Novel kinesin families in diverse microbial eukaryotes

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Novel kinesin families in diverse microbial
eukaryotes

• Scott C. Dawson (CandeLab), Lee Douglas
  (WelchLab), Matt Welch, W. Zac Cande
• MCB, UC-Berkeley

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Specific Research Questions

• What are the evolutionary relationships of
  kinesins?
• How to classify orthologous kinesins in protists?
• Are there major protist only kinesin lineages?
• (note 7 last page in handout!!!!)
• Is there a taxonomic sampling bias?
• Will better taxon sampling improve trees?
• Does sampling improve our understanding of
  kinesin evolution?

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Insufficient taxonomic sampling affects

• Robustness of phylogenies (more severe with some
  inference methods)
• Number of groups/relationships among groups
• Signatures of groups/motifs
• Biological perspective on function
  (distinguishing orthologs from paralogs)

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How to improve robustness of phylogenetic trees?
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Approach

• Use phylogenomic methods to mine partial and
  completed eukaryotic genomes (mostly microbial)
• Reconstruct kinesin evolutionary history using
  various inference methods good for large-scale
  phylogenies (e.g. Bayesian)

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Phylogenomic analysis of kinesins in diverse
eukaryotes

• 602 aligned motor domains
• 349 homologous positions (several datasets)
• NJ, quartet puzzling, bayesian inference (mb) on
  subset of 475 taxa
• Emphasized kinesins in unicellular eukaryotic
  kingdoms
• de-emphasized vertebrate/metazoans, and/or recent
  duplications

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Familiar taxa represented in our analysis

• Metazoan mouse/human, fly, worm, fish
  (Fugu/Danio), frog, tunicate (Ciona)
• Fungi basidiomycetes ascomycetes (yeasts and
  filamentous) microsporidians
• Green Arabidopsis, Rice/Maize, Chlamydomonas

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Phytophthora (oomycete), Thalassosira (diatom)
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Tetrahymena (ciliate) Toxoplasma,
Cryptosporidium, Plasmodium (apicomplexans)
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Other microbial eukaryotes used in this phylogeny
Chlamydomonas (green algae), Entamoeba,
Dictyostelium, Leishmania, Trypanosoma
(Trypanosomes/Euglenozoa) Giardia (Diplomonads)
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N602
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What is structure of the kinesin tree?
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Bayesian Inference

• Advantages
• Fast and robust based on ML (likelihood)
• Can handle many more taxa than ML
• Can handle complex inference models
• Disadvantages
• need to specify posterior probabilities
• also need to make sure have run to saturation
  (e.g. gt3 million reps for our trees)

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Putative Kinesin Family Sister Groups

• BimC/Kip2/Cenp-E/Novel1/KHC
• Unc104/KRP85/95/Novel2
• Mklp/Cterm (several subgroups)
• MCAK/Kip3, Chromo, Nod, Novel3
• Several large unclassified groups
• This is somewhat different from previous trees
  sampling? methodology?

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What is the relationship between phylogenetic
depth and nomenclature?Ex Mklp1/Cho1/N-6BimC
Motif Novel Families
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Motifs tend to break down at greater
phylogenetic depths
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Novel trypanosome kinesin family
C
B
A
Unc104
KRP85/95
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How to define and name novel groups and/or new
sequences?

• Names of existing groups
• Names of novel/future groups
• Classification of new sequences

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Criteria for candidate kinesin groups

• Robust phylogeny using full-length motor domain
• Strong support (gt70 is strong for this level)
• Monophyletic (common ancestor all decendants)
• At least 2 members of gt1 higher-level group
  (genus level or higher)

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Candidate
Candidate
Not candidate
Includes all decendants
Candidate
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Monophyletic Mklp/Cho1/N-6 common ancestor plus
all decendants facilitates classification of
future sequences/ determination of orthology
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Kinesin nomenclature for the new millennium

• Monophyletic or natural (genotypic) groups should
  trump functional (phenotypic) groups
• Avoid paraphyletic groups (KinI)
• Need to standardize wide variations in
  phylogenetic depth (avoid shallow groupings)
• Avoid taxa-specific nomenclature
• Names of superfamilies?
• Test functional hypotheses little information on
  function on orthologs in diverse eukaryotes