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Dr. Christopher J. Creevey, Bioinformatics and pharmacogenomics Laboratory, Department of biology, National University of Ireland Maynooth, Maynooth, Co. Kildare, Ireland.
Detection of Adaptive evolution in protein coding sequences.
Adaptive
evolution was originally defined by Charles Darwin when he made the observation
that island populations of finches has a diversity of mouth parts that
was unexplainable by natural evolutionary trends. The original population
of birds were not inhabiting the islands for a long period of time, but
yet they had developed a huge diversity of bill morphologies. The explanation
is that there was a selective pressure on the birds to adapt very quickly
to the large number of small niches on the island and so this facilitated
the rapid, adaptive evolution of these mouth parts (some for cracking
nuts, some for rooting under bark, some for digging in sand etc.)
The
argument proceeds as follows. Living organisms multiply and would increase
indefinitely were not their numbers limited by death. Organisms also vary,
and at least some of the variation affects their likelihood of surviving
and reproducing. Finally, organisms have the property of ÔheredityÕ: that
is, like begets like. Darwin then argued that organisms do in fact multiply
and vary, and that this variability is passed from generation to generation,
and consequently populations of organisms will evolve. Those organisms
with characteristics most favourable for survival and reproduction will
not only have more offspring, but will pass their characteristics onto
those offspring. The result will be a change in the characteristics present
in the population. Evolutionary change does not require that any individual
should change, although it does require that new variants arise in the
process of reproduction, because otherwise the essential variability of
the population would disappear. The theory of natural selection not only
predicts evolutionary change, it also says something about the kind of
change. In particular, it predicts that organisms will acquire characteristics
that make them better able to survive and reproduce in the environment
in which they live. That is, it predicts the adaptation of organisms to
their environments.
This project to date has been focussed on developing methods of detecting adaptive evolution. These methods are lineage specific and are implemented in a sofware program Crann. The results so far show that the methods are more sensitive than tradional pairwise distance based methods.
Supertree reconstruction from genomic data
One way to build larger more comprehensive phylogenies is to combine the vast amount of phylogenetic information already available. A supertree does this by combining all the taxa from a collection of fundamental (or source) trees into a single phylogeny. An ideal supertree that agrees completely with all its fundamental trees is called a strict supertree, and can only result when all its fundamental trees are compatible. Two fundamental trees are compatible if, when only their shared taxa are considered, their relationships to each other are the same in both trees. However an ideal strict supertree is rarely found because phylogeneies based on different genes are subject to different evolutionary processes and because of events like lateral gene transfer and duplication. In this case supertree construction must be able to glean the true phlyogentic signal from the noise caused by homoplasy.
With the availability of whole genomes, supertree methods have become very important in reconstructing whole genome phylogenies. New methods have been developed, each approaching the problem from a different perspective.
There are many methods available to reconstruct phylogenies from single genes, however there are very few methods of reconstructing a phylogeny for multiple genes with differing numbers of taxa. Good phylogenies are required for adaptive evolutionary analyses, but different genes from the same species tend to support different phylogenies. How then can a phylogeny be reconstructed that represents the evolutionary history of the majority of the genes in a dataset? One answer may be to reconstruct a phylogeny for each gene represented in the dataset (a set of fundamental trees). If a phylogeny representing the entire dataset (a supertree) is proposed, then each fundamental tree may be compared to the supertree and their similarity scored. The value obtained by summing the scores from each comparison to a fundamental tree will represent how similar the supertree is to the fundamental trees.
This is the approach taken in this project. Software has been written that implements novel algorithms developed in the laboratory and is available at http://bioinf.may.ie/software/clann/. email chris.creevey@may.ie for more details.
| 1 | Wilkinson M., Cotton J.A., Creevey C.J., Eulenstein O., Harris, S.R., Lapointe, F.J., Levasseur, C., Mcinerney, J.O., Pisani, D., And Thorley, J.L. (In Press) The Shape of Supertrees to Come: Tree Shape Related Properties of Fourteen Supertree Methods. Systematic Biology. |
| 2 | Fitzpatrick,
D. A, Creevey C. J. and McInerney, J. O. Evidence
of positive Darwinian selection in putative meningococcal vaccine
antigens (In Press, Journal of Molecular Evolution) |
| 3 | Creevey,
C.J.,
Philip G.K. and McInerney J.O. (2005) The Opisthokonta and the Ecdysozoa
may not be clades: Stronger support for the grouping of plant and
animal than for animal and fungi and stronger support for the coelomata
than Ecdysozoa. Molecular Biology and Evolution 22 (5): 1175-1184. link |
| 4 | Creevey C. J. and McInerney, J. O. (2004) Clann: Investigating phylogenetic information through supertree analyses. Bioinformatics 21 (3): 390-2. Full text |
| 5 | Creevey,
C.J.,
Fitzpatrick D.A., Philip, G.K., Kinsella, R.J., O’Connell, M.J.,
Pentony, M.M., Travers, S.A. and Wilkinson M. (2004). Does a tree-like
phylogeny only exist at the tips in the prokaryotes? Proceedings of the Royal Society London, B series: Biological Sciences 271 (1557): 2551-8.pdf |
| 6 | Creevey C. J. and McInerney, J. O. (2003). Crann: Dectecting positive selection in protein coding DNA sequences. Bioinformatics 19 (13) 1726. pdf |
| 7 | McInerney, J. O., Littlewood, T. J. and Creevey, C. J. (2003). Detecting Adaptive Molecular Evolution: Additional Tools for the Parasitologist. Advances in Parasitology; 54:359-79. pdf |
| 8 | Kinsella, R. J., Fitzpatrick, D. A., Creevey, C. J. and McInerney, J. O. (2003) Fatty acid biosynthesis in Mycobacterium tuberculosis: Lateral gene transfer, adaptive evolution and gene duplication. Proceedings of the National Academy of Science USA 100(18):10320-5 pdf |
| 9 | Creevey C. J. and McInerney, J. O. (2002). An algorithm for detecting directional and non-directional positive selection, neutrality and negative selection in protein coding DNA sequences. Gene, 300: 43-51. pdf |
Last updated: 18/04/2005.