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      Transcriptomic and phenotypic analysis of murine embryonic stem cell derived BMP2 + lineage cells: an insight into mesodermal patterning

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          Abstract

          Transcriptome analysis of BMP2 + cells in comparison to the undifferentiated BMP2 ES cells and the control population from 7-day old embryoid bodies led to the identification of 479 specifically upregulated and 193 downregulated transcripts.

          Abstract

          Background

          Bone morphogenetic protein (BMP)2 is a late mesodermal marker expressed during vertebrate development and plays a crucial role in early embryonic development. The nature of the BMP2-expressing cells during the early stages of embryonic development, their transcriptome and cell phenotypes developed from these cells have not yet been characterized.

          Results

          We generated a transgenic BMP2 embryonic stem (ES) cell lineage expressing both puromycin acetyltransferase and enhanced green fluorescent protein (EGFP) driven by the BMP2 promoter. Puromycin resistant and EGFP positive BMP2 + cells with a purity of over 93% were isolated. Complete transcriptome analysis of BMP2 + cells in comparison to the undifferentiated ES cells and the control population from seven-day-old embryoid bodies (EBs; intersection of genes differentially expressed between undifferentiated ES cells and BMP2 + EBs as well as differentially expressed between seven-day-old control EBs and BMP2 + EBs by t-test, p < 0.01, fold change >2) by microarray analysis led to identification of 479 specifically upregulated and 193 downregulated transcripts. Transcription factors, apoptosis promoting factors and other signaling molecules involved in early embryonic development are mainly upregulated in BMP2 + cells. Long-term differentiation of the BMP2 + cells resulted in neural crest stem cells (NCSCs), smooth muscle cells, epithelial-like cells, neuronal-like cells, osteoblasts and monocytes. Interestingly, development of cardiomyocytes from the BMP2 + cells requires secondary EB formation.

          Conclusion

          This is the first study to identify the complete transcriptome of BMP2 + cells and cell phenotypes from a mesodermal origin, thus offering an insight into the role of BMP2 + cells during embryonic developmental processes in vivo.

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          Most cited references71

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Cluster analysis and display of genome-wide expression patterns.

            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. 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 interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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              • Record: found
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              Genesis: cluster analysis of microarray data.

              A versatile, platform independent and easy to use Java suite for large-scale gene expression analysis was developed. Genesis integrates various tools for microarray data analysis such as filters, normalization and visualization tools, distance measures as well as common clustering algorithms including hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines. The results of the clustering are transparent across all implemented methods and enable the analysis of the outcome of different algorithms and parameters. Additionally, mapping of gene expression data onto chromosomal sequences was implemented to enhance promoter analysis and investigation of transcriptional control mechanisms.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2007
                4 September 2007
                : 8
                : 9
                : R184
                Affiliations
                [1 ]Institute of Neurophysiology, University of Cologne, Robert-Koch Str. 39, 50931 Cologne, Germany
                [2 ]Institute of Pathology, University of Cologne, Joseph-Stelzmann-Str. 9, 50931 Cologne, Germany
                [3 ]Max-Delbrueck-Center for Molecular Medicine - MDC, Robert-Rössle Str. 10, 13092 Berlin, Germany
                [4 ]Department of Pathology, The University of Texas Health Science Center at San Antonio, TX 78229, USA
                Article
                gb-2007-8-9-r184
                10.1186/gb-2007-8-9-r184
                2375022
                17784959
                5bfe6b03-deef-4ba0-a82c-4bde42e6a9f8
                Copyright © 2007 Doss 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
                : 11 December 2006
                : 30 May 2007
                : 4 September 2007
                Categories
                Research

                Genetics
                Genetics

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