BIO222
Molecular Systematics and Phylogenetics (E. Conti)
Vorlesungen:
In the last 20 years the number of systematic studies that use molecular data and explicit analytical approaches to reconstruct the tree of life has exploded. Therefore courses that cover both these recent developments have become essential in the training of new evolutionary biologists and systematists. This course will introduce the basic concepts and applications of macromolecular techniques and phylogenetic analysis to understand evolution primarily, but not only, of plants. Questions addressed will include: What kind of evolutionary and systematic questions are best addressed by using molecular data and phylogenetic analysis? What kind of experimental and analytical techniques are used by evolutionary biologists and stystematists? How are they used? What kind of data are obtained? How do results of these molecular studies compare with those from classical studies? Specific topics to be covered include: gene duplications; chloroplast DNA- vs. mitochondrial DNA- vs. nuclear DNA-based data; new genes for phylogenetic reconstruction; homology assessment; sequence alignment; methods of phylogenetic analysis, including: optimality criteria, tree-building algorithms, statistical robustness of phylogenetic trees, choosing among alternative trees, molecules and morphology in phylogeny reconstruction, character evolution. A detailed set of primary literature for each topic will be organized and made available in the library of the Botanischer Garten.
Praktikum:
The laboratory portion of the course will give students the opportunity to gain hands-on experience with selected molecular techniques and computer software used in contemporary systematics. Experimental approaches to be covered include: DNA data retrieval, primer design, DNA sequencing and cloning, analysis of DNA sequences, multiple alignments, tree reconstruction, character mapping. Data banks and software demonstrations will include: GenBank, TreeBase, Sequencher, Clustal, PAUP, Phylip, PAML, MacClade. Students will choose one or more data sets from published studies, re-analyze the data, and compare the results with those reported in the corresponding articles. Students will also have the option of developing a small research project in my lab.