metagenomic workshop
DESCRIPTION
METAGENOMIC WORKSHOP. James R. Cole, Ph.D. Ribosomal Database Project Center for Microbial Ecology Michigan State University. http://rdp.cme.msu.edu. Some Bacterial Names. Bacillus subtilis (Ehrenberg 1835) Cohn 1872 Rhizobium meliloti Dangeard 1926 - PowerPoint PPT PresentationTRANSCRIPT
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METAGENOMIC WORKSHOP
James R. Cole, Ph.D.Ribosomal Database ProjectCenter for Microbial Ecology
Michigan State University
http://rdp.cme.msu.edu
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Some Bacterial Names
• Bacillus subtilis (Ehrenberg 1835) Cohn 1872
• Rhizobium meliloti Dangeard 1926• Sinorhizomium meliloti (Dangeard 1926) De Lajudie
et al. 1994• Ensifer meliloti (Dangeard 1926) Young 2003
• Actinobacteria Stackenbrandt et al. 1997
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Prokaryotic Nomenclature
• Bacterial and Archaeal Names are covered by an official set of rules: – “The International Code of Nomenclature of
Prokaryotes”
– Covers ranks from Class to Subspecies.
– Ranks of Kingdom and Phylum (Domain) are not covered by the code.
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Synonymy
New Combination (taxonomic change)Rhizobium meliloti -> Ensifer meliloti
Homotypic Synonym (same type strain)Aeromonas caviae = Aeromonas punctata
Heterotypic Synonym (different type strain)Wautersia eutropha => Cupriavidis necator
9612 Species Names But Only 8062 Species?
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Prokaryotic Taxonomy
• There is no formal Prokaryotic taxonomyTaxonomy is a matter of opinion!
• Changes in opinion may require changes in nomenclature Rhizobium meliloti -> Ensifer meliloti
• Every taxon must be circumscribed•
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Bacterial Species
• One strain of a species is designated as the “type strain”. Other closely related strains are of the same species.
• There is no completely objective method for species delimitation.
• The current accepted standard is 70% DNA-DNA hybridization (DDH)
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Stackebrandt, E. and J. Ebers. (2006) Taxonomic parameters revisited: tarnished gold standards. Microbiology Today :152-155.
DDH vs 16S Similarity
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Goris, J., Konstantinidis, K.T., Klappenbach, J.A., Coenye, T., Vandamme, P., Tiedje, J.M. (2007) DNA–DNA hybridization values and their relationship to whole-genome sequence similarities. IJSEM 57:81–91. doi:10.1099/ijs.0.64483-0
DDH vs Genome Similarity
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Bacterial Species Definition
• The species concept in bacteria is not well defined.
• As an ad-hoc measure, 70% DHH has several limitations.
• Less than 98.5% 16S similarity indicates different species, but greater than 98.5% does not indicate the same species.
• ANI may be a good candidate to replace DHH as an ad-hoc species definition.
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Nomenclatural References
• The International Code of Nomenclature of Prokaryotes: http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=icnb
• List of Prokaryotic Names with Standing in Nomenclature http://www.bacterio.cict.fr/index.html
• Bacterial Nomenclature Up-to-Date http://www.dsmz.de/microorganisms/bacterial_nomenclature.php
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Taxonomy References
• NCBI Taxonomyhttp://www.ncbi.nlm.nih.gov/Taxonomy/
• TOBAhttp://www.taxonomicoutline.org/
• Bergey’s Taxonomyhttp://www.bergeys.org/outlines.html
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Phylogenetic Inference
Use simplest method that works.
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Why rRNA?
• Universal• No ortholog - paralog problem• No horizontal gene transfer• Easy to amplify and sequence• Large database
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Jukes & Cantor
To: A G C T --------------------------------- A | 1-3a a a a From: G | a 1-3a a a C | a a 1-3a a T | a a a 1-3a
p = 3/4 ( 1 - e- 4/3 u t )
ut = - 3/4 loge ( 1 - 4/3 p )
a = u dt
(ut = evolutionary distance)
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Substitution Models
• Jukes & Cantor (0 parameters)– All rates equal
• Kimura (2 parameters)– Transition & transversion different
• HKY (6 parameters)– Plus different frequency of four nucleotides
• Generalized time reversible– 8 parameters
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Alignment Mask
• Use to remove unstable regions from phylogenetic analysis– Inserts and deletes make homolog assigment difficult
• Rapidly changing regions add noise• Should be reported in publication (but often are
not)• Alignment masks should be provided with
alignment• Can be created by using ad-hoc rules
– Eg 50% residues in column
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Phylogenetic Methods
• UPGMA– Assumes clock
• Neighbor Joining– No clock, distance based
• Parsimony– Slow, used in other fields
• Maximum Likelihood– Slow, but fast converging, allows different rates
• Bayesian– Can be faster then maximum likelihood
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Confidence Estimation
• Bootstrapping alignment columns– Estimates confidence for individual branch
order– Sensitive to “unstable” sequenes
• Kishino-Hasegawa-Templeton test– Compares whole trees– Asks one is significantly better– Uses Maximum Likelihood
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Phylogeny Programs
• Phylogeny Program List:http://evolution.genetics.washington.edu/phylip/software.html
• Phyliphttp://evolution.genetics.washington.edu/phylip
• MEGAhttp://www.megasoftware.net/
• Clearcuthttp://bioinformatics.hungry.com/clearcut/
• Weighborhttp://www.t6.lanl.gov/billb/weighbor/index.html
• Mr. Bayes• http://mrbayes.csit.fsu.edu/
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The Ribosomal Database Project
Sequences and tools
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Aligned and annotated sequences
tutorials and helpupload and align
your own 16Ssequences inyour private
myRDP space and use the new
analysis Pipelineinteractive online tools
powerful search andselection features
view by publication or genome
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RDP-II Screenshotsfast search algorithm,limit searches to sequences spanning specific regions,
change depth and edit distance
place sequences into bacterial taxonomy,works well with partial or full-length sequences,
bootstrap confidence estimate,prior alignment not required
finds nearest neighbor,more accurate than BLAST,
uses “q-gram” matching method
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examine sequences by publication
Browse and select from taxonomic hierarchy
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rRNA sequence from genome projects
Provides links to other genome-related information
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Ribosomal Database Project-IImyRDP Personal/Collaborative Workspace
upload and align your own 16S sequences in your
myRDP space
your gateway to thehigh-throughput pipeline
share specific data with research buddies
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Ribosomal Database Project-IImyRDP High-Throughput Pipeline
sequencer debugging:status and quality
summary for each sequence
Library-level information
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Ribosomal Database Project-IImyRDP Single-Read Pipeline
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Interactive assignments customized on a per-student basis
Short video tutorials cover all major features
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RDP 10 Alignment
• INFERNAL Stochastic Context-Free Grammar Aligner (Eddy)
• INFERNAL (Eddy)– Fast– Replaces RNAcad (Brown)
• Incorporates secondary structure information
• Probabilistic model • New training set
http://www.rna.icmb.utexas.edu
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