Population Genomics Course: Difference between revisions

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==Syllabus==
==Syllabus==
===Part 1. Introduction & Overview===
===Part 1. Introduction & Overview===
• Lecture (45 min)
*Lecture: 8:30-9:30
o Bacterial population structure: B. burgdorferi in Northeast US
*Population processes
o Phylogenetic vs. coalescent trees
** Recombination: Muller's Rachet; Hill-Roberson effect
o Bioinformatics pipeline/protocol
** Recombination and natural selection: Background selection & selective sweeps
• In-Class Exercise (15 min): Tree Puzzles
*Bacterial population structure: B. burgdorferi in Northeast US
*Bioinformatics pipeline/protocol
*In-Class Exercise (15 min): Tree Puzzles
===Part 2. Building genome phylogeny/Geographic structuring/Population growth?===
===Part 2. Building genome phylogeny/Geographic structuring/Population growth?===
• Data: cp26 plasmids from ~20 B. burgdorferi sensu lato genomes
*In-class exercise: 10:00-11:30
• Demo (15 min)
*Data set: cp26 plasmids from 23 B. burgdorferi sensu lato genomes
o Genome alignment: MUGSY
*Genome alignment: MUGSY & Alignment viewer: Gmaj
o Alignment viewer: Gmaj
*Genome tree: FastTree
o Genome tree: FastTree
*Tree viewer: R package APE
o Tree viewer: R package APE
• In-Class Exercise (45 min)
===Part 3. Estimation of recombination rate===
===Part 3. Estimation of recombination rate===
• Data: three pairs of sister-group cp26 plasmids
*In-class exercise: 2-3
• Demo (15 min):
*Data set: three pairs of sister-group cp26 plasmids
o LAMAC
*LAMAC; LDhat
o LDhat
*Own script for sister-group counts? (D statistics)
o Own script for sister-group counts?
• In-Class Exercise (45 min)
===Part 4. Simulation of natural selection & Summary===
===Part 4. Simulation of natural selection & Summary===
• Data:
*In-class exercise: 3:30-5
• Demo (20 min): BacSim
*ms, seq-gen; Genomes
• In-Class Exercise (45 min):
*BacSim
 
==Assignment & Assessment==
==Assignment & Assessment==

Revision as of 15:06, 26 May 2013

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
  • Bacterial population structure: B. burgdorferi in Northeast US
  • Bioinformatics pipeline/protocol
  • In-Class Exercise (15 min): Tree Puzzles

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 viewer: R package APE

Part 3. Estimation of recombination rate

  • In-class exercise: 2-3
  • Data set: three pairs of sister-group cp26 plasmids
  • LAMAC; LDhat
  • Own script for sister-group counts? (D statistics)

Part 4. Simulation of natural selection & Summary

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

Assignment & Assessment

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