Sektion Biologie

biol-243 Inference of Positive Selection

Modulnummer biol243
Modulname Inference of Positive Selection
Studiengang und –abschnitt Master of Science/Education Biologie
Wahlmodul zu biol201, biol405, biol408
Fachspezifische Vertiefung „Biodiversität und Evolution“
Häufigkeit des Angebots einmal im Studienjahr,  Sommersemester
Modulverantwortliche Prof. Dr. Eva Stukenbrock
Studienberatung zum Modul Prof. Dr. Eva Stukenbrock
Lehrveranstaltungen und Dozenten Seminar: Prof. Dr. Eva Stukenbrock, Julien Y. Dutheil with Post doc
Übung: Prof. Dr. Eva Stukenbrock, Julien Y. Dutheil with Post doc
Vorkenntnisse Bachelor of Science
Sprache Deutsch/Englisch
Plätze 12
Lehrformen (Präsenzstunden (P) / Seminar 2 SWS; PräsZeit: 21 h, Vor-Nachber:10,5 h
Übung 6 SWS; PräsZeit: 63 h, Vor-Nachber: 10,5 h
Art und Gewichtung der  
Prüfungsleistungen Vortrag (50%); Schriftiche Ausarbeitung (50%)
Ausweis Bei Anmeldung im Prüfungsamt
Europ. Credit Points des Moduls 5
Ziele des Moduls

Positive selection occurs when a new or previously rare mutation confers a fitness advantage to individuals carrying it. Positive selection is essential in the adaptation of organisms to new ecological niches, environmental changes or during the divergence of new species. Different methods allow us to detect signatures of positive selection in sequence data, but using different statistical approaches. In this course we will discuss concept of sequence evolution, and we will see and use different methods for detection of positive selection in nucleotide as well as amino acid sequence data.

Inhalte des Moduls

The course will introduce the population genetics theory of positive selection. Central questions addressed in this course are: What is positive selection, and what is the impact of positive selection on speciation and adaptation to new environments. How can positive selection be detected in DNA/protein sequences?

The course will introduce models of codon sequence evolution that can be used to infer positive selection. The students will read and discuss original key articles: Mc Donald and Kreitman (1991), Nei and Gojobori (1986), Yang and Nielsen (1998).

Methods presented will be used by the students with real data analysis. Standard software will be presented such as DNASP and PAML. Participants will learn how to prepare a data set of molecular sequences, with emphasis on the alignment improvement. We will also emphasize the underlying statistical concepts of the methods introduced.
Vermittelte Kompetenzen

The course enables students to understand the theory of positive selection and to learn methods and tools for analyses of DNA/protein sequences.

 Students use and learn state of the art software in the field by analyse real datasets (practical part).

Computational Molecular Evolution

Ziheng Yang, October 2006, Oxford University Press 

CHAPTER 8 Neutral and Adaptive Protein Evolution 

Kosiol, Carolin, and Maria Anisimova. "Selection on the protein-coding genome." Evolutionary Genomics. Humana Press, 2012. 113-140.