11,747 research outputs found
An experimental evaluation of a loop versus a reference design for two-channel microarrays
Motivation: Despite theoretical arguments that socalled "loop designs" of two-channel DNA microarray experiments are more efficient, biologists keep on using "reference designs". We describe two sets of microarray experiments with RNA from two different biological systems (TPA-stimulated mammalian cells and Streptomyces coelicor). In each case, both a loop and a reference design were performed using the same RNA preparations with the aim to study their relative efficiency. Results: The results of these experiments show that (1) the loop design attains a much higher precision than the reference design, (2) multiplicative spot effects are a large source of variability, and if they are not accounted for in the mathematical model, for example by taking log-ratios or including spot-effects, then the model will perform poorly. The first result is reinforced by a simulation study. Practical recommendations are given on how simple loop designs can be extended to more realistic experimental designs and how standard statistical methods allow the experimentalist to use and interpret the results from loop designs in practice
MMpred: functional miRNA – mRNA interaction analyses by miRNA expression prediction
Background: MicroRNA (miRNA) directed gene repression is an important mechanism of posttranscriptional
regulation. Comprehensive analyses of how microRNA influence biological processes requires paired
miRNA-mRNA expression datasets. However, a review of both GEO and ArrayExpress repositories revealed few
such datasets, which was in stark contrast to the large number of messenger RNA (mRNA) only datasets. It is of
interest that numerous primary miRNAs (precursors of microRNA) are known to be co-expressed with coding
genes (host genes).
Results: We developed a miRNA-mRNA interaction analyses pipeline. The proposed solution is based on two
miRNA expression prediction methods – a scaling function and a linear model. Additionally, miRNA-mRNA anticorrelation
analyses are used to determine the most probable miRNA gene targets (i.e. the differentially
expressed genes under the influence of up- or down-regulated microRNA). Both the consistency and accuracy
of the prediction method is ensured by the application of stringent statistical methods. Finally, the predicted
targets are subjected to functional enrichment analyses including GO, KEGG and DO, to better understand the
predicted interactions.
Conclusions: The MMpred pipeline requires only mRNA expression data as input and is independent of third
party miRNA target prediction methods. The method passed extensive numerical validation based on the
binding energy between the mature miRNA and 3’ UTR region of the target gene. We report that MMpred is
capable of generating results similar to that obtained using paired datasets. For the reported test cases we
generated consistent output and predicted biological relationships that will help formulate further testable
hypotheses
A Revised Design for Microarray Experiments to Account for Experimental Noise and Uncertainty of Probe Response
Background
Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance.
Results
Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other based on 60 mer probes from an Agilent design. To assess experimental variance in probe binding, all probes were replicated ten times. To assess probe performance, the probes were calibrated using a dilution series of target molecules and the signal response was fitted to an adsorption model. We found that significant variance of the signal could be controlled by averaging across probes and removing probes that are nonresponsive or poorly responsive in the calibration experiment. Taking this into account, one can obtain a more reliable signal with the added option of obtaining absolute rather than relative measurements.
Conclusion
The assessment of technical variance within the experiments, combined with the calibration of probes allows to remove poorly responding probes and yields more reliable signals for the remaining ones. Once an array is properly calibrated, absolute quantification of signals becomes straight forward, alleviating the need for normalization and reference hybridizations
DNA meets the SVD
This paper introduces an important area of computational cell biology where complex, publicly available genomic data is being examined by linear algebra methods, with the aim of revealing biological and medical insights
Combination of small molecule microarray and confocal microscopy techniques for live cell staining fluorescent dye discovery
Discovering new fluorochromes is significantly advanced by high-throughput screening (HTS) methods. In the present study a combination of small molecule microarray (SMM) prescreening and confocal laser scanning microscopy (CLSM) was developed in order to discover novel cell staining fluorescent dyes. Compounds with high native fluorescence were selected from a 14,585-member library and further tested on living cells under the microscope. Eleven compartment- specific, cell-permeable (or plasma membrane-targeted) fluorochromes were identified. Their cytotoxicity was tested and found that between 1-10 micromolar range, they were non-toxic even during long-term incubations. © 2013 by the authors; licensee MDPI, Basel, Switzerland
High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation
Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered
regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The
regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little
information on how these function in the global control of the process. We used microarray analysis to obtain a highresolution
time-course profile of gene expression during development of a single leaf over a 3-week period to senescence.
A complex experimental design approach and a combination of methods were used to extract high-quality replicated data
and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to
reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well
as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups
of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic
processes, signaling pathways, and specific TF activity, which will underpin the development of network models to
elucidate the process of senescence
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Microarray detection of human parainfluenzavirus 4 infection associated with respiratory failure in an immunocompetent adult.
A pan-viral DNA microarray, the Virochip (University of California, San Francisco), was used to detect human parainfluenzavirus 4 (HPIV-4) infection in an immunocompetent adult presenting with a life-threatening acute respiratory illness. The virus was identified in an endotracheal aspirate specimen, and the microarray results were confirmed by specific polymerase chain reaction and serological analysis for HPIV-4. Conventional clinical laboratory testing using an extensive panel of microbiological tests failed to yield a diagnosis. This case suggests that the potential severity of disease caused by HPIV-4 in adults may be greater than previously appreciated and illustrates the clinical utility of a microarray for broad-based viral pathogen screening
A stochastic model dissects cell states in biological transition processes
Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations
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