Unit information: Phylogenetic Methods in Palaeobiology in 2020/21

Unit name	Phylogenetic Methods in Palaeobiology
Unit code	EASCM0035
Credit points	10
Level of study	M/7
Teaching block(s)	Teaching Block 1A (weeks 1 - 6)
Unit director	Professor. Pisani
Open unit status	Not open
Pre-requisites	None
Co-requisites	None
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

In this 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 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).

Practicals 1 to 3 are formative: students complete a series of exercises to learn how to use a diversity of phylogenetic software. Feedback will be provided.

Practical 4 is a Graded Practical: students are given a problem to complete that will be marked. The mark for this work gives the overall unit mark.

Practical 5 is formative: students use this practical class to review the work undertaken in practicals 1 – 3 and continue to work on the assessed assignment set in practical 4. Students can request feedback on specific topics

Intended Learning Outcomes

Students will:

• have transferable skills that are of use outside palaeontology (A) working with supercomputers in a Unix environment (B) basics of computer scripting
• 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
• understand the Molecular clock and molecular phylogenetics/phylogenomics
• be able to use a range of phylogenetic tree-finding methods - parsimony, maximum likelihood, and Bayesian analysis
• understand and be able to implement combined (total evidence) analyses of molecular and morphological data – including fossils

Teaching Information

The unit will be taught through a combination of

• asynchronous online materials and, if subsequently possible, synchronous face-to-face lectures
• synchronous office hours
• asynchronous directed individual formative activities and exercises
• guided, structured reading
• practical work in the laboratory

Students who either begin or continue their studies in an online mode may be required to complete laboratory work, or alternative activities, in person, either during the academic year 2020/21 or subsequently, in order to meet the intended learning outcomes for the unit, prepare them for subsequent units or to satisfy accreditation requirements.

Assessment Information

Coursework (100%)

In Practical 4 students are assigned one assessed exercise. This consists of a paper to read and a dataset to analyse. During the practical students will complete phylogenetic analyses of the given dataset and compare their results with those of the published paper.

Students' results are written up as a short Research Paper (500 words minimum - 1200 words maximum & one figure, if necessary with panels) + References.

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.

Further Reading:

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