One of the outstanding challenges in comparative genomics is to interpret the
evolutionary importance of regulatory variation between species. Rigorous
molecular evolution-based methods to infer evidence for natural selection from
expression data are at a premium in the field, and to date, phylogenetic
approaches have not been well-suited to address the question in the small sets
of taxa profiled in standard surveys of gene expression. We have developed a
strategy to infer evolutionary histories from expression profiles by analyzing
suites of genes of common function. In a manner conceptually similar to
molecular evolution models in which the evolutionary rates of DNA sequence at
multiple loci follow a gamma distribution, we modeled expression of the genes
of an \emph{a priori}-defined pathway with rates drawn from an inverse gamma
distribution. We then developed a fitting strategy to infer the parameters of
this distribution from expression measurements, and to identify gene groups
whose expression patterns were consistent with evolutionary constraint or rapid
evolution in particular species. Simulations confirmed the power and accuracy
of our inference method. As an experimental testbed for our approach, we
generated and analyzed transcriptional profiles of four \emph{Saccharomyces}
yeasts. The results revealed pathways with signatures of constrained and
accelerated regulatory evolution in individual yeasts and across the phylogeny,
highlighting the prevalence of pathway-level expression change during the
divergence of yeast species. We anticipate that our pathway-based phylogenetic
approach will be of broad utility in the search to understand the evolutionary
relevance of regulatory change.Comment: 30 pages, 12 figures, 2 tables, contact authors for supplementary
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