Statistical framework for phylogenomic analysis of gene family expression profiles.
Microarray technology has produced massive expression data that are invaluable for investigating the genome-wide evolutionary pattern of gene expression. To this end, phylogenetic expression analysis is highly desirable. On the basis of the Brownian process, we developed a statistical framework (called the E(0) model), assuming the independent expression of evolution between lineages. Several evolutionary mechanisms are integrated to characterize the pattern of expression diversity after gene duplications, including gradual drift and dramatic shift (punctuated equilibrium). When the phylogeny of a gene family is given, we show that the likelihood function follows a multivariate normal distribution; the variance-covariance matrix is determined by the phylogenetic topology and evolutionary parameters. Maximum-likelihood methods for multiple microarray experiments are developed, and likelihood-ratio tests are designed for testing the evolutionary pattern of gene expression. To reconstruct the evolutionary trace of expression diversity after gene (or genome) duplications, we developed a Bayesian-based method and use the posterior mean as predictors. Potential applications in evolutionary genomics are discussed.
Gu
Xun
X
Department of Genetics, Development and Cell Biology (GDCB), Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, Iowa 50011, USA. xgu@iastate.edu
D000465:Algorithms; D001499:Bayes Theorem; D019143:Evolution, Molecular; D005656:Fungal Proteins / Q000737:chemistry; D015870:Gene Expression; D005786:Gene Expression Regulation; D005800:Genes, Fungal; D014644:Genetic Variation; D016678:Genome; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis; D010802:Phylogeny
D005656:Fungal Proteins