Workshop on Molecular Evolution


Course Information

facebook-buttonCourse Date: July 20 – July 30, 2017

Deadline: April 7, 2017 | Apply here

Tuition: $2400.00
Room and Board: $702.50
Financial Assistance Available: Yes

Course Website

2017 Schedule

Director: Anne Yoder, Duke University; and Joseph Bielawski, Dalhousie University

Course Description

MBL’s Workshop on Molecular Evolution is the most prestigious workshop serving the field of evolutionary studies. Founded in 1988, it is the longest-running workshop if its kind, and it has earned worldwide recognition for its rich and intensive learning experience. Students work closely with internationally-recognized scientists, receiving (i) high-level instruction in the principles of molecular evolution and evolutionary genomics, (ii) advanced training in statistical methods best suited to modern datasets, and (iii) hands-on experience with the latest software tools (often from the authors of the programs they are using). The material is delivered via lectures, discussions, and bioinformatic exercises motivated by contemporary topics in molecular evolution. A hallmark of this workshop is the direct interaction between students and field-leading scientists. The workshop serves graduate students, postdocs, and established faculty from around the world seeking to apply the principles of molecular evolution to questions of anthropology, conservation genetics, development, behavior, physiology, and ecology. The workshop also welcomes participants from federal agencies and science journalists. A priority of this workshop is to foster an environment where students can learn from each other as well from the course faculty.

Content has been carefully selected to provide participants with the background and practical skills required by modern molecular datasets. The schedule addresses the following subject areas, with each subject having one or more exercises focused on practical data analysis and interpretation skills.

  • An evolutionary perspective on molecular data: sequence matching; protein sequence versus protein structure; homology, orthology and parology; mathematical, statistical, and theoretical aspects of sequence database searches; multiple alignment; information resources
  • Foundations of phylogenetic analysis: theoretical, mathematical, and statistical principles; sampling properties of sequence data; Maximum likelihood theory and practice; Bayesian analysis; hypothesis testing
  • Species-level phylogenomics: species trees from gene trees; species delimitation; multi locus and SNP data; empirical examples
  • Deep phylogenomics: deep evolutionary relationships; lateral gene transfer; modeling approaches; topology testing; sequencing strategies
  • Foundations of population genetic analysis: neutral theory; coalescence theory; maximum likelihood and Bayesian estimation of population genetic parameters; empirical examples
  • Population genomics: phylogeography; molecular ecology; next-generation population genetics; signatures of natural selection; natural populations of non-model organisms
  • Comparative genomics: genome content; genome structure; gene and genome evolutionary dynamics; prediction of gene function
  • Molecular evolution integrated at organism and higher levels: population biology and ecology; natural selection; systematics and conservation
  • Molecular evolution integrated at lower levels: biochemistry; cell biology; physiology; natural selection; relationship of genotype to phenotype

As the course progresses, participants learn how to use the following software to address questions concerning the origins, maintenance, and function of molecular variation: ASTRAL, BEAST2, BEST, BPP, FASTA, FigTree, GARLI, MIGRATE, MAFFT, MP-EST, RaxML, RevBayes, PAML, PAUP*, Phybase, ipyrad and SVD Quartets. Students will have the opportunity to work with software on their own laptops as well receive training on how to use the same programs on a high performance computer cluster.

2017 Course Faculty

Peter Beerli, Florida State University
Joseph Bielawski, Dalhousie University
Belinda Chang, University of Toronto
Mario dos Reis, Queen Mary University London
Casey Dunn, Brown University
Deren Eaton, Yale University
Scott Edwards, Harvard University
Tracy Heath, Iowa State University
David Hillis, University of Texas
Mark Holder, University of Kansas
John Huelsenbeck, University of California-Berkeley
Lacey Knowles, University of Michigan
Laura Kubatko, Ohio State University
Paul Lewis, University of Connecticut
Emily Jane McTavish, University of California-Merced
Conor Meehan, Institute of Tropical Medicine
William Pearson, University of Virginia
David Swofford, Duke University
David Weisrock, University of Kentucky
Anne Yoder, Duke University

2017 Research Facilitators

Peter Larsen, Duke University
Nicholas Meyerson, University of Colorado Boulder
April Wright, Iowa State University