The current version of this document can be found at: https://github.com/Phylogenetics-Brown-BIOL1425/phylogeneticbiology

This repository contains the source code, datasets, and documentation for Casey Dunn's Phylogenetic Biology course (Biology 1425) at Brown University.

Phylogenetic Biology

Spring 2016

Brown University

Professor: Casey Dunn

Time: Spring 2016, Tuesday and Thursday, 1:00PM-2:50PM

Location: First floor conference room, Walter Hall (80 Waterman St.)

Contact: [email protected]. Please prefix the subject line of e-mails related to the class with “phylobio:”

Office Hours: Tuesday 10:30am-12:00pm, Walter Hall (80 Waterman St.) Room 301

Enrollment is capped at 16 students. To be considered for a spot, please fill out this form.

Phylogenetic Biology is the study of the evolutionary relationships between organisms, and the use of evolutionary relationships to understand other aspects of organism biology. This course will survey phylogenetic methods, providing a detailed picture of the statistical, mathematical, and computational tools for building phylogenies and using them to study evolution. We will also examine the application of these tools to particular problems in the literature and emerging areas of study.

Most weeks, there will be a lecture on Tuesday and a combined paper discussion and lab on Thursdays. Papers and lab exercises will be posted on this syllabus at least a week in advance.

Students are expected to have taken classes in:

• Statistics (eg Biol 0495)

• Evolutionary Biology (eg Biol 0480, 0410, 0430, 1430, 1485)

Exceptions will be made if students can demonstrate proficiency in these areas, or in closely related ares such as computer science and math.

• Final Project, 40% . Each student will conduct their own phylogenetic study, which could include development of a new method, reconstructing the phylogeny of a particular group of organisms, examining the evolution of one more more characters on a tree, or examination of the behavior of a particular method. The final project will be developed and submitted as a shared git repository forked from a standard template. The professor and other students will review the project as it is developed so that it can be iteratively improved, tested, and refined. At the end of the course, each student will make a 10 minute presentation summarizing their work.

• Analysis assignments, 25% . There will be several analysis assignments provided as git repositories. These will provide you with the opportunity to apply your new skills to example datasets.

• Class participation, 15% . Attendance and participation in class discussions will be taken into account.

• Discussion leader, 20%. Students will lead discussions of papers that describe particular methods and applications. They are expected to summarize the methods and results of the paper, tie the paper to other topics covered in class, and lead a discussion that examines its strengths, weaknesses, and implications. The prepared presentation should last about 20 minutes, and will be followed by discussion for about 20 minutes. Each student will present 2 papers, either solo or in collaboration with other students.

• Required:. Baum, D. and Smith, S. (2012). Tree Thinking. An Introduction to Phylogenetic Biology. Roberts Publishers. Required. This text covers many of the principles of tree thinking and phylogenetic methods.

• Suggested:. Haddock, S. H. D. and Dunn, C. W. (2010). Practical Computing for Biologists. Sinauer Associates. You will perform a variety of phylogenetic analyses, which will require running programs at the command line and editing text files. If you are not familiar with these skills already, this book will provide the necessary background.

• Primary literature. Scientific papers from the primary literature are a critical component of this course. These will be assigned over the course of the semester as they are selected by students and the professor.

The assignments and final project will require that you have access to a computer running Unix or Linux. If you have an Apple Mac or a computer with Linux installed, you are already set. If your computer runs Microsoft Windows you have a couple options. You can run your analyses in a computer lab with Apple Macs or Linux computers, use a raspberry pi (several will be available), or you can install Linux on your windows computer within a virtual machine.

We will also use Brown's high performance computing cluster Oscar for computationally intensive analyses.

Specific computational skills we will teach and use include:

• The command line (bash) and simple shell scripts
• Text manipulation (data, code, and prose)
• Introductory data analysis in R
• git, a version control tool and so much more. In combination with github, we will use git to store and share files, track changes to files, provide feedback to each other, back up files, move files, and disseminate our work.

• Avoid spaces in file names, as they can lead to cryptic errors at the command line unless properly addressed (eg, by putting quotes around the full file name). This plays havoc with a variety of programs, including git.

• Intermediate files in phylogenetic analyses, such as posterior samples, can be very large. Since git caches each committed version of each file, this can make your git repository unwieldy. It is best to not add these large files (>50MB) to your repository. They can be in your folder right along side your other files on your local machine, just don't run git add on them. You can also create a .gitignore file so that you aren't reminded that they are untracked each time you run git commit. Excluding these intermediate files from your git repository doesn't usually reduce the reproducibility of your project, since they can be regenerated by anyone that has the project data and scripts (both of which should be in the repository).

• Do use subfolders in your repository to keep things organized. For example, if you are downloading many small data files put them in their own folder.

1. Understanding what phylogenetic trees are

2. Reading phylogenetic trees

3. An overview of example applications

4. Gene trees and species trees

1. Tree space

2. Characters and homology

3. Multiple sequence alignment

4. Optimality Criteria

5. Heuristics for finding trees

6. Summarizing trees

7. Measuring tree support

8. Dating trees

1. Models of molecular evolution

2. Calculating the likelihood of a tree

3. Bayesian inference

4. Relationship between Bayesian and likelihood approaches

5. Models of morphological evolution

1. Designing a phylogenetic study

2. Taxon and character sampling

3. Missing data

4. Sources of systematic error

1. Common scenarios

2. KH Test

3. SH Test

4. Other tests

1. Reconstructing discrete and continuous characters

2. Testing evolutionary scenarios

3. Characterizing patterns of character evolution, including phylogenetic signal

4. Examining the co-evolution of multiple characters, including independent contrasts

5. Accounting for phylogenetic uncertainty

1. Coalescence

2. Incomplete lineage sorting

3. Phylogeography

4. Speciation

1. Project design

2. Sequence assembly

3. Identifying homologs

4. Identifying orthologs

5. Simultaneous estimation of gene trees and species trees

1. Final Project presentations

You will use the following programs to work with phylogenies on your laptop. We will use computationally intensive programs, such as raxml and mrbayes, on the cluster.

• Mesquite. Mesquite will require that you also install Java. OS X will prompt you to install Java when you launch mesquite, if you don't already have java installed. You can install Java on Microsoft Windows from the Java site

• R

• FigTree

• CyberDuck

• Tracer

• Sublime Text 3

##External links

The following sites have a wide variety of material that is relevant to the theory and and practice of phylogenetic biology.

An extensive list of tools, tutorials, and examples of phylogenetic tools in the programming language R maintained by Briam O'Meara: CRAN Task View: Phylogenetics

The Workshop on Molecular Evolution at Woods Hole. This is an intensive summer course on phylogenetics, with an emphasis on building phylogenetic trees. Check out the faculty pages for lecture pdfs: Workshop on Molecular Evolution

The Applied Phylogenetics Workshop in Bodega Bay. This is another summer course on phylogenetics, but with a bit more emphasis on using phylogenies to test evolutionary questions: Applied Phylogenetics Workshop

The site for the book I co-authored with Steve Haddock, Practical Computing for Biologists: Practical Computing

Here are some of the appendices from the book, which summarize frequently used commands: Appendices

Documentation and resources for Oscar, the computer cluster we will use for our analyses: Oscar

The following resources provide additional background, and as papers to select from to read for class. Other papers can be selected as well. * indicates critical papers that should be read in each course.

Paradis, E. (2011) Analysis of Phylogenetics and Evolution with R. Springer

Felsenstein, J. (2004) Inferring phylogenies. Sinauer Associates.

Swofford, D. L., Olsen, G. J., Waddell, P. J., & Hillis, D. M. (1996). Phylogenetic inference. In: Molecular Systematics, Second Edition. eds: D. M. Hillis, C Moritz, & B. K. Mable. Sinauer Associates

Here are some papers that illustrate interesting applications for phylogenetics, key concepts, and methods. Many papers on this list were compiled by Felipe Zapata. We will draw from some of these for reading in the class.

De Queiroz K: Species concepts and species delimitation. Syst. Biol. 2007, 56:879–886. http://dx.doi.org/10.1080/10635150701701083

Drummond AJ, Ho SYW, Phillips MJ, Rambaut A: Relaxed phylogenetics and dating with confidence. PLoS Biol. 2006, 4:e88. http://dx.doi.org/10.1371/journal.pbio.0040088

• Felsenstein J: Phylogenies and the Comparative Method [Internet]. American Naturalist 1985, 125:1–15. http://www.jstor.org/stable/2461605

Gire SK, Goba A, Andersen KG, Sealfon RSG, Park DJ, Kanneh L, Jalloh S, Momoh M, Fullah M, Dudas G, et al.: Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science 2014, 345:1369–1372. http://dx.doi.org/10.1126/science.1259657

Guang A, Zapata F, Howison M, Lawrence CE, Dunn CW: An Integrated Perspective on Phylogenetic Workflows. Trends in Ecology & Evolution 2016, 31:116–126. http://dx.doi.org/10.1016/j.tree.2015.12.007

Heath TA, Zwickl DJ, Kim J, Hillis DM: Taxon sampling affects inferences of macroevolutionary processes from phylogenetic trees. Syst. Biol. 2008, 57:160–166. http://dx.doi.org/10.1080/10635150701884640

Hillis DM, Huelsenbeck JP, Cunningham CW: Application and accuracy of molecular phylogenies. Science 1994, 264:671–677. http://dx.doi.org/10.1126/science.8171318

Holder M, Lewis PO: Phylogeny estimation: traditional and Bayesian approaches. Nat Rev Genet 2003, 4:275–284. http://dx.doi.org/10.1038/nrg1044

Huelsenbeck JP, Ronquist F, Nielsen R, Bollback JP: Bayesian inference of phylogeny and its impact on evolutionary biology. Science 2001, 294:2310–2314. http://dx.doi.org/10.1126/science.1065889

Huelsenbeck JP, Hillis DM: Success of Phylogenetic Methods in the Four-Taxon Case. Syst. Biol. 1993, 42:247–264. http://dx.doi.org/10.1093/sysbio/42.3.247

Knowles LL: Statistical Phylogeography. Annu. Rev. Ecol. Evol. Syst. 2009, 40:593–612. http://dx.doi.org/10.1146/annurev.ecolsys.38.091206.095702

Maddison WP: Gene Trees in Species Trees. Syst. Biol. 1997, 46:523–536. http://dx.doi.org/10.1093/sysbio/46.3.523

Asynchronous Diversification in a Specialized Plant-Pollinator Mutualism http://www.sciencemag.org/cgi/doi/10.1126/science.1209175

Exceptional Convergence on the Macroevolutionary Landscape in Island Lizard Radiations http://www.sciencemag.org/cgi/doi/10.1126/science.1232392

The Role of Geography and Ecological Opportunity in the Diversification of Day Geckos (Phelsuma) http://sysbio.oxfordjournals.org/cgi/doi/10.1080/10635150802304779

Patterns of Variation in Levels of Homoplasy http://www.jstor.org/stable/2409392?origin=crossref

Locating evolutionary precursors on a phylogenetic tree. http://onlinelibrary.wiley.com/doi/10.1111/j.1558-5646.2012.01720.x/abstract

• Tempo and mode of evolutionary radiation in iguanian lizards. http://www.ncbi.nlm.nih.gov/pubmed/12920297

Independently evolving species in asexual bdelloid rotifers. http://www.ncbi.nlm.nih.gov/pubmed/17373857

A likelihood framework for inferring the evolution of geographic range on phylogenetic trees. http://doi.wiley.com/10.1111/j.0014-3820.2005.tb00940.x

Inferring rates of change in flower symmetry in asterid angiosperms http://dx.doi.org/10.1080/106351599260201

Exploring the Phylogenetic Structure of Ecological Communities: An Example for Rain Forest Trees. http://www.jstor.org/stable/10.1086/303378

Species coexistence and the dynamics of phenotypic evolution in adaptive radiation http://dx.doi.org/10.1038/nature12874

An Integrative Method for Delimiting Cohesion Species: Finding the Population-Species Interface in a Group of Californian Trapdoor Spiders with Extreme Genetic Divergence and Geographic Structuring http://sysbio.oxfordjournals.org/cgi/doi/10.1080/10635150802302443

Using heterochrony to detect modularity in the evolution of stem diversity in the plant family moringaceae http://onlinelibrary.wiley.com/doi/10.1111/j.0014-3820.2006.tb01151.x/abstract

Insights on the evolution of plant succulence from a remarkable radiation in Madagascar (Euphorbia). http://sysbio.oxfordjournals.org/cgi/doi/10.1093/sysbio/syu035

Articulating “Archiannelids”: Phylogenomics and Annelid Relationships, with Emphasis on Meiofaunal Taxa http://mbe.oxfordjournals.org/lookup/doi/10.1093/molbev/msv157

Poor Fit to the Multispecies Coalescent is Widely Detectable in Empirical Data http://sysbio.oxfordjournals.org/cgi/doi/10.1093/sysbio/syt057

Source identification in two criminal cases using phylogenetic analysis of HIV-1 DNA sequences http://www.pnas.org/content/107/50/21242.abstract

Please check the schedule a week in advance for revisions.

All original software is licensed under a GPL v3 license. Data that is downloaded from public archives is distributed in accordance with the license of the source archive. All other original content is distributed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.