generation and analysis of aflp data espm 150/290: biology, ecology, and genetics of forest diseases...
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Generation and Analysis of AFLP Data
ESPM 150/290: Biology, Ecology, and Genetics of Forest Diseases
Laboratory ExerciseApril 1, 2010
Some Considerations in Choosing a Genotyping Method
• What is the level of taxonomic resolution desired? (Populations? Species? Phyla?)– Comparison of distantly related individuals requires slowly
evolving markers (e.g., protein-coding DNA or Amino Acid sequences) due to saturation of changes in quickly-evolving markers
– Comparison of closely related individuals requires rapidly evolving markers (e.g., microsatellites or non-coding DNA sequences)
• What is the level of genotypic resolution desired? – Dominant vs. codominant markers– Fine (e.g., nucleotide-level) data vs. coarse (e.g., fragment size)
genomic scale – detailed information about one or a few loci vs. less-detailed information about more loci
Some Considerations in Choosing a Genotyping Method
• How much previous sequence knowledge is available?– DNA sequencing, microsatellite amplification, PCR-RFLP, etc.
require previous sequence information so that PCR primers can be designed
– AFLPs and RAPDs allow genetic fingerprinting when previous sequence knowledge is not available
• What are the cost and labor constraints?– DNA sequencing is more costly than fragment analysis– Techniques requiring fluorescent labeling are generally more
costly than techniques that don’t require labeling
1. Double strand denaturation
2. Annealing of the primers
3. Elongation
5’5’
5’
3’3’
A review of PCR amplificationRequirements: DNA template 2 oligonucleotides - Primers Nucleotides dATP, dCTP, dGTP, dTTP Taq polymerase
Restriction Enzymes• Found in bacteria
• Cut DNA within the molecule (endonuclease)
• Cut at sequences that are specific for each enzyme (restriction sites)
• Leave either blunt or sticky ends, depending upon the specific enzyme
http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/R/RestrictionEnzymes.html
Tobin & Dusheck, Asking About Life, 2nd ed. Copyright 2001, Harcourt, Inc.
Random Genomic Markers
DNA sequence of suitable SNPs is not availableRelatively inexpensiveScan the entire genome producing information
on several variations in the same reaction
RAPD Random Amplification of Polymorphic DNA
AFLP Amplified Fragment Length Polymorphism
AFLP Amplified Fragment Length Polymorphisms
(Vos et al., 1995)
Genomic DNA digested with 2 restriction enzymes:– EcoRI (6 bp restriction site)cuts infrequently
– MseI(4 bp restriction site)cuts frequently
GAATTCCTTAAG
TTAAAATT
Fragments of DNA resulting from restriction digestion are ligated with end-specific adaptors (a different one for each enzyme) to create a new PCR priming site
Pre selective PCR amplification is done using primers complementary to the adaptor + 1 bp (chosen by the user)
NN N N
AFLP genotyping
PCR amplification using primers corresponding to the new sequenceIf there are 2 new priming sites within 400 – 1600 bp there is amplification
The result is: Presence or absence of amplification1 or 0Dominant marker: does not distinguish between heterozygote and homozygote
Due mostly to SNPs but also to deletions/insertions
Analysis of AFLP data Similarity (cluster analysis) NJ (Neighbor Joining) UPGMA (Unweighted Pair Group Method with Arithmetic mean) AMOVA (Analysis of Molecular Variance)
Model-based Maximum likelihood Bayesian
Image Source: http://media.wiley.com/CurrentProtocols/BI/bi0603/bi0603-fig-0002-1-full.gif
Example of a sequence distance matrix
Analysis of AFLP data Similarity (cluster analysis) NJ (Neighbor Joining) UPGMA (Unweighted Pair Group Method with Arithmetic mean) AMOVA (Analysis of Molecular Variance)
Model-based Maximum likelihood Bayesian
Image Source: http://media.wiley.com/CurrentProtocols/BI/bi0603/bi0603-fig-0002-1-full.gif
Example of a sequence distance matrix
AFLP Data Map with UPGMA dendogram from Urbanelli et al. (2007): “Distinguishing taxa in the Pleurotus eryngii (King Oyster Mushroom) complex using AFLPs”• 90 populations sampled• 94 AFLP loci scored
Photos: (Top) The New York Times (Bottom L) Wikimedia Commons (Bottom R) http://steinpilz.up.seesaa.net
Example Structure Output
Rosenberg et al. (2002). Science 298: 2381-2385.
“Estimated population structure for 10 runs of structure using 1056 individuals from 52 human populations. Each graph represents the output of one run of structure. In each graph, each individual is represented by a vertical line, which is partitioned into 5 colors that represent its estimated membership fractions in K=5 clusters.” (Source: http://rosenberglab.bioinformatics.med.umich.edu/clumppExample.html)