Coreferentiality: a new method for the hypothesis-based analysis of phenotypes characterized by multivariate data

Many multifactorial biologic effects, particularly in the context of complex human diseases, are still poorly understood. At the same time, the systematic acquisition of multivariate data has become increasingly easy. The use of such data to analyze and model complex phenotypes, however, remains a challenge. Here, a new analytic approach is described, termed coreferentiality, together with an appropriate statistical test. Coreferentiality is the indirect relation of two variables of functional interest in respect to whether they parallel each other in their respective relatedness to multivariate reference data, which can be informative for a complex effect or phenotype. It is shown that the power of coreferentiality testing is comparable to multiple regression analysis, sufficient even when reference data are informative only to a relatively small extent of 2.5%, and clearly exceeding the power of simple bivariate correlation testing. Thus, coreferentiality testing uses the increased power of multivariate analysis, however, in order to address a more straightforward interpretable bivariate relatedness. Systematic application of this approach could substantially improve the analysis and modeling of complex phenotypes, particularly in the context of human study where addressing functional hypotheses by direct experimentation is often difficult.     

Non-parametric photic entrainment of Djungarian hamsters with different rhythmic phenotypes

To investigate the role of non-parametric light effects in entrainment, Djungarian hamsters of two different circadian phenotypes were exposed to skeleton photoperiods, or to light pulses at different circadian times, to compile phase response curves (PRCs). Wild-type (WT) hamsters show daily rhythms of locomotor activity in accord with the ambient light/dark conditions, with activity onset and offset strongly coupled to light-off and light-on, respectively. Hamsters of the delayed activity onset (DAO) phenotype, in contrast, progressively delay their activity onset, whereas activity offset remains coupled to light-on. The present study was performed to better understand the underlying mechanisms of this phenomenon. Hamsters of DAO and WT phenotypes were kept first under standard housing conditions with a 14:10 h light–dark cycle, and then exposed to skeleton photoperiods (one or two 15-min light pulses of 100 lx at the times of the former light–dark and/or dark–light transitions). In a second experiment, hamsters of both phenotypes were transferred to constant darkness and allowed to free-run until the lengths of the active (α) and resting (ρ) periods were equal (α:ρ = 1). At this point, animals were then exposed to light pulses (100 lx, 15 min) at different circadian times (CTs). Phase and period changes were estimated separately for activity onset and offset. When exposed to skeleton-photoperiods with one or two light pulses, the daily activity patterns of DAO and WT hamsters were similar to those obtained under conditions of a complete 14:10 h light–dark cycle. However, in the case of giving only one light pulse at the time of the former light–dark transition, animals temporarily free-ran until activity offset coincided with the light pulse. These results show that photic entrainment of the circadian activity rhythm is attained primarily via non-parametric mechanisms, with the “morning” light pulse being the essential cue. In the second experiment, typical photic PRCs were obtained with phase delays in the first half of the subjective night, phase advances in the second half, and a dead zone during the subjective day. ANOVA indicated no significant differences between WT and DAO animals despite a significantly longer free-running period (tau) in DAO hamsters. Considering the phase shifts induced around CT0 and the different period lengths, it was possible to model the entrainment patterns of both phenotypes. It was shown that light-induced phase shifts of activity offset were sufficient to compensate for the long tau in WT and DAO hamsters, thus enabling a stable entrainment of their activity offsets to be achieved. With respect to activity onsets, phase shifts were sufficient only in WT animals; in DAO hamsters, activity onset showed increasing delays. The results of the present paper clearly demonstrate that, under laboratory conditions, the non-parametric component of light and dark leads to circadian entrainment in Djungarian hamsters. However, a stable entrainment of activity onset can be achieved only if the free-running period does not exceed a certain value. With longer tau values, hamsters reveal a DAO phenotype. Under field conditions, therefore, non-photic cues/zeitgebers must obviously be involved to enable a proper circadian entrainment.     

Non-parametric analysis of platelet lifespan

A model-independent and elementary method of analysis of platelet survival is proposed. The method is based on the finding that the mean and standard deviation of the platelet lifespan can be expressed in the terms of the slope at time 0 and the area under the empirical platelet survival curve. The method is tested using Monte-Carlo simulations and then applied to a set of clinical data.     

Non-parametric analysis of platelet lifespan

Abstract. A model-independent and elementary method of analysis of platelet survival is proposed. The method is based on the finding that the mean and standard deviation of the platelet lifespan can be expressed in the terms of the slope at time 0 and the area under the empirical platelet survival curve. The method is tested using Monte-Carlo simulations and then applied to a set of clinical data.     

A comparison of background correction methods for two-colour microarrays

MOTIVATION: Microarray data must be background corrected to remove the effects of non-specific binding or spatial heterogeneity across the array, but this practice typically causes other problems such as negative corrected intensities and high variability of low intensity log-ratios. Different estimators of background, and various model-based processing methods, are compared in this study in search of the best option for differential expression analyses of small microarray experiments. RESULTS: Using data where some independent truth in gene expression is known, eight different background correction alternatives are compared, in terms of precision and bias of the resulting gene expression measures, and in terms of their ability to detect differentially expressed genes as judged by two popular algorithms, SAM and limma eBayes. A new background processing method (normexp) is introduced which is based on a convolution model. The model-based correction methods are shown to be markedly superior to the usual practice of subtracting local background estimates. Methods which stabilize the variances of the log-ratios along the intensity range perform the best. The normexp+offset method is found to give the lowest false discovery rate overall, followed by morph and vsn. Like vsn, normexp is applicable to most types of two-colour microarray data. AVAILABILITY: The background correction methods compared in this article are available in the R package limma (Smyth, 2005) from http://www.bioconductor.org. SUPPLEMENTARY INFORMATION: Supplementary data are available from http://bioinf.wehi.edu.au/resources/webReferences.html.     

High-throughput antibody microarrays for quantitative proteomic analysis

The antibody microarray is an intrinsically robust and quantitative system that delivers high-throughput and parallel measurements on particular sets of known proteins. It has become an important proteomics research tool, complementary to the conventional unbiased separation-based and mass spectrometry-based approaches. This review summarizes the technical aspects of production and the application for quantitative proteomic analysis with an emphasis on disease proteomics, especially the identification of biomarkers. Quality control, data analysis methods and the challenges for quantitative assays are also discussed.     

High-throughput antibody microarrays for quantitative proteomic analysis

The antibody microarray is an intrinsically robust and quantitative system that delivers high-throughput and parallel measurements on particular sets of known proteins. It has become an important proteomics research tool, complementary to the conventional unbiased separation-based and mass spectrometry-based approaches. This review summarizes the technical aspects of production and the application for quantitative proteomic analysis with an emphasis on disease proteomics, especially the identification of biomarkers. Quality control, data analysis methods and the challenges for quantitative assays are also discussed.     

An algorithm for simultaneous comparison of several sequences

An algorithm was developed to compare simultaneously severalDNA, RNA or protein sequences. With the algorithm, conservedregions of one sequence are located by doing pairwise comparisonswith other sequences, which is advantageous in planning site-directedmutagenesis studies. The observation matrices filled with scoresof comparisons are superimposed and added together and thosepoints having values greater than or equal to stringency areaccepted. The predicted secondary structural features can alsobe compared. Received on August 21, 1987; accepted on November 20, 1987     

Quantitative comparison of cDNA-AFLP, microarrays, and GeneChip expression data in Saccharomyces cerevisiae

cDNA-AFLP is a genome-wide expression analysis technology that does not require any prior knowledge of gene sequences. This PCR-based technique combines a high sensitivity with a high specificity, allowing detection of rarely expressed genes and distinguishing between homologous genes. In this report, we validated quantitative expression data of 110 cDNA-AFLP fragments in yeast with DNA microarrays and GeneChip data. The best correlation was found between cDNA-AFLP and GeneChip data. The cDNA-AFLP data revealed a low number of inconsistent profiles that could be explained by gel artifact, overexposure, or mismatch amplification. In addition, 18 cDNA-AFLP fragments displayed homology to genomic yeast DNA, but could not be linked unambiguously to any known ORF. These fragments were most probably derived from 5' or 3' noncoding sequences or might represent previously unidentified ORFs. Genes liable to cross hybridization showed identical results in cDNA-AFLP and GeneChip analysis. Three genes, which were readily detected with cDNA-AFLP, showed no significant expression in GeneChip experiments. We show that cDNA-AFLP is a very good alternative to microarrays and since no preexisting biological or sequence information is required, it is applicable to any species.     

Reverse-phase protein lysate microarrays for cell signaling analysis

'Reverse-phase' protein lysate microarray (RPA) assays use micro-scale, cell lysate dot blots that are printed to a substrate, followed by quantitative immunochemical protein detection, known to be particularly effective across many samples. Large-scale sample collection is a labor-intensive and time-consuming process; the information yielded from RPA assays, however, provides unique opportunities to experimentally interpret theoretical protein networks quantitatively. When specific antibodies are used, RPA can generate 1,000 times more data points using 10,000 times less sample volume than an ordinary western blot, enabling researchers to monitor quantitative proteomic responses for various time-scale and input-dose gradients simultaneously. Hence, the RPA system can be an excellent method for experimental validation of theoretical protein network models. Besides the initial screening of primary antibodies, collection of several hundreds of sample lysates from 1- to 8-h periods can be completed in approximately 10 d; subsequent RPA printing and signal detection steps require an additional 2-3 d.     

Current issues for DNA microarrays: platform comparison, double linear amplification, and universal RNA reference

DNA microarray technology has been widely used to simultaneously determine the expression levels of thousands of genes. A variety of approaches have been used, both in the implementation of this technology and in the analysis of the large amount of expression data. However, several practical issues still have not been resolved in a satisfactory manner, and among the most critical is the lack of agreement in the results obtained in different array platforms. In this study, we present a comparison of several microarray platforms [Affymetrix oligonucleotide arrays, custom complementary DNA (cDNA) arrays, and custom oligo arrays printed with oligonucleotides from three different sources] as well as analysis of various methods used for microarray target preparation and the reference design. The results indicate that the pairwise correlations of expression levels between platforms are relative low overall but that the log ratios of the highly expressed genes are strongly correlated, especially between Affymetrix and cDNA arrays. The microarray measurements were compared with quantitative real-time-polymerase chain reaction (QRT-PCR) results for 23 genes, and the varying degrees of agreement for each platform were characterized. We have also developed and tested a double amplification method which allows the use of smaller amounts of starting material. The added round of amplification produced reproducible results as compared to the arrays hybridized with single round amplified targets. Finally, the reliability of using a universal RNA reference for two-channel microarrays was tested and the results suggest that comparisons of multiple experimental conditions using the same control can be accurate.     

Systematic profiling of cellular phenotypes with spotted cell microarrays reveals mating-pheromone response genes

We have developed spotted cell microarrays for measuring cellular phenotypes on a large scale. Collections of cells are printed, stained for subcellular features, then imaged via automated, high-throughput microscopy, allowing systematic phenotypic characterization. We used this technology to identify genes involved in the response of yeast to mating pheromone. Besides morphology assays, cell microarrays should be valuable for high-throughput in situ hybridization and immunoassays, enabling new classes of genetic assays based on cell imaging.     

Extended analysis of benchmark datasets for Agilent two-color microarrays

Background  

As part of its broad and ambitious mission, the MicroArray Quality Control (MAQC) project reported the results of experiments using External RNA Controls (ERCs) on five microarray platforms. For most platforms, several different methods of data processing were considered. However, there was no similar consideration of different methods for processing the data from the Agilent two-color platform. While this omission is understandable given the scale of the project, it can create the false impression that there is consensus about the best way to process Agilent two-color data. It is also important to consider whether ERCs are representative of all the probes on a microarray.     

传粉生物学中几种花蜜采集和糖浓度测定方法的比较

花蜜的研究是花生物学中的一个重要内容,探寻实用的方法将方便野外操作。我们分别还用毛细管、注射器、滤纸条和离心法采集了5种花的花蜜,以比较各种方法的优劣,并用3种旋光测糖仪测量了慈姑Sagittaria trifolia L,的雌雄花的花蜜糖含量。目的是为寻找一种适合小型花的花蜜采集测量方法。结果表明,几种方法的适用性受花的大小、形状、蜜的分泌量及蜜腺位置的影响非常大,不同的花要采用不同的方法。对于一般的野外工作建议用毛细管采集后使用便携式旋光测糖仪测其糖含量。特别小的花和蜜量微小的花可以采用离心法收集。     

A comparison of microscope slide substrates for use in transfected cell microarrays

Transfected cell microarrays, arrays of mammalian cells expressing defined genes, offer enormous potential for the development of high-throughput cell-based detection technologies to monitor the presence of biological agents or environmental toxicants. The signals generated from these arrays are intimately linked to the efficiency of DNA uptake by the cells located on the micrometer-sized spots. However, quantitative analysis of the transfection efficiency on cellular microarrays has been limited. Further, little regard has been given to the role of the substrate in influencing the transfection efficiency of mammalian cells on transfected microarrays. In this report, we have quantified the transfection efficiency of mammalian cells on different microscope slide substrates. Using commercially available microscope slides bearing substrates that mediate cellular attachment (polystyrene, 3-aminopropylsilane, and poly-L-lysine), we have demonstrated the role of substrate hydrophobicity in determining the resulting spot size and the local DNA concentration when plasmid DNA is dispensed in a printing buffer containing gelatin and sucrose using a noncontact microarray printer. The mean spot diameter varied inversely with the substrate water contact angle (r2 = 0.970). Further, the relative local plasmid DNA concentration was a function of the mean spot diameter. The deposition of Rhodamine Red-labeled plasmid DNA revealed that, across all substrates, the average fluorescence signal within the spots varied inversely with the mean spot diameter (r2 = 0.976). The transfection efficiency of HEK 293T/17 cells varied in accord with the mean spot diameter, demonstrating that the uptake of DNA was a function of the local DNA concentration on each substrate.     

Protein microarrays for multiplex analysis of signal transduction pathways

We have developed a multiplexed reverse phase protein (RPP) microarray platform for simultaneous monitoring of site-specific phosphorylation of numerous signaling proteins using nanogram amounts of lysates derived from stimulated living cells. We first show the application of RPP microarrays to the study of signaling kinetics and pathway delineation in Jurkat T lymphocytes. RPP microarrays were used to profile the phosphorylation state of 62 signaling components in Jurkat T cells stimulated through their membrane CD3 and CD28 receptors, identifying a previously unrecognized link between CD3 crosslinking and dephosphorylation of Raf-1 at Ser259. Finally, the potential of this technology to analyze rare primary cell populations is shown in a study of differential STAT protein phosphorylation in interleukin (IL)-2-stimulated CD4(+)CD25(+) regulatory T cells. RPP microarrays, prepared using simple procedures and standard microarray equipment, represent a powerful new tool for the study of signal transduction in both health and disease.     

Development of functional gene microarrays for microbial community analysis

Functional gene arrays (FGAs) are a special type of microarrays containing probes for key genes involved in microbial functional processes, such as biogeochemical cycling of carbon, nitrogen, sulfur, phosphorus and metals, virulence and antibiotic resistance, biodegradation of environmental contaminants, and stress responses. FGAs have been demonstrated to be a specific, sensitive, and quantitative tool for rapid analysis of microbial communities from different habitats, such as waters, soils, extreme environments, bioreactors, and human microbiomes. In this review, we first summarize currently reported FGAs, and then focus on the FGA development. We will also discuss several key issues of FGA technology as well as challenges and directions in future FGA development.     

Comparison of different probe-level analysis techniques for oligonucleotide microarrays

Three different software packages for the probe-level analysis of high-density oligonucleotide microarray data were compared using an experiment-derived data set that was validated using real-time PCR. The efficiency with which these three programs could identify true positives in this data set was assessed. In addition, estimates of false-positive and false-negative rates were determined. The performance of the programs using very small data sets was also compared, and recommendations for use are suggested.