Intron position in RNA polymerase genes and their relationship to eukaryotic phylogenies

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Matthew Robinson (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Over the past two decades, there has been an increasing amount of research devoted to the study of intron evolution and its relationship to eukaryotic phylogeny. Previous studies have shown that a large percentage of intron positions are conserved evolutionarily among three major multicellular eukaryotic groups: animals, plants, and fungi. These studies also have inferred lineage-specific and sometimes massive intron losses, or parallel insertions, based largely on their distributions on molecular sequence-based trees. Interestingly, these studies infer varying numbers of ancestral introns, depending on the algorithms used and phylogenetic associations assumed. The research presented here examines intron evolution in RNA polymerase genes as data for inferring phylogenetic relationships among various eukaryotic lineages. A phylogenetic tree is inferred based solely on intron position data and these relationships are used to evaluate statistically significant deviations from sequence-based phylogenies. Intron positions were mapped carefully to the various eukaryotic largest and second-largest subunits of RNA polymerases I, II, and III. These sequences were aligned using three different alignment programs (Probcons, T-coffee, and Muscle) and compared using the Altavist web server. Once the proper alignment was established it was analyzed using ProtTest, which tested the alignments against various substitution matrices for the most accurate alignment for use in the phylogenetic analysis. Sequence-based trees were constructed using PHYML as well as RAxML to reduce bias in phylogenetic reconstruction. The intron-based tree was constructed using PAUP v4.0 using intron-positions as binary characteristics. Previous work in our lab has shown that an intron-based tree for RNA polymerase II largest subunit is topographically different from the sequence-based tree, but statistical comparisons were not performed. Such statistical comparisons are rarely made, but are needed to more clearly understand where intron- and sequence-based trees are in clear conflict. This research showed that neither the sequence- or intron-based tress could better explain the data, statistically confirming that both methods produce two different tree topologies. If intron evolution across eukaryotic diversity is to be fully understood, this type of comparison is required to determine where inferences of massive intron gain and loss are in significant conflict with sequence-based phylogenies.  

Additional Information

Publication

Thesis

Date: 2010

Keywords

Bioinformatics, Biology

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