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Review
. 2012 Apr;23(2):222-9.
doi: 10.1016/j.semcdb.2011.12.004. Epub 2011 Dec 24.

The evolution of gene expression and the transcriptome-phenotype relationship

Affiliations
Review

The evolution of gene expression and the transcriptome-phenotype relationship

Peter W Harrison et al. Semin Cell Dev Biol. 2012 Apr.

Abstract

Changes in gene expression underlie the adaptive evolution in many complex phenotypes, and the recent increase in the availability of multi-species comparative transcriptome data has made it possible to scan whole transcriptomes for loci that have experienced adaptive changes in expression. However, despite the increase in data availability, current models of gene expression evolution often do not account for the complexities and inherent noise associated with transcriptome data. Additionally, in contrast to current models of gene sequence evolution, models of transcriptome evolution often lack the sophistication to effectively determine whether transcriptional differences between species or within a clade are the result of neutral or adaptive processes. In this review, we discuss the tools, methods and models that define our current understanding of the relationship between gene expression and complex phenotype evolution. Our goal is to summarize what we know about the evolution of global gene expression patterns underlying complex traits, as well to identify some of the questions that remain to be answered.

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Figures

Fig. 1
Fig. 1
Mode of gene expression evolution inferred from levels of polymorphism and divergence, or within and between population variance respectively. This graph can be divided into regions where positive or purifying selection pressures prevail (quadrants I and II), or where neutral evolutionary processes drive changes in expression (quadrant III).
Fig. 2
Fig. 2
Affymetrix microarray and RNA-Seq expression estimates compared for identical RNA pools from Gallus gallus testes and ovaries. Each pool comprised four same-sex samples. Microarrays were run with standard hybridization, quality control, pre-processing and normalization procedures; RNA-Seq estimates are based on Illumina GAII 50 bp reads with approximately 17 million reads per sample. Male (A) and female (B) gonad expression data were combined for each technology in a comparison of male to female fold change (C).

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