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Metagene projection for cross-platform, cross-species characterization of global transcriptional states.

ABSTRACT: The high dimensionality of global transcription profiles, the expression level of 20,000 genes in a much small number of samples, presents challenges that affect the sensitivity and general applicability of analysis results. In principle, it would be better to describe the data in terms of a small number of metagenes, positive linear combinations of genes, which could reduce noise while still capturing the invariant biological features of the data. Here, we describe how to accomplish such a reduction in dimension by a metagene projection methodology, which can greatly reduce the number of features used to characterize microarray data. We show, in applications to the analysis of leukemia and lung cancer data sets, how this approach can help assess and interpret similarities and differences between independent data sets, enable cross-platform and cross-species analysis, improve clustering and class prediction, and provide a computational means to detect and remove sample contamination.

SUBMITTER: Tamayo P

PROVIDER: S-EPMC1838404 | biostudies-literature | 2007 Apr

REPOSITORIES: biostudies-literature

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Metagene projection for cross-platform, cross-species characterization of global transcriptional states.

Tamayo Pablo P Scanfeld Daniel D Ebert Benjamin L BL Gillette Michael A MA Roberts Charles W M CW Mesirov Jill P JP

Proceedings of the National Academy of Sciences of the United States of America 20070327 14

The high dimensionality of global transcription profiles, the expression level of 20,000 genes in a much small number of samples, presents challenges that affect the sensitivity and general applicability of analysis results. In principle, it would be better to describe the data in terms of a small number of metagenes, positive linear combinations of genes, which could reduce noise while still capturing the invariant biological features of the data. Here, we describe how to accomplish such a redu ...[more]

PMID: 17389406

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Project description:There is mounting evidence to suggest that the epigenetic reprogramming capacity of the oocyte is superior to that of the current factor-based reprogramming approaches and that some factor-reprogrammed induced pluripotent stem cells (iPSCs) retain a degree of epigenetic memory that can influence differentiation capacity and may be linked to the observed expression of immunogenicity genes in iPSC derivatives. One hypothesis for this differential reprogramming capacity is the "chromatin loosening/enhanced reprogramming" concept, as previously described by John Gurdon and Ian Wilmut, as well as others, which postulates that the oocyte possesses factors that loosen the somatic cell chromatin structure, providing the epigenetic and transcriptional regulatory factors more ready access to repressed genes and thereby significantly increasing epigenetic reprogramming. However, to empirically test this hypothesis a list of candidate oocyte reprogramming factors (CORFs) must be ascertained that are significantly expressed in metaphase II oocytes. Previous studies have focused on intraspecies or cross-species transcriptional analysis of up to two different species of oocytes. In this study, we have identified eight CORFs (ARID2, ASF1A, ASF1B, DPPA3, ING3, MSL3, H1FOO, and KDM6B) based on unbiased global transcriptional analysis of oocytes from three different species (human, rhesus monkey, and mouse) that both demonstrate significant (p<0.05, FC>3) expression in oocytes of all three species and have well-established roles in loosening/opening up chromatin structure. We also identified an additional 15 CORFs that fit within our proposed "chromatin opening/fate transformative" (COFT) model. These CORFs may be able to augment Shinya Yamanaka's previously identified reprogramming factors (OCT4, SOX2, KLF4, and cMYC) and potentially facilitate the removal of epigenetic memory in iPSCs and/or reduce the expression of immunogenicity genes in iPSC derivatives, and may have applications in future personalized pluripotent stem cell based therapeutics.

Dataset Information

Metagene projection for cross-platform, cross-species characterization of global transcriptional states.

Publications

Metagene projection for cross-platform, cross-species characterization of global transcriptional states.

Similar Datasets

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