Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2014-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2013-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

Genetic influences on attention deficit hyperactivity disorder symptoms from age 2 to 3: A quantitative and molecular genetic investigation

Directory of Open Access Journals (Sweden)

Saudino Kimberly J

2010-12-01

Full Text Available Abstract Background A twin study design was used to assess the degree to which additive genetic variance influences ADHD symptom scores across two ages during infancy. A further objective in the study was to observe whether genetic association with a number of candidate markers reflects results from the quantitative genetic analysis. Method We have studied 312 twin pairs at two time-points, age 2 and age 3. A composite measure of ADHD symptoms from two parent-rating scales: The Child Behavior Checklist/1.5 - 5 years (CBCL hyperactivity scale and the Revised Rutter Parent Scale for Preschool Children (RRPSPC was used for both quantitative and molecular genetic analyses. Results At ages 2 and 3 ADHD symptoms are highly heritable (h2 = 0.79 and 0.78, respectively with a high level of genetic stability across these ages. However, we also observe a significant level of genetic change from age 2 to age 3. There are modest influences of non-shared environment at each age independently (e2 = 0.22 and 0.21, respectively, with these influences being largely age-specific. In addition, we find modest association signals in DAT1 and NET1 at both ages, along with suggestive specific effects of 5-HTT and DRD4 at age 3. Conclusions ADHD symptoms are heritable at ages 2 and 3. Additive genetic variance is largely shared across these ages, although there are significant new effects emerging at age 3. Results from our genetic association analysis reflect these levels of stability and change and, more generally, suggest a requirement for consideration of age-specific genotypic effects in future molecular studies.

Quantitative-genetic analysis of wing form and bilateral asymmetry ...

Indian Academy of Sciences (India)

Unknown

lines; Procrustes analysis; wing shape; wing size. ... Models of stochastic gene expression pre- dict that intrinsic noise ... Quantitative parameters of wing size and shape asymmetries ..... the residuals of a regression on centroid size produced.

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

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Brandon Jeffrey

Full Text Available 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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Genetical analysis of the induced variation by gamma radiation in quantitative characters of Caupi [Vigna unguiculata (L.) Walp.

International Nuclear Information System (INIS)

Araujo, J.P.P. de.

1987-10-01

Genetical analysis procedures of the cobalt 60 gamma radiation effects in the induced mutations in quantitative characters of Caupi BR-1 Poty. The following characters were evaluated: day to first flower (FI), number of pods per plant (NVP), pod lenght (CMV), number of suds per pod (NSV), 100 seed wright (PCS), seed yield per plant (PSP) and seed yield per plant estimated by yield components (PSPE). The resistance of irradiated populations to cowpea aphid-borne mosaic virus (CpAMV)was also evaluated. (L.M.J.) [pt

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

Directory of Open Access Journals (Sweden)

Huang Yung-Fen

2012-02-01

Full Text Available Abstract 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

Contribution and perspectives of quantitative genetics to plant breeding in Brazil

Directory of Open Access Journals (Sweden)

Fernando Henrique Ribeiro Barrozo Toledo

2012-12-01

Full Text Available The purpose of this article is to show how quantitative genetics has contributed to the huge genetic progress obtained inplant breeding in Brazil in the last forty years. The information obtained through quantitative genetics has given Brazilian breedersthe possibility of responding to innumerable questions in their work in a much more informative way, such as the use or not of hybridcultivars, which segregating population to use, which breeding method to employ, alternatives for improving the efficiency of selectionprograms, and how to handle the data of progeny and/or cultivars evaluations to identify the most stable ones and thus improverecommendations.

Genetic data analysis for plant and animal breeding

Science.gov (United States)

This book is an advanced textbook covering the application of quantitative genetics theory to analysis of actual data (both trait and DNA marker information) for breeding populations of crops, trees, and animals. Chapter 1 is an introduction to basic software used for trait data analysis. Chapter 2 ...

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

Science.gov (United States)

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.

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Jason A Corwin

2016-02-01

Full Text Available 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

EvolQG - An R package for evolutionary quantitative genetics [version 2; referees: 1 approved, 2 approved with reservations

Directory of Open Access Journals (Sweden)

Diogo Melo

2016-06-01

Full Text Available 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 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.

A quantitative genetic analysis of intermediate asthma phenotypes

DEFF Research Database (Denmark)

Thomsen, S.F.; Ferreira, M.A.R.; Kyvik, K.O.

2009-01-01

to the observed data using maximum likelihood methods. RESULTS: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most......AIM: To study the relative contribution of genetic and environmental factors to the correlation between exhaled nitric oxide (FeNO), airway responsiveness, airway obstruction, and serum total immunoglobulin E (IgE). METHODS: Within a sampling frame of 21,162 twin subjects, 20-49 years of age, from...... substantial genetic similarity was observed between FeNO and serum total IgE, genetic correlation (rhoA) = 0.37, whereas the strongest environmental resemblance was observed between airway responsiveness and airway obstruction, specific environmental correlation (rhoE) = -0.46, and between FeNO and airway...

A quantitative genetic analysis of intermediate asthma phenotypes

DEFF Research Database (Denmark)

Thomsen, S F; Ferreira, M A R; Kyvik, K O

2009-01-01

to the observed data using maximum likelihood methods. Results: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most......Aim: To study the relative contribution of genetic and environmental factors to the correlation between exhaled nitric oxide (FeNO), airway responsiveness, airway obstruction, and serum total immunoglobulin E (IgE). Methods: Within a sampling frame of 21 162 twin subjects, 20-49 years of age, from...... substantial genetic similarity was observed between FeNO and serum total IgE, genetic correlation (rho(A)) = 0.37, whereas the strongest environmental resemblance was observed between airway responsiveness and airway obstruction, specific environmental correlation (rho(E)) = -0.46, and between FeNO and airway...

Study of quantitative genetics of gum arabic production complicated by variability in ploidy level of Acacia senegal (L.) Willd

DEFF Research Database (Denmark)

Diallo, Adja Madjiguene; Nielsen, Lene Rostgaard; Hansen, Jon Kehlet

2015-01-01

Gum arabic is an important international commodity produced by trees of Acacia senegal across Sahelian Africa, but documented results of breeding activities are limited. The objective of this study was to provide reliable estimates of quantitative genetic parameters in order to shed light on the ...... stress the importance of testing ploidy levels of selected material and use of genetic markers to qualify the assumptions in the quantitative genetic analysis....... that progenies consisted of both diploid and polyploid trees, and growth, gum yield, and gum quality varied substantially among ploidy level, populations, and progenies. Analysis of molecular variance and estimates of outcrossing rate supported that trees within open-pollinated families of diploids were half...... sibs, while the open-pollinated families of polyploids showed low variation within families. The difference in sibling relationship observed between ploidy levels complicated estimation of genetic parameters. However, based on the diploid trees, we conclude that heritability in gum arabic production...

Introduction to focus issue: quantitative approaches to genetic networks.

Science.gov (United States)

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

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

Science.gov (United States)

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Quantitative genetic methods depending on the nature of the phenotypic trait.

Science.gov (United States)

de Villemereuil, Pierre

2018-01-24

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression. © 2018 New York Academy of Sciences.

The quantitative genetics of phenotypic variation in animals

NARCIS (Netherlands)

Hill, W.G.; Mulder, H.A.; Zhang, X.S.

2007-01-01

Considerable attention has been paid to estimating genetic variability in quantitative traits and to how it is maintained and changed by selection in natural and domesticated populations, but rather little attention has been paid to how levels of environmental and phenotypic variance are influenced.

A genetic analysis of segregation distortion revealed by molecular ...

Indian Academy of Sciences (India)

Journal of Genetics, Vol. 90, No. ... Segregation analysis was based on 64 molecular markers, including 26 .... FHB of RIL populations was controlled by quantitative trait ... The authors acknowledge financial support by the National Basic.

Quantitative analysis chemistry

International Nuclear Information System (INIS)

Ko, Wansuk; Lee, Choongyoung; Jun, Kwangsik; Hwang, Taeksung

1995-02-01

This book is about quantitative analysis chemistry. It is divided into ten chapters, which deal with the basic conception of material with the meaning of analysis chemistry and SI units, chemical equilibrium, basic preparation for quantitative analysis, introduction of volumetric analysis, acid-base titration of outline and experiment examples, chelate titration, oxidation-reduction titration with introduction, titration curve, and diazotization titration, precipitation titration, electrometric titration and quantitative analysis.

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

Directory of Open Access Journals (Sweden)

Jaeyong Yee

2015-01-01

Full Text Available A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait.

Functional linear models for association analysis of quantitative traits.

Science.gov (United States)

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

Complex pedigree analysis to detect quantitative trait loci in dairy cattle

NARCIS (Netherlands)

Bink, M.C.A.M.

1998-01-01

In dairy cattle, many quantitative traits of economic importance show phenotypic variation. For breeding purposes the analysis of this phenotypic variation and uncovering the contribution of genetic factors is very important. Usually, the individual gene effects contributing to the

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

Science.gov (United States)

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

Genetic analysis of PAX3 for diagnosis of Waardenburg syndrome type I.

Science.gov (United States)

Matsunaga, Tatsuo; Mutai, Hideki; Namba, Kazunori; Morita, Noriko; Masuda, Sawako

2013-04-01

PAX3 genetic analysis increased the diagnostic accuracy for Waardenburg syndrome type I (WS1). Analysis of the three-dimensional (3D) structure of PAX3 helped verify the pathogenicity of a missense mutation, and multiple ligation-dependent probe amplification (MLPA) analysis of PAX3 increased the sensitivity of genetic diagnosis in patients with WS1. Clinical diagnosis of WS1 is often difficult in individual patients with isolated, mild, or non-specific symptoms. The objective of the present study was to facilitate the accurate diagnosis of WS1 through genetic analysis of PAX3 and to expand the spectrum of known PAX3 mutations. In two Japanese families with WS1, we conducted a clinical evaluation of symptoms and genetic analysis, which involved direct sequencing, MLPA analysis, quantitative PCR of PAX3, and analysis of the predicted 3D structure of PAX3. The normal-hearing control group comprised 92 subjects who had normal hearing according to pure tone audiometry. In one family, direct sequencing of PAX3 identified a heterozygous mutation, p.I59F. Analysis of PAX3 3D structures indicated that this mutation distorted the DNA-binding site of PAX3. In the other family, MLPA analysis and subsequent quantitative PCR detected a large, heterozygous deletion spanning 1759-2554 kb that eliminated 12-18 genes including a whole PAX3 gene.

The current and future use of ridge regression for prediction in quantitative genetics

OpenAIRE

Vlaming, Ronald; Groenen, Patrick

2015-01-01

textabstractIn recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i) the theoretical foundations of ridge regression, (ii) its link to...

Genetic variability, heritability and genetic advance of quantitative ...

African Journals Online (AJOL)

ONOS

2010-05-10

May 10, 2010 ... coefficient of variation; h2, heritability; GA, genetic advance;. EMS, ethyl methane ... The analysis of variance (ANOVA) revealed the significance degree among the ... fullest extent. The estimates of range, phenotypic and.

Comparison of Variable Number Tandem Repeat and Short Tandem Repeat Genetic Markers for Qualitative and Quantitative Chimerism Analysis Post Allogeneic Stem Cell Transplantation

International Nuclear Information System (INIS)

Mossallam, G.I.; Smith, A.G.; Mcfarland, C.

2005-01-01

Analysis of donor chimerism has become a routine procedure for the documentation of engraftment after allogeneic hematopoietic stem cell transplantation. Quantitative analysis of chimerism kinetics has been shown to predict graft failure or relapse. In this study, we compared the use of variable number tandem repeats (VNTR) and short tandem repeats (STR) as polymorphic genetic markers in chimerism analysis. This study included qualitative and quantitative assessment of both techniques to assess informative yield and sensitivity. Patients and Methods: We analyzed 206 samples representing 40 transplant recipients and their HLA identical sibling donors. A panel of six VNTR loci, 15 STR loci and 1 sex chromosome locus was used. Amplified VNTR products were visualized in an ethidium bromide stained gel. STR loci were amplified using fluorescent primers, and the products were analyzed by capillary electrophoresis. VNTR and STR analysis gave comparable qualitative results in the majority of cases. The incidence of mixed chimerism (Me) by STR analysis was 45% compared to 32% in cases evaluated by VNTR analysis. STR markers were more informative; several informative loci could be identified in all patients. Unique alleles for both patient and donor could be identified in all patients by STR versus 32/40 by VNTR analysis. The STR markers were also more sensitive in the detection of chimerism. The size of VNTR alleles and differences between the size of donor and recipient VNTR alleles affected the sensitivity of detection. With both techniques, quantitative assessment of chimerism showed some discrepancies between the estimated and the calculated percentage of donor DNA. Discordance between the two estimates was observed in 8/19 patients with Me. However, sequential monitoring of the relative band intensity of VNTR alleles offered some insight into the direction of change in engraftment over time. The higher yield of informative loci with STR and the automated measurement of

Genetic analysis and hybrid vigor study of grain yield and other quantitative traits in auto tetraploid rice

International Nuclear Information System (INIS)

Shahid, M.Q.; Xiong, C.Z.; Juan, L.Y.; Ming, X.H.

2011-01-01

Genetic analysis and genotype-by-environment interaction for important traits of auto tetraploid rice were evaluated by additive, dominance and additive X additive model. It was show n that genetic effects had more influence on grain yield and other quantitative traits of auto tetraploid rice than genotypic environment interaction. Plant height, panicle length, seed set , grain yield, dry matter production and 1000-grain weight we re mainly regulated by dominance variance. Additive and additive X additive gene action constructed the main proportion of genetic variance for heading date (flowering), number of panicles, grains per panicle, grain length, however grain width was supposed to be affected by additive X additive and dominance variance. Flag leaf length and width, fresh weight, peduncle length, unfilled grains and awn length were greatly influenced by genotypic environment interaction. Heading date produced highly negative heterosis over mid parent (H pm) and better parent ( H pb), whereas H pm and H pb were detected to be highly positive and significant for grain yield, seed set, peduncle length, filled grains and 1000-grain weight in F/sub 1/ and F/sub 2/ generations. The results indicated that auto tetraploid hybrids 96025 X Jackson (indica/japonica), 96025 X Linglun (indica/indica) and Linglun X Jackson (indica/japonica) showed highly significant hybrid vigor with improved seed set percentage and grain yield. These results suggest that intra-specific auto tetraploid rice hybrids have more hybrid vigor as compared to intra-sub specific auto tetraploid rice hybrids and auto tetraploid rice has the potential to be used for further studies and commercial application. (author)

Quantitative genetic analysis of retinal degeneration in the blind cavefish Astyanax mexicanus.

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Kelly E O'Quin

Full Text Available The retina is the light-sensitive tissue of the eye that facilitates vision. Mutations within genes affecting eye development and retinal function cause a host of degenerative visual diseases, including retinitis pigmentosa and anophthalmia/microphthalmia. The characin fish Astyanax mexicanus includes both eyed (surface fish and eyeless (cavefish morphs that initially develop eyes with normal retina; however, early in development, the eyes of cavefish degenerate. Since both surface and cave morphs are members of the same species, they serve as excellent evolutionary mutant models with which to identify genes causing retinal degeneration. In this study, we crossed the eyed and eyeless forms of A. mexicanus and quantified the thickness of individual retinal layers among 115 F(2 hybrid progeny. We used next generation sequencing (RAD-seq and microsatellite mapping to construct a dense genetic map of the Astyanax genome, scan for quantitative trait loci (QTL affecting retinal thickness, and identify candidate genes within these QTL regions. The map we constructed for Astyanax includes nearly 700 markers assembled into 25 linkage groups. Based on our scans with this map, we identified four QTL, one each associated with the thickness of the ganglion, inner nuclear, outer plexiform, and outer nuclear layers of the retina. For all but one QTL, cavefish alleles resulted in a clear reduction in the thickness of the affected layer. Comparative mapping of genetic markers within each QTL revealed that each QTL corresponds to an approximately 35 Mb region of the zebrafish genome. Within each region, we identified several candidate genes associated with the function of each affected retinal layer. Our study is the first to examine Astyanax retinal degeneration in the context of QTL mapping. The regions we identify serve as a starting point for future studies on the genetics of retinal degeneration and eye disease using the evolutionary mutant model Astyanax.

Quantitative genetic activity graphical profiles for use in chemical evaluation

Energy Technology Data Exchange (ETDEWEB)

Waters, M.D. [Environmental Protection Agency, Washington, DC (United States); Stack, H.F.; Garrett, N.E.; Jackson, M.A. [Environmental Health Research and Testing, Inc., Research Triangle Park, NC (United States)

1990-12-31

A graphic approach, terms a Genetic Activity Profile (GAP), was developed to display a matrix of data on the genetic and related effects of selected chemical agents. The profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each chemical. Either the lowest effective dose or highest ineffective dose is recorded for each agent and bioassay. Up to 200 different test systems are represented across the GAP. Bioassay systems are organized according to the phylogeny of the test organisms and the end points of genetic activity. The methodology for producing and evaluating genetic activity profile was developed in collaboration with the International Agency for Research on Cancer (IARC). Data on individual chemicals were compiles by IARC and by the US Environmental Protection Agency (EPA). Data are available on 343 compounds selected from volumes 1-53 of the IARC Monographs and on 115 compounds identified as Superfund Priority Substances. Software to display the GAPs on an IBM-compatible personal computer is available from the authors. Structurally similar compounds frequently display qualitatively and quantitatively similar profiles of genetic activity. Through examination of the patterns of GAPs of pairs and groups of chemicals, it is possible to make more informed decisions regarding the selection of test batteries to be used in evaluation of chemical analogs. GAPs provided useful data for development of weight-of-evidence hazard ranking schemes. Also, some knowledge of the potential genetic activity of complex environmental mixtures may be gained from an assessment of the genetic activity profiles of component chemicals. The fundamental techniques and computer programs devised for the GAP database may be used to develop similar databases in other disciplines. 36 refs., 2 figs.

Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

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Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

2012-04-01

We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

Cracking anxiety in the mouse : a quantitative (epi)genetic approach

NARCIS (Netherlands)

Labots, M.

2017-01-01

The aim of this thesis was to improve existing methodologies and apply genetic strategies in order to identify (main-effect, epistatic, multiple and pleiotropic) quantitative trait loci and to decipher functional candidate genes for anxiety-related behavior and baseline blood plasma total

Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk

DEFF Research Database (Denmark)

Buitenhuis, Albert Johannes; Sundekilde, Ulrik; Poulsen, Nina Aagaard

2013-01-01

Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk. F...... for lactic acid to >0.8 for orotic acid and β-hydroxybutyrate. A single SNP association analysis revealed 7 genome-wide significant quantitative trait loci [malonate: Bos taurus autosome (BTA)2 and BTA7; galactose-1-phosphate: BTA2; cis-aconitate: BTA11; urea: BTA12; carnitine: BTA25...

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

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Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

On coding genotypes for genetic markers with multiple alleles in genetic association study of quantitative traits

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Wang Tao

2011-09-01

Full Text Available Abstract Background In genetic association study of quantitative traits using F∞ models, how to code the marker genotypes and interpret the model parameters appropriately is important for constructing hypothesis tests and making statistical inferences. Currently, the coding of marker genotypes in building F∞ models has mainly focused on the biallelic case. A thorough work on the coding of marker genotypes and interpretation of model parameters for F∞ models is needed especially for genetic markers with multiple alleles. Results In this study, we will formulate F∞ genetic models under various regression model frameworks and introduce three genotype coding schemes for genetic markers with multiple alleles. Starting from an allele-based modeling strategy, we first describe a regression framework to model the expected genotypic values at given markers. Then, as extension from the biallelic case, we introduce three coding schemes for constructing fully parameterized one-locus F∞ models and discuss the relationships between the model parameters and the expected genotypic values. Next, under a simplified modeling framework for the expected genotypic values, we consider several reduced one-locus F∞ models from the three coding schemes on the estimability and interpretation of their model parameters. Finally, we explore some extensions of the one-locus F∞ models to two loci. Several fully parameterized as well as reduced two-locus F∞ models are addressed. Conclusions The genotype coding schemes provide different ways to construct F∞ models for association testing of multi-allele genetic markers with quantitative traits. Which coding scheme should be applied depends on how convenient it can provide the statistical inferences on the parameters of our research interests. Based on these F∞ models, the standard regression model fitting tools can be used to estimate and test for various genetic effects through statistical contrasts with the

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

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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.

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

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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.

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

Science.gov (United States)

de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

2016-11-01

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

Quantitative investment analysis

CERN Document Server

DeFusco, Richard

2007-01-01

In the "Second Edition" of "Quantitative Investment Analysis," financial experts Richard DeFusco, Dennis McLeavey, Jerald Pinto, and David Runkle outline the tools and techniques needed to understand and apply quantitative methods to today's investment process.

QuASAR: quantitative allele-specific analysis of reads.

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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.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

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Akira Ishikawa

2017-11-01

Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

Science.gov (United States)

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Lab-on-capillary: a rapid, simple and quantitative genetic analysis platform integrating nucleic acid extraction, amplification and detection.

Science.gov (United States)

Fu, Yu; Zhou, Xiaoming; Xing, Da

2017-12-05

In this work, we describe for the first time a genetic diagnosis platform employing a polydiallyldimethylammonium chloride (PDDA)-modified capillary and a liquid-based thermalization system for rapid, simple and quantitative DNA analysis with minimal user interaction. Positively charged PDDA is modified on the inner surface of the silicon dioxide capillary by using an electrostatic self-assembly approach that allows the negatively charged DNA to be separated from the lysate in less than 20 seconds. The capillary loaded with the PCR mix is incorporated in the thermalization system, which can achieve on-site real-time PCR. This system is based on the circulation of pre-heated liquids in the chamber, allowing for high-speed thermalization of the capillary and fast amplification. Multiple targets can be simultaneously analysed with multiplex spatial melting. Starting with live Escherichia coli (E. coli) cells in milk, as a realistic sample, the current method can achieve DNA extraction, amplification, and detection within 40 min.

Quantitative genetics of plastron shape in slider turtles (Trachemys scripta).

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Myers, Erin M; Janzen, Fredric J; Adams, Dean C; Tucker, John K

2006-03-01

Shape variation is widespread in nature and embodies both a response to and a source for evolution and natural selection. To detect patterns of shape evolution, one must assess the quantitative genetic underpinnings of shape variation as well as the selective environment that the organisms have experienced. Here we used geometric morphometrics to assess variation in plastron shell shape in 1314 neonatal slider turtles (Trachemys scripta) from 162 clutches of laboratory-incubated eggs from two nesting areas. Multivariate analysis of variance indicated that nesting area has a limited role in describing plastron shape variation among clutches, whereas differences between individual clutches were highly significant, suggesting a prominent clutch effect. The covariation between plastron shape and several possible maternal effect variables (yolk hormone levels and egg dimensions) was assessed for a subset of clutches and found to be negligible. We subsequently employed several recently proposed methods for estimating heritability from shape variables, and generalized a univariate approach to accommodate unequal sample sizes. Univariate estimates of shape heritability based on Procrustes distances yielded large values for both nesting populations (h2 approximately 0.86), and multivariate estimates of maximal additive heritability were also large for both nesting populations (h2max approximately 0.57). We also estimated the dominant trend in heritable shape change for each nesting population and found that the direction of shape evolution was not the same for the two sites. Therefore, although the magnitude of shape evolution was similar between nesting populations, the manner in which plastron shape is evolving is not. We conclude that the univariate approach for assessing quantitative genetic parameters from geometric morphometric data has limited utility, because it is unable to accurately describe how shape is evolving.

Genetic and Molecular Mechanisms of Quantitative Trait Loci Controlling Maize Inflorescence Architecture.

Science.gov (United States)

Li, Manfei; Zhong, Wanshun; Yang, Fang; Zhang, Zuxin

2018-03-01

The establishment of inflorescence architecture is critical for the reproduction of flowering plant species. The maize plant generates two types of inflorescences, the tassel and the ear, and their architectures have a large effect on grain yield and yield-related traits that are genetically controlled by quantitative trait loci (QTLs). Since ear and tassel architecture are deeply affected by the activity of inflorescence meristems, key QTLs and genes regulating meristematic activity have important impacts on inflorescence development and show great potential for optimizing grain yield. Isolation of yield trait-related QTLs is challenging, but these QTLs have direct application in maize breeding. Additionally, characterization and functional dissection of QTLs can provide genetic and molecular knowledge of quantitative variation in inflorescence architecture. In this review, we summarize currently identified QTLs responsible for the establishment of ear and tassel architecture and discuss the potential genetic control of four ear-related and four tassel-related traits. In recent years, several inflorescence architecture-related QTLs have been characterized at the gene level. We review the mechanisms of these characterized QTLs.

On the road to quantitative genetic/genomic analyses of root growth and development components underlying root architecture

International Nuclear Information System (INIS)

Draye, X.; Dorlodot, S. de; Lavigne, T.

2006-01-01

The quantitative genetic and functional genomic analyses of root development, growth and plasticity will be instrumental in revealing the major regulatory pathways of root architecture. Such knowledge, combined with in-depth consideration of root physiology (e.g. uptake, exsudation), form (space-time dynamics of soil exploration) and ecology (including root environment), will settle the bases for designing root ideotypes for specific environments, for low-input agriculture or for successful agricultural production with minimal impact on the environment. This report summarizes root research initiated in our lab between 2000 and 2004 in the following areas: quantitative analysis of root branching in bananas, high throughput characterisation of root morphology, image analysis, QTL mapping of detailed features of root architecture in rice, and attempts to settle a Crop Root Research Consortium. (author)

Quantitative genetic variance and multivariate clines in the Ivyleaf morning glory, Ipomoea hederacea.

Science.gov (United States)

Stock, Amanda J; Campitelli, Brandon E; Stinchcombe, John R

2014-08-19

Clinal variation is commonly interpreted as evidence of adaptive differentiation, although clines can also be produced by stochastic forces. Understanding whether clines are adaptive therefore requires comparing clinal variation to background patterns of genetic differentiation at presumably neutral markers. Although this approach has frequently been applied to single traits at a time, we have comparatively fewer examples of how multiple correlated traits vary clinally. Here, we characterize multivariate clines in the Ivyleaf morning glory, examining how suites of traits vary with latitude, with the goal of testing for divergence in trait means that would indicate past evolutionary responses. We couple this with analysis of genetic variance in clinally varying traits in 20 populations to test whether past evolutionary responses have depleted genetic variance, or whether genetic variance declines approaching the range margin. We find evidence of clinal differentiation in five quantitative traits, with little evidence of isolation by distance at neutral loci that would suggest non-adaptive or stochastic mechanisms. Within and across populations, the traits that contribute most to population differentiation and clinal trends in the multivariate phenotype are genetically variable as well, suggesting that a lack of genetic variance will not cause absolute evolutionary constraints. Our data are broadly consistent theoretical predictions of polygenic clines in response to shallow environmental gradients. Ecologically, our results are consistent with past findings of natural selection on flowering phenology, presumably due to season-length variation across the range. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Development and interlaboratory validation of quantitative polymerase chain reaction method for screening analysis of genetically modified soybeans.

Science.gov (United States)

Takabatake, Reona; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2013-01-01

A novel real-time polymerase chain reaction (PCR)-based quantitative screening method was developed for three genetically modified soybeans: RRS, A2704-12, and MON89788. The 35S promoter (P35S) of cauliflower mosaic virus is introduced into RRS and A2704-12 but not MON89788. We then designed a screening method comprised of the combination of the quantification of P35S and the event-specific quantification of MON89788. The conversion factor (Cf) required to convert the amount of a genetically modified organism (GMO) from a copy number ratio to a weight ratio was determined experimentally. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDR), respectively. The determined RSDR values for the method were less than 25% for both targets. We consider that the developed method would be suitable for the simple detection and approximate quantification of GMO.

Quantitative Genetic Analysis for Yield and Yield Components in Boro Rice (Oryza sativa L.

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Supriyo CHAKRABORTY

2010-03-01

Full Text Available Twenty-nine genotypes of boro rice (Oryza sativa L. were grown in a randomized block design with three replications in plots of 4m x 1m with a crop geometry of 20 cm x 20 cm between November-April, in Regional Agricultural Research Station, Nagaon, India. Quantitative data were collected on five randomly selected plants of each genotype per replication for yield/plant, and six other yield components, namely plant height, panicles/plant, panicle length, effective grains/panicle, 100 grain weight and harvest index. Mean values of the characters for each genotype were used for analysis of variance and covariance to obtain information on genotypic and phenotypic correlation along with coheritability between two characters. Path analyses were carried out to estimate the direct and indirect effects of boro rice�s yield components. The objective of the study was to identify the characters that mostly influence the yield for increasing boro rice productivity through breeding program. Correlation analysis revealed significant positive genotypic correlation of yield/plant with plant height (0.21, panicles/plant (0.53, panicle length (0.53, effective grains/panicle (0.57 and harvest index (0.86. Path analysis based on genotypic correlation coefficients elucidated high positive direct effect of harvest index (0.8631, panicle length (0.2560 and 100 grain weight (0.1632 on yield/plant with a residual effect of 0.33. Plant height and panicles/plant recorded high positive indirect effect on yield/plant via harvest index whereas effective grains/panicle on yield/plant via harvest index and panicle length. Results of the present study suggested that five component characters, namely harvest index, effective grains/plant, panicle length, panicles/plant and plant height influenced the yield of boro rice. A genotype with higher magnitude of these component characters could be either selected from the existing genotypes or evolved by breeding program for genetic

Spectral Quantitative Analysis Model with Combining Wavelength Selection and Topology Structure Optimization

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Qian Wang

2016-01-01

Full Text Available Spectroscopy is an efficient and widely used quantitative analysis method. In this paper, a spectral quantitative analysis model with combining wavelength selection and topology structure optimization is proposed. For the proposed method, backpropagation neural network is adopted for building the component prediction model, and the simultaneousness optimization of the wavelength selection and the topology structure of neural network is realized by nonlinear adaptive evolutionary programming (NAEP. The hybrid chromosome in binary scheme of NAEP has three parts. The first part represents the topology structure of neural network, the second part represents the selection of wavelengths in the spectral data, and the third part represents the parameters of mutation of NAEP. Two real flue gas datasets are used in the experiments. In order to present the effectiveness of the methods, the partial least squares with full spectrum, the partial least squares combined with genetic algorithm, the uninformative variable elimination method, the backpropagation neural network with full spectrum, the backpropagation neural network combined with genetic algorithm, and the proposed method are performed for building the component prediction model. Experimental results verify that the proposed method has the ability to predict more accurately and robustly as a practical spectral analysis tool.

GENES - a software package for analysis in experimental statistics and quantitative genetics

Directory of Open Access Journals (Sweden)

Cosme Damião Cruz

2013-06-01

Full Text Available GENES is a software package used for data analysis and processing with different biometricmodels and is essential in genetic studies applied to plant and animal breeding. It allows parameterestimation to analyze biologicalphenomena and is fundamental for the decision-making process andpredictions of success and viability of selection strategies. The program can be downloaded from theInternet (http://www.ufv.br/dbg/genes/genes.htm orhttp://www.ufv.br/dbg/biodata.htm and is available inPortuguese, English and Spanish. Specific literature (http://www.livraria.ufv.br/ and a set of sample filesare also provided, making GENES easy to use. The software is integrated into the programs MS Word, MSExcel and Paint, ensuring simplicity and effectiveness indata import and export ofresults, figures and data.It is also compatible with the free software R and Matlab, through the supply of useful scripts available forcomplementary analyses in different areas, including genome wide selection, prediction of breeding valuesand use of neural networks in genetic improvement.

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

Science.gov (United States)

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.

Genetical Genomics for Evolutionary Studies

NARCIS (Netherlands)

Prins, J.C.P.; Smant, G.; Jansen, R.C.

2012-01-01

Genetical genomics combines acquired high-throughput genomic data with genetic analysis. In this chapter, we discuss the application of genetical genomics for evolutionary studies, where new high-throughput molecular technologies are combined with mapping quantitative trait loci (QTL) on the genome

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

Science.gov (United States)

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.

A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification

KAUST Repository

Malvezzi, Alex J.; Murray, Christopher S.; Feldheim, Kevin A.; DiBattista, Joseph; Garant, Dany; Gobler, Christopher J.; Chapman, Demian D.; Baumann, Hannes

2015-01-01

Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive

Quantitative genetic analysis of life-history traits of Caenorhabditis elegans in stressful environments

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Shorto Alison

2008-01-01

Full Text Available Abstract Background Organisms live in environments that vary. For life-history traits that vary across environments, fitness will be maximised when the phenotype is appropriately matched to the environmental conditions. For the free-living nematode Caenorhabditis elegans, we have investigated how two major life-history traits, (i the development of environmentally resistant dauer larvae and (ii reproduction, respond to environmental stress (high population density and low food availability, and how these traits vary between lines and the genetic basis of this variation. Results We found that lines of C. elegans vary in their phenotypic plasticity of dauer larva development, i.e. there is variation in the likelihood of developing into a dauer larva for the same environmental change. There was also variation in how lifetime fecundity and the rate of reproduction changed under conditions of environmental stress. These traits were related, such that lines that are highly plastic for dauer larva development also maintain a high population growth rate when stressed. We identified quantitative trait loci (QTL on two chromosomes that control the dauer larva development and population size phenotypes. The QTLs affecting the dauer larva development and population size phenotypes on chromosome II are closely linked, but are genetically separable. This chromosome II QTL controlling dauer larva development does not encompass any loci previously identified to control dauer larva development. This chromosome II region contains many predicted 7-transmembrane receptors. Such proteins are often involved in information transduction, which is clearly relevant to the control of dauer larva development. Conclusion C. elegans alters both its larval development and adult reproductive strategy in response to environmental stress. Together the phenotypic and genotypic data suggest that these two major life-history traits are co-ordinated responses to environmental stress

Quantitative analysis of microtubule orientation in interdigitated leaf pavement cells.

Science.gov (United States)

Akita, Kae; Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2015-01-01

Leaf pavement cells are shaped like a jigsaw puzzle in most dicotyledon species. Molecular genetic studies have identified several genes required for pavement cells morphogenesis and proposed that microtubules play crucial roles in the interdigitation of pavement cells. In this study, we performed quantitative analysis of cortical microtubule orientation in leaf pavement cells in Arabidopsis thaliana. We captured confocal images of cortical microtubules in cotyledon leaf epidermis expressing GFP-tubulinβ and quantitatively evaluated the microtubule orientations relative to the pavement cell growth axis using original image processing techniques. Our results showed that microtubules kept parallel orientations to the growth axis during pavement cell growth. In addition, we showed that immersion treatment of seed cotyledons in solutions containing tubulin polymerization and depolymerization inhibitors decreased pavement cell complexity. Treatment with oryzalin and colchicine inhibited the symmetric division of guard mother cells.

Integrated genetic analysis microsystems

International Nuclear Information System (INIS)

Lagally, Eric T; Mathies, Richard A

2004-01-01

With the completion of the Human Genome Project and the ongoing DNA sequencing of the genomes of other animals, bacteria, plants and others, a wealth of new information about the genetic composition of organisms has become available. However, as the demand for sequence information grows, so does the workload required both to generate this sequence and to use it for targeted genetic analysis. Microfabricated genetic analysis systems are well poised to assist in the collection and use of these data through increased analysis speed, lower analysis cost and higher parallelism leading to increased assay throughput. In addition, such integrated microsystems may point the way to targeted genetic experiments on single cells and in other areas that are otherwise very difficult. Concomitant with these advantages, such systems, when fully integrated, should be capable of forming portable systems for high-speed in situ analyses, enabling a new standard in disciplines such as clinical chemistry, forensics, biowarfare detection and epidemiology. This review will discuss the various technologies available for genetic analysis on the microscale, and efforts to integrate them to form fully functional robust analysis devices. (topical review)

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

Science.gov (United States)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of 30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Stochastic filtering of quantitative data from STR DNA analysis

DEFF Research Database (Denmark)

Tvedebrink, Torben; Eriksen, Poul Svante; Mogensen, Helle Smidt

due to the apparatus used for measurements). Pull-up effects (more systematic increase caused by overlap in the spectrum) Stutters (peaks located four basepairs before the true peak). We present filtering techniques for all three technical artifacts based on statistical analysis of data from......The quantitative data observed from analysing STR DNA is a mixture of contributions from various sources. Apart from the true allelic peaks, the observed signal consists of at least three components resulting from the measurement technique and the PCR amplification: Background noise (random noise...... controlled experiments conducted at The Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health Sciences, Universityof Copenhagen, Denmark....

GENETIC DIVERSITY ANALYSIS OF MANGABA (Hancornia speciosa Gomes, AN EXOTIC BRAZILIAN TROPICAL SPECIES

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Ana Veruska Cruz da Silva

2012-05-01

Full Text Available Twenty genotypes from natural population of mangaba located in Itaporanga D’Ajuda (Sergipe state - Brazil were subjected to analysis using RAPD markers. Polymorphism, genetic diversity and structure parameters were determined to characterize the differences between plants. 60 DNA fragments were generated by 10 primers, 85% of which were polymorphic. Results show a quantitative genetic diversity value of 0.35 and a Shannon index of 0.46 in the population. The similarity among the specimens according to Jaccard’s coefficient ranged from 0.36 to 0.87. Using cluster analysis it was possible to indentify five groups. Three individuals also stand out since they presented significant divergence from the groups. The PCoA formed four groups, with three of the groups isolated from the others. This investigation showed that genetic diversity was relatively large among these individuals. In addition, the results demonstrated that RAPD markers are a useful tool for evaluating the genetic diversity and relationships among mangaba.

Quantitative analysis of receptor imaging

International Nuclear Information System (INIS)

Fu Zhanli; Wang Rongfu

2004-01-01

Model-based methods for quantitative analysis of receptor imaging, including kinetic, graphical and equilibrium methods, are introduced in detail. Some technical problem facing quantitative analysis of receptor imaging, such as the correction for in vivo metabolism of the tracer and the radioactivity contribution from blood volume within ROI, and the estimation of the nondisplaceable ligand concentration, is also reviewed briefly

Diagnostic performance of semi-quantitative and quantitative stress CMR perfusion analysis: a meta-analysis.

Science.gov (United States)

van Dijk, R; van Assen, M; Vliegenthart, R; de Bock, G H; van der Harst, P; Oudkerk, M

2017-11-27

Stress cardiovascular magnetic resonance (CMR) perfusion imaging is a promising modality for the evaluation of coronary artery disease (CAD) due to high spatial resolution and absence of radiation. Semi-quantitative and quantitative analysis of CMR perfusion are based on signal-intensity curves produced during the first-pass of gadolinium contrast. Multiple semi-quantitative and quantitative parameters have been introduced. Diagnostic performance of these parameters varies extensively among studies and standardized protocols are lacking. This study aims to determine the diagnostic accuracy of semi- quantitative and quantitative CMR perfusion parameters, compared to multiple reference standards. Pubmed, WebOfScience, and Embase were systematically searched using predefined criteria (3272 articles). A check for duplicates was performed (1967 articles). Eligibility and relevance of the articles was determined by two reviewers using pre-defined criteria. The primary data extraction was performed independently by two researchers with the use of a predefined template. Differences in extracted data were resolved by discussion between the two researchers. The quality of the included studies was assessed using the 'Quality Assessment of Diagnostic Accuracy Studies Tool' (QUADAS-2). True positives, false positives, true negatives, and false negatives were subtracted/calculated from the articles. The principal summary measures used to assess diagnostic accuracy were sensitivity, specificity, andarea under the receiver operating curve (AUC). Data was pooled according to analysis territory, reference standard and perfusion parameter. Twenty-two articles were eligible based on the predefined study eligibility criteria. The pooled diagnostic accuracy for segment-, territory- and patient-based analyses showed good diagnostic performance with sensitivity of 0.88, 0.82, and 0.83, specificity of 0.72, 0.83, and 0.76 and AUC of 0.90, 0.84, and 0.87, respectively. In per territory

Genetic Analysis of Health-Related Secondary Metabolites in a Brassica rapa Recombinant Inbred Line Population

NARCIS (Netherlands)

Bagheri, H.; Soda, El M.; Kim, H.K.; Fritsche, S.; Jung, C.; Aarts, M.G.M.

2013-01-01

The genetic basis of the wide variation for nutritional traits in Brassica rapa is largely unknown. A new Recombinant Inbred Line (RIL) population was profiled using High Performance Liquid Chromatography (HPLC) and Nuclear Magnetic Resonance (NMR) analysis to detect quantitative trait loci (QTLs)

Genetics of Obesity Traits: A Bivariate Genome-Wide Association Analysis

DEFF Research Database (Denmark)

Wu, Yili; Duan, Haiping; Tian, Xiaocao

2018-01-01

Previous genome-wide association studies on anthropometric measurements have identified more than 100 related loci, but only a small portion of heritability in obesity was explained. Here we present a bivariate twin study to look for the genetic variants associated with body mass index and waist......-hip ratio, and to explore the obesity-related pathways in Northern Han Chinese. Cholesky decompositionmodel for 242monozygotic and 140 dizygotic twin pairs indicated a moderate genetic correlation (r = 0.53, 95%CI: 0.42–0.64) between body mass index and waist-hip ratio. Bivariate genome-wide association.......05. Expression quantitative trait loci analysis identified rs2242044 as a significant cis-eQTL in both the normal adipose-subcutaneous (P = 1.7 × 10−9) and adipose-visceral (P = 4.4 × 10−15) tissue. These findings may provide an important entry point to unravel genetic pleiotropy in obesity traits....

Systems genetic analysis of brown adipose tissue function

Czech Academy of Sciences Publication Activity Database

Pravenec, Michal; Saba, L. M.; Zídek, Václav; Landa, Vladimír; Mlejnek, Petr; Šilhavý, Jan; Šimáková, Miroslava; Strnad, Hynek; Trnovská, J.; Škop, V.; Hüttl, M.; Marková, I.; Oliyarnyk, O.; Malínská, H.; Kazdová, L.; Smith, H.; Tabakoff, B.

2018-01-01

Roč. 50, č. 1 (2018), s. 52-66 ISSN 1094-8341 R&D Projects: GA ČR(CZ) GA13-04420S Institutional support: RVO:67985823 Keywords : brown adipose tissue * coexpression modules * quantitative trait locus * recombinant inbred strains * spontaneously hypertensive rat Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Human genetics Impact factor: 3.044, year: 2016

Genetic divergence among pumpkin landraces

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Rebeca Lourenço de Oliveira

2016-04-01

Full Text Available Estimating the genetic variability in germplasm collections is important not only for conserving genetic resources, but also for plant breeding purposes. However, generating a large number of different categories data (qualitative and quantitative often complicate the analysis and results interpretation, resulting in an incomplete distinction of accessions. This study reports the characterization and evaluation of 14 pumpkin (Cucurbita moschata accessions collected from farms in the northern region of Rio de Janeiro state. Genetic diversity among accessions was also estimated using qualitative and quantitative variables considering joint analysis. The plants were grown under field conditions in a randomized block design with three replications and six plants per plot. Eight qualitative traits (leaf size; seed shape; seed color; color of the fruit pulp; hollow; fruit shape; skin color, and fruit skin texture and eight quantitative traits (fruit weight; fruit length; fruit diameter; soluble solids, 100 seed weight, and wall thickness measured in the middle and in the lower stem were evaluated. The data were analyzed considering the Gower distance, and cluster analysis was performed using unweighted pair group method with arithmetic mean (UPGMA. Variability among accessions was observed considering morphoagronomic data. The Gower distance together with UPGMA cluster allowed for good discrimination between accessions in the groups, demonstrating that the simultaneous analysis of qualitative and quantitative data is feasible and may increase the understanding of the variation among accessions.

A population genetic interpretation of GWAS findings for human quantitative traits

Science.gov (United States)

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

Genetic variability of hull-less barley accessions based on molecular and quantitative data

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Ricardo Meneses Sayd

2015-02-01

Full Text Available The objective of this work was to characterize and quantify the genetic, molecular, and agronomic variability of hull-less barley genotypes, for the selection of parents and identification of genotypes adapted to the irrigated production system in the Brazilian Cerrado. Eighteen hull-less barley accessions were evaluated, and three covered barley accessions served as reference. The characterization was based on 157 RAPD molecular markers and ten agronomic traits. Genetic distance matrices were obtained based on molecular markers and quantitative traits. Graphic grouping and dispersion analyses were performed. Genetic, molecular, and agronomic variability was high among genotypes. Ethiopian accessions were genetically more similar, and the Brazilian ones were genetically more distant. For agronomic traits, two more consistent groupings were obtained, one with the most two-rowed materials, and the other with six-rowed materials. The more diverging materials were the two-rowed CI 13453, CN Cerrado 5, CN Cerrado 1, and CN Cerrado 2. The PI 356466, CN Cerrado 1, PI 370799, and CI 13453 genotypes show agronomic traits of interest and, as genetically different genotypes, they are indicated for crossing, in breeding programs.

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

Science.gov (United States)

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 ...

The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

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Ronald de Vlaming

2015-01-01

Full Text Available In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i the theoretical foundations of ridge regression, (ii its link to commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

Quantitative analysis of food and feed samples with droplet digital PCR.

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Dany Morisset

Full Text Available In this study, the applicability of droplet digital PCR (ddPCR for routine analysis in food and feed samples was demonstrated with the quantification of genetically modified organisms (GMOs. Real-time quantitative polymerase chain reaction (qPCR is currently used for quantitative molecular analysis of the presence of GMOs in products. However, its use is limited for detecting and quantifying very small numbers of DNA targets, as in some complex food and feed matrices. Using ddPCR duplex assay, we have measured the absolute numbers of MON810 transgene and hmg maize reference gene copies in DNA samples. Key performance parameters of the assay were determined. The ddPCR system is shown to offer precise absolute and relative quantification of targets, without the need for calibration curves. The sensitivity (five target DNA copies of the ddPCR assay compares well with those of individual qPCR assays and of the chamber digital PCR (cdPCR approach. It offers a dynamic range over four orders of magnitude, greater than that of cdPCR. Moreover, when compared to qPCR, the ddPCR assay showed better repeatability at low target concentrations and a greater tolerance to inhibitors. Finally, ddPCR throughput and cost are advantageous relative to those of qPCR for routine GMO quantification. It is thus concluded that ddPCR technology can be applied for routine quantification of GMOs, or any other domain where quantitative analysis of food and feed samples is needed.

Attitudes towards genetic testing: analysis of contradictions

DEFF Research Database (Denmark)

Jallinoja, P; Hakonen, A; Aro, A R

1998-01-01

A survey study was conducted among 1169 people to evaluate attitudes towards genetic testing in Finland. Here we present an analysis of the contradictions detected in people's attitudes towards genetic testing. This analysis focuses on the approval of genetic testing as an individual choice and o...... studies on attitudes towards genetic testing as well as in the health care context, e.g. in genetic counselling.......A survey study was conducted among 1169 people to evaluate attitudes towards genetic testing in Finland. Here we present an analysis of the contradictions detected in people's attitudes towards genetic testing. This analysis focuses on the approval of genetic testing as an individual choice...... and on the confidence in control of the process of genetic testing and its implications. Our analysis indicated that some of the respondents have contradictory attitudes towards genetic testing. It is proposed that contradictory attitudes towards genetic testing should be given greater significance both in scientific...

Genetic Parameters and Combining Ability Effects of Parents for Seed Yield and other Quantitative Traits in Black Gram [Vigna mungo (L. Hepper

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Supriyo CHAKRABORTY

2010-06-01

Full Text Available Line x tester analysis was carried out in black gram [Vigna mungo (L. Hepper], an edible legume, to estimate the gca (general combining ability effects of parents (3 lines and 3 testers and the SCA (specific combining ability effects of 9 crosses for seed yield and other eleven quantitative traits. Though additive and nonadditive gene actions governed the expression of quantitative traits, the magnitude of nonadditive gene action was higher than that of additive gene action for each quantitative trait. Two parents viz. UG157 and DPU915 were good general combiners. Two crosses namely PDB 88-31/DPU 915 and PLU 277/KAU7 had high per se performance along with positive significant SCA effect for seed yield/plant. The degree of dominance revealed overdominance for all the traits except clusters/plant with partial dominance. The predictability ratio also revealed the predominant role of nonadditive gene action in the genetic control of quantitative traits. Narrow sense heritability was also low for each trait. Recurrent selection or biparental mating followed by selection which can exploit both additive and nonadditive gene actions would be of interest for yield improvement in black gram. Due to presence of high magnitude of nonadditive gene action, heterosis breeding could also be attempted to develop low cost hybrid variety using genetic male sterility system in black gram.

A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification

KAUST Repository

Malvezzi, Alex J.

2015-02-01

Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (~2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent-offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection.

Dissecting high-dimensional phenotypes with bayesian sparse factor analysis of genetic covariance matrices.

Science.gov (United States)

Runcie, Daniel E; Mukherjee, Sayan

2013-07-01

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms that link genotype and phenotype. However, classical analytical techniques are poorly suited to quantitative genetic studies of gene expression where the number of traits assayed per individual can reach many thousand. Here, we derive a Bayesian genetic sparse factor model for estimating the genetic covariance matrix (G-matrix) of high-dimensional traits, such as gene expression, in a mixed-effects model. The key idea of our model is that we need consider only G-matrices that are biologically plausible. An organism's entire phenotype is the result of processes that are modular and have limited complexity. This implies that the G-matrix will be highly structured. In particular, we assume that a limited number of intermediate traits (or factors, e.g., variations in development or physiology) control the variation in the high-dimensional phenotype, and that each of these intermediate traits is sparse - affecting only a few observed traits. The advantages of this approach are twofold. First, sparse factors are interpretable and provide biological insight into mechanisms underlying the genetic architecture. Second, enforcing sparsity helps prevent sampling errors from swamping out the true signal in high-dimensional data. We demonstrate the advantages of our model on simulated data and in an analysis of a published Drosophila melanogaster gene expression data set.

Genetic adaptability of inheritance of resistance to biotic and abiotic ...

African Journals Online (AJOL)

Several studies that attempt to identify the genetic basis of quantitative traits ignore the presence of epistatic effects and theirs role in plant genetic adaptability. Epistasis has been detected in the inheritance of many quantitative traits on crop. Moreover, generation means analysis of several traits assessed in diverse ...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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 disordergenetically 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.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

Science.gov (United States)

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Quantitative genome-wide genetic interaction screens reveal global epistatic relationships of protein complexes in Escherichia coli.

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Mohan Babu

2014-02-01

Full Text Available Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI screens can provide insights into the biological role(s of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.

Multivariate analysis of quantitative traits can effectively classify rapeseed germplasm

Directory of Open Access Journals (Sweden)

Jankulovska Mirjana

2014-01-01

Full Text Available In this study, the use of different multivariate approaches to classify rapeseed genotypes based on quantitative traits has been presented. Tree regression analysis, PCA analysis and two-way cluster analysis were applied in order todescribe and understand the extent of genetic variability in spring rapeseed genotype by trait data. The traits which highly influenced seed and oil yield in rapeseed were successfully identified by the tree regression analysis. Principal predictor for both response variables was number of pods per plant (NP. NP and 1000 seed weight could help in the selection of high yielding genotypes. High values for both traits and oil content could lead to high oil yielding genotypes. These traits may serve as indirect selection criteria and can lead to improvement of seed and oil yield in rapeseed. Quantitative traits that explained most of the variability in the studied germplasm were classified using principal component analysis. In this data set, five PCs were identified, out of which the first three PCs explained 63% of the total variance. It helped in facilitating the choice of variables based on which the genotypes’ clustering could be performed. The two-way cluster analysissimultaneously clustered genotypes and quantitative traits. The final number of clusters was determined using bootstrapping technique. This approach provided clear overview on the variability of the analyzed genotypes. The genotypes that have similar performance regarding the traits included in this study can be easily detected on the heatmap. Genotypes grouped in the clusters 1 and 8 had high values for seed and oil yield, and relatively short vegetative growth duration period and those in cluster 9, combined moderate to low values for vegetative growth duration and moderate to high seed and oil yield. These genotypes should be further exploited and implemented in the rapeseed breeding program. The combined application of these multivariate methods

MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis.

Science.gov (United States)

Lee, Dong-Yup; Yun, Hongsoek; Park, Sunwon; Lee, Sang Yup

2003-11-01

MetaFluxNet is a program package for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes in an interactive and customized way. It allows users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications. As a result, quantitative in silico simulations of metabolic pathways can be carried out to understand the metabolic status and to design the metabolic engineering strategies. The main features of the program include a well-developed model construction environment, user-friendly interface for metabolic flux analysis (MFA), comparative MFA of strains having different genotypes under various environmental conditions, and automated pathway layout creation. http://mbel.kaist.ac.kr/ A manual for MetaFluxNet is available as PDF file.

Genetic Parameters and Combining Ability Effects of Parents for Seed Yield and other Quantitative Traits in Black Gram [Vigna mungo (L. Hepper

Directory of Open Access Journals (Sweden)

Supriyo CHAKRABORTY

2010-06-01

Full Text Available Line x tester analysis was carried out in black gram [Vigna mungo (L. Hepper], an edible legume, to estimate the gca (general combining ability effects of parents (3 lines and 3 testers and the SCA (specific combining ability effects of 9 crosses for seed yield and other eleven quantitative traits. Though additive and nonadditive gene actions governed the expression of quantitative traits, the magnitude of nonadditive gene action was higher than that of additive gene action for each quantitative trait. Two parents viz. �UG157� and �DPU915� were good general combiners. Two crosses namely �PDB 88-31�/�DPU 915� and �PLU 277�/�KAU7� had high per se performance along with positive significant SCA effect for seed yield/plant. The degree of dominance revealed overdominance for all the traits except clusters/plant with partial dominance. The predictability ratio also revealed the predominant role of nonadditive gene action in the genetic control of quantitative traits. Narrow sense heritability was also low for each trait. Recurrent selection or biparental mating followed by selection which can exploit both additive and nonadditive gene actions would be of interest for yield improvement in black gram. Due to presence of high magnitude of nonadditive gene action, heterosis breeding could also be attempted to develop low cost hybrid variety using genetic male sterility system in black gram.

Combination and Integration of Qualitative and Quantitative Analysis

Directory of Open Access Journals (Sweden)

Philipp Mayring

2001-02-01

Full Text Available In this paper, I am going to outline ways of combining qualitative and quantitative steps of analysis on five levels. On the technical level, programs for the computer-aided analysis of qualitative data offer various combinations. Where the data are concerned, the employment of categories (for instance by using qualitative content analysis allows for combining qualitative and quantitative forms of data analysis. On the individual level, the creation of types and the inductive generalisation of cases allow for proceeding from individual case material to quantitative generalisations. As for research design, different models can be distinguished (preliminary study, generalisation, elaboration, triangulation which combine qualitative and quantitative steps of analysis. Where the logic of research is concerned, it can be shown that an extended process model which combined qualitative and quantitative research can be appropriate and thus lead to an integration of the two approaches. URN: urn:nbn:de:0114-fqs010162

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

Science.gov (United States)

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.

Energy Dispersive Spectrometry and Quantitative Analysis Short Course. Introduction to X-ray Energy Dispersive Spectrometry and Quantitative Analysis

Science.gov (United States)

Carpenter, Paul; Curreri, Peter A. (Technical Monitor)

2002-01-01

This course will cover practical applications of the energy-dispersive spectrometer (EDS) to x-ray microanalysis. Topics covered will include detector technology, advances in pulse processing, resolution and performance monitoring, detector modeling, peak deconvolution and fitting, qualitative and quantitative analysis, compositional mapping, and standards. An emphasis will be placed on use of the EDS for quantitative analysis, with discussion of typical problems encountered in the analysis of a wide range of materials and sample geometries.

Quantitative genetic models of sexual selection by male choice.

Science.gov (United States)

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.

Inspection, visualisation and analysis of quantitative proteomics data

OpenAIRE

Gatto, Laurent

2016-01-01

Material Quantitative Proteomics and Data Analysis Course. 4 - 5 April 2016, Queen Hotel, Chester, UK Table D - Inspection, visualisation and analysis of quantitative proteomics data, Laurent Gatto (University of Cambridge)

Genetic analysis

NARCIS (Netherlands)

Koornneef, M.; Alonso-Blanco, C.; Stam, P.

2006-01-01

The Mendelian analysis of genetic variation, available as induced mutants or as natural variation, requires a number of steps that are described in this chapter. These include the determination of the number of genes involved in the observed trait's variation, the determination of dominance

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.

Science.gov (United States)

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

Quantitative Moessbauer analysis

International Nuclear Information System (INIS)

Collins, R.L.

1978-01-01

The quantitative analysis of Moessbauer data, as in the measurement of Fe 3+ /Fe 2+ concentration, has not been possible because of the different mean square velocities (x 2 ) of Moessbauer nuclei at chemically different sites. A method is now described which, based on Moessbauer data at several temperatures, permits the comparison of absorption areas at (x 2 )=0. (Auth.)

Quantitative Data Analysis--In the Graduate Curriculum

Science.gov (United States)

Albers, Michael J.

2017-01-01

A quantitative research study collects numerical data that must be analyzed to help draw the study's conclusions. Teaching quantitative data analysis is not teaching number crunching, but teaching a way of critical thinking for how to analyze the data. The goal of data analysis is to reveal the underlying patterns, trends, and relationships of a…

Integrated analysis of genetic data with R

Directory of Open Access Journals (Sweden)

Zhao Jing

2006-01-01

Full Text Available Abstract Genetic data are now widely available. There is, however, an apparent lack of concerted effort to produce software systems for statistical analysis of genetic data compared with other fields of statistics. It is often a tremendous task for end-users to tailor them for particular data, especially when genetic data are analysed in conjunction with a large number of covariates. Here, R http://www.r-project.org, a free, flexible and platform-independent environment for statistical modelling and graphics is explored as an integrated system for genetic data analysis. An overview of some packages currently available for analysis of genetic data is given. This is followed by examples of package development and practical applications. With clear advantages in data management, graphics, statistical analysis, programming, internet capability and use of available codes, it is a feasible, although challenging, task to develop it into an integrated platform for genetic analysis; this will require the joint efforts of many researchers.

Toward genetics-based virus taxonomy: comparative analysis of a genetics-based classification and the taxonomy of picornaviruses.

Science.gov (United States)

Lauber, Chris; Gorbalenya, Alexander E

2012-04-01

Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890-3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the "GENETIC classification"). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny.

Original methods of quantitative analysis developed for diverse samples in various research fields. Quantitative analysis at NMCC

International Nuclear Information System (INIS)

Sera, Koichiro

2003-01-01

Nishina Memorial Cyclotron Center (NMCC) has been opened for nationwide-common utilization of positron nuclear medicine (PET) and PIXE since April 1993. At the present time, nearly 40 subjects of PIXE in various research fields are pursued here, and more than 50,000 samples have been analyzed up to the present. In order to perform quantitative analyses of diverse samples, technical developments in sample preparation, measurement and data analysis have been continuously carried out. Especially, a standard-free method for quantitative analysis'' made it possible to perform analysis of infinitesimal samples, powdered samples and untreated bio samples, which could not be well analyzed quantitatively in the past. The standard-free method'' and a ''powdered internal standard method'' made the process for target preparation quite easier. It has been confirmed that results obtained by these methods show satisfactory accuracy and reproducibility preventing any ambiguity coming from complicated target preparation processes. (author)

Arthritis Genetics Analysis Aids Drug Discovery

Science.gov (United States)

... NIH Research Matters January 13, 2014 Arthritis Genetics Analysis Aids Drug Discovery An international research team identified 42 new ... Edition Distracted Driving Raises Crash Risk Arthritis Genetics Analysis Aids Drug Discovery Oxytocin Affects Facial Recognition Connect with Us ...

Genetic analysis of relative traits for a drought-sensitive mutant

International Nuclear Information System (INIS)

Gao Kangning; Wang Huaqi

2009-01-01

A drought-sensitive mutant (M616), selected from Handao 616 (HD616) by 60 Co γ-irradiation at 200Gy, was used. Some morphological and yield related traits of M166 and HD616 related to drought resistance were investigated. We further developed F 1 and F 2 reciprocal hybrid combinations derived from the crosses between M616 and HD616, between M616 and IRAT109, respectively, and genetic analysis of 3 traits including plant height, culm width of main stem and seed setting rate on main panicle were camed out. The results showed that M616 showed obviously sensitive to drought stress. Analysis of variance for three traits in upland and paddy between F 1 reciprocal hybrid combinations showed that each trait had no significant difference, and indicated that there were no differences of cytoplasmic hereditary effect. In addition, 3 traits of F 2 populations, were found that the frequency distributions of culm width showed normal distribution, indicating that culm width was polygenic trait, and the frequency distribution of plant height and seed setting rate did not show normal distribution, indicating that the two traits were qualitative-quantitative traits. Genetic analysis of relative traits for a drought-sensitive mutant of upland rice was a basic work for the gene location and cloning. (authors)

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

Science.gov (United States)

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

Science.gov (United States)

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 analysis of untreated bio-samples

International Nuclear Information System (INIS)

Sera, K.; Futatsugawa, S.; Matsuda, K.

1999-01-01

A standard-free method of quantitative analysis for untreated samples has been developed. For hair samples, measurements were performed by irradiating with a proton beam a few hairs as they are, and quantitative analysis was carried out by means of a standard-free method developed by ourselves. First, quantitative values of concentration of zinc were derived, then concentration of other elements was obtained by regarding zinc as an internal standard. As the result, values of concentration of sulphur for 40 samples agree well with the average value for a typical Japanese and also with each other within 20%, and validity of the present method could be confirmed. Accuracy was confirmed by comparing the results with those obtained by the usual internal standard method, too. For the purpose of a surface analysis of a bone sample, a very small incidence angle of the proton beam was used, so that both energy loss of the projectile and self-absorption of X-rays become negligible. As the result, consistent values of concentration for many elements were obtained by the standard-free method

Quantitative analysis of boron by neutron radiography

International Nuclear Information System (INIS)

Bayuelken, A.; Boeck, H.; Schachner, H.; Buchberger, T.

1990-01-01

The quantitative determination of boron in ores is a long process with chemical analysis techniques. As nuclear techniques like X-ray fluorescence and activation analysis are not applicable for boron, only the neutron radiography technique, using the high neutron absorption cross section of this element, can be applied for quantitative determinations. This paper describes preliminary tests and calibration experiments carried out at a 250 kW TRIGA reactor. (orig.) [de

Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy

Directory of Open Access Journals (Sweden)

Saud Alhusaini

2016-01-01

Full Text Available Over the last decade, the field of imaging genomics has combined high-throughput genotype data with quantitative magnetic resonance imaging (QMRI measures to identify genes associated with brain structure, cognition, and several brain-related disorders. Despite its successful application in different psychiatric and neurological disorders, the field has yet to be advanced in epilepsy. In this article we examine the relevance of imaging genomics for future genetic studies in epilepsy from three perspectives. First, we discuss prior genome-wide genetic mapping efforts in epilepsy, considering the possibility that some studies may have been constrained by inherent theoretical and methodological limitations of the genome-wide association study (GWAS method. Second, we offer a brief overview of the imaging genomics paradigm, from its original inception, to its role in the discovery of important risk genes in a number of brain-related disorders, and its successful application in large-scale multinational research networks. Third, we provide a comprehensive review of past studies that have explored the eligibility of brain QMRI traits as endophenotypes for epilepsy. While the breadth of studies exploring QMRI-derived endophenotypes in epilepsy remains narrow, robust syndrome-specific neuroanatomical QMRI traits have the potential to serve as accessible and relevant intermediate phenotypes for future genetic mapping efforts in epilepsy.

Microsatellite data analysis for population genetics

Science.gov (United States)

Theories and analytical tools of population genetics have been widely applied for addressing various questions in the fields of ecological genetics, conservation biology, and any context where the role of dispersal or gene flow is important. Underlying much of population genetics is the analysis of ...

The Analysis of Polyploid Genetic Data

NARCIS (Netherlands)

Meirmans, P.G.; Liu, S.; van Tienderen, P.H.

2018-01-01

Though polyploidy is an important aspect of the evolutionary genetics of both plants and animals, the development of population genetic theory of polyploids has seriously lagged behind that of diploids. This is unfortunate since the analysis of polyploid genetic data—and the interpretation of the

Quantitative trait loci mapping for stomatal traits in interspecific ...

Indian Academy of Sciences (India)

M. Sumathi

2018-02-23

Feb 23, 2018 ... Journal of Genetics, Vol. ... QTL analysis was carried out to identify the chromosomal regions affecting ... Keywords. linkage map; quantitative trait loci; stomata; stress ..... of India for providing financial support for the project.

Structural model analysis of multiple quantitative traits.

Directory of Open Access Journals (Sweden)

Renhua Li

2006-07-01

Full Text Available We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

Genetic Analysis of Micro-environmental Plasticity in Drosophila melanogaster

DEFF Research Database (Denmark)

Morgante, Fabio; Sorensen, Daniel A; Sørensen, Peter

Quantitative genetic models recognize the potential for genotype by environment interaction, whereby different genotypes have different plastic responses to changes in macro-environmental conditions. Recently, it has been recognized that micro-environmental plasticity (‘residual’ variance) may also...... be genetically variable. This study utilized the Drosophila Genetic Reference Panel (DGRP) to accurately estimate the genetic variance of micro-environmental plasticity for chill coma recovery time and startle response. Estimates of broad sense heritabilities for both traits are substantial (from 0.51 to 0.......77), of the same order as the heritability at the level of the trait mean for startle response and even larger for chill coma recovery. Genome wide association analyses identified molecular variants (from 15 to 31 depending on the sex and the trait) associated with micro-environmental plasticity. These findings...

An analysis of the genetic diversity and genetic structure of ...

African Journals Online (AJOL)

Scientific approaches to conservation of threatened species depend on a good understanding of the genetic information of wild and artificial population. The genetic diversity and structure analysis of 10 Eucommia ulmoides population was analyzed using inter-simple sequence repeat (ISSR) markers in this paper.

Quantitative image analysis of synovial tissue

NARCIS (Netherlands)

van der Hall, Pascal O.; Kraan, Maarten C.; Tak, Paul Peter

2007-01-01

Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the

Quantitative Auger analysis of Nb-Ge superconducting alloys

International Nuclear Information System (INIS)

Buitrago, R.H.

1980-01-01

The feasibility of using Auger electron analysis for quantitative analysis was investigated by studying Nb 3 Ge thin-film Auger data with different approaches. A method base on elemental standards gave consistent quantitative values with reported Nb-Ge data. Alloy sputter yields were also calculated and results were consistent with those for pure elements

Genetic itemization of exotic sugarcane clones of the basis of quantitative and qualitative parameters

International Nuclear Information System (INIS)

Seema, N.; Khan, M. T.; Khan, I. A.; Yasmeen, S.

2017-01-01

Sugarcane varietal development program in Pakistan primarily depends on evaluation of imported genotypes because of the unfavorable climatic conditions for sugarcane flowering and hybridization in the country. Performance of 41 exotic sugarcane clones was assessed in this study on the basis of seven quantitative (plant height, number of tillers, internode length, number of internode, cane girth, cane yield, and weight per stool) and six qualitative (sucrose %, brix %, CCS %, fiber %, sugar recovery % and sugar yield) attributes. Sugarcane clones comprised of fifteen genotypes from Canal Point (USA), eight from Homma (USA), and eighteen from Brazil. The clones exhibited statistically significant differences for tillers per plant, weight per stool, plant height, cane yield, brix%, sucrose%, fiber%, sugar recovery and sugar yield. Highest cane yield of 51.66 t/ha was observed for Canal Point clone CPNIA-240 while the lowest yield of 26.66 t/ha was recorded in Homma clone HoNIA-795. The highest sugar recovery (10.83 and 10.81) was exhibited by the clones SPNIA-396 and SPNIA-8 whereas the lowest (4.00) was observed in clone SPNIA-05. Moreover, maximum sugar yield was recorded in clone SPNIA-8 (5.37 tha-1) and minimum was observed in clone SPNIA-05 (0.91). Ward's linkage cluster analysis of the exotic clones placed the genotypes into six major groups in dendrogram. Genotypes appeared in the clusters irrespective of their geographical location. Cluster II, IV and V showed excellent qualitative, combination of quantitative and qualitative, and quantitative characters respectively. Clones from different clusters demonstrate genetic variations and thus can be subjected to selection and hybridization for further improvement. The accessions demonstrating excellent cane and sugar yield can serve as potential candidates for varietal development program in Pakistan. (author)

The Analysis of Polyploid Genetic Data.

Science.gov (United States)

Meirmans, Patrick G; Liu, Shenglin; van Tienderen, Peter H

2018-03-16

Though polyploidy is an important aspect of the evolutionary genetics of both plants and animals, the development of population genetic theory of polyploids has seriously lagged behind that of diploids. This is unfortunate since the analysis of polyploid genetic data-and the interpretation of the results-requires even more scrutiny than with diploid data. This is because of several polyploidy-specific complications in segregation and genotyping such as tetrasomy, double reduction, and missing dosage information. Here, we review the theoretical and statistical aspects of the population genetics of polyploids. We discuss several widely used types of inferences, including genetic diversity, Hardy-Weinberg equilibrium, population differentiation, genetic distance, and detecting population structure. For each, we point out how the statistical approach, expected result, and interpretation differ between different ploidy levels. We also discuss for each type of inference what biases may arise from the polyploid-specific complications and how these biases can be overcome. From our overview, it is clear that the statistical toolbox that is available for the analysis of genetic data is flexible and still expanding. Modern sequencing techniques will soon be able to overcome some of the current limitations to the analysis of polyploid data, though the techniques are lagging behind those available for diploids. Furthermore, the availability of more data may aggravate the biases that can arise, and increase the risk of false inferences. Therefore, simulations such as we used throughout this review are an important tool to verify the results of analyses of polyploid genetic data.

COMPUTER METHODS OF GENETIC ANALYSIS.

Directory of Open Access Journals (Sweden)

A. L. Osipov

2017-02-01

Full Text Available The basic statistical methods used in conducting the genetic analysis of human traits. We studied by segregation analysis, linkage analysis and allelic associations. Developed software for the implementation of these methods support.

Genetic Architecture and heritability of some Quantitative Characters,oil content and fatty.acid composition in safflower

International Nuclear Information System (INIS)

Ragab, A.I.; Fried, W.

1992-01-01

The nature of gene action for some quantitative, oil content and quality characters in safflower was studied in an F 1 diallel set involving 4 parents. Both additive and dominance genetic variance were important for most traits. The magnitude of non additive gene action was higher than of additive genetic variance for all traits, except for first branch height, palmitic and stearic acids. The distribution of positive and negative alleles in the parental populations was a symmetrical for all traits except for 100-seed weight. Most of dominant genes had positive effects in plant height, oil content and oleic acid. Dominance degree was over dominance for all traits except for flowering date and first branch height which showed partial dominance. The narrow sense heritability was 75%, 82%, and 89% for stearic acid, flowering date and first branch height, whears 50 to 67% were found for seed yield/plant, plant height, and oil content. Values of less than 50% were determined for other traits. The V r-W r graphical analysis showed partial dominance for flowering date, first branch height, no. of capitula/plant, palmitic and linoleic acids. Complete dominance for 100-seed weight and over dominance for plant height, seed yield, oil content and oleic acid. 2 fig., 2 tab

Sparse Canonical Correlation Analysis via Truncated ℓ1-norm with Application to Brain Imaging Genetics.

Science.gov (United States)

Du, Lei; Zhang, Tuo; Liu, Kefei; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L; Guo, Lei; Saykin, Andrew J; Shen, Li

2016-01-01

Discovering bi-multivariate associations between genetic markers and neuroimaging quantitative traits is a major task in brain imaging genetics. Sparse Canonical Correlation Analysis (SCCA) is a popular technique in this area for its powerful capability in identifying bi-multivariate relationships coupled with feature selection. The existing SCCA methods impose either the ℓ 1 -norm or its variants. The ℓ 0 -norm is more desirable, which however remains unexplored since the ℓ 0 -norm minimization is NP-hard. In this paper, we impose the truncated ℓ 1 -norm to improve the performance of the ℓ 1 -norm based SCCA methods. Besides, we propose two efficient optimization algorithms and prove their convergence. The experimental results, compared with two benchmark methods, show that our method identifies better and meaningful canonical loading patterns in both simulated and real imaging genetic analyse.

Interdependence of PRECIS Role Operators: A Quantitative Analysis of Their Associations.

Science.gov (United States)

Mahapatra, Manoranjan; Biswas, Subal Chandra

1986-01-01

Analyzes associations among different role operators quantitatively by taking input strings from 200 abstracts, each related to subject fields of taxation, genetic psychology, and Shakespearean drama, and subjecting them to the Chi-square test. Significant associations by other differencing operators and connectives are discussed. A schema of role…

Genetic analysis in Bartter syndrome from India.

Science.gov (United States)

Sharma, Pradeep Kumar; Saikia, Bhaskar; Sharma, Rachna; Ankur, Kumar; Khilnani, Praveen; Aggarwal, Vinay Kumar; Cheong, Hae

2014-10-01

Bartter syndrome is a group of inherited, salt-losing tubulopathies presenting as hypokalemic metabolic alkalosis with normotensive hyperreninemia and hyperaldosteronism. Around 150 cases have been reported in literature till now. Mutations leading to salt losing tubulopathies are not routinely tested in Indian population. The authors have done the genetic analysis for the first time in the Bartter syndrome on two cases from India. First case was antenatal Bartter syndrome presenting with massive polyuria and hyperkalemia. Mutational analysis revealed compound heterozygous mutations in KCNJ1(ROMK) gene [p(Leu220Phe), p(Thr191Pro)]. Second case had a phenotypic presentation of classical Bartter syndrome however, genetic analysis revealed only heterozygous novel mutation in SLC12A gene p(Ala232Thr). Bartter syndrome is a clinical diagnosis and genetic analysis is recommended for prognostication and genetic counseling.

Genetic divergence in quercus suber L. based on qualitative and quantitative traits

International Nuclear Information System (INIS)

Akbar, F.; Shinwari, Z.K.; Khan, S.J.

2011-01-01

Sesame (Sesamum indicum L.) is one of the world's oldest oil crops and has been cultivated in Asia since ancient times. The breeding potential of the germplasm accessions held in PGRP gene-bank has hardly been exploited to date. This study was carried out to evaluate the phenotypic variability in the local sesame genotypes using 16 qualitative and quantitative traits. A total of 105 sesame accessions collected from diverse ecologies of Pakistan were used. A considerable level of variation was recorded for a number of morphologic and agronomic traits, while limited diversity for observed among the accessions for characters like stem hairiness, flower color (white with purple shading), seed color and to some extent phyllody disease. The correlation coefficient analysis indicated that plant height, capsules plant/sup -1/, capsule length and 1000-seed weight had the significant positive effect on seed yield. The characters related to maturity, days to flower initiation an d days to 50% flowering showed negative correlation with seed yield. Multivariate analysis was performed in order to establish similarity and dissimilarity patterns. Principal component (PC) analysis revealed that first three PC axes explained 54.21% of the total multivariate variation, while the first four PC axes explaining 63.64%. Plant height, days to maturity, capsules plant/sup -1/ and seed yield plant/sup -1/ were the major determinants of the genetic diversity in the collection. Cluster analysis places all the accessions into seven groups. Clustering was not associated with the geographical distribution instead accessions were mainly grouped due to their morphological differences. Elite sesame germplasm has been selected on the basis of best agro-morphological performance from 105 sesame collections. These results have an important suggestion for sesame germplasm agro-morphological assessment, enhancement, categorization and conservation in Pakistan. (author)

[Quantitative data analysis for live imaging of bone.

Science.gov (United States)

Seno, Shigeto

Bone tissue is a hard tissue, it was difficult to observe the interior of the bone tissue alive. With the progress of microscopic technology and fluorescent probe technology in recent years, it becomes possible to observe various activities of various cells forming bone society. On the other hand, the quantitative increase in data and the diversification and complexity of the images makes it difficult to perform quantitative analysis by visual inspection. It has been expected to develop a methodology for processing microscopic images and data analysis. In this article, we introduce the research field of bioimage informatics which is the boundary area of biology and information science, and then outline the basic image processing technology for quantitative analysis of live imaging data of bone.

A non-parametric mixture model for genome-enabled prediction of genetic value for a quantitative trait.

Science.gov (United States)

Gianola, Daniel; Wu, Xiao-Lin; Manfredi, Eduardo; Simianer, Henner

2010-10-01

A Bayesian nonparametric form of regression based on Dirichlet process priors is adapted to the analysis of quantitative traits possibly affected by cryptic forms of gene action, and to the context of SNP-assisted genomic selection, where the main objective is to predict a genomic signal on phenotype. The procedure clusters unknown genotypes into groups with distinct genetic values, but in a setting in which the number of clusters is unknown a priori, so that standard methods for finite mixture analysis do not work. The central assumption is that genetic effects follow an unknown distribution with some "baseline" family, which is a normal process in the cases considered here. A Bayesian analysis based on the Gibbs sampler produces estimates of the number of clusters, posterior means of genetic effects, a measure of credibility in the baseline distribution, as well as estimates of parameters of the latter. The procedure is illustrated with a simulation representing two populations. In the first one, there are 3 unknown QTL, with additive, dominance and epistatic effects; in the second, there are 10 QTL with additive, dominance and additive × additive epistatic effects. In the two populations, baseline parameters are inferred correctly. The Dirichlet process model infers the number of unique genetic values correctly in the first population, but it produces an understatement in the second one; here, the true number of clusters is over 900, and the model gives a posterior mean estimate of about 140, probably because more replication of genotypes is needed for correct inference. The impact on inferences of the prior distribution of a key parameter (M), and of the extent of replication, was examined via an analysis of mean body weight in 192 paternal half-sib families of broiler chickens, where each sire was genotyped for nearly 7,000 SNPs. In this small sample, it was found that inference about the number of clusters was affected by the prior distribution of M. For a

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

Science.gov (United States)

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.

Integrating molecular QTL data into genome-wide genetic association analysis: Probabilistic assessment of enrichment and colocalization.

Directory of Open Access Journals (Sweden)

Xiaoquan Wen

2017-03-01

Full Text Available We propose a novel statistical framework for integrating the result from molecular quantitative trait loci (QTL mapping into genome-wide genetic association analysis of complex traits, with the primary objectives of quantitatively assessing the enrichment of the molecular QTLs in complex trait-associated genetic variants and the colocalizations of the two types of association signals. We introduce a natural Bayesian hierarchical model that treats the latent association status of molecular QTLs as SNP-level annotations for candidate SNPs of complex traits. We detail a computational procedure to seamlessly perform enrichment, fine-mapping and colocalization analyses, which is a distinct feature compared to the existing colocalization analysis procedures in the literature. The proposed approach is computationally efficient and requires only summary-level statistics. We evaluate and demonstrate the proposed computational approach through extensive simulation studies and analyses of blood lipid data and the whole blood eQTL data from the GTEx project. In addition, a useful utility from our proposed method enables the computation of expected colocalization signals using simple characteristics of the association data. Using this utility, we further illustrate the importance of enrichment analysis on the ability to discover colocalized signals and the potential limitations of currently available molecular QTL data. The software pipeline that implements the proposed computation procedures, enloc, is freely available at https://github.com/xqwen/integrative.

Quantitative phase analysis by neutron diffraction

Energy Technology Data Exchange (ETDEWEB)

Lee, Chang Hee; Song, Su Ho; Lee, Jin Ho; Shim, Hae Seop [Korea Atomic Energy Research Institute, Taejon (Korea)

1999-06-01

This study is to apply quantitative phase analysis (QPA) by neutron diffraction to the round robin samples provided by the International Union of Crystallography(IUCr). We measured neutron diffraction patterns for mixed samples which have several different weight percentages and their unique characteristic features. Neutron diffraction method has been known to be superior to its complementary methods such as X-ray or Synchrotron, but it is still accepted as highly reliable under limited conditions or samples. Neutron diffraction has strong capability especially on oxides due to its scattering cross-section of the oxygen and it can become a more strong tool for analysis on the industrial materials with this quantitative phase analysis techniques. By doing this study, we hope not only to do one of instrument performance tests on our HRPD but also to improve our ability on the analysis of neutron diffraction data by comparing our QPA results with others from any advanced reactor facilities. 14 refs., 4 figs., 6 tabs. (Author)

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Research Article Volume 92 Issue 3 December 2013 pp 529-543 ... combining ability; NCII design; QTL analysis; digenic; multiple alleles. ... and Quantitative Genetics, College of Agricultural Science, Yangzhou University, 225009 Yangzhou, ...

Are quantitative trait-dependent sampling designs cost-effective for analysis of rare and common variants?

Science.gov (United States)

Yilmaz, Yildiz E; Bull, Shelley B

2011-11-29

Use of trait-dependent sampling designs in whole-genome association studies of sequence data can reduce total sequencing costs with modest losses of statistical efficiency. In a quantitative trait (QT) analysis of data from the Genetic Analysis Workshop 17 mini-exome for unrelated individuals in the Asian subpopulation, we investigate alternative designs that sequence only 50% of the entire cohort. In addition to a simple random sampling design, we consider extreme-phenotype designs that are of increasing interest in genetic association analysis of QTs, especially in studies concerned with the detection of rare genetic variants. We also evaluate a novel sampling design in which all individuals have a nonzero probability of being selected into the sample but in which individuals with extreme phenotypes have a proportionately larger probability. We take differential sampling of individuals with informative trait values into account by inverse probability weighting using standard survey methods which thus generalizes to the source population. In replicate 1 data, we applied the designs in association analysis of Q1 with both rare and common variants in the FLT1 gene, based on knowledge of the generating model. Using all 200 replicate data sets, we similarly analyzed Q1 and Q4 (which is known to be free of association with FLT1) to evaluate relative efficiency, type I error, and power. Simulation study results suggest that the QT-dependent selection designs generally yield greater than 50% relative efficiency compared to using the entire cohort, implying cost-effectiveness of 50% sample selection and worthwhile reduction of sequencing costs.

Island Rule, quantitative genetics and brain-body size evolution in Homo floresiensis.

Science.gov (United States)

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).

Genetic control of environmental variation of two quantitative traits of Drosophila melanogaster revealed by whole-genome sequencing

DEFF Research Database (Denmark)

Sørensen, Peter; de los Campos, Gustavo; Morgante, Fabio

2015-01-01

and others more volatile performance. Understanding the mechanisms responsible for environmental variability not only informs medical questions but is relevant in evolution and in agricultural science. In this work fully sequenced inbred lines of Drosophila melanogaster were analyzed to study the nature...... of genetic control of environmental variance for two quantitative traits: starvation resistance (SR) and startle response (SL). The evidence for genetic control of environmental variance is compelling for both traits. Sequence information is incorporated in random regression models to study the underlying...... genetic signals, which are shown to be different in the two traits. Genomic variance in sexual dimorphism was found for SR but not for SL. Indeed, the proportion of variance captured by sequence information and the contribution to this variance from four chromosome segments differ between sexes in SR...

A Multivariate Study on Genetic Variation in Teak (Tectona grandis (L.))

DEFF Research Database (Denmark)

Kjær, Erik Dahl; Siegismund, Hans Redlef; Suangtho, V.

1996-01-01

Genetic differentiation between populations of teak (Tectona grandis (L.)) was examined in 9 quantitative characters and 10 allozyme loci. Large differences between populations were revealed in the quantitative traits. Regional patterns were revealed by multivariate analysis of the data, but ther...

Risk analysis of bioprocesses based on genetically modified bacteria. Pathway and exposure modeling

Energy Technology Data Exchange (ETDEWEB)

Rein, A.; Bittens, M. [Tuebingen Univ. (Germany). Zentrum fuer Angewandte Geowissenschaften

2003-07-01

For soils contaminated with polychlorinated biphenyls (PCBs), a plant-microorganism system for in situ - bioremediation has been developed. It consists of genetically modified microorganisms (GMOs) in conjunction with plant roots. The GMOs are Pseudomonas fluorescens strains which are genetically engineered to degrade PCB congeners in situ. Their metabolism requires root exudates and is therefore tightly coupled to plant rhizospheres. Compared to wild type organisms, the genetically modified bacteria develop a specificity to PCB as a substrate and therefore foster biodegradation in a more efficient way. To evaluate the efficiency and impact of this bioremediation system for potential field application, lysimeter tests are carried out. The lysimeters are filled with contaminated soil from a PCB release site in Denmark and planted with GMO inoculated plants. On the basis of these experiments, a detailed risk analysis is carried out to obtain conclusions to field-conditions (potential deliberate GMO-release). A qualitative and quantitative assessment of actual or potential effects is performed, addressing transport, fate and exposure of PCBs, GMOs and specific degradation products in different environmental compartments. (orig.)

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

Science.gov (United States)

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.

Quantitative standard-less XRF analysis

International Nuclear Information System (INIS)

Ulitzka, S.

2002-01-01

Full text: For most analytical tasks in the mining and associated industries matrix-matched calibrations are used for the monitoring of ore grades and process control. In general, such calibrations are product specific (iron ore, bauxite, alumina, mineral sands, cement etc.) and apply to a relatively narrow concentration range but give the best precision and accuracy for those materials. A wide range of CRMs is available and for less common materials synthetic standards can be made up from 'pure' chemicals. At times, analysis of materials with varying matrices (powders, scales, fly ash, alloys, polymers, liquors, etc.) and diverse physical shapes (non-flat, metal drillings, thin layers on substrates etc.) is required that could also contain elements which are not part of a specific calibration. A qualitative analysis can provide information about the presence of certain elements and the relative intensities of element peaks in a scan can give a rough idea about their concentrations. More often however, quantitative values are required. The paper will look into the basics of quantitative standardless analysis and show results for some well-defined CRMs. Copyright (2002) Australian X-ray Analytical Association Inc

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Timothée Bonnet

2017-01-01

Full Text Available 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

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

Science.gov (United States)

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

Rapid Genetic Analysis in Congenital Hyperinsulinism

DEFF Research Database (Denmark)

Christesen, Henrik Thybo; Brusgaard, Klaus; Alm, Jan

2007-01-01

BACKGROUND: In severe, medically unresponsive congenital hyperinsulinism (CHI), the histological differentiation of focal versus diffuse disease is vital, since the surgical management is completely different. Genetic analysis may help in the differential diagnosis, as focal CHI is associated...... with a paternal germline ABCC8 or KCNJ11 mutation and a focal loss of maternal chromosome 11p15, whereas a maternal mutation, or homozygous/compound heterozygous ABCC8 and KCNJ11 mutations predict diffuse-type disease. However, genotyping usually takes too long to be helpful in the absence of a founder mutation....... METHODS: In 4 patients, a rapid genetic analysis of the ABBC8 and KCNJ11 genes was performed within 2 weeks on request prior to the decision of pancreatic surgery. RESULTS: Two patients had no mutations, rendering the genetic analysis non-informative. Peroperative multiple biopsies showed diffuse disease...

Identifying novel genes for atherosclerosis through mouse-human comparative genetics

NARCIS (Netherlands)

Wang, XS; Ishimori, N; Korstanje, R; Rollins, J; Paigen, B

Susceptibility to atherosclerosis is determined by both environmental and genetic factors. Its genetic determinants have been studied by use of quantitative- trait - locus ( QTL) analysis. So far, 21 atherosclerosis QTLs have been identified in the mouse: 7 in a high- fat - diet model only, 9 in a

Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites

KAUST Repository

Abkallo, Hussein M.

2016-10-01

Identifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.

Reactor applications of quantitative diffraction analysis

International Nuclear Information System (INIS)

Feguson, I.F.

1976-09-01

Current work in quantitative diffraction analysis was presented under the main headings of: thermal systems, fast reactor systems, SGHWR applications and irradiation damage. Preliminary results are included on a comparison of various new instrumental methods of boron analysis as well as preliminary new results on Zircaloy corrosion, and materials transfer in liquid sodium. (author)

Multivariate genetic analysis of brain structure in an extended twin design

DEFF Research Database (Denmark)

Posthuma, D; de Geus, E.J.; Neale, M.C.

2000-01-01

quantitative scale and thus can be assessed in affected and unaffected individuals. Continuous measures increase the statistical power to detect genetic effects (Neale et al., 1994), and allow studies to be designed to collect data from informative subjects such as extreme concordant or discordant pairs....... Intermediate phenotypes for discrete traits, such as psychiatric disorders, can be neurotransmitter levels, brain function, or structure. In this paper we conduct a multivariate analysis of data from 111 twin pairs and 34 additional siblings on cerebellar volume, intracranial space, and body height....... The analysis is carried out on the raw data and specifies a model for the mean and the covariance structure. Results suggest that cerebellar volume and intracranial space vary with age and sex. Brain volumes tend to decrease slightly with age, and males generally have a larger brain volume than females...

Quantitative analysis of myocardial tissue with digital autofluorescence microscopy

Directory of Open Access Journals (Sweden)

Thomas Jensen

2016-01-01

Full Text Available Background: The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including staining may benefit. Methods: This study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm are presented. Results: It is shown that the autofluorescence intensity of unstained microsections at two different wavelengths is a suitable starting point for automated digital analysis of myocytes, fibrous tissue, lipofuscin, and the extracellular compartment. The output of the method is absolute quantitation along with accurate outlines of above-mentioned components. The digital quantitations are verified by comparison to point grid quantitations performed on the microsections after Van Gieson staining. Conclusion: The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue. The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.

Development and evaluation of event-specific quantitative PCR method for genetically modified soybean A2704-12.

Science.gov (United States)

Takabatake, Reona; Akiyama, Hiroshi; Sakata, Kozue; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Teshima, Reiko; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2011-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event; A2704-12. During the plant transformation, DNA fragments derived from pUC19 plasmid were integrated in A2704-12, and the region was found to be A2704-12 specific. The pUC19-derived DNA sequences were used as primers for the specific detection of A2704-12. We first tried to construct a standard plasmid for A2704-12 quantification using pUC19. However, non-specific signals appeared with both qualitative and quantitative PCR analyses using the specific primers with pUC19 as a template, and we then constructed a plasmid using pBR322. The conversion factor (C(f)), which is required to calculate the amount of the genetically modified organism (GMO), was experimentally determined with two real-time PCR instruments, the Applied Biosystems 7900HT and the Applied Biosystems 7500. The determined C(f) values were both 0.98. The quantitative method was evaluated by means of blind tests in multi-laboratory trials using the two real-time PCR instruments. The limit of quantitation for the method was estimated to be 0.1%. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSD(R)), and the determined bias and RSD(R) values for the method were each less than 20%. These results suggest that the developed method would be suitable for practical analyses for the detection and quantification of A2704-12.

QUANTITATIVE GENETICS OF MORPHOLOGICAL DIFFERENTIATION IN PEROMYSCUS. II. ANALYSIS OF SELECTION AND DRIFT.

Science.gov (United States)

Lofsvold, David

1988-01-01

The hypothesis that the morphological divergence of local populations of Peromyscus is due to random genetic drift was evaluated by testing the proportionality of the among-locality covariance matrix, L, and the additive genetic covariance matrix, G. Overall, significant proportionality of L̂ and Ĝ was not observed, indicating the evolutionary divergence of local populations does not result from random genetic drift. The forces of selection needed to differentiate three taxa of Peromyscus were reconstructed to examine the divergence of species and subspecies. The selection gradients obtained illustrate the inadequacy of univariate analyses of selection by finding that some characters evolve in the direction opposite to the force of selection acting directly on them. A retrospective selection index was constructed using the estimated selection gradients, and truncation selection on this index was used to estimate the minimum selective mortality per generation required to produce the observed change. On any of the time scales used, the proportion of the population that would need to be culled was quite low, the greatest being of the same order of magnitude as the selective intensities observed in extant natural populations. Thus, entirely plausible intensities of directional natural selection can produce species-level differences in a period of time too short to be resolved in the fossil record. © 1988 The Society for the Study of Evolution.

Clinical and genetic analysis of Indian patients with NDP-related retinopathies.

Science.gov (United States)

Sudha, Dhandayuthapani; Ganapathy, Aparna; Mohan, Puja; Mannan, Ashraf U; Krishna, Shuba; Neriyanuri, Srividya; Swaminathan, Meenakshi; Rishi, Pukhraj; Chidambaram, Subbulakshmi; Arunachalam, Jayamuruga Pandian

2017-06-10

NDP-related retinopathies are a group of X-linked disorders characterized by degenerative and proliferative changes of the neuroretina, occasionally accompanied with varying degrees of mental retardation and sensorineural hearing loss. NDP is the predominant gene associated with NDP-related retinopathies. The purpose of this study was to report the clinical and genetic findings in three unrelated patients diagnosed with NDP-related retinopathies. The patients underwent complete ophthalmic examination followed by genetic analyses. NDP gene was screened by direct sequencing approach. Targeted resequencing of several other ocular genes was carried out in patient samples that either indicated NDP gene deletion or tested negative for NDP mutation. Gene quantitation analysis was performed using real-time PCR. The whole NDP gene was deleted in patient I, while a missense NDP mutation, c.205T>C, was identified in patient II, and both had classical Norrie disease ocular phenotype (with no other systemic defects). Patient III who was diagnosed with familial exudative vitreoretinopathy did not show any mutation in the known candidate genes as well as in other ocular genes tested. The patient with whole NDP gene deletion did not exhibit any apparent extraocular defects (like mental retardation or sensorineural hearing loss) during his first decade of life, and this is considered to be a notable finding. Our study also provides evidence emphasizing the need for genetic testing which could eliminate ambiguities in clinical diagnosis and detect carrier status, thereby aiding the patient and family members during genetic counseling.

Analysis of genetic diversity inpigeonpeagermplasm using ...

Indian Academy of Sciences (India)

Navya

2016-11-25

Nov 25, 2016 ... accessions from Orissa (105) and AP (15) do not group with any Indian accessions. ... In the present work, comparison between SSAP and REMAP revealed ... (sequence-specific amplified polymorphism) for genetic analysis of sweet potato. ... Sharma,V.and Nandinemi, M.R. 2014 Assessment of genetic ...

Functional mapping imprinted quantitative trait loci underlying developmental characteristics

Directory of Open Access Journals (Sweden)

Li Gengxin

2008-03-01

Full Text Available Abstract Background Genomic imprinting, a phenomenon referring to nonequivalent expression of alleles depending on their parental origins, has been widely observed in nature. It has been shown recently that the epigenetic modification of an imprinted gene can be detected through a genetic mapping approach. Such an approach is developed based on traditional quantitative trait loci (QTL mapping focusing on single trait analysis. Recent studies have shown that most imprinted genes in mammals play an important role in controlling embryonic growth and post-natal development. For a developmental character such as growth, current approach is less efficient in dissecting the dynamic genetic effect of imprinted genes during individual ontology. Results Functional mapping has been emerging as a powerful framework for mapping quantitative trait loci underlying complex traits showing developmental characteristics. To understand the genetic architecture of dynamic imprinted traits, we propose a mapping strategy by integrating the functional mapping approach with genomic imprinting. We demonstrate the approach through mapping imprinted QTL controlling growth trajectories in an inbred F2 population. The statistical behavior of the approach is shown through simulation studies, in which the parameters can be estimated with reasonable precision under different simulation scenarios. The utility of the approach is illustrated through real data analysis in an F2 family derived from LG/J and SM/J mouse stains. Three maternally imprinted QTLs are identified as regulating the growth trajectory of mouse body weight. Conclusion The functional iQTL mapping approach developed here provides a quantitative and testable framework for assessing the interplay between imprinted genes and a developmental process, and will have important implications for elucidating the genetic architecture of imprinted traits.

Genome-wide conserved non-coding microsatellite (CNMS) marker-based integrative genetical genomics for quantitative dissection of seed weight in chickpea.

Science.gov (United States)

Bajaj, Deepak; Saxena, Maneesha S; Kujur, Alice; Das, Shouvik; Badoni, Saurabh; Tripathi, Shailesh; Upadhyaya, Hari D; Gowda, C L L; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K; Parida, Swarup K

2015-03-01

Phylogenetic footprinting identified 666 genome-wide paralogous and orthologous CNMS (conserved non-coding microsatellite) markers from 5'-untranslated and regulatory regions (URRs) of 603 protein-coding chickpea genes. The (CT)n and (GA)n CNMS carrying CTRMCAMV35S and GAGA8BKN3 regulatory elements, respectively, are abundant in the chickpea genome. The mapped genic CNMS markers with robust amplification efficiencies (94.7%) detected higher intraspecific polymorphic potential (37.6%) among genotypes, implying their immense utility in chickpea breeding and genetic analyses. Seventeen differentially expressed CNMS marker-associated genes showing strong preferential and seed tissue/developmental stage-specific expression in contrasting genotypes were selected to narrow down the gene targets underlying seed weight quantitative trait loci (QTLs)/eQTLs (expression QTLs) through integrative genetical genomics. The integration of transcript profiling with seed weight QTL/eQTL mapping, molecular haplotyping, and association analyses identified potential molecular tags (GAGA8BKN3 and RAV1AAT regulatory elements and alleles/haplotypes) in the LOB-domain-containing protein- and KANADI protein-encoding transcription factor genes controlling the cis-regulated expression for seed weight in the chickpea. This emphasizes the potential of CNMS marker-based integrative genetical genomics for the quantitative genetic dissection of complex seed weight in chickpea. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Effects of normalization on quantitative traits in association test

Science.gov (United States)

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Effects of normalization on quantitative traits in association test

Directory of Open Access Journals (Sweden)

Yap Von Bing

2009-12-01

Full Text Available Abstract Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest.

Quantitative risk analysis of a space shuttle subsystem

International Nuclear Information System (INIS)

Frank, M.V.

1989-01-01

This paper reports that in an attempt to investigate methods for risk management other than qualitative analysis techniques, NASA has funded pilot study quantitative risk analyses for space shuttle subsystems. The authors performed one such study of two shuttle subsystems with McDonnell Douglas Astronautics Company. The subsystems were the auxiliary power units (APU) on the orbiter, and the hydraulic power units on the solid rocket booster. The technology and results of the APU study are presented in this paper. Drawing from a rich in-flight database as well as from a wealth of tests and analyses, the study quantitatively assessed the risk of APU-initiated scenarios on the shuttle during all phases of a flight mission. Damage states of interest were loss of crew/vehicle, aborted mission, and launch scrub. A quantitative risk analysis approach to deciding on important items for risk management was contrasted with the current NASA failure mode and effects analysis/critical item list approach

Uncertainty of quantitative microbiological methods of pharmaceutical analysis.

Science.gov (United States)

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.

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

Science.gov (United States)

2014-01-01

Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus).

Science.gov (United States)

Ren, Yi; McGregor, Cecilia; Zhang, Yan; Gong, Guoyi; Zhang, Haiying; Guo, Shaogui; Sun, Honghe; Cai, Wantao; Zhang, Jie; Xu, Yong

2014-01-20

Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. The integrated map described herein enhances the utility of genomic tools over previous watermelon genetic maps. A

PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

Science.gov (United States)

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

2008-05-15

A bio bar code 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 bar code assay requires lengthy experimental procedures including the preparation and release of bar code 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 bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code 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.

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

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Janani Iyer

2016-05-01

Full Text Available 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.

Principal Component Analysis of Some Quantitative and Qualitative Traits in Iranian Spinach Landraces

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Mohebodini Mehdi

2017-08-01

Full Text Available Landraces of spinach in Iran have not been sufficiently characterised for their morpho-agronomic traits. Such characterisation would be helpful in the development of new genetically improved cultivars. In this study 54 spinach accessions collected from the major spinach growing areas of Iran were evaluated to determine their phenotypic diversity profile of spinach genotypes on the basis of 10 quantitative and 9 qualitative morpho-agronomic traits. High coefficients of variation were recorded in some quantitative traits (dry yield and leaf area and all of the qualitative traits. Using principal component analysis, the first four principal components with eigen-values more than 1 contributed 87% of the variability among accessions for quantitative traits, whereas the first four principal components with eigen-values more than 0.8 contributed 79% of the variability among accessions for qualitative traits. The most important relations observed on the first two principal components were a strong positive association between leaf width and petiole length; between leaf length and leaf numbers in flowering; and among fresh yield, dry yield and petiole diameter; a near zero correlation between days to flowering with leaf width and petiole length. Prickly seeds, high percentage of female plants, smooth leaf texture, high numbers of leaves at flowering, greygreen leaves, erect petiole attitude and long petiole length are important characters for spinach breeding programmes.

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

Science.gov (United States)

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

Quantitative Analysis of cardiac SPECT

International Nuclear Information System (INIS)

Nekolla, S.G.; Bengel, F.M.

2004-01-01

The quantitative analysis of myocardial SPECT images is a powerful tool to extract the highly specific radio tracer uptake in these studies. If compared to normal data bases, the uptake values can be calibrated on an individual basis. Doing so increases the reproducibility of the analysis substantially. Based on the development over the last three decades starting from planar scinitigraphy, this paper discusses the methods used today incorporating the changes due to tomographic image acquisitions. Finally, the limitations of these approaches as well as consequences from most recent hardware developments, commercial analysis packages and a wider view of the description of the left ventricle are discussed. (orig.)

An integrated system for genetic analysis

Directory of Open Access Journals (Sweden)

Duan Xiao

2006-04-01

Full Text Available Abstract Background Large-scale genetic mapping projects require data management systems that can handle complex phenotypes and detect and correct high-throughput genotyping errors, yet are easy to use. Description We have developed an Integrated Genotyping System (IGS to meet this need. IGS securely stores, edits and analyses genotype and phenotype data. It stores information about DNA samples, plates, primers, markers and genotypes generated by a genotyping laboratory. Data are structured so that statistical genetic analysis of both case-control and pedigree data is straightforward. Conclusion IGS can model complex phenotypes and contain genotypes from whole genome association studies. The database makes it possible to integrate genetic analysis with data curation. The IGS web site http://bioinformatics.well.ox.ac.uk/project-igs.shtml contains further information.

Good practices for quantitative bias analysis.

Science.gov (United States)

Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander

2014-12-01

Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage

Quantitative phase analysis in industrial research

International Nuclear Information System (INIS)

Ahmad Monshi

1996-01-01

X-Ray Diffraction (XRD) is the only technique able to identify phase and all the other analytical techniques give information about the elements. Quantitative phase analysis of minerals and industrial products is logically the next step after a qualitative examination and is of great importance in industrial research. Since the application of XRD in industry, early in this century, workers were trying to develop quantitative XRD methods. In this paper some of the important methods are briefly discussed and partly compared. These methods are Internal Standard, Known Additions, Double Dilution, External Standard, Direct Comparison, Diffraction Absorption and Ratio of Slopes

Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

Science.gov (United States)

Dobata, Shigeto

2012-12-01

Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

Distribution of lod scores in oligogenic linkage analysis.

Science.gov (United States)

Williams, J T; North, K E; Martin, L J; Comuzzie, A G; Göring, H H; Blangero, J

2001-01-01

In variance component oligogenic linkage analysis it can happen that the residual additive genetic variance bounds to zero when estimating the effect of the ith quantitative trait locus. Using quantitative trait Q1 from the Genetic Analysis Workshop 12 simulated general population data, we compare the observed lod scores from oligogenic linkage analysis with the empirical lod score distribution under a null model of no linkage. We find that zero residual additive genetic variance in the null model alters the usual distribution of the likelihood-ratio statistic.

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

line-cross analysis; epistasis; dominance; adaptation; experimental evolution; reverse evolution; life-history evolution; quantitative genetics; Drosophila. ... set of five populations maintained for several hundred generations on a two-week discrete-generation life cycle and a set of five populations adapted to starvation stress.

Micro-computer system for quantitative image analysis of damage microstructure

International Nuclear Information System (INIS)

Kohyama, A.; Kohno, Y.; Satoh, K.; Igata, N.

1984-01-01

Quantitative image analysis of radiation induced damage microstructure is very important in evaluating material behaviors in radiation environment. But, quite a few improvement have been seen in quantitative analysis of damage microstructure in these decades. The objective of this work is to develop new system for quantitative image analysis of damage microstructure which could improve accuracy and efficiency of data sampling and processing and could enable to get new information about mutual relations among dislocations, precipitates, cavities, grain boundaries, etc. In this system, data sampling is done with X-Y digitizer. The cavity microstructure in dual-ion irradiated 316 SS is analyzed and the effectiveness of this system is discussed. (orig.)

Quantitative trait loci and metabolic pathways

Science.gov (United States)

McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

1998-01-01

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

Gene set analysis for interpreting genetic studies

DEFF Research Database (Denmark)

Pers, Tune H

2016-01-01

Interpretation of genome-wide association study (GWAS) results is lacking behind the discovery of new genetic associations. Consequently, there is an urgent need for data-driven methods for interpreting genetic association studies. Gene set analysis (GSA) can identify aetiologic pathways...

Quantitative Structure-Activity Relationship Analysis of the ...

African Journals Online (AJOL)

Erah

Quantitative Structure-Activity Relationship Analysis of the Anticonvulsant ... Two types of molecular descriptors, including the 2D autocorrelation ..... It is based on the simulation of natural .... clustering anticonvulsant, antidepressant, and.

Genetic approaches in comparative and evolutionary physiology

Science.gov (United States)

Bridgham, Jamie T.; Kelly, Scott A.; Garland, Theodore

2015-01-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. PMID:26041111

Cryptic Genetic Variation in Evolutionary Developmental Genetics

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Annalise B. Paaby

2016-06-01

Full Text Available Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes—processes that cannot be fully observed in continuously varying visible traits.

Quantitative Imaging in Cancer Evolution and Ecology

Science.gov (United States)

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

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

DEFF Research Database (Denmark)

Volkov, Petr; Olsson, Anders H; Gillberg, Linn

2016-01-01

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, w...... and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes.......Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men......, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5...

Data from quantitative label free proteomics analysis of rat spleen

Directory of Open Access Journals (Sweden)

Khadar Dudekula

2016-09-01

Full Text Available The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides. A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis. Keywords: Spleen, Rat, Protein extraction, Label-free quantitative proteomics

Quantitative data analysis in education a critical introduction using SPSS

CERN Document Server

Connolly, Paul

2007-01-01

This book provides a refreshing and user-friendly guide to quantitative data analysis in education for students and researchers. It assumes absolutely no prior knowledge of quantitative methods or statistics. Beginning with the very basics, it provides the reader with the knowledge and skills necessary to be able to undertake routine quantitative data analysis to a level expected of published research. Rather than focusing on teaching statistics through mathematical formulae, the book places an emphasis on using SPSS to gain a real feel for the data and an intuitive grasp of t

The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer

International Nuclear Information System (INIS)

Mitra, Anirban P; Almal, Arpit A; George, Ben; Fry, David W; Lenehan, Peter F; Pagliarulo, Vincenzo; Cote, Richard J; Datar, Ram H; Worzel, William P

2006-01-01

Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR

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

Science.gov (United States)

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

Quantitative analysis method for ship construction quality

Directory of Open Access Journals (Sweden)

FU Senzong

2017-03-01

Full Text Available The excellent performance of a ship is assured by the accurate evaluation of its construction quality. For a long time, research into the construction quality of ships has mainly focused on qualitative analysis due to a shortage of process data, which results from limited samples, varied process types and non-standardized processes. Aiming at predicting and controlling the influence of the construction process on the construction quality of ships, this article proposes a reliability quantitative analysis flow path for the ship construction process and fuzzy calculation method. Based on the process-quality factor model proposed by the Function-Oriented Quality Control (FOQC method, we combine fuzzy mathematics with the expert grading method to deduce formulations calculating the fuzzy process reliability of the ordinal connection model, series connection model and mixed connection model. The quantitative analysis method is applied in analyzing the process reliability of a ship's shaft gear box installation, which proves the applicability and effectiveness of the method. The analysis results can be a useful reference for setting key quality inspection points and optimizing key processes.

Quantitative X-ray analysis of pigments

International Nuclear Information System (INIS)

Araujo, M. Marrocos de

1987-01-01

The 'matrix-flushing' and the 'adiabatic principle' methods have been applied for the quantitative analysis through X-ray diffraction patterns of pigments and extenders mixtures, frequently used in paint industry. The results obtained have shown the usefulness of these methods, but still ask for improving their accuracy. (Author) [pt

[Phenotypic and genetic analysis of a patient presented with Tietz/Waardenburg type II a syndrome].

Science.gov (United States)

Wang, Huanhuan; Tang, Lifang; Zhang, Jingmin; Hu, Qin; Chen, Yingwei; Xiao, Bing

2015-08-01

To determine the genetic cause for a patient featuring decreased pigmentation of the skin and iris, hearing loss and multiple congenital anomalies. Routine chromosomal banding was performed to analyze the karyotype of the patient and his parents. Single nucleotide polymorphism array (SNP array) was employed to identify cryptic chromosome aberrations, and quantitative real-time PCR was used to confirm the results. Karyotype analysis has revealed no obvious anomaly for the patient and his parents. SNP array analysis of the patient has demonstrated a 3.9 Mb deletion encompassing 3p13p14.1, which caused loss of entire MITF gene. The deletion was confirmed by quantitative real-time PCR. Clinical features of the patient have included severe bilateral hearing loss, decreased pigmentation of the skin and iris and multiple congenital anomalies. The patient, carrying a 3p13p14.1 deletion, has features of Tietz syndrome/Waardenburg syndrome type IIa. This case may provide additional data for the study of genotype-phenotype correlation of this disease.

Development and Evaluation of Event-Specific Quantitative PCR Method for Genetically Modified Soybean MON87701.

Science.gov (United States)

Tsukahara, Keita; Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Nishimaki-Mogami, Tomoko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2016-01-01

A real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event, MON87701. First, a standard plasmid for MON87701 quantification was constructed. The conversion factor (C f ) required to calculate the amount of genetically modified organism (GMO) was experimentally determined for a real-time PCR instrument. The determined C f for the real-time PCR instrument was 1.24. For the evaluation of the developed method, a blind test was carried out in an inter-laboratory trial. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr), respectively. The determined biases and the RSDr values were less than 30 and 13%, respectively, at all evaluated concentrations. The limit of quantitation of the method was 0.5%, and the developed method would thus be applicable for practical analyses for the detection and quantification of MON87701.

Genetic Analysis for Some of Morphological Traits in Bread Wheat under Drought Stress Condition Using Generations Mean Analysis

Directory of Open Access Journals (Sweden)

Jamileh Abedi

2015-06-01

Full Text Available Perception of genes action controlling of quantitative traits is very important in genetic breeding methods the plant populations. to study and estimate the parameters of genetic and appointment the best genetically model for justification the genetic changing some of traits the bread wheat under drought stress condition, parents (P1 & P2 and F3, F4, F5 generations together the four control cultivars (Kharchia, Gaspard, Moghan and Mahuti were evaluated by generation mean analysis using a agoment design including six blocks. Generation mean analysis was performed for all traits with Mather and Jinks model using joint scaling test. Three parameter model [m d h] provided the best fit for all traits expect harvest index, main spike grain weight, number of grain per plant, Total spike weight of plant with significant at 5% and 1% levels . Though additive and dominance effect both had interfered in controlling often the traits but with attention to difference effects and variety component was determined that dominance is more impressive than additive effect for traits of number of tiller, main spike weight, grain yield and grain number of main spike. Therefore will benefit using of these traits in the collection and to improve these traits hybridization would be much efficient than the selection strategies. In this study additive Ч additive epistasis effect only observed for traits of Total spike weight of plant, number of grain per plant, main spike grain weight and harvest index and other traits hadn’t any epistasis effect that it was demonstration lack of existence the genes reciprocal effect in the inheritance studied traits. Therefore we can suggest that the selection strategies perform in terminal generations and additive Ч additive epistasis effect would be confirmed in selection under self-pollination condition.

Novel approach in quantitative analysis of shearography method

International Nuclear Information System (INIS)

Wan Saffiey Wan Abdullah

2002-01-01

The application of laser interferometry in industrial non-destructive testing and material characterization is becoming more prevalent since this method provides non-contact full-field inspection of the test object. However their application only limited to the qualitative analysis, current trend has changed to the development of this method by the introduction of quantitative analysis, which attempts to detail the defect examined. This being the design feature for a ranges of object size to be examined. The growing commercial demand for quantitative analysis for NDT and material characterization is determining the quality of optical and analysis instrument. However very little attention is currently being paid to understanding, quantifying and compensating for the numerous error sources which are a function of interferometers. This paper presents a comparison of measurement analysis using the established theoretical approach and the new approach, taken into account the factor of divergence illumination and other geometrical factors. The difference in the measurement system could be associated in the error factor. (Author)

Genetic susceptibility to bone and soft tissue sarcomas: a field synopsis and meta-analysis.

Science.gov (United States)

Benna, Clara; Simioni, Andrea; Pasquali, Sandro; De Boni, Davide; Rajendran, Senthilkumar; Spiro, Giovanna; Colombo, Chiara; Virgone, Calogero; DuBois, Steven G; Gronchi, Alessandro; Rossi, Carlo Riccardo; Mocellin, Simone

2018-04-06

The genetic architecture of bone and soft tissue sarcomas susceptibility is yet to be elucidated. We aimed to comprehensively collect and meta-analyze the current knowledge on genetic susceptibility in these rare tumors. We conducted a systematic review and meta-analysis of the evidence on the association between DNA variation and risk of developing sarcomas through searching PubMed, The Cochrane Library, Scopus and Web of Science databases. To evaluate result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate result noteworthiness. Integrative analysis of genetic and eQTL (expression quantitative trait locus) data was coupled with network and pathway analysis to explore the hypothesis that specific cell functions are involved in sarcoma predisposition. We retrieved 90 eligible studies comprising 47,796 subjects (cases: 14,358, 30%) and investigating 1,126 polymorphisms involving 320 distinct genes. Meta-analysis identified 55 single nucleotide polymorphisms (SNPs) significantly associated with disease risk with a high (N=9), moderate (N=38) and low (N=8) level of evidence, findings being classified as noteworthy basically only when the level of evidence was high. The estimated joint population attributable risk for three independent SNPs (rs11599754 of ZNF365/EGR2 , rs231775 of CTLA4 , and rs454006 of PRKCG ) was 37.2%. We also identified 53 SNPs significantly associated with sarcoma risk based on single studies.Pathway analysis enabled us to propose that sarcoma predisposition might be linked especially to germline variation of genes whose products are involved in the function of the DNA repair machinery. We built the first knowledgebase on the evidence linking DNA variation to sarcomas susceptibility, which can be used to generate mechanistic hypotheses and inform future studies in this field of oncology.

Multivariate analysis in a genetic divergence study of Psidium guajava.

Science.gov (United States)

Nogueira, A M; Ferreira, M F S; Guilhen, J H S; Ferreira, A

2014-12-18

The family Myrtaceae is widespread in the Atlantic Forest and is well-represented in the Espírito Santo State in Brazil. In the genus Psidium of this family, guava (Psidium guajava L.) is the most economically important species. Guava is widely cultivated in tropical and subtropical countries; however, the widespread cultivation of only a small number of guava tree cultivars may cause the genetic vulnerability of this crop, making the search for promising genotypes in natural populations important for breeding programs and conservation. In this study, the genetic diversity of 66 guava trees sampled in the southern region of Espírito Santo and in Caparaó, MG, Brazil were evaluated. A total of 28 morphological descriptors (11 quantitative and 17 multicategorical) and 18 microsatellite markers were used. Principal component, discriminant and cluster analyses, descriptive analyses, and genetic diversity analyses using simple sequence repeats were performed. Discrimination of accessions using molecular markers resulted in clustering of genotypes of the same origin, which was not observed using morphological data. Genetic diversity was detected between and within the localities evaluated, regardless of the methodology used. Genetic differentiation among the populations using morphological and molecular data indicated the importance of the study area for species conservation, genetic erosion estimation, and exploitation in breeding programs.

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

Science.gov (United States)

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.

Bayesian meta-analysis of genetic association studies with different sets of markers

NARCIS (Netherlands)

Verzilli, Claudio; Shah, Tina; Casas, Juan P.; Chapman, Juliet; Sandhu, Manjinder; Debenham, Sally L.; Boekholdt, Matthijs S.; Khaw, Kay Tee; Wareham, Nicholas J.; Judson, Richard; Benjamin, Emelia J.; Kathiresan, Sekar; Larson, Martin G.; Rong, Jian; Sofat, Reecha; Humphries, Steve E.; Smeeth, Liam; Cavalleri, Gianpiero; Whittaker, John C.; Hingorani, Aroon D.

2008-01-01

Robust assessment of genetic effects on quantitative traits or complex-disease risk requires synthesis of evidence from multiple studies. Frequently, studies have genotyped partially overlapping sets of SNPs within a gene or region of interest, hampering attempts to combine all the available data.

Assessment of a Competency-Based Undergraduate Course on Genetic and Genomics.

Science.gov (United States)

Kronk, Rebecca; Colbert, Alison; Lengetti, Evelyn

2017-08-24

In response to new demands in the nursing profession, an innovative undergraduate genetics course was designed based on the Essential Nursing Competencies and Curricula Guidelines for Genetics and Genomics. Reflective journaling and storytelling were used as major pedagogies, alongside more traditional approaches. Thematic content analysis of student reflections revealed transformational learning as the major theme emerging from genomic and genetic knowledge acquisition. Quantitative analyses of precourse/postcourse student self-assessments of competencies revealed significant findings.

Quantitative methods for the analysis of electron microscope images

DEFF Research Database (Denmark)

Skands, Peter Ulrik Vallø

1996-01-01

The topic of this thesis is an general introduction to quantitative methods for the analysis of digital microscope images. The images presented are primarily been acquired from Scanning Electron Microscopes (SEM) and interfermeter microscopes (IFM). The topic is approached though several examples...... foundation of the thesis fall in the areas of: 1) Mathematical Morphology; 2) Distance transforms and applications; and 3) Fractal geometry. Image analysis opens in general the possibility of a quantitative and statistical well founded measurement of digital microscope images. Herein lies also the conditions...

Genome-wide association mapping identifies the genetic basis of discrete and quantitative variation in sexual weaponry in a wild sheep population.

Science.gov (United States)

Johnston, Susan E; McEwan, John C; Pickering, Natalie K; Kijas, James W; Beraldi, Dario; Pilkington, Jill G; Pemberton, Josephine M; Slate, Jon

2011-06-01

Understanding the genetic architecture of phenotypic variation in natural populations is a fundamental goal of evolutionary genetics. Wild Soay sheep (Ovis aries) have an inherited polymorphism for horn morphology in both sexes, controlled by a single autosomal locus, Horns. The majority of males have large normal horns, but a small number have vestigial, deformed horns, known as scurs; females have either normal horns, scurs or no horns (polled). Given that scurred males and polled females have reduced fitness within each sex, it is counterintuitive that the polymorphism persists within the population. Therefore, identifying the genetic basis of horn type will provide a vital foundation for understanding why the different morphs are maintained in the face of natural selection. We conducted a genome-wide association study using ∼36000 single nucleotide polymorphisms (SNPs) and determined the main candidate for Horns as RXFP2, an autosomal gene with a known involvement in determining primary sex characters in humans and mice. Evidence from additional SNPs in and around RXFP2 supports a new model of horn-type inheritance in Soay sheep, and for the first time, sheep with the same horn phenotype but different underlying genotypes can be identified. In addition, RXFP2 was shown to be an additive quantitative trait locus (QTL) for horn size in normal-horned males, accounting for up to 76% of additive genetic variation in this trait. This finding contrasts markedly from genome-wide association studies of quantitative traits in humans and some model species, where it is often observed that mapped loci only explain a modest proportion of the overall genetic variation. © 2011 Blackwell Publishing Ltd.

Complex Genetics of Behavior: BXDs in the Automated Home-Cage.

Science.gov (United States)

Loos, Maarten; Verhage, Matthijs; Spijker, Sabine; Smit, August B

2017-01-01

This chapter describes a use case for the genetic dissection and automated analysis of complex behavioral traits using the genetically diverse panel of BXD mouse recombinant inbred strains. Strains of the BXD resource differ widely in terms of gene and protein expression in the brain, as well as in their behavioral repertoire. A large mouse resource opens the possibility for gene finding studies underlying distinct behavioral phenotypes, however, such a resource poses a challenge in behavioral phenotyping. To address the specifics of large-scale screening we describe how to investigate: (1) how to assess mouse behavior systematically in addressing a large genetic cohort, (2) how to dissect automation-derived longitudinal mouse behavior into quantitative parameters, and (3) how to map these quantitative traits to the genome, deriving loci underlying aspects of behavior.

Analysis of the quantitative dermatoglyphics of the digito-palmar complex in patients with multiple sclerosis.

Science.gov (United States)

Supe, S; Milicić, J; Pavićević, R

1997-06-01

Recent studies on the etiopathogenesis of multiple sclerosis (MS) all point out that there is a polygenetical predisposition for this illness. The so called "MS Trait" determines the reactivity of the immunological system upon ecological factors. The development of the glyphological science and the study of the characteristics of the digito-palmar dermatoglyphic complex (for which it was established that they are polygenetically determined characteristics) all enable a better insight into the genetic development during early embriogenesis. The aim of this study was to estimate certain differences in the dermatoglyphics of digito-palmar complexes between the group with multiple sclerosis and the comparable, phenotypically healthy groups of both sexes. This study is based on the analysis of 18 quantitative characteristics of the digito-palmar complex in 125 patients with multiple sclerosis (41 males and 84 females) in comparison to a group of 400 phenotypically healthy patients (200 males and 200 females). The conducted analysis pointed towards a statistically significant decrease of the number of digital and palmar ridges, as well as with lower values of atd angles in a group of MS patients of both sexes. The main discriminators were the characteristic palmar dermatoglyphics with the possibility that the discriminate analysis classifies over 80% of the examinees which exceeds the statistical significance. The results of this study suggest a possible discrimination of patients with MS and the phenotypically health population through the analysis of the dermatoglyphic status, and therefore the possibility that multiple sclerosis is genetically predisposed disease.

Investigation on Genetic Variation of Iran Watermelon Accession

Directory of Open Access Journals (Sweden)

majid reza kiyani

2009-06-01

Full Text Available In order to determine of genetic variation in germplasm of 120 watermelon accessions, a field trial conducted at agricultural and natural resource research center of khorasan . These Accessions with four commercial cultivars as control were planted in agnomental design with six replications. 15 quantitative morphological traits were measured and some statistical parameter and analysis include of Mean, Coefficient variance, cluster analysis, correlation regression coefficients were determine for this traits. yield, Sugar percent , time between flowering and ripping, fruit length, fruit width, fruit mass to fruit weight ratio , fruit skin to fruit weight ratio , seed weight to fruit weight ratio , 100 seed weight , seed length , seed diameter , seed width were the most useful traits for identifying of genotypes from each other. A one side analysis of variance was performed for different regions genetic diversity detection, which indicated a significant difference between regions for all traits except fruit Ph and fruit skin thickness. Cluster analysis divided genotypes into eight groups based on quantitative data. Correlation analysis between traits showed a significant relation between yield and all traits except fruit ph, time to flowering and seed fruit length.

Genetic mapping in mice reveals the involvement of Pcdh9 in long-term social and object recognition and sensorimotor development

NARCIS (Netherlands)

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S.; Van'T Spijker, Heleen M.; Akkermans, Guus; Stiedl, Oliver; Van Engeland, Herman; Koopmans, Bastijn; Van Lith, Hein A.; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J.; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J. Peter H; Yamamoto, Nobuhiko; Kas, Martien J.

2015-01-01

Background Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the

Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development

NARCIS (Netherlands)

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

2015-01-01

BACKGROUND: Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the

Analysis of genetic structure and relationship among nine ...

Indian Academy of Sciences (India)

These results indicated that the clustering analysis using the Structure program might provide an ..... of the current genetic relations among the breeds, and con- tribute to ... sis of the genetic structure of the Canary goat populations using.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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…

Linkage Map Construction and Quantitative Trait Locus Analysis of Agronomic and Fiber Quality Traits in Cotton

Directory of Open Access Journals (Sweden)

Michael A. Gore

2014-03-01

Full Text Available The superior fiber properties of L. serve as a source of novel variation for improving fiber quality in Upland cotton ( L., but introgression from has been largely unsuccessful due to hybrid breakdown and a lack of genetic and genomic resources. In an effort to overcome these limitations, we constructed a linkage map and conducted a quantitative trait locus (QTL analysis of 10 agronomic and fiber quality traits in a recombinant inbred mapping population derived from a cross between TM-1, an Upland cotton line, and NM24016, an elite line with stabilized introgression from . The linkage map consisted of 429 simple-sequence repeat (SSR and 412 genotyping-by-sequencing (GBS-based single-nucleotide polymorphism (SNP marker loci that covered half of the tetraploid cotton genome. Notably, the 841 marker loci were unevenly distributed among the 26 chromosomes of tetraploid cotton. The 10 traits evaluated on the TM-1 × NM24016 population in a multienvironment trial were highly heritable, and most of the fiber traits showed considerable transgressive variation. Through the QTL analysis, we identified a total of 28 QTLs associated with the 10 traits. Our study provides a novel resource that can be used by breeders and geneticists for the genetic improvement of agronomic and fiber quality traits in Upland cotton.

Timing Analysis of Genetic Logic Circuits using D-VASim

DEFF Research Database (Denmark)

Baig, Hasan; Madsen, Jan

and propagation delay analysis of single as well as cascaded geneticlogic circuits can be performed. D-VASim allows user to change the circuit parameters during runtime simulation to observe its effectson circuit’s timing behavior. The results obtained from D-VASim can be used not only to characterize the timing...... delay analysis may play a very significant role in the designing of genetic logic circuits. In thisdemonstration, we present the capability of D-VASim (Dynamic Virtual Analyzer and Simulator) to perform the timing and propagationdelay analysis of genetic logic circuits. Using D-VASim, the timing...... behavior of geneticlogic circuits but also to analyze the timing constraints of cascaded genetic logic circuits....

Quantitative scenario analysis of low and intermediate level radioactive repository

International Nuclear Information System (INIS)

Lee, Keon Jae; Lee, Sang Yoon; Park, Keon Baek; Song, Min Cheon; Lee, Ho Jin

1998-03-01

Derivation of hypothetical radioactive waste disposal facility os conducted through sub-component characteristic analysis and conceptual modeling. It is studied that quantitative analysis of constructed scenario in terms of annual effective dose equivalent. This study is sequentially conducted according to performance assessment of radioactive waste disposal facility such as : ground water flow analysis, source term analysis, ground water transport, surface water transport, dose and pathways. The routine program module such as VAM2D-PAGAN-GENII is used for quantitative scenario analysis. Detailed data used in this module are come from experimental data of Korean territory and default data given within this module. Is case of blank data for code execution, it is estimated through reasonable engineering sense

Genetic analysis of Mexican Criollo cattle populations.

Science.gov (United States)

Ulloa-Arvizu, R; Gayosso-Vázquez, A; Ramos-Kuri, M; Estrada, F J; Montaño, M; Alonso, R A

2008-10-01

The objective of this study was to evaluate the genetic structure of Mexican Criollo cattle populations using microsatellite genetic markers. DNA samples were collected from 168 animals from four Mexican Criollo cattle populations, geographically isolated in remote areas of Sierra Madre Occidental (West Highlands). Also were included samples from two breeds with Iberian origin: the fighting bull (n = 24) and the milking central American Criollo (n = 24) and one Asiatic breed: Guzerat (n = 32). Genetic analysis consisted of the estimation of the genetic diversity in each population by the allele number and the average expected heterozygosity found in nine microsatellite loci. Furthermore, genetic relationships among the populations were defined by their genetic distances. Our data shows that Mexican cattle populations have a relatively high level of genetic diversity based either on the mean number of alleles (10.2-13.6) and on the expected heterozygosity (0.71-0.85). The degree of observed homozygosity within the Criollo populations was remarkable and probably caused by inbreeding (reduced effective population size) possibly due to reproductive structure within populations. Our data shows that considerable genetic differentiation has been occurred among the Criollo cattle populations in different regions of Mexico.

Microchromatography of hemoglobins. VIII. A general qualitative and quantitative method in plastic drinking straws and the quantitative analysis of Hb-F.

Science.gov (United States)

Schroeder, W A; Pace, L A

1978-03-01

The microchromatographic procedure for the quantitative analysis of the hemoglobin components in a hemolysate uses columns of DEAE-cellulose in a plastic drinking straw with a glycine-KCN-NaCl developer. Not only may the method be used for the quantitative analysis of Hb-F but also for the analysis of the varied components in mixtures of hemoglobins.

Development and validation of an event-specific quantitative PCR method for genetically modified maize MIR162.

Science.gov (United States)

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

2014-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize event, MIR162. We first prepared a standard plasmid for MIR162 quantification. The conversion factor (Cf) required to calculate the genetically modified organism (GMO) amount was empirically determined for two real-time PCR instruments, the Applied Biosystems 7900HT (ABI7900) and the Applied Biosystems 7500 (ABI7500) for which the determined Cf values were 0.697 and 0.635, respectively. To validate the developed method, a blind test was carried out in an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr). The determined biases were less than 25% and the RSDr values were less than 20% at all evaluated concentrations. These results suggested that the limit of quantitation of the method was 0.5%, and that the developed method would thus be suitable for practical analyses for the detection and quantification of MIR162.

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

Science.gov (United States)

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

Genetic disparity and relationship among quantitatively inherited yield related traits in diallel crosses of upland cotton

International Nuclear Information System (INIS)

Bibi, M.; Khan, N.U.; Mohammad, F.; Gul, R.; Idrees, M.; Sayal, O.U.; Khakwani, A.A.; Khan, I.A.

2011-01-01

In quantitative genetics, development of high yielding genotypes from parental cultivars of same ancestry is some what confusing as compared to genetically diverse parents. However, sufficient recombinations through allelic variations in mating of closely-related populations result in superior agronomic performance. Development of improved cotton genotypes is one of the prime objectives of any cotton breeding programmes. Genetic divergence and yield potential of parental cotton genotypes versus their diallel hybrids, relationship of yield with various morpho-yield traits and their heritability were studied in 8 X 8 F/sub 1/ diallel hybrids and their parental cultivars in Gossypium hirsutum L. during 2008-09 at Khyber Pakhtunkhwa Agricultural University, Peshawar, Pakistan. Highly significant (p less than or equal to 0.01) differences were observed among parental genotypes and F/sub 1/ populations for all the traits. Results revealed that F/sub 1/ hybrids i.e., CIM-506 X CIM-554, CIM-473 X CIM-554, CIM-446 X CIM-496 and CIM-446 X CIM-554 produced significantly higher number of sympodia, bolls per populations showed incredible performance for plant height, locules per boll and seeds plant and seed cotton yield. Some F/sub 1/ per locule. Seed cotton yield manifested positive association with morpho-yield traits which also accounted for greater genetic variations to yield being dependent trait. Heritabilities (broad sense) were moderate to high in magnitude for all populations with larger genetic potential, positive relationship between yield and yield traits. Results revealed that F1 contributing traits and moderate to high heritability can guide intensive selection and improvement per se in segregating populations. (author)

Quantitative Trait Locus Analysis of Mating Behavior and Male Sex Pheromones in Nasonia Wasps

Directory of Open Access Journals (Sweden)

Wenwen Diao

2016-06-01

Full Text Available A major focus in speciation genetics is to identify the chromosomal regions and genes that reduce hybridization and gene flow. We investigated the genetic architecture of mating behavior in the parasitoid wasp species pair Nasonia giraulti and Nasonia oneida that exhibit strong prezygotic isolation. Behavioral analysis showed that N. oneida females had consistently higher latency times, and broke off the mating sequence more often in the mounting stage when confronted with N. giraulti males compared with males of their own species. N. oneida males produce a lower quantity of the long-range male sex pheromone (4R,5S-5-hydroxy-4-decanolide (RS-HDL. Crosses between the two species yielded hybrid males with various pheromone quantities, and these males were used in mating trials with females of either species to measure female mate discrimination rates. A quantitative trait locus (QTL analysis involving 475 recombinant hybrid males (F2, 2148 reciprocally backcrossed females (F3, and a linkage map of 52 equally spaced neutral single nucleotide polymorphism (SNP markers plus SNPs in 40 candidate mating behavior genes revealed four QTL for male pheromone amount, depending on partner species. Our results demonstrate that the RS-HDL pheromone plays a role in the mating system of N. giraulti and N. oneida, but also that additional communication cues are involved in mate choice. No QTL were found for female mate discrimination, which points at a polygenic architecture of female choice with strong environmental influences.

Quantiprot - a Python package for quantitative analysis of protein sequences.

Science.gov (United States)

Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

2017-07-17

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

Collaborative ring trial of the papaya endogenous reference gene and its polymerase chain reaction assays for genetically modified organism analysis.

Science.gov (United States)

Wei, Jiaojun; Li, Feiwu; Guo, Jinchao; Li, Xiang; Xu, Junfeng; Wu, Gang; Zhang, Dabing; Yang, Litao

2013-11-27

The papaya (Carica papaya L.) Chymopapain (CHY) gene has been reported as a suitable endogenous reference gene for genetically modified (GM) papaya detection in previous studies. Herein, we further validated the use of the CHY gene and its qualitative and quantitative polymerase chain reaction (PCR) assays through an interlaboratory collaborative ring trial. A total of 12 laboratories working on detection of genetically modified organisms participated in the ring trial and returned test results. Statistical analysis of the returned results confirmed the species specificity, low heterogeneity, and single-copy number of the CHY gene among different papaya varieties. The limit of detection of the CHY qualitative PCR assay was 0.1%, while the limit of quantification of the quantitative PCR assay was ∼25 copies of haploid papaya genome with acceptable PCR efficiency and linearity. The differences between the tested and true values of papaya content in 10 blind samples ranged from 0.84 to 6.58%. These results indicated that the CHY gene was suitable as an endogenous reference gene for the identification and quantification of GM papaya.

The usefulness of 3D quantitative analysis with using MRI for measuring osteonecrosis of the femoral head

International Nuclear Information System (INIS)

Hwang, Ji Young; Lee, Sun Wha; Park, Youn Soo

2006-01-01

We wanted to evaluate the usefulness of MRI 3D quantitative analysis for measuring osteonecrosis of the femoral head in comparison with MRI 2D quantitative analysis and quantitative analysis of the specimen. For 3 months at our hospital, 14 femoral head specimens with osteonecrosis were obtained after total hip arthroplasty. The patients preoperative MRIs were retrospectively reviewed for quantitative analysis of the size of the necrosis. Each necrotic fraction of the femoral head was measured by 2D quantitative analysis with using mid-coronal and mid-sagittal MRIs, and by 3D quantitative analysis with using serial continuous coronal MRIs and 3D reconstruction software. The necrotic fraction of the specimen was physically measured by the fluid displacement method. The necrotic fraction according to MRI 2D or 3D quantitative analysis was compared with that of the specimen by using Spearman's correlation test. On the correlative analysis, the necrotic fraction by MRI 2D quantitative analysis and quantitative analysis of the specimen showed moderate correlation (r = 0.657); on the other hand, the necrotic fraction by MRI 3D quantitative analysis and quantitative analysis of the specimen demonstrated a strong correlation (r = 0.952) (ρ < 0.05). MRI 3D quantitative analysis was more accurate than 2D quantitative analysis using MRI for measuring osteonecrosis of the femoral head. Therefore, it may be useful for predicting the clinical outcome and deciding the proper treatment option

Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset

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Jihye Kim

2013-09-01

Full Text Available Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underlying these traits. Based on the previously published single nucleotide polymorphism (SNP genotype data on 8,842 individuals enrolled in the Korea Association Resource project, we performed a series of systematic genome-wide association analyses for 49 quantitative traits of basic epidemiological, anthropometric, or blood chemistry parameters. Each analysis result was subjected to subsequent gene set analyses based on Gene Ontology (GO terms using gene set analysis software, GSA-SNP, identifying a set of GO terms significantly associated to each trait (pcorr < 0.05. Pairwise comparison of the traits in terms of the semantic similarity in their GO sets revealed surprising cases where phenotypically uncorrelated traits showed high similarity in terms of biological pathways. For example, the pH level was related to 7 other traits that showed low phenotypic correlations with it. A literature survey implies that these traits may be regulated partly by common pathways that involve neuronal or nerve systems.

What Really Happens in Quantitative Group Research? Results of a Content Analysis of Recent Quantitative Research in "JSGW"

Science.gov (United States)

Boyle, Lauren H.; Whittaker, Tiffany A.; Eyal, Maytal; McCarthy, Christopher J.

2017-01-01

The authors conducted a content analysis on quantitative studies published in "The Journal for Specialists in Group Work" ("JSGW") between 2012 and 2015. This brief report provides a general overview of the current practices of quantitative group research in counseling. The following study characteristics are reported and…

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

Science.gov (United States)

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.

Quantitative proteomic analysis of post-translational modifications of human histones

DEFF Research Database (Denmark)

Beck, Hans Christian; Nielsen, Eva C; Matthiesen, Rune

2006-01-01

, and H4 in a site-specific and dose-dependent manner. This unbiased analysis revealed that a relative increase in acetylated peptide from the histone variants H2A, H2B, and H4 was accompanied by a relative decrease of dimethylated Lys(57) from histone H2B. The dose-response results obtained...... by quantitative proteomics of histones from HDACi-treated cells were consistent with Western blot analysis of histone acetylation, cytotoxicity, and dose-dependent expression profiles of p21 and cyclin A2. This demonstrates that mass spectrometry-based quantitative proteomic analysis of post-translational...

Genetic basis of qualitative and quantitative resistance to powdery mildew in wheat: from consensus regions to candidate genes.

Science.gov (United States)

Marone, Daniela; Russo, Maria A; Laidò, Giovanni; De Vita, Pasquale; Papa, Roberto; Blanco, Antonio; Gadaleta, Agata; Rubiales, Diego; Mastrangelo, Anna M

2013-08-19

Powdery mildew (Blumeria graminis f. sp. tritici) is one of the most damaging diseases of wheat. The objective of this study was to identify the wheat genomic regions that are involved in the control of powdery mildew resistance through a quantitative trait loci (QTL) meta-analysis approach. This meta-analysis allows the use of collected QTL data from different published studies to obtain consensus QTL across different genetic backgrounds, thus providing a better definition of the regions responsible for the trait, and the possibility to obtain molecular markers that will be suitable for marker-assisted selection. Five QTL for resistance to powdery mildew were identified under field conditions in the durum-wheat segregating population Creso × Pedroso. An integrated map was developed for the projection of resistance genes/ alleles and the QTL from the present study and the literature, and to investigate their distribution in the wheat genome. Molecular markers that correspond to candidate genes for plant responses to pathogens were also projected onto the map, particularly considering NBS-LRR and receptor-like protein kinases. More than 80 independent QTL and 51 resistance genes from 62 different mapping populations were projected onto the consensus map using the Biomercator statistical software. Twenty-four MQTL that comprised 2-6 initial QTL that had widely varying confidence intervals were found on 15 chromosomes. The co-location of the resistance QTL and genes was investigated. Moreover, from analysis of the sequences of DArT markers, 28 DArT clones mapped on wheat chromosomes have been shown to be associated with the NBS-LRR genes and positioned in the same regions as the MQTL for powdery mildew resistance. The results from the present study provide a detailed analysis of the genetic basis of resistance to powdery mildew in wheat. The study of the Creso × Pedroso durum-wheat population has revealed some QTL that had not been previously identified. Furthermore

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

Science.gov (United States)

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.

Data from quantitative label free proteomics analysis of rat spleen.

Science.gov (United States)

Dudekula, Khadar; Le Bihan, Thierry

2016-09-01

The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides). A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis.

Quantitative analysis of some brands of chloroquine tablets ...

African Journals Online (AJOL)

Quantitative analysis of some brands of chloroquine tablets marketed in Maiduguri using spectrophotometric ... and compared with that of the standard, wavelength of maximum absorbance at 331nm for chloroquine. ... HOW TO USE AJOL.

Construction of a genetic map using EST-SSR markers and QTL analysis of major agronomic characters in hexaploid sweet potato (Ipomoea batatas (L.) Lam).

Science.gov (United States)

Kim, Jin-Hee; Chung, Il Kyung; Kim, Kyung-Min

2017-01-01

The Sweet potato, Ipomoea batatas (L.) Lam, is difficult to study in genetics and genomics because it is a hexaploid. The sweet potato study not have been performed domestically or internationally. In this study was performed to construct genetic map and quantitative trait loci (QTL) analysis. A total of 245 EST-SSR markers were developed, and the map was constructed by using 210 of those markers. The total map length was 1508.1 cM, and the mean distance between markers was 7.2 cM. Fifteen characteristics were investigated for QTLs analysis. According to those, the Four QTLs were identified, and The LOD score was 3.0. Further studies need to develop molecular markers in terms of EST-SSR markers for doing to be capable of efficient breeding. The genetic map created here using EST-SSR markers will facilitate planned breeding of sweet potato cultivars with various desirable traits.

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

Science.gov (United States)

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.

Accurate quantitative XRD phase analysis of cement clinkers

International Nuclear Information System (INIS)

Kern, A.

2002-01-01

Full text: Knowledge about the absolute phase abundance in cement clinkers is a requirement for both, research and quality control. Traditionally, quantitative analysis of cement clinkers has been carried out by theoretical normative calculation from chemical analysis using the so-called Bogue method or by optical microscopy. Therefore chemical analysis, mostly performed by X-ray fluorescence (XRF), forms the basis of cement plan control by providing information for proportioning raw materials, adjusting kiln and burning conditions, as well as cement mill feed proportioning. In addition, XRF is of highest importance with respect to the environmentally relevant control of waste recovery raw materials and alternative fuels, as well as filters, plants and sewage. However, the performance of clinkers and cements is governed by the mineralogy and not the elemental composition, and the deficiencies and inherent errors of Bogue as well as microscopic point counting are well known. With XRD and Rietveld analysis a full quantitative analysis of cement clinkers can be performed providing detailed mineralogical information about the product. Until recently several disadvantages prevented the frequent application of the Rietveld method in the cement industry. As the measurement of a full pattern is required, extended measurement times made an integration of this method into existing automation environments difficult. In addition, several drawbacks of existing Rietveld software such as complexity, low performance and severe numerical instability were prohibitive for automated use. The latest developments of on-line instrumentation, as well as dedicated Rietveld software for quantitative phase analysis (TOPAS), now make a decisive breakthrough possible. TOPAS not only allows the analysis of extremely complex phase mixtures in the shortest time possible, but also a fully automated online phase analysis for production control and quality management, free of any human interaction

Genomic value prediction for quantitative traits under the epistatic model

Directory of Open Access Journals (Sweden)

Xu Shizhong

2011-01-01

Full Text Available Abstract Background Most quantitative traits are controlled by multiple quantitative trait loci (QTL. The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects and marker pairs (epistatic effects to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement. Results In this study, we created 126 recombinant inbred lines of soybean and genotyped 80 makers across the genome. We applied the genome selection technique to predict the genomic value of somatic embryo number (a quantitative trait for each line. Cross validation analysis showed that the squared correlation coefficient between the observed and predicted embryo numbers was 0.33 when only main (additive effects were used for prediction. When the interaction (epistatic effects were also included in the model, the squared correlation coefficient reached 0.78. Conclusions This study provided an excellent example for the application of genome selection to plant breeding.

Global scaling for semi-quantitative analysis in FP-CIT SPECT.

Science.gov (United States)

Kupitz, D; Apostolova, I; Lange, C; Ulrich, G; Amthauer, H; Brenner, W; Buchert, R

2014-01-01

Semi-quantitative characterization of dopamine transporter availability from single photon emission computed tomography (SPECT) with 123I-ioflupane (FP-CIT) is based on uptake ratios relative to a reference region. The aim of this study was to evaluate the whole brain as reference region for semi-quantitative analysis of FP-CIT SPECT. The rationale was that this might reduce statistical noise associated with the estimation of non-displaceable FP-CIT uptake. 150 FP-CIT SPECTs were categorized as neurodegenerative or non-neurodegenerative by an expert. Semi-quantitative analysis of specific binding ratios (SBR) was performed with a custom-made tool based on the Statistical Parametric Mapping software package using predefined regions of interest (ROIs) in the anatomical space of the Montreal Neurological Institute. The following reference regions were compared: predefined ROIs for frontal and occipital lobe and whole brain (without striata, thalamus and brainstem). Tracer uptake in the reference region was characterized by the mean, median or 75th percentile of its voxel intensities. The area (AUC) under the receiver operating characteristic curve was used as performance measure. The highest AUC of 0.973 was achieved by the SBR of the putamen with the 75th percentile in the whole brain as reference. The lowest AUC for the putamen SBR of 0.937 was obtained with the mean in the frontal lobe as reference. We recommend the 75th percentile in the whole brain as reference for semi-quantitative analysis in FP-CIT SPECT. This combination provided the best agreement of the semi-quantitative analysis with visual evaluation of the SPECT images by an expert and, therefore, is appropriate to support less experienced physicians.

Molecular Diversity Analysis and Genetic Mapping of Pod Shatter Resistance Loci in Brassica carinata L.

Directory of Open Access Journals (Sweden)

Rosy Raman

2017-11-01

Full Text Available Seed lost due to easy pod dehiscence at maturity (pod shatter is a major problem in several members of Brassicaceae family. We investigated the level of pod shatter resistance in Ethiopian mustard (Brassica carinata and identified quantitative trait loci (QTL for targeted introgression of this trait in Ethiopian mustard and its close relatives of the genus Brassica. A set of 83 accessions of B. carinata, collected from the Australian Grains Genebank, was evaluated for pod shatter resistance based on pod rupture energy (RE. In comparison to B. napus (RE = 2.16 mJ, B. carinata accessions had higher RE values (2.53 to 20.82 mJ. A genetic linkage map of an F2 population from two contrasting B. carinata selections, BC73526 (shatter resistant with high RE and BC73524 (shatter prone with low RE comprising 300 individuals, was constructed using a set of 6,464 high quality DArTseq markers and subsequently used for QTL analysis. Genetic analysis of the F2 and F2:3 derived lines revealed five statistically significant QTL (LOD ≥ 3 that are linked with pod shatter resistance on chromosomes B1, B3, B8, and C5. Herein, we report for the first time, identification of genetic loci associated with pod shatter resistance in B. carinata. These characterized accessions would be useful in Brassica breeding programs for introgression of pod shatter resistance alleles in to elite breeding lines. Molecular markers would assist marker-assisted selection for tracing the introgression of resistant alleles. Our results suggest that the value of the germplasm collections can be harnessed through genetic and genomics tools.

Quantitative possibility analysis. Present status in ESCA

International Nuclear Information System (INIS)

Brion, D.

1981-01-01

A short review of the recent developments in quantification of X-ray photoelectron spectroscopy or ESCA is presented. The basic equations are reminded. Each involved parameter (photoionisation, inelastic mean free paths, 'response function' of the instruments, intensity measurement) is separately discussed in relation with the accuracy and the precision of the method. Other topics are considered such as roughness, surface contamination, matrix effect and inhomogeneous composition. Some aspects of the quantitative ESCA analysis and AES analysis are compared [fr

Analysis of genetic relationships of mulberry (Morus L.) germplasm ...

African Journals Online (AJOL)

STORAGESEVER

2009-06-03

Jun 3, 2009 ... Full Length Research Paper. Analysis of genetic ... Key words: Mulberry, molecular marker, genetic diversity, SRAP. ... Europe, North and South America, and Africa, and it is cultivated ... Xingjiang autonomous region, China.

A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations

Science.gov (United States)

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A.

2012-01-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure. PMID:22927824

A quantitative comparison of the similarity between genes and geography in worldwide human populations.

Science.gov (United States)

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A

2012-08-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure.

Uncertainties in elemental quantitative analysis by PIXE

International Nuclear Information System (INIS)

Montenegro, E.C.; Baptista, G.B.; Paschoa, A.S.; Barros Leite, C.V.

1979-01-01

The effects of the degree of non-uniformity of the particle beam, matrix composition and matrix thickness in a quantitative elemental analysis by particle induced X-ray emission (PIXE) are discussed and a criterion to evaluate the resulting degree of uncertainty in the mass determination by this method is established. (Auth.)

Genetic dissection of milk yield traits and mastitis resistance quantitative trait loci on chromosome 20 in dairy cattle.

Science.gov (United States)

Kadri, Naveen K; Guldbrandtsen, Bernt; Lund, Mogens S; Sahana, Goutam

2015-12-01

Intense selection to increase milk yield has had negative consequences for mastitis incidence in dairy cattle. Due to low heritability of mastitis resistance and an unfavorable genetic correlation with milk yield, a reduction in mastitis through traditional breeding has been difficult to achieve. Here, we examined quantitative trait loci (QTL) that segregate for clinical mastitis and milk yield on Bos taurus autosome 20 (BTA20) to determine whether both traits are affected by a single polymorphism (pleiotropy) or by multiple closely linked polymorphisms. In the latter but not the former situation, undesirable genetic correlation could potentially be broken by selecting animals that have favorable variants for both traits. First, we performed a within-breed association study using a haplotype-based method in Danish Holstein cattle (HOL). Next, we analyzed Nordic Red dairy cattle (RDC) and Danish Jersey cattle (JER) with the goal of determining whether these QTL identified in Holsteins were segregating across breeds. Genotypes for 12,566 animals (5,966 HOL, 5,458 RDC, and 1,142 JER) were determined by using the Illumina Bovine SNP50 BeadChip (50K; Illumina, San Diego, CA), which identifies 1,568 single nucleotide polymorphisms on BTA20. Data were combined, phased, and clustered into haplotype states, followed by within- and across-breed haplotype-based association analyses using a linear mixed model. Association signals for both clinical mastitis and milk yield peaked in the 26- to 40-Mb region on BTA20 in HOL. Single-variant association analyses were carried out in the QTL region using whole sequence level variants imputed from references of 2,036 HD genotypes (BovineHD BeadChip; Illumina) and 242 whole-genome sequences. The milk QTL were also segregating in RDC and JER on the BTA20-targeted region; however, an indication of differences in the causal factor(s) was observed across breeds. A previously reported F279Y mutation (rs385640152) within the growth hormone

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

OpenAIRE

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 dete...

Evaluation of breast lesions by contrast enhanced ultrasound: Qualitative and quantitative analysis

International Nuclear Information System (INIS)

Wan Caifeng; Du Jing; Fang Hua; Li Fenghua; Wang Lin

2012-01-01

Objective: To evaluate and compare the diagnostic performance of qualitative, quantitative and combined analysis for characterization of breast lesions in contrast enhanced ultrasound (CEUS), with histological results used as the reference standard. Methods: Ninety-one patients with 91 breast lesions BI-RADS 3–5 at US or mammography underwent CEUS. All lesions underwent qualitative and quantitative enhancement evaluation. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of different analytical method for discrimination between benign and malignant breast lesions. Results: Histopathologic analysis of the 91 lesions revealed 44 benign and 47 malignant. For qualitative analysis, benign and malignant lesions differ significantly in enhancement patterns (p z1 ), 0.768 (A z2 ) and 0.926(A z3 ) respectively. The values of A z1 and A z3 were significantly higher than that for A z2 (p = 0.024 and p = 0.008, respectively). But there was no significant difference between the values of A z1 and A z3 (p = 0.625). Conclusions: The diagnostic performance of qualitative and combined analysis was significantly higher than that for quantitative analysis. Although quantitative analysis has the potential to differentiate benign from malignant lesions, it has not yet improved the final diagnostic accuracy.

New Approach to Quantitative Analysis by Laser-induced Breakdown Spectroscopy

International Nuclear Information System (INIS)

Lee, D. H.; Kim, T. H.; Yun, J. I.; Jung, E. C.

2009-01-01

Laser-induced breakdown spectroscopy (LIBS) has been studied as the technique of choice in some particular situations like screening, in situ measurement, process monitoring, hostile environments, etc. Especially, LIBS can fulfill the qualitative and quantitative analysis for radioactive high level waste (HLW) glass in restricted experimental conditions. Several ways have been suggested to get quantitative information from LIBS. The one approach is to use the absolute intensities of each element. The other approach is to use the elemental emission intensities relative to the intensity of the internal standard element whose concentration is known already in the specimen. But these methods are not applicable to unknown samples. In the present work, we introduce new approach to LIBS quantitative analysis by using H α (656.28 nm) emission line as external standard

Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis.

Science.gov (United States)

Xie, Jianbo; Tian, Jiaxing; Du, Qingzhang; Chen, Jinhui; Li, Ying; Yang, Xiaohui; Li, Bailian; Zhang, Deqiang

2016-05-01

Gibberellins (GAs) regulate a wide range of important processes in plant growth and development, including photosynthesis. However, the mechanism by which GAs regulate photosynthesis remains to be understood. Here, we used multi-gene association to investigate the effect of genes in the GA-responsive pathway, as constructed by RNA sequencing, on photosynthesis, growth, and wood property traits, in a population of 435 Populus tomentosa By analyzing changes in the transcriptome following GA treatment, we identified many key photosynthetic genes, in agreement with the observed increase in measurements of photosynthesis. Regulatory motif enrichment analysis revealed that 37 differentially expressed genes related to photosynthesis shared two essential GA-related cis-regulatory elements, the GA response element and the pyrimidine box. Thus, we constructed a GA-responsive pathway consisting of 47 genes involved in regulating photosynthesis, including GID1, RGA, GID2, MYBGa, and 37 photosynthetic differentially expressed genes. Single nucleotide polymorphism (SNP)-based association analysis showed that 142 SNPs, representing 40 candidate genes in this pathway, were significantly associated with photosynthesis, growth, and wood property traits. Epistasis analysis uncovered interactions between 310 SNP-SNP pairs from 37 genes in this pathway, revealing possible genetic interactions. Moreover, a structural gene-gene matrix based on a time-course of transcript abundances provided a better understanding of the multi-gene pathway affecting photosynthesis. The results imply a functional role for these genes in mediating photosynthesis, growth, and wood properties, demonstrating the potential of combining transcriptome-based regulatory pathway construction and genetic association approaches to detect the complex genetic networks underlying quantitative traits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

Science.gov (United States)

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Genetic analysis of repeated, biparental, diploid, hydatidiform moles

DEFF Research Database (Denmark)

Sunde, Lone; Vejerslev, Lars O.; Jensen, Mie Poulsen

1993-01-01

for the abnormal development can be envisaged, environmental as well as genetic. To conform to current ideas of molar pathogenesis, it is suggested that the present conceptuses might have arisen from imbalances in imprinted genomic regions. This could be a consequence of uniparental disomy in critical regions......A woman presented with five consecutive pregnancies displaying molar morphology. In the fifth pregnancy, a non-malformed, liveborn infant was delivered. Genetic analyses (RFLP analysis, cytogenetics, flow cytometry) were performed in pregnancies II-V. It was demonstrated that these pregnancies...... originated in separate conceptions, all conceptuses were diploid, and all had maternally as well as paternally derived genetic markers. By cytogenetic analysis, aberrant heteromorphisms were noted; no other abnormalities were observed in chromosome structure or in DNA sequence. Many different causes...

Large-scale in silico mapping of complex quantitative traits in inbred mice.

Directory of Open Access Journals (Sweden)

Pengyuan Liu

2007-07-01

Full Text Available Understanding the genetic basis of common disease and disease-related quantitative traits will aid in the development of diagnostics and therapeutics. The processs of gene discovery can be sped up by rapid and effective integration of well-defined mouse genome and phenome data resources. We describe here an in silico gene-discovery strategy through genome-wide association (GWA scans in inbred mice with a wide range of genetic variation. We identified 937 quantitative trait loci (QTLs from a survey of 173 mouse phenotypes, which include models of human disease (atherosclerosis, cardiovascular disease, cancer and obesity as well as behavioral, hematological, immunological, metabolic, and neurological traits. 67% of QTLs were refined into genomic regions <0.5 Mb with approximately 40-fold increase in mapping precision as compared with classical linkage analysis. This makes for more efficient identification of the genes that underlie disease. We have identified two QTL genes, Adam12 and Cdh2, as causal genetic variants for atherogenic diet-induced obesity. Our findings demonstrate that GWA analysis in mice has the potential to resolve multiple tightly linked QTLs and achieve single-gene resolution. These high-resolution QTL data can serve as a primary resource for positional cloning and gene identification in the research community.

Genetic diversity of popcorn genotypes using molecular analysis.

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Resh, F S; Scapim, C A; Mangolin, C A; Machado, M F P S; do Amaral, A T; Ramos, H C C; Vivas, M

2015-08-19

In this study, we analyzed dominant molecular markers to estimate the genetic divergence of 26 popcorn genotypes and evaluate whether using various dissimilarity coefficients with these dominant markers influences the results of cluster analysis. Fifteen random amplification of polymorphic DNA primers produced 157 amplified fragments, of which 65 were monomorphic and 92 were polymorphic. To calculate the genetic distances among the 26 genotypes, the complements of the Jaccard, Dice, and Rogers and Tanimoto similarity coefficients were used. A matrix of Dij values (dissimilarity matrix) was constructed, from which the genetic distances among genotypes were represented in a more simplified manner as a dendrogram generated using the unweighted pair-group method with arithmetic average. Clusters determined by molecular analysis generally did not group material from the same parental origin together. The largest genetic distance was between varieties 17 (UNB-2) and 18 (PA-091). In the identification of genotypes with the smallest genetic distance, the 3 coefficients showed no agreement. The 3 dissimilarity coefficients showed no major differences among their grouping patterns because agreement in determining the genotypes with large, medium, and small genetic distances was high. The largest genetic distances were observed for the Rogers and Tanimoto dissimilarity coefficient (0.74), followed by the Jaccard coefficient (0.65) and the Dice coefficient (0.48). The 3 coefficients showed similar estimations for the cophenetic correlation coefficient. Correlations among the matrices generated using the 3 coefficients were positive and had high magnitudes, reflecting strong agreement among the results obtained using the 3 evaluated dissimilarity coefficients.

ImatraNMR: Novel software for batch integration and analysis of quantitative NMR spectra

Science.gov (United States)

Mäkelä, A. V.; Heikkilä, O.; Kilpeläinen, I.; Heikkinen, S.

2011-08-01

Quantitative NMR spectroscopy is a useful and important tool for analysis of various mixtures. Recently, in addition of traditional quantitative 1D 1H and 13C NMR methods, a variety of pulse sequences aimed for quantitative or semiquantitative analysis have been developed. To obtain actual usable results from quantitative spectra, they must be processed and analyzed with suitable software. Currently, there are many processing packages available from spectrometer manufacturers and third party developers, and most of them are capable of analyzing and integration of quantitative spectra. However, they are mainly aimed for processing single or few spectra, and are slow and difficult to use when large numbers of spectra and signals are being analyzed, even when using pre-saved integration areas or custom scripting features. In this article, we present a novel software, ImatraNMR, designed for batch analysis of quantitative spectra. In addition to capability of analyzing large number of spectra, it provides results in text and CSV formats, allowing further data-analysis using spreadsheet programs or general analysis programs, such as Matlab. The software is written with Java, and thus it should run in any platform capable of providing Java Runtime Environment version 1.6 or newer, however, currently it has only been tested with Windows and Linux (Ubuntu 10.04). The software is free for non-commercial use, and is provided with source code upon request.

Genetic architecture and temporal patterns of biomass accumulation in spring barley revealed by image analysis.

Science.gov (United States)

Neumann, Kerstin; Zhao, Yusheng; Chu, Jianting; Keilwagen, Jens; Reif, Jochen C; Kilian, Benjamin; Graner, Andreas

2017-08-10

Genetic mapping of phenotypic traits generally focuses on a single time point, but biomass accumulates continuously during plant development. Resolution of the temporal dynamics that affect biomass recently became feasible using non-destructive imaging. With the aim to identify key genetic factors for vegetative biomass formation from the seedling stage to flowering, we explored growth over time in a diverse collection of two-rowed spring barley accessions. High heritabilities facilitated the temporal analysis of trait relationships and identification of quantitative trait loci (QTL). Biomass QTL tended to persist only a short period during early growth. More persistent QTL were detected around the booting stage. We identified seven major biomass QTL, which together explain 55% of the genetic variance at the seedling stage, and 43% at the booting stage. Three biomass QTL co-located with genes or QTL involved in phenology. The most important locus for biomass was independent from phenology and is located on chromosome 7HL at 141 cM. This locus explained ~20% of the genetic variance, was significant over a long period of time and co-located with HvDIM, a gene involved in brassinosteroid synthesis. Biomass is a dynamic trait and is therefore orchestrated by different QTL during early and late growth stages. Marker-assisted selection for high biomass at booting stage is most effective by also including favorable alleles from seedling biomass QTL. Selection for dynamic QTL may enhance genetic gain for complex traits such as biomass or, in the future, even grain yield.

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

Science.gov (United States)

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.

Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

Science.gov (United States)

Ober, Ulrike; Huang, Wen; Magwire, Michael; Schlather, Martin; Simianer, Henner; Mackay, Trudy F C

2015-01-01

The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

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

Science.gov (United States)

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.

Genetic and genomic analysis modeling of germline c-MYC overexpression and cancer susceptibility

Directory of Open Access Journals (Sweden)

Nunes Virginia

2008-01-01

Full Text Available Abstract Background Germline genetic variation is associated with the differential expression of many human genes. The phenotypic effects of this type of variation may be important when considering susceptibility to common genetic diseases. Three regions at 8q24 have recently been identified to independently confer risk of prostate cancer. Variation at 8q24 has also recently been associated with risk of breast and colorectal cancer. However, none of the risk variants map at or relatively close to known genes, with c-MYC mapping a few hundred kilobases distally. Results This study identifies cis-regulators of germline c-MYC expression in immortalized lymphocytes of HapMap individuals. Quantitative analysis of c-MYC expression in normal prostate tissues suggests an association between overexpression and variants in Region 1 of prostate cancer risk. Somatic c-MYC overexpression correlates with prostate cancer progression and more aggressive tumor forms, which was also a pathological variable associated with Region 1. Expression profiling analysis and modeling of transcriptional regulatory networks predicts a functional association between MYC and the prostate tumor suppressor KLF6. Analysis of MYC/Myc-driven cell transformation and tumorigenesis substantiates a model in which MYC overexpression promotes transformation by down-regulating KLF6. In this model, a feedback loop through E-cadherin down-regulation causes further transactivation of c-MYC. Conclusion This study proposes that variation at putative 8q24 cis-regulator(s of transcription can significantly alter germline c-MYC expression levels and, thus, contribute to prostate cancer susceptibility by down-regulating the prostate tumor suppressor KLF6 gene.

RESEARCH NOTE Molecular genetic analysis of consanguineous ...

Indian Academy of Sciences (India)

Navya

Molecular genetic analysis of consanguineous families with primary microcephaly ... Translational Research Institute, Academic Health System, Hamad Medical ..... bridging the gap between homozygosity mapping and deep sequencing.

A genetic analysis of Trichuris trichiura and Trichuris suis from Ecuador

DEFF Research Database (Denmark)

Meekums, Hayley; Hawash, Mohamed B F; Sparks, Alexandra M

2015-01-01

BACKGROUND: Since the nematodes Trichuris trichiura and T. suis are morphologically indistinguishable, genetic analysis is required to assess epidemiological cross-over between people and pigs. This study aimed to clarify the transmission biology of trichuriasis in Ecuador. FINDINGS: Adult...... Trichuris worms were collected during a parasitological survey of 132 people and 46 pigs in Esmeraldas Province, Ecuador. Morphometric analysis of 49 pig worms and 64 human worms revealed significant variation. In discriminant analysis morphometric characteristics correctly classified male worms according...... to genetically analyse Trichuris parasites. Although T. trichiura does not appear to be zoonotic in Ecuador, there is evidence of genetic exchange between T. trichiura and T. suis warranting more detailed genetic sampling....

Parameter estimation using the genetic algorithm and its impact on quantitative precipitation forecast

Directory of Open Access Journals (Sweden)

Y. H. Lee

2006-12-01

Full Text Available In this study, optimal parameter estimations are performed for both physical and computational parameters in a mesoscale meteorological model, and their impacts on the quantitative precipitation forecasting (QPF are assessed for a heavy rainfall case occurred at the Korean Peninsula in June 2005. Experiments are carried out using the PSU/NCAR MM5 model and the genetic algorithm (GA for two parameters: the reduction rate of the convective available potential energy in the Kain-Fritsch (KF scheme for cumulus parameterization, and the Asselin filter parameter for numerical stability. The fitness function is defined based on a QPF skill score. It turns out that each optimized parameter significantly improves the QPF skill. Such improvement is maximized when the two optimized parameters are used simultaneously. Our results indicate that optimizations of computational parameters as well as physical parameters and their adequate applications are essential in improving model performance.

Development and application of a multi-targeting reference plasmid as calibrator for analysis of five genetically modified soybean events.

Science.gov (United States)

Pi, Liqun; Li, Xiang; Cao, Yiwei; Wang, Canhua; Pan, Liangwen; Yang, Litao

2015-04-01

Reference materials are important in accurate analysis of genetically modified organism (GMO) contents in food/feeds, and development of novel reference plasmid is a new trend in the research of GMO reference materials. Herein, we constructed a novel multi-targeting plasmid, pSOY, which contained seven event-specific sequences of five GM soybeans (MON89788-5', A2704-12-3', A5547-127-3', DP356043-5', DP305423-3', A2704-12-5', and A5547-127-5') and sequence of soybean endogenous reference gene Lectin. We evaluated the specificity, limit of detection and quantification, and applicability of pSOY in both qualitative and quantitative PCR analyses. The limit of detection (LOD) was as low as 20 copies in qualitative PCR, and the limit of quantification (LOQ) in quantitative PCR was 10 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and Lectin assays were higher than 90%, and the squared regression coefficients (R(2)) were more than 0.999. The quantification bias varied from 0.21% to 19.29%, and the relative standard deviations were from 1.08% to 9.84% in simulated samples analysis. All the results demonstrated that the developed multi-targeting plasmid, pSOY, was a credible substitute of matrix reference materials, and could be used as a reliable reference calibrator in the identification and quantification of multiple GM soybean events.

Modelling Autistic Features in Mice Using Quantitative Genetic Approaches

NARCIS (Netherlands)

Molenhuis, Remco T; Bruining, Hilgo; Kas, Martien J

2017-01-01

Animal studies provide a unique opportunity to study the consequences of genetic variants at the behavioural level. Human studies have identified hundreds of risk genes for autism spectrum disorder (ASD) that can lead to understanding on how genetic variation contributes to individual differences in

Strains and Stressors: An Analysis of Touchscreen Learning in Genetically Diverse Mouse Strains

Science.gov (United States)

Graybeal, Carolyn; Bachu, Munisa; Mozhui, Khyobeni; Saksida, Lisa M.; Bussey, Timothy J.; Sagalyn, Erica; Williams, Robert W.; Holmes, Andrew

2014-01-01

Touchscreen-based systems are growing in popularity as a tractable, translational approach for studying learning and cognition in rodents. However, while mouse strains are well known to differ in learning across various settings, performance variation between strains in touchscreen learning has not been well described. The selection of appropriate genetic strains and backgrounds is critical to the design of touchscreen-based studies and provides a basis for elucidating genetic factors moderating behavior. Here we provide a quantitative foundation for visual discrimination and reversal learning using touchscreen assays across a total of 35 genotypes. We found significant differences in operant performance and learning, including faster reversal learning in DBA/2J compared to C57BL/6J mice. We then assessed DBA/2J and C57BL/6J for differential sensitivity to an environmental insult by testing for alterations in reversal learning following exposure to repeated swim stress. Stress facilitated reversal learning (selectively during the late stage of reversal) in C57BL/6J, but did not affect learning in DBA/2J. To dissect genetic factors underlying these differences, we phenotyped a family of 27 BXD strains generated by crossing C57BL/6J and DBA/2J. There was marked variation in discrimination, reversal and extinction learning across the BXD strains, suggesting this task may be useful for identifying underlying genetic differences. Moreover, different measures of touchscreen learning were only modestly correlated in the BXD strains, indicating that these processes are comparatively independent at both genetic and phenotypic levels. Finally, we examined the behavioral structure of learning via principal component analysis of the current data, plus an archival dataset, totaling 765 mice. This revealed 5 independent factors suggestive of “reversal learning,” “motivation-related late reversal learning,” “discrimination learning,” “speed to respond,” and �

Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm.

Science.gov (United States)

Yan, Jingwen; Du, Lei; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-09-01

Imaging genetics is an emerging field that studies the influence of genetic variation on brain structure and function. The major task is to examine the association between genetic markers such as single-nucleotide polymorphisms (SNPs) and quantitative traits (QTs) extracted from neuroimaging data. The complexity of these datasets has presented critical bioinformatics challenges that require new enabling tools. Sparse canonical correlation analysis (SCCA) is a bi-multivariate technique used in imaging genetics to identify complex multi-SNP-multi-QT associations. However, most of the existing SCCA algorithms are designed using the soft thresholding method, which assumes that the input features are independent from one another. This assumption clearly does not hold for the imaging genetic data. In this article, we propose a new knowledge-guided SCCA algorithm (KG-SCCA) to overcome this limitation as well as improve learning results by incorporating valuable prior knowledge. The proposed KG-SCCA method is able to model two types of prior knowledge: one as a group structure (e.g. linkage disequilibrium blocks among SNPs) and the other as a network structure (e.g. gene co-expression network among brain regions). The new model incorporates these prior structures by introducing new regularization terms to encourage weight similarity between grouped or connected features. A new algorithm is designed to solve the KG-SCCA model without imposing the independence constraint on the input features. We demonstrate the effectiveness of our algorithm with both synthetic and real data. For real data, using an Alzheimer's disease (AD) cohort, we examine the imaging genetic associations between all SNPs in the APOE gene (i.e. top AD gene) and amyloid deposition measures among cortical regions (i.e. a major AD hallmark). In comparison with a widely used SCCA implementation, our KG-SCCA algorithm produces not only improved cross-validation performances but also biologically meaningful

Quantitative subsurface analysis using frequency modulated thermal wave imaging

Science.gov (United States)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

A cross-species genetic analysis identifies candidate genes for mouse anxiety and human bipolar disorder

Directory of Open Access Journals (Sweden)

David G Ashbrook

2015-07-01

Full Text Available Bipolar disorder (BD is a significant neuropsychiatric disorder with a lifetime prevalence of ~1%. To identify genetic variants underlying BD genome-wide association studies (GWAS have been carried out. While many variants of small effect associated with BD have been identified few have yet been confirmed, partly because of the low power of GWAS due to multiple comparisons being made. Complementary mapping studies using murine models have identified genetic variants for behavioral traits linked to BD, often with high power, but these identified regions often contain too many genes for clear identification of candidate genes. In the current study we have aligned human BD GWAS results and mouse linkage studies to help define and evaluate candidate genes linked to BD, seeking to use the power of the mouse mapping with the precision of GWAS. We use quantitative trait mapping for open field test and elevated zero maze data in the largest mammalian model system, the BXD recombinant inbred mouse population, to identify genomic regions associated with these BD-like phenotypes. We then investigate these regions in whole genome data from the Psychiatric Genomics Consortium’s bipolar disorder GWAS to identify candidate genes associated with BD. Finally we establish the biological relevance and pathways of these genes in a comprehensive systems genetics analysis.We identify four genes associated with both mouse anxiety and human BD. While TNR is a novel candidate for BD, we can confirm previously suggested associations with CMYA5, MCTP1 and RXRG. A cross-species, systems genetics analysis shows that MCTP1, RXRG and TNR coexpress with genes linked to psychiatric disorders and identify the striatum as a potential site of action. CMYA5, MCTP1, RXRG and TNR are associated with mouse anxiety and human BD. We hypothesize that MCTP1, RXRG and TNR influence intercellular signaling in the striatum.

Brief Communication: Quantitative- and molecular-genetic differentiation in humans and chimpanzees: implications for the evolutionary processes underlying cranial diversification.

Science.gov (United States)

Weaver, Timothy D

2014-08-01

Estimates of the amount of genetic differentiation in humans among major geographic regions (e.g., Eastern Asia vs. Europe) from quantitative-genetic analyses of cranial measurements closely match those from classical- and molecular-genetic markers. Typically, among-region differences account for ∼10% of the total variation. This correspondence is generally interpreted as evidence for the importance of neutral evolutionary processes (e.g., genetic drift) in generating among-region differences in human cranial form, but it was initially surprising because human cranial diversity was frequently assumed to show a strong signature of natural selection. Is the human degree of similarity of cranial and DNA-sequence estimates of among-region genetic differentiation unusual? How do comparisons with other taxa illuminate the evolutionary processes underlying cranial diversification? Chimpanzees provide a useful starting point for placing the human results in a broader comparative context, because common chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) are the extant species most closely related to humans. To address these questions, I used 27 cranial measurements collected on a sample of 861 humans and 263 chimpanzees to estimate the amount of genetic differentiation between pairs of groups (between regions for humans and between species or subspecies for chimpanzees). Consistent with previous results, the human cranial estimates are quite similar to published DNA-sequence estimates. In contrast, the chimpanzee cranial estimates are much smaller than published DNA-sequence estimates. It appears that cranial differentiation has been limited in chimpanzees relative to humans. © 2014 Wiley Periodicals, Inc.

Short Communication: Genetic linkage map of Cucurbita maxima with molecular and morphological markers.

Science.gov (United States)

Ge, Y; Li, X; Yang, X X; Cui, C S; Qu, S P

2015-05-22

Cucurbita maxima is one of the most widely cultivated vegetables in China and exhibits distinct morphological characteristics. In this study, genetic linkage analysis with 57 simple-sequence repeats, 21 amplified fragment length polymorphisms, 3 random-amplified polymorphic DNA, and one morphological marker revealed 20 genetic linkage groups of C. maxima covering a genetic distance of 991.5 cM with an average of 12.1 cM between adjacent markers. Genetic linkage analysis identified the simple-sequence repeat marker 'PU078072' 5.9 cM away from the locus 'Rc', which controls rind color. The genetic map in the present study will be useful for better mapping, tagging, and cloning of quantitative trait loci/gene(s) affecting economically important traits and for breeding new varieties of C. maxima through marker-assisted selection.

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

Science.gov (United States)

Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

2011-09-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

Quantitative analysis by nuclear magnetic resonance spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Wainai, T; Mashimo, K [Nihon Univ., Tokyo. Coll. of Science and Engineering

1976-04-01

Recent papers on the practical quantitative analysis by nuclear magnetic resonance spectroscopy (NMR) are reviewed. Specifically, the determination of moisture in liquid N/sub 2/O/sub 4/ as an oxidizing agent for rocket propulsion, the analysis of hydroperoxides, the quantitative analysis using a shift reagent, the analysis of aromatic sulfonates, and the determination of acids and bases are reviewed. Attention is paid to the accuracy. The sweeping velocity and RF level in addition to the other factors must be on the optimal condition to eliminate the errors, particularly when computation is made with a machine. Higher sweeping velocity is preferable in view of S/N ratio, but it may be limited to 30 Hz/s. The relative error in the measurement of area is generally 1%, but when those of dilute concentration and integrated, the error will become smaller by one digit. If impurities are treated carefully, the water content on N/sub 2/O/sub 4/ can be determined with accuracy of about 0.002%. The comparison method between peak heights is as accurate as that between areas, when the uniformity of magnetic field and T/sub 2/ are not questionable. In the case of chemical shift movable due to content, the substance can be determined by the position of the chemical shift. Oil and water contents in rape-seed, peanuts, and sunflower-seed are determined by measuring T/sub 1/ with 90 deg pulses.

Exploring meat quality of pig throug the application of molecular genetics

DEFF Research Database (Denmark)

Zhang, Lu

association mapping, expression study and genetic variation analysis. Many state of the art technologies including high-density SNP chip genotyping, hig-throughput re-sequencing and strand-specific RNA-Seq were employed. Numerous quantitative trait loci, candidate genes and a segmental duplication associated...

Analysis of genetic structure in Melia volkensii (Gurke.) populations ...

African Journals Online (AJOL)

Administrator

2Farm Forestry Programme, Kenya Forestry Research Institute, P. O. Box 20412, Nairobi, Kenya. Accepted 5 ... were used to estimate genetic distances between populations and for construction of neighbour-joining phenograms. Analysis of Molecular Variance (AMOVA) indicated significant genetic differentiation between ...

Genetic and environmental influences on infant growth: prospective analysis of the Gemini twin birth cohort.

Directory of Open Access Journals (Sweden)

Laura Johnson

Full Text Available Infancy is a critical period during which rapid growth potentially programs future disease risk. Identifying the modifiable determinants of growth is therefore important. To capture the complexity of infant growth, we modeled growth trajectories from birth to six months in order to compare the genetic and environmental influences on growth trajectory parameters with single time-point measures at birth, three and six months of age.Data were from Gemini, a population sample of 2402 UK families with twins. An average 10 weight measurements per child made by health professionals were available over the first six months. Weights at birth, three and six months were identified. Longitudinal growth trajectories were modeled using SITAR utilizing all available weight measures for each child. SITAR generates three parameters: size (characterizing mean weight throughout infancy, tempo (indicating age at peak weight velocity (PWV, and velocity (reflecting the size of PWV. Genetic and environmental influences were estimated using quantitative genetic analysis.In line with previous studies, heritability of weight at birth and three months was low (38%, but it was higher at six months (62%. Heritability of the growth trajectory parameters was high for size (69% and velocity (57%, but low (35% for tempo. Common environmental influences predominated for tempo (42%.Modeled growth parameters using SITAR indicated that size and velocity were primarily under genetic influence but tempo was predominantly environmentally determined. These results emphasize the importance of identifying specific modifiable environmental determinants of the timing of peak infant growth.

Stable Isotope Quantitative N-Glycan Analysis by Liquid Separation Techniques and Mass Spectrometry.

Science.gov (United States)

Mittermayr, Stefan; Albrecht, Simone; Váradi, Csaba; Millán-Martín, Silvia; Bones, Jonathan

2017-01-01

Liquid phase separation analysis and subsequent quantitation remains a challenging task for protein-derived oligosaccharides due to their inherent structural complexity and diversity. Incomplete resolution or co-detection of multiple glycan species complicates peak area-based quantitation and associated statistical analysis when optical detection methods are used. The approach outlined herein describes the utilization of stable isotope variants of commonly used fluorescent tags that allow for mass-based glycan identification and relative quantitation following separation by liquid chromatography (LC) or capillary electrophoresis (CE). Comparability assessment of glycoprotein-derived oligosaccharides is performed by derivatization with commercially available isotope variants of 2-aminobenzoic acid or aniline and analysis by LC- and CE-mass spectrometry. Quantitative information is attained from the extracted ion chromatogram/electropherogram ratios generated from the light and heavy isotope clusters.

Quantitative Gait Analysis in Patients with Huntington’s Disease

Directory of Open Access Journals (Sweden)

Seon Jong Pyo

2017-09-01

Full Text Available Objective Gait disturbance is the main factor contributing to a negative impact on quality of life in patients with Huntington’s disease (HD. Understanding gait features in patients with HD is essential for planning a successful gait strategy. The aim of this study was to investigate temporospatial gait parameters in patients with HD compared with healthy controls. Methods We investigated 7 patients with HD. Diagnosis was confirmed by genetic analysis, and patients were evaluated with the Unified Huntington’s Disease Rating Scale (UHDRS. Gait features were assessed with a gait analyzer. We compared the results of patients with HD to those of 7 age- and sex-matched normal controls. Results Step length and stride length were decreased and base of support was increased in the HD group compared to the control group. In addition, coefficients of variability for step and stride length were increased in the HD group. The HD group showed slower walking velocity, an increased stance/swing phase in the gait cycle and a decreased proportion of single support time compared to the control group. Cadence did not differ significantly between groups. Among the UHDRS subscores, total motor score and total behavior score were positively correlated with step length, and total behavior score was positively correlated with walking velocity in patients with HD. Conclusion Increased variability in step and stride length, slower walking velocity, increased stance phase, and decreased swing phase and single support time with preserved cadence suggest that HD gait patterns are slow, ataxic and ineffective. This study suggests that quantitative gait analysis is needed to assess gait problems in HD.

Isolation and characterization of microsatellite markers and analysis of genetic variability in Curculigo latifolia Dryand.

Science.gov (United States)

Babaei, Nahid; Abdullah, Nur Ashikin Psyquay; Saleh, Ghizan; Abdullah, Thohirah Lee

2012-11-01

Curculin, a sweet protein found in Curculigo latifolia fruit has great potential for the pharmaceutical industry. This protein interestingly has been found to have both sweet taste and taste-modifying capacities comparable with other natural sweeteners. According to our knowledge this is the first reported case on the isolation of microsatellite loci in this genus. Hence, the current development of microsatellite markers for C. latifolia will facilitate future population genetic studies and breeding programs for this valuable plant. In this study 11 microsatellite markers were developed using 3' and 5' ISSR markers. The primers were tested on 27 accessions from all states of Peninsular Malaysia. The number of alleles per locus ranged from three to seven, with allele size ranging from 141 to 306 bp. The observed and expected heterozygosity ranged between 0.00-0.65 and 0.38-0.79, respectively. The polymorphic information content ranged from 0.35 to 0.74 and the Shannon's information index ranged from 0.82 to 1.57. These developed polymorphic microsatellites were used for constructing a dendrogram by unweighted pair group method with arithmetic mean cluster analysis using the Dice's similarity coefficient. Accessions association according to their geographical origin was observed. Based on characteristics of isolated microsatellites for C. latifolia accessions all genotype can be distinguished using these 11 microsatellite markers. These polymorphic markers could also be applied to studies on uniformity determination and somaclonal variation of tissue culture plantlets, varieties identification, genetic diversity, analysis of phylogenetic relationship, genetic linkage maps and quantitative trait loci in C. latifolia.

Quantitative analysis of myocardial tissue with digital autofluorescence microscopy

DEFF Research Database (Denmark)

Jensen, Thomas; Holten-Rossing, Henrik; Svendsen, Ida M H

2016-01-01

to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including...... staining may benefit. METHODS: This study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm......BACKGROUND: The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar...

Identification of autophagosome-associated proteins and regulators by quantitative proteomic analysis and genetic screens

DEFF Research Database (Denmark)

Dengjel, Jörn; Høyer-Hansen, Maria; Nielsen, Maria

2012-01-01

Autophagy is one of the major intracellular catabolic pathways, but little is known about the composition of autophagosomes. To study the associated proteins, we isolated autophagosomes from human breast cancer cells using two different biochemical methods and three stimulus types: amino acid dep...... regulators of autophagy, including subunits of the retromer complex. The combined spatiotemporal proteomic and genetic data sets presented here provide a basis for further characterization of autophagosome biogenesis and cargo selection....

MetaGenyo: a web tool for meta-analysis of genetic association studies.

Science.gov (United States)

Martorell-Marugan, Jordi; Toro-Dominguez, Daniel; Alarcon-Riquelme, Marta E; Carmona-Saez, Pedro

2017-12-16

Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/ .

Smoothing of the bivariate LOD score for non-normal quantitative traits.

Science.gov (United States)

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Quantitative analysis of target components by comprehensive two-dimensional gas chromatography

NARCIS (Netherlands)

Mispelaar, V.G. van; Tas, A.C.; Smilde, A.K.; Schoenmakers, P.J.; Asten, A.C. van

2003-01-01

Quantitative analysis using comprehensive two-dimensional (2D) gas chromatography (GC) is still rarely reported. This is largely due to a lack of suitable software. The objective of the present study is to generate quantitative results from a large GC x GC data set, consisting of 32 chromatograms.

Genetic Pathways to Insomnia

OpenAIRE

Mackenzie J. Lind; Philip R. Gehrman

2016-01-01

This review summarizes current research on the genetics of insomnia, as genetic contributions are thought to be important for insomnia etiology. We begin by providing an overview of genetic methods (both quantitative and measured gene), followed by a discussion of the insomnia genetics literature with regard to each of the following common methodologies: twin and family studies, candidate gene studies, and genome-wide association studies (GWAS). Next, we summarize the most recent gene identif...

Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator

DEFF Research Database (Denmark)

Carayol, Jérôme; Chabert, Christian; Di Cara, Alessandro

2017-01-01

of an organism. Proteome analysis especially can provide new insights into the molecular mechanisms of complex traits like obesity. The role of genetic variation in determining protein level variation has not been assessed in obesity. To address this, we design a large-scale protein quantitative trait locus (p...

Role of image analysis in quantitative characterisation of nuclear fuel materials

International Nuclear Information System (INIS)

Dubey, J.N.; Rao, T.S.; Pandey, V.D.; Majumdar, S.

2005-01-01

Image analysis is one of the important techniques, widely used for materials characterization. It provides the quantitative estimation of the microstructural features present in the material. This information is very much valuable for finding out the criteria for taking up the fuel for high burn up. Radiometallurgy Division has been carrying out development and fabrication of plutonium related fuels for different type of reactors viz. Purnima, Fast Breeder Test Reactor (FBTR), Prototype Fast Breeder Reactor (PFBR), Boiling Water Reactor (BWR), Advanced Heavy Water Reactor (AHWR), Pressurised Heavy Water Reactor (PHWR) and KAMINI Reactor. Image analysis has been carried out on microstructures of PHWR, AHWR, FBTR and KAMINI fuels. Samples were prepared as per standard ASTM metallographic procedure. Digital images of the microstructure of these specimens were obtained using CCD camera, attached to the optical microscope. These images are stores on computer and used for detection and analysis of features of interest with image analysis software. Quantitative image analysis technique has been standardised and used for finding put type of the porosity, its size, shape and distribution in the above sintered oxide and carbide fuels. This technique has also been used for quantitative estimation of different phases present in KAMINI fuel. Image analysis results have been summarised and presented in this paper. (author)

Micro photometer's automation for quantitative spectrograph analysis

International Nuclear Information System (INIS)

Gutierrez E, C.Y.A.

1996-01-01

A Microphotometer is used to increase the sharpness of dark spectral lines. Analyzing these lines one sample content and its concentration could be determined and the analysis is known as Quantitative Spectrographic Analysis. The Quantitative Spectrographic Analysis is carried out in 3 steps, as follows. 1. Emulsion calibration. This consists of gauging a photographic emulsion, to determine the intensity variations in terms of the incident radiation. For the procedure of emulsion calibration an adjustment with square minimum to the data obtained is applied to obtain a graph. It is possible to determine the density of dark spectral line against the incident light intensity shown by the microphotometer. 2. Working curves. The values of known concentration of an element against incident light intensity are plotted. Since the sample contains several elements, it is necessary to find a work curve for each one of them. 3. Analytical results. The calibration curve and working curves are compared and the concentration of the studied element is determined. The automatic data acquisition, calculation and obtaining of resulting, is done by means of a computer (PC) and a computer program. The conditioning signal circuits have the function of delivering TTL levels (Transistor Transistor Logic) to make the communication between the microphotometer and the computer possible. Data calculation is done using a computer programm

Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

Directory of Open Access Journals (Sweden)

Ulrike Ober

Full Text Available The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17% of the genetic variance among lines in females (males, the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

[Rapid analysis of suppositories by quantitative 1H NMR spectroscopy].

Science.gov (United States)

Abramovich, R A; Kovaleva, S A; Goriainov, S V; Vorob'ev, A N; Kalabin, G A

2012-01-01

Rapid analysis of suppositories with ibuprofen and arbidol by quantitative 1H NMR spectroscopy was performed. Optimal conditions for the analysis were developed. The results are useful for design of rapid methods for quality control of suppositories with different components

Quantitative time domain analysis of lifetime-based Förster resonant energy transfer measurements with fluorescent proteins: Static random isotropic fluorophore orientation distributions

DEFF Research Database (Denmark)

Alexandrov, Yuriy; Nikolic, Dino Solar; Dunsby, Christopher

2018-01-01

Förster resonant energy transfer (FRET) measurements are widely used to obtain information about molecular interactions and conformations through the dependence of FRET efficiency on the proximity of donor and acceptor fluorophores. Fluorescence lifetime measurements can provide quantitative...... into new software for fitting donor emission decay profiles. Calculated FRET parameters, including molar population fractions, are compared for the analysis of simulated and experimental FRET data under the assumption of static and dynamic fluorophores and the intermediate regimes between fully dynamic...... analysis of FRET efficiency and interacting population fraction. Many FRET experiments exploit the highly specific labelling of genetically expressed fluorescent proteins, applicable in live cells and organisms. Unfortunately, the typical assumption of fast randomization of fluorophore orientations...

Quantitative EDXS analysis of organic materials using the ζ-factor method

International Nuclear Information System (INIS)

Fladischer, Stefanie; Grogger, Werner

2014-01-01

In this study we successfully applied the ζ-factor method to perform quantitative X-ray analysis of organic thin films consisting of light elements. With its ability to intrinsically correct for X-ray absorption, this method significantly improved the quality of the quantification as well as the accuracy of the results compared to conventional techniques in particular regarding the quantification of light elements. We describe in detail the process of determining sensitivity factors (ζ-factors) using a single standard specimen and the involved parameter optimization for the estimation of ζ-factors for elements not contained in the standard. The ζ-factor method was then applied to perform quantitative analysis of organic semiconducting materials frequently used in organic electronics. Finally, the results were verified and discussed concerning validity and accuracy. - Highlights: • The ζ-factor method is used for quantitative EDXS analysis of light elements. • We describe the process of determining ζ-factors from a single standard in detail. • Organic semiconducting materials are successfully quantified

Disentangling the intertwined genetic bases of root and shoot growth in Arabidopsis.

Directory of Open Access Journals (Sweden)

Marie Bouteillé

Full Text Available Root growth and architecture are major components of plant nutrient and water use efficiencies and these traits are the matter of extensive genetic analysis in several crop species. Because root growth relies on exported assimilate from the shoot, and changes in assimilate supply are known to alter root architecture, we hypothesized (i that the genetic bases of root growth could be intertwined with the genetic bases of shoot growth and (ii that the link could be either positive, with alleles favouring shoot growth also favouring root growth, or negative, because of competition for assimilates. We tested these hypotheses using a quantitative genetics approach in the model species Arabidopsis thaliana and the Bay-0 × Shahdara recombinant inbred lines population. In accordance with our hypothesis, root and shoot growth traits were strongly correlated and most root growth quantitative trait loci (QTLs colocalized with shoot growth QTLs with positive alleles originating from either the same or the opposite parent. In order to identify regions that could be responsible for root growth independently of the shoot, we generated new variables either based on root to shoot ratios, residuals of root to shoot correlations or coordinates of principal component analysis. These variables showed high heritability allowing genetic analysis. They essentially all yielded similar results pointing towards two regions involved in the root--shoot balance. Using Heterogeneous Inbred Families (a kind of near-isogenic lines, we validated part of the QTLs present in these two regions for different traits. Our study thus highlights the difficulty of disentangling intertwined genetic bases of root and shoot growth and shows that this difficulty can be overcome by using simple statistical tools.

Quantitative analysis by computer controlled X-ray fluorescence spectrometer

International Nuclear Information System (INIS)

Balasubramanian, T.V.; Angelo, P.C.

1981-01-01

X-ray fluorescence spectroscopy has become a widely accepted method in the metallurgical field for analysis of both minor and major elements. As encountered in many other analytical techniques, the problem of matrix effect generally known as the interelemental effects is to be dealt with effectively in order to make the analysis accurate. There are several methods by which the effects of matrix on the analyte are minimised or corrected for and the mathematical correction is one among them. In this method the characteristic secondary X-ray intensities are measured from standard samples and correction coefficients. If any, for interelemental effects are evaluated by mathematical calculations. This paper describes attempts to evaluate the correction coefficients for interelemental effects by multiple linear regression programmes using a computer for the quantitative analysis of stainless steel and a nickel base cast alloy. The quantitative results obtained using this method for a standard stainless steel sample are compared with the given certified values. (author)

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

Science.gov (United States)

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?

Science.gov (United States)

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.

PIQMIe: A web server for semi-quantitative proteomics data management and analysis

NARCIS (Netherlands)

A. Kuzniar (Arnold); R. Kanaar (Roland)

2014-01-01

textabstractWe present the Proteomics Identifications and Quantitations Data Management and Integration Service or PIQMIe that aids in reliable and scalable data management, analysis and visualization of semi-quantitative mass spectrometry based proteomics experiments. PIQMIe readily integrates

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

Science.gov (United States)

Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

1999-01-01

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

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

Directory of Open Access Journals (Sweden)

Nuno D Pires

2016-01-01

Full Text Available 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.

Genetic Diversity of Upland Rice Germplasm in Malaysia Based on Quantitative Traits

Directory of Open Access Journals (Sweden)

M. Sohrabi

2012-01-01

Full Text Available Genetic diversity is prerequisite for any crop improvement program as it helps in the development of superior recombinants. Fifty Malaysian upland rice accessions were evaluated for 12 growth traits, yield and yield components. All of the traits were significant and highly significant among the accessions. The higher magnitudes of genotypic and phenotypic coefficients of variation were recorded for flag leaf length-to-width ratio, spikelet fertility, and days to flowering. High heritability along with high genetic advance was registered for yield of plant, days to flowering, and flag leaf length-to-width ratio suggesting preponderance of additive gene action in the gene expression of these characters. Plant height showed highly significant positive correlation with most of the traits. According to UPGMA cluster analysis all accessions were clustered into six groups. Twelve morphological traits provided around 77% of total variation among the accessions.

Critical appraisal of semi-quantitative analysis of 2-deoxyglucose autoradiograms

Energy Technology Data Exchange (ETDEWEB)

Kelly, P T; McCulloch, J [Glasgow Univ. (UK)

1983-06-13

Semi-quantitative analysis (e.g. optical density ratios) of (/sup 14/C)2-deoxyglucose autoradiograms is widely used in neuroscience research. The authors demonstrate that a fixed ratio of /sup 14/C-concentrations in the CNS does not yield a constant optical density ratio but is dependent upon the exposure time in the preparation of the autoradiograms and the absolute amounts of /sup 14/C from which the concentration ratio is derived. The failure of a fixed glucose utilization ratio to result in a constant optical density ratio represents a major interpretative difficulty in investigations where only semi-quantitative analysis of (/sup 14/C)2-deoxyglucose autoradiograms is undertaken.

Quantitative Analysis of Complex Tropical Forest Stands: A Review ...

African Journals Online (AJOL)

FIRST LADY

The importance of data analysis in quantitative assessment of natural resources .... Data collection design is an important process in complex forest statistical ... Ideally, the sample size should be equal among groups and sufficiently large.

Transportation and quantitative analysis of socio-economic development of relations

Science.gov (United States)

Chen, Yun

2017-12-01

Transportation has a close relationship with socio-economic. This article selects the indicators which can measure the development of transportation and socio-economic, using the method of correlation analysis, regression analysis, intensity of transportation analysis and transport elastic analysis, to analyze the relationship between them quantitatively, so that it has the fact guiding sense in the national development planning for the future.

Quantitative high-resolution genomic analysis of single cancer cells.

Science.gov (United States)

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

Quantitative Proteomic Analysis of Sulfolobus solfataricus Membrane Proteins

NARCIS (Netherlands)

Pham, T.K.; Sierocinski, P.; Oost, van der J.; Wright, P.C.

2010-01-01

A quantitative proteomic analysis of the membrane of the archaeon Sulfolobus solfataricus P2 using iTRAQ was successfully demonstrated in this technical note. The estimated number of membrane proteins of this organism is 883 (predicted based on Gravy score), corresponding to 30 % of the total

Theme trends and knowledge structure on choroidal neovascularization: a quantitative and co-word analysis.

Science.gov (United States)

Zhao, Fangkun; Shi, Bei; Liu, Ruixin; Zhou, Wenkai; Shi, Dong; Zhang, Jinsong

2018-04-03

The distribution pattern and knowledge structure of choroidal neovascularization (CNV) was surveyed based on literatures in PubMed. Published scientific papers about CNV were retrieved from Jan 1st, 2012 to May 31st, 2017. Extracted MeSH terms were analyzed quantitatively by using Bibliographic Item Co-Occurrence Matrix Builder (BICOMB) and high-frequency MeSH terms were identified. Hierarchical cluster analysis was conducted by SPSS 19.0 according to the MeSH term-source article matrix. High-frequency MeSH terms co-occurrence matrix was constructed to support strategic diagram and social network analysis (SNA). According to the searching strategy, all together 2366 papers were included, and the number of annual papers changed slightly from Jan 1st, 2012 to May 31st, 2017. Among all the extracted MeSH terms, 44 high-frequency MeSH terms were identified and hotspots were clustered into 6 categories. In the strategic diagram, clinical drug therapy, pathology and diagnosis related researches of CNV were well developed. In contrast, the metabolism, etiology, complications, prevention and control of CNV in animal models, and genetics related researches of CNV were relatively immature, which offers potential research space for future study. As for the SNA result, the position status of each component was described by the centrality values. The studies on CNV are relatively divergent and the 6 research categories concluded from this study could reflect the publication trends on CNV to some extent. By providing a quantitative bibliometric research across a 5-year span, it could help to depict an overall command of the latest topics and provide some hints for researchers when launching new projects.

Genetic and Quantitative Trait Locus Analysis of Cell Wall Components and Forage Digestibility in the Zheng58 × HD568 Maize RIL Population at Anthesis Stage.

Science.gov (United States)

Li, Kun; Wang, Hongwu; Hu, Xiaojiao; Ma, Feiqian; Wu, Yujin; Wang, Qi; Liu, Zhifang; Huang, Changling

2017-01-01

The plant cell wall plays vital roles in various aspects of the plant life cycle. It provides a basic structure for cells and gives mechanical rigidity to the whole plant. Some complex cell wall components are involved in signal transduction during pathogenic infection and pest infestations. Moreover, the lignification level of cell walls strongly influences the digestibility of forage plants. To determine the genetic bases of cell wall components and digestibility, quantitative trait locus (QTL) analyses for six related traits were performed using a recombinant inbred line (RIL) population from a cross between Zheng58 and HD568. Eight QTL for in vitro neutral detergent fiber (NDF) digestibility were observed, out of which only two increasing alleles came from HD568. Three QTL out of ten with alleles increasing in vitro dry matter digestibility also originated from HD568. Five-ten QTL were detected for lignin, cellulose content, acid detergent fiber, and NDF content. Among these results, 29.8% (14/47) of QTL explained >10% of the phenotypic variation in the RIL population, whereas 70.2% (33/47) explained ≤10%. These results revealed that in maize stalks, a few large-effect QTL and a number of minor-effect QTL contributed to most of the genetic components involved in cell wall biosynthesis and digestibility.

Quantitative X-ray analysis of biological fluids: the microdroplet technique

International Nuclear Information System (INIS)

Roinel, N.

1988-01-01

X-ray microanalysis can be used to quantitatively determine the elemental composition of microvolumes of biological fluids. This article describes the various steps in preparation of microdroplets for analysis: The manufacturing of micropipettes, the preparation of the specimen support, the deposition of droplets on the support, shock-freezing, and lyophilization. Examples of common artifacts (incomplete rehydration prior to freezing or partial rehydration after lyophilization) are demonstrated. Analysis can be carried out either by wavelength-dispersive analysis, which is the most sensitive method, or by energy-dispersive analysis, which is more commonly available. The minimum detectable concentration is 0.05 mmol.liter-1 for 0.1-nl samples analyzed by wavelength-dispersive spectrometry and 0.5-1 mmol.liter-1 for samples analyzed by energy-dispersive spectrometry. A major problem, especially in wavelength-dispersive analysis, where high beam currents are used, is radiation damage to the specimen; in particular chloride (but also other elements) can be lost. Quantitative analysis requires the use of standard solutions with elemental concentration in the same range as those present in the specimen

Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

Science.gov (United States)

Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

2007-09-01

Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

SimHap GUI: an intuitive graphical user interface for genetic association analysis.

Science.gov (United States)

Carter, Kim W; McCaskie, Pamela A; Palmer, Lyle J

2008-12-25

Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool. We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress. SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.

Method of quantitative x-ray diffractometric analysis of Ta-Ta2C system

International Nuclear Information System (INIS)

Gavrish, A.A.; Glazunov, M.P.; Korolev, Yu.M.; Spitsyn, V.I.; Fedoseev, G.K.

1976-01-01

The syste86 Ta-Ta 2 C has beemonsidered because of specific features of diffraction patterns of the components, namely, overlapping of the most intensive reflexes of both phases. The method of standard binary system has been used for quantitative analysis. Because of overlapping of the intensive reflexes dsub(1/01)=2.36(Ta 2 C) and dsub(110)=2.33(Ta), the other, most intensive, reflexes have been used for quantitative determination of Ta 2 C and Ta: dsub(103)=1.404 A for tantalum subcarbide and dsub(211)=1.35A for tantalum. Besides, the TaTa 2 C phases have been determined quantitatively with the use of another pair of reflexes: dsub(102)=1.82 A for Ta 2 C and dsub(200)=1.65 A for tantalum. The agreement between the results obtained while performing the quantitative phase analysis is good. To increase reliability and accuracy of the quantitative determination of Ta and Ta 2 C, it is expedient to carry out the analysis with the use of two above-mentioned pairs of reflexes located in different regions of the diffraction spectrum. Thus, the procedure of quantitative analysis of Ta and Ta 2 C in different ratios has been developed taking into account the specific features of the diffraction patterns of these components as well as the ability of Ta 2 C to texture in the process of preparation

A genetic epidemiological mega analysis of smoking initiation in adolescents

NARCIS (Netherlands)

Maes, H.H.; Prom-Wormley, E.; Eaves, L.J.; Rhee, S.H.; Hewitt, J.K.; Young, S.; Corley, R.; McGue, M.K.; Iacono, W.G.; Legrand, L.; Samek, D.; Murrelle, E.L.; Silberg, J.L.; Miles, D.; Schieken, R.M.; Beunen, G.P.; Thomis, M.; Rose, R.J.; Dick, D.M.; Boomsma, D.I.; Bartels, M.; Vink, J.M.; Lichtenstein, P.; White, V.; Kaprio, J.; Neale, M.C.

2017-01-01

Introduction. Previous studies in adolescents were not adequately powered to accurately disentangle genetic and environmental influences on smoking initiation across adolescence. Methods. Mega-analysis of pooled genetically informative data on smoking initiation was performed, with structural

A Quantitative Analysis of the Behavioral Checklist of the Movement ABC Motor Test

Science.gov (United States)

Ruiz, Luis Miguel; Gomez, Marta; Graupera, Jose Luis; Gutierrez, Melchor; Linaza, Jose Luis

2007-01-01

The fifth section of the Henderson and Sugden's Movement ABC Checklist is part of the general Checklist that accompanies The Movement ABC Battery. The authors maintain that the analysis of this section must be mainly qualitative instead of quantitative. The main objective of this study was to employ a quantitative analysis of this behavioural…

Quantitative assessment of in-solution digestion efficiency identifies optimal protocols for unbiased protein analysis

DEFF Research Database (Denmark)

Leon, Ileana R; Schwämmle, Veit; Jensen, Ole N

2013-01-01

a combination of qualitative and quantitative LC-MS/MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein...... conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents prior to analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative LC-MS/MS workflow quantified over 3700 distinct peptides with 96% completeness between all...... protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows...

Chemical Fingerprint Analysis and Quantitative Analysis of Rosa rugosa by UPLC-DAD

Directory of Open Access Journals (Sweden)

Sanawar Mansur

2016-12-01

Full Text Available A method based on ultra performance liquid chromatography with a diode array detector (UPLC-DAD was developed for quantitative analysis of five active compounds and chemical fingerprint analysis of Rosa rugosa. Ten batches of R. rugosa collected from different plantations in the Xinjiang region of China were used to establish the fingerprint. The feasibility and advantages of the used UPLC fingerprint were verified for its similarity evaluation by systematically comparing chromatograms with professional analytical software recommended by State Food and Drug Administration (SFDA of China. In quantitative analysis, the five compounds showed good regression (R2 = 0.9995 within the test ranges, and the recovery of the method was in the range of 94.2%–103.8%. The similarities of liquid chromatography fingerprints of 10 batches of R. rugosa were more than 0.981. The developed UPLC fingerprint method is simple, reliable, and validated for the quality control and identification of R. rugosa. Additionally, simultaneous quantification of five major bioactive ingredients in the R. rugosa samples was conducted to interpret the consistency of the quality test. The results indicated that the UPLC fingerprint, as a characteristic distinguishing method combining similarity evaluation and quantification analysis, can be successfully used to assess the quality and to identify the authenticity of R. rugosa.

Phase analysis in duplex stainless steel: comparison of EBSD and quantitative metallography methods

International Nuclear Information System (INIS)

Michalska, J; Chmiela, B

2014-01-01

The purpose of the research was to work out the qualitative and quantitative analysis of phases in DSS in as-received state and after thermal aging. For quantitative purposes, SEM observations, EDS analyses and electron backscattered diffraction (EBSD) methods were employed. Qualitative analysis of phases was performed by two methods: EBSD and classical quantitative metallography. A juxtaposition of different etchants for the revealing of microstructure and brief review of sample preparation methods for EBSD studies were presented. Different ways of sample preparation were tested and based on these results a detailed methodology of DSS phase analysis was developed including: surface finishing, selective etching methods and image acquisition. The advantages and disadvantages of applied methods were pointed out and compared the accuracy of the analysis phase performed by both methods

Comparative study of standard space and real space analysis of quantitative MR brain data.

Science.gov (United States)

Aribisala, Benjamin S; He, Jiabao; Blamire, Andrew M

2011-06-01

To compare the robustness of region of interest (ROI) analysis of magnetic resonance imaging (MRI) brain data in real space with analysis in standard space and to test the hypothesis that standard space image analysis introduces more partial volume effect errors compared to analysis of the same dataset in real space. Twenty healthy adults with no history or evidence of neurological diseases were recruited; high-resolution T(1)-weighted, quantitative T(1), and B(0) field-map measurements were collected. Algorithms were implemented to perform analysis in real and standard space and used to apply a simple standard ROI template to quantitative T(1) datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared. Regional mean T(1) values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T(1) histograms were more compact in real space, with smaller right-sided tails indicating lower partial volume errors compared to standard space analysis. Standard space analysis of quantitative MRI brain data introduces more partial volume effect errors biasing the analysis of quantitative data compared to analysis of the same dataset in real space. Copyright © 2011 Wiley-Liss, Inc.

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection

OpenAIRE

Kwan, Johnny S. H.; Kung, Annie W. C.; Sham, Pak C.

2011-01-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias. © The Author(s) 2011.

Statistical shape analysis using 3D Poisson equation--A quantitatively validated approach.

Science.gov (United States)

Gao, Yi; Bouix, Sylvain

2016-05-01

Statistical shape analysis has been an important area of research with applications in biology, anatomy, neuroscience, agriculture, paleontology, etc. Unfortunately, the proposed methods are rarely quantitatively evaluated, and as shown in recent studies, when they are evaluated, significant discrepancies exist in their outputs. In this work, we concentrate on the problem of finding the consistent location of deformation between two population of shapes. We propose a new shape analysis algorithm along with a framework to perform a quantitative evaluation of its performance. Specifically, the algorithm constructs a Signed Poisson Map (SPoM) by solving two Poisson equations on the volumetric shapes of arbitrary topology, and statistical analysis is then carried out on the SPoMs. The method is quantitatively evaluated on synthetic shapes and applied on real shape data sets in brain structures. Copyright © 2016 Elsevier B.V. All rights reserved.

Genetic analysis of Myanmar Vigna species in responses to salt ...

African Journals Online (AJOL)

Genetic analysis of Myanmar Vigna species in responses to salt stress at the ... of reduction was highly dependent on different genotypes and salinity levels. ... the mechanism of salt tolerance and for the provision of genetic resources for ...

How to measure genetic heterogeneity

International Nuclear Information System (INIS)

Yamada, Ryo

2009-01-01

Genetic information of organisms is coded as a string of four letters, A, T, G and C, a sequence in macromolecules called deoxyribonucleic acid (DNA). DNA sequence offers blueprint of organisms and its heterogeneity determines identity and variation of species. The quantitation of this genetic heterogeneity is fundamental to understand biology. We compared previously-reported three measures, covariance matrix expression of list of loci (pair-wise r 2 ), the most popular index in genetics, and its multi-dimensional form, Ψ, and entropy-based index, ε. Thereafter we proposed two methods so that we could handle the diplotypic heterogeneity and quantitate the conditions where the number of DNA sequence samples is much smaller than the number of possible variants.

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

Science.gov (United States)

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

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

Directory of Open Access Journals (Sweden)

Sheina B. Sim

2017-06-01

Full Text Available Genetic sexing strains (GSS used in sterile insect technique (SIT programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp, also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera.

Quantitative analysis of background parenchymal enhancement in whole breast on MRI: Influence of menstrual cycle and comparison with a qualitative analysis.

Science.gov (United States)

Jung, Yongsik; Jeong, Seong Kyun; Kang, Doo Kyoung; Moon, Yeorae; Kim, Tae Hee

2018-06-01

We quantitatively analyzed background parenchymal enhancement (BPE) in whole breast according to menstrual cycle and compared it with a qualitative analysis method. A data set of breast magnetic resonance imaging (MRI) from 273 breast cancer patients was used. For quantitative analysis, we used semiautomated in-house software with MATLAB. From each voxel of whole breast, the software calculated BPE using following equation: [(signal intensity [SI] at 1 min 30 s after contrast injection - baseline SI)/baseline SI] × 100%. In total, 53 patients had minimal, 108 mild, 87 moderate, and 25 marked BPE. On quantitative analysis, mean BPE values were 33.1% in the minimal, 42.1% in the mild, 59.1% in the moderate, and 81.9% in the marked BPE group showing significant difference (p = .009 for minimal vs. mild, p quantitative BPE (r = 0.63, p Quantitative analysis of BPE correlated well with the qualitative BPE grade. Quantitative BPE values were lowest in the second week and highest in the fourth week. Copyright © 2018 Elsevier B.V. All rights reserved.

Genetic analysis for grain quality traits in pakistani wheat varieties

International Nuclear Information System (INIS)

Minhas, N.M.; Ajmal, S.U.; Iqbal, Z.; Munir, M.

2014-01-01

A set of eight parental diallel involving seven commercial wheat cultivars and one breeding line was made to investigate the nature of gene action determining inheritance pattern of grain quality characters. Highly significant differences were observed among the genotypes for 1000 grain weight, protein content, wet gluten and lysine content. Adequacy tests were employed to estimate the fitness of data sets to additive dominance model. Both the tests i.e. analysis of uniformity of Wr, Vr and joint regression analysis validated the data of these traits for genetic analysis. Gene actions for grain quality traits were ascertained following Hayman's analysis of variance. Results of the genetic analysis revealed that both additive and dominance genetic components were involved in the manifestation of characters under study. However, additive gene effects were more pronounced in the genetic control of these traits. Non significance of b1, b2 and b3 values revealed the absence of directional dominance, symmetrical distribution of genes among the parental lines and absence of specific genes action respectively in all the traits. Maternal effects were also noted in 1000 grain weight, protein content and wet gluten percentage. It is concluded that additive effects are crucial in the expression of grain quality characters of wheat in germplasm under study and single plant selection may be recommended in segregating generations for effective improvement in these characters. (author)

Genetic analysis of recombinant inbred lines for Sorghum bicolor × Sorghum propinquum.

Science.gov (United States)

Kong, Wenqian; Jin, Huizhe; Franks, Cleve D; Kim, Changsoo; Bandopadhyay, Rajib; Rana, Mukesh K; Auckland, Susan A; Goff, Valorie H; Rainville, Lisa K; Burow, Gloria B; Woodfin, Charles; Burke, John J; Paterson, Andrew H

2013-01-01

We describe a recombinant inbred line (RIL) population of 161 F5 genotypes for the widest euploid cross that can be made to cultivated sorghum (Sorghum bicolor) using conventional techniques, S. bicolor × Sorghum propinquum, that segregates for many traits related to plant architecture, growth and development, reproduction, and life history. The genetic map of the S. bicolor × S. propinquum RILs contains 141 loci on 10 linkage groups collectively spanning 773.1 cM. Although the genetic map has DNA marker density well-suited to quantitative trait loci mapping and samples most of the genome, our previous observations that sorghum pericentromeric heterochromatin is recalcitrant to recombination is highlighted by the finding that the vast majority of recombination in sorghum is concentrated in small regions of euchromatin that are distal to most chromosomes. The advancement of the RIL population in an environment to which the S. bicolor parent was well adapted (indeed bred for) but the S. propinquum parent was not largely eliminated an allele for short-day flowering that confounded many other traits, for example, permitting us to map new quantitative trait loci for flowering that previously eluded detection. Additional recombination that has accrued in the development of this RIL population also may have improved resolution of apices of heterozygote excess, accounting for their greater abundance in the F5 than the F2 generation. The S. bicolor × S. propinquum RIL population offers advantages over early-generation populations that will shed new light on genetic, environmental, and physiological/biochemical factors that regulate plant growth and development.

Towards quantitative laser-induced breakdown spectroscopy analysis of soil samples

International Nuclear Information System (INIS)

Bousquet, B.; Sirven, J.-B.; Canioni, L.

2007-01-01

A quantitative analysis of chromium in soil samples is presented. Different emission lines related to chromium are studied in order to select the best one for quantitative features. Important matrix effects are demonstrated from one soil to the other, preventing any prediction of concentration in different soils on the basis of a univariate calibration curve. Finally, a classification of the LIBS data based on a series of Principal Component Analyses (PCA) is applied to a reduced dataset of selected spectral lines related to the major chemical elements in the soils. LIBS data of heterogeneous soils appear to be widely dispersed, which leads to a reconsideration of the sampling step in the analysis process

Quantitative high-resolution genomic analysis of single cancer cells.

Directory of Open Access Journals (Sweden)

Juliane Hannemann

Full Text Available During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

Quantitative risk analysis as a basis for emergency planning

Energy Technology Data Exchange (ETDEWEB)

Yogui, Regiane Tiemi Teruya [Bureau Veritas do Brasil, Rio de Janeiro, RJ (Brazil); Macedo, Eduardo Soares de [Instituto de Pesquisas Tecnologicas (IPT), Sao Paulo, SP (Brazil)

2009-07-01

Several environmental accidents happened in Brazil and in the world during the 70's and 80's. This strongly motivated the preparation for emergencies in the chemical and petrochemical industries. Environmental accidents affect the environment and the communities that are neighbor to the industrial facilities. The present study aims at subsidizing and providing orientation to develop Emergency Planning from the data obtained on Quantitative Risk Analysis, elaborated according to the Technical Standard P4.261/03 from CETESB (Sao Paulo Environmental Agency). It was observed, during the development of the research, that the data generated on these studies need a complementation and a deeper analysis, so that it is possible to use them on the Emergency Plans. The main issues that were analyzed and discussed on this study were the reevaluation of hazard identification for the emergency plans, the consequences and vulnerability analysis for the response planning, the risk communication, and the preparation to respond to the emergencies of the communities exposed to manageable risks. As a result, the study intends to improve the interpretation and use of the data deriving from the Quantitative Risk Analysis to develop the emergency plans. (author)

Quantitative analysis of patient-specific dosimetric IMRT verification

International Nuclear Information System (INIS)

Budgell, G J; Perrin, B A; Mott, J H L; Fairfoul, J; Mackay, R I

2005-01-01

Patient-specific dosimetric verification methods for IMRT treatments are variable, time-consuming and frequently qualitative, preventing evidence-based reduction in the amount of verification performed. This paper addresses some of these issues by applying a quantitative analysis parameter to the dosimetric verification procedure. Film measurements in different planes were acquired for a series of ten IMRT prostate patients, analysed using the quantitative parameter, and compared to determine the most suitable verification plane. Film and ion chamber verification results for 61 patients were analysed to determine long-term accuracy, reproducibility and stability of the planning and delivery system. The reproducibility of the measurement and analysis system was also studied. The results show that verification results are strongly dependent on the plane chosen, with the coronal plane particularly insensitive to delivery error. Unexpectedly, no correlation could be found between the levels of error in different verification planes. Longer term verification results showed consistent patterns which suggest that the amount of patient-specific verification can be safely reduced, provided proper caution is exercised: an evidence-based model for such reduction is proposed. It is concluded that dose/distance to agreement (e.g., 3%/3 mm) should be used as a criterion of acceptability. Quantitative parameters calculated for a given criterion of acceptability should be adopted in conjunction with displays that show where discrepancies occur. Planning and delivery systems which cannot meet the required standards of accuracy, reproducibility and stability to reduce verification will not be accepted by the radiotherapy community

Fluorescent foci quantitation for high-throughput analysis

Directory of Open Access Journals (Sweden)

Elena Ledesma-Fernández

2015-06-01

Full Text Available A number of cellular proteins localize to discrete foci within cells, for example DNA repair proteins, microtubule organizing centers, P bodies or kinetochores. It is often possible to measure the fluorescence emission from tagged proteins within these foci as a surrogate for the concentration of that specific protein. We wished to develop tools that would allow quantitation of fluorescence foci intensities in high-throughput studies. As proof of principle we have examined the kinetochore, a large multi-subunit complex that is critical for the accurate segregation of chromosomes during cell division. Kinetochore perturbations lead to aneuploidy, which is a hallmark of cancer cells. Hence, understanding kinetochore homeostasis and regulation are important for a global understanding of cell division and genome integrity. The 16 budding yeast kinetochores colocalize within the nucleus to form a single focus. Here we have created a set of freely-available tools to allow high-throughput quantitation of kinetochore foci fluorescence. We use this ‘FociQuant’ tool to compare methods of kinetochore quantitation and we show proof of principle that FociQuant can be used to identify changes in kinetochore protein levels in a mutant that affects kinetochore function. This analysis can be applied to any protein that forms discrete foci in cells.

A simple approach to quantitative analysis using three-dimensional spectra based on selected Zernike moments.

Science.gov (United States)

Zhai, Hong Lin; Zhai, Yue Yuan; Li, Pei Zhen; Tian, Yue Li

2013-01-21

A very simple approach to quantitative analysis is proposed based on the technology of digital image processing using three-dimensional (3D) spectra obtained by high-performance liquid chromatography coupled with a diode array detector (HPLC-DAD). As the region-based shape features of a grayscale image, Zernike moments with inherently invariance property were employed to establish the linear quantitative models. This approach was applied to the quantitative analysis of three compounds in mixed samples using 3D HPLC-DAD spectra, and three linear models were obtained, respectively. The correlation coefficients (R(2)) for training and test sets were more than 0.999, and the statistical parameters and strict validation supported the reliability of established models. The analytical results suggest that the Zernike moment selected by stepwise regression can be used in the quantitative analysis of target compounds. Our study provides a new idea for quantitative analysis using 3D spectra, which can be extended to the analysis of other 3D spectra obtained by different methods or instruments.

Single particle transfer for quantitative analysis with total-reflection X-ray fluorescence spectrometry

International Nuclear Information System (INIS)

Esaka, Fumitaka; Esaka, Konomi T.; Magara, Masaaki; Sakurai, Satoshi; Usuda, Shigekazu; Watanabe, Kazuo

2006-01-01

The technique of single particle transfer was applied to quantitative analysis with total-reflection X-ray fluorescence (TXRF) spectrometry. The technique was evaluated by performing quantitative analysis of individual Cu particles with diameters between 3.9 and 13.2 μm. The direct quantitative analysis of the Cu particle transferred onto a Si carrier gave a discrepancy between measured and calculated Cu amounts due to the absorption effects of incident and fluorescent X-rays within the particle. By the correction for the absorption effects, the Cu amounts in individual particles could be determined with the deviation within 10.5%. When the Cu particles were dissolved with HNO 3 solution prior to the TXRF analysis, the deviation was improved to be within 3.8%. In this case, no correction for the absorption effects was needed for quantification

Variable-number-of-tandem-repeats analysis of genetic diversity in Pasteuria ramosa.

Science.gov (United States)

Mouton, L; Ebert, D

2008-05-01

Variable-number-of-tandem-repeats (VNTR) markers are increasingly being used in population genetic studies of bacteria. They were recently developed for Pasteuria ramosa, an endobacterium that infects Daphnia species. In the present study, we genotyped P. ramosa in 18 infected hosts from the United Kingdom, Belgium, and two lakes in the United States using seven VNTR markers. Two Daphnia species were collected: D. magna and D. dentifera. Six loci showed length polymorphism, with as many as five alleles identified for a single locus. Similarity coefficient calculations showed that the extent of genetic variation between pairs of isolates within populations differed according to the population, but it was always less than the genetic distances among populations. Analysis of the genetic distances performed using principal component analysis revealed strong clustering by location of origin, but not by host Daphnia species. Our study demonstrated that the VNTR markers available for P. ramosa are informative in revealing genetic differences within and among populations and may therefore become an important tool for providing detailed analysis of population genetics and epidemiology.

A roadmap for the genetic analysis of renal aging.

Science.gov (United States)

Noordmans, Gerda A; Hillebrands, Jan-Luuk; van Goor, Harry; Korstanje, Ron

2015-10-01

Several studies show evidence for the genetic basis of renal disease, which renders some individuals more prone than others to accelerated renal aging. Studying the genetics of renal aging can help us to identify genes involved in this process and to unravel the underlying pathways. First, this opinion article will give an overview of the phenotypes that can be observed in age-related kidney disease. Accurate phenotyping is essential in performing genetic analysis. For kidney aging, this could include both functional and structural changes. Subsequently, this article reviews the studies that report on candidate genes associated with renal aging in humans and mice. Several loci or candidate genes have been found associated with kidney disease, but identification of the specific genetic variants involved has proven to be difficult. CUBN, UMOD, and SHROOM3 were identified by human GWAS as being associated with albuminuria, kidney function, and chronic kidney disease (CKD). These are promising examples of genes that could be involved in renal aging, and were further mechanistically evaluated in animal models. Eventually, we will provide approaches for performing genetic analysis. We should leverage the power of mouse models, as testing in humans is limited. Mouse and other animal models can be used to explain the underlying biological mechanisms of genes and loci identified by human GWAS. Furthermore, mouse models can be used to identify genetic variants associated with age-associated histological changes, of which Far2, Wisp2, and Esrrg are examples. A new outbred mouse population with high genetic diversity will facilitate the identification of genes associated with renal aging by enabling high-resolution genetic mapping while also allowing the control of environmental factors, and by enabling access to renal tissues at specific time points for histology, proteomics, and gene expression. © 2015 The Authors. Aging Cell published by the Anatomical Society and John

A roadmap for the genetic analysis of renal aging

Science.gov (United States)

Noordmans, Gerda A; Hillebrands, Jan-Luuk; van Goor, Harry; Korstanje, Ron

2015-01-01

Several studies show evidence for the genetic basis of renal disease, which renders some individuals more prone than others to accelerated renal aging. Studying the genetics of renal aging can help us to identify genes involved in this process and to unravel the underlying pathways. First, this opinion article will give an overview of the phenotypes that can be observed in age-related kidney disease. Accurate phenotyping is essential in performing genetic analysis. For kidney aging, this could include both functional and structural changes. Subsequently, this article reviews the studies that report on candidate genes associated with renal aging in humans and mice. Several loci or candidate genes have been found associated with kidney disease, but identification of the specific genetic variants involved has proven to be difficult. CUBN, UMOD, and SHROOM3 were identified by human GWAS as being associated with albuminuria, kidney function, and chronic kidney disease (CKD). These are promising examples of genes that could be involved in renal aging, and were further mechanistically evaluated in animal models. Eventually, we will provide approaches for performing genetic analysis. We should leverage the power of mouse models, as testing in humans is limited. Mouse and other animal models can be used to explain the underlying biological mechanisms of genes and loci identified by human GWAS. Furthermore, mouse models can be used to identify genetic variants associated with age-associated histological changes, of which Far2, Wisp2, and Esrrg are examples. A new outbred mouse population with high genetic diversity will facilitate the identification of genes associated with renal aging by enabling high-resolution genetic mapping while also allowing the control of environmental factors, and by enabling access to renal tissues at specific time points for histology, proteomics, and gene expression. PMID:26219736

Quantitative analysis of thallium-201 myocardial scintigraphy

International Nuclear Information System (INIS)

Kanemoto, Nariaki; Hoer, G.; Johost, S.; Maul, F.-D.; Standke, R.

1981-01-01

The method of quantitative analysis of thallium-201 myocardial scintigraphy using computer assisted technique was described. Calculated indices are washout factor, vitality index and redistribution factor. Washout factor is the ratio of counts at certain period of time after exercise and immediately after exercise. This value is neccessary for the evaluation of redistribution to the ischemic areas in serial imagings to correct the Tl-201 washout from the myocardium under the assumption that the washout is constant in the whole myocardium. Vitality index is the ratio between the Tl-201 uptake in the region of interest and that of the maximum. Redistribution factor is the ratio of the redistribution in the region of interest in serial imagings after exercise to that of immediately after exercise. Four examples of exercise Tl-201 myocardial scintigrams and the quantitative analyses before and after the percutaneous transluminal coronary angioplasty were presented. (author)

Isolation and genetic analysis of pure cells from forensic biological mixtures: The precision of a digital approach.

Science.gov (United States)

Fontana, F; Rapone, C; Bregola, G; Aversa, R; de Meo, A; Signorini, G; Sergio, M; Ferrarini, A; Lanzellotto, R; Medoro, G; Giorgini, G; Manaresi, N; Berti, A

2017-07-01

Latest genotyping technologies allow to achieve a reliable genetic profile for the offender identification even from extremely minute biological evidence. The ultimate challenge occurs when genetic profiles need to be retrieved from a mixture, which is composed of biological material from two or more individuals. In this case, DNA profiling will often result in a complex genetic profile, which is then subject matter for statistical analysis. In principle, when more individuals contribute to a mixture with different biological fluids, their single genetic profiles can be obtained by separating the distinct cell types (e.g. epithelial cells, blood cells, sperm), prior to genotyping. Different approaches have been investigated for this purpose, such as fluorescent-activated cell sorting (FACS) or laser capture microdissection (LCM), but currently none of these methods can guarantee the complete separation of different type of cells present in a mixture. In other fields of application, such as oncology, DEPArray™ technology, an image-based, microfluidic digital sorter, has been widely proven to enable the separation of pure cells, with single-cell precision. This study investigates the applicability of DEPArray™ technology to forensic samples analysis, focusing on the resolution of the forensic mixture problem. For the first time, we report here the development of an application-specific DEPArray™ workflow enabling the detection and recovery of pure homogeneous cell pools from simulated blood/saliva and semen/saliva mixtures, providing full genetic match with genetic profiles of corresponding donors. In addition, we assess the performance of standard forensic methods for DNA quantitation and genotyping on low-count, DEPArray™-isolated cells, showing that pure, almost complete profiles can be obtained from as few as ten haploid cells. Finally, we explore the applicability in real casework samples, demonstrating that the described approach provides complete

Universal platform for quantitative analysis of DNA transposition

Directory of Open Access Journals (Sweden)

Pajunen Maria I

2010-11-01

Full Text Available Abstract Background Completed genome projects have revealed an astonishing diversity of transposable genetic elements, implying the existence of novel element families yet to be discovered from diverse life forms. Concurrently, several better understood transposon systems have been exploited as efficient tools in molecular biology and genomics applications. Characterization of new mobile elements and improvement of the existing transposition technology platforms warrant easy-to-use assays for the quantitative analysis of DNA transposition. Results Here we developed a universal in vivo platform for the analysis of transposition frequency with class II mobile elements, i.e., DNA transposons. For each particular transposon system, cloning of the transposon ends and the cognate transposase gene, in three consecutive steps, generates a multifunctional plasmid, which drives inducible expression of the transposase gene and includes a mobilisable lacZ-containing reporter transposon. The assay scores transposition events as blue microcolonies, papillae, growing within otherwise whitish Escherichia coli colonies on indicator plates. We developed the assay using phage Mu transposition as a test model and validated the platform using various MuA transposase mutants. For further validation and to illustrate universality, we introduced IS903 transposition system components into the assay. The developed assay is adjustable to a desired level of initial transposition via the control of a plasmid-borne E. coli arabinose promoter. In practice, the transposition frequency is modulated by varying the concentration of arabinose or glucose in the growth medium. We show that variable levels of transpositional activity can be analysed, thus enabling straightforward screens for hyper- or hypoactive transposase mutants, regardless of the original wild-type activity level. Conclusions The established universal papillation assay platform should be widely applicable to a

The quantitative basis of the Arabidopsis innate immune system to endemic pathogens depends on pathogen genetics

DEFF Research Database (Denmark)

Corwin, Jason A; Copeland, Daniel; Feusier, Julie

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 Arabido......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....... 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...... 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...

Genetic mapping of quantitative trait loci (QTLs) with effects on ...

African Journals Online (AJOL)

SERVER

2008-02-05

Feb 5, 2008 ... This paper reports on the development of a genetic ... RILs along with the two parental lines were evaluated in the screen- .... A genetic linkage map of cowpea showing the QTLs (in green) that is associated with the resistance.

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq.

Science.gov (United States)

Wang, Jun; Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

Polyglot programming in applications used for genetic data analysis.

Science.gov (United States)

Nowak, Robert M

2014-01-01

Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development.

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update.

Science.gov (United States)

Peakall, Rod; Smouse, Peter E

2012-10-01

GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G'(ST), G''(ST), Jost's D(est) and F'(ST) through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. rod.peakall@anu.edu.au.

Pitfalls in genetic analysis of pheochromocytomas/paragangliomas-case report.

Science.gov (United States)

Canu, Letizia; Rapizzi, Elena; Zampetti, Benedetta; Fucci, Rossella; Nesi, Gabriella; Richter, Susan; Qin, Nan; Giachè, Valentino; Bergamini, Carlo; Parenti, Gabriele; Valeri, Andrea; Ercolino, Tonino; Eisenhofer, Graeme; Mannelli, Massimo

2014-07-01

About 35% of patients with pheochromocytoma/paraganglioma carry a germline mutation in one of the 10 main susceptibility genes. The recent introduction of next-generation sequencing will allow the analysis of all these genes in one run. When positive, the analysis is generally unequivocal due to the association between a germline mutation and a concordant clinical presentation or positive family history. When genetic analysis reveals a novel mutation with no clinical correlates, particularly in the presence of a missense variant, the question arises whether the mutation is pathogenic or a rare polymorphism. We report the case of a 35-year-old patient operated for a pheochromocytoma who turned out to be a carrier of a novel SDHD (succinate dehydrogenase subunit D) missense mutation. With no positive family history or clinical correlates, we decided to perform additional analyses to test the clinical significance of the mutation. We performed in silico analysis, tissue loss of heterozygosity analysis, immunohistochemistry, Western blot analysis, SDH enzymatic assay, and measurement of the succinate/fumarate concentration ratio in the tumor tissue by tandem mass spectrometry. Although the in silico analysis gave contradictory results according to the different methods, all the other tests demonstrated that the SDH complex was conserved and normally active. We therefore came to the conclusion that the variant was a nonpathogenic polymorphism. Advancements in technology facilitate genetic analysis of patients with pheochromocytoma but also offer new challenges to the clinician who, in some cases, needs clinical correlates and/or functional tests to give significance to the results of the genetic assay.

Quantitative pulsed eddy current analysis

International Nuclear Information System (INIS)

Morris, R.A.

1975-01-01

The potential of pulsed eddy current testing for furnishing more information than conventional single-frequency eddy current methods has been known for some time. However, a fundamental problem has been analyzing the pulse shape with sufficient precision to produce accurate quantitative results. Accordingly, the primary goal of this investigation was to: demonstrate ways of digitizing the short pulses encountered in PEC testing, and to develop empirical analysis techniques that would predict some of the parameters (e.g., depth) of simple types of defect. This report describes a digitizing technique using a computer and either a conventional nuclear ADC or a fast transient analyzer; the computer software used to collect and analyze pulses; and some of the results obtained. (U.S.)

Quantitative surface analysis using deuteron-induced nuclear reactions

International Nuclear Information System (INIS)

Afarideh, Hossein

1991-01-01

The nuclear reaction analysis (NRA) technique consists of looking at the energies of the reaction products which uniquely define the particular elements present in the sample and it analysis the yield/energy distribution to reveal depth profiles. A summary of the basic features of the nuclear reaction analysis technique is given, in particular emphasis is placed on quantitative light element determination using (d,p) and (d,alpha) reactions. The experimental apparatus is also described. Finally a set of (d,p) spectra for the elements Z=3 to Z=17 using 2 MeV incident deutrons is included together with example of more applications of the (d,alpha) spectra. (author)

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

Science.gov (United States)

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.

Genetic diversity analysis of common beans based on molecular markers

Directory of Open Access Journals (Sweden)

Homar R. Gill-Langarica

2011-01-01

Full Text Available A core collection of the common bean (Phaseolus vulgaris L., representing genetic diversity in the entire Mexican holding, is kept at the INIFAP (Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias, Mexico Germplasm Bank. After evaluation, the genetic structure of this collection (200 accessions was compared with that of landraces from the states of Oaxaca, Chiapas and Veracruz (10 genotypes from each, as well as a further 10 cultivars, by means of four amplified fragment length polymorphisms (AFLP +3/+3 primer combinations and seven simple sequence repeats (SSR loci, in order to define genetic diversity, variability and mutual relationships. Data underwent cluster (UPGMA and molecular variance (AMOVA analyses. AFLP analysis produced 530 bands (88.5% polymorphic while SSR primers amplified 174 alleles, all polymorphic (8.2 alleles per locus. AFLP indicated that the highest genetic diversity was to be found in ten commercial-seed classes from two major groups of accessions from Central Mexico and Chiapas, which seems to be an important center of diversity in the south. A third group included genotypes from Nueva Granada, Mesoamerica, Jalisco and Durango races. Here, SSR analysis indicated a reduced number of shared haplotypes among accessions, whereas the highest genetic components of AMOVA variation were found within accessions. Genetic diversity observed in the common-bean core collection represents an important sample of the total Phaseolus genetic variability at the main Germplasm Bank of INIFAP. Molecular marker strategies could contribute to a better understanding of the genetic structure of the core collection as well as to its improvement and validation.

Genetic diversity analysis of common beans based on molecular markers

Directory of Open Access Journals (Sweden)

Homar R. Gill-Langarica

Full Text Available A core collection of the common bean (Phaseolus vulgaris L., representing genetic diversity in the entire Mexican holding, is kept at the INIFAP (Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias, Mexico Germplasm Bank. After evaluation, the genetic structure of this collection (200 accessions was compared with that of landraces from the states of Oaxaca, Chiapas and Veracruz (10 genotypes from each, as well as a further 10 cultivars, by means of four amplified fragment length polymorphisms (AFLP +3/+3 primer combinations and seven simple sequence repeats (SSR loci, in order to define genetic diversity, variability and mutual relationships. Data underwent cluster (UPGMA and molecular variance (AMOVA analyses. AFLP analysis produced 530 bands (88.5% polymorphic while SSR primers amplified 174 alleles, all polymorphic (8.2 alleles per locus. AFLP indicated that the highest genetic diversity was to be found in ten commercial-seed classes from two major groups of accessions from Central Mexico and Chiapas, which seems to be an important center of diversity in the south. A third group included genotypes from Nueva Granada, Mesoamerica, Jalisco and Durango races. Here, SSR analysis indicated a reduced number of shared haplotypes among accessions, whereas the highest genetic components of AMOVA variation were found within accessions. Genetic diversity observed in the common-bean core collection represents an important sample of the total Phaseolus genetic variability at the main Germplasm Bank of INIFAP. Molecular marker strategies could contribute to a better understanding of the genetic structure of the core collection as well as to its improvement and validation.

Genetic diversity analysis of common beans based on molecular markers.

Science.gov (United States)

Gill-Langarica, Homar R; Muruaga-Martínez, José S; Vargas-Vázquez, M L Patricia; Rosales-Serna, Rigoberto; Mayek-Pérez, Netzahualcoyotl

2011-10-01

A core collection of the common bean (Phaseolus vulgaris L.), representing genetic diversity in the entire Mexican holding, is kept at the INIFAP (Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias, Mexico) Germplasm Bank. After evaluation, the genetic structure of this collection (200 accessions) was compared with that of landraces from the states of Oaxaca, Chiapas and Veracruz (10 genotypes from each), as well as a further 10 cultivars, by means of four amplified fragment length polymorphisms (AFLP) +3/+3 primer combinations and seven simple sequence repeats (SSR) loci, in order to define genetic diversity, variability and mutual relationships. Data underwent cluster (UPGMA) and molecular variance (AMOVA) analyses. AFLP analysis produced 530 bands (88.5% polymorphic) while SSR primers amplified 174 alleles, all polymorphic (8.2 alleles per locus). AFLP indicated that the highest genetic diversity was to be found in ten commercial-seed classes from two major groups of accessions from Central Mexico and Chiapas, which seems to be an important center of diversity in the south. A third group included genotypes from Nueva Granada, Mesoamerica, Jalisco and Durango races. Here, SSR analysis indicated a reduced number of shared haplotypes among accessions, whereas the highest genetic components of AMOVA variation were found within accessions. Genetic diversity observed in the common-bean core collection represents an important sample of the total Phaseolus genetic variability at the main Germplasm Bank of INIFAP. Molecular marker strategies could contribute to a better understanding of the genetic structure of the core collection as well as to its improvement and validation.

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

Science.gov (United States)

Hill, William G

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

Evaluation of shear wave elastography for differential diagnosis of breast lesions: A new qualitative analysis versus conventional quantitative analysis.

Science.gov (United States)

Ren, Wei-Wei; Li, Xiao-Long; Wang, Dan; Liu, Bo-Ji; Zhao, Chong-Ke; Xu, Hui-Xiong

2018-04-13

To evaluate a special kind of ultrasound (US) shear wave elastography for differential diagnosis of breast lesions, using a new qualitative analysis (i.e. the elasticity score in the travel time map) compared with conventional quantitative analysis. From June 2014 to July 2015, 266 pathologically proven breast lesions were enrolled in this study. The maximum, mean, median, minimum, and standard deviation of shear wave speed (SWS) values (m/s) were assessed. The elasticity score, a new qualitative feature, was evaluated in the travel time map. The area under the receiver operating characteristic (AUROC) curves were plotted to evaluate the diagnostic performance of both qualitative and quantitative analyses for differentiation of breast lesions. Among all quantitative parameters, SWS-max showed the highest AUROC (0.805; 95% CI: 0.752, 0.851) compared with SWS-mean (0.786; 95% CI:0.732, 0.834; P = 0.094), SWS-median (0.775; 95% CI:0.720, 0.824; P = 0.046), SWS-min (0.675; 95% CI:0.615, 0.731; P = 0.000), and SWS-SD (0.768; 95% CI:0.712, 0.817; P = 0.074). The AUROC of qualitative analysis in this study obtained the best diagnostic performance (0.871; 95% CI: 0.825, 0.909, compared with the best parameter of SWS-max in quantitative analysis, P = 0.011). The new qualitative analysis of shear wave travel time showed the superior diagnostic performance in the differentiation of breast lesions in comparison with conventional quantitative analysis.

A genetic analysis of Trichuris trichiura and Trichuris suis from Ecuador.

Science.gov (United States)

Meekums, Hayley; Hawash, Mohamed B F; Sparks, Alexandra M; Oviedo, Yisela; Sandoval, Carlos; Chico, Martha E; Stothard, J Russell; Cooper, Philip J; Nejsum, Peter; Betson, Martha

2015-03-19

Since the nematodes Trichuris trichiura and T. suis are morphologically indistinguishable, genetic analysis is required to assess epidemiological cross-over between people and pigs. This study aimed to clarify the transmission biology of trichuriasis in Ecuador. Adult Trichuris worms were collected during a parasitological survey of 132 people and 46 pigs in Esmeraldas Province, Ecuador. Morphometric analysis of 49 pig worms and 64 human worms revealed significant variation. In discriminant analysis morphometric characteristics correctly classified male worms according to host species. In PCR-RFLP analysis of the ribosomal Internal Transcribed Spacer (ITS-2) and 18S DNA (59 pig worms and 82 human worms), nearly all Trichuris exhibited expected restriction patterns. However, two pig-derived worms showed a "heterozygous-type" ITS-2 pattern, with one also having a "heterozygous-type" 18S pattern. Phylogenetic analysis of the mitochondrial large ribosomal subunit partitioned worms by host species. Notably, some Ecuadorian T. suis clustered with porcine Trichuris from USA and Denmark and some with Chinese T. suis. This is the first study in Latin America to genetically analyse Trichuris parasites. Although T. trichiura does not appear to be zoonotic in Ecuador, there is evidence of genetic exchange between T. trichiura and T. suis warranting more detailed genetic sampling.

A novel structure-aware sparse learning algorithm for brain imaging genetics.

Science.gov (United States)

Du, Lei; Jingwen, Yan; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-01-01

Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most existing SCCA algorithms are designed using the soft threshold strategy, which assumes that the features in the data are independent from each other. This independence assumption usually does not hold in imaging genetic data, and thus inevitably limits the capability of yielding optimal solutions. We propose a novel structure-aware SCCA (denoted as S2CCA) algorithm to not only eliminate the independence assumption for the input data, but also incorporate group-like structure in the model. Empirical comparison with a widely used SCCA implementation, on both simulated and real imaging genetic data, demonstrated that S2CCA could yield improved prediction performance and biologically meaningful findings.

A markerless protocol for genetic analysis of Aggregatibacter actinomycetemcomitans

Science.gov (United States)

Cheng, Ya-An; Jee, Jason; Hsu, Genie; Huang, Yanyan; Chen, Casey; Lin, Chun-Pin

2015-01-01

Background/Purpose The genomes of different Aggregatibacter actinomycetemcomitans strains contain many strain-specific genes and genomic islands (defined as DNA found in some but not all strains) of unknown functions. Genetic analysis for the functions of these islands will be constrained by the limited availability of genetic markers and vectors for A. actinomycetemcomitans. In this study we tested a novel genetic approach of gene deletion and restoration in a naturally competent A. actinomycetemcomitans strain D7S-1. Methods Specific genes’ deletion mutants and mutants restored with the deleted genes were constructed by a markerless loxP/Cre system. In mutants with sequential deletion of multiple genes loxP with different spacer regions were used to avoid unwanted recombinations between loxP sites. Results Eight single-gene deletion mutants, four multiple-gene deletion mutants, and two mutants with restored genes were constructed. No unintended non-specific deletion mutants were generated by this protocol. The protocol did not negatively affect the growth and biofilm formation of A. actinomycetemcomitans. Conclusion The protocol described in this study is efficient and specific for genetic manipulation of A. actinomycetemcomitans, and will be amenable for functional analysis of multiple genes in A. actinomycetemcomitans. PMID:24530245

Structural and Temporal Variation in Genetic Diversity of European Spring Two-Row Barley Cultivars and Association Mapping of Quantitative Traits

Directory of Open Access Journals (Sweden)

Alessandro Tondelli

2013-07-01

Full Text Available Two hundred sixteen barley ( L. cultivars were selected to represent the diversity and history of European spring two-row barley breeding and to search for alleles controlling agronomic traits by association genetics. The germplasm was genotyped with 7864 gene-based single nucleotide polymorphism markers and corresponding field trial trait data relating to growth and straw strength were obtained at multiple European sites. Analysis of the marker data by statistical population genetics approaches revealed two important trends in the genetic diversity of European two-row spring barley, namely, i directional selection for approximately 14% of total genetic variation of the population in the last approximately 50 yr and ii highly uneven genomic distribution of genetic diversity. Association analysis of the phenotypic and genotypic data identified multiple loci affecting the traits investigated, some of which co-map with selected regions. Collectively, these data show that the genetic makeup of European two-row spring barley is evolving under breeder selection, with signs of extinction of diversity in some genomic regions, suggesting that “breeding the best with the best” is leading towards fixation of some breeder targets. Nevertheless, modern germplasm also retains many regions of high diversity, suggesting that site-specific genetic approaches for allele identification and crop improvement such as association genetics are likely to be successful.

Endogenous Reference Genes and Their Quantitative Real-Time PCR Assays for Genetically Modified Bread Wheat (Triticum aestivum L.) Detection.

Science.gov (United States)

Yang, Litao; Quan, Sheng; Zhang, Dabing

2017-01-01

Endogenous reference genes (ERG) and their derivate analytical methods are standard requirements for analysis of genetically modified organisms (GMOs). Development and validation of suitable ERGs is the primary step for establishing assays that monitoring the genetically modified (GM) contents in food/feed samples. Herein, we give a review of the ERGs currently used for GM wheat analysis, such as ACC1, PKABA1, ALMT1, and Waxy-D1, as well as their performances in GM wheat analysis. Also, we discussed one model for developing and validating one ideal RG for one plant species based on our previous research work.

Genetic and Physiological Characterization of Two Clusters of Quantitative Trait Loci Associated With Seed Dormancy and Plant Height in Rice

OpenAIRE

Ye, Heng; Beighley, Donn H.; Feng, Jiuhuan; Gu, Xing-You

2013-01-01

Seed dormancy and plant height have been well-studied in plant genetics, but their relatedness and shared regulatory mechanisms in natural variants remain unclear. The introgression of chromosomal segments from weedy into cultivated rice (Oryza sativa) prompted the detection of two clusters (qSD1-2/qPH1 and qSD7-2/qPH7) of quantitative trait loci both associated with seed dormancy and plant height. Together, these two clusters accounted for >96% of the variances for plant height and ~71% of t...

MCM - 2 and Ki - 67 as proliferation markers in renal cell carcinoma: A quantitative and semi - quantitative analysis.

Science.gov (United States)

Mehdi, Muhammad Zain; Nagi, Abdul Hanan; Naseem, Nadia

2016-01-01

Fuhrman nuclear grade is the most important histological parameter to predict prognosis in a patient of renal cell carcinoma (RCC). However, it suffers from inter-observer and intra-observer variation giving rise to need of a parameter that not only correlates with nuclear grade but is also objective and reproducible. Proliferation is the measure of aggressiveness of a tumour and it is strongly correlated with Fuhrman nuclear grade, clinical survival and recurrence in RCC. Ki-67 is conventionally used to assess proliferation. Mini-chromosome maintenance 2 (MCM-2) is a lesser known marker of proliferation and identifies a greater proliferation faction. This study was designed to assess the prognostic significance of MCM-2 by comparing it with Fuhrman nuclear grade and Ki-67. n=50 cases of various ages, stages, histological subtypes and grades of RCC were selected for this study. Immunohistochemical staining using Ki-67(MIB-1, Mouse monoclonal antibody, Dako) and MCM-2 (Mouse monoclonal antibody, Thermo) was performed on the paraffin embedded blocks in the department of Morbid anatomy and Histopathology, University of Health Sciences, Lahore. Labeling indices (LI) were determined by two pathologists independently using quantitative and semi-quantitative analysis. Statistical analysis was carried out using SPSS 20.0. Kruskall-Wallis test was used to determine a correlation of proliferation markers with grade, and Pearson's correlate was used to determine correlation between the two proliferation markers. Labeling index of MCM-2 (median=24.29%) was found to be much higher than Ki-67(median=13.05%). Both markers were significantly related with grade (p=0.00; Kruskall-Wallis test). LI of MCM-2 was found to correlate significantly with LI of Ki-67(r=0.0934;p=0.01 with Pearson's correlate). Results of semi-quantitative analysis correlated well with quantitative analysis. Both Ki-67 and MCM-2 are markers of proliferation which are closely linked to grade. Therefore, they

In vitro propagation of Rauwolfia serpentina using liquid medium, assessment of genetic fidelity of micropropagated plants, and simultaneous quantitation of reserpine, ajmaline, and ajmalicine.

Science.gov (United States)

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).

Quantitative Myocardial Perfusion Imaging Versus Visual Analysis in Diagnosing Myocardial Ischemia: A CE-MARC Substudy.

Science.gov (United States)

Biglands, John D; Ibraheem, Montasir; Magee, Derek R; Radjenovic, Aleksandra; Plein, Sven; Greenwood, John P

2018-05-01

This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography. Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion. This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of >2 mm diameter, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver-operating characteristic curve analysis. The area under the curve for visual analysis was 0.88 (95% confidence interval: 0.81 to 0.95) with a sensitivity of 81.0% (95% confidence interval: 69.1% to 92.8%) and specificity of 86.0% (95% confidence interval: 78.7% to 93.4%). For quantitative stress myocardial blood flow the area under the curve was 0.89 (95% confidence interval: 0.83 to 0.96) with a sensitivity of 87.5% (95% confidence interval: 77.3% to 97.7%) and specificity of 84.5% (95% confidence interval: 76.8% to 92.3%). There was no statistically significant difference between the diagnostic performance of quantitative and visual analyses (p = 0.72). Incorporating rest myocardial

A critical appraisal of semi-quantitative analysis of 2-deoxyglucose autoradiograms

International Nuclear Information System (INIS)

Kelly, P.T.; McCulloch, J.

1983-01-01

Semi-quantitative analysis (e.g. optical density ratios) of [ 14 C]2-deoxyglucose autoradiograms is widely used in neuroscience research. The authors demonstrate that a fixed ratio of 14 C-concentrations in the CNS does not yield a constant optical density ratio but is dependent upon the exposure time in the preparation of the autoradiograms and the absolute amounts of 14 C from which the concentration ratio is derived. The failure of a fixed glucose utilization ratio to result in a constant optical density ratio represents a major interpretative difficulty in investigations where only semi-quantitative analysis of [ 14 C]2-deoxyglucose autoradiograms is undertaken. (Auth.)

Quantitative analysis of culture using millions of digitized books.

Science.gov (United States)

Michel, Jean-Baptiste; Shen, Yuan Kui; Aiden, Aviva Presser; Veres, Adrian; Gray, Matthew K; Pickett, Joseph P; Hoiberg, Dale; Clancy, Dan; Norvig, Peter; Orwant, Jon; Pinker, Steven; Nowak, Martin A; Aiden, Erez Lieberman

2011-01-14

We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of 'culturomics,' focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. Culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities.

Quantitative analysis of culture using millions of digitized books

Science.gov (United States)

Michel, Jean-Baptiste; Shen, Yuan Kui; Aiden, Aviva P.; Veres, Adrian; Gray, Matthew K.; Pickett, Joseph P.; Hoiberg, Dale; Clancy, Dan; Norvig, Peter; Orwant, Jon; Pinker, Steven; Nowak, Martin A.; Aiden, Erez Lieberman

2011-01-01

We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of ‘culturomics’, focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. ‘Culturomics’ extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities. PMID:21163965

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

Science.gov (United States)

Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

2015-01-01

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

A symbiotic liaison between the genetic and epigenetic code

Directory of Open Access Journals (Sweden)

Holger eHeyn

2014-05-01

Full Text Available With rapid advances in sequencing technologies, we are undergoing a paradigm shift from hypothesis- to data-driven research. Genome-wide profiling efforts gave informative insights into biological processes; however, considering the wealth of variation, the major challenge remains their meaningful interpretation. In particular sequence variation in non-coding contexts is often challenging to interpret. Here, data integration approaches for the identification of functional genetic variability represent a likely solution. Exemplary, functional linkage analysis integrating genotype and expression data determined regulatory quantitative trait loci (QTL and proposed causal relationships. In addition to gene expression, epigenetic regulation and specifically DNA methylation was established as highly valuable surrogate mark for functional variance of the genetic code. Epigenetic modification served as powerful mediator trait to elucidate mechanisms forming phenotypes in health and disease. Particularly, integrative studies of genetic and DNA methylation data yet guided interpretation strategies of risk genotypes, but also proved their value for physiological traits, such as natural human variation and aging. This Perspective seeks to illustrate the power of data integration in the genomic era exemplified by DNA methylation quantitative trait loci (meQTLs. However, the model is further extendable to virtually all traceable molecular traits.

Dominant Epistasis Between Two Quantitative Trait Loci Governing Sporulation Efficiency in Yeast Saccharomyces cerevisiae

Science.gov (United States)

Bergman, Juraj; Mitrikeski, Petar T.

2015-01-01

Summary Sporulation efficiency in the yeast Saccharomyces cerevisiae is a well-established model for studying quantitative traits. A variety of genes and nucleotides causing different sporulation efficiencies in laboratory, as well as in wild strains, has already been extensively characterised (mainly by reciprocal hemizygosity analysis and nucleotide exchange methods). We applied a different strategy in order to analyze the variation in sporulation efficiency of laboratory yeast strains. Coupling classical quantitative genetic analysis with simulations of phenotypic distributions (a method we call phenotype modelling) enabled us to obtain a detailed picture of the quantitative trait loci (QTLs) relationships underlying the phenotypic variation of this trait. Using this approach, we were able to uncover a dominant epistatic inheritance of loci governing the phenotype. Moreover, a molecular analysis of known causative quantitative trait genes and nucleotides allowed for the detection of novel alleles, potentially responsible for the observed phenotypic variation. Based on the molecular data, we hypothesise that the observed dominant epistatic relationship could be caused by the interaction of multiple quantitative trait nucleotides distributed across a 60--kb QTL region located on chromosome XIV and the RME1 locus on chromosome VII. Furthermore, we propose a model of molecular pathways which possibly underlie the phenotypic variation of this trait. PMID:27904371

Quantitative analysis of macro-ARG using IP system

International Nuclear Information System (INIS)

Nakajima, Eiichi; Kawai, Kenji; Furuta, Yoshitake

1997-01-01

Recent progress in imaging plate (IP) system allow us to analyze autoradiographic images quantitatively. In the 'whole-body autoradiography', a method clarify the distribution of radioisotope or labeled compounds in the tissues and organs in a freeze-dried whole-body section of small animals such as rats and mice, the sections are pressed against a IP for exposure and the IP is scanned by Bio-Imaging Analyzer (Fuji Photo Film Co., Ltd) and a digital autoradiographic image is given. Quantitative data concerning the activity in different tissues can be obtained using an isotope scale as a reference source. Fading effect, application of IP system for distribution of receptor binding ARG, analysis of radio-spots on TLC and radioactive concentration in liquid such as blood are also discussed. (author)

Potential Application of Quantitative Prostate-specific Antigen Analysis in Forensic Examination of Seminal Stains

Directory of Open Access Journals (Sweden)

Zhenping Liu

2015-01-01

Full Text Available The aims of this study are to use quantitative analysis of the prostate-specific antigen (PSA in the seminal stain examination and to explore the practical value of this analysis in forensic science. For a comprehensive analysis, vaginal swabs from 48 rape cases were tested both by a PSA fluorescence analyzer (i-CHROMA Reader and by a conventional PSA strip test. To confirm the results of these PSA tests, seminal DNA was tested following differential extraction. Compared to the PSA strip test, the PSA rapid quantitative fluorescence analyzer provided the more accurate and sensitive results. More importantly, individualized schemes based on quantitative PSA results of samples can be developed to improve the quality and procedural efficiency in the forensic seminal inspection of samples prior to DNA analysis.

On the Need for Quantitative Bias Analysis in the Peer-Review Process.

Science.gov (United States)

Fox, Matthew P; Lash, Timothy L

2017-05-15

Peer review is central to the process through which epidemiologists generate evidence to inform public health and medical interventions. Reviewers thereby act as critical gatekeepers to high-quality research. They are asked to carefully consider the validity of the proposed work or research findings by paying careful attention to the methodology and critiquing the importance of the insight gained. However, although many have noted problems with the peer-review system for both manuscripts and grant submissions, few solutions have been proposed to improve the process. Quantitative bias analysis encompasses all methods used to quantify the impact of systematic error on estimates of effect in epidemiologic research. Reviewers who insist that quantitative bias analysis be incorporated into the design, conduct, presentation, and interpretation of epidemiologic research could substantially strengthen the process. In the present commentary, we demonstrate how quantitative bias analysis can be used by investigators and authors, reviewers, funding agencies, and editors. By utilizing quantitative bias analysis in the peer-review process, editors can potentially avoid unnecessary rejections, identify key areas for improvement, and improve discussion sections by shifting from speculation on the impact of sources of error to quantification of the impact those sources of bias may have had. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

DMPD: The Toll-like receptors: analysis by forward genetic methods. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 16001129 The Toll-like receptors: analysis by forward genetic methods. Beutler B. I...mmunogenetics. 2005 Jul;57(6):385-92. (.png) (.svg) (.html) (.csml) Show The Toll-like receptors: analysis by forwar...d genetic methods. PubmedID 16001129 Title The Toll-like receptors: analysis by forward genetic meth

A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

Science.gov (United States)

Tucker, George; Loh, Po-Ru; Berger, Bonnie

2013-10-04

Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely

Immune adherence: a quantitative and kinetic analysis

Energy Technology Data Exchange (ETDEWEB)

Sekine, T [National Cancer Center, Tokyo (Japan). Research Inst.

1978-09-01

Quantitative and kinetic analysis of the immune-adherence reaction (IA) between C3b fragments and IA receptors as an agglutination reaction is difficult. Analysis is possible, however, by use of radio-iodinated bovine serum albumin as antigen at low concentrations (less than 200 ng/ml) and optimal concentration of antibody to avoid precipitation of antigen-antibody complexes with human erythrocytes without participation of complement. Antigen and antibody are reacted at 37/sup 0/C, complement is added, the mixture incubated and human erythrocytes added; after further incubation, ice-cold EDTA containing buffer is added and the erythrocytes centrifuged and assayed for radioactivity. Control cells reacted with heated guinea pig serum retained less than 5% of the added radioactivity. The method facilitates measurement of IA reactivity and permits more detailed analysis of the mechanism underlying the reaction.

Quantitative Determination of Aluminum in Deodorant Brands: A Guided Inquiry Learning Experience in Quantitative Analysis Laboratory

Science.gov (United States)

Sedwick, Victoria; Leal, Anne; Turner, Dea; Kanu, A. Bakarr

2018-01-01

The monitoring of metals in commercial products is essential for protecting public health against the hazards of metal toxicity. This article presents a guided inquiry (GI) experimental lab approach in a quantitative analysis lab class that enabled students' to determine the levels of aluminum in deodorant brands. The utility of a GI experimental…

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

Science.gov (United States)

Peakall, Rod; Smouse, Peter E.

2012-01-01

Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s Dest and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. Contact: rod.peakall@anu.edu.au PMID:22820204

Quantitative data analysis with SPSS release 8 for Windows a guide for social scientists

CERN Document Server

Bryman, Alan

2002-01-01

The latest edition of this best-selling introduction to Quantitative Data Analysis through the use of a computer package has been completely updated to accommodate the needs of users of SPSS Release 8 for Windows. Like its predecessor, it provides a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS for Windows. It assumes no previous familiarity with either statistics or computing but takes the reader step-by-step through the techniques, reinforced by exercises for further practice. Techniques explained in Quantitative Data Analysis with SPSS Release 8 for Windows include: * correlation * simple and multiple regression * multivariate analysis of variance and covariance * factor analysis The book also covers issues such as sampling, statistical significance, conceptualization and measurement and the selection of appropriate tests. For further information or to download the book's datasets, please visit the webstite: http://www.routledge.com/textbooks/...

Quantitative analysis on electrooculography (EOG) for neurodegenerative disease

Science.gov (United States)

Liu, Chang-Chia; Chaovalitwongse, W. Art; Pardalos, Panos M.; Seref, Onur; Xanthopoulos, Petros; Sackellares, J. C.; Skidmore, Frank M.

2007-11-01

Many studies have documented abnormal horizontal and vertical eye movements in human neurodegenerative disease as well as during altered states of consciousness (including drowsiness and intoxication) in healthy adults. Eye movement measurement may play an important role measuring the progress of neurodegenerative diseases and state of alertness in healthy individuals. There are several techniques for measuring eye movement, Infrared detection technique (IR). Video-oculography (VOG), Scleral eye coil and EOG. Among those available recording techniques, EOG is a major source for monitoring the abnormal eye movement. In this real-time quantitative analysis study, the methods which can capture the characteristic of the eye movement were proposed to accurately categorize the state of neurodegenerative subjects. The EOG recordings were taken while 5 tested subjects were watching a short (>120 s) animation clip. In response to the animated clip the participants executed a number of eye movements, including vertical smooth pursued (SVP), horizontal smooth pursued (HVP) and random saccades (RS). Detection of abnormalities in ocular movement may improve our diagnosis and understanding a neurodegenerative disease and altered states of consciousness. A standard real-time quantitative analysis will improve detection and provide a better understanding of pathology in these disorders.

Quantitative XPS analysis of high Tc superconductor surfaces

International Nuclear Information System (INIS)

Jablonski, A.; Sanada, N.; Suzuki, Y.; Fukuda, Y.; Nagoshi, M.

1993-01-01

The procedure of quantitative XPS analysis involving the relative sensitivity factors is most convenient to apply to high T c superconductor surfaces because this procedure does not require standards. However, a considerable limitation of such an approach is its relatively low accuracy. In the present work, a proposition is made to use for this purpose a modification of the relative sensitivity factor approach accounting for the matrix and the instrumental effects. The accuracy of this modification when applied to the binary metal alloys is 2% or better. A quantitative XPS analysis was made for surfaces of the compounds Bi 2 Sr 2 CuO 6 , Bi 2 Sr 2 CaCu 2 O 8 , and YBa 2 Cu 3 O Y . The surface composition determined for the polycrystalline samples corresponds reasonably well to the bulk stoichiometry. Slight deficiency of oxygen was found for the Bi-based compounds. The surface exposed on cleavage of the Bi 2 Sr 2 CaCu 2 O 8 single crystal was found to be enriched with bismuth, which indicates that the cleavage occurs along the BiO planes. This result is in agreement with the STM studies published in the literature

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

Science.gov (United States)

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.

EMBO Course “Formal Analysis of Genetic Regulation”

CERN Document Server

1979-01-01

The E M B 0 course on "Formal Analysis of Genetic Regulation" A course entitled "Formal analysis of Genetic Regulation" was held at the University of Brussels from 6 to 16 September 1977 under the auspices of EMBO (European Molecular Biology Organization). As indicated by the title of the book (but not explicitly enough by the title of the course), the main emphasis was put on a dynamic analysis of systems using logical methods, that is, methods in which functions and variables take only a limited number of values - typically two. In this respect, this course was complementary to an EMBO course using continuous methods which was held some months later in Israel by Prof. Segel. People from four very different laboratories took an active part in teaching our course in Brussels : Drs Anne LEUSSLER and Philippe VAN HAM, from the Laboratory of Prof. Jean FLORINE (Laboratoire des Systemes logiques et numeriques, Faculte des Sciences appliquees, Universite Libre de Bruxelles). Dr Stuart KAUFFMAN (Dept. of Biochemist...

Genetic variants of FOXP1 and FOXF1 are associated with the ...

Indian Academy of Sciences (India)

JIE ZHANG

2018-03-01

Mar 1, 2018 ... This study aimed to investigate whether the genetic variants of CRTC1, BARX1, FOXP1 and ... The student's t-test was used to compare FOXP1 expression in the tumour and the adjacent normal tissues. .... Quantitative PCR was carried out ..... Expression (GTEx) pilot analysis: multitissue gene regulation.

Quantitative Analysis of Complex Tropical Forest Stands: A Review ...

African Journals Online (AJOL)

The importance of data analysis in quantitative assessment of natural resources remains significant in the sustainable management of complex tropical forest resources. Analyses of data from complex tropical forest stands have not been easy or clear due to improper data management. It is pivotal to practical researches ...

Phenotypic and molecular genetic analysis of Pyruvate Kinase ...

African Journals Online (AJOL)

Phenotypic and molecular genetic analysis of Pyruvate Kinase deficiency in a Tunisian family. Jaouani Mouna, Hamdi Nadia, Chaouch Leila, Kalai Miniar, Mellouli Fethi, Darragi Imen, Boudriga Imen, Chaouachi Dorra, Bejaoui Mohamed, Abbes Salem ...

Quantitative analysis of eyes and other optical systems in linear optics.

Science.gov (United States)

Harris, William F; Evans, Tanya; van Gool, Radboud D

2017-05-01

To show that 14-dimensional spaces of augmented point P and angle Q characteristics, matrices obtained from the ray transference, are suitable for quantitative analysis although only the latter define an inner-product space and only on it can one define distances and angles. The paper examines the nature of the spaces and their relationships to other spaces including symmetric dioptric power space. The paper makes use of linear optics, a three-dimensional generalization of Gaussian optics. Symmetric 2 × 2 dioptric power matrices F define a three-dimensional inner-product space which provides a sound basis for quantitative analysis (calculation of changes, arithmetic means, etc.) of refractive errors and thin systems. For general systems the optical character is defined by the dimensionally-heterogeneous 4 × 4 symplectic matrix S, the transference, or if explicit allowance is made for heterocentricity, the 5 × 5 augmented symplectic matrix T. Ordinary quantitative analysis cannot be performed on them because matrices of neither of these types constitute vector spaces. Suitable transformations have been proposed but because the transforms are dimensionally heterogeneous the spaces are not naturally inner-product spaces. The paper obtains 14-dimensional spaces of augmented point P and angle Q characteristics. The 14-dimensional space defined by the augmented angle characteristics Q is dimensionally homogenous and an inner-product space. A 10-dimensional subspace of the space of augmented point characteristics P is also an inner-product space. The spaces are suitable for quantitative analysis of the optical character of eyes and many other systems. Distances and angles can be defined in the inner-product spaces. The optical systems may have multiple separated astigmatic and decentred refracting elements. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.

Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis)

Science.gov (United States)

FUNK, W. CHRIS; LOVICH, ROBERT E.; HOHENLOHE, PAUL A.; HOFMAN, COURTNEY A.; MORRISON, SCOTT A.; SILLETT, T. SCOTT; GHALAMBOR, CAMERON K.; MALDONADO, JESUS E.; RICK, TORBEN C.; DAY, MITCH D.; POLATO, NICHOLAS R.; FITZPATRICK, SARAH W.; COONAN, TIMOTHY J.; CROOKS, KEVIN R.; DILLON, ADAM; GARCELON, DAVID K.; KING, JULIE L.; BOSER, CHRISTINA L.; GOULD, NICHOLAS; ANDELT, WILLIAM F.

2016-01-01

The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox (Urocyon littoralis). This species consists of 6 subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction-site Associated DNA (RAD) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small Ne (range = 2.1–89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland gray foxes, and vice versa, indicating genetic drift drives genome-wide divergence. Nonetheless, outlier tests identified 3.6–6.6% of loci as high FST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high FST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small Ne in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness, and reduced adaptive potential. PMID:26992010

Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis).

Science.gov (United States)

Funk, W Chris; Lovich, Robert E; Hohenlohe, Paul A; Hofman, Courtney A; Morrison, Scott A; Sillett, T Scott; Ghalambor, Cameron K; Maldonado, Jesus E; Rick, Torben C; Day, Mitch D; Polato, Nicholas R; Fitzpatrick, Sarah W; Coonan, Timothy J; Crooks, Kevin R; Dillon, Adam; Garcelon, David K; King, Julie L; Boser, Christina L; Gould, Nicholas; Andelt, William F

2016-05-01

The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox (Urocyon littoralis). This species consists of six subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction-site Associated DNA (RAD) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small Ne (range = 2.1-89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland grey foxes, and vice versa, indicating genetic drift drives genome-wide divergence. Nonetheless, outlier tests identified 3.6-6.6% of loci as high FST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high FST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small Ne in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness and reduced adaptive potential. © 2016 John Wiley & Sons Ltd.

Quantitative X ray analysis system. User's manual and guide to X ray fluorescence technique

International Nuclear Information System (INIS)

2009-01-01

This guide covers trimmed and re-arranged version 3.6 of the Quantitative X ray Analysis System (QXAS) software package that includes the most frequently used methods of quantitative analysis. QXAS is a comprehensive quantitative analysis package that has been developed by the IAEA through research and technical contracts. Additional development has also been carried out in the IAEA Laboratories in Seibersdorf where QXAS was extensively tested. New in this version of the manual are the descriptions of the Voigt-profile peak fitting, the backscatter fundamental parameters' and emission-transmission methods of chemical composition analysis, an expanded chapter on the X ray fluorescence physics, and completely revised and increased number of practical examples of utilization of the QXAS software package. The analytical data accompanying this manual were collected in the IAEA Seibersdorf Laboratories in the years 2006/2007

Quantitative proteomic analysis of intact plastids.

Science.gov (United States)

Shiraya, Takeshi; Kaneko, Kentaro; Mitsui, Toshiaki

2014-01-01

Plastids are specialized cell organelles in plant cells that are differentiated into various forms including chloroplasts, chromoplasts, and amyloplasts, and fulfill important functions in maintaining the overall cell metabolism and sensing environmental factors such as sunlight. It is therefore important to grasp the mechanisms of differentiation and functional changes of plastids in order to enhance the understanding of vegetality. In this chapter, details of a method for the extraction of intact plastids that makes analysis possible while maintaining the plastid functions are provided; in addition, a quantitative shotgun method for analyzing the composition and changes in the content of proteins in plastids as a result of environmental impacts is described.

Quantitative analysis of elastography images in the detection of breast cancer

International Nuclear Information System (INIS)

Landoni, V.; Francione, V.; Marzi, S.; Pasciuti, K.; Ferrante, F.; Saracca, E.; Pedrini, M.; Strigari, L.; Crecco, M.; Di Nallo, A.

2012-01-01

Purpose: The aim of this study was to develop a quantitative method for breast cancer diagnosis based on elastosonography images in order to reduce whenever possible unnecessary biopsies. The proposed method was validated by correlating the results of quantitative analysis with the diagnosis assessed by histopathologic exam. Material and methods: 109 images of breast lesions (50 benign and 59 malignant) were acquired with the traditional B-mode technique and with elastographic modality. Images in Digital Imaging and COmmunications in Medicine format (DICOM) were exported into a software, written in Visual Basic, especially developed to perform this study. The lesion was contoured and the mean grey value and softness inside the region of interest (ROI) were calculated. The correlations between variables were investigated and receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of the proposed method. Pathologic results were used as standard reference. Results: Both the mean grey value and the softness inside the ROI resulted statistically different at the t test for the two populations of lesions (i.e., benign versus malignant): p < 0.0001. The area under the curve (AUC) was 0.924 (0.834–0.973) and 0.917 (0.826–0.970) for the mean grey value and for the softness respectively. Conclusions: Quantitative elastosonography is a promising ultrasound technique in the detection of breast cancer but large prospective trials are necessary to determine whether quantitative analysis of images can help to overcome some pitfalls of the methodic.

Renal geology (quantitative renal stone analysis) by 'Fourier transform infrared spectroscopy'.

Science.gov (United States)

Singh, Iqbal

2008-01-01

To prospectively determine the precise stone composition (quantitative analysis) by using infrared spectroscopy in patients with urinary stone disease presenting to our clinic. To determine an ideal method for stone analysis suitable for use in a clinical setting. After routine and a detailed metabolic workup of all patients of urolithiasis, stone samples of 50 patients of urolithiasis satisfying the entry criteria were subjected to the Fourier transform infrared spectroscopic analysis after adequate sample homogenization at a single testing center. Calcium oxalate monohydrate and dihydrate stone mixture was most commonly encountered in 35 (71%) followed by calcium phosphate, carbonate apatite, magnesium ammonium hexahydrate and xanthine stones. Fourier transform infrared spectroscopy allows an accurate, reliable quantitative method of stone analysis. It also helps in maintaining a computerized large reference library. Knowledge of precise stone composition may allow the institution of appropriate prophylactic therapy despite the absence of any detectable metabolic abnormalities. This may prevent and or delay stone recurrence.

Quantitative proteomic analysis of ibuprofen-degrading Patulibacter sp. strain I11

DEFF Research Database (Denmark)

Almeida, Barbara; Kjeldal, Henrik; Lolas, Ihab Bishara Yousef

2013-01-01

was identified and quantified by gel based shotgun-proteomics. In total 251 unique proteins were quantitated using this approach. Biological process and pathway analysis indicated a number of proteins that were up-regulated in response to active degradation of ibuprofen, some of them are known to be involved...... in the degradation of aromatic compounds. Data analysis revealed that several of these proteins are likely involved in ibuprofen degradation by Patulibacter sp. strain I11.......Ibuprofen is the third most consumed pharmaceutical drug in the world. Several isolates have been shown to degrade ibuprofen, but very little is known about the biochemistry of this process. This study investigates the degradation of ibuprofen by Patulibacter sp. strain I11 by quantitative...

Genetic and immunohistochemical analysis of HSPA5 in mouse and human retinas.

Science.gov (United States)

Chintalapudi, Sumana R; Wang, XiaoFei; Li, Huiling; Lau, Yin H Chan; Williams, Robert W; Jablonski, Monica M

2016-01-01

Photoreceptor degenerative diseases are among the leading causes of vision loss. Although the causative genetic mutations are often known, mechanisms leading to photoreceptor degeneration remain poorly defined. We have previously demonstrated that the photoreceptor membrane-associated protein XAP-1 antigen is a product of the HSPA5 gene. In this study, we used systems genetic methods, statistical modeling, and immunostaining to identify and analyze candidate genes that modulate Hspa5 expression in the retina. Quantitative trait locus (QTL) mapping was used to map the genomic region that regulates Hspa5 in the cross between C57BL/6J X DBA/2J mice (BXD) genetic reference panel. The stepwise refinement of candidate genes was based on expression QTL mapping, gene expression correlation analyses (direct and partial), and analysis of regional sequence variants. The subcellular localization of candidate proteins and HSPA5 in mouse and human retinas was evaluated by immunohistochemistry. Differences in the localization of extracellular HSPA5 were assessed between healthy human donor and atrophic age-related macular degeneration (AMD) donor eyes. In the eyes of healthy mice, extracellular HSPA5 was confined to the area around the cone photoreceptor outer segments. Mapping variation in Hspa5 mRNA expression levels in the retina revealed a statistically significant trans -acting expression QTL (eQTL) on Chromosome 2 (Chr 2) and a suggestive locus on Chr 15. Sulf2 on Chr 2 was the strongest candidate gene based on partial correlation analysis, Pearson correlation with Hspa5 , expression levels in the retina, a missense variant in exon 14, and its reported function in the extracellular matrix and interphotoreceptor matrix. SULF2 is localized to the rod and cone photoreceptors in both human and mouse retinas. In human retinas with no pathology, extracellular HSPA5 was localized around many cones within the macular area. In contrast, fewer HSPA5-immunopositive cones were

Quantitative trait loci associated with anthracnose resistance in sorghum

Science.gov (United States)

With an aim to develop a durable resistance to the fungal disease anthracnose, two unique genetic sources of resistance were selected to create genetic mapping populations to identify regions of the sorghum genome that encode anthracnose resistance. A series of quantitative trait loci were identifi...

Analysis association of milk fat and protein percent in quantitative ...

African Journals Online (AJOL)

Analysis association of milk fat and protein percent in quantitative trait locus ... African Journal of Biotechnology ... Protein and fat percent as content of milk are high-priority criteria for financial aims and selection of programs in dairy cattle.

Different responsiveness to a high-fat/cholesterol diet in two inbred mice and underlying genetic factors: a whole genome microarray analysis

Directory of Open Access Journals (Sweden)

Jin Gang

2009-10-01

Full Text Available Abstract Background To investigate different responses to a high-fat/cholesterol diet and uncover their underlying genetic factors between C57BL/6J (B6 and DBA/2J (D2 inbred mice. Methods B6 and D2 mice were fed a high-fat/cholesterol diet for a series of time-points. Serum and bile lipid profiles, bile acid yields, hepatic apoptosis, gallstones and atherosclerosis formation were measured. Furthermore, a whole genome microarray was performed to screen hepatic genes expression profile. Quantitative real-time PCR, western blot and TUNEL assay were conducted to validate microarray data. Results After fed the high-fat/cholesterol diet, serum and bile total cholesterol, serum cholesterol esters, HDL cholesterol and Non-HDL cholesterol levels were altered in B6 but not significantly changed in D2; meanwhile, biliary bile acid was decreased in B6 but increased in D2. At the same time, hepatic apoptosis, gallstones and atherosclerotic lesions occurred in B6 but not in D2. The hepatic microarray analysis revealed distinctly different genes expression patterns between B6 and D2 mice. Their functional pathway groups included lipid metabolism, oxidative stress, immune/inflammation response and apoptosis. Quantitative real time PCR, TUNEL assay and western-blot results were consistent with microarray analysis. Conclusion Different genes expression patterns between B6 and D2 mice might provide a genetic basis for their distinctive responses to a high-fat/cholesterol diet, and give us an opportunity to identify novel pharmaceutical targets in related diseases in the future.

Contribution of the surface contamination of uranium-materials on the quantitative analysis results by electron probe microbeam analysis

International Nuclear Information System (INIS)

Bonino, O.; Fournier, C.; Fucili, C.; Dugne, O.; Merlet, C.

2000-01-01

The analytical testing of uranium materials is necessary for quality research and development in nuclear industry applications (enrichment, safety studies, fuel, etc). Electron Probe Microbeam Analysis Wavelength Dispersive Spectrometry (EPMA-WDS) is a dependable non-destructive analytical technology. The characteristic X-ray signal is measured to identify and quantify the sample components, and the analyzed volume is about one micron cube. The surface contamination of uranium materials modifies and contributes to the quantitative analysis results of EPMA-WDS. This contribution is not representative of the bulk. A thin oxidized layer appears in the first instants after preparation (burnishing, cleaning) as well as a carbon contamination layer, due to metallographic preparation and carbon cracking under the impact of the electron probe. Several analytical difficulties subsequently arise, including an overlapping line between the carbon Ka ray and the Uranium U NIVOVI ray. Sensitivity and accuracy of the quantification of light elements like carbon and oxygen are also reduced by the presence of uranium. The aim of this study was to improve the accuracy of quantitative analysis on uranium materials by EPMA-WDS by taking account of the contribution of surface contamination. The first part of this paper is devoted to the study of the contaminated surface of the uranium materials U, UFe 2 and U 6 Fe a few hours after preparation. These oxidation conditions are selected so as to reproduce the same contamination surfaces occurring in microprobe analytical conditions. Surface characterization techniques were SIMS and Auger spectroscopy. The contaminated surfaces are shown. They consist of successive layers: a carbon layer, an oxidized iron layer, followed by an iron depletion layer (only in UFe 2 and U 6 Fe), and a ternary oxide layer (U-Fe-O for UFe 2 et U 6 Fe and UO 2+x for uranium). The second part of the paper addresses the estimation of the errors in quantitative

A new quantitative analysis on nitriding kinetics in the oxidized Zry-4 at 900-1200 .deg. C

Energy Technology Data Exchange (ETDEWEB)

Park, Sanggi [ACT Co. Ltd., Daejeon (Korea, Republic of)

2016-10-15

Two major roles of nitrogen on the zirconium based cladding degradation were identified: mechanical degradation of the cladding, and the additional chemical heat release. It has long been known that accelerated oxidation can occur in air due to the nitrogen. In addition, significant uptake of nitrogen can also occur. The nitriding of pre-oxidized zirconium based alloys leads to micro porous and less coherent oxide scales. This paper aims to quantitatively investigate the nitriding mechanism and kinetics by proposing a new methodology that is coupled with the mass balance analysis and the optical microscope image processing analysis. A new quantitative analysis methodology is described in chapter 2 and the investigation of the nitriding kinetics is performed in chapter 3. The experimental details are previously reported in. Previously only qualitative analysis was performed in, and hence the quantitative analysis will be performed in this paper. In this paper, the nitriding kinetics and mechanism were quantitatively analyzed by the new proposed analysis methods: the mass balance analysis and the optical microscope image processing analysis. Using these combined methods, the mass gain curves and the optical microscopes are analyzed in very detail, and the mechanisms of nitriding accelerated, stabilized and saturated behaviors were well understood. This paper has two very distinctive achievements as follows: 1) Development of very effective quantitative analysis methods only using two main results of oxidation tests: No detailed analytical sample measurements (e.g. TEM, EPMA and so on.) were required. These methods can effectively reduce the cost and effort of the post-test investigation. 2) The first identification of the nitriding behaviors and its very accurate analysis in a quantitative way. Based on this quantitative analysis results on the nitriding kinetics, these new findings will contribute significantly the understanding the air oxidation behaviors and model

A novel genetic tool for clonal analysis of fourth chromosome mutations

OpenAIRE

Sousa-Neves, Rui; Schinaman, Joseph M.

2012-01-01

The fourth chromosome of Drosophila remains one of the most intractable regions of the fly genome to genetic analysis. The main difficulty posed to the genetic analyses of mutations on this chromosome arises from the fact that it does not undergo meiotic recombination, which makes recombination mapping impossible, and also prevents clonal analysis of mutations, a technique which relies on recombination to introduce the prerequisite recessive markers and FLP-recombinase recognition targets (FR...

Patient-specific coronary blood supply territories for quantitative perfusion analysis

Science.gov (United States)

Zakkaroff, Constantine; Biglands, John D.; Greenwood, John P.; Plein, Sven; Boyle, Roger D.; Radjenovic, Aleksandra; Magee, Derek R.

2018-01-01

Abstract Myocardial perfusion imaging, coupled with quantitative perfusion analysis, provides an important diagnostic tool for the identification of ischaemic heart disease caused by coronary stenoses. The accurate mapping between coronary anatomy and under-perfused areas of the myocardium is important for diagnosis and treatment. However, in the absence of the actual coronary anatomy during the reporting of perfusion images, areas of ischaemia are allocated to a coronary territory based on a population-derived 17-segment (American Heart Association) AHA model of coronary blood supply. This work presents a solution for the fusion of 2D Magnetic Resonance (MR) myocardial perfusion images and 3D MR angiography data with the aim to improve the detection of ischaemic heart disease. The key contribution of this work is a novel method for the mediated spatiotemporal registration of perfusion and angiography data and a novel method for the calculation of patient-specific coronary supply territories. The registration method uses 4D cardiac MR cine series spanning the complete cardiac cycle in order to overcome the under-constrained nature of non-rigid slice-to-volume perfusion-to-angiography registration. This is achieved by separating out the deformable registration problem and solving it through phase-to-phase registration of the cine series. The use of patient-specific blood supply territories in quantitative perfusion analysis (instead of the population-based model of coronary blood supply) has the potential of increasing the accuracy of perfusion analysis. Quantitative perfusion analysis diagnostic accuracy evaluation with patient-specific territories against the AHA model demonstrates the value of the mediated spatiotemporal registration in the context of ischaemic heart disease diagnosis. PMID:29392098

Analysis of genetic polymorphism of nine short tandem repeat loci in ...

African Journals Online (AJOL)

Yomi

2012-03-15

Mar 15, 2012 ... Key words: short tandem repeat, repeat motif, genetic polymorphism, Han population, forensic genetics. INTRODUCTION. Short tandem repeat (STR) is widely .... Data analysis. The exact test of Hardy-Weinberg equilibrium was conducted with. Arlequin version 3.5 software (Computational and Molecular.

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

Directory of Open Access Journals (Sweden)

Apirak Sakunpak

2014-02-01

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.

Bias due to two-stage residual-outcome regression analysis in genetic association studies.

Science.gov (United States)

Demissie, Serkalem; Cupples, L Adrienne

2011-11-01

Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

Difficult Questions and Ambivalent Answers on Genetic Testing

OpenAIRE

Andréa Wiszmeg; Susanne Lundin; Eva Torkelson; Niclas Hagen; Cecilia Lundberg

2012-01-01

A qualitative pilot study on the attitudes of some citizens in southern Sweden toward predictive genetic testing – and a quantitative nation wide opinion poll targeting the same issues, was initiated by the Cultural Scientific Research Team of BAGADILICO. The latter is an international biomedical research environment on neurological disease at Lund University. The data of the two studies crystallized through analysis into themes around which the informants’ personal negotiations of opinions a...

Genetic Code Analysis Toolkit: A novel tool to explore the coding properties of the genetic code and DNA sequences

Science.gov (United States)

Kraljić, K.; Strüngmann, L.; Fimmel, E.; Gumbel, M.

2018-01-01

The genetic code is degenerated and it is assumed that redundancy provides error detection and correction mechanisms in the translation process. However, the biological meaning of the code's structure is still under current research. This paper presents a Genetic Code Analysis Toolkit (GCAT) which provides workflows and algorithms for the analysis of the structure of nucleotide sequences. In particular, sets or sequences of codons can be transformed and tested for circularity, comma-freeness, dichotomic partitions and others. GCAT comes with a fertile editor custom-built to work with the genetic code and a batch mode for multi-sequence processing. With the ability to read FASTA files or load sequences from GenBank, the tool can be used for the mathematical and statistical analysis of existing sequence data. GCAT is Java-based and provides a plug-in concept for extensibility. Availability: Open source Homepage:http://www.gcat.bio/

Optimal climate policy is a utopia. From quantitative to qualitative cost-benefit analysis

International Nuclear Information System (INIS)

Van den Bergh, Jeroen C.J.M.

2004-01-01

The dominance of quantitative cost-benefit analysis (CBA) and optimality concepts in the economic analysis of climate policy is criticised. Among others, it is argued to be based in a misplaced interpretation of policy for a complex climate-economy system as being analogous to individual inter-temporal welfare optimisation. The transfer of quantitative CBA and optimality concepts reflects an overly ambitious approach that does more harm than good. An alternative approach is to focus the attention on extreme events, structural change and complexity. It is argued that a qualitative rather than a quantitative CBA that takes account of these aspects can support the adoption of a minimax regret approach or precautionary principle in climate policy. This means: implement stringent GHG reduction policies as soon as possible

Method of quantitative analysis of superconducting metal-conducting composite materials

International Nuclear Information System (INIS)

Bogomolov, V.N.; Zhuravlev, V.V.; Petranovskij, V.P.; Pimenov, V.A.

1990-01-01

Technique for quantitative analysis of superconducting metal-containing composite materials, SnO 2 -InSn, WO 3 -InW, Zn)-InZn in particular, has been developed. The method of determining metal content in a composite is based on the dependence of superconducting transition temperature on alloy composition. Sensitivity of temperature determination - 0.02K, error of analysis for InSn system - 0.5%

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

NARCIS (Netherlands)

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.

Background 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

Meta-analysis for quantitative microbiological risk assessments and benchmarking data

NARCIS (Netherlands)

Besten, den H.M.W.; Zwietering, M.H.

2012-01-01

Meta-analysis studies are increasingly being conducted in the food microbiology area to quantitatively integrate the findings of many individual studies on specific questions or kinetic parameters of interest. Meta-analyses provide global estimates of parameters and quantify their variabilities, and

Quantitative variation in natural populations

International Nuclear Information System (INIS)

Parsons, P.A.

1975-01-01

Quantitative variation is considered in natural populations using Drosophila as the example. A knowledge of such variation enables its rapid exploitation in directional selection experiments as shown for scutellar chaeta number. Where evidence has been obtained, genetic architectures are in qualitative agreement with Mather's concept of balance for traits under stabilizing selection. Additive genetic control is found for acute environmental stresses, but not for less acute stresses as shown by exposure to 60 Co-γ rays. D. simulans probably has a narrower ecological niche than its sibling species D. melanogaster associated with lower genetic heterogeneity. One specific environmental stress to which D. simulans is sensitive in nature is ethyl alcohol as shown by winery data. (U.S.)

Trabecular bone microarchitecture analysis, a way for an early detection of genetic dwarfism? Case study of a dwarf mother's offspring.

Science.gov (United States)

Colombo, Antony; Hoogland, Menno; Coqueugniot, Hélène; Dutour, Olivier; Waters-Rist, Andrea

2018-03-01

A 66 year-old woman with a disproportionate dwarfism and who bore seven children was discovered at the Middenbeemster archaeological site (The Netherlands). Three are perinates and show no macroscopic or radiological evidence for a FGFR3 mutation causing hypo-or achondroplasia. This mutation induces dysfunction of the growth cartilage, leading to abnormalities in the development of trabecular bone. Because the mutation is autosomal dominant, these perinates have a 50% risk of having been affected. This study determines whether trabecular bone microarchitecture (TBMA) analysis is useful for detecting genetic dwarfism. Proximal metaphyses of humeri were μCT-scanned with a resolution of 7-12 μm. Three volumes of interest were segmented from each bone with TIVMI© software. The TBMA was quantified in BoneJ© using six parameters on which a multivariate analysis was then performed. Two of the Middenbeemster perinates show a quantitatively different TBMA organization. These results and the family's medical history suggest a diagnosis of genetic dwarfism for this two perinates. This study provides evidence to support the efficacy of μCT for diagnosing early-stage bone disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Visual and Quantitative Analysis Methods of Respiratory Patterns for Respiratory Gated PET/CT.

Science.gov (United States)

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 quantitative indices of respiratory stability and determining quantitative cutoff value for differentiating regular and irregular respiration.

GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

Science.gov (United States)

Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy

2011-08-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.