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An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data
- PLoS Comput. Biol
, 2009
"... The parts of the genome transcribed by a cell or tissue reflect the biological processes and functions it carries out. We characterized the features of mammalian tissue transcriptomes at the gene level through analysis of RNA deep sequencing (RNA-Seq) data across human and mouse tissues and cell lin ..."
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Cited by 58 (0 self)
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The parts of the genome transcribed by a cell or tissue reflect the biological processes and functions it carries out. We characterized the features of mammalian tissue transcriptomes at the gene level through analysis of RNA deep sequencing (RNA-Seq) data across human and mouse tissues and cell lines. We observed that roughly 8,000 protein-coding genes were ubiquitously expressed, contributing to around 75 % of all mRNAs by message copy number in most tissues. These mRNAs encoded proteins that were often intracellular, and tended to be involved in metabolism, transcription, RNA processing or translation. In contrast, genes for secreted or plasma membrane proteins were generally expressed in only a subset of tissues. The distribution of expression levels was broad but fairly continuous: no support was found for the concept of distinct expression classes of genes. Expression estimates that included reads mapping to coding exons only correlated better with qRT-PCR data than estimates which also included 39 untranslated regions (UTRs). Muscle and liver had the least complex transcriptomes, in that they expressed predominantly ubiquitous genes and a large fraction of the transcripts came from a few highly expressed genes, whereas brain, kidney and testis expressed more complex transcriptomes with the vast majority of genes expressed and relatively small contributions from the most expressed genes. mRNAs expressed in brain had unusually long 39UTRs, and mean 39UTR length was higher for genes involved in development, morphogenesis and signal transduction, suggesting added complexity of UTR-based regulation for these genes. Our results support a model in
Construction, visualisation, and clustering of transcription networks from microarray expression data
- PLoS Comput. Biol
, 2007
"... Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while mi ..."
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Cited by 25 (2 self)
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Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express 3D.
REVIEW Assessing the Evolution of Gene Expression Using Microarray Data
"... Abstract: Classical studies of the evolution of gene function have predominantly focused on mutations within protein coding regions. With the advent of microarrays, however, it has become possible to evaluate the transcriptional activity of a gene as an additional characteristic of function. Recent ..."
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Abstract: Classical studies of the evolution of gene function have predominantly focused on mutations within protein coding regions. With the advent of microarrays, however, it has become possible to evaluate the transcriptional activity of a gene as an additional characteristic of function. Recent studies have revealed an equally important role for gene regulation in the retention and evolution of duplicate genes. Here we review approaches to assessing the evolution of gene expression using microarray data, and discuss potential influences on expression divergence. Currently, there are no established standards on how best to identify and quantify instances of expression divergence. There have also been few efforts to date that incorporate suspected influences into mathematical models of expression divergence. Such developments will be crucial to a comprehensive understanding of the role gene duplications and expression evolution play in the emergence of complex traits and functional diversity. An integrative approach to gene family evolution, including both orthologous and paralogous genes, has the potential to bring strong predictive power both to the functional annotation of extant proteins and to the inference of functional characteristics of ancestral gene family members.
unknown title
, 2008
"... alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene ..."
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alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene
unknown title
, 2008
"... alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene ..."
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alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene
Supplementary material
"... Similar gene expression profiles do not imply similar tissue functions ..."
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unknown title
, 2008
"... alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene ..."
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alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene
unknown title
, 2008
"... MicroRNA-mediated up-regulation of an alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene ..."
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MicroRNA-mediated up-regulation of an alternatively polyadenylated variant of the mouse cytoplasmic b-actin gene
Edinburgh Research Explorer
"... Construction, visualisation, and clustering of transcription networks from Microarray expression data Citation for published version: ..."
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Construction, visualisation, and clustering of transcription networks from Microarray expression data Citation for published version:
Protein Conservation and Variation Suggest Mechanisms of Cell Type-Specific Modulation of Signaling Pathways
, 2014
"... Many proteins and signaling pathways are present in most cell types and tissues and yet perform specialized functions. To elucidate mechanisms by which these ubiquitous pathways are modulated, we overlaid information about cross-cell line protein abundance and variability, and evolutionary conservat ..."
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Many proteins and signaling pathways are present in most cell types and tissues and yet perform specialized functions. To elucidate mechanisms by which these ubiquitous pathways are modulated, we overlaid information about cross-cell line protein abundance and variability, and evolutionary conservation onto functional pathway components and topological layers in the pathway hierarchy. We found that the input (receptors) and the output (transcription factors) layers evolve more rapidly than proteins in the intermediary transmission layer. In contrast, protein expression variability decreases from the input to the output layer. We observed that the differences in protein variability between the input and transmission layer can be attributed to both the network position and the tendency of variable proteins to physically interact with constitutively expressed proteins. Differences in protein expression variability and conservation are also accompanied by the tendency of conserved and constitutively expressed proteins to acquire somatic mutations, while germline mutations tend to occur in cell type-specific proteins. Thus, conserved core proteins in the transmission layer could perform a fundamental role in most cell types and are therefore less tolerant to germline mutations. In summary, we propose that the core signal transmission machinery is largely modulated by a variable input layer through physical protein interactions. We hypothesize that the bow-tie organization of cellular signaling on the level of protein abundance variability contributes to
