Phylogeography  Phylogenetics oUnderstanding phylogenetic trees oMajor approaches to determining phylogenies  Phylogeography

Phylogenetics  Study of the evolutionary relationships among individuals, groups, or species  Relationships often represented as dichotomous branching tree  Extremely common approach for detecting and displaying relationships among genotypes  Important in evolution, systematics, and ecology (phylogeography)

A B M K I J N L H G F E D C Z Y X W V U T P Q S R O Ç Evolution

What is a phylogeny? Z Y X W V U T P Q S R O Ç  Homology: similarity that is the result of inheritance from a common ancestor

Phylogenetic Tree Terms ABCDEFGHIJ ROOT interior branches node terminal branches Leaves, Operational Taxonomic Units (OTUs) Group, cluster, clade

Bacteria 1 Bacteria 3 Bacteria 2 Eukaryote 1 Eukaryote 4 Eukaryote 3 Eukaryote 2 Tree Topology (Bacteria1,(Bacteria2,Bacteria3),(Eukaryote1,((Eukaryote2,Eukaryote3),Eukaryote4))) Bacteria 1 Bacteria 3 Bacteria 2 Eukaryote 1 Eukaryote 4 Eukaryote 3 Eukaryote 2

How about these? Are these trees different?

Rooted versus Unrooted Trees archaea eukaryote Unrooted tree Rooted by outgroup bacteria outgroup root eukaryote archaea Monophyletic group Monophyletic group

D C B A G E F C B A F E G D Rooting with D as outgroup

D C B A G E F C B A F E G D C B A F E G D Now with C as outgroup

Which of these four trees is different? Baum et al.

Phenetics (distance) vs Cladistics (character state based) Lowe, Harris, and Ashton 2004

Choosing Phylogenetic Trees  MANY possible trees can be built for a given set of taxa  Very computationally intensive to choose among these Lowe, Harris, and Ashton 2004

Felsenstein 2004 Choosing Phylogenetic Trees  Many algorithms exist for searching tree space  Local optima are problem: need to traverse valleys to get to other peaks  Heuristic search: cut trees up systematically and reassemble  Branch and bound: search for optimal path through tree space

Phylogeography  The study of evolutionary relationships among individuals based on phylogenetic analysis of DNA sequences in geographic context  Can be used to infer evolutionary history of populations  Migrations  Population subdivisions  Bottlenecks/Founder Effects  Can provide insights on current relationships among populations  Connectedness of populations  Effects of landscape features on gene flow

Phylogeography  Topology of tree provides clues about evolutionary and ecological history of a set of populations  Dispersal creates poor correspondence between geography and tree topology  Vicariance (division of populations preventing gene flow among subpopulations) results in neat mapping of geography onto haplotypes

Example: Pocket gophers (Geomys pinetis)  Fossorial rodent that inhabits 3-state area in the U.S.  RFLP for mtDNA of 87 individuals revealed 23 haplotypes  Parsimony network reveals geographic relationships among haplotypes  Haplotypes generally confined to single populations  Major east-west split in distribution revealed Avise 2004

I II III IV V Example: Brown Bears (Ursus arctos)  Reduced to <1% of original range in North America  Sequence mtDNA control region of bears from worldwide distribution  Notice unique haplotype F in ABC islands of Alaska  Notice position of polar bear Lowe, Harris, and Ashton 2004

Brown Bear Surprise  Subsequent study of samples from ice cores (36,000-43,000 years old) found all four haplotypes  How do you explain the modern distribution? Current Ancient

Brown Bears in North America (Ursus arctos)  Diversity assessed based on 8 microsatellite loci  Reduced diversity for more isolated sites (Kodiak, Yellowstone)

Brown Bear Nuclear Differentiation  Assessed differentiation based on 17 nuclear microsatellite loci  Strong differentiation between Kodiak and Admiralty islands Lowe, Harris, and Ashton 2004

Brown Bear Nuclear Differentiation  Less differentiation for nuclear than mitochondrial markers  Degree of differentiation driven by distances between islands: Admiralty much more divergent than Chicagof or Baranof  Why? Lowe, Harris, and Ashton 2004  Also, maternal inheritance of mitochondrion  Smaller effective population size of mitochondrion  Mitochondrion is one locus: selective sweeps!

Ursus arctos in Europe  Highly degraded populations, low genetic diversity  Haplotypes reveal 3 refugia during glaciation  Migration and admixture following deglaciation (“suture zones” in Scandinavia and central Europe) Taberlet et al. 1998; Molecular Ecology 7:453

Human Phylogeography  Most evidence points to origins in Africa and subsequent migrations Cavalli-Sforza 2003 Nature Genetics 33:266

Human Phylogeography: mtDNA  Most ancient and diverse haplotypes in Africa (dots)  Migration and admixture is evident from presence of African haplotypes in other clades

Human Phylogeography: X-chromosome genes  Pyruvate dehydrogenase E1 alpha subunit sequence  25 polymorphic sites, 23 of which were in African sample  African θ=6.9, non-African θ=0.57  Using chimp sequence as outgroup, estimated that divergence occurred 1.9 million years ago

Complexities to Human Phylogeography  Some genes show evidence of Asian origin  Sequence of X-linked ribonucleotide reductase M2 pseudogene 4  Suggests single origin model is too simple: admixture and selection? Garrigan 2007 Nature Reviews Genetics 7:669

Evidence of Admixture in Ancient Eurasians Garrigan 2007 Nature Reviews Genetics 7:669

Evidence for Ancient Population Structure in Nuclear but not Mitochondrial Trees Garrigan 2007 Nature Reviews Genetics 7:669

Evidence for Ancient Population Structure in Nuclear but not Mitochondrial Trees Garrigan 2007 Nature Reviews Genetics 7:669

Alternative Models to Single Origin Garrigan 2007 Nature Reviews Genetics 7:669

Human Phylogeography with SNP  Assayed 500,000 SNP genotypes for 3,192 Europeans  Used Principal Components Analysis to ordinate samples in space  High correspondence betweeen sample ordination and geographic origin of samples  Individuals assigned to populations of origin with high accuracy

Nested Clade Analysis Combines spatial and temporal tests of association Can be used to distinguish ongoing population processes from historical events

D c – Clade distance (measures geographic range of a particular clade) D n – Nested clade distance (geographic relationship to other same level categories) I-T – average distance between interior and tip clades within nested group Branco et al 2002 Evolution 56:792–803 Use random permutation testing to test significance of associations

Templeton AR 1998 Molecular Ecology 7:

Nested Clade Analysis - critique and summary (reflections of a colleague) Hardly anyone believes in it anyway (ie Wayne Maddison is strongly against it, because it is too conjectural - not statistically sound) All you need to know is that people use it to make conclusions about range expansions and historical vicariant events, based on molecular data The method replies on this inference key, which ultimately tells you nothing in the end