Quality determination and the repair of poor quality spots in array experiments

Background  

A common feature of microarray experiments is the occurence of missing gene expression data. These missing values occur for a variety of reasons, in particular, because of the filtering of poor quality spots and the removal of undefined values when a logarithmic transformation is applied to negative background-corrected intensities. The efficiency and power of an analysis performed can be substantially reduced by having an incomplete matrix of gene intensities. Additionally, most statistical methods require a complete intensity matrix. Furthermore, biases may be introduced into analyses through missing information on some genes. Thus methods for appropriately replacing (imputing) missing data and/or weighting poor quality spots are required.     

A Taxonomic Search Engine: Federating taxonomic databases using web services

Background  

The taxonomic name of an organism is a key link between different databases that store information on that organism. However, in the absence of a single, comprehensive database of organism names, individual databases lack an easy means of checking the correctness of a name. Furthermore, the same organism may have more than one name, and the same name may apply to more than one organism.     

Radiographic joint damage in rheumatoid arthritis is associated with differences in cartilage turnover and can be predicted by serum biomarkers: an evaluation from 1 to 4 years after diagnosis

Introduction  

The objective of this study was to determine whether serum biomarkers for degradation and synthesis of the extracellular matrix of cartilage are associated with, and can predict, radiographic damage in patients with rheumatoid arthritis (RA).     

Vertical Distribution of Corn Stover Dry Mass Grown at Several US Locations

Corn (Zea mays L.) stover was identified as a renewable non-food agricultural feedstock for production of liquid fuels, biopower, and other bioproducts, but it is also needed for erosion control, carbon sequestration, and nutrient cycling. To help balance these multiple demands, our objectives were to (1) determine height distribution of corn stover biomass, (2) quantify the percentage of stover that is corn cob, and (3) develop a general relationship between plant harvest height and stover remaining in the field for a broad range of growing conditions, soil types, and hybrids in different regions. Plant height, dry grain, stover, and cob yield data were collected at eight US locations. Overall, stover yield increased about 0.85 Mg ha^-1 and cob yield increased about 0.10 Mg ha^-1 for each 1.0 Mg ha^-1 increase in dry grain yield. At grain harvest, the stover-to-grain ratio ranged from 0.64 to 0.96 and cob-to-grain ratio ranged from 0.11 to 0.19. A strong nearly 1:1 linear (r ²?=?0.93) relationship between the relative cutting height and relative biomass remaining in the field was observed across all sites. These data were requested by the US Department of Agriculture-Natural Resource Conservation Service to help improve version 2 of the Revised Universal Soil Loss Equation (RUSLE2) and Wind Erosion Prediction System and better estimate corn stover harvest rates based on cutting height or selective organ harvest (e.g., grain and cob only). This information will improve the capacity of RUSLE2 and similar models to predict the erosion risk associated with harvesting corn residues.     

Discovery of potent,selective, bioavailable phosphodiesterase 2 (PDE2) inhibitors active in an osteoarthritis pain model,Part I: Transformation of selective pyrazolodiazepinone phosphodiesterase 4 (PDE4) inhibitors into selective PDE2 inhibitors

We identified potent, selective PDE2 inhibitors by optimizing residual PDE2 activity in a series of PDE4 inhibitors, while simultaneously minimizing PDE4 activity. These newly designed PDE2 inhibitors bind to the PDE2 enzyme in a cGMP-like mode in contrast to the cAMP-like binding mode found in PDE4. Structure activity relationship studies coupled with an inhibitor bound crystal structure in the active site of the catalytic domain of PDE2 identified structural features required to minimize PDE4 inhibition while simultaneously maximizing PDE2 inhibition.     

Characterization of substrate binding and catalysis in the potential antibacterial target N-acetylglucosamine-1-phosphate uridyltransferase (GlmU)

N-Acetylglucosamine-1-phosphate uridyltransferase (GlmU) catalyzes the first step in peptidoglycan biosynthesis in both Gram-positive and Gram-negative bacteria. The products of the GlmU reaction are essential for bacterial survival, making this enzyme an attractive target for antibiotic drug discovery. A series of Haemophilus influenzae GlmU (hiGlmU) structures were determined by X-ray crystallography in order to provide structural and functional insights into GlmU activity and inhibition. The information derived from these structures was combined with biochemical characterization of the K25A, Q76A, D105A, Y103A, V223A, and E224A hiGlmU mutants in order to map these active-site residues to catalytic activity of the enzyme and refine the mechanistic model of the GlmU uridyltransferase reaction. These studies suggest that GlmU activity follows a sequential substrate-binding order that begins with UTP binding noncovalently to the GlmU enzyme. The uridyltransferase active site then remains in an open apo-like conformation until N-acetylglucosamine-1-phosphate (GlcNAc-1-P) binds and induces a conformational change at the GlcNAc-binding subsite. Following the binding of GlcNAc-1-P to the UTP-charged uridyltransferase active site, the non-esterified oxygen of GlcNAc-1-P performs a nucleophilic attack on the alpha-phosphate group of UTP. The new data strongly suggest that the mechanism of phosphotransfer in the uridyltransferase reaction in GlmU is primarily through an associative mechanism with a pentavalent phosphate intermediate and an inversion of stereochemistry. Finally, the structural and biochemical characterization of the uridyltransferase active site and catalytic mechanism described herein provides a basis for the structure-guided design of novel antibacterial agents targeting GlmU activity.     

Raspberry viruses affect the behavior and performance of Amphorophora agathonica in single and mixed infections

Pathogens may alter their hosts, which consequently increases transmission efficiency by vectors. We examined the effects of Raspberry leaf mottle virus [RLMV; Closterovirus (Closteroviridae)] and Raspberry latent virus [RpLV; Reovirus (Reoviridae)], alone and in a co‐infection in raspberry, Rubus idaeus L. (Rosaceae) cv. Meeker, on the behavior and performance of its vector, Amphorophora agathonica Hottes (Hemiptera: Aphididae). Longevity was increased in aphids feeding on all infected‐plant treatments compared with healthy plants, but aphid fecundity only increased in the co‐infection treatment. In a two‐way choice study between infected and healthy plants, aphids showed no difference in preference between plants after 30 min of exposure. After 24 h, aphids significantly preferred to settle on plants infected with RLMV over healthy, but healthy plants over plants infected with RpLV. There were no differences in settling preferences between healthy and co‐infected plants. An electrical penetration graph study showed no differences in aphid feeding behavior on plants infected with RLMV and RLMV+RpLV when compared with healthy controls. Our results are consistent with past findings that infected plant's impact vector performance and behavior, but also highlight the need to further investigate greater virus diversity and effects of mixed infections.     

tigaR: integrative significance analysis of temporal differential gene expression induced by genomic abnormalities

Background

To determine which changes in the host cell genome are crucial for cervical carcinogenesis, a longitudinal in vitro model system of HPV-transformed keratinocytes was profiled in a genome-wide manner. Four cell lines affected with either HPV16 or HPV18 were assayed at 8 sequential time points for gene expression (mRNA) and gene copy number (DNA) using high-resolution microarrays. Available methods for temporal differential expression analysis are not designed for integrative genomic studies.

Results

Here, we present a method that allows for the identification of differential gene expression associated with DNA copy number changes over time. The temporal variation in gene expression is described by a generalized linear mixed model employing low-rank thin-plate splines. Model parameters are estimated with an empirical Bayes procedure, which exploits integrated nested Laplace approximation for fast computation. Iteratively, posteriors of hyperparameters and model parameters are estimated. The empirical Bayes procedure shrinks multiple dispersion-related parameters. Shrinkage leads to more stable estimates of the model parameters, better control of false positives and improvement of reproducibility. In addition, to make estimates of the DNA copy number more stable, model parameters are also estimated in a multivariate way using triplets of features, imposing a spatial prior for the copy number effect.

Conclusion

With the proposed method for analysis of time-course multilevel molecular data, more profound insight may be gained through the identification of temporal differential expression induced by DNA copy number abnormalities. In particular, in the analysis of an integrative oncogenomics study with a time-course set-up our method finds genes previously reported to be involved in cervical carcinogenesis. Furthermore, the proposed method yields improvements in sensitivity, specificity and reproducibility compared to existing methods. Finally, the proposed method is able to handle count (RNAseq) data from time course experiments as is shown on a real data set.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-327) contains supplementary material, which is available to authorized users.     

Ribosomal RNA secondary structure: compensatory mutations and implications for phylogenetic analysis

Using sequence data from the 28S ribosomal RNA (rRNA) genes of selected vertebrates, we investigated the effects that constraints imposed by secondary structure have on the phylogenetic analysis of rRNA sequence data. Our analysis indicates that characters from both base-pairing regions (stems) and non-base-pairing regions (loops) contain phylogenetic information, as judged by the level of support of the phylogenetic results compared with a well-established tree based on both morphological and molecular data. The best results (the greatest level of support of well-accepted nodes) were obtained when the complete data set was used. However, some previously supported nodes were resolved using either the stem or loop bases alone. Stem bases sustain a greater number of compensatory mutations than would be expected at random, but the number is < 40% of that expected under a hypothesis of perfect compensation to maintain secondary structure. Therefore, we suggest that in phylogenetic analyses, the weighting of stem characters be reduced by no more than 20%, relative to that of loop characters. In contrast to previous suggestions, we do not recommend weighting of stem positions by one-half, compared with that of loop positions, because this overcompensates for the constraints that selection imposes on the secondary structure of rRNA.