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Published online before print March 27, 2008, 10.1101/gr.073254.107
Genome Res. 18:771-779, 2008
©2008 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/08 $5.00
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Methods

SNP-specific array-based allele-specific expression analysis

Hans T. Bjornsson1, Thomas J. Albert2, Christine M. Ladd-Acosta1, Roland D. Green2, Michael A. Rongione1, Christina M. Middle2, Rafael A. Irizarry3, Karl W. Broman3, and Andrew P. Feinberg1,4

1 Department of Medicine and Center for Epigenetics, Institute of Basic Biomedical Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA; 2 NimbleGen Systems Inc., Madison, Wisconsin 53711, USA; 3 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA

We have developed an optimized array-based approach for customizable allele-specific gene expression (ASE) analysis. The central features of the approach are the ability to select SNPs at will for detection, and the absence of need to PCR amplify the target. A surprisingly long probe length (39–49 nt) was needed for allelic discrimination. Reconstitution experiments demonstrate linearity of ASE over a broad range. Using this approach, we have discovered at least two novel imprinted genes, NLRP2, which encodes a member of the inflammasome, and OSBPL1A, which encodes a presumed oxysterol-binding protein, were both preferentially expressed from the maternal allele. In contrast, ERAP2, which encodes an aminopeptidase, did not show preferential parent-of-origin expression, but rather, cis-acting nonimprinted differential allelic control. The approach is scalable to the whole genome and can be used for discovery of functional epigenetic modifications in patient samples.


4 Corresponding author.

E-mail afeinberg{at}jhu.ed; fax (410) 614-9819.

[Supplemental material is available online at www.genome.org. Full allele-specific expression array data is available at www.biostat.wisc.edu/~kbroman/.]

Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.073254.107.


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