"PRINCIPLES OF PHYLOGENETICS: ECOLOGY AND EVOLUTION" Integrative Biology 200B Spring 2011 University of California, Berkeley Nick Matzke, revised from B.D. Mishler March 3, 2011. Comparative genomics; Evolution and development This is the era of whole-genome sequencing; molecular data are becoming available at a rate unanticipated even a few years ago. Sequencing projects in a number of countries have produced a growing number of fully sequenced genomes, providing computational biologists with tremendous opportunities. However, comparative genomics has so far largely been restricted to pair-wise comparisons of genomes. The importance of taking a phylogenetic approach to systematically relating larger sets of genomes has only recently been realized. A recent synthesis of phylogenetic systematics and molecular biology/genomics – two fields once estranged – is beginning to form a new field that could be called "phylogenomics" (Eisen 1998). Something can be learned about the function of genes by examining them in one organism. However, a much richer array of tools is available using a phylogenetic approach. Close sister-group comparisons between lineages differing in a critical phenotype (e.g., desiccation or freeze tolerance) can allow a quick narrowing of the search for genetic causes. Dissecting a complicated, evolutionarily advanced genotype/phenotype complex (e.g., development of the angiosperm flower), by tracing the components back through simpler ancestral reconstructions, can lead to quicker understanding. Hence, phylogenomics allows one to go beyond the use of pairwise sequence similarities, and use phylogenic comparative methods as discussed in this class to confirm and/or to establish gene function and interactions. Most importantly for the systematist, the new comparative genomic data should also greatly increase the accuracy of reconstructions of the Tree of Life. Even though nucleotide sequence comparisons have become the workhorse of phylogenetic analysis at all levels, there are clearly phylogenetic problems for which nucleotide sequence data are poorly suited, because of their simple nature (having only four character states) and tendency to evolve in a regular, more-or-less clocklike fashion. In particular, "deep" branching questions (with relatively short internodes of interest mixed with long terminal branches) are notoriously difficult to resolve with DNA sequence data. It is fortunate therefore, that fundamentally new kinds of structural genomic characters such as inversions, translocations, losses, duplications, and insertion/deletion of introns will be increasingly available in the future. These characters need to be evaluated using much the same Deep change in functionRecent Change in functionIncreasing complexitySister-group comparison Ancestor-descendant comparisons A phylogenetically distant comparison = large background differences A phylogenetically close comparison = low background differences Using reconstructed ancestral statesprinciples of character analysis that were originally developed for morphological characters. They must be looked at carefully to establish likely homology (e.g., examining the ends of breakpoints across genomes to see whether a single rearrangement event is likely to have occurred), independence, and discreteness of character states. Thus close collaboration between systematists and molecular biologists will be required to code these genomic characters properly, and to assemble them into matrices with other data types. Next two figures from: Jonathan A. Eisen and Claire M. Fraser, Phylogenomics: Intersection of Evolution and Genomics , Science, Vol 300, Issue 5626, 1706-1707 , 13 June 2003 Outline of a phylogenomic methodology (next page). In this method, information about the evolutionary relationships among genes is used to predict the functions of uncharacterized genes (see text for details). Two hypothetical scenarios are presented and the path of trying to infer the function of two uncharacterized genes in each case is traced. (A) A gene family has undergone a gene duplication that was accompanied by functional divergence. (B) Gene function has changed in one lineage. The true tree (which is assumed to be unknown) is shown at the bottom. The genes are referred to by numbers (whichrepresent the species from which these genes come) and letters (which in A represent different genes within a species). The thin branches in the evolutionary trees correspond to the gene phylogeny and the thick gray branches in A (bottom) correspond to the phylogeny of the species in which the duplicate genes evolve in parallel (as paralogs). Different colors (and symbols) represent different gene functions; gray (with hatching) represents either unknown or unpredictable functions.Example below taken from: JA Eisen "A phylogenomic study of the MutS family of proteins" Nucleic Acids Research, Vol 26, Issue 18 4291-4300. Phylogenomic analysis of the MutS family of proteins. (A) Unrooted neighbor-joining tree of the proteins in the MutS family. (B) Proposed subfamilies of orthologs are highlighted. (C) Known functions of genes are overlaid onto the tree. For simplicity, only two colors are used, red for mismatch repair and blue for meiotic-crossing over and chromosome segregation. (D) Prediction of functions of uncharacterized proteins based on position in the tree.Gene duplication and gene loss in the history of the bacterial MutS homologs. (A) Neighbor-joining phylogenetic tree of the Mu tS1 and Mu tS2 subfamilies (using only those proteins from species with both). The identical topology of the tree in the two subfamilies suggests the occurrence of a duplication prior to the divergence of these bacteria. (B) Gene loss within the bacteria. Gene loss was determined by overlaying the presence and absence of MutS1 and MutS2 orthologs onto the tree of the species for which complete genomes are available (since only with a complete genome sequence can one be relatively certain that a gene is absent from a species). The thick gray lines represent the evolutionary history of the species based on a combination of the MutS and rRNA trees for these species. The thin colored lines represent the evolutionary history of the two MutS subfamilies (Mu tS1 in red and Mu tS2 in blue). Branch lengths do not correspond to evolutionary distance. Gene loss is indicated by a dashed line and each loss is
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