Cytogenetic mapping of the W chromosome in the genus Leporinus (Teleostei, Anostomidae) using a highly repetitive DNA sequence

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Economic design of two-stage (X)over-bar charts: the Markov chain approach

When the (X) over bar chart is in use, samples are regularly taken from the process, and their means are plotted on the chart. In some cases, it is too expensive to obtain the X values, but not the values of a correlated variable Y. This paper presents a model for the economic design of a two-stage control chart, that is. a control chart based on both performance (X) and surrogate (Y) variables. The process is monitored by the surrogate variable until it signals an out-of-control behavior, and then a switch is made to the (X) over bar chart. The (X) over bar chart is built with central, warning. and action regions. If an X sample mean falls in the central region, the process surveillance returns to the (Y) over bar chart. Otherwise. The process remains under the (X) over bar chart's surveillance until an (X) over bar sample mean falls outside the control limits. The search for an assignable cause is undertaken when the performance variable signals an out-of-control behavior. In this way, the two variables, are used in an alternating fashion. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A study is performed to examine the economic advantages of using performance and surrogate variables. (C) 2003 Elsevier B.V. All rights reserved.

Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC

Linear mixed effects models are frequently used to analyse longitudinal data, due to their flexibility in modelling the covariance structure between and within observations. Further, it is easy to deal with unbalanced data, either with respect to the number of observations per subject or per time period, and with varying time intervals between observations. In most applications of mixed models to biological sciences, a normal distribution is assumed both for the random effects and for the residuals. This, however, makes inferences vulnerable to the presence of outliers. Here, linear mixed models employing thick-tailed distributions for robust inferences in longitudinal data analysis are described. Specific distributions discussed include the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted, and the Gibbs sampler and the Metropolis-Hastings algorithms are used to carry out the posterior analyses. An example with data on orthodontic distance growth in children is discussed to illustrate the methodology. Analyses based on either the Student-t distribution or on the usual Gaussian assumption are contrasted. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process for modelling distributions of the random effects and of residuals in linear mixed models, and the MCMC implementation allows the computations to be performed in a flexible manner.

Economic design of (X)over-bar charts with variable parameters: the Markov chain approach

This paper presents an economic design of (X) over bar control charts with variable sample sizes, variable sampling intervals, and variable control limits. The sample size n, the sampling interval h, and the control limit coefficient k vary between minimum and maximum values, tightening or relaxing the control. The control is relaxed when an (X) over bar value falls close to the target and is tightened when an (X) over bar value falls far from the target. A cost model is constructed that involves the cost of false alarms, the cost of finding and eliminating the assignable cause, the cost associated with production in an out-of-control state, and the cost of sampling and testing. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A comprehensive study is performed to examine the economic advantages of varying the (X) over bar chart parameters.

A LINE2 repetitive DNA sequence from the cichlid fish, Oreochromis niloticus: sequence analysis and chromosomal distribution

We report the cloning and characterization of a long interspersed nucleotide element (LINE) fi-om a cichlid fish, Oreochromis niloticus, and show the distribution of this element, called CiLINE2 for cichlid LINE2, in the chromosomes of this species. The identification of an open reading frame in CiLINE2 with amino acid sequence similarity to reverse transcriptases encoded by LINE-like elements in Caenorhabditis elegans, Platemys spixii, Schistosoma mansoni, Gallus gallus (CRI), Drosophila melanogaster (I factor), and Homo sapiens (LINE2), as well as the structure of the element, suggest it is a member of this family of non-long terminal repeat-containing retrotransposons. Search of a DNA sequence database identified sequences similar to CiLINE2 in four other fish species (Haplotaxodon microlepis, Oreochromis mossambicus, Pseudotropheus zebra, and Fugu rubripes). Southern blot hybridization experiments revealed the presence of sequences similar to CiLINE2 in all Tilapiini species analyzed from the genera Oreochromis, Tilapia, and Sarotherodon, and gave an estimated copy number of about 5500 for the haploid genome of O. niloticus. Fluorescent in situ hybridization showed that CiLINE2 sequences were organized in small clusters dispersed over all chromosomes of O. niloticus, with a higher concentration near chromosome ends. Furthermore the long arm of chromosome 1 was strikingly enriched with this sequence. The distribution of LINE2-related elements might underlie the difference in chromosome banding patterns observed between cold-blooded vertebrates and mammals.

Contrasting intra versus interspecies DNA sequence variation for representatives of the Batrachospermales (Rhodophyta): Insights from a DNA barcoding approach

Sixty-five accessions of the species-rich freshwater red algal order Batrachospermales were characterized through DNA sequencing of two regions: the mitochondrial cox1 gene (664 bp), which is proposed as the DNA barcode for red algae, and the UPA (universal plastid amplicon) marker (370 bp), which has been recently identified as a universally amplifying region of the plastid genome. upgma phenograms of both markers were consistent in their species-level relationships, although levels of sequence divergence were very different. Intraspecific variation of morphologically identified accessions for the cox1 gene ranged from 0 to 67 bp (divergences were highest for the two taxa with the greatest number of accessions; Batrachospermum helminthosum and Batrachospermum macrosporum); while in contrast, the more conserved universal plastid amplicon exhibited much lower intraspecific variation (generally 0-3 bp). Comparisons to previously published mitochondrial cox2-3 spacer sequences for B. helminthosum indicated that the cox1 gene and cox2-3 spacer were characterized by similar levels of sequence divergence, and phylogeographic patterns based on these two markers were consistent. The two taxa represented by the largest numbers of specimens (B. helminthosum and B. macrosporum) have cox1 intraspecific divergence values that are substantially higher than previously reported, but no morphological differences can be discerned at this time among the intraspecific groups revealed in the analyses. DNA barcode data, which are based on a short fragment of an organellar genome, need to be interpreted in conjunction with other taxonomic characters, and additional batrachospermalean taxa need to be analyzed in detail to be able to draw generalities regarding intraspecific variation in this order. Nevertheless, these analyses reveal a number of batrachospermalean taxa worthy of more detailed DNA barcode study, and it is predicted that such research will have a substantial effect on the taxonomy of species within the Batrachospermales in the future.

The Mycobacterium tuberculosis Rv2540c DNA sequence encodes a bifunctional chorismate synthase

Background. The emergence of multi- and extensively-drug resistant Mycobacterium tuberculosis strains has created an urgent need for new agents to treat tuberculosis (TB). The enzymes of shikimate pathway are attractive targets to the development of antitubercular agents because it is essential for M. tuberculosis and is absent from humans. Chorismate synthase (CS) is the seventh enzyme of this route and catalyzes the NADH- and FMN-dependent synthesis of chorismate, a precursor of aromatic amino acids, naphthoquinones, menaquinones, and mycobactins. Although the M. tuberculosis Rv2540c (aroF) sequence has been annotated to encode a chorismate synthase, there has been no report on its correct assignment and functional characterization of its protein product. Results. In the present work, we describe DNA amplification of aroF-encoded CS from M. tuberculosis (MtCS), molecular cloning, protein expression, and purification to homogeneity. N-terminal amino acid sequencing, mass spectrometry and gel filtration chromatography were employed to determine identity, subunit molecular weight and oligomeric state in solution of homogeneous recombinant MtCS. The bifunctionality of MtCS was determined by measurements of both chorismate synthase and NADH:FMN oxidoreductase activities. The flavin reductase activity was characterized, showing the existence of a complex between FMN ox and MtCS. FMNox and NADH equilibrium binding was measured. Primary deuterium, solvent and multiple kinetic isotope effects are described and suggest distinct steps for hydride and proton transfers, with the former being more rate-limiting. Conclusion. This is the first report showing that a bacterial CS is bifunctional. Primary deuterium kinetic isotope effects show that C4-proS hydrogen is being transferred during the reduction of FMNox by NADH and that hydride transfer contributes significantly to the rate-limiting step of FMN reduction reaction. Solvent kinetic isotope effects and proton inventory results indicate that proton transfer from solvent partially limits the rate of FMN reduction and that a single proton transfer gives rise to the observed solvent isotope effect. Multiple isotope effects suggest a stepwise mechanism for the reduction of FMNox. The results on enzyme kinetics described here provide evidence for the mode of action of MtCS and should thus pave the way for the rational design of antitubercular agents. © 2008 Ely et al; licensee BioMed Central Ltd.

New insights into telomeric DNA sequence (TTAGGG)n location in bat chromosomes

Molossidae species, Cynomops abrasus (2n = 34, fundamental number, FN = 64), Eumops auripendulus (2n = 42, FN = 62), Molossus rufus (2n = 48, FN = 64), Molossops temminckii (2n = 48, FN = 64), and Nyctinomops laticaudatus (2n = 48, FN = 64), and Phyllostomidae species, Phyllostomus discolor (2n = 32, FN = 60), have karyotypes with different chromosome and fundamental numbers, different localization of constitutive heterochromatin, and different numbers and location of nucleolar organizer regions (NORs). Fluorescence in situ hybridization with a human probe of the telomeric sequence (TTAGGG)n produced fluorescent signals in telomeric regions of the six bat species' chromosomes; in E. auripendulus, pericentromeric signals were also observed in the acrocentric and subtelocentric chromosomes. A relationship between telomeric sequences and NORs, and between telomeric sequences and constitutive heterochromatin was detected in chromosomes bearing NORs in C. abrasus, M. temminckii, N. laticaudatus, and P. discolor. No interstitial signal was observed in the meta- or submetacentric chromosomes of these species. ©FUNPEC-RP.

Context-sensitive analysis without calling-context

Since Sharir and Pnueli, algorithms for context-sensitivity have been defined in terms of 'valid' paths in an interprocedural flow graph. The definition of valid paths requires atomic call and ret statements, and encapsulated procedures. Thus, the resulting algorithms are not directly applicable when behavior similar to call and ret instructions may be realized using non-atomic statements, or when procedures do not have rigid boundaries, such as with programs in low level languages like assembly or RTL. We present a framework for context-sensitive analysis that requires neither atomic call and ret instructions, nor encapsulated procedures. The framework presented decouples the transfer of control semantics and the context manipulation semantics of statements. A new definition of context-sensitivity, called stack contexts, is developed. A stack context, which is defined using trace semantics, is more general than Sharir and Pnueli's interprocedural path based calling-context. An abstract interpretation based framework is developed to reason about stack-contexts and to derive analogues of calling-context based algorithms using stack-context. The framework presented is suitable for deriving algorithms for analyzing binary programs, such as malware, that employ obfuscations with the deliberate intent of defeating automated analysis. The framework is used to create a context-sensitive version of Venable et al.'s algorithm for analyzing x86 binaries without requiring that a binary conforms to a standard compilation model for maintaining procedures, calls, and returns. Experimental results show that a context-sensitive analysis using stack-context performs just as well for programs where the use of Sharir and Pnueli's calling-context produces correct approximations. However, if those programs are transformed to use call obfuscations, a contextsensitive analysis using stack-context still provides the same, correct results and without any additional overhead. © Springer Science+Business Media, LLC 2011.

Demographic, economic-demographic and other demographically related model: an analysis

Includes bibliography

Delimiting the Origin of a B Chromosome by FISH Mapping, Chromosome Painting and DNA Sequence Analysis in Astyanax paranae (Teleostei, Characiformes)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of an Electrochemical Insulin Sensor Based on a High Affinity DNA Sequence Found in the Insulin-linked Polymorphic Region

The detection of pertinent biomarkers has the potential provide an early indication of disease progression before considerable damage has been incurred. A decrease in an individual’s sensitivity to insulin, which may be quantified as the ratio of insulin to glucose in the blood after a glucose pulse, has recently been reported as an early predictor of insulin-dependent diabetes mellitus. Routine measurement of insulin levels is therefore desirable in the care of diabetes-prone individuals. A rapid, simple, and reagentless method for insulin detection would allow for wide-spread screenings that provide earlier signs of diabetes onset. The aim of this thesis is to develop a folding-base electrochemical sensor for the detection of insulin. The sensor described herein consists of a DNA probe immobilized on a gold disc electrode via an alkanethiol linker and embedded in an alkanethiol self-assembled monolayer. The probe is labeled with a redox reporter, which readily transfers electrons to the gold electrode in the absence of insulin. In the presence of insulin, electron transfer is inhibited, presumably due to a binding-induced conformational or dynamic change in the DNA probe that significantly alters the electron-tunneling pathway. A 28-base segment of the insulin-linked polymorphic region that has been reported to bind insulin with high affinity serves as the capture element of the DNA probe. Three probe constructs that vary in their secondary structure and position of the redox label are evaluated for their utility as insulin-sensing elements on the electrochemical platform. The effects of probe modification on secondary structure are also evaluated using circular dichroism spectroscopy.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.