Introducing CAFE: Computational Analysis of (gene) Family Evolution
Carrie L. Ganote, Fábio Mace do Mendes, Robert Henschel, Matthew W. Hahn, Ben Fulton · IUScholarWorks (Indiana University) · 2018
Comparison of whole genomes has revealed large and frequent changes in the size of gene families, the result of gene duplication and loss. Comparative genomic analyses allow us to identify large-scale patterns of change and to make inferences regarding the role of natural selection in gene gain and loss. But genome assemblies constructed from these data are often fragmented and incomplete, resulting in annotation errors, especially in the number of genes present in a genome. To make these analyses possible, we have developed a stochastic birth-and-death model for gene family evolution—applied in the software package CAFE—which is robust in the face of less-than-ideal assemblies. Application of this method to data from multiple whole genomes of many groups has revealed remarkable patterns of gene gain and loss, including gene movement among chromosomes (especially sex chromosomes), polymorphic copy-number variants under local selection, and provides novel methods for carrying out genome assembly, to more accurately estimate gene number. We will describe the application of CAFE to genome sets, and illustrate the conclusions possible from CAFE analysis. The demonstration will use a publicly available VM running CAFE, posted on the Jetstream cloud.