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A Bayesian method for DNA barcoding. Kasper Munch, Wouter Boomsma, Eske Willerslev, Rasmus Nielsen, University of Copenhagen. Assignment to existing species. Identification of new species. Assignment to taxonomic levels in general. Varieties of barcoding. Motivation.

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a bayesian method for dna barcoding

A Bayesian method for DNA barcoding

Kasper Munch, Wouter Boomsma, Eske Willerslev, Rasmus Nielsen, University of Copenhagen

varieties of barcoding
Assignment to existing species.

Identification of new species.

Assignment to taxonomic levels in general

Varieties of barcoding
motivation
Motivation
  • Environmental aDNA samples.
  • Putative Neandertal DNA.
  • Often short query sequences.
    • Little information.
  • Permissive PCR conditions.
    • Not always from the intended locus.
slide4
Given a set of database reference sequences from different species

– according to which criteria should we assign new query sequences to taxonomic levels?

?

true species assignment
True species assignment
  • Requires proper population genetic analyses quantifying variablity within species.
  • Often not possible...
    • small database sample size for each species.
    • short query PCR products.
phylogenetic alternative
Phylogenetic alternative
  • Purely phylogenetic criteria which ignore population genetic problems.
  • Taxonomic annotation of database sequences is used to map phylogenetic groups to taxonomic levels.
  • The simpler approach has its own advangates:

Less data required / Fewer assumptions

ingroup or outgroup
Ingroup or outgroup?

Monophyletic

taxonomic group

Query

estimating trees
Estimating trees
  • Estimation of a single tree is not sufficient because of the uncertainty regarding the phylogeny.
  • We suggest instead to use a Bayesian approach which quantifies this uncertainty
bayesian approach
Bayesian approach
  • Let Q be the query sequence, X the database data, G a gene tree, and F a desired taxonomic group, then

where Giis the ith gene tree sampled from p(G | X).

assignment pipeline
Assignment pipeline

Retrieval of sequences

and taxonomy annotation

NCBI blast

Query

Sequence

Homology

set

Database

(GenBank)

ClustalW

Taxonomy

summary

Sampled

trees

Alignment

Summary

Statistics

MrBayes

summary statistics
Summary statistics
  • For each tree:
    • Find the sister group to the query.
    • Find the list of taxonomic levels shared by the sequences in the sister group (consensus taxonomy)

Sister group

Query

summary statistics1
Summary statistics
  • For each tree:
    • Find the sister group to the query.
    • Find the list of taxonomic levels shared by the sequences in the sister group (consensus taxonomy)
  • For each name of each taxonomic level:
    • Find the fraction of samples trees where the consensus taxonomy include that name.
environmental samples
Environmental Samples
  • 379 environmental samples (aDNA)
  • RBCL and TRNL markers.
  • Aim is the identification of environmental flora
botanical evaluation
Botanical evaluation

Temperate climate

similar to central Sweden.

testing putative neandertal dna
Testing putative Neandertal DNA
  • Needless to say we have had several negative examples ...
  • One positive example:
    • Posterior probability of 91%.
problems
Problems
  • No population genetic modelling:
    • Outgroup problem.
    • Species issues are is not addressed.
    • Lineage sorting - not reciprocal monophyli.
  • Incomplete database
advantages
Advantages
  • Phylogenetic uncertainty and statistical uncertainty of assignment is addressed.
  • Posterior probability of assignment.
  • Alternative to single tree assignment.
  • Can be used on any database.
conclusions
Conclusions
  • The phylogenetic barcoding does not model the coalescence process.
  • It is the appropriate method for assignment with little data, or when assigning to higher taxonomic levels.
  • Bayesian approach offers a measure of confidence in assignment.