Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Study of cerebral gene expression densities using Voronoi analysis

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved.

Interaction among nitric oxide (NO)-related genes in migraine susceptibility

The pathogenic mechanisms involved in migraine are complex and not completely clarified. Because there is evidence for the involvement of nitric oxide (NO) in migraine pathophysiology, candidate gene approaches focusing on genes affecting the endothelial function have been studied including the genes encoding endothelial NO synthase (eNOS), inducible NO synthase (iNOS), and vascular endothelial growth factor (VEGF). However, investigations on gene-gene interactions are warranted to better elucidate the genetic basis of migraine. This study aimed at characterizing interactions among nine clinically relevant polymorphisms in eNOS (T-786C/rs2070744, the 27 bp VNTR in intron 4, the Glu298Asp/rs1799983, and two additional tagSNPs rs3918226 and rs743506), iNOS (C(-1026)A/rs2779249 and G2087A/rs2297518), and VEGF (C(-2578)A/rs699947 and G(-634)C/rs2010963) in migraine patients and control group. Genotypes were determined by real-time polymerase chain reaction using the Taqman(A (R)) allele discrimination assays or PCR and fragment separation by electrophoresis in 99 healthy women without migraine (control group) and in 150 women with migraine divided into two groups: 107 with migraine without aura and 43 with aura. The multifactor dimensionality reduction method was used to detect and characterize gene-gene interactions. We found a significant interaction between eNOS rs743506 and iNOS 2087G/A polymorphisms in migraine patients compared to control group (P < 0.05), suggesting that this combination affect the susceptibility to migraine. Further studies are needed to determine the molecular mechanisms explaining this interaction.

Epistasis among eNOS, MMP-9 and VEGF maternal genotypes in hypertensive disorders of pregnancy

Polymorphisms of the endothelial nitric oxide synthase (eNOS), matrix metalloproteinase-9 (MMP-9) and vascular endothelial growth factor (VEGF) genes were shown to be associated with hypertensive disorders of pregnancy. However, epistasis is suggested to be an important component of the genetic susceptibility to preeclampsia (PE). The aim of this study was to characterize the interactions among these genes in PE and gestational hypertension (GH). Seven clinically relevant polymorphisms of eNOS (T-786C, rs2070744, a variable number of tandem repeats in intron 4 and Glu298Asp, rs1799983), MMP-9 (C-1562T, rs3918242 and -90(CA)(13-25), rs2234681) and VEGF (C-2578A, rs699947 and G-634C, rs2010963) were genotyped by TaqMan allelic discrimination assays or PCR and fragment separation by electrophoresis in 122 patients with PE, 107 patients with GH and a control group of 102 normotensive pregnant (NP) women. A robust multifactor dimensionality reduction analysis was used to characterize gene-gene interactions. Although no significant genotype combinations were observed for the comparison between the GH and NP groups (P>0.05), the combination of MMP-9-1562CC with VEGF-634GG was more frequent in NP women than in women with PE (P<0.05). Moreover, the combination of MMP-9-1562CC with VEGF-634CC or MMP-9-1562CT with VEGF-634CC or-634GG was more frequent in women with PE than in NP women (P<0.05). These results are obscured when single polymorphisms in these genes are considered and suggest that specific genotype combinations of MMP-9 and VEGF contribute to PE susceptibility. Hypertension Research (2012) 35, 917-921; doi:10.1038/hr.2012.60; published online 10 May 2012

Association of AXIN2 with Non-syndromic Oral Clefts in Multiple Populations

We have previously shown the association of AXIN2 with oral clefts in a US population. Here, we expanded our study to explore the association of 11 AXIN2 markers in 682 cleft families from multiple populations. Alleles for each AXIN2 marker were tested for transmission distortion with clefts by means of the Family-based Association Test. We observed an association with SNP rs7224837 and all clefts in the combined populations (p = 0.001), and with SNP rs3923086 and cleft lip and palate in Asian populations (p = 0.004). We confirmed our association findings in an additional 528 cleft families from the United States (p < 0.009). We tested for gene-gene interaction between AXIN2 and additional cleft susceptibility loci. We assessed and detected Axin2 mRNA and protein expression during murine palatogenesis. In addition, we also observed co-localization of Axin2 with Irf6 proteins, particularly in the epithelium. Our results continue to support a role for AXIN2 in the etiology of human clefting. Additional studies should be performed to improve our understanding of the biological mechanisms linking AXIN2 to oral clefts.

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Allelic variations in the vitamin D receptor gene, insulin secretion and parents' heights are independently associated with height in obese children and adolescents

Polymorphisms in the VDR gene were reported to be associated with variations in intrauterine and postnatal growth and with adult height, but also with other traits that are strongly correlated such as the BMI, insulin sensitivity, insulin secretion and hyperglycemia. Here, we assessed the impact of VDR polymorphisms on body height and its interactions with obesity- and glucose tolerance-related traits in obese children and adolescents. We studied 173 prepubertal (Tanner's stage 1) and 146 pubertal (Tanner's stages 2-5) obese children who were referred for a weight-loss program. Three single nucleotide polymorphisms were genotyped: rs1544410 (BsmI), rs7975232 (ApaI) and rs731236 (TaqI). BsmI and TaqI genotypes were significantly associated with height in pubertal children, but the associations did not reach statistical significance in prepubertal children. In stepwise regression analyses, the lean body mass, insulin secretion, BsmI or TaqI genotypes and the father's and the mother's height were independently and positively associated with height in pubertal children. These covariables accounted for 46% of the trait variance. The height of homozygous carriers of the minor allele of BsmI was 0.65 z-scores (4 cm) higher than the height of homozygous carriers of the major allele (P=.0006). Haplotype analyses confirmed the associations of the minor alleles of BsmI and TaqI with increased height. In conclusion, VDR genotypes were significantly associated with height in pubertal obese children. The associations were independent from the effects of confounding traits, such as the body fat mass, insulin secretion, insulin sensitivity and glucose tolerance. (C) 2012 Elsevier Inc. All rights reserved.

Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery

Pellegrino R, Sunaga DY, Guindalini C, Martins RC, Mazzotti DR, Wei Z, Daye ZJ, Andersen ML, Tufik S. Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery. Physiol Genomics 44: 1003-1012, 2012. First published September 4, 2012; doi: 10.1152/physiolgenomics.00058.2012.-Although the specific functions of sleep have not been completely elucidated, the literature has suggested that sleep is essential for proper homeostasis. Sleep loss is associated with changes in behavioral, neurochemical, cellular, and metabolic function as well as impaired immune response. Using high-resolution microarrays we evaluated the gene expression profiles of healthy male volunteers who underwent 60 h of prolonged wakefulness (PW) followed by 12 h of sleep recovery (SR). Peripheral whole blood was collected at 8 am in the morning before the initiation of PW (Baseline), after the second night of PW, and one night after SR. We identified over 500 genes that were differentially expressed. Notably, these genes were related to DNA damage and repair and stress response, as well as diverse immune system responses, such as natural killer pathways including killer cell lectin-like receptors family, as well as granzymes and T-cell receptors, which play important roles in host defense. These results support the idea that sleep loss can lead to alterations in molecular processes that result in perturbation of cellular immunity, induction of inflammatory responses, and homeostatic imbalance. Moreover, expression of multiple genes was downregulated following PW and upregulated after SR compared with PW, suggesting an attempt of the body to re-establish internal homeostasis. In silico validation of alterations in the expression of CETN3, DNAJC, and CEACAM genes confirmed previous findings related to the molecular effects of sleep deprivation. Thus, the present findings confirm that the effects of sleep loss are not restricted to the brain and can occur intensely in peripheral tissues.

Molecular evolution of a malaria resistance gene (DARC) in primates

Genes involved in host-pathogen interactions are often strongly affected by positive natural selection. The Duffy antigen, coded by the Duffy antigen receptor for chemokines (DARC) gene, serves as a receptor for Plasmodium vivax in humans and for Plasmodium knowlesi in some nonhuman primates. In the majority of sub-Saharan Africans, a nucleic acid variant in GATA-1 of the gene promoter is responsible for the nonexpression of the Duffy antigen on red blood cells and consequently resistance to invasion by P. vivax. The Duffy antigen also acts as a receptor for chemokines and is expressed in red blood cells and many other tissues of the body. Because of this dual role, we sequenced a 3,000-bp region encompassing the entire DARC gene as well as part of its 5' and 3' flanking regions in a phylogenetic sample of primates and used statistical methods to evaluate the nature of selection pressures acting on the gene during its evolution. We analyzed both coding and regulatory regions of the DARC gene. The regulatory analysis showed accelerated rates of substitution at several sites near known motifs. Our tests of positive selection in the coding region using maximum likelihood by branch sites and maximum likelihood by codon sites did not yield statistically significant evidence for the action of positive selection. However, the maximum likelihood test in which the gene was subdivided into different structural regions showed that the known binding region for P. vivax/P. knowlesi is under very different selective pressures than the remainder of the gene. In fact, most of the gene appears to be under strong purifying selection, but this is not evident in the binding region. We suggest that the binding region is under the influence of two opposing selective pressures, positive selection possibly exerted by the parasite and purifying selection exerted by chemokines.

Effect of human TGF-beta on the gene expression profile of Schistosoma mansoni adult worms

Schistosoma mansoni is responsible for schistosomiasis, a parasitic disease that affects 200 million people worldwide. Molecular mechanisms of host-parasite interaction are complex and involve a crosstalk between host signals and parasite receptors. TGF-beta signaling pathway has been shown to play an important role in S. mansoni development and embryogenesis. In particular human (h) TGF-beta has been shown to bind to a S. mansoni receptor, transduce a signal that regulates the expression of a schistosome target gene. Here we describe 381 parasite genes whose expression levels are affected by in vitro treatment with hTGF-beta. Among these differentially expressed genes we highlight genes related to morphology, development and cell cycle that could be players of cytokine effects on the parasite. We confirm by qPCR the expression changes detected with microarrays for 5 out of 7 selected genes. We also highlight a set of non-coding RNAs transcribed from the same loci of protein-coding genes that are differentially expressed upon hTCF-beta treatment. These datasets offer potential targets to be explored in order to understand the molecular mechanisms behind the possible role of hTGF-beta effects on parasite biology. (C) 2012 Elsevier B.V. All rights reserved.

Sugarwin: A Sugarcane Insect-Induced Gene with Antipathogenic Activity

In sugarcane fields, colonization of the stalk by opportunistic fungi usually occurs after the caterpillar Diatraea saccharalis attacks the sugarcane plant. Plants respond to insect attack by inducing and accumulating a large set of defense proteins. Two homologues of a barley wound-inducible protein (BARWIN), sugarcane wound-inducible proteins SUGARWIN1 and SUGARWIN2, have been identified in sugarcane by an in silico analysis. Antifungal properties have been described for a number of BARWIN homologues. We report that a SUGARWIN:green fluorescent protein fusion protein is located in the endoplasmic reticulum and in the extracellular space of sugarcane plants. The induction of sugarwin transcripts occurs in response to mechanical wounding, D. saccharalis damage, and methyl jasmonate treatment. The accumulation of transcripts is late induced and is restricted to the site of the wound. Although the transcripts of sugarwin genes were strongly increased following insect attack, the protein itself did not show any effect on insect development; rather, it altered fungal morphology, leading to the apoptosis of the germlings. These results suggest that, in the course of evolution, sugarwin-encoding genes were recruited by sugarcane due to their antipathogenic activity. We rationalize that sugarcane is able to induce sugarwin gene expression in response to D. saccharalis feeding as a concerted plant response to the anticipated invasion by the fungi that typically penetrate the plant stalk after insect damage.

Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: identification of a novel QTL in rat chromosome 5

Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

Abstract Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks.