Enhancement of stress tolerance in transgenic tobacco plants constitutively expressing AtIpk2β, an inositol polyphosphate 6-/3-kinase from Arabidopsis thaliana

Inositol phosphates (IPs) and their turnover products have been implicated to play important roles in stress signaling in eukaryotic cells. In higher plants genes encoding inositol polyphosphate kinases have been identified previously, but their physiological functions have not been fully resolved. Here we expressed Arabidopsis inositol polyphosphate 6-/3-kinase (AtIpk2β) in two heterologous systems, i.e. the yeast Saccharomycescerevisiae and in tobacco (Nicotiana tabacum), and tested the effect on abiotic stress tolerance. Expression of AtIpk2β rescued the salt-, osmotic- and temperature-sensitive growth defects of a yeast mutant strain (arg82Δ) that lacks inositol polyphosphate multikinase activity encoded by the ARG82/IPK2 gene. Transgenic tobacco plants constitutively expressing AtIpk2β under the control of the Cauliflower Mosaic Virus 35S promoter were generated and found to exhibit improved tolerance to diverse abiotic stresses when compared to wild type plants. Expression patterns of various stress responsive genes were enhanced, and the activities of anti-oxidative enzymes were elevated in transgenic plants, suggesting a possible involvement of AtIpk2β in plant stress responses

QTL Mapping of Combining Ability and Heterosis of Agronomic Traits in Rice Backcross Recombinant Inbred Lines and Hybrid Crosses

BACKGROUND: Combining ability effects are very effective genetic parameters in deciding the next phase of breeding programs. Although some breeding strategies on the basis of evaluating combining ability have been utilized extensively in hybrid breeding, little is known about the genetic basis of combining ability. Combining ability is a complex trait that is controlled by polygenes. With the advent and development of molecular markers, it is feasible to evaluate the genetic bases of combining ability and heterosis of elite rice hybrids through QTL analysis. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we first developed a QTL-mapping method for dissecting combining ability and heterosis of agronomic traits. With three testcross populations and a BCRIL population in rice, biometric and QTL analyses were conducted for ten agronomic traits. The significance of general combining ability and special combining ability for most of the traits indicated the importance of both additive and non-additive effects on expression levels. A large number of additive effect QTLs associated with performance per se of BCRIL and general combining ability, and dominant effect QTLs associated with special combining ability and heterosis were identified for the ten traits. CONCLUSIONS/SIGNIFICANCE: The combining ability of agronomic traits could be analyzed by the QTL mapping method. The characteristics revealed by the QTLs for combining ability of agronomic traits were similar with those by multitudinous QTLs for agronomic traits with performance per se of BCRIL. Several QTLs (1-6 in this study) were identified for each trait for combining ability. It demonstrated that some of the QTLs were pleiotropic or linked tightly with each other. The identification of QTLs responsible for combining ability and heterosis in the present study provides valuable information for dissecting genetic basis of combining ability

The Genome of Ganderma lucidum Provide Insights into Triterpense Biosynthesis and Wood Degradation

BACKGROUND: Ganoderma lucidum (Reishi or Ling Zhi) is one of the most famous Traditional Chinese Medicines and has been widely used in the treatment of various human diseases in Asia countries. It is also a fungus with strong wood degradation ability with potential in bioenergy production. However, genes, pathways and mechanisms of these functions are still unknown. METHODOLOGY/PRINCIPAL FINDINGS: The genome of G. lucidum was sequenced and assembled into a 39.9 megabases (Mb) draft genome, which encoded 12,080 protein-coding genes and ∼83% of them were similar to public sequences. We performed comprehensive annotation for G. lucidum genes and made comparisons with genes in other fungi genomes. Genes in the biosynthesis of the main G. lucidum active ingredients, ganoderic acids (GAs), were characterized. Among the GAs synthases, we identified a fusion gene, the N and C terminal of which are homologous to two different enzymes. Moreover, the fusion gene was only found in basidiomycetes. As a white rot fungus with wood degradation ability, abundant carbohydrate-active enzymes and ligninolytic enzymes were identified in the G. lucidum genome and were compared with other fungi. CONCLUSIONS/SIGNIFICANCE: The genome sequence and well annotation of G. lucidum will provide new insights in function analyses including its medicinal mechanism. The characterization of genes in the triterpene biosynthesis and wood degradation will facilitate bio-engineering research in the production of its active ingredients and bioenergy

A Novel Statistic for Genome-Wide Interaction Analysis

Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001<FDR<0.003, respectively, which were seen in two independent studies of psoriasis. These included five interacting pairs of SNPs in genes LST1/NCR3, CXCR5/BCL9L, and GLS2, some of which were located in the target sites of miR-324-3p, miR-433, and miR-382, as well as 15 pairs of interacting SNPs that had nonsynonymous substitutions. Our results demonstrated that genome-wide interaction analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies

A gene frequency model for QTL mapping using Bayesian inference

<p>Abstract</p> <p>Background</p> <p>Information for mapping of quantitative trait loci (QTL) comes from two sources: linkage disequilibrium (non-random association of allele states) and cosegregation (non-random association of allele origin). Information from LD can be captured by modeling conditional means and variances at the QTL given marker information. Similarly, information from cosegregation can be captured by modeling conditional covariances. Here, we consider a Bayesian model based on gene frequency (BGF) where both conditional means and variances are modeled as a function of the conditional gene frequencies at the QTL. The parameters in this model include these gene frequencies, additive effect of the QTL, its location, and the residual variance. Bayesian methodology was used to estimate these parameters. The priors used were: logit-normal for gene frequencies, normal for the additive effect, uniform for location, and inverse chi-square for the residual variance. Computer simulation was used to compare the power to detect and accuracy to map QTL by this method with those from least squares analysis using a regression model (LSR).</p> <p>Results</p> <p>To simplify the analysis, data from unrelated individuals in a purebred population were simulated, where only LD information contributes to map the QTL. LD was simulated in a chromosomal segment of 1 cM with one QTL by random mating in a population of size 500 for 1000 generations and in a population of size 100 for 50 generations. The comparison was studied under a range of conditions, which included SNP density of 0.1, 0.05 or 0.02 cM, sample size of 500 or 1000, and phenotypic variance explained by QTL of 2 or 5%. Both 1 and 2-SNP models were considered. Power to detect the QTL for the BGF, ranged from 0.4 to 0.99, and close or equal to the power of the regression using least squares (LSR). Precision to map QTL position of BGF, quantified by the mean absolute error, ranged from 0.11 to 0.21 cM for BGF, and was better than the precision of LSR, which ranged from 0.12 to 0.25 cM.</p> <p>Conclusions</p> <p>In conclusion given a high SNP density, the gene frequency model can be used to map QTL with considerable accuracy even within a 1 cM region.</p

A Robust Statistical Method for Association-Based eQTL Analysis

Background: It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS) is statistical inference of linkage disequilibrium (LD) between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation. Methodology: We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations. Results/Conclusions: The analyses show that the new method confers an improved statistical power for detecting genuin

Modeling mitochondrial dysfunctions in the brain: from mice to men

The biologist Lewis Thomas once wrote: “my mitochondria comprise a very large proportion of me. I cannot do the calculation, but I suppose there is almost as much of them in sheer dry bulk as there is the rest of me”. As humans, or indeed as any mammal, bird, or insect, we contain a specific molecular makeup that is driven by vast numbers of these miniscule powerhouses residing in most of our cells (mature red blood cells notwithstanding), quietly replicating, living independent lives and containing their own DNA. Everything we do, from running a marathon to breathing, is driven by these small batteries, and yet there is evidence that these molecular energy sources were originally bacteria, possibly parasitic, incorporated into our cells through symbiosis. Dysfunctions in these organelles can lead to debilitating, and sometimes fatal, diseases of almost all the bodies’ major organs. Mitochondrial dysfunction has been implicated in a wide variety of human disorders either as a primary cause or as a secondary consequence. To better understand the role of mitochondrial dysfunction in human disease, a multitude of pharmacologically induced and genetically manipulated animal models have been developed showing to a greater or lesser extent the clinical symptoms observed in patients with known and unknown causes of the disease. This review will focus on diseases of the brain and spinal cord in which mitochondrial dysfunction has been proven or is suspected and on animal models that are currently used to study the etiology, pathogenesis and treatment of these diseases

Molecular biology of the blood-brain and the blood-cerebrospinal fluid barriers: similarities and differences

Efficient processing of information by the central nervous system (CNS) represents an important evolutionary advantage. Thus, homeostatic mechanisms have developed that provide appropriate circumstances for neuronal signaling, including a highly controlled and stable microenvironment. To provide such a milieu for neurons, extracellular fluids of the CNS are separated from the changeable environment of blood at three major interfaces: at the brain capillaries by the blood-brain barrier (BBB), which is localized at the level of the endothelial cells and separates brain interstitial fluid (ISF) from blood; at the epithelial layer of four choroid plexuses, the blood-cerebrospinal fluid (CSF) barrier (BCSFB), which separates CSF from the CP ISF, and at the arachnoid barrier. The two barriers that represent the largest interface between blood and brain extracellular fluids, the BBB and the BCSFB, prevent the free paracellular diffusion of polar molecules by complex morphological features, including tight junctions (TJs) that interconnect the endothelial and epithelial cells, respectively. The first part of this review focuses on the molecular biology of TJs and adherens junctions in the brain capillary endothelial cells and in the CP epithelial cells. However, normal function of the CNS depends on a constant supply of essential molecules, like glucose and amino acids from the blood, exchange of electrolytes between brain extracellular fluids and blood, as well as on efficient removal of metabolic waste products and excess neurotransmitters from the brain ISF. Therefore, a number of specific transport proteins are expressed in brain capillary endothelial cells and CP epithelial cells that provide transport of nutrients and ions into the CNS and removal of waste products and ions from the CSF. The second part of this review concentrates on the molecular biology of various solute carrier (SLC) transport proteins at those two barriers and underlines differences in their expression between the two barriers. Also, many blood-borne molecules and xenobiotics can diffuse into brain ISF and then into neuronal membranes due to their physicochemical properties. Entry of these compounds could be detrimental for neural transmission and signalling. Thus, BBB and BCSFB express transport proteins that actively restrict entry of lipophilic and amphipathic substances from blood and/or remove those molecules from the brain extracellular fluids. The third part of this review concentrates on the molecular biology of ATP-binding cassette (ABC)-transporters and those SLC transporters that are involved in efflux transport of xenobiotics, their expression at the BBB and BCSFB and differences in expression in the two major blood-brain interfaces. In addition, transport and diffusion of ions by the BBB and CP epithelium are involved in the formation of fluid, the ISF and CSF, respectively, so the last part of this review discusses molecular biology of ion transporters/exchangers and ion channels in the brain endothelial and CP epithelial cells