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.
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TL;DR: In infected mice, FCRL5 is expressed on the majority of antigen-specific germinal-center-derived memory B cells (MBCs), and upon challenge,FCRL5+ MBCs rapidly give rise to antibody-producing cells expressing additional atypical markers, demonstrating functionality in vivo.
71 citations
TL;DR: The practical implementation of iPSCs to study HD is examined, such as approaches to differentiate embryonic stem cells (ESCs) or iPSC into medium spiny neurons, the cell type most susceptible in HD.
64 citations
Cites background from "Large scale comparison of global ge..."
...While some reports show a high conservation in expression of orthologous genes (Zheng-Bradley et al., 2010), there are many examples of divergence of gene function, alternate splicing events and differences in copy number variants between mice and humans (Gharib and Robinson-Rechavi, 2011) (Table…...
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...While some reports show a high conservation in expression of orthologous genes (Zheng-Bradley et al., 2010), there are many examples of divergence of gene function, alternate splicing events and differences in copy number variants between mice and humans (Gharib and Robinson-Rechavi, 2011) (Table 1)....
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TL;DR: Together, the oligonucleotide microarray and the PiceaGenExpress database represent the first resource of this kind for gymnosperm plants and are expected to accelerate genetic studies in the large and important group of conifer trees.
Abstract: Conifers have very large genomes (13 to 30 Gigabases) that are mostly uncharacterized although extensive cDNA resources have recently become available. This report presents a global overview of transcriptome variation in a conifer tree and documents conservation and diversity of gene expression patterns among major vegetative tissues. An oligonucleotide microarray was developed from Picea glauca and P. sitchensis cDNA datasets. It represents 23,853 unique genes and was shown to be suitable for transcriptome profiling in several species. A comparison of secondary xylem and phelloderm tissues showed that preferential expression in these vascular tissues was highly conserved among Picea spp. RNA-Sequencing strongly confirmed tissue preferential expression and provided a robust validation of the microarray design. A small database of transcription profiles called PiceaGenExpress was developed from over 150 hybridizations spanning eight major tissue types. In total, transcripts were detected for 92% of the genes on the microarray, in at least one tissue. Non-annotated genes were predominantly expressed at low levels in fewer tissues than genes of known or predicted function. Diversity of expression within gene families may be rapidly assessed from PiceaGenExpress. In conifer trees, dehydrins and late embryogenesis abundant (LEA) osmotic regulation proteins occur in large gene families compared to angiosperms. Strong contrasts and low diversity was observed in the dehydrin family, while diverse patterns suggested a greater degree of diversification among LEAs. Together, the oligonucleotide microarray and the PiceaGenExpress database represent the first resource of this kind for gymnosperm plants. The spruce transcriptome analysis reported here is expected to accelerate genetic studies in the large and important group comprised of conifer trees.
62 citations
Cites background or result from "Large scale comparison of global ge..."
...It is also consistent with findings from comparative expression studies of mice and humans showing that house-keeping genes were more highly expressed and were more conserved among species both in terms of their sequence and their expression [7]....
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...A comparative analysis of mouse and human showed a high level of conservation in the expression of orthologous genes, showing the stability of house-keeping genes and the variability of tissue specific genes [7]....
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TL;DR: The molecular and cellular mechanisms underpinning olfaction in teleosts and mammals are similar despite 430 million years of evolutionary divergence, and novel marker genes that characterize rare neuronal populations in both mouse and zebrafish are identified.
Abstract: Studies of the two major olfactory organs of rodents, the olfactory mucosa (OM) and the vomeronasal organ (VNO), unraveled the molecular basis of smell in vertebrates. However, some vertebrates lack a VNO. Here we generated and analyzed the olfactory transcriptome of the zebrafish and compared it to the olfactory transcriptomes of mouse to investigate the evolutionary and molecular relationship between single and dual olfactory systems. Our analyses revealed a high degree of molecular conservation, with orthologs of mouse olfactory cell-specific markers and all but one of their chemosensory receptor classes expressed in the single zebrafish olfactory organ. Zebrafish chemosensory receptor genes are expressed across a large dynamic range and their RNA abundance correlates positively with the number of neurons expressing that RNA. Thus we estimate the relative proportions of neuronal sub-types expressing different chemosensory receptors. Receptor repertoire size drives the absolute abundance of different classes of neurons, but we find similar underlying patterns in both species. Finally, we identified novel marker genes that characterize rare neuronal populations in both mouse and zebrafish. In sum, we find that the molecular and cellular mechanisms underpinning olfaction in teleosts and mammals are similar despite 430 million years of evolutionary divergence.
62 citations
TL;DR: The Sanger Mouse Genetics Project generates knockout mice strains using the EUCOMM/KOMP-CSD embryonic stem (ES) cell collection and characterizes the consequences of the mutations using a high-throughput primary phenotyping screen.
Abstract: The Sanger Mouse Genetics Project generates knockout mice strains using the EUCOMM/KOMP-CSD embryonic stem (ES) cell collection and characterizes the consequences of the mutations using a high-throughput primary phenotyping screen. Upon achieving germline transmission, new strains are subject to a panel of quality control (QC) PCR- and qPCR-based assays to confirm the correct targeting, cassette structure, and the presence of the 3′ LoxP site (required for the potential conditionality of the allele). We report that over 86 % of the 731 strains studied showed the correct targeting and cassette structure, of which 97 % retained the 3′ LoxP site. We discuss the characteristics of the lines that failed QC and postulate that the majority of these may be due to mixed ES cell populations which were not detectable with the original screening techniques employed when creating the ES cell resource.
61 citations
References
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TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
34,830 citations
TL;DR: There is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities, and the exploratory data analyses of the probe level data motivate a new summary measure that is a robust multi-array average (RMA) of background-adjusted, normalized, and log-transformed PM values.
Abstract: SUMMARY In this paper we report exploratory analyses of high-density oligonucleotide array data from the Affymetrix GeneChip R � system with the objective of improving upon currently used measures of gene expression. Our analyses make use of three data sets: a small experimental study consisting of five MGU74A mouse GeneChip R � arrays, part of the data from an extensive spike-in study conducted by Gene Logic and Wyeth’s Genetics Institute involving 95 HG-U95A human GeneChip R � arrays; and part of a dilution study conducted by Gene Logic involving 75 HG-U95A GeneChip R � arrays. We display some familiar features of the perfect match and mismatch probe ( PM and MM )v alues of these data, and examine the variance–mean relationship with probe-level data from probes believed to be defective, and so delivering noise only. We explain why we need to normalize the arrays to one another using probe level intensities. We then examine the behavior of the PM and MM using spike-in data and assess three commonly used summary measures: Affymetrix’s (i) average difference (AvDiff) and (ii) MAS 5.0 signal, and (iii) the Li and Wong multiplicative model-based expression index (MBEI). The exploratory data analyses of the probe level data motivate a new summary measure that is a robust multiarray average (RMA) of background-adjusted, normalized, and log-transformed PM values. We evaluate the four expression summary measures using the dilution study data, assessing their behavior in terms of bias, variance and (for MBEI and RMA) model fit. Finally, we evaluate the algorithms in terms of their ability to detect known levels of differential expression using the spike-in data. We conclude that there is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities. ∗ To whom correspondence should be addressed
10,711 citations
"Large scale comparison of global ge..." refers methods in this paper
...The resulting 1,323 CEL files were pre-processed using Bioconductor’s RMA package [32] to create an integrated, normalized data matrix....
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TL;DR: In this paper, high-density oligonucleotide arrays offer the opportunity to examine patterns of gene expression on a genome scale, and the authors have designed custom arrays that interrogate the expression of the vast majority of proteinencoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues.
Abstract: The tissue-specific pattern of mRNA expression can indicate important clues about gene function. High-density oligonucleotide arrays offer the opportunity to examine patterns of gene expression on a genome scale. Toward this end, we have designed custom arrays that interrogate the expression of the vast majority of protein-encoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues. The resulting data set provides the expression patterns for thousands of predicted genes, as well as known and poorly characterized genes, from mice and humans. We have explored this data set for global trends in gene expression, evaluated commonly used lines of evidence in gene prediction methodologies, and investigated patterns indicative of chromosomal organization of transcription. We describe hundreds of regions of correlated transcription and show that some are subject to both tissue and parental allele-specific expression, suggesting a link between spatial expression and imprinting.
3,513 citations
"Large scale comparison of global ge..." refers background or 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]....
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...Alternatively, many other studies made use of species-specific arrays to identify coexpressed groups of orthologous genes [4-6,16,17]....
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TL;DR: The ability of the trained ANN models to recognize SRBCTs is demonstrated, and the potential applications of these methods for tumor diagnosis and the identification of candidate targets for therapy are demonstrated.
Abstract: The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in clinical practice. The ANNs correctly classified all samples and identified the genes most relevant to the classification. Expression of several of these genes has been reported in SRBCTs, but most have not been associated with these cancers. To test the ability of the trained ANN models to recognize SRBCTs, we analyzed additional blinded samples that were not previously used for the training procedure, and correctly classified them in all cases. This study demonstrates the potential applications of these methods for tumor diagnosis and the identification of candidate targets for therapy.
2,683 citations
"Large scale comparison of global ge..." refers methods in this paper
...PCA has been often used to study high-dimensional data generated by genome-wide gene expression studies [22-25]....
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Book•
27 Jan 2006
TL;DR: In this article, the authors present a detailed case study of R algorithms with publicly available data, and a major section of the book is devoted to fully worked case studies, with a companion website where readers can reproduce every number, figure and table on their own computers.
Abstract: Full four-color book.
Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R.
All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies.
Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
2,625 citations