Gene interactions constrain the course of evolution of phosphine resistance in the lesser grain borer, Rhyzopertha dominica

Phosphine, a widely used fumigant for the protection of stored grain from insect pests, kills organisms indirectly by inducing oxidative stress. High levels of heritable resistance to phosphine in the insect pest of stored grain, Rhyzopertha dominica have been detected in Asia, Australia and South America. In order to understand the evolution of phosphine resistance and to isolate the responsible genes, we have undertaken genetic linkage analysis of fully sensitive (QRD14), moderately resistant (QRD369) and highly resistant (QRD569) strains of R. dominica collected in Australia. We previously determined that two loci, rph1 and rph2, confer high-level resistance on strain QRD569, which was collected in 1997. We have now confirmed that rph1 is responsible for the moderate resistance of strain QRD369, which was collected in 1990, and is shared with a highly resistant strain from the same geographical region, QRD569. In contrast, rph2 by itself confers only very weak resistance, either as a heterozygote or as a homozygote and was not discovered in the field until weak resistance (probably due to rph1) had become ubiquitous. Thus, high-level resistance against phosphine has evolved via stepwise acquisition of resistance alleles, first at rph1 and thereafter at rph2. The semi-dominance of rph2 together with the synergistic interaction between rph1 and rph2 would have led to rapid selection for homozygosity. A lack of visible fitness cost associated with alleles at either locus suggests that the resistance phenotype will persist in the field.

Phosphine Resistance in the Rust Red Flour Beetle, Tribolium castaneum (Coleoptera: Tenebrionidae): Inheritance, Gene Interactions and Fitness Costs

The recent emergence of heritable high level resistance to phosphine in stored grain pests is a serious concern among major grain growing countries around the world. Here we describe the genetics of phosphine resistance in the rust red flour beetle Tribolium castaneum (Herbst), a pest of stored grain as well as a genetic model organism. We investigated three field collected strains of T. castaneum viz., susceptible (QTC4), weakly resistant (QTC1012) and strongly resistant (QTC931) to phosphine. The dose-mortality responses of their test- and inter-cross progeny revealed that most resistance was conferred by a single major resistance gene in the weakly (3.2x) resistant strain. This gene was also found in the strongly resistant (431x) strain, together with a second major resistance gene and additional minor factors. The second major gene by itself confers only 12-206x resistance, suggesting that a strong synergistic epistatic interaction between the genes is responsible for the high level of resistance (431x) observed in the strongly resistant strain. Phosphine resistance is not sex linked and is inherited as an incompletely recessive, autosomal trait. The analysis of the phenotypic fitness response of a population derived from a single pair inter-strain cross between the susceptible and strongly resistant strains indicated the changes in the level of response in the strong resistance phenotype; however this effect was not consistent and apparently masked by the genetic background of the weakly resistant strain. The results from this work will inform phosphine resistance management strategies and provide a basis for the identification of the resistance genes.

Triacylglycerol-rich lipoprotein-gene interactions in endothelial cells

Lipoproteins such as LDL (low-density lipoprotein) and oxidized LDL have potentially adverse effects on endothelial cells due to their ability to activate pro-inflammatory pathways regulated via the transcription factor NF-kappaB (nuclear factor kappaB). Triacylglycerol-rich lipoproteins (the chylomicrons, very-low-density lipoprotein and their respective remnant particles) have also been implicated in the induction of a pro-inflammatory phenotype and up-regulation of adhesion molecule expression. Although early studies supported the proposal that LPL (lipoprotein lipase)-mediated hydrolysis of TRLs (triglyceride-rich lipoproteins) at the endothelium could activate the NFkappaB pathway, more recent studies provide evidence of pro-and anti-inflammatory responses when cells are exposed to fatty acids of TRL particles. A large number of genes are up- and down-regulated when cells are exposed to TRL, with the net effect reflecting receptor- and nonreceptor-mediated pathways that are activated or inhibited depending on fatty acid type, the lipid and apolipoprotein composition of the TRL and the presence or absence of LPL. Early concepts of TRL particles as essentially pro-inflammatory stimuli to the endothelium provide an overly simplistic view of their impact on the vascular compartment.

Nutrient gene interactions in lipid metabolism

Purpose of review To summarize recent findings relating to the impact of dietary fat composition on whole body lipid metabolism, and common gene variants on the blood lipid response to dietary fat change. Recent findings In recent years a more comprehensive understanding of the impact of polyunsaturated fat (PUFA) intake on the regulation of transcription factors involved in lipogenesis and fatty acid and lipoprotein metabolism has emerged. The evidence is suggestive of a greater potency of the long chain n-3 PUFA eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), and in particular their oxidative products, relative to n-6 Pi In the area of nutrigenetics a number of common gene variants have been identified which may be important determinants of the blood lipid response to altered dietary fat composition. However, confirmation of associations in independent cohorts, and an understanding of the size effect of individual or combinations of genotypes, is often lacking. Summary Although in the future, genotyping holds the potential as a public health tool to target and personalize dietary advice, nutrigenetics is a relatively new science, and further research is needed to address the existing inconsistencies and knowledge gaps.

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.

Detecting reliable gene interactions by a hierarchy of Bayesian network classifiers

The main purpose of a gene interaction network is to map the relationships of the genes that are out of sight when a genomic study is tackled. DNA microarrays allow the measure of gene expression of thousands of genes at the same time. These data constitute the numeric seed for the induction of the gene networks. In this paper, we propose a new approach to build gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling. The interactions induced by the Bayesian classifiers are based both on the expression levels and on the phenotype information of the supervised variable. Feature selection and bootstrap resampling add reliability and robustness to the overall process removing the false positive findings. The consensus among all the induced models produces a hierarchy of dependences and, thus, of variables. Biologists can define the depth level of the model hierarchy so the set of interactions and genes involved can vary from a sparse to a dense set. Experimental results show how these networks perform well on classification tasks. The biological validation matches previous biological findings and opens new hypothesis for future studies

Specificity in transforming growth factor β-induced transcription of the plasminogen activator inhibitor-1 gene: Interactions of promoter DNA, transcription factor μE3, and Smad proteins

Transforming growth factor β (TGF-β) regulates a broad range of biological processes, including cell growth, development, differentiation, and immunity. TGF-β signals through its cell surface receptor serine kinases that phosphorylate Smad2 or Smad3 proteins. Because Smad3 and its partner Smad4 bind to only 4-bp Smad binding elements (SBEs) in DNA, a central question is how specificity of TGF-β-induced transcription is achieved. We show that Smad3 selectively binds to two of the three SBEs in PE2.1, a TGF-β-inducible fragment of the plasminogen activator inhibitor-1 promoter, to mediate TGF-β-induced transcription; moreover, a precise 3-bp spacer between one SBE and the E-box, a binding site for transcription factor μE3 (TFE3), is essential for TGF-β-induced transcription. Whereas an isolated Smad3 MH1 domain binds to TFE3, TGF-β receptor-mediated phosphorylation of full-length Smad3 enhances its binding to TFE3. Together, these studies elucidate an important mechanism for specificity in TGF-β-induced transcription of the plasminogen activator inhibitor-1 gene.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

Candidate gene studies on cardiovascular traits

Cardiovascular diseases (CVD) are a major cause of death and disability in Western countries and a growing health problem in the developing world. The genetic component of both coronary heart disease (CHD) and ischemic stroke events has been established in twin studies, and the traits predisposing to CVD, such as hypertension, dyslipidemias, obesity, diabetes, and smoking behavior, are all partly hereditary. Better understanding of the pathophysiology of CVD-related traits could help to target disease prevention and clinical treatment to individuals at an especially high disease risk and provide novel pharmaceutical interventions. This thesis aimed to clarify the genetic background of CVD at a population level using large Nordic population cohorts and a candidate gene approach. The first study concentrated on the allelic diversity of the thrombomodulin (THBD) gene in two Finnish cohorts, FINRISK-92 and FINRISK-97. The results from this study implied that THBD variants do not substantially contribute to CVD risk. In the second study, three other candidate genes were added to the analyses. The study investigated the epistatic effects of coagulation factor V (F5), intercellular adhesion molecule -1 (ICAM1), protein C (PROC), and THBD in the same FINRISK cohorts. The results were encouraging; we were able to identify several single SNPs and SNP combinations associating with CVD and mortality. Interestingly, THBD variants appeared in the associating SNP combinations despite the negative results from Study I, suggesting that THBD contributes to CVD through gene-gene interactions. In the third study, upstream transcription factor -1 (USF1) was analyzed in a cohort of Swedish men. USF1 was associated with metabolic syndrome, characterized by accumulation of different CVD risk factors. A putative protective and a putative risk variant were identified. A direct association with CVD was not observed. The longitudinal nature of the study also clarified the effect of USF1 variants on CVD risk factors followed in four examinations throughout adulthood. The three studies provided valuable information on the study of complex traits, highlighting the use of large study samples, the importance of replication, and the full coverage of the major allelic variants of the target genes to assure reliable findings. Although the genetic basis of coronary heart disease and ischemic stroke remains unknown, single genetic findings may facilitate the recognition of high-risk subgroups.

Associations of gene polymorphisms and nutrition with calcium homeostasis and bone mineral density : Studies on skeletal nutrigenetics

Heredity explains a major part of the variation in calcium homeostasis and bone strength, and the susceptibility to osteoporosis is polygenetically regulated. Bone phenotype results from the interplay between lifestyle and genes, and several nutritional factors modulate bone health throughout life. Thus, nutrigenetics examining the genetic variation in nutrient intake and homeostatic control is an important research area in the etiology of osteoporosis. Despite continuing progress in the search for candidate genes for osteoporosis, the results thus far have been inconclusive. The main objective of this thesis was to investigate the associations of lactase, vitamin D receptor (VDR), calcium sensing receptor (CaSR) and parathyroid hormone (PTH) gene polymorphisms and lifestyle factors and their interactions with bone health in Finns at varying stages of the skeletal life span. Markers of calcium homeostasis and bone remodelling were measured from blood and urine samples. Bone strength was measured at peripheral and central bone sites. Lifestyle factors were assessed with questionnaires and interviews. Genetic lactase non-persistence (the C/C-13910 genotype) was associated with lower consumption of milk from childhood, predisposing females in particular to inadequate calcium intake. Consumption of low-lactose milk and milk products was shown to decrease the risk for inadequate calcium intake. In young adulthood, bone loss was more common in males than in females. Males with the lactase C/C-13910 genotype may be more susceptible to bone loss than males with the other lactase genotypes, although calcium intake predicts changes in bone mass more than the lactase genotype. The BsmI and FokI polymorphisms of the VDR gene were associated with bone mass in growing adolescents, but the associations weakened with age. In young adults, the A986S polymorphism of the calcium sensing receptor gene was associated with serum ionized calcium concentrations, and the BstBI polymorphism of the parathyroid gene was related to bone strength. The FokI polymorphism and sodium intake showed an interaction effect on urinary calcium excretion. A novel gene-gene interaction between the VDR FokI and PTH BstBI gene polymorphisms was found in the regulation of PTH secretion and urinary calcium excretion. Further research should be carried out with more number of Finns at varying stages of the skeletal life span and more detailed measurements of bone strength. Research should concern mechanisms by which genetic variants affect calcium homeostasis and bone strength, and the role of diet-gene and gene-gene interactions in the pathogenesis of osteoporosis.

Site-directed gene integration in transgenic zebrafish mediated by cre recombinase using a combination of mutant Lox sites

With current gene-transfer techniques in fish, insertion of DNA into the genome occurs randomly and in many instances at multiple sites. Associated position effects, copy number differences, and multiple gene interactions make gene expression experiments difficult to interpret and fish phenotype less predictable. To meet different fish engineering needs, we describe here a gene targeting model in zebrafish. At first, four target zebrafish lines, each harboring a single genomic lox71 target site, were generated by zebrafish transgenesis. The zygotes of transgenic zebrafish lines were coinjected with capped Cre mRNA and a knockin vector pZklox66RFP. Site-specific integration event happened from one target zebrafish line. In this line two integrant zebrafish were obtained from more than 80,000 targeted embryos (integrating efficiency about 10(-4) to 10(-5)) and confirmed to have a sole copy of the integrating DNA at the target genome site. Genomic polymerase chain reaction analysis and DNA sequencing verified the correct gene target events where lox71 and lox66 have accurately recombined into double mutant lox72 and wild-type loxP. Each integrant zebrafish chosen for analysis harbored the transgene rfp at the designated egfp concatenates. Although the Cre-mediated recombination is site specific, it is dependent on a randomly placed target site. That is, a genomic target cannot be preselected for integration based solely on its sequence. Conclusively, an rfp reporter gene was successfully inserted into the egfp target locus of zebrafish genome by Cre-lox-mediated recombination. This site-directed knockin system using the lox71/lox66 combination should be a promising gene-targeting platform serving various purposes in fish genetic engineering.