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Towards reconstruction of gene networks from expression data by supervised learning

GENOME BIOLOGY 2003年第1期4卷 R6-R6页

作者： Soinov, LA Krestyaninova, MA Brazma, A European Bioinformat Inst Microarray Informat Grp Cambridge CB10 1SD England European Bioinformat Inst Sequence Database Grp Cambridge CB10 1SD England

Background: Microarray experiments are generating datasets that can help in reconstructing gene networks. One of the most important problems in network reconstruction is finding, for each gene in the network, which genes can affect it and how. We use a supervised learning approach to address this question by building decision-tree-related classifiers, which predict gene expression from the expression data of other genes. Results: We present algorithms that work for continuous expression levels and do not require a priori discretization. We apply our method to publicly available data for the budding yeast cell cycle. The obtained classifiers can be presented as simple rules defining gene interrelations. In most cases the extracted rules confirm the existing knowledge about cell-cycle gene expression, while hitherto unknown relationships can be treated as new hypotheses. Conclusions: All the relations between the considered genes are consistent with the facts reported in the literature. This indicates that the approach presented here is valid and that the resulting rules can be used as elements for building and explaining gene networks.

关键词： additional data file Classification Rule Minimum Description Length Network Reconstruction Induction Algorithm

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Analysis of gene expression in a developmental context emphasizes distinct biological leitmotifs in human cancers

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GENOME BIOLOGY 2008年第7期9卷 R108-R108页

作者： Naxerova, Kamila Bult, Carol J. Peaston, Anne Fancher, Karen Knowles, Barbara B. Kasif, Simon Kohane, Isaac S. Harvard Mit Div Hlth Sci & Technol Childrens Hosp Informat Program Boston MA 02115 USA Jackson Lab Bar Harbor ME 04609 USA Boston Univ Dept Biomed Engn Boston MA 02215 USA

Background: In recent years, the molecular underpinnings of the long-observed resemblance between neoplastic and immature tissue have begun to emerge. Genome-wide transcriptional profiling has revealed similar gene expression signatures in several tumor types and early developmental stages of their tissue of origin. However, it remains unclear whether such a relationship is a universal feature of malignancy, whether heterogeneities exist in the developmental component of different tumor types and to which degree the resemblance between cancer and development is a tissue-specific phenomenon. Results: We defined a developmental landscape by summarizing the main features of ten developmental time courses and projected gene expression from a variety of human tumor types onto this landscape. This comparison demonstrates a clear imprint of developmental gene expression in a wide range of tumors and with respect to different, even non-cognate developmental backgrounds. Our analysis reveals three classes of cancers with developmentally distinct transcriptional patterns. We characterize the biological processes dominating these classes and validate the class distinction with respect to a new time series of murine embryonic lung development. Finally, we identify a set of genes that are upregulated in most cancers and we show that this signature is active in early development. Conclusion: This systematic and quantitative overview of the relationship between the neoplastic and developmental transcriptome spanning dozens of tissues provides a reliable outline of global trends in cancer gene expression, reveals potentially clinically relevant differences in the gene expression of different cancer types and represents a reference framework for interpretation of smaller-scale functional studies.

关键词： Papillary Thyroid Carcinoma additional data file Gene Expression Signature Downregulated Gene Lung Development

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Quantitative protein expression profiling reveals extensive post-transcriptional regulation and post-translational modifications in schizont-stage malaria parasites

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GENOME BIOLOGY 2008年第12期9卷 R177-R177页

作者： Foth, Bernardo J. Zhang, Neng Mok, Sachel Preiser, Peter R. Bozdech, Zbynek Nanyang Technol Univ Sch Biol Sci Singapore 637551 Singapore

Background: Malaria is a one of the most important infectious diseases and is caused by parasitic protozoa of the genus Plasmodium. Previously, quantitative characterization of the P. falciparum transcriptome demonstrated that the strictly controlled progression of these parasites through their intra-erythrocytic developmental cycle is accompanied by a continuous cascade of gene expression. Although such analyses have proven immensely useful, the correlations between abundance of transcripts and their cognate proteins remain poorly characterized. Results: Here, we present a quantitative time-course analysis of relative protein abundance for schizont-stage parasites (34 to 46 hours after invasion) based on two-dimensional differential gel electrophoresis of protein samples labeled with fluorescent dyes. For this purpose we analyzed parasite samples taken at 4-hour intervals from a tightly synchronized culture and established more than 500 individual protein abundance profiles with high temporal resolution and quantitative reproducibility. Approximately half of all profiles exhibit a significant change in abundance and 12% display an expression peak during the observed 12-hour time interval. Intriguingly, identification of 54 protein spots by mass spectrometry revealed that 58% of the corresponding proteins - including actin-I, enolase, eukaryotic initiation factor (eIF) 4A, eIF5A, and several heat shock proteins - are represented by more than one isoform, presumably caused by post-translational modifications, with the various isoforms of a given protein frequently showing different expression patterns. Furthermore, comparisons with transcriptome data generated from the same parasite samples reveal evidence of significant post-transcriptional gene expression regulation. Conclusions: Together, our data indicate that both post-transcriptional and post-translational events are widespread and of presumably great biological significance during the intra-erythrocytic develo

关键词： Protein Spot Protein Abundance additional data file Protein Expression Profile Schizont Stage

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Comparing cDNA and oligonucleotide array data: concordance of gene expression across platforms for the NCI-60 cancer cells

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GENOME BIOLOGY 2003年第12期4卷 R82-R82页

作者： Lee, JK Bussey, KJ Gwadry, FG Reinhold, W Riddick, G Pelletier, SL Nishizuka, S Szakacs, G Annereau, JP Shankavaram, U Lababidi, S Smith, LH Gottesman, MM Weinstein, JN NCI Cell Biol Lab Ctr Canc Res NIH Bethesda MD 20892 USA NCI Mol Pharmacol Lab Ctr Canc Res NIH Bethesda MD 20892 USA

Microarray gene-expression profiles are generally validated one gene at a time by real-time RT-PCR. We describe here a different approach based on simultaneous mutual validation of large numbers of genes using two different expression-profiling platforms. The result described here for the NCI-60 cancer cell lines is a consensus set of genes that give similar profiles on spotted cDNA arrays and Affymetrix oligonucleotide chips. Global concordance is parameterized by a 'correlation of correlations' coefficient.

关键词： additional data file Oligo Array cDNA Array UniGene Cluster Correlation Screening

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Defining the chromatin signature of inducible genes in T cells

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GENOME BIOLOGY 2009年第10期10卷 R107-R107页

作者： Lim, Pek S. Hardy, Kristine Bunting, Karen L. Ma, Lina Peng, Kaiman Chen, Xinxin Shannon, Mary F. Australian Natl Univ Genome Biol Program John Curtin Sch Med Res Acton ACT 0200 Australia Australian Natl Univ ACRF Biomol Resource Facil John Curtin Sch Med Res Acton ACT 0200 Australia

Background: Specific chromatin characteristics, especially the modification status of the core histone proteins, are associated with active and inactive genes. There is growing evidence that genes that respond to environmental or developmental signals may possess distinct chromatin marks. Using a T cell model and both genome-wide and gene-focused approaches, we examined the chromatin characteristics of genes that respond to T cell activation. Results: To facilitate comparison of genes with similar basal expression levels, we used expression-profiling data to bin genes according to their basal expression levels. We found that inducible genes in the lower basal expression bins, especially rapidly induced primary response genes, were more likely than their non-responsive counterparts to display the histone modifications of active genes, have RNA polymerase II (Pol II) at their promoters and show evidence of ongoing basal elongation. There was little or no evidence for the presence of active chromatin marks in the absence of promoter Pol II on these inducible genes. In addition, we identified a subgroup of genes with active promoter chromatin marks and promoter Pol II but no evidence of elongation. Following T cell activation, we find little evidence for a major shift in the active chromatin signature around inducible gene promoters but many genes recruit more Pol II and show increased evidence of elongation. Conclusions: These results suggest that the majority of inducible genes are primed for activation by having an active chromatin signature and promoter Pol II with or without ongoing elongation.

关键词： additional data file Inducible Gene Active Chromatin Basal Expression Level Primary Response Gene

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Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions

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GENOME BIOLOGY 2001年第2期2卷 1-13页

作者： Haab, Brian B. Dunham, Maitreya J. Brown, Patrick O. Stanford Univ Sch Med Dept Biochem Stanford CA 94305 USA Stanford Univ Sch Med Dept Genet Stanford CA 94305 USA

Background: We have developed and tested a method for printing protein microarrays and using these microarrays in a comparative fluorescence assay to measure the abundance of many specific proteins in complex solutions. A robotic device was used to print hundreds of specific antibody or antigen solutions in an array on the surface of derivatized microscope slides. Two complex protein samples, one serving as a standard for comparative quantitation, the other representing an experimental sample in which the protein quantities were to be measured, were labeled by covalent attachment of spectrally resolvable fluorescent dyes. Results: Specific antibody-antigen interactions localized specific components of the complex mixtures to defined cognate spots in the array, where the relative intensity of the fluorescent signal representing the experimental sample and the reference standard provided a measure of each protein's abundance in the experimental sample. To test the specificity, sensitivity and accuracy of this assay, we analyzed the performance of 115 antibody/antigen pairs. 50% of the arrayed antigens and 20% of the arrayed antibodies provided specific and accurate measurements of their cognate ligands at or below concentrations of 0.34 mu g/ml and 1.6 mu g/ml, respectively. Some of the antibody/antigen pairs allowed detection of the cognate ligands at absolute concentrations below 1 ng/ml, and partial concentrations of 1 part in 106, sensitivities sufficient for measurement of many clinically important proteins in patient blood samples. Conclusions: These results suggest that protein microarrays can provide a practical means to characterize patterns of variation in hundreds of thousands of different proteins in clinical or research applications.

关键词： additional data file Total Protein Concentration Fluorescence Ratio Protein Microarrays Partial Concentration

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The LeFE algorithm: embracing the complexity of gene expression in the interpretation of microarray data

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GENOME BIOLOGY 2007年第9期8卷 R187-R187页

作者： Eichler, Gabriel S. Reimers, Mark Kane, David Weinstein, John N. NCI Genom & Bioinformat Grp Mol Pharmacol Lab Ctr Canc ResNIH Bethesda MD 20892 USA Boston Univ Bioinformat Program Boston MA 02215 USA Virginia Commonwealth Univ Dept Biostat Richmond VA 23284 USA SRA Int Fairfax VA 22033 USA

Interpretation of microarray data remains a challenge, and most methods fail to consider the complex, nonlinear regulation of gene expression. To address that limitation, we introduce Learner of Functional Enrichment (LeFE), a statistical/machine learning algorithm based on Random Forest, and demonstrate it on several diverse datasets: smoker/never smoker, breast cancer classification, and cancer drug sensitivity. We also compare it with previously published algorithms, including Gene Set Enrichment Analysis. LeFE regularly identifies statistically significant functional themes consistent with known biology.

关键词： Epidermal Growth Factor Receptor Gefitinib additional data file Gene Category Signature Vector

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The source of laterally transferred genes in bacterial genomes -: art. no. R57

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GENOME BIOLOGY 2003年第9期4卷 R57-R57页

作者： Daubin, V Lerat, E Perrière, G Univ Lyon 1 UMR CNRS 5558 Lab Biometrie & Biol Evolut F-69622 Villeurbanne France

Background: Laterally transferred genes have often been identified on the basis of compositional features that distinguish them from ancestral genes in the genome. These genes are usually A+T-rich, arguing either that there is a bias towards acquiring genes from donor organisms having low G+C contents or that genes acquired from organisms of similar genomic base compositions go undetected in these analyses. Results: By examining the genome contents of closely related, fully sequenced bacteria, we uncovered genes confined to a single genome and examined the sequence features of these acquired genes. The analysis shows that few transfer events are overlooked by compositional analyses. Most observed lateral gene transfers do not correspond to free exchange of regular genes among bacterial genomes, but more probably represent the constituents of phages or other selfish elements. Conclusions: Although bacteria tend to acquire large amounts of DNA, the origin of these genes remains obscure. We have shown that contrary to what is often supposed, their composition cannot be explained by a previous genomic context. In contrast, these genes fit the description of recently described genes in lambdoid phages, named 'morons'. Therefore, results from genome content and compositional approaches to detect lateral transfers should not be cited as evidence for genetic exchange between distantly related bacteria.

关键词： Codon Codon Usage additional data file Base Composition Native Gene

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Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses

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GENOME BIOLOGY 2007年第6期8卷 R101-R101页

作者： Li, Long Zhu, Qianqian He, Xin Sinha, Saurabh Halfon, Marc S. SUNY Buffalo Dept Biochem Buffalo NY 14214 USA SUNY Buffalo Dept Biol Sci Buffalo NY 14214 USA Univ Illinois Dept Comp Sci Urbana IL 61801 USA New York State Ctr Excellence Bioinformat & Life Buffalo NY 14203 USA Roswell Pk Canc Inst Dept Mol & Cellular Biol Buffalo NY 14263 USA

Background: Transcriptional cis-regulatory modules (for example, enhancers) play a critical role in regulating gene expression. While many individual regulatory elements have been characterized, they have never been analyzed as a class. Results: We have performed the first such large-scale study of cis-regulatory modules in order to determine whether they have common properties that might aid in their identification and contribute to our understanding of the mechanisms by which they function. A total of 280 individual, experimentally verified cis-regulatory modules from Drosophila were analyzed for a range of sequence-level and functional properties. We report here that regulatory modules do indeed share common properties, among them an elevated GC content, an increased level of interspecific sequence conservation, and a tendency to be transcribed into RNA. However, we find that dense clustering of transcription factor binding sites, especially homotypic clustering, which is commonly believed to be a general characteristic of regulatory modules, is rather a feature that belongs chiefly to a specific subclass. This has important implications for current computational approaches, many of which are biased toward this subset. We explore two new strategies to assess binding site clustering and gauge their performances with respect to their ability to detect all 280 modules and various functionally coherent subsets. Conclusion: Our findings demonstrate that cis-regulatory modules share common features that help to define them as a class and that may lead to new insights into mechanisms of gene regulation. However, these properties alone may not be sufficient to reliably distinguish regulatory from nonregulatory sequences. We also demonstrate that there are distinct subclasses of cis-regulatory modules that are more amenable to in silico detection than others and that these differences must be taken into account when attempting genome-wide regulatory element discovery.

关键词： Transcription Factor Binding Site additional data file Median Rank Morphogen Gradient Conservation Fraction

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Statistical modeling for selecting housekeeper genes

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GENOME BIOLOGY 2004年第8期5卷 1-10页

作者： Szabo, A Perou, CM Karaca, M Perreard, L Quackenbush, JF Bernard, PS Huntsman Canc Inst Dept Oncol Sci Salt Lake City UT 84112 USA Univ N Carolina Lineberger Comprehens Canc Ctr Chapel Hill NC 27599 USA Univ N Carolina Dept Genet Chapel Hill NC 27599 USA ARUP Labs Inc Salt Lake City UT 84108 USA Univ Utah Dept Pathol Salt Lake City UT 84112 USA

There is a need for statistical methods to identify genes that have minimal variation in expression across a variety of experimental conditions. These 'housekeeper' genes are widely employed as controls for quantification of test genes using gel analysis and real-time RT-PCR. Using real-time quantitative RT-PCR, we analyzed 80 primary breast tumors for variation in expression of six putative housekeeper genes (MRPL19 (mitochondrial ribosomal protein L19), PSMC4 (proteasome (prosome, macropain) 26S subunit, ATPase, 4), SF3A1 (splicing factor 3a, subunit 1, 120 kDa), PUM1 (pumilio homolog 1 (Drosophila)), ACTB (actin, beta) and GAPD (glyceraldehyde-3-phosphate dehydrogenase)). We present appropriate models for selecting the best housekeepers to normalize quantitative data within a given tissue type (for example, breast cancer) and across different types of tissue samples.

关键词： Mean Square Error Tissue Type additional data file Primary Breast Tumor Breast Tumor Sample

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