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Unit information: Phylogenetics Methods & Research in 2019/20

Please note: Due to alternative arrangements for teaching and assessment in place from 18 March 2020 to mitigate against the restrictions in place due to COVID-19, information shown for 2019/20 may not always be accurate.

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Phylogenetics Methods & Research
Unit code EASC30069
Credit points 20
Level of study H/6
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Professor. Pisani
Open unit status Not open
Pre-requisites

N/A

Co-requisites

N/A

School/department School of Earth Sciences
Faculty Faculty of Science

Description including Unit Aims

The unit aims to introduce students to:

  • Phylogenetics using parsimony as an easy to understand, exemplar, method.
  • Modern phylogenetic methods: (A) Maximum Likelihood; (B) Bayesian Analysis
  • Modern dating methods to derive evolutionary timescales integrating fossils and genomic data (Molecular clocks).
  • Supercomputing and the UNIX environment.
  • Research design and implementation.

In the first five weeks of the unit students will gain a general understanding of modern methods in macroevolutionary analysis through a series of lectures covering Phylogenetic reconstruction, Inference of divergence time and the Comparative method. Practicals in these weeks will include how to use supercomputers (using a UNIX/LINUX shell interface) and how to use an array of standard software for data analysis (e.g. PAUP MrBayes Phylobayes).

In week five students will meet with the Unit Director to agree a research topic.

From the sixth week students will undertake an independent research project using publicly available data from Morphobank or Genebank, grounded on the practical and theoretical knowledge they accumulated in lectures and practicals. Students will independently research the agreed topic, obtain relevant publicly available data, and complete a series of appropriate analyses to test specific evolutionary hypotheses, as previously agreed with the Unit Director.

At a second supervisory meeting (drop in session) in week 8 students will present a bulleted point document describing the project write-up plan. Completion of the project will culminate in a report of the project results in the style of a short scientific paper at the end of the unit (submission in week 10).

Intended Learning Outcomes

Students will:

  • be able to use a range of phylogenetic tree-finding methods - parsimony, maximum likelihood, and Bayesian analysis
  • be able to analyse morphological and molecular data to determine the evolutionary relationships of living and extinct organisms
  • be able to use appropriate software (e.g. Paup, MrBayes) to test the veracity of phylogenetic hypotheses
  • understand morphological character coding and how to use it to discover phylogenetic patterns in the tree of life
  • be able to use modern dating techniques combining fossil and genomic information.
  • be able to use molecular phylogenetics/phylogenomics methods
  • understand and be able to implement combined (total evidence) analyses of molecular and morphological data – including fossils
  • have transferable skills that are of use outside palaeontology (A) working with supercomputers in a Unix environment, (B) use statistical software, (C) develop a research plan and execute it.

Teaching Information

5 weeks of lectures and practicals, plus an independent research period.

Assessment Information

Coursework (100%)

Coursework comprises a written report of the 5 week project undertaken (2500 words; one figure with panels allowed)

Reading and References

Essential:

  • Nascimento et al. (2017) A biologist’s guide to Bayesian phylogenetic analysis. Nat Ecol Evol. 1(10):1446-1454
  • Dos Reis et al. (2016) Bayesian molecular clock dating of species divergences in the genomics era. Nat Rev Genet 17(2): 71-80.

Independent reading of the broad literature to select a topic for the project is essential.

Further Reading:

  • Felsenstein J (2004) Inferring phylogenies. Sinauer Associates, Inc. Sunderland, Massachusetts

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