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Reticulate Evolution

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Alexandra Jacunski

on 29 January 2015

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Transcript of Reticulate Evolution

Reticulate Evolution
and the Tree of Life The Applications of
Phylogenetic Networks Phylogenetic Networks Applications Herpes Virus Shortcomings Hepatitis C Worked Example Unrooted Networks Rooted Phylogenetic Networks General Principles The Phylogenetic
Tree Constructing the Tree
of Life The Origin of the Tree Introduction Structure that helps to infer evolutionary relationships
Many varieties of tree, including:
Cladogram: representation of branching pattern; meaningless branch spans
Phylogram: branches proportional to character change
Chronogram: evolutionary time represented by branches Use of multiple sequence alignment (MSA) between genetic or amino acid sequences
Four primary methods of computational phylogeny
Distance-matrix methods
Maximum parsimony
Maximum likelihood
Bayesian inference Defined as "any graph used to represent evolutionary relationships ...between a set of taxa that labels some of its nodes" (Huson et al, p.69)
Like their tree counterparts, phylogenetic networks can be rooted or unrooted
The computation of unrooted networks is more simple than that of rooted networks Split Networks
Given incompatible incompatible phylogenetic trees
Quasi-median Networks
Representation of multi-state characters; best for closely-related species
Haplotype Networks
Nodes indicate haplotypes within a group of taxa; edges join the most similar ones.
Unrooted tree with auxiliary edges Cluster network
Hybridization Network
Recombination Network
Duplication-Loss-Transfer (DLT) Network
etc... Split Network... 569 patients infected with Hepatitis sequenced between 1997 and 2006 at different targets
Almost 20% presented as intergenic recombinants
Phylogenetic network analysis performed on 11 novel and 30 known gE sequences of HSV-1 strains using Neighbor-net network analysis and Bayesian phylogenetic tree analysis.
Neighbor-net: loosely based on NJ; uses distance matrix; agglomerates clusters; creates split networks (+)ssRNA virus with single ORF of ~9600bp
Seven genotypes (1-7) with around 80 subtypes between them
Genotypes are said to differ
by 30-35% NT sites, while
subtypes differ by 20-25%
(Ohno et al, 2007). Originally presented as a concept depicting the interrelatedness of all living things by Darwin as the only illustration in his book (below; 1859)
Evoution of Lamarck's Philosophie Zoologique
20th-century phenetics developed as a way to classify organisms based on observable traits Computational Phylogenetics Methods Distance Matrix Methods Maximum Parsimony Maximum Likelihood Bayesian Inference Unweighted Pair Group Method with Arithmetic Mean (UPGMA): follows the molecular clock hypothesis Neighbour Joining Method (NJ): not constrained by molecular clock Non-parametric statistical method
Expectation that the best tress is the one that involves the fewest changes to explain the observed data
Can include ordered and/or weighted characters
Weighting of 3rd base of a given codon, e.g. Infers probability distribution to assign probability of possible phylogenetic trees
i.e. more mutations at internal nodes is less probable
Similar to maximum parsimony, but allows varying rates of evolution (for both given branches and given sites)
Can use a pruning algorithm to calculate likelihood of subtrees Also similar to maximum likelihood
Generation of posterior distribution based on phylogenetic tree & a model of evolution based on prior of this parameter and the likelihood of the data (given by MSA) Failings of This Type of Phylogenetic Investigation Tree-like representations of 'life' pertain only to vertical inheritance
This ignores reticulation events such as horizontal gene transfer (HGT), recombination, hybridization,
Reticulate evolution in all sorts of species have led us to a "net of life" rather than the "tree of life" Huson et al, p.70 Split Network Given a set of splits S on X={a...g}, where
{a,b}/{c,d,e,f,g} {a,b,c}/{d,e,f,g}
{a,b,e,f,g,}/{c,d} {a,f,g}/{b,c,d,e}
and all trivial splits...
what is the split network N? {a,b}/{c,d,e,f,g} and {a,b,c,}/{d,e,f,g} give us a normal tree. A B C D E F G Consider adding {a,b,e,f,g}/{c,d}: issue comes in with c in {a,b}/{c,d,e,f,g} and {a,b,c}/{d,e,f,g} c d a b e f g a f g b d e Must also account for {a,f,g}/{b,c,d,e} Put it together... {a,b}/{c,d,e,f,g}; {a,b,c}/{d,e,f,g}; {a,b,e,f,g,}/{c,d}; {a,f,g}/{b,c,d,e} a b c d e f g in our base {a,b}/{c,d,e,f,g} & {a,b,c}/{d,e,f,g} Schmidt-Chanasit et al. A 10-year molecular survey of herpes simplex virus type 1 in Germany demonstrates a stable and high prevalence of genotypes A and B. J Clin Vir. 2009. 44(3) 235-237.
nb. sample names: Strain designation(gG genotype/gI genotype) Works Cited Gonzales-Candelas et al. Recombination in Hepatitis C Virus. Viruses. 2001. 3:2006
Ohno et al. Hew Hepatitis C virus (HCV) genotyping system that allows for
identification of HCV genotypes 1a, 1b, 2a, 2b, 3a, 3v, 4, 5a, 6a. J. Clin. Mircobiol. 1997. 35(1):201-207.
Huson et al. Phylogenetic Networks: Concepts, Algorithms and Applcations.
Cambridge University Press. 2010.
Schmidt-Chanasit et al. A 10-year molecular survey of herpes simplex virus type 1 in
Germany demonstrates a stable and high prevalence of genotypes A and B. J Clin Vir. 2009. 44(3) 235-237. Full genome; species subset - NN/Parsimony Full genome; all strains - N/Parsimony Consensus cluster between two genes: also significantly unhappy Still a developing field
Computational feasibility (polynomial-time solvable)
Development of heuristics
Discernment of mutational changes in the genome from real reticulation events Reports of recombination in HCV not published until 2002; many negative reports exist (note publication bias). Difficulties include
Superinfection exclusion
Lowish rates of coinfection (1.3-39% reported)
Artificial patterns associated with high mutation rate. (Gonzalez-Candelas et al, 2011)
Acquired a total of 936 genomic sequences of Hepatitis C; pruned down to 870 full-length, high-quality sequences; AA aln
Regular phylogenetic analysis and phylogenetic network analysis performed on full spectrum of sequences and subsets thereof using NJ and Network-Net analysis, respectively. c Persistent Homology Influenza
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