Multi-species microarrays reveal the effect of sequence divergence on gene expression profiles
Author(s) -
Yoav Gilad,
Scott A. Rifkin,
Paul Bertone,
Mark Gerstein,
Kevin P. White
Publication year - 2005
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.3335705
Subject(s) - biology , dna microarray , gene , gene expression , genetics , coding region , sequence (biology) , complementary dna , spurious relationship , gene expression profiling , divergence (linguistics) , evolutionary biology , expressed sequence tag , computational biology , natural selection , selection (genetic algorithm) , linguistics , philosophy , machine learning , artificial intelligence , computer science
Interspecies comparisons of gene expression levels will increase our understanding of the evolution of transcriptional mechanisms and help to identify targets of natural selection. This approach holds particular promise for apes, as many human-specific adaptations are thought to result from differences in gene expression rather than in coding sequence. To date, however, all studies directly comparing interspecies gene expression have been performed on single-species arrays, so that it has been impossible to distinguish differential hybridization due to sequence mismatches from underlying expression differences. To evaluate the severity of this potential problem, we constructed a new multiprimate cDNA array using probes from human, chimpanzee, orangutan, and rhesus. We find a large effect of sequence divergence on hybridization signal, even in the closest pair of species, human and chimpanzee. By comparing single-species array analyses with results from multispecies arrays, we examine how estimates of differential gene expression are affected by sequence divergence. Our results indicate that naive use of single-species arrays in direct interspecies comparisons can yield spurious results.
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