Skip Navigation


Bioinformatics Advance Access originally published online on March 23, 2007
Bioinformatics 2007 23(10):1235-1242; doi:10.1093/bioinformatics/btm111
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
23/10/1235    most recent
btm111v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (17)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Oshlack, A.
Right arrow Articles by Gilad, Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Oshlack, A.
Right arrow Articles by Gilad, Y.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Using DNA microarrays to study gene expression in closely related species

Alicia Oshlack 1,*, Adrien E. Chabot 2, Gordon K. Smyth 1 and Yoav Gilad 2,*

1Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia and 2Department of Human Genetics, University of Chicago, Chicago, IL 60605, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Comparisons of gene expression levels within and between species have become a central tool in the study of the genetic basis for phenotypic variation, as well as in the study of the evolution of gene regulation. DNA microarrays are a key technology that enables these studies. Currently, however, microarrays are only available for a small number of species. Thus, in order to study gene expression levels in species for which microarrays are not available, researchers face three sets of choices: (i) use a microarray designed for another species, but only compare gene expression levels within species, (ii) construct a new microarray for every species whose gene expression profiles will be compared or (iii) build a multi-species microarray with probes from each species of interest. Here, we use data collected using a multi-primate cDNA array to evaluate the reliability of each approach.

Results: We find that, for inter-species comparisons, estimates of expression differences based on multi-species microarrays are more accurate than those based on multiple species-specific arrays. We also demonstrate that within-species expression differences can be estimated using a microarray for a closely related species, without discernible loss of information.

Contact: A.O. (oshlack{at}wehi.edu.au) or Y.G. (gilad{at}uchicago.edu)

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Martin Bishop

Received on January 9, 2006; revised on February 25, 2007; accepted on March 14, 2007

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Integr. Comp. Biol.Home page
H. E. Machado, A. A. Pollen, H. A. Hofmann, and S. C.P. Renn
Interspecific profiling of gene expression informed by comparative genomic hybridization: A review and a novel approach in African cichlid fishes
Integr. Comp. Biol., December 1, 2009; 49(6): 644 - 659.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
L. Lin, S. Liu, H. Brockway, J. Seok, P. Jiang, W. H. Wong, and Y. Xing
Using high-density exon arrays to profile gene expression in closely related species
Nucleic Acids Res., July 1, 2009; 37(12): e90 - e90.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
Y. Lu, P. Huggins, and Z. Bar-Joseph
Cross species analysis of microarray expression data
Bioinformatics, June 15, 2009; 25(12): 1476 - 1483.
[Abstract] [Full Text] [PDF]

Home page
 EndocrinologyHome page
S. Priyanka, P. Jayaram, R. Sridaran, and R. Medhamurthy
Genome-Wide Gene Expression Analysis Reveals a Dynamic Interplay between Luteotropic and Luteolytic Factors in the Regulation of Corpus Luteum Function in the Bonnet Monkey (Macaca radiata)
Endocrinology, March 1, 2009; 150(3): 1473 - 1484.
[Abstract] [Full Text] [PDF]

Home page
 Proc. Natl. Acad. Sci. USAHome page
T. Bedford and D. L. Hartl
Optimization of gene expression by natural selection
PNAS, January 27, 2009; 106(4): 1133 - 1138.
[Abstract] [Full Text] [PDF]

Home page
 GeneticsHome page
R. Chaix, M. Somel, D. P. Kreil, P. Khaitovich, and G. A. Lunter
Evolution of Primate Gene Expression: Drift and Corrective Sweeps?
Genetics, November 1, 2008; 180(3): 1379 - 1389.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.