Estimating evolution of temporal sequence changes: a practical approach to inferring ancestral developmental sequences and sequence heterochrony.

Developmental biology often yields data in a temporal context. Temporal data in phylogenetic systematics has important uses in the field of evolutionary developmental biology and, in general, comparative biology. The evolution of temporal sequences, specifically developmental sequences, has proven difficult to examine due to the highly variable temporal progression of development. Issues concerning the analysis of temporal sequences and problems with current methods of analysis are discussed. We present here an algorithm to infer ancestral temporal sequences, quantify sequence heterochronies, and estimate pseudoreplicate consensus support for sequence changes using Parsimov-based genetic inference [PGi]. Real temporal developmental sequence data sets are used to compare PGi with currently used approaches, and PGi is shown to be the most efficient, accurate, and practical method to examine biological data and infer ancestral states on a phylogeny. The method is also expandable to address further issues in developmental evolution, namely modularity.