterisation whenever possible. It is concluded that a single method of hazard characterisation would not be suitable for all kinds of risk assessments, and that a range of different approaches is necessary so that the method used is the most appropriate for the data available and for the risk characterisation issue. Future refinements to dose-response characterisation should incorporate more clearly the extent of uncertainty and variability in the resulting output.

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

DOE PAGES

Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

2005-01-01

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

A quantitative genetic analysis of hibernation emergence date in a wild population of Columbian ground squirrels.

PubMed

Lane, J E; Kruuk, L E B; Charmantier, A; Murie, J O; Coltman, D W; Buoro, M; Raveh, S; Dobson, F S

2011-09-01

The life history schedules of wild organisms have long attracted scientific interest, and, in light of ongoing climate change, an understanding of their genetic and environmental underpinnings is increasingly becoming of applied concern. We used a multi-generation pedigree and detailed phenotypic records, spanning 18 years, to estimate the quantitative genetic influences on the timing of hibernation emergence in a wild population of Columbian ground squirrels (Urocitellus columbianus). Emergence date was significantly heritable [h(2) = 0.22 ± 0.05 (in females) and 0.34 ± 0.14 (in males)], and there was a positive genetic correlation (r(G) = 0.76 ± 0.22) between male and female emergence dates. In adult females, the heritabilities of body mass at emergence and oestrous date were h(2) = 0.23 ± 0.09 and h(2) = 0.18 ± 0.12, respectively. The date of hibernation emergence has been hypothesized to have evolved so as to synchronize subsequent reproduction with upcoming peaks in vegetation abundance. In support of this hypothesis, although levels of phenotypic variance in emergence date were higher than oestrous date, there was a highly significant genetic correlation between the two (r(G) = 0.98 ± 0.01). Hibernation is a prominent feature in the annual cycle of many small mammals, but our understanding of its influences lags behind that for phenological traits in many other taxa. Our results provide the first insight into its quantitative genetic influences and thus help contribute to a more general understanding of its evolutionary significance. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Detection methods and performance criteria for genetically modified organisms.

PubMed

Bertheau, Yves; Diolez, Annick; Kobilinsky, André; Magin, Kimberly

2002-01-01

Detection methods for genetically modified organisms (GMOs) are necessary for many applications, from seed purity assessment to compliance of food labeling in several countries. Numerous analytical methods are currently used or under development to support these needs. The currently used methods are bioassays and protein- and DNA-based detection protocols. To avoid discrepancy of results between such largely different methods and, for instance, the potential resulting legal actions, compatibility of the methods is urgently needed. Performance criteria of methods allow evaluation against a common standard. The more-common performance criteria for detection methods are precision, accuracy, sensitivity, and specificity, which together specifically address other terms used to describe the performance of a method, such as applicability, selectivity, calibration, trueness, precision, recovery, operating range, limit of quantitation, limit of detection, and ruggedness. Performance criteria should provide objective tools to accept or reject specific methods, to validate them, to ensure compatibility between validated methods, and be used on a routine basis to reject data outside an acceptable range of variability. When selecting a method of detection, it is also important to consider its applicability, its field of applications, and its limitations, by including factors such as its ability to detect the target analyte in a given matrix, the duration of the analyses, its cost effectiveness, and the necessary sample sizes for testing. Thus, the current GMO detection methods should be evaluated against a common set of performance criteria.

Decay Of Bacterial Pathogens, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure-Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria (FIB), and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manure-amended agricultural soils. Known concentrations of transformed green...

Decay Of Bacterial Pathogen, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria, and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manre-amended agricultural soils. Known concentrations of transformed green fluore...

Quantitative PCR for Genetic Markers of Human Fecal Pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantificationapproach. We report the development of quantitative PCR assays for quantification of two recently described human-...

Genetic variation affecting host-parasite interactions: major-effect quantitative trait loci affect the transmission of sigma virus in Drosophila melanogaster.

PubMed

Bangham, Jenny; Knott, Sara A; Kim, Kang-Wook; Young, Robert S; Jiggins, Francis M

2008-09-01

In natural populations, genetic variation affects resistance to disease. Whether that genetic variation comprises lots of small-effect polymorphisms or a small number of large-effect polymorphisms has implications for adaptation, selection and how genetic variation is maintained in populations. Furthermore, how much genetic variation there is, and the genes that underlie this variation, affects models of co-evolution between parasites and their hosts. We are studying the genetic variation that affects the resistance of Drosophila melanogaster to its natural pathogen--the vertically transmitted sigma virus. We have carried out three separate quantitative trait locus mapping analyses to map gene variants on the second chromosome that cause variation in the rate at which males transmit the infection to their offspring. All three crosses identified a locus in a similar chromosomal location that causes a large drop in the rate at which the virus is transmitted. We also found evidence for an additional smaller-effect quantitative trait locus elsewhere on the chromosome. Our data, together with previous experiments on the sigma virus and parasitoid wasps, indicate that the resistance of D. melanogaster to co-evolved pathogens is controlled by a limited number of major-effect polymorphisms.

Quantitative PCR for genetic markers of human fecal pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantification approach. We report the development of quantitative PCR assays for enumeration of two recently described hum...

Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development

PubMed Central

Pires, Nuno D.; Bemer, Marian; Müller, Lena M.; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

2016-01-01

Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict. PMID:26811909

Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

PubMed

Pires, Nuno D; Bemer, Marian; Müller, Lena M; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

2016-01-01

Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

An Quantitative Analysis Method Of Trabecular Pattern In A Bone

NASA Astrophysics Data System (ADS)

Idesawa, Masanor; Yatagai, Toyohiko

1982-11-01

Orientation and density of trabecular pattern observed in a bone is closely related to its mechanical properties and deseases of a bone are appeared as changes of orientation and/or density distrbution of its trabecular patterns. They have been treated from a qualitative point of view so far because quantitative analysis method has not be established. In this paper, the authors proposed and investigated some quantitative analysis methods of density and orientation of trabecular patterns observed in a bone. These methods can give an index for evaluating orientation of trabecular pattern quantitatively and have been applied to analyze trabecular pattern observed in a head of femur and their availabilities are confirmed. Key Words: Index of pattern orientation, Trabecular pattern, Pattern density, Quantitative analysis

Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

PubMed

Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

2015-10-01

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

[Reconstituting evaluation methods based on both qualitative and quantitative paradigms].

PubMed

Miyata, Hiroaki; Okubo, Suguru; Yoshie, Satoru; Kai, Ichiro

2011-01-01

Debate about the relationship between quantitative and qualitative paradigms is often muddled and confusing and the clutter of terms and arguments has resulted in the concepts becoming obscure and unrecognizable. In this study we conducted content analysis regarding evaluation methods of qualitative healthcare research. We extracted descriptions on four types of evaluation paradigm (validity/credibility, reliability/credibility, objectivity/confirmability, and generalizability/transferability), and classified them into subcategories. In quantitative research, there has been many evaluation methods based on qualitative paradigms, and vice versa. Thus, it might not be useful to consider evaluation methods of qualitative paradigm are isolated from those of quantitative methods. Choosing practical evaluation methods based on the situation and prior conditions of each study is an important approach for researchers.

Genetic background effects in quantitative genetics: gene-by-system interactions.

PubMed

Sardi, Maria; Gasch, Audrey P

2018-04-11

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.

Validation and application of quantitative PCR assays using host-specific Bacteroidales genetic markers for swine fecal pollution tracking.

PubMed

Fan, Lihua; Shuai, Jiangbing; Zeng, Ruoxue; Mo, Hongfei; Wang, Suhua; Zhang, Xiaofeng; He, Yongqiang

2017-12-01

Genome fragment enrichment (GFE) method was applied to identify host-specific bacterial genetic markers that differ among different fecal metagenomes. To enrich for swine-specific DNA fragments, swine fecal DNA composite (n = 34) was challenged against a DNA composite consisting of cow, human, goat, sheep, chicken, duck and goose fecal DNA extracts (n = 83). Bioinformatic analyses of 384 non-redundant swine enriched metagenomic sequences indicated a preponderance of Bacteroidales-like regions predicted to encode metabolism-associated, cellular processes and information storage and processing. After challenged against fecal DNA extracted from different animal sources, four sequences from the clone libraries targeting two Bacteroidales- (genes 1-38 and 3-53), a Clostridia- (gene 2-109) as well as a Bacilli-like sequence (gene 2-95), respectively, showed high specificity to swine feces based on PCR analysis. Host-specificity and host-sensitivity analysis confirmed that oligonucleotide primers and probes capable of annealing to select Bacteroidales-like sequences (1-38 and 3-53) exhibited high specificity (>90%) in quantitative PCR assays with 71 fecal DNAs from non-target animal sources. The two assays also demonstrated broad distributions of corresponding genetic markers (>94% positive) among 72 swine feces. After evaluation with environmental water samples from different areas, swine-targeted assays based on two Bacteroidales-like GFE sequences appear to be suitable quantitative tracing tools for swine fecal pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

Quantitative mass spectrometry methods for pharmaceutical analysis

PubMed Central

Loos, Glenn; Van Schepdael, Ann

2016-01-01

Quantitative pharmaceutical analysis is nowadays frequently executed using mass spectrometry. Electrospray ionization coupled to a (hybrid) triple quadrupole mass spectrometer is generally used in combination with solid-phase extraction and liquid chromatography. Furthermore, isotopically labelled standards are often used to correct for ion suppression. The challenges in producing sensitive but reliable quantitative data depend on the instrumentation, sample preparation and hyphenated techniques. In this contribution, different approaches to enhance the ionization efficiencies using modified source geometries and improved ion guidance are provided. Furthermore, possibilities to minimize, assess and correct for matrix interferences caused by co-eluting substances are described. With the focus on pharmaceuticals in the environment and bioanalysis, different separation techniques, trends in liquid chromatography and sample preparation methods to minimize matrix effects and increase sensitivity are discussed. Although highly sensitive methods are generally aimed for to provide automated multi-residue analysis, (less sensitive) miniaturized set-ups have a great potential due to their ability for in-field usage. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644982

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.

PubMed

Chavez, Juan D; Eng, Jimmy K; Schweppe, Devin K; Cilia, Michelle; Rivera, Keith; Zhong, Xuefei; Wu, Xia; Allen, Terrence; Khurgel, Moshe; Kumar, Akhilesh; Lampropoulos, Athanasios; Larsson, Mårten; Maity, Shuvadeep; Morozov, Yaroslav; Pathmasiri, Wimal; Perez-Neut, Mathew; Pineyro-Ruiz, Coriness; Polina, Elizabeth; Post, Stephanie; Rider, Mark; Tokmina-Roszyk, Dorota; Tyson, Katherine; Vieira Parrine Sant'Ana, Debora; Bruce, James E

2016-01-01

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

A Spectral Method for Color Quantitation of a Protein Drug Solution.

PubMed

Swartz, Trevor E; Yin, Jian; Patapoff, Thomas W; Horst, Travis; Skieresz, Susan M; Leggett, Gordon; Morgan, Charles J; Rahimi, Kimia; Marhoul, Joseph; Kabakoff, Bruce

2016-01-01

Color is an important quality attribute for biotherapeutics. In the biotechnology industry, a visual method is most commonly utilized for color characterization of liquid drug protein solutions. The color testing method is used for both batch release and on stability testing for quality control. Using that method, an analyst visually determines the color of the sample by choosing the closest matching European Pharmacopeia reference color solution. The requirement to judge the best match makes it a subjective method. Furthermore, the visual method does not capture data on hue or chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we describe a quantitative method for color determination that greatly reduces the variability in measuring color and allows for a more precise understanding of color differences. Following color industry standards established by International Commission on Illumination, this method converts a protein solution's visible absorption spectra to L*a*b* color space. Color matching is achieved within the L*a*b* color space, a practice that is already widely used in other industries. The work performed here is to facilitate the adoption and transition for the traditional visual assessment method to a quantitative spectral method. We describe here the algorithm used such that the quantitative spectral method correlates with the currently used visual method. In addition, we provide the L*a*b* values for the European Pharmacopeia reference color solutions required for the quantitative method. We have determined these L*a*b* values by gravimetrically preparing and measuring multiple lots of the reference color solutions. We demonstrate that the visual assessment and the quantitative spectral method are comparable using both low- and high-concentration antibody solutions and solutions with varying turbidity. In the biotechnology industry, a visual

Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

PubMed Central

Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.

2010-01-01

The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

Quantitative analysis of fracture surface by roughness and fractal method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, X.W.; Tian, J.F.; Kang, Y.

1995-09-01

In recent years there has been extensive research and great development in Quantitative Fractography, which acts as an integral part of fractographic analysis. A prominent technique for studying the fracture surface is based on fracture profile generation and the major means for characterizing the profile quantitatively are roughness and fractal methods. By this way, some quantitative indexes such as the roughness parameters R{sub L} for profile and R{sub S} for surface, fractal dimensions D{sub L} for profile and D{sub S} for surface can be measured. Given the relationships between the indexes and the mechanical properties of materials, it is possiblemore » to achieve the goal of protecting materials from fracture. But, as the case stands, the theory and experimental technology of quantitative fractography are still imperfect and remain to be studied further. Recently, Gokhale and Underwood et al have proposed an assumption-free method for estimating the surface roughness by vertically sectioning the fracture surface with sections at an angle of 120 deg with each other, which could be expressed as follows: R{sub S} = {ovr R{sub L}{center_dot}{Psi}} where {Psi} is the profile structure factor. This method is based on the classical sterological principles and verified with the aid of computer simulations for some ruled surfaces. The results are considered to be applicable to fracture surfaces with any arbitrary complexity and anisotropy. In order to extend the detail applications to this method in quantitative fractography, the authors made a study on roughness and fractal methods dependent on this method by performing quantitative measurements on some typical low-temperature impact fractures.« less

Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction: application to 35S in maize.

PubMed

Cankar, Katarina; Chauvensy-Ancel, Valérie; Fortabat, Marie-Noelle; Gruden, Kristina; Kobilinsky, André; Zel, Jana; Bertheau, Yves

2008-05-15

Detection of nonauthorized genetically modified organisms (GMOs) has always presented an analytical challenge because the complete sequence data needed to detect them are generally unavailable although sequence similarity to known GMOs can be expected. A new approach, differential quantitative polymerase chain reaction (PCR), for detection of nonauthorized GMOs is presented here. This method is based on the presence of several common elements (e.g., promoter, genes of interest) in different GMOs. A statistical model was developed to study the difference between the number of molecules of such a common sequence and the number of molecules identifying the approved GMO (as determined by border-fragment-based PCR) and the donor organism of the common sequence. When this difference differs statistically from zero, the presence of a nonauthorized GMO can be inferred. The interest and scope of such an approach were tested on a case study of different proportions of genetically modified maize events, with the P35S promoter as the Cauliflower Mosaic Virus common sequence. The presence of a nonauthorized GMO was successfully detected in the mixtures analyzed and in the presence of (donor organism of P35S promoter). This method could be easily transposed to other common GMO sequences and other species and is applicable to other detection areas such as microbiology.

Studying learning in the healthcare setting: the potential of quantitative diary methods.

PubMed

Ciere, Yvette; Jaarsma, Debbie; Visser, Annemieke; Sanderman, Robbert; Snippe, Evelien; Fleer, Joke

2015-08-01

Quantitative diary methods are longitudinal approaches that involve the repeated measurement of aspects of peoples' experience of daily life. In this article, we outline the main characteristics and applications of quantitative diary methods and discuss how their use may further research in the field of medical education. Quantitative diary methods offer several methodological advantages, such as measuring aspects of learning with great detail, accuracy and authenticity. Moreover, they enable researchers to study how and under which conditions learning in the health care setting occurs and in which way learning can be promoted. Hence, quantitative diary methods may contribute to theory development and the optimization of teaching methods in medical education.

Methods for genetic transformation of filamentous fungi.

PubMed

Li, Dandan; Tang, Yu; Lin, Jun; Cai, Weiwen

2017-10-03

Filamentous fungi have been of great interest because of their excellent ability as cell factories to manufacture useful products for human beings. The development of genetic transformation techniques is a precondition that enables scientists to target and modify genes efficiently and may reveal the function of target genes. The method to deliver foreign nucleic acid into cells is the sticking point for fungal genome modification. Up to date, there are some general methods of genetic transformation for fungi, including protoplast-mediated transformation, Agrobacterium-mediated transformation, electroporation, biolistic method and shock-wave-mediated transformation. This article reviews basic protocols and principles of these transformation methods, as well as their advantages and disadvantages.

Quantitative genetic analysis of cellular adhesion molecules: the Fels Longitudinal Study.

PubMed

Lee, Miryoung; Czerwinski, Stefan A; Choh, Audrey C; Demerath, Ellen W; Sun, Shumei S; Chumlea, Wm C; Towne, Bradford; Siervogel, Roger M

2006-03-01

Circulating concentrations of inflammatory markers predict cardiovascular disease (CVD) risk and are closely associated with obesity. However, little is known concerning genetic influences on serum levels of inflammatory markers. In this study, we estimated the heritability (h2) of soluble cellular adhesion molecule (sCAM) concentrations and examined the correlational architecture between different sCAMs. The study population included 234 men and 270 women aged 18-76 years, belonging to 121 families participating in the Fels Longitudinal Study. Serum levels of soluble intercellular adhesion molecule-1 (sICAM-1), vascular cell adhesion molecule-1 (sVCAM-1), E-selectin (sESEL-1) and P-selectin (sPSEL-1) were assayed using commercially available kits. A variance components-based maximum likelihood method was used to estimate the h2 of the different serum inflammatory markers while simultaneously adjusting for the effects of known CVD risk factors, such as age and smoking. Additionally, we used bivariate extensions of these methods to estimate genetic and random environmental correlations among sCAMs. Levels of sCAMs were significantly heritable: h2=0.24+/-0.10 for sICAM-1, h2=0.22+/-0.10 for sVCAM-1, h2=0.50+/-0.11 for sESEL-1, and h2=0.46+/-0.10 for sPSEL-1. In addition, a significant genetic correlation (rho(G)=0.63) was found between sICAM-1 and sVCAM-1 indicating some degree of shared genetic control. In the Fels Longitudinal Study, the levels of four sCAMs are significantly influenced by genetic effects, and sICAM-1 shares a common genetic background with sVCAM-1.

Physical methods for genetic plant transformation

NASA Astrophysics Data System (ADS)

Rivera, Ana Leonor; Gómez-Lim, Miguel; Fernández, Francisco; Loske, Achim M.

2012-09-01

Production of transgenic plants is a routine process for many crop species. Transgenes are introduced into plants to confer novel traits such as improved nutritional qualities, tolerance to pollutants, resistance to pathogens and for studies of plant metabolism. Nowadays, it is possible to insert genes from plants evolutionary distant from the host plant, as well as from fungi, viruses, bacteria and even animals. Genetic transformation requires penetration of the transgene through the plant cell wall, facilitated by biological or physical methods. The objective of this article is to review the state of the art of the physical methods used for genetic plant transformation and to describe the basic physics behind them.

Comparative Evaluation of Quantitative Test Methods for Gases on a Hard Surface

DTIC Science & Technology

2017-02-01

COMPARATIVE EVALUATION OF QUANTITATIVE TEST METHODS FOR GASES ON A HARD SURFACE ECBC-TR-1426 Vipin Rastogi...1 COMPARATIVE EVALUATION OF QUANTITATIVE TEST METHODS FOR GASES ON A HARD SURFACE 1. INTRODUCTION Members of the U.S. Environmental...Generator 4 2.4 Experimental Design Each quantitative method was performed three times on three consecutive days. For the CD runs, three

Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants.

PubMed

Quenouille, J; Paulhiac, E; Moury, B; Palloix, A

2014-06-01

The combination of major resistance genes with quantitative resistance factors is hypothesized as a promising breeding strategy to preserve the durability of resistant cultivar, as recently observed in different pathosystems. Using the pepper (Capsicum annuum)/Potato virus Y (PVY, genus Potyvirus) pathosystem, we aimed at identifying plant genetic factors directly affecting the frequency of virus adaptation to the major resistance gene pvr2(3) and at comparing them with genetic factors affecting quantitative resistance. The resistance breakdown frequency was a highly heritable trait (h(2)=0.87). Four loci including additive quantitative trait loci (QTLs) and epistatic interactions explained together 70% of the variance of pvr2(3) breakdown frequency. Three of the four QTLs controlling pvr2(3) breakdown frequency were also involved in quantitative resistance, strongly suggesting that QTLs controlling quantitative resistance have a pleiotropic effect on the durability of the major resistance gene. With the first mapping of QTLs directly affecting resistance durability, this study provides a rationale for sustainable resistance breeding. Surprisingly, a genetic trade-off was observed between the durability of PVY resistance controlled by pvr2(3) and the spectrum of the resistance against different potyviruses. This trade-off seemed to have been resolved by the combination of minor-effect durability QTLs under long-term farmer selection.

Sample normalization methods in quantitative metabolomics.

PubMed

Wu, Yiman; Li, Liang

2016-01-22

To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. Copyright © 2015 Elsevier B.V. All rights reserved.

Electric Field Quantitative Measurement System and Method

NASA Technical Reports Server (NTRS)

Generazio, Edward R. (Inventor)

2016-01-01

A method and system are provided for making a quantitative measurement of an electric field. A plurality of antennas separated from one another by known distances are arrayed in a region that extends in at least one dimension. A voltage difference between at least one selected pair of antennas is measured. Each voltage difference is divided by the known distance associated with the selected pair of antennas corresponding thereto to generate a resulting quantity. The plurality of resulting quantities defined over the region quantitatively describe an electric field therein.

A functional–structural model of rice linking quantitative genetic information with morphological development and physiological processes

PubMed Central

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-01-01

Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. PMID:21247905

Distance-based microfluidic quantitative detection methods for point-of-care testing.

PubMed

Tian, Tian; Li, Jiuxing; Song, Yanling; Zhou, Leiji; Zhu, Zhi; Yang, Chaoyong James

2016-04-07

Equipment-free devices with quantitative readout are of great significance to point-of-care testing (POCT), which provides real-time readout to users and is especially important in low-resource settings. Among various equipment-free approaches, distance-based visual quantitative detection methods rely on reading the visual signal length for corresponding target concentrations, thus eliminating the need for sophisticated instruments. The distance-based methods are low-cost, user-friendly and can be integrated into portable analytical devices. Moreover, such methods enable quantitative detection of various targets by the naked eye. In this review, we first introduce the concept and history of distance-based visual quantitative detection methods. Then, we summarize the main methods for translation of molecular signals to distance-based readout and discuss different microfluidic platforms (glass, PDMS, paper and thread) in terms of applications in biomedical diagnostics, food safety monitoring, and environmental analysis. Finally, the potential and future perspectives are discussed.

[A new method of processing quantitative PCR data].

PubMed

Ke, Bing-Shen; Li, Guang-Yun; Chen, Shi-Min; Huang, Xiang-Yan; Chen, Ying-Jian; Xu, Jun

2003-05-01

Today standard PCR can't satisfy the need of biotechnique development and clinical research any more. After numerous dynamic research, PE company found there is a linear relation between initial template number and cycling time when the accumulating fluorescent product is detectable.Therefore,they developed a quantitative PCR technique to be used in PE7700 and PE5700. But the error of this technique is too great to satisfy the need of biotechnique development and clinical research. A better quantitative PCR technique is needed. The mathematical model submitted here is combined with the achievement of relative science,and based on the PCR principle and careful analysis of molecular relationship of main members in PCR reaction system. This model describes the function relation between product quantity or fluorescence intensity and initial template number and other reaction conditions, and can reflect the accumulating rule of PCR product molecule accurately. Accurate quantitative PCR analysis can be made use this function relation. Accumulated PCR product quantity can be obtained from initial template number. Using this model to do quantitative PCR analysis,result error is only related to the accuracy of fluorescence intensity or the instrument used. For an example, when the fluorescence intensity is accurate to 6 digits and the template size is between 100 to 1,000,000, the quantitative result accuracy will be more than 99%. The difference of result error is distinct using same condition,same instrument but different analysis method. Moreover,if the PCR quantitative analysis system is used to process data, it will get result 80 times of accuracy than using CT method.

Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

Cancer.gov

In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

PubMed

Saito, Akira; Numata, Yasushi; Hamada, Takuya; Horisawa, Tomoyoshi; Cosatto, Eric; Graf, Hans-Peter; Kuroda, Masahiko; Yamamoto, Yoichiro

2016-01-01

Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience. Such features include pleomorphism and heterogeneity. In this paper, we propose a method for the objective measurement of pleomorphism and heterogeneity, using the cell-level co-occurrence matrix. Our method is based on the widely used Gray-level co-occurrence matrix (GLCM), where relations between neighboring pixel intensity levels are captured into a co-occurrence matrix, followed by the application of analysis functions such as Haralick features. In the pathological tissue image, through image processing techniques, each nucleus can be measured and each nucleus has its own measureable features like nucleus size, roundness, contour length, intra-nucleus texture data (GLCM is one of the methods). In GLCM each nucleus in the tissue image corresponds to one pixel. In this approach the most important point is how to define the neighborhood of each nucleus. We define three types of neighborhoods of a nucleus, then create the co-occurrence matrix and apply Haralick feature functions. In each image pleomorphism and heterogeneity are then determined quantitatively. For our method, one pixel corresponds to one nucleus feature, and we therefore named our method Cell Feature Level Co-occurrence Matrix (CFLCM). We tested this method for several nucleus features. CFLCM is showed as a useful quantitative method for pleomorphism and heterogeneity on histopathological image

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Comparison of genetic algorithm methods for fuel management optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeChaine, M.D.; Feltus, M.A.

1995-12-31

The CIGARO system was developed for genetic algorithm fuel management optimization. Tests are performed to find the best fuel location swap mutation operator probability and to compare genetic algorithm to a truly random search method. Tests showed the fuel swap probability should be between 0% and 10%, and a 50% definitely hampered the optimization. The genetic algorithm performed significantly better than the random search method, which did not even satisfy the peak normalized power constraint.

The influence of genetic drift and selection on quantitative traits in a plant pathogenic fungus.

PubMed

Stefansson, Tryggvi S; McDonald, Bruce A; Willi, Yvonne

2014-01-01

Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55-0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.

The Consortium on the Genetics of Endophenotypes in Schizophrenia: Model Recruitment, Assessment, and Endophenotyping Methods for a Multisite Collaboration

PubMed Central

Calkins, Monica E.; Dobie, Dorcas J.; Cadenhead, Kristin S.; Olincy, Ann; Freedman, Robert; Green, Michael F.; Greenwood, Tiffany A.; Gur, Raquel E.; Gur, Ruben C.; Light, Gregory A.; Mintz, Jim; Nuechterlein, Keith H.; Radant, Allen D.; Schork, Nicholas J.; Seidman, Larry J.; Siever, Larry J.; Silverman, Jeremy M.; Stone, William S.; Swerdlow, Neal R.; Tsuang, Debby W.; Tsuang, Ming T.; Turetsky, Bruce I.; Braff, David L.

2007-01-01

Background: The Consortium on the Genetics of Schizophrenia (COGS) is an ongoing, National Institute of Mental Health–funded, 7-site collaboration investigating the occurrence and genetic architecture of quantitative endophenotypes related to schizophrenia. The purpose of this article is to provide a description of the COGS structure and methods, including participant recruitment and assessment. Methods: The hypothesis-driven recruitment strategy ascertains families that include a proband with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnosis of schizophrenia, and at least one unaffected full sibling available for genotyping and endophenotyping, along with parents available for genotyping and (optional depending on age) endophenotyping. The family structure is selected to provide contrast in quantitative endophenotypic traits and thus to maximize the power of the planned genetic analyses. Probands are recruited from many sources including clinician referrals, local National Alliance for the Mentally Ill chapters, and advertising via the media. All participants undergo a standardized protocol that includes clinical characterization, a blood draw for genotyping, and endophenotype assessments (P50 suppression, prepulse inhibition, antisaccade performance, continuous performance tasks, letter-number span, verbal memory, and a computerized neurocognitive battery). Investigators participate in weekly teleconferences to coordinate and evaluate recruitment, clinical assessment, endophenotyping, and continuous quality control of data gathering and analyses. Data integrity is maintained through use of a highly quality-assured, centralized web-based database. Results: As of February 2006, 355 families have been enrolled and 688 participants have been endophenotyped, including schizophrenia probands (n = 154, M:F = 110:44), first-degree biological relatives (n = 343, M:F = 151:192), and community comparison subjects (n = 191, M:F = 81

Advancing the study of violence against women using mixed methods: integrating qualitative methods into a quantitative research program.

PubMed

Testa, Maria; Livingston, Jennifer A; VanZile-Tamsen, Carol

2011-02-01

A mixed methods approach, combining quantitative with qualitative data methods and analysis, offers a promising means of advancing the study of violence. Integrating semi-structured interviews and qualitative analysis into a quantitative program of research on women's sexual victimization has resulted in valuable scientific insight and generation of novel hypotheses for testing. This mixed methods approach is described and recommendations for integrating qualitative data into quantitative research are provided.

Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

PubMed Central

Hurme, P; Sillanpää, M J; Arjas, E; Repo, T; Savolainen, O

2000-01-01

We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect. PMID:11063704

Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

PubMed

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2013-11-01

Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Entering the second century of maize quantitative genetics

USDA-ARS?s Scientific Manuscript database

Maize is the most widely grown cereal in the world. In addition to its role in global agriculture, it has also long served as a model organism for genetic research. Maize stands at a genetic crossroads, as it has access to all the tools available for plant genetics but exhibits a genetic architectur...

Quantitative genetic analysis of the bTB diagnostic single intradermal comparative cervical test (SICCT).

PubMed

Tsairidou, Smaragda; Brotherstone, Susan; Coffey, Mike; Bishop, Stephen C; Woolliams, John A

2016-11-24

Bovine tuberculosis (bTB) is a disease of significant economic importance and is a persistent animal health problem with implications for public health worldwide. Control of bTB in the UK has relied on diagnosis through the single intradermal comparative cervical test (SICCT). However, limitations in the sensitivity of this test hinder successful eradication and the control of bTB remains a major challenge. Genetic selection for cattle that are more resistant to bTB infection can assist in bTB control. The aim of this study was to conduct a quantitative genetic analysis of SICCT measurements collected during bTB herd testing. Genetic selection for bTB resistance will be partially informed by SICCT-based diagnosis; therefore it is important to know whether, in addition to increasing bTB resistance, this might also alter genetically the epidemiological characteristics of SICCT. Our main findings are that: (1) the SICCT test is robust at the genetic level, since its hierarchy and comparative nature provide substantial protection against random genetic changes that arise from genetic drift and from correlated responses among its components due to either natural or artificial selection; (2) the comparative nature of SICCT provides effective control for initial skin thickness and age-dependent differences; and (3) continuous variation in SICCT is only lowly heritable and has a weak correlation with SICCT positivity among healthy animals which was not significantly different from zero (P > 0.05). These emerging results demonstrate that genetic selection for bTB resistance is unlikely to change the probability of correctly identifying non-infected animals, i.e. the test's specificity, while reducing the overall number of cases. This study cannot exclude all theoretical risks from selection on resistance to bTB infection but the role of SICCT in disease control is unlikely to be rapidly undermined, with any adverse correlated responses expected to be weak and slow, which

A 100-Year Review: Methods and impact of genetic selection in dairy cattle-From daughter-dam comparisons to deep learning algorithms.

PubMed

Weigel, K A; VanRaden, P M; Norman, H D; Grosu, H

2017-12-01

In the early 1900s, breed society herdbooks had been established and milk-recording programs were in their infancy. Farmers wanted to improve the productivity of their cattle, but the foundations of population genetics, quantitative genetics, and animal breeding had not been laid. Early animal breeders struggled to identify genetically superior families using performance records that were influenced by local environmental conditions and herd-specific management practices. Daughter-dam comparisons were used for more than 30 yr and, although genetic progress was minimal, the attention given to performance recording, genetic theory, and statistical methods paid off in future years. Contemporary (herdmate) comparison methods allowed more accurate accounting for environmental factors and genetic progress began to accelerate when these methods were coupled with artificial insemination and progeny testing. Advances in computing facilitated the implementation of mixed linear models that used pedigree and performance data optimally and enabled accurate selection decisions. Sequencing of the bovine genome led to a revolution in dairy cattle breeding, and the pace of scientific discovery and genetic progress accelerated rapidly. Pedigree-based models have given way to whole-genome prediction, and Bayesian regression models and machine learning algorithms have joined mixed linear models in the toolbox of modern animal breeders. Future developments will likely include elucidation of the mechanisms of genetic inheritance and epigenetic modification in key biological pathways, and genomic data will be used with data from on-farm sensors to facilitate precision management on modern dairy farms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

PubMed

Pursiheimo, Anna; Vehmas, Anni P; Afzal, Saira; Suomi, Tomi; Chand, Thaman; Strauss, Leena; Poutanen, Matti; Rokka, Anne; Corthals, Garry L; Elo, Laura L

2015-10-02

As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as "real" experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.

Human fecal source identification with real-time quantitative PCR

EPA Science Inventory

Waterborne diseases represent a significant public health risk worldwide, and can originate from contact with water contaminated with human fecal material. We describe a real-time quantitative PCR (qPCR) method that targets a Bacteroides dori human-associated genetic marker for...

Quantitative assessment of skin, hair, and iris variation in a diverse sample of individuals and associated genetic variation.

PubMed

Norton, Heather L; Edwards, Melissa; Krithika, S; Johnson, Monique; Werren, Elizabeth A; Parra, Esteban J

2016-08-01

The main goals of this study are to 1) quantitatively measure skin, hair, and iris pigmentation in a diverse sample of individuals, 2) describe variation within and between these samples, and 3) demonstrate how quantitative measures can facilitate genotype-phenotype association tests. We quantitatively characterize skin, hair, and iris pigmentation using the Melanin (M) Index (skin) and CIELab values (hair) in 1,450 individuals who self-identify as African American, East Asian, European, Hispanic, or South Asian. We also quantify iris pigmentation in a subset of these individuals using CIELab values from high-resolution iris photographs. We compare mean skin M index and hair and iris CIELab values among populations using ANOVA and MANOVA respectively and test for genotype-phenotype associations in the European sample. All five populations are significantly different for skin (P <2 × 10(-16) ) and hair color (P <2 × 10(-16) ). Our quantitative analysis of iris and hair pigmentation reinforces the continuous, rather than discrete, nature of these traits. We confirm the association of three loci (rs16891982, rs12203592, and rs12913832) with skin pigmentation and four loci (rs12913832, rs12203592, rs12896399, and rs16891982) with hair pigmentation. Interestingly, the derived rs12203592 T allele located within the IRF4 gene is associated with lighter skin but darker hair color. The quantitative methods used here provide a fine-scale assessment of pigmentation phenotype and facilitate genotype-phenotype associations, even with relatively small sample sizes. This represents an important expansion of current investigations into pigmentation phenotype and associated genetic variation by including non-European and admixed populations. Am J Phys Anthropol 160:570-581, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population.

PubMed

Bonnet, Timothée; Wandeler, Peter; Camenisch, Glauco; Postma, Erik

2017-01-01

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called "stasis paradox" highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population

PubMed Central

Wandeler, Peter; Camenisch, Glauco

2017-01-01

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called “stasis paradox” highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is

ADVANCING THE STUDY OF VIOLENCE AGAINST WOMEN USING MIXED METHODS: INTEGRATING QUALITATIVE METHODS INTO A QUANTITATIVE RESEARCH PROGRAM

PubMed Central

Testa, Maria; Livingston, Jennifer A.; VanZile-Tamsen, Carol

2011-01-01

A mixed methods approach, combining quantitative with qualitative data methods and analysis, offers a promising means of advancing the study of violence. Integrating semi-structured interviews and qualitative analysis into a quantitative program of research on women’s sexual victimization has resulted in valuable scientific insight and generation of novel hypotheses for testing. This mixed methods approach is described and recommendations for integrating qualitative data into quantitative research are provided. PMID:21307032

Methodological Reporting in Qualitative, Quantitative, and Mixed Methods Health Services Research Articles

PubMed Central

Wisdom, Jennifer P; Cavaleri, Mary A; Onwuegbuzie, Anthony J; Green, Carla A

2012-01-01

Objectives Methodologically sound mixed methods research can improve our understanding of health services by providing a more comprehensive picture of health services than either method can alone. This study describes the frequency of mixed methods in published health services research and compares the presence of methodological components indicative of rigorous approaches across mixed methods, qualitative, and quantitative articles. Data Sources All empirical articles (n = 1,651) published between 2003 and 2007 from four top-ranked health services journals. Study Design All mixed methods articles (n = 47) and random samples of qualitative and quantitative articles were evaluated to identify reporting of key components indicating rigor for each method, based on accepted standards for evaluating the quality of research reports (e.g., use of p-values in quantitative reports, description of context in qualitative reports, and integration in mixed method reports). We used chi-square tests to evaluate differences between article types for each component. Principal Findings Mixed methods articles comprised 2.85 percent (n = 47) of empirical articles, quantitative articles 90.98 percent (n = 1,502), and qualitative articles 6.18 percent (n = 102). There was a statistically significant difference (χ2(1) = 12.20, p = .0005, Cramer's V = 0.09, odds ratio = 1.49 [95% confidence interval = 1,27, 1.74]) in the proportion of quantitative methodological components present in mixed methods compared to quantitative papers (21.94 versus 47.07 percent, respectively) but no statistically significant difference (χ2(1) = 0.02, p = .89, Cramer's V = 0.01) in the proportion of qualitative methodological components in mixed methods compared to qualitative papers (21.34 versus 25.47 percent, respectively). Conclusion Few published health services research articles use mixed methods. The frequency of key methodological components is variable. Suggestions are provided to increase the

Method and apparatus for chromatographic quantitative analysis

DOEpatents

Fritz, James S.; Gjerde, Douglas T.; Schmuckler, Gabriella

1981-06-09

An improved apparatus and method for the quantitative analysis of a solution containing a plurality of anion species by ion exchange chromatography which utilizes a single eluent and a single ion exchange bed which does not require periodic regeneration. The solution containing the anions is added to an anion exchange resin bed which is a low capacity macroreticular polystyrene-divinylbenzene resin containing quarternary ammonium functional groups, and is eluted therefrom with a dilute solution of a low electrical conductance organic acid salt. As each anion species is eluted from the bed, it is quantitatively sensed by conventional detection means such as a conductivity cell.

Construction of measurement uncertainty profiles for quantitative analysis of genetically modified organisms based on interlaboratory validation data.

PubMed

Macarthur, Roy; Feinberg, Max; Bertheau, Yves

2010-01-01

A method is presented for estimating the size of uncertainty associated with the measurement of products derived from genetically modified organisms (GMOs). The method is based on the uncertainty profile, which is an extension, for the estimation of uncertainty, of a recent graphical statistical tool called an accuracy profile that was developed for the validation of quantitative analytical methods. The application of uncertainty profiles as an aid to decision making and assessment of fitness for purpose is also presented. Results of the measurement of the quantity of GMOs in flour by PCR-based methods collected through a number of interlaboratory studies followed the log-normal distribution. Uncertainty profiles built using the results generally give an expected range for measurement results of 50-200% of reference concentrations for materials that contain at least 1% GMO. This range is consistent with European Network of GM Laboratories and the European Union (EU) Community Reference Laboratory validation criteria and can be used as a fitness for purpose criterion for measurement methods. The effect on the enforcement of EU labeling regulations is that, in general, an individual analytical result needs to be < 0.45% to demonstrate compliance, and > 1.8% to demonstrate noncompliance with a labeling threshold of 0.9%.

Methods for the survey and genetic analysis of populations

DOEpatents

Ashby, Matthew

2003-09-02

The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine.

Quantitative Method of Measuring Metastatic Activity

NASA Technical Reports Server (NTRS)

Morrison, Dennis R. (Inventor)

1999-01-01

The metastatic potential of tumors can be evaluated by the quantitative detection of urokinase and DNA. The cell sample selected for examination is analyzed for the presence of high levels of urokinase and abnormal DNA using analytical flow cytometry and digital image analysis. Other factors such as membrane associated uroldnase, increased DNA synthesis rates and certain receptors can be used in the method for detection of potentially invasive tumors.

Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes.

PubMed

Pillai, S G; Tang, Y; van den Oord, E; Klotsman, M; Barnes, K; Carlsen, K; Gerritsen, J; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Ortega, H G; Anderson, W H; Helms, P J

2008-03-01

Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the contribution of genes and environments to disease expression. To determine the minimum number of sets of features required to characterize subjects with asthma which will be useful in identifying important genetic and environmental contributors. Methods Probands aged 7-35 years with physician diagnosed asthma and symptomatic siblings were identified in 1022 nuclear families from 11 centres in six countries forming the Genetics of Asthma International Network. Factor analysis was used to identify distinct phenotypes from questionnaire, clinical, and laboratory data, including baseline pulmonary function, allergen skin prick test (SPT). Five distinct factors were identified:(1) baseline pulmonary function measures [forced expiratory volume in 1 s (FEV(1)) and forced vital capacity (FVC)], (2) specific allergen sensitization by SPT, (3) self-reported allergies, (4) symptoms characteristic of rhinitis and (5) symptoms characteristic of asthma. Replication in symptomatic siblings was consistent with shared genetic and/or environmental effects, and was robust across age groups, gender, and centres. Cronbach's alpha ranged from 0.719 to 0.983 suggesting acceptable internal scale consistencies. Derived scales were correlated with serum IgE, methacholine PC(20), age and asthma severity (interrupted sleep). IgE correlated with all three atopy-related factors, the strongest with the SPT factor whereas severity only correlated with baseline lung function, and with symptoms characteristic of rhinitis and of asthma. In children and adolescents with established asthma, five distinct sets of correlated patient characteristics appear to represent important aspects of the disease. Factor scores as

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

PubMed Central

Charmantier, Anne; Perrins, Christopher; McCleery, Robin H.; Sheldon, Ben C.

2006-01-01

Why do individuals stop reproducing after a certain age, and how is this age determined? The antagonistic pleiotropy theory for the evolution of senescence predicts that increased early-life performance should be accompanied by earlier (or faster) senescence. Hence, an individual that has started to breed early should also lose its reproductive capacities early. We investigate here the relationship between age at first reproduction (AFR) and age at last reproduction (ALR) in a free-ranging mute swan (Cygnus olor) population monitored for 36 years. Using multivariate analyses on the longitudinal data, we show that both traits are strongly selected in opposite directions. Analysis of the phenotypic covariance between these characters shows that individuals vary in their inherent quality, such that some individuals have earlier AFR and later ALR than expected. Quantitative genetic pedigree analyses show that both traits possess additive genetic variance but also that AFR and ALR are positively genetically correlated. Hence, although both traits display heritable variation and are under opposing directional selection, their evolution is constrained by a strong evolutionary tradeoff. These results are consistent with the theory that increased early-life performance comes with faster senescence because of genetic tradeoffs. PMID:16618935

[Application of case-based method in genetics and eugenics teaching].

PubMed

Li, Ya-Xuan; Zhao, Xin; Zhang, Fei-Xiong; Hu, Ying-Kao; Yan, Yue-Ming; Cai, Min-Hua; Li, Xiao-Hui

2012-05-01

Genetics and Eugenics is a cross-discipline between genetics and eugenics. It is a common curriculum in many Chinese universities. In order to increase the learning interest, we introduced case teaching method and got a better teaching effect. Based on our teaching practices, we summarized some experiences about this subject. In this article, the main problem of case-based method applied in Genetics and Eugenics teaching was discussed.

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

PubMed

Hu, Hsien-Ming; Zhao, Xin; Kaushik, Swati; Robillard, Lilliane; Barthelet, Antoine; Lin, Kevin K; Shah, Khyati N; Simmons, Andy D; Raponi, Mitch; Harding, Thomas C; Bandyopadhyay, Sourav

2018-04-17

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy. This quantitative map is predictive of interactions maintained in other cell lines, identifies DNA-repair factors, predicts cancer cell line responses to therapy, and prioritizes synergistic drug combinations. We identify that ARID1A loss confers resistance to PARP inhibitors in cells and ovarian cancer patients and that loss of GPBP1 causes resistance to cisplatin and PARP inhibitors through the regulation of genes involved in homologous recombination. This map helps navigate patient genomic data and optimize chemotherapeutic regimens by delineating factors involved in the response to specific types of DNA damage. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

International collaborative study of the endogenous reference gene, sucrose phosphate synthase (SPS), used for qualitative and quantitative analysis of genetically modified rice.

PubMed

Jiang, Lingxi; Yang, Litao; Zhang, Haibo; Guo, Jinchao; Mazzara, Marco; Van den Eede, Guy; Zhang, Dabing

2009-05-13

One rice ( Oryza sativa ) gene, sucrose phosphate synthase (SPS), has been proven to be a suitable endogenous reference gene for genetically modified (GM) rice detection in a previous study. Herein are the reported results of an international collaborative ring trial for validation of the SPS gene as an endogenous reference gene and its optimized qualitative and quantitative polymerase chain reaction (PCR) systems. A total of 12 genetically modified organism (GMO) detection laboratories from seven countries participated in the ring trial and returned their results. The validated results confirmed the species specificity of the method through testing 10 plant genomic DNAs, low heterogeneity, and a stable single-copy number of the rice SPS gene among 7 indica varieties and 5 japonica varieties. The SPS qualitative PCR assay was validated with a limit of detection (LOD) of 0.1%, which corresponded to about 230 copies of haploid rice genomic DNA, while the limit of quantification (LOQ) for the quantitative PCR system was about 23 copies of haploid rice genomic DNA, with acceptable PCR efficiency and linearity. Furthermore, the bias between the test and true values of eight blind samples ranged from 5.22 to 26.53%. Thus, we believe that the SPS gene is suitable for use as an endogenous reference gene for the identification and quantification of GM rice and its derivates.

Methodological reporting in qualitative, quantitative, and mixed methods health services research articles.

PubMed

Wisdom, Jennifer P; Cavaleri, Mary A; Onwuegbuzie, Anthony J; Green, Carla A

2012-04-01

Methodologically sound mixed methods research can improve our understanding of health services by providing a more comprehensive picture of health services than either method can alone. This study describes the frequency of mixed methods in published health services research and compares the presence of methodological components indicative of rigorous approaches across mixed methods, qualitative, and quantitative articles. All empirical articles (n = 1,651) published between 2003 and 2007 from four top-ranked health services journals. All mixed methods articles (n = 47) and random samples of qualitative and quantitative articles were evaluated to identify reporting of key components indicating rigor for each method, based on accepted standards for evaluating the quality of research reports (e.g., use of p-values in quantitative reports, description of context in qualitative reports, and integration in mixed method reports). We used chi-square tests to evaluate differences between article types for each component. Mixed methods articles comprised 2.85 percent (n = 47) of empirical articles, quantitative articles 90.98 percent (n = 1,502), and qualitative articles 6.18 percent (n = 102). There was a statistically significant difference (χ(2) (1) = 12.20, p = .0005, Cramer's V = 0.09, odds ratio = 1.49 [95% confidence interval = 1,27, 1.74]) in the proportion of quantitative methodological components present in mixed methods compared to quantitative papers (21.94 versus 47.07 percent, respectively) but no statistically significant difference (χ(2) (1) = 0.02, p = .89, Cramer's V = 0.01) in the proportion of qualitative methodological components in mixed methods compared to qualitative papers (21.34 versus 25.47 percent, respectively). Few published health services research articles use mixed methods. The frequency of key methodological components is variable. Suggestions are provided to increase the transparency of mixed methods studies and

Global genetic architecture of an erythroid quantitative trait locus, HMIP-2.

PubMed

Menzel, Stephan; Rooks, Helen; Zelenika, Diana; Mtatiro, Siana N; Gnanakulasekaran, Akshala; Drasar, Emma; Cox, Sharon; Liu, Li; Masood, Mariam; Silver, Nicholas; Garner, Chad; Vasavda, Nisha; Howard, Jo; Makani, Julie; Adekile, Adekunle; Pace, Betty; Spector, Tim; Farrall, Martin; Lathrop, Mark; Thein, Swee Lay

2014-11-01

HMIP-2 is a human quantitative trait locus affecting peripheral numbers, size and hemoglobin composition of red blood cells, with a marked effect on the persistence of the fetal form of hemoglobin, HbF, in adults. The locus consists of multiple common variants in an enhancer region for MYB (chr 6q23.3), which encodes the hematopoietic transcription factor cMYB. Studying a European population cohort and four African-descended groups of patients with sickle cell anemia, we found that all share a set of two spatially separate HbF-promoting alleles at HMIP-2, termed "A" and "B." These typically occurred together ("A-B") on European chromosomes, but existed on separate homologous chromosomes in Africans. Using haplotype signatures for "A" and "B," we interrogated public population datasets. Haplotypes carrying only "A" or "B" were typical for populations in Sub-Saharan Africa. The "A-B" combination was frequent in European, Asian, and Amerindian populations. Both alleles were infrequent in tropical regions, possibly undergoing negative selection by geographical factors, as has been reported for malaria with other hematological traits. We propose that the ascertainment of worldwide distribution patterns for common, HbF-promoting alleles can aid their further genetic characterization, including the investigation of gene-environment interaction during human migration and adaptation. © 2014 The Authors. Annals of Human Genetics published by University College London (UCL) and John Wiley & Sons Ltd.

The efficiency of close inbreeding to reduce genetic adaptation to captivity

PubMed Central

Theodorou, K; Couvet, D

2015-01-01

Although ex situ conservation is indispensable for thousands of species, captive breeding is associated with negative genetic changes: loss of genetic variance and genetic adaptation to captivity that is deleterious in the wild. We used quantitative genetic individual-based simulations to model the effect of genetic management on the evolution of a quantitative trait and the associated fitness of wild-born individuals that are brought to captivity. We also examined the feasibility of the breeding strategies under a scenario of a large number of loci subject to deleterious mutations. We compared two breeding strategies: repeated half-sib mating and a method of minimizing mean coancestry (referred to as gc/mc). Our major finding was that half-sib mating is more effective in reducing genetic adaptation to captivity than the gc/mc method. Moreover, half-sib mating retains larger allelic and adaptive genetic variance. Relative to initial standing variation, the additive variance of the quantitative trait increased under half-sib mating during the sojourn in captivity. Although fragmentation into smaller populations improves the efficiency of the gc/mc method, half-sib mating still performs better in the scenarios tested. Half-sib mating shows two caveats that could mitigate its beneficial effects: low heterozygosity and high risk of extinction when populations are of low fecundity and size and one of the following conditions are met: (i) the strength of selection in captivity is comparable with that in the wild, (ii) deleterious mutations are numerous and only slightly deleterious. Experimental validation of half-sib mating is therefore needed for the advancement of captive breeding programs. PMID:25052417

Method of detecting genetic translocations identified with chromosomal abnormalities

DOEpatents

Gray, Joe W.; Pinkel, Daniel; Tkachuk, Douglas

2001-01-01

Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyses. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acid probes are typically of a complexity greater than 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar but genetically different diseases, and for many prognostic and diagnostic applications.

Method of detecting genetic deletions identified with chromosomal abnormalities

DOEpatents

Gray, Joe W; Pinkel, Daniel; Tkachuk, Douglas

2013-11-26

Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyzes. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acids probes are typically of a complexity greater tha 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particlularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar ut genetically different diseases, and for many prognostic and diagnostic applications.

Genetics Home Reference: prostate cancer

MedlinePlus

... prostate cancer Genetic Testing Registry: Prostate cancer aggressiveness quantitative trait locus on chromosome 19 Genetic Testing Registry: ... OMIM (25 links) PROSTATE CANCER PROSTATE CANCER AGGRESSIVENESS QUANTITATIVE TRAIT LOCUS ON CHROMOSOME 19 PROSTATE CANCER ANTIGEN ...

Genetic Diversity of Globally Dispersed Lacustrine Group I Haptophytes: Implications for Quantitative Temperature Reconstructions

NASA Astrophysics Data System (ADS)

Richter, N.; Longo, W. M.; Amaral-Zettler, L. A.; Huang, Y.

2017-12-01

There are significant uncertainties surrounding the forcings that drive terrestrial temperature changes on local and regional scales. Quantitative temperature reconstructions from terrestrial sites, such as lakes, help to unravel the fundamental processes that drive changes in temperature on different temporal and spatial scales. Recent studies at Brown University show that distinct alkenones, long chain ketones produced by haptophytes, are found in many freshwater, alkaline lakes in the Northern Hemisphere, highlighting these systems as targets for quantitative continental temperature reconstructions. These freshwater alkenones are produced by the Group I haptophyte phylotype and are characterized by a distinct signature: the presence of isomeric tri-unsaturated ketones and absence of alkenoates. There are currently no cultured representatives of the "Group I" haptophytes, hence they are only known based on their rRNA gene signatures. Here we present robust evidence that Northern Hemispheric freshwater, alkaline lakes with the characteristic "Group I" alkenone signature all host the same clade of Isochrysidales haptophytes. We employed next generation DNA amplicon sequencing to target haptophyte specific hypervariable regions of the large and small-subunit ribosomal RNA gene from 13 different lakes from three continents (i.e., North America, Europe, and Asia). Combined with previously published sequences, our genetic data show that the Group I haptophyte is genetically diverse on a regional and global scale, and even within the same lake. We present two case studies from a suite of five lakes in Alaska and three in Iceland to assess the impact of various environmental factors affecting Group I diversity and alkenone production. Despite the genetic diversity in this group, the overall ketone signature is conserved. Based on global surface sediment samples and in situ Alaskan lake calibrations, alkenones produced by different operational taxonomic units of the Group

Effect of genetic algorithm as a variable selection method on different chemometric models applied for the analysis of binary mixture of amoxicillin and flucloxacillin: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2016-03-01

Different chemometric models were applied for the quantitative analysis of amoxicillin (AMX), and flucloxacillin (FLX) in their binary mixtures, namely, partial least squares (PLS), spectral residual augmented classical least squares (SRACLS), concentration residual augmented classical least squares (CRACLS) and artificial neural networks (ANNs). All methods were applied with and without variable selection procedure (genetic algorithm GA). The methods were used for the quantitative analysis of the drugs in laboratory prepared mixtures and real market sample via handling the UV spectral data. Robust and simpler models were obtained by applying GA. The proposed methods were found to be rapid, simple and required no preliminary separation steps.

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance. | Office of Cancer Genomics

Cancer.gov

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy.

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

Methods in Molecular Biology Mouse Genetics: Methods and Protocols | Center for Cancer Research

Cancer.gov

Mouse Genetics: Methods and Protocols provides selected mouse genetic techniques and their application in modeling varieties of human diseases. The chapters are mainly focused on the generation of different transgenic mice to accomplish the manipulation of genes of interest, tracing cell lineages, and modeling human diseases.

Initialization Method for Grammar-Guided Genetic Programming

NASA Astrophysics Data System (ADS)

García-Arnau, M.; Manrique, D.; Ríos, J.; Rodríguez-Patón, A.

This paper proposes a new tree-generation algorithm for grammarguided genetic programming that includes a parameter to control the maximum size of the trees to be generated. An important feature of this algorithm is that the initial populations generated are adequately distributed in terms of tree size and distribution within the search space. Consequently, genetic programming systems starting from the initial populations generated by the proposed method have a higher convergence speed. Two different problems have been chosen to carry out the experiments: a laboratory test involving searching for arithmetical equalities and the real-world task of breast cancer prognosis. In both problems, comparisons have been made to another five important initialization methods.

Quantitative genetics of circulating Hyaluronic Acid (HA) and its correlation with hand osteoarthritis and obesity-related phenotypes in a community-based sample.

PubMed

Prakash, Jai; Gabdulina, Gulzhan; Trofimov, Svetlana; Livshits, Gregory

2017-09-01

One of the potential molecular biomarkers of osteoarthritis (OA) is hyaluronic acid (HA). HA levels may be related to the severity and progression of OA. However, little is known about the contribution of major risk factors for osteoarthritis, e.g. obesity-related phenotypes and genetics to HA variation. To clarify the quantitative effect of these factors on HA. An ethnically homogeneous sample of 911 apparently healthy European-derived individuals, assessed for radiographic hand osteoarthritis (RHOA), HA, leptin, adiponectin, and several anthropometrical measures of obesity-related phenotypes was studied. Model-based quantitative genetic analysis was used to reveal genetic and shared environmental factors affecting the variation of the study's phenotypes. The HA levels significantly correlated with the age, RHOA, adiponectin, obesity-related phenotypes, and the waist-to-hip ratio. The putative genetic effects contributed significantly to the variation of HA (66.2 ± 9.3%) and they were also significant factors in the variations of all the other studied phenotypes, with the heritability estimate ranging between 0.122 ± 4.4% (WHR) and 45.7 ± 2.2% (joint space narrowing). This is the first study to report heritability estimates of HA variation and its correlation with obesity-related phenotypes, ADP and RHOA. However, the nature of genetic effects on HA and its correlation with other study phenotypes require further clarification.

Industrial ecology: Quantitative methods for exploring a lower carbon future

NASA Astrophysics Data System (ADS)

Thomas, Valerie M.

2015-03-01

Quantitative methods for environmental and cost analyses of energy, industrial, and infrastructure systems are briefly introduced and surveyed, with the aim of encouraging broader utilization and development of quantitative methods in sustainable energy research. Material and energy flow analyses can provide an overall system overview. The methods of engineering economics and cost benefit analysis, such as net present values, are the most straightforward approach for evaluating investment options, with the levelized cost of energy being a widely used metric in electricity analyses. Environmental lifecycle assessment has been extensively developed, with both detailed process-based and comprehensive input-output approaches available. Optimization methods provide an opportunity to go beyond engineering economics to develop detailed least-cost or least-impact combinations of many different choices.

Intra-laboratory validation of chronic bee paralysis virus quantitation using an accredited standardised real-time quantitative RT-PCR method.

PubMed

Blanchard, Philippe; Regnault, Julie; Schurr, Frank; Dubois, Eric; Ribière, Magali

2012-03-01

Chronic bee paralysis virus (CBPV) is responsible for chronic bee paralysis, an infectious and contagious disease in adult honey bees (Apis mellifera L.). A real-time RT-PCR assay to quantitate the CBPV load is now available. To propose this assay as a reference method, it was characterised further in an intra-laboratory study during which the reliability and the repeatability of results and the performance of the assay were confirmed. The qPCR assay alone and the whole quantitation method (from sample RNA extraction to analysis) were both assessed following the ISO/IEC 17025 standard and the recent XP U47-600 standard issued by the French Standards Institute. The performance of the qPCR assay and of the overall CBPV quantitation method were validated over a 6 log range from 10(2) to 10(8) with a detection limit of 50 and 100 CBPV RNA copies, respectively, and the protocol of the real-time RT-qPCR assay for CBPV quantitation was approved by the French Accreditation Committee. Copyright © 2011 Elsevier B.V. All rights reserved.

"The Theory was Beautiful Indeed": Rise, Fall and Circulation of Maximizing Methods in Population Genetics (1930-1980).

PubMed

Grodwohl, Jean-Baptiste

2017-08-01

Describing the theoretical population geneticists of the 1960s, Joseph Felsenstein reminisced: "our central obsession was finding out what function evolution would try to maximize. Population geneticists used to think, following Sewall Wright, that mean relative fitness, W, would be maximized by natural selection" (Felsenstein 2000). The present paper describes the genesis, diffusion and fall of this "obsession", by giving a biography of the mean fitness function in population genetics. This modeling method devised by Sewall Wright in the 1930s found its heyday in the late 1950s and early 1960s, in the wake of Motoo Kimura's and Richard Lewontin's works. It seemed a reliable guide in the mathematical study of deterministic effects (the study of natural selection in populations of infinite size, with no drift), leading to powerful generalizations presenting law-like properties. Progress in population genetics theory, it then seemed, would come from the application of this method to the study of systems with several genes. This ambition came to a halt in the context of the influential objections made by the Australian mathematician Patrick Moran in 1963. These objections triggered a controversy between mathematically- and biologically-inclined geneticists, with affected both the formal standards and the aims of population genetics as a science. Over the course of the 1960s, the mean fitness method withered with the ambition of developing the deterministic theory. The mathematical theory became increasingly complex. Kimura re-focused his modeling work on the theory of random processes; as a result of his computer simulations, Lewontin became the staunchest critic of maximizing principles in evolutionary biology. The mean fitness method then migrated to other research areas, being refashioned and used in evolutionary quantitative genetics and behavioral ecology.

A general method for bead-enhanced quantitation by flow cytometry

PubMed Central

Montes, Martin; Jaensson, Elin A.; Orozco, Aaron F.; Lewis, Dorothy E.; Corry, David B.

2009-01-01

Flow cytometry provides accurate relative cellular quantitation (percent abundance) of cells from diverse samples, but technical limitations of most flow cytometers preclude accurate absolute quantitation. Several quantitation standards are now commercially available which, when added to samples, permit absolute quantitation of CD4+ T cells. However, these reagents are limited by their cost, technical complexity, requirement for additional software and/or limited applicability. Moreover, few studies have validated the use of such reagents in complex biological samples, especially for quantitation of non-T cells. Here we show that addition to samples of known quantities of polystyrene fluorescence standardization beads permits accurate quantitation of CD4+ T cells from complex cell samples. This procedure, here termed single bead-enhanced cytofluorimetry (SBEC), was equally capable of enumerating eosinophils as well as subcellular fragments of apoptotic cells, moieties with very different optical and fluorescent characteristics. Relative to other proprietary products, SBEC is simple, inexpensive and requires no special software, suggesting that the method is suitable for the routine quantitation of most cells and other particles by flow cytometry. PMID:17067632

Quantitative structure-property relationship (QSPR) modeling of drug-loaded polymeric micelles via genetic function approximation.

PubMed

Wu, Wensheng; Zhang, Canyang; Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments.

Quantitative evaluation methods of skin condition based on texture feature parameters.

PubMed

Pang, Hui; Chen, Tianhua; Wang, Xiaoyi; Chang, Zhineng; Shao, Siqi; Zhao, Jing

2017-03-01

In order to quantitatively evaluate the improvement of the skin condition after using skin care products and beauty, a quantitative evaluation method for skin surface state and texture is presented, which is convenient, fast and non-destructive. Human skin images were collected by image sensors. Firstly, the median filter of the 3 × 3 window is used and then the location of the hairy pixels on the skin is accurately detected according to the gray mean value and color information. The bilinear interpolation is used to modify the gray value of the hairy pixels in order to eliminate the negative effect of noise and tiny hairs on the texture. After the above pretreatment, the gray level co-occurrence matrix (GLCM) is calculated. On the basis of this, the four characteristic parameters, including the second moment, contrast, entropy and correlation, and their mean value are calculated at 45 ° intervals. The quantitative evaluation model of skin texture based on GLCM is established, which can calculate the comprehensive parameters of skin condition. Experiments show that using this method evaluates the skin condition, both based on biochemical indicators of skin evaluation methods in line, but also fully consistent with the human visual experience. This method overcomes the shortcomings of the biochemical evaluation method of skin damage and long waiting time, also the subjectivity and fuzziness of the visual evaluation, which achieves the non-destructive, rapid and quantitative evaluation of skin condition. It can be used for health assessment or classification of the skin condition, also can quantitatively evaluate the subtle improvement of skin condition after using skin care products or stage beauty.

Blending quantitative and qualitative methods in language research and intervention.

PubMed

Brinton, Bonnie; Fujiki, Martin

2003-05-01

Best practice in speech-language pathology should be informed by current research findings. Traditional research methods are not always geared to address some of the complex, individual questions that arise in clinical intervention, however. Qualitative research methods may provide useful tools for bridging the gap from research to practice. Combinations of qualitative and quantitative procedures may be particularly helpful in sorting out some of the important issues surrounding language intervention in both clinical and research contexts. Examples of research blending qualitative and quantitative methods, as well as the case study of Sid, an 11-year-old boy with specific language impairment, are presented to illustrate how a combination of procedures can be used to enhance language research and intervention.

Genetic dissection of fruiting body-related traits using quantitative trait loci mapping in Lentinula edodes.

PubMed

Gong, Wen-Bing; Li, Lei; Zhou, Yan; Bian, Yin-Bing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

2016-06-01

To provide a better understanding of the genetic architecture of fruiting body formation of Lentinula edodes, quantitative trait loci (QTLs) mapping was employed to uncover the loci underlying seven fruiting body-related traits (FBRTs). An improved L. edodes genetic linkage map, comprising 572 markers on 12 linkage groups with a total map length of 983.7 cM, was constructed by integrating 82 genomic sequence-based insertion-deletion (InDel) markers into a previously published map. We then detected a total of 62 QTLs for seven target traits across two segregating testcross populations, with individual QTLs contributing 5.5 %-30.2 % of the phenotypic variation. Fifty-three out of the 62 QTLs were clustered in six QTL hotspots, suggesting the existence of main genomic regions regulating the morphological characteristics of fruiting bodies in L. edodes. A stable QTL hotspot on MLG2, containing QTLs for all investigated traits, was identified in both testcross populations. QTLs for related traits were frequently co-located on the linkage groups, demonstrating the genetic basis for phenotypic correlation of traits. Meta-QTL (mQTL) analysis was performed and identified 16 mQTLs with refined positions and narrow confidence intervals (CIs). Nine genes, including those encoding MAP kinase, blue-light photoreceptor, riboflavin-aldehyde-forming enzyme and cyclopropane-fatty-acyl-phospholipid synthase, and cytochrome P450s, were likely to be candidate genes controlling the shape of fruiting bodies. The study has improved our understanding of the genetic architecture of fruiting body formation in L. edodes. To our knowledge, this is the first genome-wide QTL detection of FBRTs in L. edodes. The improved genetic map, InDel markers and QTL hotspot regions revealed here will assist considerably in the conduct of future genetic and breeding studies of L. edodes.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

PubMed

Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C

2015-02-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

A quantitative method for evaluating alternatives. [aid to decision making

NASA Technical Reports Server (NTRS)

Forthofer, M. J.

1981-01-01

When faced with choosing between alternatives, people tend to use a number of criteria (often subjective, rather than objective) to decide which is the best alternative for them given their unique situation. The subjectivity inherent in the decision-making process can be reduced by the definition and use of a quantitative method for evaluating alternatives. This type of method can help decision makers achieve degree of uniformity and completeness in the evaluation process, as well as an increased sensitivity to the factors involved. Additional side-effects are better documentation and visibility of the rationale behind the resulting decisions. General guidelines for defining a quantitative method are presented and a particular method (called 'hierarchical weighted average') is defined and applied to the evaluation of design alternatives for a hypothetical computer system capability.

Quantitative methods in assessment of neurologic function.

PubMed

Potvin, A R; Tourtellotte, W W; Syndulko, K; Potvin, J

1981-01-01

Traditionally, neurologists have emphasized qualitative techniques for assessing results of clinical trials. However, in recent years qualitative evaluations have been increasingly augmented by quantitative tests for measuring neurologic functions pertaining to mental state, strength, steadiness, reactions, speed, coordination, sensation, fatigue, gait, station, and simulated activities of daily living. Quantitative tests have long been used by psychologists for evaluating asymptomatic function, assessing human information processing, and predicting proficiency in skilled tasks; however, their methodology has never been directly assessed for validity in a clinical environment. In this report, relevant contributions from the literature on asymptomatic human performance and that on clinical quantitative neurologic function are reviewed and assessed. While emphasis is focused on tests appropriate for evaluating clinical neurologic trials, evaluations of tests for reproducibility, reliability, validity, and examiner training procedures, and for effects of motivation, learning, handedness, age, and sex are also reported and interpreted. Examples of statistical strategies for data analysis, scoring systems, data reduction methods, and data display concepts are presented. Although investigative work still remains to be done, it appears that carefully selected and evaluated tests of sensory and motor function should be an essential factor for evaluating clinical trials in an objective manner.

Genetic algorithms as global random search methods

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.

1995-01-01

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Genetic algorithms as global random search methods

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.

1995-01-01

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

PubMed

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Quantitative Resistance: More Than Just Perception of a Pathogen.

PubMed

Corwin, Jason A; Kliebenstein, Daniel J

2017-04-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. © 2017 American Society of Plant Biologists. All rights reserved.

Quantitative Resistance: More Than Just Perception of a Pathogen

PubMed Central

2017-01-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. PMID:28302676

Improved method and apparatus for chromatographic quantitative analysis

DOEpatents

Fritz, J.S.; Gjerde, D.T.; Schmuckler, G.

An improved apparatus and method are described for the quantitative analysis of a solution containing a plurality of anion species by ion exchange chromatography which utilizes a single element and a single ion exchange bed which does not require periodic regeneration. The solution containing the anions is added to an anion exchange resin bed which is a low capacity macroreticular polystyrene-divinylbenzene resin containing quarternary ammonium functional groups, and is eluted therefrom with a dilute solution of a low electrical conductance organic acid salt. As each anion species is eluted from the bed, it is quantitatively sensed by conventional detection means such as a conductivity cell.

Simultaneous quantitative determination of paracetamol and tramadol in tablet formulation using UV spectrophotometry and chemometric methods

NASA Astrophysics Data System (ADS)

Glavanović, Siniša; Glavanović, Marija; Tomišić, Vladislav

2016-03-01

The UV spectrophotometric methods for simultaneous quantitative determination of paracetamol and tramadol in paracetamol-tramadol tablets were developed. The spectrophotometric data obtained were processed by means of partial least squares (PLS) and genetic algorithm coupled with PLS (GA-PLS) methods in order to determine the content of active substances in the tablets. The results gained by chemometric processing of the spectroscopic data were statistically compared with those obtained by means of validated ultra-high performance liquid chromatographic (UHPLC) method. The accuracy and precision of data obtained by the developed chemometric models were verified by analysing the synthetic mixture of drugs, and by calculating recovery as well as relative standard error (RSE). A statistically good agreement was found between the amounts of paracetamol determined using PLS and GA-PLS algorithms, and that obtained by UHPLC analysis, whereas for tramadol GA-PLS results were proven to be more reliable compared to those of PLS. The simplest and the most accurate and precise models were constructed by using the PLS method for paracetamol (mean recovery 99.5%, RSE 0.89%) and the GA-PLS method for tramadol (mean recovery 99.4%, RSE 1.69%).

Methods for genetic modification of megakaryocytes and platelets.

PubMed

Pendaries, Caroline; Watson, Stephen P; Spalton, Jennifer C

2007-09-01

During recent decades there have been major advances in the fields of thrombosis and haemostasis, in part through development of powerful molecular and genetic technologies. Nevertheless, genetic modification of megakaryocytes and generation of mutant platelets in vitro remains a highly specialized area of research. Developments are hampered by the low frequency of megakaryocytes and their progenitors, a poor efficiency of transfection and a lack of understanding with regard to the mechanism by which megakaryocytes release platelets. Current methods used in the generation of genetically modified megakaryocytes and platelets include mutant mouse models, cell line studies and use of viruses to transform primary megakaryocytes or haematopoietic precursor cells. This review summarizes the advantages, limitations and technical challenges of such methods, with a particular focus on recent successes and advances in this rapidly progressing field including the potential for use in gene therapy for treatment of patients with platelet disorders.

Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs.

PubMed

Jeffrey, Brandon; Kuzhiyil, Najeeb; de Leon, Natalia; Lübberstedt, Thomas

2016-01-01

Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

Probing myocardium biomechanics using quantitative optical coherence elastography

NASA Astrophysics Data System (ADS)

Wang, Shang; Lopez, Andrew L.; Morikawa, Yuka; Tao, Ge; Li, Jiasong; Larina, Irina V.; Martin, James F.; Larin, Kirill V.

2015-03-01

We present a quantitative optical coherence elastographic method for noncontact assessment of the myocardium elasticity. The method is based on shear wave imaging optical coherence tomography (SWI-OCT), where a focused air-puff system is used to induce localized tissue deformation through a low-pressure short-duration air stream and a phase-sensitive OCT system is utilized to monitor the propagation of the induced tissue displacement with nanoscale sensitivity. The 1-D scanning of M-mode OCT imaging and the application of optical phase retrieval and mapping techniques enable the reconstruction and visualization of 2-D depth-resolved shear wave propagation in tissue with ultra-high frame rate. The feasibility of this method in quantitative elasticity measurement is demonstrated on tissue-mimicking phantoms with the estimated Young's modulus compared with uniaxial compression tests. We also performed pilot experiments on ex vivo mouse cardiac muscle tissues with normal and genetically altered cardiomyocytes. Our results indicate this noncontact quantitative optical coherence elastographic method can be a useful tool for the cardiac muscle research and studies.

A unifying theory for genetic epidemiological analysis of binary disease data

PubMed Central

2014-01-01

Background Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Results Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. Conclusions We have derived a genetic-epidemiological function for quantitative

A unifying theory for genetic epidemiological analysis of binary disease data.

PubMed

Lipschutz-Powell, Debby; Woolliams, John A; Doeschl-Wilson, Andrea B

2014-02-19

Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. We have derived a genetic-epidemiological function for quantitative genetic analyses of binary

Quantitative Structure-Property Relationship (QSPR) Modeling of Drug-Loaded Polymeric Micelles via Genetic Function Approximation

PubMed Central

Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments. PMID:25780923

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Indirect scaling methods for testing quantitative emotion theories.

PubMed

Junge, Martin; Reisenzein, Rainer

2013-01-01

Two studies investigated the utility of indirect scaling methods, based on graded pair comparisons, for the testing of quantitative emotion theories. In Study 1, we measured the intensity of relief and disappointment caused by lottery outcomes, and in Study 2, the intensity of disgust evoked by pictures, using both direct intensity ratings and graded pair comparisons. The stimuli were systematically constructed to reflect variables expected to influence the intensity of the emotions according to theoretical models of relief/disappointment and disgust, respectively. Two probabilistic scaling methods were used to estimate scale values from the pair comparison judgements: Additive functional measurement (AFM) and maximum likelihood difference scaling (MLDS). The emotion models were fitted to the direct and indirect intensity measurements using nonlinear regression (Study 1) and analysis of variance (Study 2). Both studies found substantially improved fits of the emotion models for the indirectly determined emotion intensities, with their advantage being evident particularly at the level of individual participants. The results suggest that indirect scaling methods yield more precise measurements of emotion intensity than rating scales and thereby provide stronger tests of emotion theories in general and quantitative emotion theories in particular.

A comparative analysis of the effectiveness of cytogenetic and molecular genetic methods in the detection of Down syndrome.

PubMed

Mačkić-Đurović, Mirela; Projić, Petar; Ibrulj, Slavka; Cakar, Jasmina; Marjanović, Damir

2014-05-01

The goal of this study was to examine the effectiveness of 6 STR markers application (D21S1435, D21S11, D21S1270, D21S1411, D21S226 and IFNAR) in molecular genetic diagnostics of Down syndrome (DS) and to compare it with cytogenetic method. Testing was performed on 73 children, with the previously cytogenetically confirmed Down syndrome. DNA isolated from the buccal swab was used. Previously mentioned loci located on chromosome 21 were simultaneously amplified using quantitative fluorescence PCR (QF PCR). Using this method, 60 previously cytogenetically diagnosed DS with standard type of trisomy 21 were confirmed. Furthermore, six of eight children with mosaic type of DS were detected. Two false negative results for mosaic type of DS were obtained. Finally, five children with the translocation type of Down syndrome were also confirmed with this molecular test. In conclusion, molecular genetic analysis of STR loci is fast, cheap and simple method that could be used in detection of DS. Regarding possible false results detected for certain number of mosaic types, cytogenetic analysis should be used as a confirmatory test.

A quantitative chemotherapy genetic interaction map reveals new factors associated with PARP inhibitor resistance | Office of Cancer Genomics

Cancer.gov

Nearly every cancer patient is treated with chemotherapy yet our understanding of factors that dictate response and resistance to such agents remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells that charts the impact of knockdown of 625 cancer and DNA repair related genes on sensitivity to 29 drugs, covering all classes of cancer chemotherapeutics.

A thioacidolysis method tailored for higher‐throughput quantitative analysis of lignin monomers

PubMed Central

Foster, Cliff; Happs, Renee M.; Doeppke, Crissa; Meunier, Kristoffer; Gehan, Jackson; Yue, Fengxia; Lu, Fachuang; Davis, Mark F.

2016-01-01

Abstract Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β‐O‐4 linkages. Current thioacidolysis methods are low‐throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non‐chlorinated organic solvent and is tailored for higher‐throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1–2 mg of biomass per assay and has been quantified using fast‐GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, including standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day‐to‐day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. The method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses. PMID:27534715

A thioacidolysis method tailored for higher-throughput quantitative analysis of lignin monomers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harman-Ware, Anne E.; Foster, Cliff; Happs, Renee M.

Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β-O-4 linkages. Current thioacidolysis methods are low-throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non-chlorinated organic solvent and is tailored for higher-throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1-2 mg of biomass per assay and has been quantified using fast-GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, includingmore » standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day-to-day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. As a result, the method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses.« less

A thioacidolysis method tailored for higher-throughput quantitative analysis of lignin monomers

DOE PAGES

Harman-Ware, Anne E.; Foster, Cliff; Happs, Renee M.; ...

2016-09-14

Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β-O-4 linkages. Current thioacidolysis methods are low-throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non-chlorinated organic solvent and is tailored for higher-throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1-2 mg of biomass per assay and has been quantified using fast-GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, includingmore » standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day-to-day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. As a result, the method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses.« less

SOME USES OF MODELS OF QUANTITATIVE GENETIC SELECTION IN SOCIAL SCIENCE.

PubMed

Weight, Michael D; Harpending, Henry

2017-01-01

The theory of selection of quantitative traits is widely used in evolutionary biology, agriculture and other related fields. The fundamental model known as the breeder's equation is simple, robust over short time scales, and it is often possible to estimate plausible parameters. In this paper it is suggested that the results of this model provide useful yardsticks for the description of social traits and the evaluation of transmission models. The differences on a standard personality test between samples of Old Order Amish and Indiana rural young men from the same county and the decline of homicide in Medieval Europe are used as illustrative examples of the overall approach. It is shown that the decline of homicide is unremarkable under a threshold model while the differences between rural Amish and non-Amish young men are too large to be a plausible outcome of simple genetic selection in which assortative mating by affiliation is equivalent to truncation selection.

International ring trial for the validation of an event-specific Golden Rice 2 quantitative real-time polymerase chain reaction method.

PubMed

Jacchia, Sara; Nardini, Elena; Bassani, Niccolò; Savini, Christian; Shim, Jung-Hyun; Trijatmiko, Kurniawan; Kreysa, Joachim; Mazzara, Marco

2015-05-27

This article describes the international validation of the quantitative real-time polymerase chain reaction (PCR) detection method for Golden Rice 2. The method consists of a taxon-specific assay amplifying a fragment of rice Phospholipase D α2 gene, and an event-specific assay designed on the 3' junction between transgenic insert and plant DNA. We validated the two assays independently, with absolute quantification, and in combination, with relative quantification, on DNA samples prepared in haploid genome equivalents. We assessed trueness, precision, efficiency, and linearity of the two assays, and the results demonstrate that both the assays independently assessed and the entire method fulfill European and international requirements for methods for genetically modified organism (GMO) testing, within the dynamic range tested. The homogeneity of the results of the collaborative trial between Europe and Asia is a good indicator of the robustness of the method.

Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

PubMed

Levesque, Ives R; Sled, John G; Pike, G Bruce

2011-09-01

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

A novel quadruplex real-time PCR method for simultaneous detection of Cry2Ae and two genetically modified cotton events (GHB119 and T304-40).

PubMed

Li, Xiang; Wang, Xiuxiu; Yang, Jielin; Liu, Yueming; He, Yuping; Pan, Liangwen

2014-05-16

To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5'-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products.

Automated design of genetic toggle switches with predetermined bistability.

PubMed

Chen, Shuobing; Zhang, Haoqian; Shi, Handuo; Ji, Weiyue; Feng, Jingchen; Gong, Yan; Yang, Zhenglin; Ouyang, Qi

2012-07-20

Synthetic biology aims to rationally construct biological devices with required functionalities. Methods that automate the design of genetic devices without post-hoc adjustment are therefore highly desired. Here we provide a method to predictably design genetic toggle switches with predetermined bistability. To accomplish this task, a biophysical model that links ribosome binding site (RBS) DNA sequence to toggle switch bistability was first developed by integrating a stochastic model with RBS design method. Then, to parametrize the model, a library of genetic toggle switch mutants was experimentally built, followed by establishing the equivalence between RBS DNA sequences and switch bistability. To test this equivalence, RBS nucleotide sequences for different specified bistabilities were in silico designed and experimentally verified. Results show that the deciphered equivalence is highly predictive for the toggle switch design with predetermined bistability. This method can be generalized to quantitative design of other probabilistic genetic devices in synthetic biology.

Embedding Quantitative Methods by Stealth in Political Science: Developing a Pedagogy for Psephology

ERIC Educational Resources Information Center

Gunn, Andrew

2017-01-01

Student evaluations of quantitative methods courses in political science often reveal they are characterised by aversion, alienation and anxiety. As a solution to this problem, this paper describes a pedagogic research project with the aim of embedding quantitative methods by stealth into the first-year undergraduate curriculum. This paper…

QUALITATIVE AND QUANTITATIVE METHODS OF SUICIDE RESEARCH IN OLD AGE.

PubMed

Ojagbemi, A

2017-06-01

This paper examines the merits of the qualitative and quantitative methods of suicide research in the elderly using two studies identified through a free search of the Pubmed database for articles that might have direct bearing on suicidality in the elderly. The studies have been purposively selected for critical appraisal because they meaningfully reflect the quantitative and qualitative divide as well as the social, economic, and cultural boundaries between the elderly living in sub-Saharan Africa and Europe. The paper concludes that an integration of both the qualitative and quantitative research approaches may provide a better platform for unraveling the complex phenomenon of suicide in the elderly.

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

NASA Technical Reports Server (NTRS)

Norga, Koenraad K.; Gurganus, Marjorie C.; Dilda, Christy L.; Yamamoto, Akihiko; Lyman, Richard F.; Patel, Prajal H.; Rubin, Gerald M.; Hoskins, Roger A.; Mackay, Trudy F.; Bellen, Hugo J.

2003-01-01

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

Novel Autism Subtype-Dependent Genetic Variants Are Revealed by Quantitative Trait and Subphenotype Association Analyses of Published GWAS Data

PubMed Central

Hu, Valerie W.; Addington, Anjene; Hyman, Alexander

2011-01-01

The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders. PMID:21556359

Increasing Literacy in Quantitative Methods: The Key to the Future of Canadian Psychology

PubMed Central

Counsell, Alyssa; Cribbie, Robert A.; Harlow, Lisa. L.

2016-01-01

Quantitative methods (QM) dominate empirical research in psychology. Unfortunately most researchers in psychology receive inadequate training in QM. This creates a challenge for researchers who require advanced statistical methods to appropriately analyze their data. Many of the recent concerns about research quality, replicability, and reporting practices are directly tied to the problematic use of QM. As such, improving quantitative literacy in psychology is an important step towards eliminating these concerns. The current paper will include two main sections that discuss quantitative challenges and opportunities. The first section discusses training and resources for students and presents descriptive results on the number of quantitative courses required and available to graduate students in Canadian psychology departments. In the second section, we discuss ways of improving quantitative literacy for faculty, researchers, and clinicians. This includes a strong focus on the importance of collaboration. The paper concludes with practical recommendations for improving quantitative skills and literacy for students and researchers in Canada. PMID:28042199

Increasing Literacy in Quantitative Methods: The Key to the Future of Canadian Psychology.

PubMed

Counsell, Alyssa; Cribbie, Robert A; Harlow, Lisa L

2016-08-01

Quantitative methods (QM) dominate empirical research in psychology. Unfortunately most researchers in psychology receive inadequate training in QM. This creates a challenge for researchers who require advanced statistical methods to appropriately analyze their data. Many of the recent concerns about research quality, replicability, and reporting practices are directly tied to the problematic use of QM. As such, improving quantitative literacy in psychology is an important step towards eliminating these concerns. The current paper will include two main sections that discuss quantitative challenges and opportunities. The first section discusses training and resources for students and presents descriptive results on the number of quantitative courses required and available to graduate students in Canadian psychology departments. In the second section, we discuss ways of improving quantitative literacy for faculty, researchers, and clinicians. This includes a strong focus on the importance of collaboration. The paper concludes with practical recommendations for improving quantitative skills and literacy for students and researchers in Canada.

MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

PubMed

Ristov, Strahil; Brajkovic, Vladimir; Cubric-Curik, Vlatka; Michieli, Ivan; Curik, Ino

2016-09-10

Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source

Quantitative genetic analysis of brain copper and zinc in BXD recombinant inbred mice.

PubMed

Jones, Leslie C; McCarthy, Kristin A; Beard, John L; Keen, Carl L; Jones, Byron C

2006-01-01

Copper and zinc are trace nutrients essential for normal brain function, yet an excess of these elements can be toxic. It is important therefore that these metals be closely regulated. We recently conducted a quantitative trait loci (QTL) analysis to identify chromosomal regions in the mouse containing possible regulatory genes. The animals came from 15 strains of the BXD/Ty recombinant inbred (RI) strain panel and the brain regions analyzed were frontal cortex, caudate-putamen, nucleus accumbens and ventral midbrain. Several QTL were identified for copper and/or zinc, most notably on chromosomes 1, 8, 16 and 17. Genetic correlational analysis also revealed associations between these metals and dopamine, cocaine responses, saccharine preference, immune response and seizure susceptibility. Notably, the QTL on chromosome 17 is also associated with seizure susceptibility and contains the histocompatibility H2 complex. This work shows that regulation of zinc and copper is under polygenic influence and is intimately related to CNS function. Future work will reveal genes underlying the QTL and how they interact with other genes and the environment. More importantly, revelation of the genetic underpinnings of copper and zinc brain homeostasis will aid our understanding of neurological diseases that are related to copper and zinc imbalance.

Regression and Data Mining Methods for Analyses of Multiple Rare Variants in the Genetic Analysis Workshop 17 Mini-Exome Data

PubMed Central

Bailey-Wilson, Joan E.; Brennan, Jennifer S.; Bull, Shelley B; Culverhouse, Robert; Kim, Yoonhee; Jiang, Yuan; Jung, Jeesun; Li, Qing; Lamina, Claudia; Liu, Ying; Mägi, Reedik; Niu, Yue S.; Simpson, Claire L.; Wang, Libo; Yilmaz, Yildiz E.; Zhang, Heping; Zhang, Zhaogong

2012-01-01

Group 14 of Genetic Analysis Workshop 17 examined several issues related to analysis of complex traits using DNA sequence data. These issues included novel methods for analyzing rare genetic variants in an aggregated manner (often termed collapsing rare variants), evaluation of various study designs to increase power to detect effects of rare variants, and the use of machine learning approaches to model highly complex heterogeneous traits. Various published and novel methods for analyzing traits with extreme locus and allelic heterogeneity were applied to the simulated quantitative and disease phenotypes. Overall, we conclude that power is (as expected) dependent on locus-specific heritability or contribution to disease risk, large samples will be required to detect rare causal variants with small effect sizes, extreme phenotype sampling designs may increase power for smaller laboratory costs, methods that allow joint analysis of multiple variants per gene or pathway are more powerful in general than analyses of individual rare variants, population-specific analyses can be optimal when different subpopulations harbor private causal mutations, and machine learning methods may be useful for selecting subsets of predictors for follow-up in the presence of extreme locus heterogeneity and large numbers of potential predictors. PMID:22128066

Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data.

PubMed Central

Orr, H A

1998-01-01

Evolutionary biologists have long sought a way to determine whether a phenotypic difference between two taxa was caused by natural selection or random genetic drift. Here I argue that data from quantitative trait locus (QTL) analyses can be used to test the null hypothesis of neutral phenotypic evolution. I propose a sign test that compares the observed number of plus and minus alleles in the "high line" with that expected under neutrality, conditioning on the known phenotypic difference between the taxa. Rejection of the null hypothesis implies a role for directional natural selection. This test is applicable to any character in any organism in which QTL analysis can be performed. PMID:9691061

Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

ERIC Educational Resources Information Center

Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

Methods of analysis and resources available for genetic trait mapping.

PubMed

Ott, J

1999-01-01

Methods of genetic linkage analysis are reviewed and put in context with other mapping techniques. Sources of information are outlined (books, web sites, computer programs). Special consideration is given to statistical problems in canine genetic mapping (heterozygosity, inbreeding, marker maps).

Nuclear medicine and quantitative imaging research (instrumentation and quantitative methods of evaluation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beck, R.N.; Cooper, M.D.

1990-09-01

This report summarizes goals and accomplishments of the research program supported under DOE Grant No. FG02-86ER60418 entitled Instrumentation and Quantitative Methods of Evaluation, with R. Beck, P. I. and M. Cooper, Co-P.I. during the period January 15, 1990 through September 1, 1990. This program addresses the problems involving the basic science and technology underlying the physical and conceptual tools of radioactive tracer methodology as they relate to the measurement of structural and functional parameters of physiologic importance in health and disease. The principal tool is quantitative radionuclide imaging. The overall objective of this program is to further the development andmore » transfer of radiotracer methodology from basic theory to routine clinical practice in order that individual patients and society as a whole will receive the maximum net benefit from the new knowledge gained. The focus of the research is on the development of new instruments and radiopharmaceuticals, and the evaluation of these through the phase of clinical feasibility. 7 figs.« less

Quantitative Evaluation Method of Each Generation Margin for Power System Planning

NASA Astrophysics Data System (ADS)

Su, Su; Tanaka, Kazuyuki

As the power system deregulation advances, the competition among the power companies becomes heated, and they seek more efficient system planning using existing facilities. Therefore, an efficient system planning method has been expected. This paper proposes a quantitative evaluation method for the (N-1) generation margin considering the overload and the voltage stability restriction. Concerning the generation margin related with the overload, a fast solution method without the recalculation of the (N-1) Y-matrix is proposed. Referred to the voltage stability, this paper proposes an efficient method to search the stability limit. The IEEE30 model system which is composed of 6 generators and 14 load nodes is employed to validate the proposed method. According to the results, the proposed method can reduce the computational cost for the generation margin related with the overload under the (N-1) condition, and specify the value quantitatively.

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses

PubMed Central

Zhang, S; Meng, L; Wang, J; Zhang, L

2017-01-01

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population. PMID:28722705

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses.

PubMed

Zhang, S; Meng, L; Wang, J; Zhang, L

2017-10-01

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population.

Comparison of genetic diversity and population structure of Pacific Coast whitebark pine across multiple markers

Treesearch

Andrew D. Bower; Bryce A. Richardson; Valerie Hipkins; Regina Rochefort; Carol Aubry

2011-01-01

Analysis of "neutral" molecular markers and "adaptive" quantitative traits are common methods of assessing genetic diversity and population structure. Molecular markers typically reflect the effects of demographic and stochastic processes but are generally assumed to not reflect natural selection. Conversely, quantitative (or "adaptive")...

Quantitative determination of casein genetic variants in goat milk: Application in Girgentana dairy goat breed.

PubMed

Montalbano, Maria; Segreto, Roberta; Di Gerlando, Rosalia; Mastrangelo, Salvatore; Sardina, Maria Teresa

2016-02-01

The study was conducted to develop a high-performance liquid chromatographic (HPLC) method to quantify casein genetic variants (αs2-, β-, and κ-casein) in milk of homozygous individuals of Girgentana goat breed. For calibration experiments, pure genetic variants were extracted from individual milk samples of animals with known genotypes. The described HPLC approach was precise, accurate and highly suitable for quantification of goat casein genetic variants of homozygous individuals. The amount of each casein per allele was: αs2-casein A = 2.9 ± 0.8 g/L and F = 1.8 ± 0.4 g/L; β-casein C = 3.0 ± 0.8 g/L and C1 = 2.0 ± 0.7 g/L and κ-casein A = 1.6 ± 0.3 g/L and B = 1.1 ± 0.2 g/L. A good correlation was found between the quantities of αs2-casein genetic variants A and F, and β-casein C and C1 with other previously described method. The main important result was obtained for κ-casein because, till now, no data were available on quantification of single genetic variants for this protein. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics.

PubMed

Yildizoglu, Tugce; Weislogel, Jan-Marek; Mohammad, Farhan; Chan, Edwin S-Y; Assam, Pryseley N; Claridge-Chang, Adam

2015-12-01

Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.

Comparison of Quantitative Antifungal Testing Methods for Textile Fabrics.

PubMed

Imoto, Yasuo; Seino, Satoshi; Nakagawa, Takashi; Yamamoto, Takao A

2017-01-01

　Quantitative antifungal testing methods for textile fabrics under growth-supportive conditions were studied. Fungal growth activities on unfinished textile fabrics and textile fabrics modified with Ag nanoparticles were investigated using the colony counting method and the luminescence method. Morphological changes of the fungi during incubation were investigated by microscopic observation. Comparison of the results indicated that the fungal growth activity values obtained with the colony counting method depended on the morphological state of the fungi on textile fabrics, whereas those obtained with the luminescence method did not. Our findings indicated that unique characteristics of each testing method must be taken into account for the proper evaluation of antifungal activity.

Estimation of genetic parameters and their sampling variances of quantitative traits in the type 2 modified augmented design

USDA-ARS?s Scientific Manuscript database

We proposed a method to estimate the error variance among non-replicated genotypes, thus to estimate the genetic parameters by using replicated controls. We derived formulas to estimate sampling variances of the genetic parameters. Computer simulation indicated that the proposed methods of estimatin...

Quantitative methods for analysing cumulative effects on fish migration success: a review.

PubMed

Johnson, J E; Patterson, D A; Martins, E G; Cooke, S J; Hinch, S G

2012-07-01

It is often recognized, but seldom addressed, that a quantitative assessment of the cumulative effects, both additive and non-additive, of multiple stressors on fish survival would provide a more realistic representation of the factors that influence fish migration. This review presents a compilation of analytical methods applied to a well-studied fish migration, a more general review of quantitative multivariable methods, and a synthesis on how to apply new analytical techniques in fish migration studies. A compilation of adult migration papers from Fraser River sockeye salmon Oncorhynchus nerka revealed a limited number of multivariable methods being applied and the sub-optimal reliance on univariable methods for multivariable problems. The literature review of fisheries science, general biology and medicine identified a large number of alternative methods for dealing with cumulative effects, with a limited number of techniques being used in fish migration studies. An evaluation of the different methods revealed that certain classes of multivariable analyses will probably prove useful in future assessments of cumulative effects on fish migration. This overview and evaluation of quantitative methods gathered from the disparate fields should serve as a primer for anyone seeking to quantify cumulative effects on fish migration survival. © 2012 The Authors. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.

Quantitative genetics and utilization of mutants

USDA-ARS?s Scientific Manuscript database

The relatively low level of genetic variability currently available in cotton makes mutagenesis attractive to overcome this problem. Mutations can occur either spontaneously or be induced. The majority of the genes we use today are spontaneous mutants that developed over a long period of time. Induc...

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Reproducibility of CSF quantitative culture methods for estimating rate of clearance in cryptococcal meningitis.

PubMed

Dyal, Jonathan; Akampurira, Andrew; Rhein, Joshua; Morawski, Bozena M; Kiggundu, Reuben; Nabeta, Henry W; Musubire, Abdu K; Bahr, Nathan C; Williams, Darlisha A; Bicanic, Tihana; Larsen, Robert A; Meya, David B; Boulware, David R

2016-05-01

Quantitative cerebrospinal fluid (CSF) cultures provide a measure of disease severity in cryptococcal meningitis. The fungal clearance rate by quantitative cultures has become a primary endpoint for phase II clinical trials. This study determined the inter-assay accuracy of three different quantitative culture methodologies. Among 91 participants with meningitis symptoms in Kampala, Uganda, during August-November 2013, 305 CSF samples were prospectively collected from patients at multiple time points during treatment. Samples were simultaneously cultured by three methods: (1) St. George's 100 mcl input volume of CSF with five 1:10 serial dilutions, (2) AIDS Clinical Trials Group (ACTG) method using 1000, 100, 10 mcl input volumes, and two 1:100 dilutions with 100 and 10 mcl input volume per dilution on seven agar plates; and (3) 10 mcl calibrated loop of undiluted and 1:100 diluted CSF (loop). Quantitative culture values did not statistically differ between St. George-ACTG methods (P= .09) but did for St. George-10 mcl loop (P< .001). Repeated measures pairwise correlation between any of the methods was high (r≥0.88). For detecting sterility, the ACTG-method had the highest negative predictive value of 97% (91% St. George, 60% loop), but the ACTG-method had occasional (∼10%) difficulties in quantification due to colony clumping. For CSF clearance rate, St. George-ACTG methods did not differ overall (mean -0.05 ± 0.07 log10CFU/ml/day;P= .14) on a group level; however, individual-level clearance varied. The St. George and ACTG quantitative CSF culture methods produced comparable but not identical results. Quantitative cultures can inform treatment management strategies. © The Author 2016. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A novel quadruplex real-time PCR method for simultaneous detection of Cry2Ae and two genetically modified cotton events (GHB119 and T304-40)

PubMed Central

2014-01-01

Background To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. Results To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5′-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. Conclusions The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products. PMID:24884946

Autoradiographic method for quantitation of deposition and distribution of radiocalcium in bone

PubMed Central

Lawrence Riggs, B; Bassingthwaighte, James B.; Jowsey, Jenifer; Peter Pequegnat, E

2010-01-01

A method is described for quantitating autoradiographs of bone-seeking isotopes in microscopic sections of bone. Autoradiographs of bone sections containing 45Ca and internal calibration standards are automatically scanned with a microdensitometer. The digitized optical density output is stored on magnetic tape and is converted by computer to equivalent activity of 45Ca per gram of bone. The computer determines the total 45Ca uptake in the bone section and, on the basis of optical density and anatomic position, quantitatively divides the uptake into 4 components, each representing a separate physiologic process (bone formation, secondary mineralization, diffuse long-term exchange, and surface short-term exchange). The method is also applicable for quantitative analysis of microradiographs of bone sections for mineral content and density. PMID:5416906

Mapping Quantitative Traits in Unselected Families: Algorithms and Examples

PubMed Central

Dupuis, Josée; Shi, Jianxin; Manning, Alisa K.; Benjamin, Emelia J.; Meigs, James B.; Cupples, L. Adrienne; Siegmund, David

2009-01-01

Linkage analysis has been widely used to identify from family data genetic variants influencing quantitative traits. Common approaches have both strengths and limitations. Likelihood ratio tests typically computed in variance component analysis can accommodate large families but are highly sensitive to departure from normality assumptions. Regression-based approaches are more robust but their use has primarily been restricted to nuclear families. In this paper, we develop methods for mapping quantitative traits in moderately large pedigrees. Our methods are based on the score statistic which in contrast to the likelihood ratio statistic, can use nonparametric estimators of variability to achieve robustness of the false positive rate against departures from the hypothesized phenotypic model. Because the score statistic is easier to calculate than the likelihood ratio statistic, our basic mapping methods utilize relatively simple computer code that performs statistical analysis on output from any program that computes estimates of identity-by-descent. This simplicity also permits development and evaluation of methods to deal with multivariate and ordinal phenotypes, and with gene-gene and gene-environment interaction. We demonstrate our methods on simulated data and on fasting insulin, a quantitative trait measured in the Framingham Heart Study. PMID:19278016

Quantitative detection method for Roundup Ready soybean in food using duplex real-time PCR MGB chemistry.

PubMed

Samson, Maria Cristina; Gullì, Mariolina; Marmiroli, Nelson

2010-07-01

Methodologies that enable the detection of genetically modified organisms (GMOs) (authorized and non-authorized) in food and feed strongly influence the potential for adequate updating and implementation of legislation together with labeling requirements. Quantitative polymerase chain reaction (qPCR) systems were designed to boost the sensitivity and specificity on the identification of GMOs in highly degraded DNA samples; however, such testing will become economically difficult to cope with due to increasing numbers of approved genetically modified (GM) lines. Multiplexing approaches are therefore in development to provide cost-efficient solution. Construct-specific primers and probe were developed for quantitative analysis of Roundup Ready soybean (RRS) event glyphosate-tolerant soybean (GTS) 40-3-2. The lectin gene (Le1) was used as a reference gene, and its specificity was verified. RRS- and Le1-specific quantitative real-time PCR (qRTPCR) were optimized in a duplex platform that has been validated with respect to limit of detection (LOD) and limit of quantification (LOQ), as well as accuracy. The analysis of model processed food samples showed that the degradation of DNA has no adverse or little effects on the performance of quantification assay. In this study, a duplex qRTPCR using TaqMan minor groove binder-non-fluorescent quencher (MGB-NFQ) chemistry was developed for specific detection and quantification of RRS event GTS 40-3-2 that can be used for practical monitoring in processed food products.

A Method for Aircraft Concept Selection Using Multicriteria Interactive Genetic Algorithms

NASA Technical Reports Server (NTRS)

Buonanno, Michael; Mavris, Dimitri

2005-01-01

The problem of aircraft concept selection has become increasingly difficult in recent years as a result of a change from performance as the primary evaluation criteria of aircraft concepts to the current situation in which environmental effects, economics, and aesthetics must also be evaluated and considered in the earliest stages of the decision-making process. This has prompted a shift from design using historical data regression techniques for metric prediction to the use of physics-based analysis tools that are capable of analyzing designs outside of the historical database. The use of optimization methods with these physics-based tools, however, has proven difficult because of the tendency of optimizers to exploit assumptions present in the models and drive the design towards a solution which, while promising to the computer, may be infeasible due to factors not considered by the computer codes. In addition to this difficulty, the number of discrete options available at this stage may be unmanageable due to the combinatorial nature of the concept selection problem, leading the analyst to arbitrarily choose a sub-optimum baseline vehicle. These concept decisions such as the type of control surface scheme to use, though extremely important, are frequently made without sufficient understanding of their impact on the important system metrics because of a lack of computational resources or analysis tools. This paper describes a hybrid subjective/quantitative optimization method and its application to the concept selection of a Small Supersonic Transport. The method uses Genetic Algorithms to operate on a population of designs and promote improvement by varying more than sixty parameters governing the vehicle geometry, mission, and requirements. In addition to using computer codes for evaluation of quantitative criteria such as gross weight, expert input is also considered to account for criteria such as aeroelasticity or manufacturability which may be impossible or

[Quantitative and qualitative research methods, can they coexist yet?].

PubMed

Hunt, Elena; Lavoie, Anne-Marise

2011-06-01

Qualitative design is gaining ground in Nursing research. In spite of a relative progress however, the evidence based practice movement continues to dominate and to underline the exclusive value of quantitative design (particularly that of randomized clinical trials) for clinical decision making. In the actual context convenient to those in power making utilitarian decisions on one hand, and facing nursing criticism of the establishment in favor of qualitative research on the other hand, it is difficult to chose a practical and ethical path that values the nursing role within the health care system, keeping us committed to quality care and maintaining researcher's integrity. Both qualitative and quantitative methods have advantages and disadvantages, and clearly, none of them can, by itself, capture, describe and explain reality adequately. Therefore, a balance between the two methods is needed. Researchers bare responsibility to society and science, and they should opt for the appropriate design susceptible to answering the research question, not promote the design favored by the research funding distributors.

A quantitative framework for the forward design of synthetic miRNA circuits.

PubMed

Bloom, Ryan J; Winkler, Sally M; Smolke, Christina D

2014-11-01

Synthetic genetic circuits incorporating regulatory components based on RNA interference (RNAi) have been used in a variety of systems. A comprehensive understanding of the parameters that determine the relationship between microRNA (miRNA) and target expression levels is lacking. We describe a quantitative framework supporting the forward engineering of gene circuits that incorporate RNAi-based regulatory components in mammalian cells. We developed a model that captures the quantitative relationship between miRNA and target gene expression levels as a function of parameters, including mRNA half-life and miRNA target-site number. We extended the model to synthetic circuits that incorporate protein-responsive miRNA switches and designed an optimized miRNA-based protein concentration detector circuit that noninvasively measures small changes in the nuclear concentration of β-catenin owing to induction of the Wnt signaling pathway. Our results highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable and predictable behaviors in mammalian cells.

Quantitation of valve regurgitation severity by three-dimensional vena contracta area is superior to flow convergence method of quantitation on transesophageal echocardiography.

PubMed

Abudiab, Muaz M; Chao, Chieh-Ju; Liu, Shuang; Naqvi, Tasneem Z

2017-07-01

Quantitation of regurgitation severity using the proximal isovelocity acceleration (PISA) method to calculate effective regurgitant orifice (ERO) area has limitations. Measurement of three-dimensional (3D) vena contracta area (VCA) accurately grades mitral regurgitation (MR) severity on transthoracic echocardiography (TTE). We evaluated 3D VCA quantitation of regurgitant jet severity using 3D transesophageal echocardiography (TEE) in 110 native mitral, aortic, and tricuspid valves and six prosthetic valves in patients with at least mild valvular regurgitation. The ASE-recommended integrative method comprising semiquantitative and quantitative assessment of valvular regurgitation was used as a reference method, including ERO area by 2D PISA for assigning severity of regurgitation grade. Mean age was 62.2±14.4 years; 3D VCA quantitation was feasible in 91% regurgitant valves compared to 78% by the PISA method. When both methods were feasible and in the presence of a single regurgitant jet, 3D VCA and 2D PISA were similar in differentiating assigned severity (ANOVAP<.001). In valves with multiple jets, however, 3D VCA had a better correlation to assigned severity (ANOVAP<.0001). The agreement of 2D PISA and 3D VCA with the integrative method was 47% and 58% for moderate and 65% and 88% for severe regurgitation, respectively. Measurement of 3D VCA by TEE is superior to the 2D PISA method in determination of regurgitation severity in multiple native and prosthetic valves. © 2017, Wiley Periodicals, Inc.

Genetics-based methods for detection of Salmonella spp. in foods.

PubMed

Mozola, Mark A

2006-01-01

Genetic methods are now at the forefront of foodborne pathogen testing. The sensitivity, specificity, and inclusivity advantages offered by deoxyribonucleic acid (DNA) probe technology have driven an intense effort in methods development over the past 20 years. DNA probe-based methods for Salmonella spp. and other pathogens have progressed from time-consuming procedures involving the use of radioisotopes to simple, high throughput, automated assays. The analytical sensitivity of nucleic acid amplification technology has facilitated a reduction in analysis time by allowing enriched samples to be tested for previously undetectable quantities of analyte. This article will trace the evolution of the development of genetic methods for detection of Salmonella in foods, review the basic assay formats and their advantages and limitations, and discuss method performance characteristics and considerations for selection of methods.

Baculovirus expression system and method for high throughput expression of genetic material

DOEpatents

Clark, Robin; Davies, Anthony

2001-01-01

The present invention provides novel recombinant baculovirus expression systems for expressing foreign genetic material in a host cell. Such expression systems are readily adapted to an automated method for expression foreign genetic material in a high throughput manner. In other aspects, the present invention features a novel automated method for determining the function of foreign genetic material by transfecting the same into a host by way of the recombinant baculovirus expression systems according to the present invention.

Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis.

PubMed

Diego, Vincent P; de Chaves, Raquel Nichele; Blangero, John; de Souza, Michele Caroline; Santos, Daniel; Gomes, Thayse Natacha; dos Santos, Fernanda Karina; Garganta, Rui; Katzmarzyk, Peter T; Maia, José A R

2015-08-01

The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families. The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF). Sex-specific effects were assessed by genotype-by-sex interaction (GSI) models and sex-specific heritabilities. GSI effects and heterogeneity were tested in the residual environmental variance. SPSS 17 and SOLAR v. 4.1 were used in all computations. The genetic component for PA and SB domains varied from low to moderate (11% to 46%), when analyzing both genders combined. We found GSI effects for vigorous PA (p = 0.02) and time spent watching television (WT) (p < 0.001) that showed significantly higher additive genetic variance estimates in males. The heterogeneity in the residual environmental variance was significant for moderate PA (p = 0.02), vigorous PA (p = 0.006) and total PA (p = 0.001). Sex-specific heritability estimates were significantly higher in males only for WT, with a male-to-female difference in heritability of 42.5 (95% confidence interval: 6.4, 70.4). Low to moderate genetic effects on PA and SB traits were found. Results from the GSI model show that there are sex-specific effects in two phenotypes, VPA and WT with a stronger genetic influence in males.

Novel Quantitative Real-Time LCR for the Sensitive Detection of SNP Frequencies in Pooled DNA: Method Development, Evaluation and Application

PubMed Central

Psifidi, Androniki; Dovas, Chrysostomos; Banos, Georgios

2011-01-01

Background Single nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture. A variety of methods exist for SNP detection but few can quantify SNP frequencies when the mutated DNA molecules correspond to a small fraction of the wild-type DNA. Furthermore, there is no generally accepted gold standard for SNP quantification, and, in general, currently applied methods give inconsistent results in selected cohorts. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples. Methods The development and evaluation of a novel Ligase Chain Reaction (LCR) protocol that uses a DNA-specific fluorescent dye to allow quantitative real-time analysis is described. Different reaction components and thermocycling parameters affecting the efficiency and specificity of LCR were examined. Several protocols, including gap-LCR modifications, were evaluated using plasmid standard and genomic DNA pools. A protocol of choice was identified and applied for the quantification of a polymorphism at codon 136 of the ovine PRNP gene that is associated with susceptibility to a transmissible spongiform encephalopathy in sheep. Conclusions The real-time LCR protocol developed in the present study showed high sensitivity, accuracy, reproducibility and a wide dynamic range of SNP quantification in different DNA pools. The limits of detection and quantification of SNP frequencies were 0.085% and 0.35%, respectively. Significance The proposed real-time LCR protocol is applicable when sensitive detection and accurate quantification of low copy number mutations in DNA pools is needed. Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food. PMID:21283808

Quantitative genetics of secondary hip joint osteoarthritis in a Labrador Retriever-Greyhound pedigree.

PubMed

Hays, Laurel; Zhang, Zhiwu; Mateescu, Raluca G; Lust, George; Burton-Wurster, Nancy I; Todhunter, Rory J

2007-01-01

To evaluate the quantitative inheritance of secondary hip joint osteoarthritis in a canine pedigree. 137 Labrador Retrievers, Greyhounds, and mixed-breed dogs. Necropsy scores ranging from 0 to 4 were obtained for each hip joint. Seven unaffected Greyhounds with normal hip joint conformation were also used for genetic modeling, but were not euthanized. Sixty-six male and 71 female dogs were allocated to 2 groups (< or = 12 months of age and > 12 months of age). Statistical models were developed to establish the inheritance pattern of hip joint osteoarthritis that developed secondary to hip dysplasia. 62 dogs had evidence of osteoarthritis in a hip joint, and 75 had no evidence of osteoarthritis. After sex was adjusted for, the necropsy score was found to be inherited additively but without dominance. Each Labrador Retriever allele increased the necropsy score by 0.7 to 0.9 points, compared with the Greyhound allele, and male sex increased the necropsy score 0.74 over female sex. Approximately 10% of the variation in necropsy score was attributable to the litter of puppies' origin. Because secondary hip joint osteoarthritis is inherited additively, selection pressure could be applied to reduce its incidence. Similar statistical models can be used in linkage and association mapping to detect the genes in the underlying quantitative trait loci that contribute to hip joint osteoarthritis.

Comparison study on qualitative and quantitative risk assessment methods for urban natural gas pipeline network.

PubMed

Han, Z Y; Weng, W G

2011-05-15

In this paper, a qualitative and a quantitative risk assessment methods for urban natural gas pipeline network are proposed. The qualitative method is comprised of an index system, which includes a causation index, an inherent risk index, a consequence index and their corresponding weights. The quantitative method consists of a probability assessment, a consequences analysis and a risk evaluation. The outcome of the qualitative method is a qualitative risk value, and for quantitative method the outcomes are individual risk and social risk. In comparison with previous research, the qualitative method proposed in this paper is particularly suitable for urban natural gas pipeline network, and the quantitative method takes different consequences of accidents into consideration, such as toxic gas diffusion, jet flame, fire ball combustion and UVCE. Two sample urban natural gas pipeline networks are used to demonstrate these two methods. It is indicated that both of the two methods can be applied to practical application, and the choice of the methods depends on the actual basic data of the gas pipelines and the precision requirements of risk assessment. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Novel quantitative real-time LCR for the sensitive detection of SNP frequencies in pooled DNA: method development, evaluation and application.

PubMed

Psifidi, Androniki; Dovas, Chrysostomos; Banos, Georgios

2011-01-19

Single nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture. A variety of methods exist for SNP detection but few can quantify SNP frequencies when the mutated DNA molecules correspond to a small fraction of the wild-type DNA. Furthermore, there is no generally accepted gold standard for SNP quantification, and, in general, currently applied methods give inconsistent results in selected cohorts. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples. The development and evaluation of a novel Ligase Chain Reaction (LCR) protocol that uses a DNA-specific fluorescent dye to allow quantitative real-time analysis is described. Different reaction components and thermocycling parameters affecting the efficiency and specificity of LCR were examined. Several protocols, including gap-LCR modifications, were evaluated using plasmid standard and genomic DNA pools. A protocol of choice was identified and applied for the quantification of a polymorphism at codon 136 of the ovine PRNP gene that is associated with susceptibility to a transmissible spongiform encephalopathy in sheep. The real-time LCR protocol developed in the present study showed high sensitivity, accuracy, reproducibility and a wide dynamic range of SNP quantification in different DNA pools. The limits of detection and quantification of SNP frequencies were 0.085% and 0.35%, respectively. The proposed real-time LCR protocol is applicable when sensitive detection and accurate quantification of low copy number mutations in DNA pools is needed. Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food.

A 100-year review: Methods and impact of genetic selection in dairy cattle—From daughter–dam comparisons to deep learning algorithms

USDA-ARS?s Scientific Manuscript database

In the early 1900s, breed society herdbooks had been established, and milk recording programs were in their infancy. Farmers were interested in improving the productivity of dairy cattle, but the foundations of population genetics, quantitative genetics, and animal breeding had not yet been laid. Li...

How powerful are summary-based methods for identifying expression-trait associations under different genetic architectures?

PubMed

Veturi, Yogasudha; Ritchie, Marylyn D

2018-01-01

Transcriptome-wide association studies (TWAS) have recently been employed as an approach that can draw upon the advantages of genome-wide association studies (GWAS) and gene expression studies to identify genes associated with complex traits. Unlike standard GWAS, summary level data suffices for TWAS and offers improved statistical power. Two popular TWAS methods include either (a) imputing the cis genetic component of gene expression from smaller sized studies (using multi-SNP prediction or MP) into much larger effective sample sizes afforded by GWAS - TWAS-MP or (b) using summary-based Mendelian randomization - TWAS-SMR. Although these methods have been effective at detecting functional variants, it remains unclear how extensive variability in the genetic architecture of complex traits and diseases impacts TWAS results. Our goal was to investigate the different scenarios under which these methods yielded enough power to detect significant expression-trait associations. In this study, we conducted extensive simulations based on 6000 randomly chosen, unrelated Caucasian males from Geisinger's MyCode population to compare the power to detect cis expression-trait associations (within 500 kb of a gene) using the above-described approaches. To test TWAS across varying genetic backgrounds we simulated gene expression and phenotype using different quantitative trait loci per gene and cis-expression /trait heritability under genetic models that differentiate the effect of causality from that of pleiotropy. For each gene, on a training set ranging from 100 to 1000 individuals, we either (a) estimated regression coefficients with gene expression as the response using five different methods: LASSO, elastic net, Bayesian LASSO, Bayesian spike-slab, and Bayesian ridge regression or (b) performed eQTL analysis. We then sampled with replacement 50,000, 150,000, and 300,000 individuals respectively from the testing set of the remaining 5000 individuals and conducted GWAS on each

Mixing Qualitative and Quantitative Methods: Insights into Design and Analysis Issues

ERIC Educational Resources Information Center

Lieber, Eli

2009-01-01

This article describes and discusses issues related to research design and data analysis in the mixing of qualitative and quantitative methods. It is increasingly desirable to use multiple methods in research, but questions arise as to how best to design and analyze the data generated by mixed methods projects. I offer a conceptualization for such…

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour.

PubMed

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E; Kayser, Manfred

2017-02-27

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour

PubMed Central

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H.; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R.; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E.; Kayser, Manfred

2017-01-01

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing. PMID:28240252

Criteria for quantitative and qualitative data integration: mixed-methods research methodology.

PubMed

Lee, Seonah; Smith, Carrol A M

2012-05-01

Many studies have emphasized the need and importance of a mixed-methods approach for evaluation of clinical information systems. However, those studies had no criteria to guide integration of multiple data sets. Integrating different data sets serves to actualize the paradigm that a mixed-methods approach argues; thus, we require criteria that provide the right direction to integrate quantitative and qualitative data. The first author used a set of criteria organized from a literature search for integration of multiple data sets from mixed-methods research. The purpose of this article was to reorganize the identified criteria. Through critical appraisal of the reasons for designing mixed-methods research, three criteria resulted: validation, complementarity, and discrepancy. In applying the criteria to empirical data of a previous mixed methods study, integration of quantitative and qualitative data was achieved in a systematic manner. It helped us obtain a better organized understanding of the results. The criteria of this article offer the potential to produce insightful analyses of mixed-methods evaluations of health information systems.

Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

PubMed

Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

2015-11-13

The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science

A Method for Comprehensive Glycosite-Mapping and Direct Quantitation of Serum Glycoproteins.

PubMed

Hong, Qiuting; Ruhaak, L Renee; Stroble, Carol; Parker, Evan; Huang, Jincui; Maverakis, Emanual; Lebrilla, Carlito B

2015-12-04

A comprehensive glycan map was constructed for the top eight abundant glycoproteins in plasma using both specific and nonspecific enzyme digestions followed by nano liquid chromatography (LC)-chip/quadrupole time-of-flight mass spectrometry (MS) analysis. Glycopeptides were identified using an in-house software tool, GPFinder. A sensitive and reproducible multiple reaction monitoring (MRM) technique on a triple quadrupole MS was developed and applied to quantify immunoglobulins G, A, M, and their site-specific glycans simultaneously and directly from human serum/plasma without protein enrichments. A total of 64 glycopeptides and 15 peptides were monitored for IgG, IgA, and IgM in a 20 min ultra high performance (UP)LC gradient. The absolute protein contents were quantified using peptide calibration curves. The glycopeptide ion abundances were normalized to the respective protein abundances to separate protein glycosylation from protein expression. This technique yields higher method reproducibility and less sample loss when compared with the quantitation method that involves protein enrichments. The absolute protein quantitation has a wide linear range (3-4 orders of magnitude) and low limit of quantitation (femtomole level). This rapid and robust quantitation technique, which provides quantitative information for both proteins and glycosylation, will further facilitate disease biomarker discoveries.

Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype

PubMed Central

Kappen, Claudia

2016-01-01

The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes. PMID:26800342

Analytical methods for quantitation of prenylated flavonoids from hops.

PubMed

Nikolić, Dejan; van Breemen, Richard B

2013-01-01

The female flowers of hops ( Humulus lupulus L.) are used as a flavoring agent in the brewing industry. There is growing interest in possible health benefits of hops, particularly as estrogenic and chemopreventive agents. Among the possible active constituents, most of the attention has focused on prenylated flavonoids, which can chemically be classified as prenylated chalcones and prenylated flavanones. Among chalcones, xanthohumol (XN) and desmethylxanthohumol (DMX) have been the most studied, while among flavanones, 8-prenylnaringenin (8-PN) and 6-prenylnaringenin (6-PN) have received the most attention. Because of the interest in medicinal properties of prenylated flavonoids, there is demand for accurate, reproducible and sensitive analytical methods to quantify these compounds in various matrices. Such methods are needed, for example, for quality control and standardization of hop extracts, measurement of the content of prenylated flavonoids in beer, and to determine pharmacokinetic properties of prenylated flavonoids in animals and humans. This review summarizes currently available analytical methods for quantitative analysis of the major prenylated flavonoids, with an emphasis on the LC-MS and LC-MS-MS methods and their recent applications to biomedical research on hops. This review covers all methods in which prenylated flavonoids have been measured, either as the primary analytes or as a part of a larger group of analytes. The review also discusses methodological issues relating to the quantitative analysis of these compounds regardless of the chosen analytical approach.

Quantitative impact characterization of aeronautical CFRP materials with non-destructive testing methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kiefel, Denis, E-mail: Denis.Kiefel@airbus.com, E-mail: Rainer.Stoessel@airbus.com; Stoessel, Rainer, E-mail: Denis.Kiefel@airbus.com, E-mail: Rainer.Stoessel@airbus.com; Grosse, Christian, E-mail: Grosse@tum.de

2015-03-31

In recent years, an increasing number of safety-relevant structures are designed and manufactured from carbon fiber reinforced polymers (CFRP) in order to reduce weight of airplanes by taking the advantage of their specific strength into account. Non-destructive testing (NDT) methods for quantitative defect analysis of damages are liquid- or air-coupled ultrasonic testing (UT), phased array ultrasonic techniques, and active thermography (IR). The advantage of these testing methods is the applicability on large areas. However, their quantitative information is often limited on impact localization and size. In addition to these techniques, Airbus Group Innovations operates a micro x-ray computed tomography (μ-XCT)more » system, which was developed for CFRP characterization. It is an open system which allows different kinds of acquisition, reconstruction, and data evaluation. One main advantage of this μ-XCT system is its high resolution with 3-dimensional analysis and visualization opportunities, which enables to gain important quantitative information for composite part design and stress analysis. Within this study, different NDT methods will be compared at CFRP samples with specified artificial impact damages. The results can be used to select the most suitable NDT-method for specific application cases. Furthermore, novel evaluation and visualization methods for impact analyzes are developed and will be presented.« less

Evaluating methods to visualize patterns of genetic differentiation on a landscape.

PubMed

House, Geoffrey L; Hahn, Matthew W

2018-05-01

With advances in sequencing technology, research in the field of landscape genetics can now be conducted at unprecedented spatial and genomic scales. This has been especially evident when using sequence data to visualize patterns of genetic differentiation across a landscape due to demographic history, including changes in migration. Two recent model-based visualization methods that can highlight unusual patterns of genetic differentiation across a landscape, SpaceMix and EEMS, are increasingly used. While SpaceMix's model can infer long-distance migration, EEMS' model is more sensitive to short-distance changes in genetic differentiation, and it is unclear how these differences may affect their results in various situations. Here, we compare SpaceMix and EEMS side by side using landscape genetics simulations representing different migration scenarios. While both methods excel when patterns of simulated migration closely match their underlying models, they can produce either un-intuitive or misleading results when the simulated migration patterns match their models less well, and this may be difficult to assess in empirical data sets. We also introduce unbundled principal components (un-PC), a fast, model-free method to visualize patterns of genetic differentiation by combining principal components analysis (PCA), which is already used in many landscape genetics studies, with the locations of sampled individuals. Un-PC has characteristics of both SpaceMix and EEMS and works well with simulated and empirical data. Finally, we introduce msLandscape, a collection of tools that streamline the creation of customizable landscape-scale simulations using the popular coalescent simulator ms and conversion of the simulated data for use with un-PC, SpaceMix and EEMS. © 2017 John Wiley & Sons Ltd.

Development and application of absolute quantitative detection by duplex chamber-based digital PCR of genetically modified maize events without pretreatment steps.

PubMed

Zhu, Pengyu; Fu, Wei; Wang, Chenguang; Du, Zhixin; Huang, Kunlun; Zhu, Shuifang; Xu, Wentao

2016-04-15

The possibility of the absolute quantitation of GMO events by digital PCR was recently reported. However, most absolute quantitation methods based on the digital PCR required pretreatment steps. Meanwhile, singleplex detection could not meet the demand of the absolute quantitation of GMO events that is based on the ratio of foreign fragments and reference genes. Thus, to promote the absolute quantitative detection of different GMO events by digital PCR, we developed a quantitative detection method based on duplex digital PCR without pretreatment. Moreover, we tested 7 GMO events in our study to evaluate the fitness of our method. The optimized combination of foreign and reference primers, limit of quantitation (LOQ), limit of detection (LOD) and specificity were validated. The results showed that the LOQ of our method for different GMO events was 0.5%, while the LOD is 0.1%. Additionally, we found that duplex digital PCR could achieve the detection results with lower RSD compared with singleplex digital PCR. In summary, the duplex digital PCR detection system is a simple and stable way to achieve the absolute quantitation of different GMO events. Moreover, the LOQ and LOD indicated that this method is suitable for the daily detection and quantitation of GMO events. Copyright © 2016 Elsevier B.V. All rights reserved.

Novel method for quantitative ANA measurement using near-infrared imaging.

PubMed

Peterson, Lisa K; Wells, Daniel; Shaw, Laura; Velez, Maria-Gabriela; Harbeck, Ronald; Dragone, Leonard L

2009-09-30

Antinuclear antibodies (ANA) have been detected in patients with systemic rheumatic diseases and are used in the screening and/or diagnosis of autoimmunity in patients as well as mouse models of systemic autoimmunity. Indirect immunofluorescence (IIF) on HEp-2 cells is the gold standard for ANA screening. However, its usefulness is limited in diagnosis, prognosis and monitoring of disease activity due to the lack of standardization in performing the technique, subjectivity in interpreting the results and the fact that it is only semi-quantitative. Various immunological techniques have been developed in an attempt to improve upon the method to quantify ANA, including enzyme-linked immunosorbent assays (ELISAs), line immunoassays (LIAs), multiplexed bead immunoassays and IIF on substrates other than HEp-2 cells. Yet IIF on HEp-2 cells remains the most common screening method for ANA. In this study, we describe a simple quantitative method to detect ANA which combines IIF on HEp-2 coated slides with analysis using a near-infrared imaging (NII) system. Using NII to determine ANA titer, 86.5% (32 of 37) of the titers for human patient samples were within 2 dilutions of those determined by IIF, which is the acceptable range for proficiency testing. Combining an initial screening for nuclear staining using microscopy with titration by NII resulted in 97.3% (36 of 37) of the titers detected to be within two dilutions of those determined by IIF. The NII method for quantitative ANA measurements using serum from both patients and mice with autoimmunity provides a fast, relatively simple, objective, sensitive and reproducible assay, which could easily be standardized for comparison between laboratories.

Mixed methods in gerontological research: Do the qualitative and quantitative data “touch”?

PubMed Central

Happ, Mary Beth

2010-01-01

This paper distinguishes between parallel and integrated mixed methods research approaches. Barriers to integrated mixed methods approaches in gerontological research are discussed and critiqued. The author presents examples of mixed methods gerontological research to illustrate approaches to data integration at the levels of data analysis, interpretation, and research reporting. As a summary of the methodological literature, four basic levels of mixed methods data combination are proposed. Opportunities for mixing qualitative and quantitative data are explored using contemporary examples from published studies. Data transformation and visual display, judiciously applied, are proposed as pathways to fuller mixed methods data integration and analysis. Finally, practical strategies for mixing qualitative and quantitative data types are explicated as gerontological research moves beyond parallel mixed methods approaches to achieve data integration. PMID:20077973

Toward automatic phenotyping of retinal images from genetically determined mono- and dizygotic twins using amplitude modulation-frequency modulation methods

NASA Astrophysics Data System (ADS)

Soliz, P.; Davis, B.; Murray, V.; Pattichis, M.; Barriga, S.; Russell, S.

2010-03-01

This paper presents an image processing technique for automatically categorize age-related macular degeneration (AMD) phenotypes from retinal images. Ultimately, an automated approach will be much more precise and consistent in phenotyping of retinal diseases, such as AMD. We have applied the automated phenotyping to retina images from a cohort of mono- and dizygotic twins. The application of this technology will allow one to perform more quantitative studies that will lead to a better understanding of the genetic and environmental factors associated with diseases such as AMD. A method for classifying retinal images based on features derived from the application of amplitude-modulation frequency-modulation (AM-FM) methods is presented. Retinal images from identical and fraternal twins who presented with AMD were processed to determine whether AM-FM could be used to differentiate between the two types of twins. Results of the automatic classifier agreed with the findings of other researchers in explaining the variation of the disease between the related twins. AM-FM features classified 72% of the twins correctly. Visual grading found that genetics could explain between 46% and 71% of the variance.

Quantitative methods used in Australian health promotion research: a review of publications from 1992-2002.

PubMed

Smith, Ben J; Zehle, Katharina; Bauman, Adrian E; Chau, Josephine; Hawkshaw, Barbara; Frost, Steven; Thomas, Margaret

2006-04-01

This study examined the use of quantitative methods in Australian health promotion research in order to identify methodological trends and priorities for strengthening the evidence base for health promotion. Australian health promotion articles were identified by hand searching publications from 1992-2002 in six journals: Health Promotion Journal of Australia, Australian and New Zealand journal of Public Health, Health Promotion International, Health Education Research, Health Education and Behavior and the American Journal of Health Promotion. The study designs and statistical methods used in articles presenting quantitative research were recorded. 591 (57.7%) of the 1,025 articles used quantitative methods. Cross-sectional designs were used in the majority (54.3%) of studies with pre- and post-test (14.6%) and post-test only (9.5%) the next most common designs. Bivariate statistical methods were used in 45.9% of papers, multivariate methods in 27.1% and simple numbers and proportions in 25.4%. Few studies used higher-level statistical techniques. While most studies used quantitative methods, the majority were descriptive in nature. The study designs and statistical methods used provided limited scope for demonstrating intervention effects or understanding the determinants of change.

Applying quantitative benefit-risk analysis to aid regulatory decision making in diagnostic imaging: methods, challenges, and opportunities.

PubMed

Agapova, Maria; Devine, Emily Beth; Bresnahan, Brian W; Higashi, Mitchell K; Garrison, Louis P

2014-09-01

Health agencies making regulatory marketing-authorization decisions use qualitative and quantitative approaches to assess expected benefits and expected risks associated with medical interventions. There is, however, no universal standard approach that regulatory agencies consistently use to conduct benefit-risk assessment (BRA) for pharmaceuticals or medical devices, including for imaging technologies. Economics, health services research, and health outcomes research use quantitative approaches to elicit preferences of stakeholders, identify priorities, and model health conditions and health intervention effects. Challenges to BRA in medical devices are outlined, highlighting additional barriers in radiology. Three quantitative methods--multi-criteria decision analysis, health outcomes modeling and stated-choice survey--are assessed using criteria that are important in balancing benefits and risks of medical devices and imaging technologies. To be useful in regulatory BRA, quantitative methods need to: aggregate multiple benefits and risks, incorporate qualitative considerations, account for uncertainty, and make clear whose preferences/priorities are being used. Each quantitative method performs differently across these criteria and little is known about how BRA estimates and conclusions vary by approach. While no specific quantitative method is likely to be the strongest in all of the important areas, quantitative methods may have a place in BRA of medical devices and radiology. Quantitative BRA approaches have been more widely applied in medicines, with fewer BRAs in devices. Despite substantial differences in characteristics of pharmaceuticals and devices, BRA methods may be as applicable to medical devices and imaging technologies as they are to pharmaceuticals. Further research to guide the development and selection of quantitative BRA methods for medical devices and imaging technologies is needed. Copyright © 2014 AUR. Published by Elsevier Inc. All rights

A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods

PubMed Central

Jha, Abhinav K; Caffo, Brian; Frey, Eric C

2016-01-01

The objective optimization and evaluation of nuclear-medicine quantitative imaging methods using patient data is highly desirable but often hindered by the lack of a gold standard. Previously, a regression-without-truth (RWT) approach has been proposed for evaluating quantitative imaging methods in the absence of a gold standard, but this approach implicitly assumes that bounds on the distribution of true values are known. Several quantitative imaging methods in nuclear-medicine imaging measure parameters where these bounds are not known, such as the activity concentration in an organ or the volume of a tumor. We extended upon the RWT approach to develop a no-gold-standard (NGS) technique for objectively evaluating such quantitative nuclear-medicine imaging methods with patient data in the absence of any ground truth. Using the parameters estimated with the NGS technique, a figure of merit, the noise-to-slope ratio (NSR), can be computed, which can rank the methods on the basis of precision. An issue with NGS evaluation techniques is the requirement of a large number of patient studies. To reduce this requirement, the proposed method explored the use of multiple quantitative measurements from the same patient, such as the activity concentration values from different organs in the same patient. The proposed technique was evaluated using rigorous numerical experiments and using data from realistic simulation studies. The numerical experiments demonstrated that the NSR was estimated accurately using the proposed NGS technique when the bounds on the distribution of true values were not precisely known, thus serving as a very reliable metric for ranking the methods on the basis of precision. In the realistic simulation study, the NGS technique was used to rank reconstruction methods for quantitative single-photon emission computed tomography (SPECT) based on their performance on the task of estimating the mean activity concentration within a known volume of interest

A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods.

PubMed

Jha, Abhinav K; Caffo, Brian; Frey, Eric C

2016-04-07

The objective optimization and evaluation of nuclear-medicine quantitative imaging methods using patient data is highly desirable but often hindered by the lack of a gold standard. Previously, a regression-without-truth (RWT) approach has been proposed for evaluating quantitative imaging methods in the absence of a gold standard, but this approach implicitly assumes that bounds on the distribution of true values are known. Several quantitative imaging methods in nuclear-medicine imaging measure parameters where these bounds are not known, such as the activity concentration in an organ or the volume of a tumor. We extended upon the RWT approach to develop a no-gold-standard (NGS) technique for objectively evaluating such quantitative nuclear-medicine imaging methods with patient data in the absence of any ground truth. Using the parameters estimated with the NGS technique, a figure of merit, the noise-to-slope ratio (NSR), can be computed, which can rank the methods on the basis of precision. An issue with NGS evaluation techniques is the requirement of a large number of patient studies. To reduce this requirement, the proposed method explored the use of multiple quantitative measurements from the same patient, such as the activity concentration values from different organs in the same patient. The proposed technique was evaluated using rigorous numerical experiments and using data from realistic simulation studies. The numerical experiments demonstrated that the NSR was estimated accurately using the proposed NGS technique when the bounds on the distribution of true values were not precisely known, thus serving as a very reliable metric for ranking the methods on the basis of precision. In the realistic simulation study, the NGS technique was used to rank reconstruction methods for quantitative single-photon emission computed tomography (SPECT) based on their performance on the task of estimating the mean activity concentration within a known volume of interest

A Framework for Mixing Methods in Quantitative Measurement Development, Validation, and Revision: A Case Study

ERIC Educational Resources Information Center

Luyt, Russell

2012-01-01

A framework for quantitative measurement development, validation, and revision that incorporates both qualitative and quantitative methods is introduced. It extends and adapts Adcock and Collier's work, and thus, facilitates understanding of quantitative measurement development, validation, and revision as an integrated and cyclical set of…

Quantitative methods in electroencephalography to access therapeutic response.

PubMed

Diniz, Roseane Costa; Fontenele, Andrea Martins Melo; Carmo, Luiza Helena Araújo do; Ribeiro, Aurea Celeste da Costa; Sales, Fábio Henrique Silva; Monteiro, Sally Cristina Moutinho; Sousa, Ana Karoline Ferreira de Castro

2016-07-01

Pharmacometrics or Quantitative Pharmacology aims to quantitatively analyze the interaction between drugs and patients whose tripod: pharmacokinetics, pharmacodynamics and disease monitoring to identify variability in drug response. Being the subject of central interest in the training of pharmacists, this work was out with a view to promoting this idea on methods to access the therapeutic response of drugs with central action. This paper discusses quantitative methods (Fast Fourier Transform, Magnitude Square Coherence, Conditional Entropy, Generalised Linear semi-canonical Correlation Analysis, Statistical Parametric Network and Mutual Information Function) used to evaluate the EEG signals obtained after administration regimen of drugs, the main findings and their clinical relevance, pointing it as a contribution to construction of different pharmaceutical practice. Peter Anderer et. al in 2000 showed the effect of 20mg of buspirone in 20 healthy subjects after 1, 2, 4, 6 and 8h after oral ingestion of the drug. The areas of increased power of the theta frequency occurred mainly in the temporo-occipital - parietal region. It has been shown by Sampaio et al., 2007 that the use of bromazepam, which allows the release of GABA (gamma amino butyric acid), an inhibitory neurotransmitter of the central nervous system could theoretically promote dissociation of cortical functional areas, a decrease of functional connectivity, a decrease of cognitive functions by means of smaller coherence (electrophysiological magnitude measured from the EEG by software) values. Ahmad Khodayari-Rostamabad et al. in 2015 talk that such a measure could be a useful clinical tool potentially to assess adverse effects of opioids and hence give rise to treatment guidelines. There was the relation between changes in pain intensity and brain sources (at maximum activity locations) during remifentanil infusion despite its potent analgesic effect. The statement of mathematical and computational

Bayesian data augmentation methods for the synthesis of qualitative and quantitative research findings

PubMed Central

Crandell, Jamie L.; Voils, Corrine I.; Chang, YunKyung; Sandelowski, Margarete

2010-01-01

The possible utility of Bayesian methods for the synthesis of qualitative and quantitative research has been repeatedly suggested but insufficiently investigated. In this project, we developed and used a Bayesian method for synthesis, with the goal of identifying factors that influence adherence to HIV medication regimens. We investigated the effect of 10 factors on adherence. Recognizing that not all factors were examined in all studies, we considered standard methods for dealing with missing data and chose a Bayesian data augmentation method. We were able to summarize, rank, and compare the effects of each of the 10 factors on medication adherence. This is a promising methodological development in the synthesis of qualitative and quantitative research. PMID:21572970

Quantitative Urine Culture Method Using a Plastic „Paddle” Containing Dual Media

PubMed Central

Craig, William A.; Kunin, Calvin M.

1972-01-01

A new dip-inoculum method for quantitative urine culture is described which utilizes a dual-chambered plastic „paddle” housing both a general purpose and differential medium. Comparative bacterial counts of 1,000 clinical specimens using the pour plate and this device were identical in 82.9% and within a factor of five in 95.6%. The „paddle” detected all but 19 of 258 specimens (92.6%) with 100,000 or greater colonies per ml. This simple, convenient method should allow more extensive use of quantitative urine culture in the diagnosis and follow-up of patients with urinary tract infections in office practice. It should not be considered as a substitute for the more definitive pour plate method or for standard methods for characterization of bacteriological species when more exact information is required. PMID:4555636

Quantitative Imaging in Cancer Evolution and Ecology

PubMed Central

Grove, Olya; Gillies, Robert J.

2013-01-01

Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral

Simple and rapid method for isolation and quantitation of polyhydroxyalkanoate by SDS-sonication treatment.

PubMed

Arikawa, Hisashi; Sato, Shunsuke; Fujiki, Tetsuya; Matsumoto, Keiji

2017-08-01

We developed a new method for isolation and quantitation of polyhydroxyalkanoate (PHA) from culture broth. In this method, the cells were sonicated in sodium dodecyl sulfate (SDS) solution and centrifuged to recover PHA. The recovered PHA was rinsed with deionized water and ethanol, and then weighed after drying. Hazardous chemicals such as chloroform, methanol, and sulfuric acid were not used, and no expensive analytical instruments were needed. We applied this method to Cupriavidus necator culture broths that included various amounts of poly(3-hydroxybutyrate) (PHB) or poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBHHx) from flasks and jar fermentors. The quantitation by this method was practical for use with a wide range of production amounts and PHA monomer compositions compared to the conventional whole-cell methanolysis method with gas chromatographic analysis, and besides, the recovered PHAs were adequately pure (≥96% purity). Therefore, this new method would be valuable not only for quantitation of PHA but also for preparation of samples to characterize their mechanical properties. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

MR Imaging-based Semi-quantitative Methods for Knee Osteoarthritis

PubMed Central

JARRAYA, Mohamed; HAYASHI, Daichi; ROEMER, Frank Wolfgang; GUERMAZI, Ali

2016-01-01

Magnetic resonance imaging (MRI)-based semi-quantitative (SQ) methods applied to knee osteoarthritis (OA) have been introduced during the last decade and have fundamentally changed our understanding of knee OA pathology since then. Several epidemiological studies and clinical trials have used MRI-based SQ methods to evaluate different outcome measures. Interest in MRI-based SQ scoring system has led to continuous update and refinement. This article reviews the different SQ approaches for MRI-based whole organ assessment of knee OA and also discuss practical aspects of whole joint assessment. PMID:26632537

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Quantitative, Qualitative and Geospatial Methods to Characterize HIV Risk Environments.

PubMed

Conners, Erin E; West, Brooke S; Roth, Alexis M; Meckel-Parker, Kristen G; Kwan, Mei-Po; Magis-Rodriguez, Carlos; Staines-Orozco, Hugo; Clapp, John D; Brouwer, Kimberly C

2016-01-01

Increasingly, 'place', including physical and geographical characteristics as well as social meanings, is recognized as an important factor driving individual and community health risks. This is especially true among marginalized populations in low and middle income countries (LMIC), whose environments may also be more difficult to study using traditional methods. In the NIH-funded longitudinal study Mapa de Salud, we employed a novel approach to exploring the risk environment of female sex workers (FSWs) in two Mexico/U.S. border cities, Tijuana and Ciudad Juárez. In this paper we describe the development, implementation, and feasibility of a mix of quantitative and qualitative tools used to capture the HIV risk environments of FSWs in an LMIC setting. The methods were: 1) Participatory mapping; 2) Quantitative interviews; 3) Sex work venue field observation; 4) Time-location-activity diaries; 5) In-depth interviews about daily activity spaces. We found that the mixed-methodology outlined was both feasible to implement and acceptable to participants. These methods can generate geospatial data to assess the role of the environment on drug and sexual risk behaviors among high risk populations. Additionally, the adaptation of existing methods for marginalized populations in resource constrained contexts provides new opportunities for informing public health interventions.

Quantitative, Qualitative and Geospatial Methods to Characterize HIV Risk Environments

PubMed Central

Conners, Erin E.; West, Brooke S.; Roth, Alexis M.; Meckel-Parker, Kristen G.; Kwan, Mei-Po; Magis-Rodriguez, Carlos; Staines-Orozco, Hugo; Clapp, John D.; Brouwer, Kimberly C.

2016-01-01

Increasingly, ‘place’, including physical and geographical characteristics as well as social meanings, is recognized as an important factor driving individual and community health risks. This is especially true among marginalized populations in low and middle income countries (LMIC), whose environments may also be more difficult to study using traditional methods. In the NIH-funded longitudinal study Mapa de Salud, we employed a novel approach to exploring the risk environment of female sex workers (FSWs) in two Mexico/U.S. border cities, Tijuana and Ciudad Juárez. In this paper we describe the development, implementation, and feasibility of a mix of quantitative and qualitative tools used to capture the HIV risk environments of FSWs in an LMIC setting. The methods were: 1) Participatory mapping; 2) Quantitative interviews; 3) Sex work venue field observation; 4) Time-location-activity diaries; 5) In-depth interviews about daily activity spaces. We found that the mixed-methodology outlined was both feasible to implement and acceptable to participants. These methods can generate geospatial data to assess the role of the environment on drug and sexual risk behaviors among high risk populations. Additionally, the adaptation of existing methods for marginalized populations in resource constrained contexts provides new opportunities for informing public health interventions. PMID:27191846

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Technical Performance Assessment

PubMed Central

2017-01-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined. PMID:24919831

Genetic variance of tolerance and the toxicant threshold model.

PubMed

Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

2012-04-01

A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change. Copyright © 2012 SETAC.

A scoring system for appraising mixed methods research, and concomitantly appraising qualitative, quantitative and mixed methods primary studies in Mixed Studies Reviews.

PubMed

Pluye, Pierre; Gagnon, Marie-Pierre; Griffiths, Frances; Johnson-Lafleur, Janique

2009-04-01

A new form of literature review has emerged, Mixed Studies Review (MSR). These reviews include qualitative, quantitative and mixed methods studies. In the present paper, we examine MSRs in health sciences, and provide guidance on processes that should be included and reported. However, there are no valid and usable criteria for concomitantly appraising the methodological quality of the qualitative, quantitative and mixed methods studies. To propose criteria for concomitantly appraising the methodological quality of qualitative, quantitative and mixed methods studies or study components. A three-step critical review was conducted. 2322 references were identified in MEDLINE, and their titles and abstracts were screened; 149 potentially relevant references were selected and the full-text papers were examined; 59 MSRs were retained and scrutinized using a deductive-inductive qualitative thematic data analysis. This revealed three types of MSR: convenience, reproducible, and systematic. Guided by a proposal, we conducted a qualitative thematic data analysis of the quality appraisal procedures used in the 17 systematic MSRs (SMSRs). Of 17 SMSRs, 12 showed clear quality appraisal procedures with explicit criteria but no SMSR used valid checklists to concomitantly appraise qualitative, quantitative and mixed methods studies. In two SMSRs, criteria were developed following a specific procedure. Checklists usually contained more criteria than needed. In four SMSRs, a reliability assessment was described or mentioned. While criteria for quality appraisal were usually based on descriptors that require specific methodological expertise (e.g., appropriateness), no SMSR described the fit between reviewers' expertise and appraised studies. Quality appraisal usually resulted in studies being ranked by methodological quality. A scoring system is proposed for concomitantly appraising the methodological quality of qualitative, quantitative and mixed methods studies for SMSRs. This

Quantitative magnetic resonance micro-imaging methods for pharmaceutical research.

PubMed

Mantle, M D

2011-09-30

The use of magnetic resonance imaging (MRI) as a tool in pharmaceutical research is now well established and the current literature covers a multitude of different pharmaceutically relevant research areas. This review focuses on the use of quantitative magnetic resonance micro-imaging techniques and how they have been exploited to extract information that is of direct relevance to the pharmaceutical industry. The article is divided into two main areas. The first half outlines the theoretical aspects of magnetic resonance and deals with basic magnetic resonance theory, the effects of nuclear spin-lattice (T(1)), spin-spin (T(2)) relaxation and molecular diffusion upon image quantitation, and discusses the applications of rapid magnetic resonance imaging techniques. In addition to the theory, the review aims to provide some practical guidelines for the pharmaceutical researcher with an interest in MRI as to which MRI pulse sequences/protocols should be used and when. The second half of the article reviews the recent advances and developments that have appeared in the literature concerning the use of quantitative micro-imaging methods to pharmaceutically relevant research. Copyright © 2010 Elsevier B.V. All rights reserved.

Virtualising the Quantitative Research Methods Course: An Island-Based Approach

ERIC Educational Resources Information Center

Baglin, James; Reece, John; Baker, Jenalle

2015-01-01

Many recent improvements in pedagogical practice have been enabled by the rapid development of innovative technologies, particularly for teaching quantitative research methods and statistics. This study describes the design, implementation, and evaluation of a series of specialised computer laboratory sessions. The sessions combined the use of an…

A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.

PubMed

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-04-01

Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.

Genetically Informative Research on Adolescent Substance Use: Methods, Findings, and Challenges

ERIC Educational Resources Information Center

Lynskey, Michael T.; Agrawal, Arpana; Heath, Andrew C.

2010-01-01

Objective: To provide an overview of the genetic epidemiology of substance use and misuse in adolescents. Method: A selective review of genetically informative research strategies, their limitations, and key findings examining issues related to the heritability of substance use and substance use disorders in children and adolescents is presented.…

Method for the Simultaneous Quantitation of Apolipoprotein E Isoforms using Tandem Mass Spectrometry

PubMed Central

Wildsmith, Kristin R.; Han, Bomie; Bateman, Randall J.

2009-01-01

Using Apolipoprotein E (ApoE) as a model protein, we developed a protein isoform analysis method utilizing Stable Isotope Labeling Tandem Mass Spectrometry (SILT MS). ApoE isoforms are quantitated using the intensities of the b and y ions of the 13C-labeled tryptic isoform-specific peptides versus unlabeled tryptic isoform-specific peptides. The ApoE protein isoform analysis using SILT allows for the simultaneous detection and relative quantitation of different ApoE isoforms from the same sample. This method provides a less biased assessment of ApoE isoforms compared to antibody-dependent methods, and may lead to a better understanding of the biological differences between isoforms. PMID:19653990

Quantitative genetic analysis of the body composition and blood pressure association in two ethnically diverse populations.

PubMed

Ghosh, Sudipta; Dosaev, Tasbulat; Prakash, Jai; Livshits, Gregory

2017-04-01

The major aim of this study was to conduct comparative quantitative-genetic analysis of the body composition (BCP) and somatotype (STP) variation, as well as their correlations with blood pressure (BP) in two ethnically, culturally and geographically different populations: Santhal, indigenous ethnic group from India and Chuvash, indigenous population from Russia. Correspondently two pedigree-based samples were collected from 1,262 Santhal and1,558 Chuvash individuals, respectively. At the first stage of the study, descriptive statistics and a series of univariate regression analyses were calculated. Finally, multiple and multivariate regression (MMR) analyses, with BP measurements as dependent variables and age, sex, BCP and STP as independent variables were carried out in each sample separately. The significant and independent covariates of BP were identified and used for re-examination in pedigree-based variance decomposition analysis. Despite clear and significant differences between the populations in BCP/STP, both Santhal and Chuvash were found to be predominantly mesomorphic irrespective of their sex. According to MMR analyses variation of BP significantly depended on age and mesomorphic component in both samples, and in addition on sex, ectomorphy and fat mass index in Santhal and on fat free mass index in Chuvash samples, respectively. Additive genetic component contributes to a substantial proportion of blood pressure and body composition variance. Variance component analysis in addition to above mentioned results suggests that additive genetic factors influence BP and BCP/STP associations significantly. © 2017 Wiley Periodicals, Inc.

Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in Brassica rapa Fast Plants

PubMed Central

Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dósa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question “What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev),” we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students’ cognitive structures before and after the unit and explanations in students’ final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on “variation” as a proposed threshold concept and primary goal for students’ explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from “plug and play,” this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. PMID:25185225

Study books on ADHD genetics: balanced or biased?

PubMed

Te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-06-01

Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master's programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics' outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them.

A method for the quantitative determination of crystalline phases by X-ray

NASA Technical Reports Server (NTRS)

Petzenhauser, I.; Jaeger, P.

1988-01-01

A mineral analysis method is described for rapid quantitative determination of crystalline substances in those cases in which the sample is present in pure form or in a mixture of known composition. With this method there is no need for prior chemical analysis.

Validation of a Spectral Method for Quantitative Measurement of Color in Protein Drug Solutions.

PubMed

Yin, Jian; Swartz, Trevor E; Zhang, Jian; Patapoff, Thomas W; Chen, Bartolo; Marhoul, Joseph; Shih, Norman; Kabakoff, Bruce; Rahimi, Kimia

2016-01-01

A quantitative spectral method has been developed to precisely measure the color of protein solutions. In this method, a spectrophotometer is utilized for capturing the visible absorption spectrum of a protein solution, which can then be converted to color values (L*a*b*) that represent human perception of color in a quantitative three-dimensional space. These quantitative values (L*a*b*) allow for calculating the best match of a sample's color to a European Pharmacopoeia reference color solution. In order to qualify this instrument and assay for use in clinical quality control, a technical assessment was conducted to evaluate the assay suitability and precision. Setting acceptance criteria for this study required development and implementation of a unique statistical method for assessing precision in 3-dimensional space. Different instruments, cuvettes, protein solutions, and analysts were compared in this study. The instrument accuracy, repeatability, and assay precision were determined. The instrument and assay are found suitable for use in assessing color of drug substances and drug products and is comparable to the current European Pharmacopoeia visual assessment method. In the biotechnology industry, a visual assessment is the most commonly used method for color characterization, batch release, and stability testing of liquid protein drug solutions. Using this method, an analyst visually determines the color of the sample by choosing the closest match to a standard color series. This visual method can be subjective because it requires an analyst to make a judgment of the best match of color of the sample to the standard color series, and it does not capture data on hue and chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we developed a quantitative spectral method for color determination that greatly reduces the variability in measuring color and allows

The Future of Genetics in Psychology and Psychiatry: Microarrays, Genome-Wide Association, and Non-Coding RNA

ERIC Educational Resources Information Center

Plomin, Robert; Davis, Oliver S. P.

2009-01-01

Background: Much of what we thought we knew about genetics needs to be modified in light of recent discoveries. What are the implications of these advances for identifying genes responsible for the high heritability of many behavioural disorders and dimensions in childhood? Methods: Although quantitative genetics such as twin studies will continue…

[Analytic methods for seed models with genotype x environment interactions].

PubMed

Zhu, J

1996-01-01

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by

Physical methods for genetic transformation of fungi and yeast

NASA Astrophysics Data System (ADS)

Rivera, Ana Leonor; Magaña-Ortíz, Denis; Gómez-Lim, Miguel; Fernández, Francisco; Loske, Achim M.

2014-06-01

The production of transgenic fungi is a routine process. Currently, it is possible to insert genes from other fungi, viruses, bacteria and even animals, albeit with low efficiency, into the genomes of a number of fungal species. Genetic transformation requires the penetration of the transgene through the fungal cell wall, a process that can be facilitated by biological or physical methods. Novel methodologies for the efficient introduction of specific genes and stronger promoters are needed to increase production levels. A possible solution to this problem is the recently discovered shock-wave-mediated transformation. The objective of this article is to review the state of the art of the physical methods used for genetic fungi transformation and to describe some of the basic physics and molecular biology behind them.

A method for the extraction and quantitation of phycoerythrin from algae

NASA Technical Reports Server (NTRS)

Stewart, D. E.

1982-01-01

A summary of a new technique for the extraction and quantitation of phycoerythrin (PHE) from algal samples is described. Results of analysis of four extracts representing three PHE types from algae including cryptomonad and cyanophyte types are presented. The method of extraction and an equation for quantitation are given. A graph showing the relationship of concentration and fluorescence units that may be used with samples fluorescing around 575-580 nm (probably dominated by cryptophytes in estuarine waters) and 560 nm (dominated by cyanophytes characteristics of the open ocean) is provided.

Comparison of PCR and quantitative real-time PCR methods for the characterization of ruminant and cattle fecal pollution sources.

PubMed

Raith, Meredith R; Kelty, Catherine A; Griffith, John F; Schriewer, Alexander; Wuertz, Stefan; Mieszkin, Sophie; Gourmelon, Michele; Reischer, Georg H; Farnleitner, Andreas H; Ervin, Jared S; Holden, Patricia A; Ebentier, Darcy L; Jay, Jennifer A; Wang, Dan; Boehm, Alexandria B; Aw, Tiong Gim; Rose, Joan B; Balleste, E; Meijer, W G; Sivaganesan, Mano; Shanks, Orin C

2013-11-15

The State of California has mandated the preparation of a guidance document on the application of fecal source identification methods for recreational water quality management. California contains the fifth highest population of cattle in the United States, making the inclusion of cow-associated methods a logical choice. Because the performance of these methods has been shown to change based on geography and/or local animal feeding practices, laboratory comparisons are needed to determine which assays are best suited for implementation. We describe the performance characterization of two end-point PCR assays (CF128 and CF193) and five real-time quantitative PCR (qPCR) assays (Rum2Bac, BacR, BacCow, CowM2, and CowM3) reported to be associated with either ruminant or cattle feces. Each assay was tested against a blinded set of 38 reference challenge filters (19 duplicate samples) containing fecal pollution from 12 different sources suspected to impact water quality. The abundance of each host-associated genetic marker was measured for qPCR-based assays in both target and non-target animals and compared to quantities of total DNA mass, wet mass of fecal material, as well as Bacteroidales, and enterococci determined by 16S rRNA qPCR and culture-based approaches (enterococci only). Ruminant- and cow-associated genetic markers were detected in all filters containing a cattle fecal source. However, some assays cross-reacted with non-target pollution sources. A large amount of variability was evident across laboratories when protocols were not fixed suggesting that protocol standardization will be necessary for widespread implementation. Finally, performance metrics indicate that the cattle-associated CowM2 qPCR method combined with either the BacR or Rum2Bac ruminant-associated methods are most suitable for implementation. Published by Elsevier Ltd.

An improved transmutation method for quantitative determination of the components in multicomponent overlapping chromatograms.

PubMed

Shao, Xueguang; Yu, Zhengliang; Ma, Chaoxiong

2004-06-01

An improved method is proposed for the quantitative determination of multicomponent overlapping chromatograms based on a known transmutation method. To overcome the main limitation of the transmutation method caused by the oscillation generated in the transmutation process, two techniques--wavelet transform smoothing and the cubic spline interpolation for reducing data points--were adopted, and a new criterion was also developed. By using the proposed algorithm, the oscillation can be suppressed effectively, and quantitative determination of the components in both the simulated and experimental overlapping chromatograms is successfully obtained.

Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method

PubMed Central

Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

2014-01-01

Objective To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. Methods TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Results Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. Conclusions The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil. PMID:25182282

Biological characteristics of crucian by quantitative inspection method

NASA Astrophysics Data System (ADS)

Chu, Mengqi

2015-04-01

Biological characteristics of crucian by quantitative inspection method Through quantitative inspection method , the biological characteristics of crucian was preliminary researched. Crucian , Belongs to Cypriniformes, Cyprinidae, Carassius auratus, is a kind of main plant-eating omnivorous fish,like Gregarious, selection and ranking. Crucian are widely distributed, perennial water all over the country all have production. Determine the indicators of crucian in the experiment, to understand the growth, reproduction situation of crucian in this area . Using the measured data (such as the scale length ,scale size and wheel diameter and so on) and related functional to calculate growth of crucian in any one year.According to the egg shape, color, weight ,etc to determine its maturity, with the mean egg diameter per 20 eggs and the number of eggs per 0.5 grams, to calculate the relative and absolute fecundity of the fish .Measured crucian were female puberty. Based on the relation between the scale diameter and length and the information, linear relationship between crucian scale diameter and length: y=1.530+3.0649. From the data, the fertility and is closely relative to the increase of age. The older, the more mature gonad development. The more amount of eggs. In addition, absolute fecundity increases with the pituitary gland.Through quantitative check crucian bait food intake by the object, reveals the main food, secondary foods, and chance food of crucian ,and understand that crucian degree of be fond of of all kinds of bait organisms.Fish fertility with weight gain, it has the characteristics of species and populations, and at the same tmes influenced by the age of the individual, body length, body weight, environmental conditions (especially the nutrition conditions), and breeding habits, spawning times factors and the size of the egg. After a series of studies of crucian biological character, provide the ecological basis for local crucian's feeding, breeding

Development, Validation, and Interlaboratory Evaluation of a Quantitative Multiplexing Method To Assess Levels of Ten Endogenous Allergens in Soybean Seed and Its Application to Field Trials Spanning Three Growing Seasons.

PubMed

Hill, Ryan C; Oman, Trent J; Wang, Xiujuan; Shan, Guomin; Schafer, Barry; Herman, Rod A; Tobias, Rowel; Shippar, Jeff; Malayappan, Bhaskar; Sheng, Li; Xu, Austin; Bradshaw, Jason

2017-07-12

As part of the regulatory approval process in Europe, comparison of endogenous soybean allergen levels between genetically engineered (GE) and non-GE plants has been requested. A quantitative multiplex analytical method using tandem mass spectrometry was developed and validated to measure 10 potential soybean allergens from soybean seed. The analytical method was implemented at six laboratories to demonstrate the robustness of the method and further applied to three soybean field studies across multiple growing seasons (including 21 non-GE soybean varieties) to assess the natural variation of allergen levels. The results show environmental factors contribute more than genetic factors to the large variation in allergen abundance (2- to 50-fold between environmental replicates) as well as a large contribution of Gly m 5 and Gly m 6 to the total allergen profile, calling into question the scientific rational for measurement of endogenous allergen levels between GE and non-GE varieties in the safety assessment.

Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2014-01-01

Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289

Quantitative structure-activity relationship of the curcumin-related compounds using various regression methods

NASA Astrophysics Data System (ADS)

Khazaei, Ardeshir; Sarmasti, Negin; Seyf, Jaber Yousefi

2016-03-01

Quantitative structure activity relationship were used to study a series of curcumin-related compounds with inhibitory effect on prostate cancer PC-3 cells, pancreas cancer Panc-1 cells, and colon cancer HT-29 cells. Sphere exclusion method was used to split data set in two categories of train and test set. Multiple linear regression, principal component regression and partial least squares were used as the regression methods. In other hand, to investigate the effect of feature selection methods, stepwise, Genetic algorithm, and simulated annealing were used. In two cases (PC-3 cells and Panc-1 cells), the best models were generated by a combination of multiple linear regression and stepwise (PC-3 cells: r2 = 0.86, q2 = 0.82, pred_r2 = 0.93, and r2m (test) = 0.43, Panc-1 cells: r2 = 0.85, q2 = 0.80, pred_r2 = 0.71, and r2m (test) = 0.68). For the HT-29 cells, principal component regression with stepwise (r2 = 0.69, q2 = 0.62, pred_r2 = 0.54, and r2m (test) = 0.41) is the best method. The QSAR study reveals descriptors which have crucial role in the inhibitory property of curcumin-like compounds. 6ChainCount, T_C_C_1, and T_O_O_7 are the most important descriptors that have the greatest effect. With a specific end goal to design and optimization of novel efficient curcumin-related compounds it is useful to introduce heteroatoms such as nitrogen, oxygen, and sulfur atoms in the chemical structure (reduce the contribution of T_C_C_1 descriptor) and increase the contribution of 6ChainCount and T_O_O_7 descriptors. Models can be useful in the better design of some novel curcumin-related compounds that can be used in the treatment of prostate, pancreas, and colon cancers.

A collimator optimization method for quantitative imaging: application to Y-90 bremsstrahlung SPECT.

PubMed

Rong, Xing; Frey, Eric C

2013-08-01

Post-therapy quantitative 90Y bremsstrahlung single photon emission computed tomography (SPECT) has shown great potential to provide reliable activity estimates, which are essential for dose verification. Typically 90Y imaging is performed with high- or medium-energy collimators. However, the energy spectrum of 90Y bremsstrahlung photons is substantially different than typical for these collimators. In addition, dosimetry requires quantitative images, and collimators are not typically optimized for such tasks. Optimizing a collimator for 90Y imaging is both novel and potentially important. Conventional optimization methods are not appropriate for 90Y bremsstrahlung photons, which have a continuous and broad energy distribution. In this work, the authors developed a parallel-hole collimator optimization method for quantitative tasks that is particularly applicable to radionuclides with complex emission energy spectra. The authors applied the proposed method to develop an optimal collimator for quantitative 90Y bremsstrahlung SPECT in the context of microsphere radioembolization. To account for the effects of the collimator on both the bias and the variance of the activity estimates, the authors used the root mean squared error (RMSE) of the volume of interest activity estimates as the figure of merit (FOM). In the FOM, the bias due to the null space of the image formation process was taken in account. The RMSE was weighted by the inverse mass to reflect the application to dosimetry; for a different application, more relevant weighting could easily be adopted. The authors proposed a parameterization for the collimator that facilitates the incorporation of the important factors (geometric sensitivity, geometric resolution, and septal penetration fraction) determining collimator performance, while keeping the number of free parameters describing the collimator small (i.e., two parameters). To make the optimization results for quantitative 90Y bremsstrahlung SPECT more

A new method to evaluate image quality of CBCT images quantitatively without observers

PubMed Central

Shimizu, Mayumi; Okamura, Kazutoshi; Yoshida, Shoko; Weerawanich, Warangkana; Tokumori, Kenji; Jasa, Gainer R; Yoshiura, Kazunori

2017-01-01

Objectives: To develop an observer-free method for quantitatively evaluating the image quality of CBCT images by applying just-noticeable difference (JND). Methods: We used two test objects: (1) a Teflon (polytetrafluoroethylene) plate phantom attached to a dry human mandible; and (2) a block phantom consisting of a Teflon step phantom and an aluminium step phantom. These phantoms had holes with different depths. They were immersed in water and scanned with a CB MercuRay (Hitachi Medical Corporation, Tokyo, Japan) at tube voltages of 120 kV, 100 kV, 80 kV and 60 kV. Superimposed images of the phantoms with holes were used for evaluation. The number of detectable holes was used as an index of image quality. In detecting holes quantitatively, the threshold grey value (ΔG), which differentiated holes from the background, was calculated using a specific threshold (the JND), and we extracted the holes with grey values above ΔG. The indices obtained by this quantitative method (the extracted hole values) were compared with the observer evaluations (the observed hole values). In addition, the contrast-to-noise ratio (CNR) of the shallowest detectable holes and the deepest undetectable holes were measured to evaluate the contribution of CNR to detectability. Results: The results of this evaluation method corresponded almost exactly with the evaluations made by observers. The extracted hole values reflected the influence of different tube voltages. All extracted holes had an area with a CNR of ≥1.5. Conclusions: This quantitative method of evaluating CBCT image quality may be more useful and less time-consuming than evaluation by observation. PMID:28045343

Regeneration Methods Affect Genetic Variation and Structure in Shortleaf Pine (Pinus Echinata Mill.)

Treesearch

Rajiv G. Raja; Charles G. Tauer; Robert F. Wittwer; Yinghua Huang

1998-01-01

The effects of regene ration methods on genetic diversity and structure in shortleaf pine (Pinus echinata Mill.) were examined by quantifying the changes in genetic composition of shortleaf pine stands following harvest by monitoring changes in allele number and frequency at heterozygous loci over time. The results were also compared to the genetic...

Easy calculations of lod scores and genetic risks on small computers.

PubMed Central

Lathrop, G M; Lalouel, J M

1984-01-01

A computer program that calculates lod scores and genetic risks for a wide variety of both qualitative and quantitative genetic traits is discussed. An illustration is given of the joint use of a genetic marker, affection status, and quantitative information in counseling situations regarding Duchenne muscular dystrophy. PMID:6585139

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to

A New Kinetic Spectrophotometric Method for the Quantitation of Amorolfine.

PubMed

Soto, César; Poza, Cristian; Contreras, David; Yáñez, Jorge; Nacaratte, Fallon; Toral, M Inés

2017-01-01

Amorolfine (AOF) is a compound with fungicide activity based on the dual inhibition of growth of the fungal cell membrane, the biosynthesis and accumulation of sterols, and the reduction of ergosterol. In this work a sensitive kinetic and spectrophotometric method for the AOF quantitation based on the AOF oxidation by means of KMnO 4 at 30 min (fixed time), pH alkaline, and ionic strength controlled was developed. Measurements of changes in absorbance at 610 nm were used as criterion of the oxidation progress. In order to maximize the sensitivity, different experimental reaction parameters were carefully studied via factorial screening and optimized by multivariate method. The linearity, intraday, and interday assay precision and accuracy were determined. The absorbance-concentration plot corresponding to tap water spiked samples was rectilinear, over the range of 7.56 × 10 -6 -3.22 × 10 -5  mol L -1 , with detection and quantitation limits of 2.49 × 10 -6  mol L -1 and 7.56 × 10 -6  mol L -1 , respectively. The proposed method was successfully validated for the application of the determination of the drug in the spiked tap water samples and the percentage recoveries were 94.0-105.0%. The method is simple and does not require expensive instruments or complicated extraction steps of the reaction product.

Quantitative determination and validation of octreotide acetate using 1 H-NMR spectroscopy with internal standard method.

PubMed

Yu, Chen; Zhang, Qian; Xu, Peng-Yao; Bai, Yin; Shen, Wen-Bin; Di, Bin; Su, Meng-Xiang

2018-01-01

Quantitative nuclear magnetic resonance (qNMR) is a well-established technique in quantitative analysis. We presented a validated 1 H-qNMR method for assay of octreotide acetate, a kind of cyclic octopeptide. Deuterium oxide was used to remove the undesired exchangeable peaks, which was referred to as proton exchange, in order to make the quantitative signals isolated in the crowded spectrum of the peptide and ensure precise quantitative analysis. Gemcitabine hydrochloride was chosen as the suitable internal standard. Experimental conditions, including relaxation delay time, the numbers of scans, and pulse angle, were optimized first. Then method validation was carried out in terms of selectivity, stability, linearity, precision, and robustness. The assay result was compared with that by means of high performance liquid chromatography, which is provided by Chinese Pharmacopoeia. The statistical F test, Student's t test, and nonparametric test at 95% confidence level indicate that there was no significant difference between these two methods. qNMR is a simple and accurate quantitative tool with no need for specific corresponding reference standards. It has the potential of the quantitative analysis of other peptide drugs and standardization of the corresponding reference standards. Copyright © 2017 John Wiley & Sons, Ltd.

Genes, Environment, and Race: Quantitative Genetic Approaches

ERIC Educational Resources Information Center

Whitfield, Keith E.; McClearn, Gerald

2005-01-01

Understanding the origins of racial health disparities is currently a central focus of health-oriented funding agencies and the health policy community. In particular, the role of genetics in the origin of racial health disparities is receiving growing attention and has been susceptible to considerable misinterpretation. In this article, the…

Study books on ADHD genetics: balanced or biased?

PubMed Central

te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-01-01

ABSTRACT Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master’s programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics’ outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them. PMID:28532325

Objectives, criteria and methods for using molecular genetic data in priority setting for conservation of animal genetic resources.

PubMed

Boettcher, P J; Tixier-Boichard, M; Toro, M A; Simianer, H; Eding, H; Gandini, G; Joost, S; Garcia, D; Colli, L; Ajmone-Marsan, P

2010-05-01

The genetic diversity of the world's livestock populations is decreasing, both within and across breeds. A wide variety of factors has contributed to the loss, replacement or genetic dilution of many local breeds. Genetic variability within the more common commercial breeds has been greatly decreased by selectively intense breeding programmes. Conservation of livestock genetic variability is thus important, especially when considering possible future changes in production environments. The world has more than 7500 livestock breeds and conservation of all of them is not feasible. Therefore, prioritization is needed. The objective of this article is to review the state of the art in approaches for prioritization of breeds for conservation, particularly those approaches that consider molecular genetic information, and to identify any shortcomings that may restrict their application. The Weitzman method was among the first and most well-known approaches for utilization of molecular genetic information in conservation prioritization. This approach balances diversity and extinction probability to yield an objective measure of conservation potential. However, this approach was designed for decision making across species and measures diversity as distinctiveness. For livestock, prioritization will most commonly be performed among breeds within species, so alternatives that measure diversity as co-ancestry (i.e. also within-breed variability) have been proposed. Although these methods are technically sound, their application has generally been limited to research studies; most existing conservation programmes have effectively primarily based decisions on extinction risk. The development of user-friendly software incorporating these approaches may increase their rate of utilization.

Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method.

PubMed

Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

2014-02-01

To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.

Identification and quantification of three genetically modified insect resistant cotton lines using conventional and TaqMan real-time polymerase chain reaction methods.

PubMed

Yang, Litao; Pan, Aihu; Zhang, Kewei; Guo, Jinchao; Yin, Changsong; Chen, Jianxiu; Huang, Cheng; Zhang, Dabing

2005-08-10

As the genetically modified organisms (GMOs) labeling policies are issued in many countries, qualitative and quantitative polymerase chain reaction (PCR) techniques are increasingly used for the detection of genetically modified (GM) crops in foods. Qualitative PCR and TaqMan real-time quantitative PCR methods to detect and identify three varieties of insect resistant cotton, i.e., Mon531 cotton (Monsanto Co.) and GK19 and SGK321 cottons (Chinese Academy of Agricultural Sciences), which were approved for commercialization in China, were developed in this paper. Primer pairs specific to inserted DNAs, such as Cowpea trypsin inhibitor (CpTI) gene of SGK321 cotton and the specific junction DNA sequences containing partial Cry1A(c) gene and NOS terminator of Mon531, GK19, and SGK321 cotton varieties were designed to conduct the identified PCR assays. In conventional specific identified PCR assays, the limit of detection (LOD) was 0.05% for Mon531, GK19, or SGK321 in 100 ng of cotton genomic DNA for one reaction. Also, the multiplex PCR method for screening the three GM cottons was also established, which could save time and cost in practical detection. Furthermore, a real-time quantitative PCR assay based on TaqMan chemistry for detection of insect resistant gene, Cry1A(c), was developed. This assay also featured the use of a standard plasmid as a reference molecule, which contained both a specific region of the transgene Cry1A(c) and an endogenous stearoyl-acyl carrier protein desaturase (Sad1) gene of the cotton. In quantitative PCR assay, the quantification range was from 0.01 to 100% in 100 ng of the genome DNA template, and in the detection of 1.0, 3.0, and 5.0% levels of three insect resistant cotton lines, respectively, all of the relative standard deviations (RSDs) were less than 8.2% except for the GM cotton samples with 1.0% Mon531 or GK19, which meant that our real-time PCR assays involving the use of reference molecule were reliable and practical for GM

Informatics methods to enable sharing of quantitative imaging research data.

PubMed

Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

2012-11-01

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

A quantitative method for optimized placement of continuous air monitors.

PubMed

Whicker, Jeffrey J; Rodgers, John C; Moxley, John S

2003-11-01

Alarming continuous air monitors (CAMs) are a critical component for worker protection in facilities that handle large amounts of hazardous materials. In nuclear facilities, continuous air monitors alarm when levels of airborne radioactive materials exceed alarm thresholds, thus prompting workers to exit the room to reduce inhalation exposures. To maintain a high level of worker protection, continuous air monitors are required to detect radioactive aerosol clouds quickly and with good sensitivity. This requires that there are sufficient numbers of continuous air monitors in a room and that they are well positioned. Yet there are no published methodologies to quantitatively determine the optimal number and placement of continuous air monitors in a room. The goal of this study was to develop and test an approach to quantitatively determine optimal number and placement of continuous air monitors in a room. The method we have developed uses tracer aerosol releases (to simulate accidental releases) and the measurement of the temporal and spatial aspects of the dispersion of the tracer aerosol through the room. The aerosol dispersion data is then analyzed to optimize continuous air monitor utilization based on simulated worker exposure. This method was tested in a room within a Department of Energy operated plutonium facility at the Savannah River Site in South Carolina, U.S. Results from this study show that the value of quantitative airflow and aerosol dispersion studies is significant and that worker protection can be significantly improved while balancing the costs associated with CAM programs.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits.

PubMed

Yadav, Anupama; Dhole, Kaustubh; Sinha, Himanshu

2016-12-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

PubMed Central

Yadav, Anupama; Dhole, Kaustubh

2016-01-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852

Current perspectives on genetically modified crops and detection methods.

PubMed

Kamle, Madhu; Kumar, Pradeep; Patra, Jayanta Kumar; Bajpai, Vivek K

2017-07-01

Genetically modified (GM) crops are the fastest adopted commodities in the agribiotech industry. This market penetration should provide a sustainable basis for ensuring food supply for growing global populations. The successful completion of two decades of commercial GM crop production (1996-2015) is underscored by the increasing rate of adoption of genetic engineering technology by farmers worldwide. With the advent of introduction of multiple traits stacked together in GM crops for combined herbicide tolerance, insect resistance, drought tolerance or disease resistance, the requirement of reliable and sensitive detection methods for tracing and labeling genetically modified organisms in the food/feed chain has become increasingly important. In addition, several countries have established threshold levels for GM content which trigger legally binding labeling schemes. The labeling of GM crops is mandatory in many countries (such as China, EU, Russia, Australia, New Zealand, Brazil, Israel, Saudi Arabia, Korea, Chile, Philippines, Indonesia, Thailand), whereas in Canada, Hong Kong, USA, South Africa, and Argentina voluntary labeling schemes operate. The rapid adoption of GM crops has increased controversies, and mitigating these issues pertaining to the implementation of effective regulatory measures for the detection of GM crops is essential. DNA-based detection methods have been successfully employed, while the whole genome sequencing using next-generation sequencing (NGS) technologies provides an advanced means for detecting genetically modified organisms and foods/feeds in GM crops. This review article describes the current status of GM crop commercialization and discusses the benefits and shortcomings of common and advanced detection systems for GMs in foods and animal feeds.

Development of an innovative immunoassay for CP4EPSPS and Cry1AB genetically modified protein detection and quantification.

PubMed

Ermolli, M; Prospero, A; Balla, B; Querci, M; Mazzeo, A; Van Den Eede, G

2006-09-01

An innovative immunoassay, called enzyme-linked immunoabsorbant assay (ELISA) Reverse, based on a new conformation of the solid phase, was developed. The solid support was expressly designed to be immersed directly in liquid samples to detect the presence of protein targets. Its application is proposed in those cases where a large number of samples have to be screened simultaneously or when the simultaneous detection of different proteins is required. As a first application, a quantitative immunoassay for Cry1AB protein in genetically modified maize was optimized. The method was tested using genetically modified organism concentrations from 0.1 to 2.0%. The limit of detection and limit of quantitation of the method were determined as 0.0056 and 0.0168 (expressed as the percentage of genetically modified organisms content), respectively. A qualitative multiplex assay to assess the presence of two genetically modified proteins simultaneously was also established for the case of the Cry1AB and the CP4EPSPS (5-enolpyruvylshikimate-3-phosphate synthase) present in genetically modified maize and soy, respectively.

Genetical Genomics Identifies the Genetic Architecture for Growth and Weevil Resistance in Spruce

PubMed Central

Porth, Ilga; White, Richard; Jaquish, Barry; Alfaro, René; Ritland, Carol; Ritland, Kermit

2012-01-01

In plants, relationships between resistance to herbivorous insect pests and growth are typically controlled by complex interactions between genetically correlated traits. These relationships often result in tradeoffs in phenotypic expression. In this study we used genetical genomics to elucidate genetic relationships between tree growth and resistance to white pine terminal weevil (Pissodes strobi Peck.) in a pedigree population of interior spruce (Picea glauca, P. engelmannii and their hybrids) that was growing at Vernon, B.C. and segregating for weevil resistance. Genetical genomics uses genetic perturbations caused by allelic segregation in pedigrees to co-locate quantitative trait loci (QTLs) for gene expression and quantitative traits. Bark tissue of apical leaders from 188 trees was assayed for gene expression using a 21.8K spruce EST-spotted microarray; the same individuals were genotyped for 384 SNP markers for the genetic map. Many of the expression QTLs (eQTL) co-localized with resistance trait QTLs. For a composite resistance phenotype of six attack and oviposition traits, 149 positional candidate genes were identified. Resistance and growth QTLs also overlapped with eQTL hotspots along the genome suggesting that: 1) genetic pleiotropy of resistance and growth traits in interior spruce was substantial, and 2) master regulatory genes were important for weevil resistance in spruce. These results will enable future work on functional genetic studies of insect resistance in spruce, and provide valuable information about candidate genes for genetic improvement of spruce. PMID:22973444

Combining qualitative and quantitative research within mixed method research designs: a methodological review.

PubMed

Östlund, Ulrika; Kidd, Lisa; Wengström, Yvonne; Rowa-Dewar, Neneh

2011-03-01

It has been argued that mixed methods research can be useful in nursing and health science because of the complexity of the phenomena studied. However, the integration of qualitative and quantitative approaches continues to be one of much debate and there is a need for a rigorous framework for designing and interpreting mixed methods research. This paper explores the analytical approaches (i.e. parallel, concurrent or sequential) used in mixed methods studies within healthcare and exemplifies the use of triangulation as a methodological metaphor for drawing inferences from qualitative and quantitative findings originating from such analyses. This review of the literature used systematic principles in searching CINAHL, Medline and PsycINFO for healthcare research studies which employed a mixed methods approach and were published in the English language between January 1999 and September 2009. In total, 168 studies were included in the results. Most studies originated in the United States of America (USA), the United Kingdom (UK) and Canada. The analytic approach most widely used was parallel data analysis. A number of studies used sequential data analysis; far fewer studies employed concurrent data analysis. Very few of these studies clearly articulated the purpose for using a mixed methods design. The use of the methodological metaphor of triangulation on convergent, complementary, and divergent results from mixed methods studies is exemplified and an example of developing theory from such data is provided. A trend for conducting parallel data analysis on quantitative and qualitative data in mixed methods healthcare research has been identified in the studies included in this review. Using triangulation as a methodological metaphor can facilitate the integration of qualitative and quantitative findings, help researchers to clarify their theoretical propositions and the basis of their results. This can offer a better understanding of the links between theory and

[Quantitative method for simultaneous assay of four coumarins with one marker in Fraxini Cortex].

PubMed

Feng, Weihong; Wang, Zhimin; Zhang, Qiwei; Liu, Limei; Wang, Jinyu; Yang, Fei

2011-07-01

To establish a new quantitative method for simultaneous determination of multi-coumarins in Fraxini Cortex by using one chemical reference substance, and validate its feasibilities. The new quality evaluation method, quantitative analysis of multi-components by singer-marker (QAMS), was established and validated with Fraxini Cortex. Four main coumarins were selected as analytes to evaluate the quality and their relative correlation factors (RCF) were determined by HPLC-DAD. Within the linear range, the values of RCF at 340 nm of aesculin to asculetin, fraxin and fraxetin were 1.771, 0.799, 1.409, respectively. And the contents of aesculin in samples of Fraxini Cortex were authentically determined by the external standard method, and the contents of the three other coumarins were calculated by their RCF. The contents of these four coumarins in all samples were also determined by the external standard method. Within a certain range, the RCF had a good reproducibility (RSD 2.5%-3.9%). Significant differences were not observed between the quantitative results of two methods. It is feasible and suitable to evaluate the quality of Fraxini Cortex and its Yinpian by QAMS.

Proteus mirabilis biofilm - qualitative and quantitative colorimetric methods-based evaluation.

PubMed

Kwiecinska-Piróg, Joanna; Bogiel, Tomasz; Skowron, Krzysztof; Wieckowska, Ewa; Gospodarek, Eugenia

2014-01-01

Proteus mirabilis strains ability to form biofilm is a current topic of a number of research worldwide. In this study the biofilm formation of P. mirabilis strains derived from urine of the catheterized and non-catheterized patients has been investigated. A total number of 39 P. mirabilis strains isolated from the urine samples of the patients of dr Antoni Jurasz University Hospital No. 1 in Bydgoszcz clinics between 2011 and 2012 was used. Biofilm formation was evaluated using two independent quantitative and qualitative methods with TTC (2,3,5-triphenyl-tetrazolium chloride) and CV (crystal violet) application. The obtained results confirmed biofilm formation by all the examined strains, except quantitative method with TTC, in which 7.7% of the strains did not have this ability. It was shown that P. mirabilis rods have the ability to form biofilm on the surfaces of both biomaterials applied, polystyrene and polyvinyl chloride (Nelaton catheters). The differences in ability to form biofilm observed between P. mirabilis strains derived from the urine of the catheterized and non-catheterized patients were not statistically significant.

Quantitative synthesis of genetically encoded glycopeptide libraries displayed on M13 phage.

PubMed

Ng, Simon; Jafari, Mohammad R; Matochko, Wadim L; Derda, Ratmir

2012-09-21

Phage display is a powerful technology that enables the discovery of peptide ligands for many targets. Chemical modification of phage libraries have allowed the identification of ligands with properties not encountered in natural polypeptides. In this report, we demonstrated the synthesis of 2 × 10(8) genetically encoded glycopeptides from a commercially available phage-displayed peptide library (Ph.D.-7) in a two-step, one-pot reaction in <1.5 h. Unlike previous reports, we bypassed genetic engineering of phage. The glycan moiety was introduced via an oxime ligation following oxidation of an N-terminal Ser/Thr; these residues are present in the peptide libraries at 20-30% abundance. The construction of libraries was facilitated by simple characterization, which directly assessed the yield and regioselectivity of chemical reactions performed on phage. This quantification method also allowed facile yield determination of reactions in 10(9) distinct molecules. We envision that the methodology described herein will find broad application in the synthesis of custom chemically modified phage libraries.

Sibling recurrence and the genetic epidemiology of autism

PubMed Central

Constantino, John N.; Zhang, Yi; Frazier, Thomas; Abbacchi, Anna M.; Law, Paul

2010-01-01

Objective Although the symptoms of autism exhibit quantitative distributions in nature, estimates of recurrence risk in families have never previously considered or incorporated quantitative characterization of the autistic phenotype among siblings. Method We report the results of quantitative characterization of 2,920 children from 1,235 families participating in a national volunteer register who met the criteria of having at least one child clinically-affected by an autism spectrum disorder (ASD) and at least one full biological sibling. Results The occurrence of a traditionally-defined ASD in an additional child occurred in 10.9% of the families. An additional 20% of non-ASD-affected siblings had a history of language delay, half of whom had exhibited autistic qualities of speech. Quantitative characterization using the Social Responsiveness Scale (SRS) supported previously-reported aggregation of a wide range of subclinical (quantitative) autistic traits among otherwise unaffected children in multiple-incidence families, and a relative absence of quantitative autistic traits among siblings in single-incidence autism families. Girls whose standardized severity ratings fell above a first percentile severity threshold (relative to the general population distribution) were significantly less likely to have elicited community diagnoses than their male counterparts. Conclusions These data suggest that, depending on how it is defined, sibling recurrence in ASD may exceed previously-published estimates, and varies as a function of family type. The results support differences in mechanisms of genetic transmission between simplex and multiplex autism, and advance current understanding of the genetic epidemiology of autism. PMID:20889652

Causal Genetic Variation Underlying Metabolome Differences.

PubMed

Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

2017-08-01

An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

An Efficient Functional Test Generation Method For Processors Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Hudec, Ján; Gramatová, Elena

2015-07-01

The paper presents a new functional test generation method for processors testing based on genetic algorithms and evolutionary strategies. The tests are generated over an instruction set architecture and a processor description. Such functional tests belong to the software-oriented testing. Quality of the tests is evaluated by code coverage of the processor description using simulation. The presented test generation method uses VHDL models of processors and the professional simulator ModelSim. The rules, parameters and fitness functions were defined for various genetic algorithms used in automatic test generation. Functionality and effectiveness were evaluated using the RISC type processor DP32.

Quantitative nondestructive evaluation of ceramic matrix composite by the resonance method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watanabe, T.; Aizawa, T.; Kihara, J.

The resonance method was developed to make quantitative nondestructive evaluation on the mechanical properties without any troublesome procedure. Since the present method is indifferent to the geometry of specimen, both monolithic and ceramic matrix composite materials in process can be evaluated in the nondestructive manner. Al{sub 2}O{sub 3}, Si{sub 3}N{sub 4}, SiC/Si{sub 3}N{sub 4}, and various C/C composite materials are employed to demonstrate the validity and effectiveness of the present method.

Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes.

PubMed

Lang, Dean H; Sharkey, Neil A; Lionikas, Arimantas; Mack, Holly A; Larsson, Lars; Vogler, George P; Vandenbergh, David J; Blizard, David A; Stout, Joseph T; Stitt, Joseph P; McClearn, Gerald E

2005-05-01

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F(2)) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir

Treesearch

Nicholas C. Wheeler; Kathleen D. Jermstad; Konstantin V. Krutovsky; Sally N. Aitken; Glenn T. Howe; Jodie Krakowski; David B. Neale

2005-01-01

Quantitative trait locus (QTL) analyses are used by geneticists to characterize the genetic architecture of quantitative traits, provide a foundation for marker-aided-selection (MAS), and provide a framework for positional selection of candidate genes. The most useful QTL for breeding applications are those that have been verified in time, space, and/or genetic...

Genetic potential of common bean progenies obtained by different breeding methods evaluated in various environments.

PubMed

Pontes Júnior, V A; Melo, P G S; Pereira, H S; Melo, L C

2016-09-02

Grain yield is strongly influenced by the environment, has polygenic and complex inheritance, and is a key trait in the selection and recommendation of cultivars. Breeding programs should efficiently explore the genetic variability resulting from crosses by selecting the most appropriate method for breeding in segregating populations. The goal of this study was to evaluate and compare the genetic potential of common bean progenies of carioca grain for grain yield, obtained by different breeding methods and evaluated in different environments. Progenies originating from crosses between lines and CNFC 7812 and CNFC 7829 were replanted up to the F 7 generation using three breeding methods in segregating populations: population (bulk), bulk within F 2 progenies, and single-seed descent (SSD). Fifteen F 8 progenies per method, two controls (BRS Estilo and Perola), and the parents were evaluated in a 7 x 7 simple lattice design, with plots of two 4-m rows. The tests were conducted in 10 environments in four States of Brazil and in three growing seasons in 2009 and 2010. Genetic parameters including genetic variance, heritability, variance of interaction, and expected selection gain were estimated. Genetic variability among progenies and the effect of progeny-environment interactions were determined for the three methods. The breeding methods differed significantly due to the effects of sampling procedures on the progenies and due to natural selection, which mainly affected the bulk method. The SSD and bulk methods provided populations with better estimates of genetic parameters and more stable progenies that were less affected by interaction with the environment.

Methods in preimplantation genetic diagnosis.

PubMed

Lizcano Gil, Luis Arturo; Lucena, Carolina; Lucena, Elkin

2001-01-01

Preimplantation genetic diagnosis (PGD) is a new strategy, orientated toward primary prevention of congenital anomalies in couples with reproductive risk, such as advanced maternal age, carriers of chromosomal abnormalities, and carriers of monogenic conditions. For these patients, PGD is an acceptable alternative to prenatal diagnosis, mainly in those countries where pregnancy interruption is forbidden by law. PGD effectively avoids the implications linked to traditional prenatal diagnosis. Centres that provide medical servicies on reproductive biomedicine are responsible for the development and improvement of this new prevention strategy. Thanks to advances in micromanipulation techniques, associated with recent progress in molecular genetics, PGD may be employed for any genetic condition in the future.

Simple and cost-effective liquid chromatography-mass spectrometry method to measure dabrafenib quantitatively and six metabolites semi-quantitatively in human plasma.

PubMed

Vikingsson, Svante; Dahlberg, Jan-Olof; Hansson, Johan; Höiom, Veronica; Gréen, Henrik

2017-06-01

Dabrafenib is an inhibitor of BRAF V600E used for treating metastatic melanoma but a majority of patients experience adverse effects. Methods to measure the levels of dabrafenib and major metabolites during treatment are needed to allow development of individualized dosing strategies to reduce the burden of such adverse events. In this study, an LC-MS/MS method capable of measuring dabrafenib quantitatively and six metabolites semi-quantitatively is presented. The method is fully validated with regard to dabrafenib in human plasma in the range 5-5000 ng/mL. The analytes were separated on a C18 column after protein precipitation and detected in positive electrospray ionization mode using a Xevo TQ triple quadrupole mass spectrometer. As no commercial reference standards are available, the calibration curve of dabrafenib was used for semi-quantification of dabrafenib metabolites. Compared to earlier methods the presented method represents a simpler and more cost-effective approach suitable for clinical studies. Graphical abstract Combined multi reaction monitoring transitions of dabrafenib and metabolites in a typical case sample.

Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens.

PubMed

Abdollahi-Arpanahi, Rostam; Morota, Gota; Valente, Bruno D; Kranis, Andreas; Rosa, Guilherme J M; Gianola, Daniel

2016-02-03

phenotypic variation for the three traits studied. Overall, the contribution of additive genetic variance to the total genetic variance was much greater than that of dominance variance. Our results show that all genomic regions are important for the prediction of the targeted traits, and the whole-genome approach was reaffirmed as the best tool for genome-enabled prediction of quantitative traits.

IT: An Effective Pedagogic Tool in the Teaching of Quantitative Methods in Management.

ERIC Educational Resources Information Center

Nadkami, Sanjay M.

1998-01-01

Examines the possibility of supplementing conventional pedagogic methods with information technology-based teaching aids in the instruction of quantitative methods to undergraduate students. Considers the case for a problem-based learning approach, and discusses the role of information technology. (Author/LRW)

Applications of Genetic Methods to NASA Design and Operations Problems

NASA Technical Reports Server (NTRS)

Laird, Philip D.

1996-01-01

We review four recent NASA-funded applications in which evolutionary/genetic methods are important. In the process we survey: the kinds of problems being solved today with these methods; techniques and tools used; problems encountered; and areas where research is needed. The presentation slides are annotated briefly at the top of each page.

A Novel Method for Relative Quantitation of N-Glycans by Isotopic Labeling Using 18O-Water

PubMed Central

Tao, Shujuan; Orlando, Ron

2014-01-01

Quantitation is an essential aspect of comprehensive glycomics study. Here, a novel isotopic-labeling method is described for N-glycan quantitation using 18O-water. The incorporation of the 18O-labeling into the reducing end of N-glycans is simply and efficiently achieved during peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase F release. This process provides a 2-Da mass difference compared with the N-glycans released in 16O-water. A mathematical calculation method was also developed to determine the 18O/16O ratios from isotopic peaks. Application of this method to several standard glycoprotein mixtures and human serum demonstrated that this method can facilitate the relative quantitation of N-glycans over a linear dynamic range of two orders, with high accuracy and reproducibility. PMID:25365792

Research design: qualitative, quantitative and mixed methods approaches Research design: qualitative, quantitative and mixed methods approaches Creswell John W Sage 320 £29 0761924426 0761924426 [Formula: see text].

PubMed

2004-09-01

The second edition of Creswell's book has been significantly revised and updated. The author clearly sets out three approaches to research: quantitative, qualitative and mixed methods. As someone who has used mixed methods in my research, it is refreshing to read a textbook that addresses this. The differences between the approaches are clearly identified and a rationale for using each methodological stance provided.

Visual and Quantitative Analysis Methods of Respiratory Patterns for Respiratory Gated PET/CT.

PubMed

Son, Hye Joo; Jeong, Young Jin; Yoon, Hyun Jin; Park, Jong-Hwan; Kang, Do-Young

2016-01-01

We integrated visual and quantitative methods for analyzing the stability of respiration using four methods: phase space diagrams, Fourier spectra, Poincaré maps, and Lyapunov exponents. Respiratory patterns of 139 patients were grouped based on the combination of the regularity of amplitude, period, and baseline positions. Visual grading was done by inspecting the shape of diagram and classified into two states: regular and irregular. Quantitation was done by measuring standard deviation of x and v coordinates of Poincaré map (SD x , SD v ) or the height of the fundamental peak ( A 1 ) in Fourier spectrum or calculating the difference between maximal upward and downward drift. Each group showed characteristic pattern on visual analysis. There was difference of quantitative parameters (SD x , SD v , A 1 , and MUD-MDD) among four groups (one way ANOVA, p = 0.0001 for MUD-MDD, SD x , and SD v , p = 0.0002 for A 1 ). In ROC analysis, the cutoff values were 0.11 for SD x (AUC: 0.982, p < 0.0001), 0.062 for SD v (AUC: 0.847, p < 0.0001), 0.117 for A 1 (AUC: 0.876, p < 0.0001), and 0.349 for MUD-MDD (AUC: 0.948, p < 0.0001). This is the first study to analyze multiple aspects of respiration using various mathematical constructs and provides quantitative indices of respiratory stability and determining quantitative cutoff value for differentiating regular and irregular respiration.

Quantitative Evaluation of Heavy Duty Machine Tools Remanufacturing Based on Modified Catastrophe Progression Method

NASA Astrophysics Data System (ADS)

shunhe, Li; jianhua, Rao; lin, Gui; weimin, Zhang; degang, Liu

2017-11-01

The result of remanufacturing evaluation is the basis for judging whether the heavy duty machine tool can remanufacture in the EOL stage of the machine tool lifecycle management.The objectivity and accuracy of evaluation is the key to the evaluation method.In this paper, the catastrophe progression method is introduced into the quantitative evaluation of heavy duty machine tools’ remanufacturing,and the results are modified by the comprehensive adjustment method,which makes the evaluation results accord with the standard of human conventional thinking.Using the catastrophe progression method to establish the heavy duty machine tools’ quantitative evaluation model,to evaluate the retired TK6916 type CNC floor milling-boring machine’s remanufacturing.The evaluation process is simple,high quantification,the result is objective.

Genetic assignment methods for gaining insight into the management of infectious disease by understanding pathogen, vector, and host movement.

PubMed

Remais, Justin V; Xiao, Ning; Akullian, Adam; Qiu, Dongchuan; Blair, David

2011-04-01

For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease.

Quantitative data standardization of X-ray based densitometry methods

NASA Astrophysics Data System (ADS)

Sergunova, K. A.; Petraikin, A. V.; Petrjajkin, F. A.; Akhmad, K. S.; Semenov, D. S.; Potrakhov, N. N.

2018-02-01

In the present work is proposed the design of special liquid phantom for assessing the accuracy of quantitative densitometric data. Also are represented the dependencies between the measured bone mineral density values and the given values for different X-ray based densitometry techniques. Shown linear graphs make it possible to introduce correction factors to increase the accuracy of BMD measurement by QCT, DXA and DECT methods, and to use them for standardization and comparison of measurements.

Preferential access to genetic information from endogenous hominin ancient DNA and accurate quantitative SNP-typing via SPEX

PubMed Central

Brotherton, Paul; Sanchez, Juan J.; Cooper, Alan; Endicott, Phillip

2010-01-01

The analysis of targeted genetic loci from ancient, forensic and clinical samples is usually built upon polymerase chain reaction (PCR)-generated sequence data. However, many studies have shown that PCR amplification from poor-quality DNA templates can create sequence artefacts at significant levels. With hominin (human and other hominid) samples, the pervasive presence of highly PCR-amplifiable human DNA contaminants in the vast majority of samples can lead to the creation of recombinant hybrids and other non-authentic artefacts. The resulting PCR-generated sequences can then be difficult, if not impossible, to authenticate. In contrast, single primer extension (SPEX)-based approaches can genotype single nucleotide polymorphisms from ancient fragments of DNA as accurately as modern DNA. A single SPEX-type assay can amplify just one of the duplex DNA strands at target loci and generate a multi-fold depth-of-coverage, with non-authentic recombinant hybrids reduced to undetectable levels. Crucially, SPEX-type approaches can preferentially access genetic information from damaged and degraded endogenous ancient DNA templates over modern human DNA contaminants. The development of SPEX-type assays offers the potential for highly accurate, quantitative genotyping from ancient hominin samples. PMID:19864251

Wavelength Selection Method Based on Differential Evolution for Precise Quantitative Analysis Using Terahertz Time-Domain Spectroscopy.

PubMed

Li, Zhi; Chen, Weidong; Lian, Feiyu; Ge, Hongyi; Guan, Aihong

2017-12-01

Quantitative analysis of component mixtures is an important application of terahertz time-domain spectroscopy (THz-TDS) and has attracted broad interest in recent research. Although the accuracy of quantitative analysis using THz-TDS is affected by a host of factors, wavelength selection from the sample's THz absorption spectrum is the most crucial component. The raw spectrum consists of signals from the sample and scattering and other random disturbances that can critically influence the quantitative accuracy. For precise quantitative analysis using THz-TDS, the signal from the sample needs to be retained while the scattering and other noise sources are eliminated. In this paper, a novel wavelength selection method based on differential evolution (DE) is investigated. By performing quantitative experiments on a series of binary amino acid mixtures using THz-TDS, we demonstrate the efficacy of the DE-based wavelength selection method, which yields an error rate below 5%.

Examining Stress in Graduate Assistants: Combining Qualitative and Quantitative Survey Methods

ERIC Educational Resources Information Center

Mazzola, Joseph J.; Walker, Erin J.; Shockley, Kristen M.; Spector, Paul E.

2011-01-01

The aim of this study was to employ qualitative and quantitative survey methods in a concurrent mixed model design to assess stressors and strains in graduate assistants. The stressors most frequently reported qualitatively were work overload, interpersonal conflict, and organizational constraints; the most frequently reported psychological…

Tendency for interlaboratory precision in the GMO analysis method based on real-time PCR.

PubMed

Kodama, Takashi; Kurosawa, Yasunori; Kitta, Kazumi; Naito, Shigehiro

2010-01-01

The Horwitz curve estimates interlaboratory precision as a function only of concentration, and is frequently used as a method performance criterion in food analysis with chemical methods. The quantitative biochemical methods based on real-time PCR require an analogous criterion to progressively promote method validation. We analyzed the tendency of precision using a simplex real-time PCR technique in 53 collaborative studies of seven genetically modified (GM) crops. Reproducibility standard deviation (SR) and repeatability standard deviation (Sr) of the genetically modified organism (GMO) amount (%) was more or less independent of GM crops (i.e., maize, soybean, cotton, oilseed rape, potato, sugar beet, and rice) and evaluation procedure steps. Some studies evaluated whole steps consisting of DNA extraction and PCR quantitation, whereas others focused only on the PCR quantitation step by using DNA extraction solutions. Therefore, SR and Sr for GMO amount (%) are functions only of concentration similar to the Horwitz curve. We proposed S(R) = 0.1971C 0.8685 and S(r) = 0.1478C 0.8424, where C is the GMO amount (%). We also proposed a method performance index in GMO quantitative methods that is analogous to the Horwitz Ratio.

The Use of Quantitative and Qualitative Methods in the Analysis of Academic Achievement among Undergraduates in Jamaica

ERIC Educational Resources Information Center

McLaren, Ingrid Ann Marie

2012-01-01

This paper describes a study which uses quantitative and qualitative methods in determining the relationship between academic, institutional and psychological variables and degree performance for a sample of Jamaican undergraduate students. Quantitative methods, traditionally associated with the positivist paradigm, and involving the counting and…

Calibration methods influence quantitative material decomposition in photon-counting spectral CT

NASA Astrophysics Data System (ADS)

Curtis, Tyler E.; Roeder, Ryan K.

2017-03-01

Photon-counting detectors and nanoparticle contrast agents can potentially enable molecular imaging and material decomposition in computed tomography (CT). Material decomposition has been investigated using both simulated and acquired data sets. However, the effect of calibration methods on material decomposition has not been systematically investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on quantitative material decomposition. A commerciallyavailable photon-counting spectral micro-CT (MARS Bioimaging) was used to acquire images with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material basis matrix values were determined using multiple linear regression models and material decomposition was performed using a maximum a posteriori estimator. The accuracy of quantitative material decomposition was evaluated by the root mean squared error (RMSE), specificity, sensitivity, and area under the curve (AUC). An increased maximum concentration (range) in the calibration significantly improved RMSE, specificity and AUC. The effects of an increased number of concentrations in the calibration were not statistically significant for the conditions in this study. The overall results demonstrated that the accuracy of quantitative material decomposition in spectral CT is significantly influenced by calibration methods, which must therefore be carefully considered for the intended diagnostic imaging application.

Technical note: quantitative measures of iris color using high resolution photographs.

PubMed

Edwards, Melissa; Gozdzik, Agnes; Ross, Kendra; Miles, Jon; Parra, Esteban J

2012-01-01

Our understanding of the genetic architecture of iris color is still limited. This is partly related to difficulties associated with obtaining quantitative measurements of eye color. Here we introduce a new automated method for measuring iris color using high resolution photographs. This method extracts color measurements in the CIE 1976 L*a*b* (CIELAB) color space from a 256 by 256 pixel square sampled from the 9:00 meridian of the iris. Color is defined across three dimensions: L* (the lightness coordinate), a* (the red-green coordinate), and b* (the blue-yellow coordinate). We applied this method to a sample of individuals of diverse ancestry (East Asian, European and South Asian) that was genotyped for the HERC2 rs12913832 polymorphism, which is strongly associated with blue eye color. We identified substantial variation in the CIELAB color space, not only in the European sample, but also in the East Asian and South Asian samples. As expected, rs12913832 was significantly associated with quantitative iris color measurements in subjects of European ancestry. However, this SNP was also strongly associated with iris color in the South Asian sample, although there were no participants with blue irides in this sample. The usefulness of this method is not restricted only to the study of iris pigmentation. High-resolution pictures of the iris will also make it possible to study the genetic variation involved in iris textural patterns, which show substantial heritability in human populations. Copyright © 2011 Wiley Periodicals, Inc.

The genetic algorithm: A robust method for stress inversion

NASA Astrophysics Data System (ADS)

Thakur, Prithvi; Srivastava, Deepak C.; Gupta, Pravin K.

2017-01-01

The stress inversion of geological or geophysical observations is a nonlinear problem. In most existing methods, it is solved by linearization, under certain assumptions. These linear algorithms not only oversimplify the problem but also are vulnerable to entrapment of the solution in a local optimum. We propose the use of a nonlinear heuristic technique, the genetic algorithm, which searches the global optimum without making any linearizing assumption or simplification. The algorithm mimics the natural evolutionary processes of selection, crossover and mutation and, minimizes a composite misfit function for searching the global optimum, the fittest stress tensor. The validity and efficacy of the algorithm are demonstrated by a series of tests on synthetic and natural fault-slip observations in different tectonic settings and also in situations where the observations are noisy. It is shown that the genetic algorithm is superior to other commonly practised methods, in particular, in those tectonic settings where none of the principal stresses is directed vertically and/or the given data set is noisy.

A quantitative method for defining high-arched palate using the Tcof1(+/-) mutant mouse as a model.

PubMed

Conley, Zachary R; Hague, Molly; Kurosaka, Hiroshi; Dixon, Jill; Dixon, Michael J; Trainor, Paul A

2016-07-15

The palate functions as the roof of the mouth in mammals, separating the oral and nasal cavities. Its complex embryonic development and assembly poses unique susceptibilities to intrinsic and extrinsic disruptions. Such disruptions may cause failure of the developing palatal shelves to fuse along the midline resulting in a cleft. In other cases the palate may fuse at an arch, resulting in a vaulted oral cavity, termed high-arched palate. There are many models available for studying the pathogenesis of cleft palate but a relative paucity for high-arched palate. One condition exhibiting either cleft palate or high-arched palate is Treacher Collins syndrome, a congenital disorder characterized by numerous craniofacial anomalies. We quantitatively analyzed palatal perturbations in the Tcof1(+/-) mouse model of Treacher Collins syndrome, which phenocopies the condition in humans. We discovered that 46% of Tcof1(+/-) mutant embryos and new born pups exhibit either soft clefts or full clefts. In addition, 17% of Tcof1(+/-) mutants were found to exhibit high-arched palate, defined as two sigma above the corresponding wild-type population mean for height and angular based arch measurements. Furthermore, palatal shelf length and shelf width were decreased in all Tcof1(+/-) mutant embryos and pups compared to controls. Interestingly, these phenotypes were subsequently ameliorated through genetic inhibition of p53. The results of our study therefore provide a simple, reproducible and quantitative method for investigating models of high-arched palate. Copyright © 2015 Elsevier Inc. All rights reserved.

Determination of Slope Safety Factor with Analytical Solution and Searching Critical Slip Surface with Genetic-Traversal Random Method

PubMed Central

2014-01-01

In the current practice, to determine the safety factor of a slope with two-dimensional circular potential failure surface, one of the searching methods for the critical slip surface is Genetic Algorithm (GA), while the method to calculate the slope safety factor is Fellenius' slices method. However GA needs to be validated with more numeric tests, while Fellenius' slices method is just an approximate method like finite element method. This paper proposed a new method to determine the minimum slope safety factor which is the determination of slope safety factor with analytical solution and searching critical slip surface with Genetic-Traversal Random Method. The analytical solution is more accurate than Fellenius' slices method. The Genetic-Traversal Random Method uses random pick to utilize mutation. A computer automatic search program is developed for the Genetic-Traversal Random Method. After comparison with other methods like slope/w software, results indicate that the Genetic-Traversal Random Search Method can give very low safety factor which is about half of the other methods. However the obtained minimum safety factor with Genetic-Traversal Random Search Method is very close to the lower bound solutions of slope safety factor given by the Ansys software. PMID:24782679

In vitro propagation of Rauwolfia serpentina using liquid medium, assessment of genetic fidelity of micropropagated plants, and simultaneous quantitation of reserpine, ajmaline, and ajmalicine.

PubMed

Goel, M K; Mehrotra, S; Kukreja, A K; Shanker, K; Khanuja, S P S

2009-01-01

Rauwolfia serpentina holds an important position in the pharmaceutical world because of its immense anti-hypertensive properties resulting from the presence of reserpine in the oleoresin fraction of the roots. Poor seed viability, low seed germination rate, and enormous genetic variability are the major constraints for the commercial cultivation of R. serpentina through conventional mode. The present optimized protocol offers an impeccable end to end method from the establishment of aseptic cultures to in-vitro plantlet production employing semisolid as well liquid nutrient culture medium and assessment of their genetic fidelity using polymerase chain reaction based rapid amplification of polymorphic DNA analysis. In vitro shoots multiplied on Murashige and Skoog basal liquid nutrients supplemented with benzo[a]pyrene (1.0 mg/L) and NAA (0.1 mg/L) and in-vitro rhizogenesis was observed in modified MS basal nutrient containing NAA (1.0 mg/L) and 2% sucrose. In-vitro raised plants exhibited 90-95% survival under glass house/field condition and 85% similarity in the plants regenerated through this protocol. Field established plants were harvested and extraction of indole alkaloid particularly reserpine, ajmaline and ajmalicine and their simultaneous quantitation was performed using monolithic reverse phase high-performance liquid chromatography (HPLC).

Advances in the application of genetic manipulation methods to apicomplexan parasites.

PubMed

Suarez, C E; Bishop, R P; Alzan, H F; Poole, W A; Cooke, B M

2017-10-01

Apicomplexan parasites such as Babesia, Theileria, Eimeria, Cryptosporidium and Toxoplasma greatly impact animal health globally, and improved, cost-effective measures to control them are urgently required. These parasites have complex multi-stage life cycles including obligate intracellular stages. Major gaps in our understanding of the biology of these relatively poorly characterised parasites and the diseases they cause severely limit options for designing novel control methods. Here we review potentially important shared aspects of the biology of these parasites, such as cell invasion, host cell modification, and asexual and sexual reproduction, and explore the potential of the application of relatively well-established or newly emerging genetic manipulation methods, such as classical transfection or gene editing, respectively, for closing important gaps in our knowledge of the function of specific genes and proteins, and the biology of these parasites. In addition, genetic manipulation methods impact the development of novel methods of control of the diseases caused by these economically important parasites. Transient and stable transfection methods, in conjunction with whole and deep genome sequencing, were initially instrumental in improving our understanding of the molecular biology of apicomplexan parasites and paved the way for the application of the more recently developed gene editing methods. The increasingly efficient and more recently developed gene editing methods, in particular those based on the CRISPR/Cas9 system and previous conceptually similar techniques, are already contributing to additional gene function discovery using reverse genetics and related approaches. However, gene editing methods are only possible due to the increasing availability of in vitro culture, transfection, and genome sequencing and analysis techniques. We envisage that rapid progress in the development of novel gene editing techniques applied to apicomplexan parasites of

Genetic association of ubiquilin with Alzheimer's disease and related quantitative measures.

PubMed

Kamboh, M I; Minster, R L; Feingold, E; DeKosky, S T

2006-03-01

The gene coding for ubiquilin 1 (UBQLN1) is located near a linkage peak on chromosome 9q22.2 and it also impacts the function of presenilin proteins involved in early-onset Alzheimer's disease (AD). Recently, genetic variation in UBQLN1 has been shown to affect the risk of AD in two independent family-based samples. The purpose of this study was to confirm the reported association in a large case-control sample and to also examine the association of UBQLN1 SNPs with quantitative measures of AD progression, namely age-at-onset (AAO), disease duration and Mini-Mental State Examination (MMSE) score. We examined the associations of three SNPs in the UBQLN1 gene (intron 6/A>C, intron 8/T>C and intron 9/A>G) in up to 978 LOAD cases and 808 controls. All SNPs were in significant linkage disequilibrium (P<0.0001). While modest significant associations were observed in the single-site regression analysis, 3-site haplotype analysis revealed significant associations (P<0.0001 for overall haplotype analysis). One common haplotype (H4) defined by intron 6/A-intron 8/C-intron 9/G alleles was associated with AD risk and one less common haplotype (H5) defined by intron 6/C-intron 8/C-intron 9/A alleles was associated with protection. The adjusted odds ratios with potentially one and two copies of risk haplotype H4 were 1.5 (95% CI: 0.99-2.26; P=0.054) and 3.66 (95% CI: 1.43-9.39; P=0.007), respectively, and odds ratio for haplotype H5 carriers was 0.31 (95% CI: 0.10-0.95; P=0.0398). In addition to disease risk, the homozygosity of the risk haplotype was also associated with older AAO, longer disease duration and lower MMSE score. In summary, our data from a large case-control cohort indicate that genetic variation in the UBQLN1 gene has a modest effect on risk, AAO and disease duration of AD. Our haplotype data suggest the presence of additional putative functional variants either in the UBQLN1 gene or nearby genes and provide strong justification for additional work in this

Some selected quantitative methods of thermal image analysis in Matlab.

PubMed

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dual gene activation and knockout screen reveals directional dependencies in genetic networks. | Office of Cancer Genomics

Cancer.gov

Understanding the direction of information flow is essential for characterizing how genetic networks affect phenotypes. However, methods to find genetic interactions largely fail to reveal directional dependencies. We combine two orthogonal Cas9 proteins from Streptococcus pyogenes and Staphylococcus aureus to carry out a dual screen in which one gene is activated while a second gene is deleted in the same cell. We analyze the quantitative effects of activation and knockout to calculate genetic interaction and directionality scores for each gene pair.

Project-Based Learning in Undergraduate Environmental Chemistry Laboratory: Using EPA Methods to Guide Student Method Development for Pesticide Quantitation

ERIC Educational Resources Information Center

Davis, Eric J.; Pauls, Steve; Dick, Jonathan

2017-01-01

Presented is a project-based learning (PBL) laboratory approach for an upper-division environmental chemistry or quantitative analysis course. In this work, a combined laboratory class of 11 environmental chemistry students developed a method based on published EPA methods for the extraction of dichlorodiphenyltrichloroethane (DDT) and its…

Chemical genetics - a versatile method to combine science and higher level teaching in molecular genetics.

PubMed

Sandrock, Björn

2012-10-09

Phosphorylation is a key event in many cellular processes like cell cycle, transformation of environmental signals to transcriptional activation or polar growth. The chemical genetics approach can be used to analyse the effect of highly specific inhibition in vivo and is a promising method to screen for kinase targets. We have used this approach to study the role of the germinal centre kinase Don3 during the cell division in the phytopathogenic fungus Ustilago maydis. Due to the easy determination of the don3 phenotype we have chosen this approach for a genetic course for M.Sc. students and for IMPRS (International Max-Planck research school) students. According to the principle of "problem-based learning" the aim of this two-week course is to transfer knowledge about the broad spectrum of kinases to the students and that the students acquire the ability to design their own analog-sensitive kinase of interest. In addition to these training goals, we benefit from these annual courses the synthesis of basic constructs for genetic modification of several kinases in our model system U. maydis.

Method and platform standardization in MRM-based quantitative plasma proteomics.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

2013-12-16

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This

Island Rule, quantitative genetics and brain–body size evolution in Homo floresiensis

PubMed Central

2017-01-01

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis, a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60–90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus, which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa. PMID:28637851

Island Rule, quantitative genetics and brain-body size evolution in Homo floresiensis.

PubMed

Diniz-Filho, José Alexandre Felizola; Raia, Pasquale

2017-06-28

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis , a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60-90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus , which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa. © 2017 The Author(s).

QuASAR: quantitative allele-specific analysis of reads.

PubMed

Harvey, Chris T; Moyerbrailean, Gregory A; Davis, Gordon O; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-04-15

Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. http://github.com/piquelab/QuASAR. fluca@wayne.edu or rpique@wayne.edu Supplementary Material is available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

QuASAR: quantitative allele-specific analysis of reads

PubMed Central

Harvey, Chris T.; Moyerbrailean, Gregory A.; Davis, Gordon O.; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-01-01

Motivation: Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. Results: We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. Availability and implementation: http://github.com/piquelab/QuASAR. Contact: fluca@wayne.edu or rpique@wayne.edu Supplementary information: Supplementary Material is available at Bioinformatics online. PMID:25480375