Quantitative monitoring of gene expression patterns with a complementary DNA microarray.
20 Oct 1995-Science (American Association for the Advancement of Science)-Vol. 270, Iss: 5235, pp 467-470
TL;DR: A high-capacity system was developed to monitor the expression of many genes in parallel by means of simultaneous, two-color fluorescence hybridization, which enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA.
Abstract: A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
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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: The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which opens up the possibility of studying the biological relevance of small expression differences.
Abstract: Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data. The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.
18,261 citations
Cites methods from "Quantitative monitoring of gene exp..."
...The average gene-specific variation (determined as coefficient of variation, in percent) for the three control genes with the smallest variation within each tissue panel after normalization with three different factors calculated as the geometric mean of the three control genes with the lowest (NF3(1-3)), highest (NF3(8-10)) and intermediate (NF3(6-8)) gene stability values (as determined by geNorm)....
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TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Abstract: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is de- scribed that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be inter- preted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly charac- terized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
16,371 citations
TL;DR: The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data and provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-power gene expression and genomic hybridization experiments.
Abstract: The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
10,968 citations
TL;DR: It is shown that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour.
Abstract: 12 Pathology and Microbiology, and 13 Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin's lymphoma, is clinically heterogeneous: 40% of patients respond well to current therapy and have prolonged survival, whereas the remainder succumb to the disease. We proposed that this variability in natural history reflects unrecognized molecular heterogeneity in the tumours. Using DNA microarrays, we have conducted a systematic characterization of gene expression in B-cell malignancies. Here we show that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour. We identified two molecularly distinct forms of DLBCL which had gene expression patterns indicative of different stages of B-cell differentiation. One type expressed genes characteristic of germinal centre B cells ('germinal centre B-like DLBCL'); the second type expressed genes normally induced during in vitro activation of peripheral blood B cells ('activated B-like DLBCL'). Patients with germinal centre B-like DLBCL had a significantly better overall survival than those with activated B-like DLBCL. The molecular classification of tumours on the basis of gene expression can thus identify previously undetected and clinically significant subtypes of cancer.
9,493 citations
Additional excerpts
...The right panel depicts gene expression data from the following normal B-cell samples: (1) Total CD19 blood B cells; (2) Naive CD27 blood B cells; (3) Memory CD27 blood B cells; (4) cord blood CD19 B cells; (5) blood B cells; anti-IgM 6 h; (6) blood B cells; anti-IgM + IL-4 6 h; (7) blood B cells; anti-IgM + CD40 ligand 6 h; (8) blood B cells; anti-IgM + CD40 ligand + IL-4 6 h; (9) blood B cells; anti-IgM 24 h; (10) blood B cells; anti-IgM + IL-4 24 h; (11) blood B cells; anti-IgM + CD40 ligand 24 h; (12) blood B cells; anti-IgM + CD40 ligand + IL-4 24 h; (13) blood B cells; anti-IgM + CD40 ligand (low concentration) 48 h; (14) blood B cells; anti-IgM + CD40 ligand (high concentration) 48 h; (15) tonsil germinal centre B cells; (16) tonsil germinal centre centroblasts....
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TL;DR: Results indicate successful gene transfer into long-lasting progenitor cells, producing a functional multilineage progeny.
Abstract: Adenosine deaminase (ADA) deficiency results in severe combined immunodeficiency, the first genetic disorder treated by gene therapy. Two different retroviral vectors were used to transfer ex vivo the human ADA minigene into bone marrow cells and peripheral blood lymphocytes from two patients undergoing exogenous enzyme replacement therapy. After 2 years of treatment, long-term survival of T and B lymphocytes, marrow cells, and granulocytes expressing the transferred ADA gene was demonstrated and resulted in normalization of the immune repertoire and restoration of cellular and humoral immunity. After discontinuation of treatment, T lymphocytes, derived from transduced peripheral blood lymphocytes, were progressively replaced by marrow-derived T cells in both patients. These results indicate successful gene transfer into long-lasting progenitor cells, producing a functional multilineage progeny.
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TL;DR: The more than 13,400 plant ESTs that are currently available provide a new resource that will facilitate progress in many areas of plant biology and are illustrated by a description of the results obtained from analysis of 1500 Arabidopsis ESTs from a cDNA library prepared from equal portions of poly(A+) mRNA from etiolated seedlings, roots, leaves, and flowering inflorescence.
Abstract: High-throughput automated partial sequencing of anonymous cDNA clones provides a method to survey the repertoire of expressed genes from an organism. Comparison of the coding capacity of these expressed sequence tags (ESTs) with the sequences in the public data bases results in assignment of putative function to a significant proportion of the ESTs. Thus, the more than 13,400 plant ESTs that are currently available provide a new resource that will facilitate progress in many areas of plant biology. These opportunities are illustrated by a description of the results obtained from analysis of 1500 Arabidopsis ESTs from a cDNA library prepared from equal portions of poly(A+) mRNA from etiolated seedlings, roots, leaves, and flowering inflorescences. More than 900 different sequences were represented, 32% of which showed significant nucleotide or deduced amino acid sequence similarity to previously characterized genes or proteins from a wide range of organisms. At least 165 of the clones had significant deduced amino acid sequence homology to proteins or gene products that have not been previously characterized from higher plants. A summary of methods for accessing the information and materials generated by the Arabidopsis cDNA sequencing projects is provided.
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