In search of lost introns.
Many fundamental questions concerning the emergence and subsequent evolution of eukaryotic exon-intron organization are still unsettled. Genome-scale comparative studies, which can shed light on crucial aspects of eukaryotic evolution, require adequate computational tools. We describe novel computational methods for studying spliceosomal intron evolution. Our goal is to give a reliable characterization of the dynamics of intron evolution. Our algorithmic innovations address the identification of orthologous introns, and the likelihood-based analysis of intron data. We discuss a compression method for the evaluation of the likelihood function, which is noteworthy for phylogenetic likelihood problems in general. We prove that after O(n l) preprocessing time, subsequent evaluations take O(n l/log l) time almost surely in the Yule-Harding random model of n-taxon phylogenies, where l is the input sequence length. We illustrate the practicality of our methods by compiling and analyzing a data set involving 18 eukaryotes, which is more than in any other study to date. The study yields the surprising result that ancestral eukaryotes were fairly intron-rich. For example, the bilaterian ancestor is estimated to have had more than 90% as many introns as vertebrates do now.


BACKGROUND
The Java implementations of the algorithms are publicly available from the corresponding author's site http://www.iro.umontreal.ca/~csuros/introns/. Data are available on request.
Csurös
Miklós
M
Department of Computer Science and Operations Research, Université de Montréal, Québec, Canada. csuros@iro.umontreal.ca
Holey
J Andrew
JA
Rogozin
Igor B
IB
D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D004252:DNA Mutational Analysis / Q000379:methods*; D019143:Evolution, Molecular; D014644:Genetic Variation / Q000235:genetics*; D007438:Introns / Q000235:genetics*; D008969:Molecular Sequence Data; D017422:Sequence Analysis, DNA / Q000379:methods*