159 research outputs found
The neural correlates of social attention: automatic orienting to social and nonsocial cues
Previous evidence suggests that directional social cues (e.g., eye gaze) cause automatic shifts in attention toward gaze direction. It has been proposed that automatic attentional orienting driven by social cues (social orienting) involves a different neural network from automatic orienting driven by nonsocial cues. However, previous neuroimaging studies on social orienting have only compared gaze cues to symbolic cues, which typically engage top-down mechanisms. Therefore, we directly compared the neural activity involved in social orienting to that involved in purely automatic nonsocial orienting. Twenty participants performed a spatial cueing task consisting of social (gaze) cues and automatic nonsocial (peripheral squares) cues presented at short and long stimulus (cue-to-target) onset asynchronies (SOA), while undergoing fMRI. Behaviorally, a facilitation effect was found for both cue types at the short SOA, while an inhibitory effect (inhibition of return: IOR) was found only for nonsocial cues at the long SOA. Imaging results demonstrated that social and nonsocial cues recruited a largely overlapping fronto-parietal network. In addition, social cueing evoked greater activity in occipito-temporal regions at both SOAs, while nonsocial cueing recruited greater subcortical activity, but only for the long SOA (when IOR was found). A control experiment, including central arrow cues, confirmed that the occipito-temporal activity was at least in part due to the social nature of the cue and not simply to the location of presentation (central vs. peripheral). These results suggest an evolutionary trajectory for automatic orienting, from predominantly subcortical mechanisms for nonsocial orienting to predominantly cortical mechanisms for social orienting
Next-Generation Phylogeography: A Targeted Approach for Multilocus Sequencing of Non-Model Organisms
The field of phylogeography has long since realized the need and utility of incorporating nuclear DNA (nDNA) sequences into analyses. However, the use of nDNA sequence data, at the population level, has been hindered by technical laboratory difficulty, sequencing costs, and problematic analytical methods dealing with genotypic sequence data, especially in non-model organisms. Here, we present a method utilizing the 454 GS-FLX Titanium pyrosequencing platform with the capacity to simultaneously sequence two species of sea star (Meridiastra calcar and Parvulastra exigua) at five different nDNA loci across 16 different populations of 20 individuals each per species. We compare results from 3 populations with traditional Sanger sequencing based methods, and demonstrate that this next-generation sequencing platform is more time and cost effective and more sensitive to rare variants than Sanger based sequencing. A crucial advantage is that the high coverage of clonally amplified sequences simplifies haplotype determination, even in highly polymorphic species. This targeted next-generation approach can greatly increase the use of nDNA sequence loci in phylogeographic and population genetic studies by mitigating many of the time, cost, and analytical issues associated with highly polymorphic, diploid sequence markers
CodingQuarry: Highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts
Background: The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. Results: CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. Conclusions: We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available (https://sourceforge.net/projects/codingquarry/), and suitable for incorporation into genome annotation pipelines
Identification of Genes Contributing to the Virulence of Francisella tularensis SCHU S4 in a Mouse Intradermal Infection Model
Background: Francisella tularensis is a highly virulent human pathogen. The most virulent strains belong to subspecies tularensis and these strains cause a sometimes fatal disease. Despite an intense recent research effort, there is very limited information available that explains the unique features of subspecies tularensis strains that distinguish them from other F. tularensis strains and that explain their high virulence. Here we report the use of targeted mutagenesis to investigate the roles of various genes or pathways for the virulence of strain SCHU S4, the type strain of subspecies tularensis. Methodology/Principal Findings: The virulence of SCHU S4 mutants was assessed by following the outcome of infection after intradermal administration of graded doses of bacteria. By this route, the LD\u2085\u2080 of the SCHU S4 strain is one CFU. The virulence of 20 in-frame deletion mutants and 37 transposon mutants was assessed. A majority of the mutants did not show increased prolonged time to death, among them notably \u394pyrB and \u394recA. Of the remaining, mutations in six unique targets, tolC, rep, FTT0609, FTT1149c, ahpC, and hfq resulted in significantly prolonged time to death and mutations in nine targets, rplA, wbtI, iglB, iglD, purL, purF, ggt, kdtA, and glpX, led to marked attenuation with an LD\u2085\u2080 of >10\ub3 CFU. In fact, the latter seven mutants showed very marked attenuation with an LD\u2085\u2080 of 6510\u2077 CFU. Conclusions/Significance: The results demonstrate that the characterization of targeted mutants yielded important information about essential virulence determinants that will help to identify the so far little understood extreme virulence of F. tularensis subspecies tularensis.Peer reviewed: YesNRC publication: Ye
Genetic variation of transgenerational plasticity of offspring germination in response to salinity stress and the seed transcriptome of Medicago truncatula
Genetic variability in mitochondrial and nuclear genes of Larus dominicanus (Charadriiformes, Laridae) from the Brazilian coast
Plasma and dietary carotenoid, retinol and tocopherol levels and the risk of gastric adenocarcinomas in the European prospective investigation into cancer and nutrition
Despite declining incidence rates, gastric cancer (GC) is a major cause of death worldwide. Its aetiology may involve dietary antioxidant micronutrients such as carotenoids and tocopherols. The objective of this study was to determine the association of plasma levels of seven common carotenoids, their total plasma concentration, retinol and α- and γ-tocopherol, with the risk of gastric adenocarcinoma in a case–control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC), a large cohort involving 10 countries. A secondary objective was to determine the association of total sum of carotenoids, retinol and α-tocopherol on GCs by anatomical subsite (cardia/noncardia) and histological subtype (diffuse/intestinal). Analytes were measured by high-performance liquid chromatography in prediagnostic plasma from 244 GC cases and 645 controls matched by age, gender, study centre and date of blood donation. Conditional logistic regression models adjusted by body mass index, total energy intake, smoking and Helicobacter pylori infection status were used to estimate relative cancer risks. After an average 3.2 years of follow-up, a negative association with GC risk was observed in the highest vs the lowest quartiles of plasma β-cryptoxanthin (odds ratio (OR)=0.53, 95% confidence intervals (CI)=0.30–0.94, Ptrend=0.006), zeaxanthin (OR=0.39, 95% CI=0.22–0.69, Ptrend=0.005), retinol (OR=0.55, 95% CI=0.33–0.93, Ptrend=0.005) and lipid-unadjusted α-tocopherol (OR=0.59, 95% CI=0.37–0.94, Ptrend=0.022). For all analytes, no heterogeneity of risk estimates or significant associations were observed by anatomical subsite. In the diffuse histological subtype, an inverse association was observed with the highest vs lowest quartile of lipid-unadjusted α-tocopherol (OR=0.26, 95% CI=0.11–0.65, Ptrend=0.003). These results show that higher plasma concentrations of some carotenoids, retinol and α-tocopherol are associated with reduced risk of GC
Protein arginine methyltransferase 5 regulates multiple signaling pathways to promote lung cancer cell proliferation
Comparative genome structure, secondary metabolite, and effector coding capacity across Cochliobolus pathogens.
The genomes of five Cochliobolus heterostrophus strains, two Cochliobolus sativus strains, three additional Cochliobolus species (Cochliobolus victoriae, Cochliobolus carbonum, Cochliobolus miyabeanus), and closely related Setosphaeria turcica were sequenced at the Joint Genome Institute (JGI). The datasets were used to identify SNPs between strains and species, unique genomic regions, core secondary metabolism genes, and small secreted protein (SSP) candidate effector encoding genes with a view towards pinpointing structural elements and gene content associated with specificity of these closely related fungi to different cereal hosts. Whole-genome alignment shows that three to five percent of each genome differs between strains of the same species, while a quarter of each genome differs between species. On average, SNP counts among field isolates of the same C. heterostrophus species are more than 25× higher than those between inbred lines and 50× lower than SNPs between Cochliobolus species. The suites of nonribosomal peptide synthetase (NRPS), polyketide synthase (PKS), and SSP-encoding genes are astoundingly diverse among species but remarkably conserved among isolates of the same species, whether inbred or field strains, except for defining examples that map to unique genomic regions. Functional analysis of several strain-unique PKSs and NRPSs reveal a strong correlation with a role in virulence
Therapeutic strategies for functional dyspepsia and irritable bowel syndrome based on pathophysiology
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