Spatio-Temporal Characteristics of Global Warming in the Tibetan Plateau during the Last 50 Years Based on a Generalised Temperature Zone - Elevation Model

Temperature is one of the primary factors influencing the climate and ecosystem, and examining its change and fluctuation could elucidate the formation of novel climate patterns and trends. In this study, we constructed a generalised temperature zone elevation model (GTEM) to assess the trends of climate change and temporal-spatial differences in the Tibetan Plateau (TP) using the annual and monthly mean temperatures from 1961-2010 at 144 meteorological stations in and near the TP. The results showed the following: (1) The TP has undergone robust warming over the study period, and the warming rate was 0.318°C/decade. The warming has accelerated during recent decades, especially in the last 20 years, and the warming has been most significant in the winter months, followed by the spring, autumn and summer seasons. (2) Spatially, the zones that became significantly smaller were the temperature zones of -6°C and -4°C, and these have decreased 499.44 and 454.26 thousand sq km from 1961 to 2010 at average rates of 25.1% and 11.7%, respectively, over every 5-year interval. These quickly shrinking zones were located in the northwestern and central TP. (3) The elevation dependency of climate warming existed in the TP during 1961-2010, but this tendency has gradually been weakening due to more rapid warming at lower elevations than in the middle and upper elevations of the TP during 1991-2010. The higher regions and some low altitude valleys of the TP were the most significantly warming regions under the same categorizing criteria. Experimental evidence shows that the GTEM is an effective method to analyse climate changes in high altitude mountainous regions

Solution Structure of Tensin2 SH2 Domain and Its Phosphotyrosine-Independent Interaction with DLC-1

Background: Src homology 2 (SH2) domain is a conserved module involved in various biological processes. Tensin family member was reported to be involved in tumor suppression by interacting with DLC-1 (deleted-in-liver-cancer-1) via its SH2 domain. We explore here the important questions that what the structure of tensin2 SH2 domain is, and how it binds to DLC-1, which might reveal a novel binding mode. Principal Findings: Tensin2 SH2 domain adopts a conserved SH2 fold that mainly consists of five b-strands flanked by two a-helices. Most SH2 domains recognize phosphorylated ligands specifically. However, tensin2 SH2 domain was identified to interact with nonphosphorylated ligand (DLC-1) as well as phosphorylated ligand. Conclusions: We determined the solution structure of tensin2 SH2 domain using NMR spectroscopy, and revealed the interactions between tensin2 SH2 domain and its ligands in a phosphotyrosine-independent manner

Transgenic plants of Petunia hybrida harboring the CYP2E1 gene efficiently remove benzene and toluene pollutants and improve resistance to formaldehyde

The CYP2E1 protein belongs to the P450 enzymes family and plays an important role in the metabolism of small molecular and organic pollutants. In this study we generated CYP2E1 transgenic plants of Petunia using Agrobacterium rhizogenes K599. PCR analysis confirmed that the regenerated plants contained the CYP2E1 transgene and the rolB gene of the Ri plasmid. Southern blotting revealed the presence of multiple copies of CYP2E1 in the genome of transgenic plants. Fluorescent quantitative PCR revealed exogenous CYP2E1 gene expression in CYP2E1 transgenic plants at various levels, whereas no like expression was detected in either GUS transgenic plants or wild-types. The absorption of benzene and toluene by transgenic plants was analyzed through quantitative gas chromatography. Transgenic plants with high CYP2E1 expression showed a significant increase in absorption capacity of environmental benzene and toluene, compared to control GUS transgenic and wild type plants. Furthermore, these plants also presented obvious improved resistance to formaldehyde. This study, besides being the first to reveal that the CYP2E1 gene enhances plant resistance to formaldehyde, also furnishes a new method for reducing pollutants, such as benzene, toluene and formaldehyde, by using transgenic flowering horticultural plants

Urinary MicroRNA Profiling in the Nephropathy of Type 1 Diabetes

Background: Patients with Type 1 Diabetes (T1D) are particularly vulnerable to development of Diabetic nephropathy (DN) leading to End Stage Renal Disease. Hence a better understanding of the factors affecting kidney disease progression in T1D is urgently needed. In recent years microRNAs have emerged as important post-transcriptional regulators of gene expression in many different health conditions. We hypothesized that urinary microRNA profile of patients will differ in the different stages of diabetic renal disease. Methods and Findings: We studied urine microRNA profiles with qPCR in 40 T1D with >20 year follow up 10 who never developed renal disease (N) matched against 10 patients who went on to develop overt nephropathy (DN), 10 patients with intermittent microalbuminuria (IMA) matched against 10 patients with persistent (PMA) microalbuminuria. A Bayesian procedure was used to normalize and convert raw signals to expression ratios. We applied formal statistical techniques to translate fold changes to profiles of microRNA targets which were then used to make inferences about biological pathways in the Gene Ontology and REACTOME structured vocabularies. A total of 27 microRNAs were found to be present at significantly different levels in different stages of untreated nephropathy. These microRNAs mapped to overlapping pathways pertaining to growth factor signaling and renal fibrosis known to be targeted in diabetic kidney disease. Conclusions: Urinary microRNA profiles differ across the different stages of diabetic nephropathy. Previous work using experimental, clinical chemistry or biopsy samples has demonstrated differential expression of many of these microRNAs in a variety of chronic renal conditions and diabetes. Combining expression ratios of microRNAs with formal inferences about their predicted mRNA targets and associated biological pathways may yield useful markers for early diagnosis and risk stratification of DN in T1D by inferring the alteration of renal molecular processes. © 2013 Argyropoulos et al

The Waiting Time for Inter-Country Spread of Pandemic Influenza

BACKGROUND: The time delay between the start of an influenza pandemic and its subsequent initiation in other countries is highly relevant to preparedness planning. We quantify the distribution of this random time in terms of the separate components of this delay, and assess how the delay may be extended by non-pharmaceutical interventions. METHODS AND FINDINGS: The model constructed for this time delay accounts for: (i) epidemic growth in the source region, (ii) the delay until an infected individual from the source region seeks to travel to an at-risk country, (iii) the chance that infected travelers are detected by screening at exit and entry borders, (iv) the possibility of in-flight transmission, (v) the chance that an infected arrival might not initiate an epidemic, and (vi) the delay until infection in the at-risk country gathers momentum. Efforts that reduce the disease reproduction number in the source region below two and severe travel restrictions are most effective for delaying a local epidemic, and under favourable circumstances, could add several months to the delay. On the other hand, the model predicts that border screening for symptomatic infection, wearing a protective mask during travel, promoting early presentation of cases arising among arriving passengers and moderate reduction in travel volumes increase the delay only by a matter of days or weeks. Elevated in-flight transmission reduces the delay only minimally. CONCLUSIONS: The delay until an epidemic of pandemic strain influenza is imported into an at-risk country is largely determined by the course of the epidemic in the source region and the number of travelers attempting to enter the at-risk country, and is little affected by non-pharmaceutical interventions targeting these travelers. Short of preventing international travel altogether, eradicating a nascent pandemic in the source region appears to be the only reliable method of preventing country-to-country spread of a pandemic strain of influenza

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

Spreading Patterns of the Influenza A (H1N1) Pandemic

We investigate the dynamics of the 2009 influenza A (H1N1/S-OIV) pandemic by analyzing data obtained from World Health Organization containing the total number of laboratory-confirmed cases of infections - by country - in a period of 69 days, from 26 April to 3 July, 2009. Specifically, we find evidence of exponential growth in the total number of confirmed cases and linear growth in the number of countries with confirmed cases. We also find that, i) at early stages, the cumulative distribution of cases among countries exhibits linear behavior on log-log scale, being well approximated by a power law decay; ii) for larger times, the cumulative distribution presents a systematic curvature on log-log scale, indicating a gradual change to lognormal behavior. Finally, we compare these empirical findings with the predictions of a simple stochastic model. Our results could help to select more realistic models of the dynamics of influenza-type pandemics

Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood

Background Gene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization. Methods Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT), 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS) and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms. Results Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder). Conclusion The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.Boryana S Stamova, Michelle Apperson, Wynn L Walker, Yingfang Tian, Huichun Xu, Peter Adamczy, Xinhua Zhan, Da-Zhi Liu, Bradley P Ander, Isaac H Liao, Jeffrey P Gregg, Renee J Turner, Glen Jickling, Lisa Lit and Frank R Shar

Nucleotide and phylogenetic analyses of the Chlamydia trachomatis ompA gene indicates it is a hotspot for mutation

<p>Abstract</p> <p>Background</p> <p>Serovars of the human pathogen <it>Chlamydia trachomatis </it>occupy one of three specific tissue niches. Genomic analyses indicate that the serovars have a phylogeny congruent with their pathobiology and have an average substitution rate of less than one nucleotide per kilobase. In contrast, the gene that determines serovar specificity, <it>ompA</it>, has a phylogenetic association that is not congruent with tissue tropism and has a degree of nucleotide variability much higher than other genomic loci. The <it>ompA </it>gene encodes the major surface-exposed antigenic determinant, and the observed nucleotide diversity at the <it>ompA </it>locus is thought to be due to recombination and host immune selection pressure. The possible contribution of a localized increase in mutation rate, however, has not been investigated.</p> <p>Results</p> <p>Nucleotide diversity and phylogenetic relationships of the five constant and four variable domains of the <it>ompA </it>gene, as well as several loci surrounding <it>ompA</it>, were examined for each serovar. The loci flanking the <it>ompA </it>gene demonstrated that nucleotide diversity increased monotonically as <it>ompA </it>is approached and that their gene trees are not congruent with either <it>ompA </it>or tissue tropism. The variable domains of the <it>ompA </it>gene had a very high level of non-synonymous change, which is expected as these regions encode the surface-exposed epitopes and are under positive selection. However, the synonymous changes are clustered in the variable regions compared to the constant domains; if hitchhiking were to account for the increase in synonymous changes, these substitutions should be more evenly distributed across the gene. Recombination also cannot entirely account for this increase as the phylogenetic relationships of the constant and variable domains are congruent with each other.</p> <p>Conclusions</p> <p>The high number of synonymous substitutions observed within the variable domains of <it>ompA </it>appears to be due to an increased mutation rate within this region of the genome, whereas the increase in nucleotide substitution rate and the lack of phylogenetic congruence in the regions flanking <it>ompA </it>are characteristic motifs of gene conversion. Together, the increased mutation rate in the <it>ompA </it>gene, in conjunction with gene conversion and positive selection, results in a high degree of variability that promotes host immune evasion.</p