CONTRASTING PHYLOGEOGRAPHIC PATTERNS IN MITOCHONDRIAL DNA AND MICROSATELLITES: EVIDENCE OF FEMALE PHILOPATRY AND MALE-BIASED GENE FLOW AMONG REGIONAL POPULATIONS OF THE BLUE-AND-YELLOW MACAW (PSITTACIFORMES: ARA ARARAUNA) IN BRAZIL

Comparing the patterns of population differentiation among genetic markers with different modes of inheritance call provide insights into patterns of sex-biased dispersal and gene flow. The blue-and-yellow Macaw (Ara ararauna) is a Neotropical parrot with a broad geographic distribution ill South America. However, little is known about the natural history and current status Of remaining wild populations, including levels of genetic variability. The progressive decline and possible fragmentation of populations may endanger this species in the near future. We analyzed mitochondrial DNA (mtDNA) control-region sequences and six microsatellite 106 Of Blue-and-yellow Macaws sampled throughout their geographic range ill Brazil to describe population genetic Structure, to make inferences about historical demography and dispersal behavior, and to provide insight for conservation efforts. Analyses of population genetic structure based on mtDNA showed evidence of two major populations ill western and eastern Brazil that share a few low-frequency haplotypes. This phylogeographic pattern seems to have originated by the historical isolation of Blue-and-yellow Macaw populations similar to 374,000 years ago and has been maintained by restricted gene flow and female philopatry. By contrast, variation ill biparentally inherited microsatellites was not structured geographically, Male-biased dispersal and female philopatry best explain the different patterns observed in these two markers. Because females disperse less than males, the two regional populations with well-differentiated mtDNA haplogroups should be considered two different management units for conservation purposes. Received 4 November 2007 accepted 10 December 2008.

A novel COL1A1 gene-splicing mutation (c. 1875+1G > C) in a Brazilian patient with osteogenesis imperfecta

Osteogenesis imperfecta is a heterogeneous genetic disorder characterized by bone fragility and deformity, recurrent fractures, blue sclera, short stature, and dentinogenesis imperfecta. Most cases are caused by mutations in COL1A1 and COL1A2 genes. We present a novel splicing mutation in the COL1A1 gene (c. 1875+ 1G>C) in a 16-year-old Brazilian boy diagnosed as a type III osteogenesis imperfecta patient. This splicing mutation and its association with clinical phenotypes will be submitted to the reference database of COL1A1 mutations, which has no other description of this mutation.

Expression of an activating mutation in the gene encoding the K(ATP) channel subunit Kir6.2 in mouse pancreatic beta cells recapitulates neonatal diabetes

Neonatal diabetes is a rare monogenic form of diabetes that usually presents within the first six months of life. It is commonly caused by gain-of-function mutations in the genes encoding the Kir6.2 and SUR1 subunits of the plasmalemmal ATP-sensitive K(+) (K(ATP)) channel. To better understand this disease, we generated a mouse expressing a Kir6.2 mutation (V59M) that causes neonatal diabetes in humans and we used Cre-lox technology to express the mutation specifically in pancreatic beta cells. These beta-V59M mice developed severe diabetes soon after birth, and by 5 weeks of age, blood glucose levels were markedly increased and insulin was undetectable. Islets isolated from beta-V59M mice secreted substantially less insulin and showed a smaller increase in intracellular calcium in response to glucose. This was due to a reduced sensitivity of K(ATP) channels in pancreatic beta cells to inhibition by ATP or glucose. In contrast, the sulfonylurea tolbutamide, a specific blocker of K(ATP) channels, closed K(ATP) channels, elevated intracellular calcium levels, and stimulated insulin release in beta-V59M beta cells, indicating that events downstream of K(ATP) channel closure remained intact. Expression of the V59M Kir6.2 mutation in pancreatic beta cells alone is thus sufficient to recapitulate the neonatal diabetes observed in humans. beta-V59M islets also displayed a reduced percentage of beta cells, abnormal morphology, lower insulin content, and decreased expression of Kir6.2, SUR1, and insulin mRNA. All these changes are expected to contribute to the diabetes of beta-V59M mice. Their cause requires further investigation.

Positive Selection Results in Frequent Reversible Amino Acid Replacements in the G Protein Gene of Human Respiratory Syncytial Virus

Human respiratory syncytial virus (HRSV) is the major cause of lower respiratory tract infections in children under 5 years of age and the elderly, causing annual disease outbreaks during the fall and winter. Multiple lineages of the HRSVA and HRSVB serotypes co-circulate within a single outbreak and display a strongly temporal pattern of genetic variation, with a replacement of dominant genotypes occurring during consecutive years. In the present study we utilized phylogenetic methods to detect and map sites subject to adaptive evolution in the G protein of HRSVA and HRSVB. A total of 29 and 23 amino acid sites were found to be putatively positively selected in HRSVA and HRSVB, respectively. Several of these sites defined genotypes and lineages within genotypes in both groups, and correlated well with epitopes previously described in group A. Remarkably, 18 of these positively selected tended to revert in time to a previous codon state, producing a ""flipflop'' phylogenetic pattern. Such frequent evolutionary reversals in HRSV are indicative of a combination of frequent positive selection, reflecting the changing immune status of the human population, and a limited repertoire of functionally viable amino acids at specific amino acid sites.

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

Identification of the Schistosoma mansoni TNF-Alpha Receptor Gene and the Effect of Human TNF-Alpha on the Parasite Gene Expression Profile

Background: Schistosoma mansoni is the major causative agent of schistosomiasis. The parasite takes advantage of host signals to complete its development in the human body. Tumor necrosis factor-alpha (TNF-alpha) is a human cytokine involved in skin inflammatory responses, and although its effect on the adult parasite's metabolism and egg-laying process has been previously described, a comprehensive assessment of the TNF-alpha pathway and its downstream molecular effects is lacking. Methodology/Principal Findings: In the present work we describe a possible TNF-alpha receptor (TNFR) homolog gene in S. mansoni (SmTNFR). SmTNFR encodes a complete receptor sequence composed of 599 amino acids, and contains four cysteine-rich domains as described for TNFR members. Real-time RT-PCR experiments revealed that SmTNFR highest expression level is in cercariae, 3.5 (+/- 0.7) times higher than in adult worms. Downstream members of the known human TNF-alpha pathway were identified by an in silico analysis, revealing a possible TNF-alpha signaling pathway in the parasite. In order to simulate parasite's exposure to human cytokine during penetration of the skin, schistosomula were exposed to human TNF-alpha just 3 h after cercariae-to-schistosomula in vitro transformation, and large-scale gene expression measurements were performed with microarrays. A total of 548 genes with significantly altered expression were detected, when compared to control parasites. In addition, treatment of adult worms with TNF-alpha caused a significantly altered expression of 1857 genes. Interestingly, the set of genes altered in adults is different from that of schistosomula, with 58 genes in common, representing 3% of altered genes in adults and 11% in 3 h-old early schistosomula. Conclusions/Significance: We describe the possible molecular elements and targets involved in human TNF-alpha effect on S. mansoni, highlighting the mechanism by which recently transformed schistosomula may sense and respond to this host mediator at the site of cercarial penetration into the skin.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Identification of COL6A1 as a differentially expressed gene in human astrocytomas

Diffuse infiltrating gliomas are the most common tumors of the central nervous system. Gliomas are classified by the WHO according to their histopathological and clinical characteristics into four classes: grade I (pilocytic astrocytoma), grade II (diffuse astrocytoma), grade III (anaplastic astrocytoma), and grade IV (glioblastoma multiforme). Several genes have already been correlated with astrocytomas, but many others are yet to be uncovered. By analyzing the public SAGE data from 21 patients, comprising low malignant grade astrocytomas and glioblastomas, we found COL6A1 to be differentially expressed, confirming this finding by real time RT-PCR in 66 surgical samples. To the best of our knowledge, COL6A1 has never been described in gliomas. The expression of this gene has significantly different means when normal glia is compared with low-grade astrocytomas (grades I and II) and high-grade astrocytomas (grades III and IV), with a tendency to be greater in higher grade samples, thus rendering it a powerful tumor marker.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly in patients with heart failure

Background -: Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly and Thr164Ile were suggested to have an effect in heart failure. We evaluated these polymorphisms relative to clinical characteristics and prognosis of alarge cohort of patients with heart failure of different etiologies. Methods -: We studied 501 patients with heart failure of different etiologies. Mean age was 58 years (standard deviation 14.4 years), 298 (60%) were men. Polymorphisms were identified by polymerase chain reaction-restriction fragment length polymorphism. Results -: During the mean follow-up of 12.6 months (standard deviation 10.3 months), 188 (38%) patients died. Distribution of genotypes of polymorphism Arg16Gly was different relative to body mass index (chi(2) = 9.797; p = 0.04). Overall the probability of survival was not significantly predicted by genotypes of Gln27Glu, Arg16Gly, or Thr164Ile. Allele and haplotype analysis also did not disclose any significant difference regarding mortality. Exploratory analysis through classification trees pointed towards a potential association between the Gln27Glu polymorphism and mortality in older individuals. Conclusion -: In this study sample, we were not able to demonstrate an overall influence of polymorphisms Gln27Glu and Arg16Gly of beta-2 receptor gene on prognosis. Nevertheless, Gln27Glu polymorphism may have a potential predictive value in older individuals.

Chromic materials for responsive surface-enhanced resonance Raman scattering systems: a nanometric pH sensor

The use of chromic materials for responsive surface-enhanced resonance Raman scattering (SERRS) based nanosensors is reported. The potential of nano-chromic SERRS is demonstrated with the use of the halochrome methyl yellow to fabricate an ultrasensitive pH optical sensor. Some of the challenges of the incorporation of chromic materials with metal nanostructures are addressed through the use of computational calculations and a comparison to measured SERRS and surface-enhanced Raman scattering (SERS) spectra is presented. A strong correlation between the measured SERRS and the medium's proton concentration is demonstrated for the pH range 2-6. The high sensitivity achieved by the use of resonance Raman conditions is shown through responsive SERRS measurements from only femtolitres of volume and with the concentration of the reporting molecules approaching the single molecule regime.

Effect of different resistance-training regimens on the WNT-signaling pathway

The purpose of the present study was to evaluate the effects of 8 weeks of strength and power training on the expression of genes related to the canonical WNT pathway and beta-catenin protein levels in physically active men. Twenty-five subjects (27.4 +/- A 4.6 years) were balanced based on their relative maximum strength in the squat exercise (squat 1RM/body mass) and randomly assigned to strength training (ST) (n = 10), power training (PT) (n = 10), and control (C) (n = 5) groups. The ST and the PT groups performed high and low intensity squats, respectively, thrice a week, for 8 weeks. Muscle biopsies from the vastus lateralis muscle were collected before and after the training period. Relative strength and power increased similarly in both ST and PT groups (P < 0.001). Fiber cross-sectional area also increased similarly in both ST and PT groups. Gene expression and beta-catenin protein expression levels were assessed by real-time PCR and Western blot. Certain genes were up-regulated in the ST group (WNT1: 6.4-fold, P < 0.0001; SFRP1: 3.3-fold, P < 0.0001 and LEF1: 7.3-fold, P < 0.0001) and also in the PT group (WNT1: 24.9-fold, P < 0.0001; SFRP1: 2.7-fold, P < 0.0001; LEF1: 34.1-fold, P < 0.0001 and Cyclin D1: 7.7-fold, P < 0.001). In addition, the expression of key WNT pathway genes was substantially more responsive to PT than to ST (WNT1: P < 0.0001; LEF1: P < 0.0001 and Cyclin D1: P < 0.001). Finally, the total beta-catenin protein content increased only in the PT group (P < 0.05). Our data indicate that a PT regimen triggers greater responses in key elements of the WNT pathway.

Cuff-induced vascular intima thickening is influenced by titration of the Ace gene in mice

Lacchini S, Heimann AS, Evangelista FS, Cardoso L, Silva GJ, Krieger JE. Cuff-induced vascular intima thickening is influenced by titration of the Ace gene in mice. Physiol Genomics 37: 225-230, 2009. First published March 3, 2009; doi:10.1152/physiolgenomics.90288.2008.-We tested the hypothesis that small changes in angiotensin I-converting enzyme (ACE) expression can alter the vascular response to injury. Male mice containing one, two, three, and four copies of the Ace gene with no detectable vascular abnormality or changes in blood pressure were submitted to cuff-induced femoral artery injury. Femoral thickening was higher in 3- and 4-copy mice (42.4 +/- 4.3% and 45.7 +/- 6.5%, respectively) compared with 1- and 2-copy mice (8.3 +/- 1.3% and 8.5 +/- 0.9%, respectively). Femoral ACE levels from control and injured vessels were assessed in 1- and 3-copy Ace mice, which represent the extremes of the observed response. ACE vascular activity was higher in 3- vs. 1-copy Ace mice (2.4-fold, P < 0.05) in the control uninjured vessel. Upon injury, ACE activity significantly increased in both groups [2.41-fold and 2.14-fold (P < 0.05) for 1- and 3-copy groups, respectively] but reached higher levels in 3- vs. 1-copy Ace mice (P < 0.05). Pharmacological interventions were then used as a counterproof and to indirectly assess the role of angiotensin II (ANG II) on this response. Interestingly, ACE inhibition (enalapril) and ANG II AT(1) receptor blocker (losartan) reduced intima thickening in 3-copy mice to 1-copy mouse values (P < 0.05) while ANG II treatment significantly increased intima thickening in 1-copy mice to 3-copy mouse levels (P < 0.05). Together, these data indicate that small physiologically relevant changes in ACE, not associated with basal vascular abnormalities or blood pressure levels, do influence the magnitude of cuff-induced neointima thickening in mice.

Exercise training improves muscle vasodilatation in individuals with T786C polymorphism of endothelial nitric oxide synthase gene

Negrão M.V, Alves CR, Alves G.B, Pereira A.C, Dias R.G, Laterza M.C, Mota G.F, Oliveira E.M, Bassaneze V, Krieger J.E, Negrão C.E, Rondon M.U.P. Exercise training improves muscle vasodilatation in individuals with T786C polymorphism of endothelial nitric oxide synthase gene. Physiol Genomics 42A: 71-77, 2010. First published July 6, 2010; doi:10.1152/physiolgenomics.00145.2009.-Allele T at promoter region of the eNOS gene has been associated with an increase in coronary disease mortality, suggesting that this allele increases susceptibility for endothelial dysfunction. In contrast, exercise training improves endothelial function. Thus, we hypothesized that: 1) Muscle vasodilatation during exercise is attenuated in individuals homozygous for allele T, and 2) Exercise training improves muscle vasodilatation in response to exercise for TT genotype individuals. From 133 preselected healthy individuals genotyped for the T786C polymorphism, 72 participated in the study: TT (n = 37; age 27 +/- 1 yr) and CT + CC (n = 35; age 26 +/- 1 yr). Forearm blood flow (venous occlusion plethysmography) and blood pressure (oscillometric automatic cuff) were evaluated at rest and during 30% handgrip exercise. Exercise training consisted of three sessions per week for 18 wk, with intensity between anaerobic threshold and respiratory compensation point. Resting forearm vascular conductance (FVC, P = 0.17) and mean blood pressure (P = 0.70) were similar between groups. However, FVC responses during handgrip exercise were significantly lower in TT individuals compared with CT + CC individuals (0.39 +/- 0.12 vs. 1.08 +/- 0.27 units, P = 0.01). Exercise training significantly increased peak VO(2) in both groups, but resting FVC remained unchanged. This intervention significantly increased FVC response to handgrip exercise in TT individuals (P = 0.03), but not in CT + CC individuals (P = 0.49), leading to an equivalent FVC response between TT and CT + CC individuals (1.05 +/- 0.18 vs. 1.59 +/- 0.27 units, P = 0.27). In conclusion, exercise training improves muscle vasodilatation in response to exercise in TT genotype individuals, demonstrating that genetic variants influence the effects of interventions such as exercise training.