PHYLOGENETICSCONTINUED

TESTSBYTUESDAYBECAUSESOMEPROBLEMSWITHSCANTRONS

consensus tree• can also ask equally-

supported trees (equally parsimonious, equal likelihood) how well they all support same nodes

• doesn’t have to involve subset of data like in bootstrap

•may summarize the stable parts of tree across 2+ trees

ba c d e ba c d e

ba c d e

CONSENSUS phylogenyis not fully resolved

where there is disagreementamong equally-ranked trees

blue indicates dinosaurs with bifurcation of neural spine in vertebraehttp://svpow.com/papers-by-sv-powsketeers/wedel-and-taylor-2013-on-sauropod-neural-spine-bifurcation/

support for the method

•do we believe phylogeny reconstruction works? need to test it against a known history

•(fish(salamander(bird(mouse,human)) we feel pretty strongly about

•experimental phylogenetics uses virus evolution to go one step further

experimental evolution

growing T7 phage

on E. coli plates; speed up mutation

process by adding mutagen

40generations

40generations

40generations

experimental evolution

•so phylogeny is known, and ancestral strains can be kept in freezer

•sequence part of DNA and use parsimony, likelihood, and other approaches

•consistently got the right (TRUE) answer!

•can also track “traits” on this tree, e.g. changes in growth rate and plaque size on E. coli plates (and check against actual ancestors)

# DNA # DNA mutations mutations

on this on this branchbranch

Text: “Because constructing phylogenies, and science more broadly, is often a process of evaluating evidence, scientists often test the effectiveness of the methodologies used to draw conclusions.”

Rem: Rem: each each

branch is branch is 40 40

generatiogenerationsns

case studies

•text goes through Origin of Tetrapods, Human phylogeny, Darwins finches, HIV

•show phylogeny, explain the likely mechanisms for pattern

well-supported phylogeny of rabies virus

lineages, coded by host bat

species

Phylogeny: how?Methods from Streicker et al (2010 bat rabies phylogeny paper)

what gene what gene region(s)?region(s)?

PCR of PCR of gene with gene with primersprimers

how how sequence sequence

data data generatedgenerated

sampling sampling efforteffort

Phylogeny: how?Methods from Streicker et al (2010 bat rabies phylogeny paper)

tree criterion: tree criterion: uses statistical uses statistical model of DNA model of DNA

evolutionevolutionevery type of every type of

mutation happens mutation happens at different rate, at different rate,

as observedas observed

mutations happen mutations happen at different rates at different rates across codons in across codons in protein-coding protein-coding

genesgenes

are our data are our data consistently consistently

supporting same supporting same phylogeny?phylogeny?

outgroup comparison ‘roots’ phylogeny at outgroup comparison ‘roots’ phylogeny at ancestral nodeancestral node

Phylogeny: how?Methods from Streicker et al (2010 bat rabies phylogeny paper)

coalescent: coalescent: statistical model of statistical model of

how different how different evolutionary evolutionary

histories of drift, histories of drift, selection, selection,

migration, and migration, and change in change in

population size are population size are associated with associated with

DATADATA

treat bat species as treat bat species as locations and ask locations and ask how frequently how frequently

migration of virus migration of virus among species among species could explain could explain

pattern we see pattern we see now?now?

oh, no. now it is oh, no. now it is getting gnarly.getting gnarly.

For RNA viruses, rapid viral evolution and the biological similarity of closely related host species have been proposed as key determinants of the occurrence and long-term outcome of cross-species transmission. Using a data set of hundreds of rabies viruses sampled from 23 North American bat species, we present a general framework to quantify per capita rates of cross-species transmission and reconstruct historical patterns of viral

establishment in new host species using molecular sequence data. These estimates demonstrate diminishing frequencies of both cross-species transmission and host shifts with increasing phylogenetic distance between bat species .

Evolutionary constraints on viral host range indicate that host species barriers may trump the intrinsic mutability of RNA viruses in determining the fate of emerging host-virus interactions.

analysisindicates

rate of virusjumping from

one host to another

so this study requires TWO phylogenies (virus

and bats)CST: cross-species transmission

neutrality• neutral: doesn’t affect

fitness of organism

• compare mutations in protein coding regions: synonymous mutations do not change amino acid, nonsynonymous do

• if much of diversity is neutral (or nearly so), mutations will accumulate and fix (become a substitution) in populations regularly through time

“molecular clock” works for many genome partitionsneutrality acts as our NULL HYPOTHESIS

• different homologous genome regions have different rates, slower rates when more functional constraints

• remember: fossil record, biogeography/geology, mutation accumulation studies help us estimate substitution rate µ

isthmus closes via volcanicuplift ~3.5mya

two locations - are theytwo populations?

different allele frequencies,distinct clades on tree: yes

compare cytochrome oxidase mtDNA gene:

7% divergence

• d=2µt

• µ is the rate of mutations going to fixation (substitutions), under neutrality the mutation rate IS the substitution rate because selection doesn’t accelerate or halt or change probability of fixation

• here we know t=3,500,000 years, d=0.07

• µ = d/2t = (0.07)/(7,000,000) = 1x10-8

• another way to put it, rate of divergence (2µ) ~2% per million years

time(t), rate µ along 2 branches

•what is our assumption in those slides about clock calibration?

•how would YOU test that?

•idea is any mutation is equally likely to become a substitution

•how have we divided (point) mutations up so far?

neutrality• neutral: doesn’t affect

fitness of organism

• compare mutations in protein coding regions: synonymous mutations do not change amino acid, nonsynonymous do

• if much of diversity is neutral (or nearly so), mutations will accumulate and fix (become a substitution) in populations regularly through time

synonymous is assumed neutral

• so we can ask if nonsynonymous substitutions happen at a different rate

• neutrality: nonsynonymous divergence (dN) = synonymous divergence (dS) rate

• rate, not number of mutations - remember many more ways for a mutation to be nonsynonymous than synonymous

• does dN/dS =1? (book, elsewhere often this is called kA/kS; adjusts for the “more ways” of nonsynonymy)

This is the dN:dSor kA:kS approach

we have been discussing

if kA:kS >> 1, changehas been selected FORif kA:kS << 1, change

is generally BAD

if kA:kS ~ 1neutrality

positive selection: amino acid change is favored

functional constraints lead to high levels of homology: change is generally bad (purifying

selection)

region of high homology led todiscovery of new functional

regionthat influences mammalian heart

disease