Large scale comparison of global gene expression patterns in human and mouse
TL;DR: The results indicate that the global patterns of tissue-specific expression of orthologous genes are conserved in human and mouse.
Abstract: It is widely accepted that orthologous genes between species are conserved at the sequence level and perform similar functions in different organisms. However, the level of conservation of gene expression patterns of the orthologous genes in different species has been unclear. To address the issue, we compared gene expression of orthologous genes based on 2,557 human and 1,267 mouse samples with high quality gene expression data, selected from experiments stored in the public microarray repository ArrayExpress. In a principal component analysis (PCA) of combined data from human and mouse samples merged on orthologous probesets, samples largely form distinctive clusters based on their tissue sources when projected onto the top principal components. The most prominent groups are the nervous system, muscle/heart tissues, liver and cell lines. Despite the great differences in sample characteristics and experiment conditions, the overall patterns of these prominent clusters are strikingly similar for human and mouse. We further analyzed data for each tissue separately and found that the most variable genes in each tissue are highly enriched with human-mouse tissue-specific orthologs and the least variable genes in each tissue are enriched with human-mouse housekeeping orthologs. The results indicate that the global patterns of tissue-specific expression of orthologous genes are conserved in human and mouse. The expression of groups of orthologous genes co-varies in the two species, both for the most variable genes and the most ubiquitously expressed genes.
Citations
More filters
01 Mar 2001
TL;DR: Using singular value decomposition in transforming genome-wide expression data from genes x arrays space to reduced diagonalized "eigengenes" x "eigenarrays" space gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype.
Abstract: ‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.
1,815 citations
TL;DR: The utility of the gene expression data that are in the public domain and how researchers are making use of these data are discussed and recommendations are provided that can improve the utility of such data.
Abstract: Our understanding of gene expression has changed dramatically over the past decade, largely catalysed by technological developments. High-throughput experiments - microarrays and next-generation sequencing - have generated large amounts of genome-wide gene expression data that are collected in public archives. Added-value databases process, analyse and annotate these data further to make them accessible to every biologist. In this Review, we discuss the utility of the gene expression data that are in the public domain and how researchers are making use of these data. Reuse of public data can be very powerful, but there are many obstacles in data preparation and analysis and in the interpretation of the results. We will discuss these challenges and provide recommendations that we believe can improve the utility of such data.
335 citations
TL;DR: It is demonstrated that PhenomeNET can identify orthologous genes, genes involved in the same pathway and gene–disease associations through the comparison of mutant phenotypes, and is applied to prioritize genes for rare and orphan diseases for which the molecular basis is unknown.
Abstract: Phenotypes are investigated in model organisms to understand and reveal the molecular mechanisms underlying disease. Phenotype ontologies were developed to capture and compare phenotypes within the context of a single species. Recently, these ontologies were augmented with formal class definitions that may be utilized to integrate phenotypic data and enable the direct comparison of phenotypes between different species. We have developed a method to transform phenotype ontologies into a formal representation, combine phenotype ontologies with anatomy ontologies, and apply a measure of semantic similarity to construct the PhenomeNET cross-species phenotype network. We demonstrate that PhenomeNET can identify orthologous genes, genes involved in the same pathway and gene–disease associations through the comparison of mutant phenotypes. We provide evidence that the Adam19 and Fgf15 genes in mice are involved in the tetralogy of Fallot, and, using zebrafish phenotypes, propose the hypothesis that the mammalian homologs of Cx36.7 and Nkx2.5 lie in a pathway controlling cardiac morphogenesis and electrical conductivity which, when defective, cause the tetralogy of Fallot phenotype. Our method implements a whole-phenome approach toward disease gene discovery and can be applied to prioritize genes for rare and orphan diseases for which the molecular basis is unknown.
221 citations
Cites background from "Large scale comparison of global ge..."
...As orthologous genes tend to be associated with related phenotypes and share common patterns of gene expression across species (15,16), the former provides a useful validation of the PhenomeNET approach....
[...]
TL;DR: The Gene Expression Atlas is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions.
Abstract: Gene Expression Atlas (http://www.ebi.ac.uk/gxa) is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions. The content of this database derives from curation, re-annotation and statistical analysis of selected data from the ArrayExpress Archive and the European Nucleotide Archive. A simple interface allows the user to query for differential gene expression either by gene names or attributes or by biological conditions, e.g. diseases, organism parts or cell types. Since our previous report we made 20 monthly releases and, as of Release 11.08 (August 2011), the database supports 19 species, which contains expression data measured for 19,014 biological conditions in 136,551 assays from 5598 independent studies.
166 citations
Cites methods from "Large scale comparison of global ge..."
...The Functional Genomics group has now produced two more data sets of this nature, including a global mouse data re-analysis (7) and an order-of-magnitude expansion of the human Affymetrix data set (unpublished data)....
[...]
TL;DR: Cross-species comparisons of genomes, transcriptomes and gene regulation are now feasible at unprecedented resolution and throughput, enabling the comparison of human and mouse biology at the molecular level.
Abstract: Cross-species comparisons of genomes, transcriptomes and gene regulation are now feasible at unprecedented resolution and throughput, enabling the comparison of human and mouse biology at the molecular level. Insights have been gained into the degree of conservation between human and mouse at the level of not only gene expression but also epigenetics and inter-individual variation. However, a number of limitations exist, including incomplete transcriptome characterization and difficulties in identifying orthologous phenotypes and cell types, which are beginning to be addressed by emerging technologies. Ultimately, these comparisons will help to identify the conditions under which the mouse is a suitable model of human physiology and disease, and optimize the use of animal models.
158 citations
References
More filters
TL;DR: An overview of current methods and software tools for quality assessment of Affymetrix GeneChip data is given and RNA quality assessment methods which play an important role in challenging RNA sources like formalin embedded biopsies, laser-micro dissected samples, or single cells are described.
Abstract: Affymetrix GeneChips are one of the best established microarray platforms. This powerful technique allows users to measure the expression of thousands of genes simultaneously. However, a microarray experiment is a sophisticated and time consuming endeavor with many potential sources of unwanted variation that could compromise the results if left uncontrolled. Increasing data volume and data complexity have triggered growing concern and awareness of the importance of assessing the quality of generated microarray data. In this review, we give an overview of current methods and software tools for quality assessment of Affymetrix GeneChip data. We focus on quality metrics, diagnostic plots, probe-level methods, pseudo-images, and classification methods to identify corrupted chips. We also describe RNA quality assessment methods which play an important role in challenging RNA sources like formalin embedded biopsies, laser-micro dissected samples, or single cells. No wet-lab methods are discussed in this paper.
216 citations
TL;DR: There are clearly strong evolutionary constraints on tissue-specific gene expression, and a major challenge will be to understand the precise mechanisms by which many gene expression patterns remain similar despite extensive cis-regulatory restructuring.
Abstract: Vertebrates share the same general body plan and organs, possess related sets of genes, and rely on similar physiological mechanisms, yet show great diversity in morphology, habitat and behavior. Alteration of gene regulation is thought to be a major mechanism in phenotypic variation and evolution, but relatively little is known about the broad patterns of conservation in gene expression in non-mammalian vertebrates. We measured expression of all known and predicted genes across twenty tissues in chicken, frog and pufferfish. By combining the results with human and mouse data and considering only ten common tissues, we have found evidence of conserved expression for more than a third of unique orthologous genes. We find that, on average, transcription factor gene expression is neither more nor less conserved than that of other genes. Strikingly, conservation of expression correlates poorly with the amount of conserved nonexonic sequence, even using a sequence alignment technique that accounts for non-collinearity in conserved elements. Many genes show conserved human/fish expression despite having almost no nonexonic conserved primary sequence. There are clearly strong evolutionary constraints on tissue-specific gene expression. A major challenge will be to understand the precise mechanisms by which many gene expression patterns remain similar despite extensive cis-regulatory restructuring.
199 citations
"Large scale comparison of global ge..." refers background or result in this paper
...It supports previous findings [6-9] that although mechanisms of individual gene regulation may be different between the species, global functional patterns are similar and identifiable with whole transcriptome analysis....
[...]
...Table 2 Comparison of the lists of genes that display the evolutionarily conserved expression patterns in different tissues as identified by us and by Chan and colleagues [6]...
[...]
...[6] also identified close to 400 1-1-1-1-1 orthologous genes across vertebrate clades that display conserved expression in at least one of ten tissues they tested at the most stringent threshold....
[...]
...This explains the observation made by others [6] and us that tissues with relatively homogenous composition of cell types, such as heart/muscle, liver, and nervous system, would be segregated when profiling large-scale gene expression data....
[...]
...Alternatively, many other studies made use of species-specific arrays to identify coexpressed groups of orthologous genes [4-6,16,17]....
[...]
01 Jan 2005
TL;DR: Chip pseudo-images of residuals and weights obtained from fitting robust linear models to the probe level data can be used as a visual tool for identifying artifacts on GeneChip microarrays.
Abstract: This chapter covers quality assessment for Affymetrix GeneChip data. The focus is on procedures available from the affy and affy-PLM packages. Initially some exploratory plots provided by the affy package, including images of the raw probe-level data, boxplots, histograms, and M vs A plots are examined. Next methods for assessing RNA degradation are discussed, specifically we compare the standard procedures recommended by Affymetrix and RNA degradation plots. Finally, we investigate how appropriate probe-level models yield good quality assessment tools. Chip pseudo-images of residuals and weights obtained from fitting robust linear models to the probe level data can be used as a visual tool for identifying artifacts on GeneChip microarrays. Other output from the probe-level modeling tools provide summary plots that may be used to identify aberrant chips.
196 citations
TL;DR: The level of gene expression and the degree of tissue specificity are generally conserved between the human and mouse orthologs and are analogous to the observation that the rate of gene (or protein) sequence evolution is negatively correlated with the gene expression level.
Abstract: Evolutionary rates provide important information about the pattern and mechanism of evolution. Although the rate of gene sequence evolution has been well studied, the rate of gene expression evolution is poorly understood. In particular, it is unclear whether the gene expression level and tissue specificity influence the divergence of expression profiles between orthologous genes. Here we address this question using a microarray data set comprising the expression signals of 10,607 pairs of orthologous human and mouse genes from over 60 tissues per species. We show that the level of gene expression and the degree of tissue specificity are generally conserved between the human and mouse orthologs. The rate of gene expression profile change during evolution is negatively correlated with the level of gene expression, measured by either the average or the highest level among all tissues examined. This is analogous to the observation that the rate of gene (or protein) sequence evolution is negatively correlated with the gene expression level. The impacts of the degree of tissue specificity on the evolutionary rate of gene sequence and that of expression profile, however, are opposite. Highly tissue-specific genes tend to evolve rapidly at the gene sequence level but slowly at the expression profile level. Thus, different forces and selective constraints must underlie the evolution of gene sequence and that of gene expression.
146 citations
"Large scale comparison of global ge..." refers result in this paper
...While studies suggested that orthologous genes do not share similar expression patterns [1-5], other groups reported the opposite observations [6-9]....
[...]
...It supports previous findings [6-9] that although mechanisms of individual gene regulation may be different between the species, global functional patterns are similar and identifiable with whole transcriptome analysis....
[...]
TL;DR: Results indicate that gene expression divergence is subject to the effects of purifying selective constraint and suggest that it might also be substantially influenced by positive Darwinian selection.
145 citations
"Large scale comparison of global ge..." refers result in this paper
...While studies suggested that orthologous genes do not share similar expression patterns [1-5], other groups reported the opposite observations [6-9]....
[...]