Genetic isolation and morphological divergence of Black Sea bottlenose dolphins

The Black Sea is a semi-enclosed body of water that differs from the adjacent Mediterranean Sea in terms of its biodiversity, oceanographical and ecological characteristics. There is growing international concern about pollution in the Black Sea and other anthropogenic threats to its fauna. The bottlenose dolphin (Tursiops truncatus) is one of three species of cetaceans living in the Azov-Black Sea basin. Despite considerable research on bottlenose dolphins elsewhere, the extent of human impacts on the Black Sea populations is unknown. Previous attempts to award special conservation status to Black Sea cetaceans have failed specifically because policy makers have viewed their ecological and evolutionary uniqueness as equivocal. This study assessed divergence between Black Sea, Mediterranean Sea and Atlantic Ocean bottlenose dolphins for 26 cranial measurements (n = 75 adult bottlenose dolphin skulls) and mitochondrial DNA (n = 99 individuals). Black Sea bottlenose dolphins are smaller than those in the Mediterranean, and possess a uniquely shaped skull. As in a previous study, we found the Black Sea population to be genetically distinct, with relatively low levels of mtDNA diversity. Population genetic models suggest that Black Sea bottlenose dolphins have so little gene flow with the Mediterranean due to historical isolation that they should be managed separately.

Inhibition of iNOS induces antidepressant-like effects in mice: Pharmacological and genetic evidence

Recent evidence has suggested that systemic administration of non-selective NOS inhibitors induces antidepressant-like effects in animal models. However, the precise involvement of the different NOS isoforms (neuronal-nNOS and inducible-iNOS) in these effects has not been clearly defined yet. Considering that mediators of the inflammatory response, that are able to induce iNOS expression, can be increased by exposure to stress, the aim of the present study was to investigate iNOS involvement in stress-induced behavioral consequences in the forced swimming test (FST), an animal model sensitive to antidepressant drugs. Therefore, we investigated the effects induced by systemic injection of aminoguanidine (preferential iNOS inhibitor), 1400W (selective iNOS inhibitor) or n-propyl-L-arginine (NPA, selective nNOS inhibitor) in mice submitted to the FST. We also investigated the behavior of mice with genetic deletion of iNOS (knockout) submitted to the FST. Aminoguanidine significantly decreased the immobility time (IT) in the FST. 1400W but not NPA, when administered at equivalent doses considering the magnitude of their Ki values for iNOS and nNOS, respectively, reduced the IT, thus suggesting that aminoguanidine-induced effects would be due to selective iNOS inhibition. Similarly, iNOS KO presented decreased IT in the FST when compared to wild-type mice. These results are the first to show that selective inhibition of iNOS or its knockdown induces antidepressant-like effects, therefore suggesting that iNOS-mediated NO synthesis is involved in the modulation of stress-induced behavioral consequences. Moreover, they further support NO involvement in the neurobiology of depression. This article is part of a Special Issue entitled 'Anxiety and Depression'. (C) 2011 Elsevier Ltd. All rights reserved.

Thioredoxin interacting protein genetic variation is associated with diabetes and hypertension in the Brazilian general population

Objective: To investigate the relationship between TXNIP polymorphisms, diabetes and hypertension phenotypes in the Brazilian general population. Methods: Five hundred seventy-six individuals randomly selected from the general urban population according to the MONICA-WHO project guidelines were phenotyped for cardiovascular risk factors. A second, independent, sample composed of 487 family-trios from a different site was also selected. Nine TXNIP polymorphisms were studied. The potential association between TXNIP variability and glucose-phenotypes in children was also explored. TXNIP expression was quantified by real-time PCR in 53 samples from human smooth muscle cells primary culture. Results: TXNIP rs7211 and rs7212 polymorphisms were significantly associated with glucose and blood pressure related phenotypes. In multivariate logistic regression models the studied markers remained associated with diabetes even after adjustment for covariates. TXNIP rs7211 T/rs7212 G haplotype (present in approximately 17% of individuals) was significantly associated to diabetes in both samples. In children, the TXNIP rs7211 T/rs7212 G haplotype was associated with fasting insulin concentrations. Finally, cells harboring TXNIP rs7212 G allele presented higher TXNIP expression levels compared with carriers of TXNIP rs7212 CC genotype (p = 0.02). Conclusion: Carriers of TXNIP genetic variants presented higher TXNIP expression, early signs of glucose homeostasis derangement and increased susceptibility to chronic metabolic conditions such as diabetes and hypertension. Our data suggest that genetic variation in the TXNIP gene may act as a "common ground" modulator of both traits: diabetes and hypertension. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

A Genetic and Pathologic Study of a DENV2 Clinical Isolate Capable of Inducing Encephalitis and Hematological Disturbances in Immunocompetent Mice

Dengue virus (DENV) is the causative agent of dengue fever (DF), a mosquito-borne illness endemic to tropical and subtropical regions. There is currently no effective drug or vaccine formulation for the prevention of DF and its more severe forms, i.e., dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). There are two generally available experimental models for the study of DENV pathogenicity as well as the evaluation of potential vaccine candidates. The first model consists of non-human primates, which do not develop symptoms but rather a transient viremia. Second, mouse-adapted virus strains or immunocompromised mouse lineages are utilized, which display some of the pathological features of the infection observed in humans but may not be relevant to the results with regard to the wild-type original virus strains or mouse lineages. In this study, we describe a genetic and pathological study of a DENV2 clinical isolate, named JHA1, which is naturally capable of infecting and killing Balb/c mice and reproduces some of the symptoms observed in DENV-infected subjects. Sequence analyses demonstrated that the JHA1 isolate belongs to the American genotype group and carries genetic markers previously associated with neurovirulence in mouse-adapted virus strains. The JHA1 strain was lethal to immunocompetent mice following intracranial (i.c.) inoculation with a LD50 of approximately 50 PFU. Mice infected with the JHA1 strain lost weight and exhibited general tissue damage and hematological disturbances, with similarity to those symptoms observed in infected humans. In addition, it was demonstrated that the JHA1 strain shares immunological determinants with the DENV2 NGC reference strain, as evaluated by cross-reactivity of anti-envelope glycoprotein (domain III) antibodies. The present results indicate that the JHA1 isolate may be a useful tool in the study of DENV pathogenicity and will help in the evaluation of anti-DENV vaccine formulations as well as potential therapeutic approaches.

Trends of the genetic connectedness measures among Nelore beef cattle herds

Validity of comparisons between expected breeding values obtained from best linear unbiased prediction procedures in genetic evaluations is dependent on genetic connectedness among herds. Different cattle breeding programmes have their own particular features that distinguish their database structure and can affect connectedness. Thus, the evolution of these programmes can also alter the connectedness measures. This study analysed the evolution of the genetic connectedness measures among Brazilian Nelore cattle herds from 1999 to 2008, using the French Criterion of Admission to the group of Connected Herds (CACO) method, based on coefficients of determination (CD) of contrasts. Genetic connectedness levels were analysed by using simple and multiple regression analyses on herd descriptors to understand their relationship and their temporal trends from the 19992003 to the 20042008 period. The results showed a high level of genetic connectedness, with CACO estimates higher than 0.4 for the majority of them. Evaluation of the last 5-year period showed only a small increase in average CACO measures compared with the first 5 years, from 0.77 to 0.80. The percentage of herds with CACO estimates lower than 0.7 decreased from 27.5% in the first period to 16.2% in the last one. The connectedness measures were correlated with percentage of progeny from connecting sires, and the artificial insemination spread among Brazilian herds in recent years. But changes in connectedness levels were shown to be more complex, and their complete explanation cannot consider only herd descriptors. They involve more comprehensive changes in the relationship matrix, which can be only fully expressed by the CD of contrasts.

Genetic and environmental risk factors in congenital heart disease functionally converge in protein networks driving heart development

Congenital heart disease (CHD) occurs in similar to 1% of newborns. CHD arises from many distinct etiologies, ranging from genetic or genomic variation to exposure to teratogens, which elicit diverse cell and molecular responses during cardiac development. To systematically explore the relationships between CHD risk factors and responses, we compiled and integrated comprehensive datasets from studies of CHD in humans and model organisms. We examined two alternative models of potential functional relationships between genes in these datasets: direct convergence, in which CHD risk factors significantly and directly impact the same genes and molecules and functional convergence, in which risk factors significantly impact different molecules that participate in a discrete heart development network. We observed no evidence for direct convergence. In contrast, we show that CHD risk factors functionally converge in protein networks driving the development of specific anatomical structures (e.g., outflow tract, ventricular septum, and atrial septum) that are malformed by CHD. This integrative analysis of CHD risk factors and responses suggests a complex pattern of functional interactions between genomic variation and environmental exposures that modulate critical biological systems during heart development.

Cash balance management: A comparison between genetic algorithms and particle swarm optimization

This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

ALDH1A2 (RALDH2) genetic variation in human congenital heart disease

Abstract Background Signaling by the vitamin A-derived morphogen retinoic acid (RA) is required at multiple steps of cardiac development. Since conversion of retinaldehyde to RA by retinaldehyde dehydrogenase type II (ALDH1A2, a.k.a RALDH2) is critical for cardiac development, we screened patients with congenital heart disease (CHDs) for genetic variation at the ALDH1A2 locus. Methods One-hundred and thirty-three CHD patients were screened for genetic variation at the ALDH1A2 locus through bi-directional sequencing. In addition, six SNPs (rs2704188, rs1441815, rs3784259, rs1530293, rs1899430) at the same locus were studied using a TDT-based association approach in 101 CHD trios. Observed mutations were modeled through molecular mechanics (MM) simulations using the AMBER 9 package, Sander and Pmemd programs. Sequence conservation of observed mutations was evaluated through phylogenetic tree construction from ungapped alignments containing ALDH8 s, ALDH1Ls, ALDH1 s and ALDH2 s. Trees were generated by the Neighbor Joining method. Variations potentially affecting splicing mechanisms were cloned and functional assays were designed to test splicing alterations using the pSPL3 splicing assay. Results We describe in Tetralogy of Fallot (TOF) the mutations Ala151Ser and Ile157Thr that change non-polar to polar residues at exon 4. Exon 4 encodes part of the highly-conserved tetramerization domain, a structural motif required for ALDH oligomerization. Molecular mechanics simulation studies of the two mutations indicate that they hinder tetramerization. We determined that the SNP rs16939660, previously associated with spina bifida and observed in patients with TOF, does not affect splicing. Moreover, association studies performed with classical models and with the transmission disequilibrium test (TDT) design using single marker genotype, or haplotype information do not show differences between cases and controls. Conclusion In summary, our screen indicates that ALDH1A2 genetic variation is present in TOF patients, suggesting a possible causal role for this gene in rare cases of human CHD, but does not support the hypothesis that variation at the ALDH1A2 locus is a significant modifier of the risk for CHD in humans.

Association of genetic variants in the promoter region of genes encoding p22phox (CYBA) and glutamate cysteine ligase catalytic subunit (GCLC) and renal disease in patients with type 1 diabetes mellitus

Background Oxidative stress is recognized as a major pathogenic factor of cellular damage caused by hyperglycemia. NOX/NADPH oxidases generate reactive oxygen species and NOX1, NOX2 and NOX4 isoforms are expressed in kidney and require association with subunit p22phox (encoded by the CYBA gene). Increased expression of p22phox was described in animal models of diabetic nephropathy. In the opposite direction, glutathione is one of the main endogenous antioxidants whose plasmatic concentrations were reported to be reduced in diabetes patients. The aim of the present investigation was to test whether functional single nucleotide polymorphisms (SNPs) in genes involved in the generation of NADPH-dependent O2•- (-675 T → A in CYBA, unregistered) and in glutathione metabolism (-129 C → T in GCLC [rs17883901] and -65 T → C in GPX3 [rs8177412]) confer susceptibility to renal disease in type 1 diabetes patients. Methods 401 patients were sorted into two groups according to the presence (n = 104) or absence (n = 196) of overt diabetic nephropathy or according to glomerular filtration rate (GFR) estimated by Modification of Diet in Renal Disease (MDRD) equation: ≥ 60 mL (n = 265) or < 60 mL/min/1.73 m2 (n = 136) and were genotyped. Results No differences were found in the frequency of genotypes between diabetic and non-diabetic subjects. The frequency of GFR < 60 mL/min was significantly lower in the group of patients carrying CYBA genotypes T/A+A/A (18.7%) than in the group carrying the T/T genotype (35.3%) (P = 0.0143) and the frequency of GFR < 60 mL/min was significantly higher in the group of patients carrying GCLC genotypes C/T+T/T (47.1%) than in the group carrying the C/C genotype (31.1%) (p = 0.0082). Logistic regression analysis identified the presence of at least one A allele of the CYBA SNP as an independent protection factor against decreased GFR (OR = 0.38, CI95% 0.14-0.88, p = 0.0354) and the presence of at least one T allele of the GCLC rs17883901 SNP as an independent risk factor for decreased GFR (OR = 2.40, CI95% 1.27-4.56, p = 0.0068). Conclusions The functional SNPs CYBA -675 T → A and GCLC rs17883901, probably associated with cellular redox imbalances, modulate the risk for renal disease in the studied population of type 1 diabetes patients and require validation in additional cohorts.

Different approaches for dealing with rare variants in family-based genetic studies: application of a Genetic Analysis Workshop 17 problem

Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.

High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research

Abstract Background The implication of post-transcriptional regulation by microRNAs in molecular mechanisms underlying cancer disease is well documented. However, their interference at the cellular level is not fully explored. Functional in vitro studies are fundamental for the comprehension of their role; nevertheless results are highly dependable on the adopted cellular model. Next generation small RNA transcriptomic sequencing data of a tumor cell line and keratinocytes derived from primary culture was generated in order to characterize the microRNA content of these systems, thus helping in their understanding. Both constitute cell models for functional studies of microRNAs in head and neck squamous cell carcinoma (HNSCC), a smoking-related cancer. Known microRNAs were quantified and analyzed in the context of gene regulation. New microRNAs were investigated using similarity and structural search, ab initio classification, and prediction of the location of mature microRNAs within would-be precursor sequences. Results were compared with small RNA transcriptomic sequences from HNSCC samples in order to access the applicability of these cell models for cancer phenotype comprehension and for novel molecule discovery. Results Ten miRNAs represented over 70% of the mature molecules present in each of the cell types. The most expressed molecules were miR-21, miR-24 and miR-205, Accordingly; miR-21 and miR-205 have been previously shown to play a role in epithelial cell biology. Although miR-21 has been implicated in cancer development, and evaluated as a biomarker in HNSCC progression, no significant expression differences were seen between cell types. We demonstrate that differentially expressed mature miRNAs target cell differentiation and apoptosis related biological processes, indicating that they might represent, with acceptable accuracy, the genetic context from which they derive. Most miRNAs identified in the cancer cell line and in keratinocytes were present in tumor samples and cancer-free samples, respectively, with miR-21, miR-24 and miR-205 still among the most prevalent molecules at all instances. Thirteen miRNA-like structures, containing reads identified by the deep sequencing, were predicted from putative miRNA precursor sequences. Strong evidences suggest that one of them could be a new miRNA. This molecule was mostly expressed in the tumor cell line and HNSCC samples indicating a possible biological function in cancer. Conclusions Critical biological features of cells must be fully understood before they can be chosen as models for functional studies. Expression levels of miRNAs relate to cell type and tissue context. This study provides insights on miRNA content of two cell models used for cancer research. Pathways commonly deregulated in HNSCC might be targeted by most expressed and also by differentially expressed miRNAs. Results indicate that the use of cell models for cancer research demands careful assessment of underlying molecular characteristics for proper data interpretation. Additionally, one new miRNA-like molecule with a potential role in cancer was identified in the cell lines and clinical samples.

Probabilistic approaches in civil engineering: generation of random fields and structural identification with genetic algorithms

The inherent stochastic character of most of the physical quantities involved in engineering models has led to an always increasing interest for probabilistic analysis. Many approaches to stochastic analysis have been proposed. However, it is widely acknowledged that the only universal method available to solve accurately any kind of stochastic mechanics problem is Monte Carlo Simulation. One of the key parts in the implementation of this technique is the accurate and efficient generation of samples of the random processes and fields involved in the problem at hand. In the present thesis an original method for the simulation of homogeneous, multi-dimensional, multi-variate, non-Gaussian random fields is proposed. The algorithm has proved to be very accurate in matching both the target spectrum and the marginal probability. The computational efficiency and robustness are very good too, even when dealing with strongly non-Gaussian distributions. What is more, the resulting samples posses all the relevant, welldefined and desired properties of “translation fields”, including crossing rates and distributions of extremes. The topic of the second part of the thesis lies in the field of non-destructive parametric structural identification. Its objective is to evaluate the mechanical characteristics of constituent bars in existing truss structures, using static loads and strain measurements. In the cases of missing data and of damages that interest only a small portion of the bar, Genetic Algorithm have proved to be an effective tool to solve the problem.

Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy.

Genetic engineering and preclinical evaluation of oncolytic herpes simplex viruses retargeted to cancer-specific receptors

Oncolytic virotherapy exploits the ability of viruses to infect and kill cells. It is suitable as treatment for tumors that are not accessible by surgery and/or respond poorly to the current therapeutic approach. HSV is a promising oncolytic agent. It has a large genome size able to accommodate large transgenes and some attenuated oncolytic HSVs (oHSV) are already in clinical trials phase I and II. The aim of this thesis was the generation of HSV-1 retargeted to tumor-specific receptors and detargeted from HSV natural receptors, HVEM and Nectin-1. The retargeting was achieved by inserting a specific single chain antibody (scFv) for the tumor receptor selected inside the HSV glycoprotein gD. In this research three tumor receptors were considered: epidermal growth factor receptor 2 (HER2) overexpressed in 25-30% of breast and ovarian cancers and gliomas, prostate specific membrane antigen (PSMA) expressed in prostate carcinomas and in neovascolature of solid tumors; and epidermal growth factor receptor variant III (EGFRvIII). In vivo studies on HER2 retargeted viruses R-LM113 and R-LM249 have demonstrated their high safety profile. For R-LM249 the antitumor efficacy has been highlighted by target-specific inhibition of the growth of human tumors in models of HER2-positive breast and ovarian cancer in nude mice. In a murine model of HER2-positive glioma in nude mice, R-LM113 was able to significantly increase the survival time of treated mice compared to control. Up to now, PSMA and EGFRvIII viruses (R-LM593 and R-LM613) are only characterized in vitro, confirming the specific retargeting to selected targets. This strategy has proved to be generally applicable to a broad spectrum of receptors for which a single chain antibody is available.