Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration

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

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

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 sternness 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.

Original languageEnglish (US)
Article numbere2965
JournalPLoS One
Volume3
Issue number8
DOIs
StatePublished - Aug 13 2008

Fingerprint

Data integration
Microarrays
Hematopoietic Stem Cells
meta-analysis
Gene expression
Meta-Analysis
Gene Expression
gene expression
Genes
Hematopoiesis
hematopoiesis
Tissue
Septins
Integrin alpha Chains
Molecular Sequence Annotation
Biological Phenomena
genes
Validation Studies
Transcriptome
unigenes

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. / Sohal, Davendra; Yeatts, Andrew; Ye, Kenny; Pellagatti, Andrea; Zhou, Li; Pahanish, Perry; Mo, Yongkai; Bhagat, Tushar; Mariadason, John; Boultwood, Jacqueline; Melnick, Ari; Greally, John; Verma, Amit.

In: PLoS One, Vol. 3, No. 8, e2965, 13.08.2008.

Research output: Contribution to journalArticle

Sohal, Davendra ; Yeatts, Andrew ; Ye, Kenny ; Pellagatti, Andrea ; Zhou, Li ; Pahanish, Perry ; Mo, Yongkai ; Bhagat, Tushar ; Mariadason, John ; Boultwood, Jacqueline ; Melnick, Ari ; Greally, John ; Verma, Amit. / Meta-analysis of microarray studies reveals a novel hematopoietic progenitor cell signature and demonstrates feasibility of inter-platform data integration. In: PLoS One. 2008 ; Vol. 3, No. 8.
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