Thanks to the microarray technology, our understanding of transcriptome evolution at the genome-level has been considerably advanced in the past decade. Yet further investigation was challenged by several technical limitations of this technology. Recent innovation of next-generation sequencing (NGS), particularly the invent of RNA-seq technology, has shed insightful lights to resolving this problem. Though a number of statistical and computational methods have been developed to analyze RNA-seq data, the analytical framework specifically designed for evolutionary genomics remains an open question.
Researchers from Fudan University, China have developed a new method for estimating the genome expression distance from the RNA-seq data, which has explicit interpretations under the model of gene expression evolution. Moreover, this distance measure takes the data over-dispersion, gene length variation and sequencing depth variation into account so that it can be applied to multiple genomes from different species. Using mammalian RNA-seq data as example, they demonstrated that this expression distance is useful in phylogenomic analysis.
Availability – Two distribution R packages, compatible with Windows and Linux operating systems respectively, are available at http://www.xungulab.com
- Gu X, Zou Y, Huang W, Shen L, Arendsee Z, Su Z. (2013) Phylogenomic Distance Method for Analyzing Transcriptome Evolution based on RNA-seq Data. Genome Biol Evol [Epub ahead of print]. [article]