Cell-type specific analysis of translating RNAs in developing flowers reveals new levels of control

Determining both the expression levels of mRNA and the regulation of its translation is important in understanding specialized cell functions. In this study, we describe both the expression profiles of cells within spatiotemporal domains of the Arabidopsis thaliana flower and the post-transcriptional regulation of these mRNAs, at nucleotide resolution. We express a tagged ribosomal protein under the promoters of three master regulators of flower development. By precipitating tagged polysomes, we isolated cell type specific mRNAs that are probably translating, and quantified those mRNAs through deep sequencing. Cell type comparisons identified known cell-specific transcripts and uncovered many new ones, from which we inferred cell type-specific hormone responses, promoter motifs and coexpressed cognate binding factor candidates, and splicing isoforms. By comparing translating mRNAs with steady-state overall transcripts, we found evidence for widespread post-transcriptional regulation at both the intron splicing and translational stages. Sequence analyses identified structural features associated with each step. Finally, we identified a new class of noncoding RNAs associated with polysomes. Findings from our profiling lead to new hypotheses in the understanding of flower development

Hydrocarbon ratios during PEM-WEST A: A model perspective

A useful application of the hydrocarbon measurements collected during the Pacific Exploratory Mission (PEM-West A) is as markers or indices of atmospheric processing. Traditionally, ratios of particular hydrocarbons have been interpreted as photochemical indices, since much of the effect due to atmospheric transport is assumed to cancel by using ratios. However, an ever increasing body of observatonial and theoretical evidence suggests that turbulent mixing associated with atmospheric transport influences certain hydrocarbon ratios significantly. In this study a three-dimensional mesoscale photochemical model is used to study the interaction of photochemistry and atmospheric mixing on select hydrocarbons. In terms of correlations and functional relationships between various alkanes the model results and PEM-West A hydrocarbon observations share many similar characteristics as well as explainable differences. When the three-dimensional model is applied to inert tracers, hydrocarbon ratios and other relationships exactly follow those expected by simple dilution with model-imposed "background air," and the three-dimensional results for reactive hydrocarbons are quite consistent with a combined influence of photochemistry and simple dilution. Analogous to these model results, relationships between various hydrocarbons collected during the PEM-West A experiment appear to be consistent with this simplified picture of photochemistry and dilution affecting individual air masses. When hydrocarbons are chosen that have negligeble contributions to clean background air, unambiguous determinations of the relative contributions to photochemistry and dilution can be estimated from the hydrocarbon samples. Both the three-dimensional model results and the observations imply an average characteristic lifetime for dilution with background air roughly equivalent to the photochemical lifetime of butane for the western Pacific lower troposphere. Moreover, the dominance of OH as the primary photochemical oxidant downwind of anthropogenic source regions can be inferred from correlations between the highly reactive alkane ratios. By incorporating back-trajectory information within the three-dimensional model analysis, a correspondence between time and a particular hydrocarbon or hydrocarbon ratio can be determined, and the influence of atmospheric mixing or photochemistry can be quantified. Results of the three-dimensional model study are compared and applied to the PEM-West A hydrocarbon dataset, yielding a practical methodology for determining average OH concentrations and atmospheric mixing rates from the hydrocarbon measurements. Aircraft data taken below 2 km during wall flights east of Japan imply a diurnal average OH concentration of ∼3 × 106 cm-3. The characteristic time for dilution with background air is estimated to be ∼2.5 days for the two study areas examined in this work. Copyright 1996 by the American Geophysical Union

Interaction between row-type genes in barley controls meristem determinacy and reveals novel routes to improved grain

Hordeum species develop a central spikelet flanked by two lateral spikelets at each inflorescence node. In 'two-rowed' spikes, the central spikelet alone is fertile and sets grain, while in 'six-rowed' spikes, lateral spikelets can also produce grain. Induced loss-of-function alleles of any of five Six-rowed spike (VRS) genes (VRS1-5) cause complete to intermediate gains of lateral spikelet fertility. Current six-row cultivars contain natural defective vrs1 and vrs5 alleles. Little information is known about VRS mechanism(s). We used comparative developmental, expression and genetic analyses on single and double vrs mutants to learn more about how VRS genes control development and assess their agronomic potential. We show that all VRS genes repress fertility at carpel and awn emergence in developing lateral spikelets. VRS4, VRS3 and VRS5 work through VRS1 to suppress fertility, probably by inducing VRS1 expression. Pairing vrs3, vrs4 or vrs5 alleles increased lateral spikelet fertility, despite the presence of a functional VRS1 allele. The vrs3 allele caused loss of spikelet identity and determinacy, improved grain homogeneity and increased tillering in a vrs4 background, while with vrs5, decreased tiller number and increased grain weight. Interactions amongst VRS genes control spikelet infertility, determinacy and outgrowth, and novel routes to improving six-row grain.Monika Zwirek, Robbie Waugh, Sarah M. McKi

The Variety and Value of Grassroots, Ground-up Recovery Efforts

The endangered status of the southern resident killer whale population and the likelihood of further human growth and development around the Salish Sea both indicate that the population’s recovery will be a daunting, long-term challenge to Canadian and U.S. governments and First Nation Tribes. Communities and non-governmental organizations presently have, and will continue to have, a vital role to play in contributing to the collective effort to provide the whales a quieter, less disruptive Salish Sea to successfully forage, communicate, socialize and raise their calves. For this panel, presenters will describe some of the activities currently underway to reach the recreational boating community and provide the necessary information to be responsible stewards as we all have a role to play in orca recovery. Questions we want them to answer: · What needs is your program addressing? · Who is your intended audience and how do you effectively reach them? · How are you measuring the success/impact of people’s behavior change? Programs we will hear about: Green Boating, Friends of the San Juans Be Whale Wise / Whale Warning Flag, San Juan County Gulf Islands Sighting Network, SIMRES BC Cetacean Sightings Network’s Whale Report Alert System (WRAS)- Ocean Wise Give Them Space, The Whale Trail Share the Water, Orca Networ

Epigenetic analysis of regulatory T cells using multiplex bisulfite sequencing.

This work was supported by Wellcome Trust Grant 096388, JDRF Grant 9-2011-253, the National Institute for Health Research Cambridge Biomedical Research Centre (BRC) and Award P01AI039671 (to LSW. and JAT.) from the National Institute of Allergy and Infectious Diseases (NIAID). CW is supported by the Wellcome Trust (089989). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of NIAID or the National Institutes of Health. The Cambridge Institute for Medical Research is in receipt of Wellcome Trust Strategic Award 100140. We gratefully acknowledge the participation of all NIHR Cambridge BioResource volunteers. We thank the Cambridge BioResource staff for their help with volunteer recruitment. We thank members of the Cambridge BioResource SAB and Management Committee for their support of our study and the National Institute for Health Research Cambridge Biomedical Research Centre for funding. We thank Fay Rodger and Ruth Littleboy for running the Illumina MiSeq in the Molecular Genetics Laboratories, Addenbrooke's Hospital, Cambridge. This research was supported by the Cambridge NIHR BRC Cell Phenotyping Hub. In particular, we wish to thank Anna Petrunkina Harrison, Simon McCallum, Christopher Bowman, Natalia Savinykh, Esther Perez and Jelena Markovic Djuric for their advice and support in cell sorting. We also thank Helen Stevens, Pamela Clarke, Gillian Coleman, Sarah Dawson, Jennifer Denesha, Simon Duley, Meeta Maisuria-Armer and Trupti Mistry for acquisition and preparation of samples.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/eji.20154564

Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N \u3e 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies

A Systematic Review of Mosquito Coils and Passive Emanators: Defining Recommendations for Spatial Repellency Testing Methodologies.

Mosquito coils, vaporizer mats and emanators confer protection against mosquito bites through the spatial action of emanated vapor or airborne pyrethroid particles. These products dominate the pest control market; therefore, it is vital to characterize mosquito responses elicited by the chemical actives and their potential for disease prevention. The aim of this review was to determine effects of mosquito coils and emanators on mosquito responses that reduce human-vector contact and to propose scientific consensus on terminologies and methodologies used for evaluation of product formats that could contain spatial chemical actives, including indoor residual spraying (IRS), long lasting insecticide treated nets (LLINs) and insecticide treated materials (ITMs). PubMed, (National Centre for Biotechnology Information (NCBI), U.S. National Library of Medicine, NIH), MEDLINE, LILAC, Cochrane library, IBECS and Armed Forces Pest Management Board Literature Retrieval System search engines were used to identify studies of pyrethroid based coils and emanators with key-words "Mosquito coils" "Mosquito emanators" and "Spatial repellents". It was concluded that there is need to improve statistical reporting of studies, and reach consensus in the methodologies and terminologies used through standardized testing guidelines. Despite differing evaluation methodologies, data showed that coils and emanators induce mortality, deterrence, repellency as well as reduce the ability of mosquitoes to feed on humans. Available data on efficacy outdoors, dose-response relationships and effective distance of coils and emanators is inadequate for developing a target product profile (TPP), which will be required for such chemicals before optimized implementation can occur for maximum benefits in disease control

Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing

<p>Abstract</p> <p>Background</p> <p>Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorithms, each justified by theory, simulation, or ad hoc validation and yet differing in practical results from equally justified algorithms. Recently, a concordance method that measures agreement among gene lists have been introduced to assess various aspects of differential gene expression detection. This method has the advantage of basing its assessment solely on the results of real data analyses, but as it requires examining gene lists of given sizes, it may be unstable.</p> <p>Results</p> <p>Two methodologies for assessing predictive error are described: a cross-validation method and a posterior predictive method. As a nonparametric method of estimating prediction error from observed expression levels, cross validation provides an empirical approach to assessing algorithms for detecting differential gene expression that is fully justified for large numbers of biological replicates. Because it leverages the knowledge that only a small portion of genes are differentially expressed, the posterior predictive method is expected to provide more reliable estimates of algorithm performance, allaying concerns about limited biological replication. In practice, the posterior predictive method can assess when its approximations are valid and when they are inaccurate. Under conditions in which its approximations are valid, it corroborates the results of cross validation. Both comparison methodologies are applicable to both single-channel and dual-channel microarrays. For the data sets considered, estimating prediction error by cross validation demonstrates that empirical Bayes methods based on hierarchical models tend to outperform algorithms based on selecting genes by their fold changes or by non-hierarchical model-selection criteria. (The latter two approaches have comparable performance.) The posterior predictive assessment corroborates these findings.</p> <p>Conclusions</p> <p>Algorithms for detecting differential gene expression may be compared by estimating each algorithm's error in predicting expression ratios, whether such ratios are defined across microarray channels or between two independent groups.</p> <p>According to two distinct estimators of prediction error, algorithms using hierarchical models outperform the other algorithms of the study. The fact that fold-change shrinkage performed as well as conventional model selection criteria calls for investigating algorithms that combine the strengths of significance testing and fold-change estimation.</p

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte