Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration.
Microarray-based studies of global gene expression (GE) have resulted in a large amount of data that can be mined for further insights into disease and physiology. Meta-analysis of these data is hampered by technical limitations due to many different platforms, gene annotations and probes used in di...
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Public Library of Science (PLoS)
2008-08-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0002965&type=printable |
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| author | Davendra Sohal Andrew Yeatts Kenny Ye Andrea Pellagatti Li Zhou Perry Pahanish Yongkai Mo Tushar Bhagat John Mariadason Jacqueline Boultwood Ari Melnick John Greally Amit Verma |
| author_facet | Davendra Sohal Andrew Yeatts Kenny Ye Andrea Pellagatti Li Zhou Perry Pahanish Yongkai Mo Tushar Bhagat John Mariadason Jacqueline Boultwood Ari Melnick John Greally Amit Verma |
| author_sort | Davendra Sohal |
| collection | DOAJ |
| description | Microarray-based studies of global gene expression (GE) have resulted in a large amount of data that can be mined for further insights into disease and physiology. Meta-analysis of these data is hampered by technical limitations due to many different platforms, gene annotations and probes used in different studies. We tested the feasibility of conducting a meta-analysis of GE studies to determine a transcriptional signature of hematopoietic progenitor and stem cells. Data from studies that used normal bone marrow-derived hematopoietic progenitors was integrated using both RefSeq and UniGene identifiers. We observed that in spite of variability introduced by experimental conditions and different microarray platforms, our meta-analytical approach can distinguish biologically distinct normal tissues by clustering them based on their cell of origin. When studied in terms of disease states, GE studies of leukemias and myelodysplasia progenitors tend to cluster with normal progenitors and remain distinct from other normal tissues, further validating the discriminatory power of this meta-analysis. Furthermore, analysis of 57 normal hematopoietic stem and progenitor cell GE samples was used to determine a gene expression signature characteristic of these cells. Genes that were most uniformly expressed in progenitors and at the same time differentially expressed when compared to other normal tissues were found to be involved in important biological processes such as cell cycle regulation and hematopoiesis. Validation studies using a different microarray platform demonstrated the enrichment of several genes such as SMARCE, Septin 6 and others not previously implicated in hematopoiesis. Most interestingly, alpha-integrin, the only common stemness gene discovered in a recent comparative murine analysis (Science 302(5644):393) was also enriched in our dataset, demonstrating the usefulness of this analytical approach. |
| format | Article |
| id | doaj-art-c5be5fcfd2fa4a61954a741ff8fc649c |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2008-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-c5be5fcfd2fa4a61954a741ff8fc649c2025-08-20T03:22:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032008-08-0138e296510.1371/journal.pone.0002965Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration.Davendra SohalAndrew YeattsKenny YeAndrea PellagattiLi ZhouPerry PahanishYongkai MoTushar BhagatJohn MariadasonJacqueline BoultwoodAri MelnickJohn GreallyAmit VermaMicroarray-based studies of global gene expression (GE) have resulted in a large amount of data that can be mined for further insights into disease and physiology. Meta-analysis of these data is hampered by technical limitations due to many different platforms, gene annotations and probes used in different studies. We tested the feasibility of conducting a meta-analysis of GE studies to determine a transcriptional signature of hematopoietic progenitor and stem cells. Data from studies that used normal bone marrow-derived hematopoietic progenitors was integrated using both RefSeq and UniGene identifiers. We observed that in spite of variability introduced by experimental conditions and different microarray platforms, our meta-analytical approach can distinguish biologically distinct normal tissues by clustering them based on their cell of origin. When studied in terms of disease states, GE studies of leukemias and myelodysplasia progenitors tend to cluster with normal progenitors and remain distinct from other normal tissues, further validating the discriminatory power of this meta-analysis. Furthermore, analysis of 57 normal hematopoietic stem and progenitor cell GE samples was used to determine a gene expression signature characteristic of these cells. Genes that were most uniformly expressed in progenitors and at the same time differentially expressed when compared to other normal tissues were found to be involved in important biological processes such as cell cycle regulation and hematopoiesis. Validation studies using a different microarray platform demonstrated the enrichment of several genes such as SMARCE, Septin 6 and others not previously implicated in hematopoiesis. Most interestingly, alpha-integrin, the only common stemness gene discovered in a recent comparative murine analysis (Science 302(5644):393) was also enriched in our dataset, demonstrating the usefulness of this analytical approach.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0002965&type=printable |
| spellingShingle | Davendra Sohal Andrew Yeatts Kenny Ye Andrea Pellagatti Li Zhou Perry Pahanish Yongkai Mo Tushar Bhagat John Mariadason Jacqueline Boultwood Ari Melnick John Greally Amit Verma Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. PLoS ONE |
| title | Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. |
| title_full | Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. |
| title_fullStr | Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. |
| title_full_unstemmed | Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. |
| title_short | Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. |
| title_sort | meta analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter platform data integration |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0002965&type=printable |
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