Structure of hadron resonances with a nearby zero of the amplitude

We discuss the relation between the analytic structure of the scattering amplitude and the origin of an eigenstate represented by a pole of the amplitude.If the eigenstate is not dynamically generated by the interaction in the channel of interest, the residue of the pole vanishes in the zero coupling limit. Based on the topological nature of the phase of the scattering amplitude, we show that the pole must encounter with the Castillejo-Dalitz-Dyson (CDD) zero in this limit. It is concluded that the dynamical component of the eigenstate is small if a CDD zero exists near the eigenstate pole. We show that the line shape of the resonance is distorted from the Breit-Wigner form as an observable consequence of the nearby CDD zero. Finally, studying the positions of poles and CDD zeros of the KbarN-piSigma amplitude, we discuss the origin of the eigenstates in the Lambda(1405) region.Comment: 7 pages, 3 figures, v2: published versio

RNAi screening identifies Trypanosoma brucei stress response protein kinases required for survival in the mouse

Protein kinases (PKs) are a class of druggable targets in Trypanosoma brucei, the causative agent of Human African Trypanosomiasis (sleeping sickness), yet little is known about which PKs are essential for survival in mammals. A recent kinome-wide RNAi screen with 176 individual bloodstream form Trypanosoma brucei lines identified PKs required for proliferation in culture. In order to assess which PKs are also potential virulence factors essential in vivo, lines were pooled, inoculated into mice, and screened for loss of fitness after 48 h RNAi. The presence of trypanosomes in the bloodstream was assessed using RNAi target sequencing (RITseq) and compared to growth in culture. We identified 49 PKs with a significant loss of fitness in vivo in two independent experiments, and a strong correlation between in vitro and in vivo loss of fitness for the majority. Nine PKs had a more pronounced growth defect in vivo, than in vitro. Amongst these PKs were several with putative functions related to stress responses mediated through the PI3K/TOR or MAPK signaling cascades, which act to protect the parasite from complement-mediated and osmotic lysis. Identification of these virulence-associated PKs provides new insights into T. brucei-host interaction and reveals novel potential protein kinase drug targets

Novel Cβ–Cγ Bond Cleavages of Tryptophan-Containing Peptide Radical Cations

In this study, we observed unprecedented cleavages of the Cβ–Cγ bonds of tryptophan residue side chains in a series of hydrogen-deficient tryptophan-containing peptide radical cations (M•+) during low-energy collision-induced dissociation (CID). We used CID experiments and theoretical density functional theory (DFT) calculations to study the mechanism of this bond cleavage, which forms [M – 116]+ ions. The formation of an α-carbon radical intermediate at the tryptophan residue for the subsequent Cβ–Cγ bond cleavage is analogous to that occurring at leucine residues, producing the same product ions; this hypothesis was supported by the identical product ion spectra of [LGGGH – 43]+ and [WGGGH – 116]+, obtained from the CID of [LGGGH]•+ and [WGGGH]•+, respectively. Elimination of the neutral 116-Da radical requires inevitable dehydrogenation of the indole nitrogen atom, leaving the radical centered formally on the indole nitrogen atom ([Ind]•-2), in agreement with the CID data for [WGGGH]•+ and [W1-CH3GGGH]•+; replacing the tryptophan residue with a 1-methyltryptophan residue results in a change of the base peak from that arising from a neutral radical loss (116 Da) to that arising from a molecule loss (131 Da), both originating from Cβ–Cγ bond cleavage. Hydrogen atom transfer or proton transfer to the γ-carbon atom of the tryptophan residue weakens the Cβ–Cγ bond and, therefore, decreases the dissociation energy barrier dramatically

Identification of QTLs controlling gene expression networks defined a priori

BACKGROUND: Gene expression microarrays allow the quantification of transcript accumulation for many or all genes in a genome. This technology has been utilized for a range of investigations, from assessments of gene regulation in response to genetic or environmental fluctuation to global expression QTL (eQTL) analyses of natural variation. Current analysis techniques facilitate the statistical querying of individual genes to evaluate the significance of a change in response, also known as differential expression. Since genes are also known to respond as groups due to their membership in networks, effective approaches are needed to investigate transcriptome variation as related to gene network responses. RESULTS: We describe a statistical approach that is capable of assessing higher-order a priori defined gene network response, as measured by microarrays. This analysis detected significant network variation between two Arabidopsis thaliana accessions, Bay-0 and Shahdara. By extending this approach, we were able to identify eQTLs controlling network responses for 18 out of 20 a priori-defined gene networks in a recombinant inbred line population derived from accessions Bay-0 and Shahdara. CONCLUSION: This approach has the potential to be expanded to facilitate direct tests of the relationship between phenotypic trait and transcript genetic architecture. The use of a priori definitions for network eQTL identification has enormous potential for providing direction toward future eQTL analyses

Construction and application for QTL analysis of a Restriction Site Associated DNA (RAD) linkage map in barley

<p>Abstract</p> <p>Background</p> <p>Linkage maps are an integral resource for dissection of complex genetic traits in plant and animal species. Canonical map construction follows a well-established workflow: an initial discovery phase where genetic markers are mined from a small pool of individuals, followed by genotyping of selected mapping populations using sets of marker panels. A newly developed sequence-based marker technology, Restriction site Associated DNA (RAD), enables synchronous single nucleotide polymorphism (SNP) marker discovery and genotyping using massively parallel sequencing. The objective of this research was to assess the utility of RAD markers for linkage map construction, employing barley as a model system. Using the published high density EST-based SNP map in the Oregon Wolfe Barley (OWB) mapping population as a reference, we created a RAD map using a limited set of prior markers to establish linakge group identity, integrated the RAD and prior data, and used both maps for detection of quantitative trait loci (QTL).</p> <p>Results</p> <p>Using the RAD protocol in tandem with the Illumina sequence by synthesis platform, a total of 530 SNP markers were identified from initial scans of the OWB parental inbred lines - the "dominant" and "recessive" marker stocks - and scored in a 93 member doubled haploid (DH) mapping population. RAD sequence data from the structured population was converted into allele genotypes from which a genetic map was constructed. The assembled RAD-only map consists of 445 markers with an average interval length of 5 cM, while an integrated map includes 463 RAD loci and 2383 prior markers. Sequenced RAD markers are distributed across all seven chromosomes, with polymorphic loci emanating from both coding and noncoding regions in the <it>Hordeum </it>genome. Total map lengths are comparable and the order of common markers is identical in both maps. The same large-effect QTL for reproductive fitness traits were detected with both maps and the majority of these QTL were coincident with a dwarfing gene (<it>ZEO) </it>and the <it>VRS1 </it>gene, which determines the two-row and six-row germplasm groups of barley.</p> <p>Conclusions</p> <p>We demonstrate how sequenced RAD markers can be leveraged to produce high quality linkage maps for detection of single gene loci and QTLs. By combining SNP discovery and genotyping into parallel sequencing events, RAD markers should be a useful molecular breeding tool for a range of crop species. Expected improvements in cost and throughput of second and third-generation sequencing technologies will enable more powerful applications of the sequenced RAD marker system, including improvements in <it>de novo </it>genome assembly, development of ultra-high density genetic maps and association mapping.</p

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

Adiposity and Age Explain Most of the Association between Physical Activity and Fitness in Physically Active Men

BACKGROUND: To determine if there is an association between physical activity assessed by the short version of the International Physical Activity Questionnaire (IPAQ) and cardiorespiratory and muscular fitness. METHODOLOGY/PRINCIPAL FINDINGS: One hundred and eighty-two young males (age range: 20-55 years) completed the short form of the IPAQ to assess physical activity. Body composition (dual-energy X-Ray absorptiometry), muscular fitness (static and dynamic muscle force and power, vertical jump height, running speed [30 m sprint], anaerobic capacity [300 m running test]) and cardiorespiratory fitness (estimated VO(2)max: 20 m shuttle run test) were also determined in all subjects. Activity-related energy expenditure of moderate and vigorous intensity (EEPA(moderate) and EEPA(vigorous), respectively) was inversely associated with indices of adiposity (r = -0.21 to -0.37, P<0.05). Cardiorespiratory fitness (VO(2)max) was positively associated with LogEEPA(moderate) (r = 0.26, P<0.05) and LogEEPA(vigorous) (r = 0.27). However, no association between VO(2)max with LogEEPA(moderate), LogEPPA(vigorous) and LogEEPA(total) was observed after adjusting for the percentage of body fat. Multiple stepwise regression analysis to predict VO(2)max from LogEEPA(walking), LogEEPA(moderate), LogEEPA(vigorous), LogEEPA(total), age and percentage of body fat (%fat) showed that the %fat alone explained 62% of the variance in VO(2)max and that the age added another 10%, while the other variables did not add predictive value to the model [VO(2)max  = 129.6-(25.1× Log %fat) - (34.0× Log age); SEE: 4.3 ml.kg(-1). min(-1); R(2) = 0.72 (P<0.05)]. No positive association between muscular fitness-related variables and physical activity was observed, even after adjusting for body fat or body fat and age. CONCLUSIONS/SIGNIFICANCE: Adiposity and age are the strongest predictors of VO(2)max in healthy men. The energy expended in moderate and vigorous physical activities is inversely associated with adiposity. Muscular fitness does not appear to be associated with physical activity as assessed by the IPAQ

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

Moving toward a system genetics view of disease

Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone

Oncogenic role of EAPII in lung cancer development and its activation of the MAPK–ERK pathway

Cancer progression involves multiple complex and interdependent steps, including progressive proliferation, angiogenesis and metastases. The complexity of these processes requires a comprehensive elucidation of the integrated signaling networks for better understanding. EAPII interacts with multiple cancer-related proteins, but its biological significance in cancer development remains unknown. In this report we identified the elevated level of EAPII protein in non-small-cell lung carcinoma (NSCLC) patients and NSCLC cell lines in culture. The oncogenic role of EAPII in lung cancer development was demonstrated using NSCLC cells with genetic manipulations that influence EAPII expression: EAPII overexpression increases proliferation of NSCLC cells with an accelerated transition of cell cycle and facilitates xenograft tumor growth in vivo; EAPII knockdown results in apoptosis of NSCLC cells and reduces xenograft tumor formation. To further explore the mechanism of EAPII's oncogenic role in lung cancer development and to elucidate the potential signaling pathway(s) that EAPII may impact, we employed antibody array to investigate the alternation of the major signaling pathways in NSCLC cells with altered EAPII level. We found that EAPII overexpression significantly activated Raf1 and ERK1/2, but not c-Jun N-terminal kinase and p38 pathways. Consistently, the protein and mRNA levels of MYC and cyclin D1, which are targets of the mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK–ERK) pathway, are significantly increased by EAPII overexpression. Taken together, we demonstrated that EAPII is an oncogenic factor and the activation of MAPK–ERK signaling pathway by EAPII may contribute to lung cancer development