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Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data.
Mol Biol Evol. 2005 Jan; 22(1):40-50.MB

Abstract

Understanding the evolution of gene function is a primary challenge of modern evolutionary biology. Despite an expanding database from genomic and developmental studies, we are lacking quantitative methods for analyzing the evolution of some important measures of gene function, such as gene-expression patterns. Here, we introduce phylogenetic comparative methods to compare different models of gene-expression evolution in a maximum-likelihood framework. We find that expression of duplicated genes has evolved according to a nonphylogenetic model, where closely related genes are no more likely than more distantly related genes to share common expression patterns. These results are consistent with previous studies that found rapid evolution of gene expression during the history of yeast. The comparative methods presented here are general enough to test a wide range of evolutionary hypotheses using genomic-scale data from any organism.

Authors+Show Affiliations

Oakley TH
Ecology and Evolution, University of Chicago, USA. oakley@lifesci.ucsb.edu
Gu Z
No affiliation info available
Abouheif E
No affiliation info available
Patel NH
No affiliation info available
Li WH
No affiliation info available

MeSH

Evolution, MolecularFungal ProteinsGene DuplicationGene ExpressionGenome, FungalGenomicsLikelihood FunctionsPhylogenySaccharomyces cerevisiae

Pub Type(s)

Comparative Study
Journal Article
Research Support, U.S. Gov't, P.H.S.

Language

eng

PubMed ID

15356281

Citation

Oakley, Todd H., et al. "Comparative Methods for the Analysis of Gene-expression Evolution: an Example Using Yeast Functional Genomic Data." Molecular Biology and Evolution, vol. 22, no. 1, 2005, pp. 40-50.
Oakley TH, Gu Z, Abouheif E, et al. Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data. Mol Biol Evol. 2005;22(1):40-50.
Oakley, T. H., Gu, Z., Abouheif, E., Patel, N. H., & Li, W. H. (2005). Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data. Molecular Biology and Evolution, 22(1), 40-50.
Oakley TH, et al. Comparative Methods for the Analysis of Gene-expression Evolution: an Example Using Yeast Functional Genomic Data. Mol Biol Evol. 2005;22(1):40-50. PubMed PMID: 15356281.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data. AU - Oakley,Todd H, AU - Gu,Zhenglong, AU - Abouheif,Ehab, AU - Patel,Nipam H, AU - Li,Wen-Hsiung, Y1 - 2004/09/08/ PY - 2004/9/10/pubmed PY - 2005/5/20/medline PY - 2004/9/10/entrez SP - 40 EP - 50 JF - Molecular biology and evolution JO - Mol Biol Evol VL - 22 IS - 1 N2 - Understanding the evolution of gene function is a primary challenge of modern evolutionary biology. Despite an expanding database from genomic and developmental studies, we are lacking quantitative methods for analyzing the evolution of some important measures of gene function, such as gene-expression patterns. Here, we introduce phylogenetic comparative methods to compare different models of gene-expression evolution in a maximum-likelihood framework. We find that expression of duplicated genes has evolved according to a nonphylogenetic model, where closely related genes are no more likely than more distantly related genes to share common expression patterns. These results are consistent with previous studies that found rapid evolution of gene expression during the history of yeast. The comparative methods presented here are general enough to test a wide range of evolutionary hypotheses using genomic-scale data from any organism. SN - 0737-4038 UR - https://www.unboundmedicine.com/medline/citation/15356281/Comparative_methods_for_the_analysis_of_gene_expression_evolution:_an_example_using_yeast_functional_genomic_data_ DB - PRIME DP - Unbound Medicine ER -