BigData 2018

City Tech/Cornell BioMedical Big Data Week 2018: Introduction to Evolutionary Genomics Instructor: Dr Weigang Qiu, Associate Professor, Department of Biological Sciences Office: B402 Belfer Research Building Email: weigang@genectr.hunter.cuny.edu Lab Website: http://diverge.hunter.cuny.edu/labwiki/

---

What is evolutionary genomics?

Genomes differ among individuals and species. Evolutionary genomics studies genome variability and genome changes using evolutionary principles. Typical applications include identification of human genome variations associated with diseases and identification of pathogen virulence genes.

Genome changes are studied at two distinct levels: (1) within-species/within-population variations (e.g., human genetic variation), and (2) between-species divergence (e.g., human-mouse comparisons).

The key for analyzing genome variations within species is "population-thinking", the idea that there is no one individual genome that is standard, normal, or disease-free.

The key for comparing genomes across species is "tree-thinking", the idea that evolution happens by diversification (like a branching tree), not by climbing a ladder. There is no such thing as "advanced" or "primitive" species. All living species have the exact same evolutionary distances/time of divergence since the origin of life.

Case studies from Qiu Lab

• Between-sepcies genome comparisons: Comparative genomics of worldwide Lyme disease pathogens. BorreliaBase
  

  Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)
• Within-population genome comparison: Genomic epidemiology of Group B Streptococcus
• Within-host genome evolution: Evolution of multi-drug antibiotic-resistance Pseudomonas in cancer patients
  

  Developmnt of drug resistance mutation in Pseudomonas in a single cancer patient: top (April) vs. bottom (July)

Reference

• Graur, 2016, Molecular and Genome Evolution, First Edition, Sinauer Associates, Inc. ISBN: 978-1-60535-469-9. Publisher's Website
• Baum & Smith, 2013. Tree Thinking: an Introduction to Phylogenetic Biology, Roberts & Company Publishers, Inc.

Learning Goals

• Be able to compare evolutionary relationships using phylogenetic trees
• Be able to use command-line tools for batch-processing of genome files
• Be able to perform genome-wide association analysis on the R platform

Quizzes & Assignments

• "Tree Thinking Quizzes"
• FASTA manipulations with bioseq