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The flood of information on gene and protein sequences from the genome projects has revolutionised molecular and evolutionary biology and has led to the rapid development of the science called genomics. Reliable prediction of the function of a novel gene/protein requires complex computational analysis of genomic and protein sequence information which exploit the principles governing the evolution of protein structure and function. This book aims to provide an up-to-date summary of the principles of protein evolution and discusses both the methods available to analyse the evolutionary history of proteins as well as those for predicting their structure-function relationships. Protein Evolution is intended for senior undergraduates and graduate students taking courses in protein structure and evolution, as well as bioinformatics. it will also be a useful supplement for students taking wider courses in molecular evolution, as well as a valuable resource for professionals in the area of functional genomics.
of these processes. There is strong evidence that the rate of intron loss is affected by selective pressures that depend on the biology of the organism. For example, Jeffares et al. (2006) have shown that intron density correlates with the logarithm of generation time, i.e. organisms that reproduce rapidly tend to have fewer introns than organisms that have longer life cycles. This correlation is probably due to selection for smaller genomes and selection for genes that can produce proteins
that the actual variation in rates is significantly greater than expected under the Poisson clock, indicating that the variations in evolutionary rates are larger than expected by chance. There are several reasons why the molecular clock does not follow a simple Poisson process. First, there is strong evidence that the mutation rates (expressed in substitutions per unit time) may vary among different evolutionary lineages (see section 3.2). One major reason for this is that since inherited
9781405151665_4_004.qxd 10/08/2007 02:07PM Page 88 88 CHAPTER 4 protdist computes distance matrices from protein sequences (http://bioweb.pasteur.fr/seqanal/interfaces/protdist-simple.html). protpars is a protein sequence parsimony method (http://bioweb.pasteur.fr/seqanal/interfaces/protpars-simple.html) neighbor provides neighbour-joining and UPGMA methods (http://bioweb.pasteur.fr/seqanal/interfaces/neighbor-simple.html). fitch provides Fitch–Margoliash and least-squares distance methods
expressed in germline cells (Piechaczyk et al., 1984). Lateral gene transfer In lateral gene transfer genetic material from one species is transferred to another species. As will be discussed in Chapter 9, lateral gene transfer has played a major role in the evolution of Eubacteria and Archaea, but it also occurs in eukaryotes (Allers & Mevarech, 2005; Andersson, 2005; Ochman, Lawrence & Groisman, 2000). There are three major mechanisms for lateral gene transfer into bacteria (Chen, Christie &
proximity methods), tend to evolve in a correlated manner (phylogenetic profiling methods) and to be fused as a single sequence in some organisms (domain fusion methods). 7.6 Detecting distant homology of protein-coding genes 7.6.1 Detecting distant homology by consensus approaches Diversification of function of paralogous protein-coding genes can eliminate all sequence similarity in regions involved in the distinct functions of the paralogs; sequence similarity may be preserved only in short