Dr. GAVIN J. P. NAYLOR

Florida State University
School of Computational Science/
Department of Biological Science


Associate Professor

Ph.D. University of Maryland, Zoology, 1989.


Interests
Re-tracing the evolution of particular groups of sharks by following the change in the shape of their teeth through the fossil record. This will involve sampling fossil teeth from progressively more recent geological strata, quantifying and plotting their shape changes over evolutionary time. This work is morphologically based and does not involve genetics. However, accurate dating of fossil lineages will provide a means of calibrating rates of molecular evolutionary change among extant forms.
Estimating the evolutionary inter-relationships among sharks based on DNA sequence variation. This will involve PCR amplification, cloning and sequencing of 2 mitochondrial genes (2.5kb) and one nuclear gene (3kb) for approximately 100 species of sharks.
Exploring the effects of protein structure and function on the distribution of DNA sequence variation. When evolutionary changes at the amino acid level are plotted on to known (3-d crystallographically determined) protein structures, striking spatial distribution patterns are seen. If patterns of variation are similar among different clades of organisms (primates, rodents, birds, for example) the implication is that the protein under scrutiny has similar evolutionary constraints and opportunities in the various different groups. If, on the other hand, patterns of variation differ among clades it is likely that shifts in protein function have occurred that have affected the evolutionary freedom to vary. I am currently investigating such patterns in globin genes in collaboration with Dr. Mark Gerstein at Yale University.
Devising improved phylogenetic inference models which accommodate the signal-distorting effects of protein structure. Any peptide that interacts with parts of itself (through folding) will have amino acid residues that covary. Current means of estimating phylogeny assume site independence and do not accommodate such covariation. As a results they frequently yield erroneous inferences. I am developing methods that circumvent/accommodate the skewing affects of such among-site covariation.
 
 Publications
See Publications page.