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      Genome wide profiling of human embryonic stem cells (hESCs), their derivatives and embryonal carcinoma cells to develop base profiles of U.S. Federal government approved hESC lines

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          Abstract

          Background

          In order to compare the gene expression profiles of human embryonic stem cell (hESC) lines and their differentiated progeny and to monitor feeder contaminations, we have examined gene expression in seven hESC lines and human fibroblast feeder cells using Illumina ® bead arrays that contain probes for 24,131 transcript probes.

          Results

          A total of 48 different samples (including duplicates) grown in multiple laboratories under different conditions were analyzed and pairwise comparisons were performed in all groups. Hierarchical clustering showed that blinded duplicates were correctly identified as the closest related samples. hESC lines clustered together irrespective of the laboratory in which they were maintained. hESCs could be readily distinguished from embryoid bodies (EB) differentiated from them and the karyotypically abnormal hESC line BG01V. The embryonal carcinoma (EC) line NTera2 is a useful model for evaluating characteristics of hESCs. Expression of subsets of individual genes was validated by comparing with published databases, MPSS (Massively Parallel Signature Sequencing) libraries, and parallel analysis by microarray and RT-PCR.

          Conclusion

          we show that Illumina's bead array platform is a reliable, reproducible and robust method for developing base global profiles of cells and identifying similarities and differences in large number of samples.

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          Most cited references24

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          Clustering gene expression patterns.

          Recent advances in biotechnology allow researchers to measure expression levels for thousands of genes simultaneously, across different conditions and over time. Analysis of data produced by such experiments offers potential insight into gene function and regulatory mechanisms. A key step in the analysis of gene expression data is the detection of groups of genes that manifest similar expression patterns. The corresponding algorithmic problem is to cluster multicondition gene expression patterns. In this paper we describe a novel clustering algorithm that was developed for analysis of gene expression data. We define an appropriate stochastic error model on the input, and prove that under the conditions of the model, the algorithm recovers the cluster structure with high probability. The running time of the algorithm on an n-gene dataset is O[n2[log(n)]c]. We also present a practical heuristic based on the same algorithmic ideas. The heuristic was implemented and its performance is demonstrated on simulated data and on real gene expression data, with very promising results.
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            Amplified RNA synthesized from limited quantities of heterogeneous cDNA.

            The heterogeneity of neural gene expression and the spatially limited expression of many low-abundance messenger RNAs in the brain has made cloning and analysis of such messages difficult. To generate amounts of nucleic acids sufficient for use in standard cloning strategies, we have devised a method for producing amplified heterogeneous populations of RNA from limited quantities of cDNA. Whole cerebellar RNA was primed with a synthetic oligonucleotide containing the T7 RNA polymerase promoter sequence 5' to a polythymidylate region. After second-strand cDNA synthesis, T7 RNA polymerase was used to generate amplified antisense RNA (aRNA). Up to 80-fold molar amplification has been achieved from nanogram quantities of cDNA. The amplified material is similar in size distribution to the parent cDNA and shows sequence heterogeneity as assessed by Southern and Northern blot analysis. Specific messages for moderate-abundance mRNAs for actin and guanine nucleotide-binding protein (G-protein) alpha subunits have been detected in the amplified material. By using in situ transcription to generate cDNA, sequences for cyclophilin have been detected in aRNA derived from single cerebellar tissue sections. cDNA derived from a single cerebellar Purkinje cell also has been amplified and yields material that hybridizes to cognate whole RNA and mRNA but not to Escherichia coli RNA.
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              Genomic alterations in cultured human embryonic stem cells.

              Cultured human embryonic stem cell (hESC) lines are an invaluable resource because they provide a uniform and stable genetic system for functional analyses and therapeutic applications. Nevertheless, these dividing cells, like other cells, probably undergo spontaneous mutation at a rate of 10(-9) per nucleotide. Because each mutant has only a few progeny, the overall biological properties of the cell culture are not altered unless a mutation provides a survival or growth advantage. Clonal evolution that leads to emergence of a dominant mutant genotype may potentially affect cellular phenotype as well. We assessed the genomic fidelity of paired early- and late-passage hESC lines in the course of tissue culture. Relative to early-passage lines, eight of nine late-passage hESC lines had one or more genomic alterations commonly observed in human cancers, including aberrations in copy number (45%), mitochondrial DNA sequence (22%) and gene promoter methylation (90%), although the latter was essentially restricted to 2 of 14 promoters examined. The observation that hESC lines maintained in vitro develop genetic and epigenetic alterations implies that periodic monitoring of these lines will be required before they are used in in vivo applications and that some late-passage hESC lines may be unusable for therapeutic purposes.
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                Author and article information

                Journal
                BMC Dev Biol
                BMC Developmental Biology
                BioMed Central (London )
                1471-213X
                2006
                3 May 2006
                : 6
                : 20
                Affiliations
                [1 ]Laboratory of Neurosciences, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, USA
                [2 ]Buck Institute for Age Research, Novato, California 94945, USA
                [3 ]Bioinformatics Unit, Branch of Research Resources, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, USA
                [4 ]Burnham Institute for Medical Research, La Jolla, California 92037, USA
                [5 ]Laboratory of Molecular Neurobiology, Medical Biochemistry and Biophysics, Retzius Laboratory, Karolinska Institute, Stockholm 17177, Sweden
                [6 ]Illumina, Inc. San Diego, California 92121, USA
                [7 ]Department of Neuroscience, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21205, USA
                [8 ]Corporate Research Laboratories, Invitrogen Corporation, 1620 Faraday Avenue, Carlsbad, CA 92008, USA
                [9 ]Zentrum für Integrative Psychiatrie, Kiel Niemannsweg 147, 24105 Kiel, Germany
                Article
                1471-213X-6-20
                10.1186/1471-213X-6-20
                1523200
                16672070
                889012b8-dd81-4736-9375-d2f5238a7f27
                Copyright © 2006 Liu et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 December 2005
                : 3 May 2006
                Categories
                Research Article

                Developmental biology
                Developmental biology

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