Population Genomics Course

Learning Goals

• Identification of lineage-specific genomic changes of pathogens
• Estimate recombination, mutation, and selection in natural pathogen populations

Learning outcomes

• Be able to construct genome trees using genome-wide SNPs
• Use genome trees to identify orthologs and paralogs, and gene gains and losses
• Detecting recombination among bacterial genomes
• Use of coalescence tree to describe process of microbial genome evolution

Syllabus

Part 1. Introduction & Overview

• Lecture: 8:30-9:30
• Population processes
  • Recombination: Muller's Rachet; Hill-Roberson effect
  • Recombination and natural selection: Background selection & selective sweeps
• Applications
  • GWAS
  • Population history: phylogeny, structuring, gene flow, and selective sweeps (e.g., Neandertal genomes; Borrelia burgdorferi in Northeast US)
  • Genomic surveillance of infectious diseases
• Bioinformatics pipeline/protocol
• In-Class Exercise: Software setup & data download

Part 2. Building genome phylogeny/Geographic structuring/Population growth?

• In-class exercise: 10:00-11:30
• Data set: cp26 plasmids from 23 B. burgdorferi sensu lato genomes
• Genome alignment: MUGSY & Alignment viewer: Gmaj
• Genome tree: FastTree
• Tree re-rooting: R package APE see syllabus
• Interactive tree viewer: trexonline

Part 3. Estimation of recombination rate

• In-class exercise: 2-3
• Data set: three pairs of sister-group cp26 plasmids

1. MUGSY visualization

• LDhat: Instructions; PDF Manual; Based on the "Four-Gamete Test" by Hudson & Kaplan, 1985

1. Download and Install:

   svn checkout https://ldhat.svn.sourceforge.net/svnroot/ldhat; make; make clean

2. Data: cp26.ss.fas
3. Convert to LDhat file format:

   ../ldhat/convert -seq cp26.ss.fas -2only -prefix cp26

4. Generate likelihood lookup table:

   ../ldhat/lkgen -lk lk_n100_t0.01 -nseq 14; mv new_lk.txt lk_n14_t0.01

5. Estimate recombination rates:

   ../ldhat/pairwise -lk lk_n14_t0.01 -seq cp26sites.txt -loc cp26locs.txt

6. Identify hotspots:

   ../ldhat/interval -lk lk_n14_t0.01 -seq cp26sites.txt -loc cp26locs.txt

7. Summarize results:

   ../ldhat/stat -input bounds.txt -burn 500 -loc cp26locs.txt

8. Visualize in RStudio

   1. source("http://ldhat.sourceforge.net/R/coalescent.r")

   2. Plot "outfile.txt"
   3. Plot "fit.txt"
   4. Plot "res.txt"

Part 4. Simulation of natural selection & Summary

• In-class exercise: 3:30-5
• ms, seq-gen; Genomes
• BacSim