can mathematicians find the woods?

Size: px
Start display at page:

Download "can mathematicians find the woods?"

Transcription

1 Eolutionary trees, coalescents, and gene trees: can mathematicians find the woods? Joe Felsenstein Department of Genome Sciences and Department of Biology Eolutionary trees, coalescents, and gene trees: p.1/51

2 Sketch in Darwin s notebook, 1842 Eolutionary trees, coalescents, and gene trees: p.2/51

3 The only figure in Darwin s book, 1859 Eolutionary trees, coalescents, and gene trees: p.3/51

4 Ernst Haeckel s tree, 1866 Eolutionary trees, coalescents, and gene trees: p.4/51

5 Simpson s tree of horses, 1940 s Eolutionary trees, coalescents, and gene trees: p.5/51

6 Eolution of characters along trees x 1 1 x 6 x x 3 3 x 4 4 x 8 x 5 5 x x 9 8 Characters are modeled (in simple cases) as changing by Marko processes along branches of the tree, according to graphical models like this. Eolutionary trees, coalescents, and gene trees: p.6/51

7 Eolution of characters along trees xx xxx xx xxx xx xxx xx xxx xx xxx xx xxx x 6 x 776 x 6 x 76 x xx xxx xx xxx With multiple characters (such as sites in DNA) sites are often assumed to change independently, so we hae stacked graphical models. Eolutionary trees, coalescents, and gene trees: p.7/51

8 A data example: mitochondrial D-loop sequences Eolutionary trees, coalescents, and gene trees: p.8/51

9 which gies the ML tree Chimp Human Orang Gorilla Gibbon ln L = Maximum likelihood tree for the Hasegawa 232-site mitochondrial D-loop data set, with Ts/Tn set to 2, analyzed with maximum likelihood (DNAML) Mouse Boine Eolutionary trees, coalescents, and gene trees: p.9/51

10 How many trees? Rooted, bifurcating, tips labelled species number of trees , , ,027, ,459, ,729, ,749,310, ,234,143, ,905,853,580, ,458,046,676, ,190,283,353,629, ,898,783,962,510, ,332,659,870,762,850, ,643,095,476,699,771, ,200,794,532,637,891,559, Eolutionary trees, coalescents, and gene trees: p.10/51

11 Tree space in a small case an example: three species with a clock A B C trifurcation t 1 t 2 t 1 not possible OK etc. t 2 when we consider all three possible topologies, the space looks like: t 1 t 2 Eolutionary trees, coalescents, and gene trees: p.11/51

12 Through the looking glass B A 1 C wall wall F D floor 9 E Eolutionary trees, coalescents, and gene trees: p.12/51

13 Nearest-neighbor interchanges B A 1 F C D E Eolutionary trees, coalescents, and gene trees: p.13/51

14 Nearest-neighbor interchanges B A 1 F C D E A 1 F 6 B D C E Eolutionary trees, coalescents, and gene trees: p.14/51

15 Nearest-neighbor interchanges B A 1 F C D A 1 F 6 7 B 2 3 C 8 4 D 9 5 E A 1 F 6 B E 5 4 D C E Eolutionary trees, coalescents, and gene trees: p.15/51

16 Nearest-neighbor interchanges B A 1 F C D E A 1 F 6 B E 5 4 D C A B C E F 6 4 D Eolutionary trees, coalescents, and gene trees: p.16/51

17 Nearest-neighbor interchanges B A 1 F C D A 1 F 6 7 B 2 3 C 8 4 D 9 5 E A 1 F 6 B E 5 4 D C A 1 F B C E E D Eolutionary trees, coalescents, and gene trees: p.17/51

18 The Schoenberg graph A C D B E A D B E C B C E D A A E B C D B A C D E B D C A E A B C D E A B C E D A B D C E A D B C E A C B D E C A B D E A E B D C A E C B D D A B E C Eolutionary trees, coalescents, and gene trees: p.18/51

19 Where does the true tree come from? (10 billion or so species) Model of random branching (with extinction too) Model of sampling of species by the biologist Models, Trees, and Data A E B DC model of eolution of characters along the tree Aligned DNA (or protein) sequences other sequences too A B C D E ggtca aactt gagtc aacat... ggtcc aagtt gagtc gacat... ggtca aactt gagtc aacat... ggtcc aactt gactc aatat... gctca aagtt gactc ttcat... Eolutionary trees, coalescents, and gene trees: p.19/51

20 Birth-and-death processes as priors? If they hae parameters (λ, µ), what are the priors on their alues? Eolutionary trees, coalescents, and gene trees: p.20/51

21 Birth-and-death processes as priors? If they hae parameters (λ, µ), what are the priors on their alues? How do we determine how long the BD process runs? Eolutionary trees, coalescents, and gene trees: p.20/51

22 Birth-and-death processes as priors? If they hae parameters (λ, µ), what are the priors on their alues? How do we determine how long the BD process runs? If the systematist selects species, how do we characterize that process? Eolutionary trees, coalescents, and gene trees: p.20/51

23 Birth-and-death processes as priors? If they hae parameters (λ, µ), what are the priors on their alues? How do we determine how long the BD process runs? If the systematist selects species, how do we characterize that process? How do we sample N species out of a huge tree-of-life? It s not so easy Eolutionary trees, coalescents, and gene trees: p.20/51

24 What has mathematics done for us? The analogy between recursion and trees Discoered many times, basis for dynamic programming algorithms for computing likelihoods and other similar quantities. Hadamard transform methods Hendy and Penny (1989) discoered that a Hadamard transform applied to a list of frequencies of occurrences of different patterns of character alues (at the tips of the tree) yield support for different splits in the tree. Inariants Caender and also Lake (both in 1987) initiated the exploration, not of tree space but of polynomial relationships between expected frequencies of occurrence of patterns of character alues. Related to the practice of algebraic statistics. Eolutionary trees, coalescents, and gene trees: p.21/51

25 The Hadamard Conjugation C D E B A 0.6 Tree 0.8 F 0 31 Partitions Hadamard Transform Conjugate Spectrum Eolutionary trees, coalescents, and gene trees: p.22/51

26 My ancestor? Charles the Great (Charlemagne) born 747 about 44 more generations Cornelia John Maud William Itzhak Jacob Helen Will Sheimdel Le Eleanor Jake Joe 1850s 1880s 1910s 1942 Eolutionary trees, coalescents, and gene trees: p.23/51

27 Chromosome 1, back up one lineage 6 (none) now Eolutionary trees, coalescents, and gene trees: p.24/51

28 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.25/51

29 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.26/51

30 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.27/51

31 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.28/51

32 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.29/51

33 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.30/51

34 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.31/51

35 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.32/51

36 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.33/51

37 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.34/51

38 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.35/51

39 Coalescent genealogy for one gene Time Eolutionary trees, coalescents, and gene trees: p.36/51

40 Untangling the crossed lines... Time Eolutionary trees, coalescents, and gene trees: p.37/51

41 Genealogy of a sample of 3 copies Time Eolutionary trees, coalescents, and gene trees: p.38/51

42 J. F. C. Kingman s (1982) coalescent 1. start with n tips 2. go back an amount of time( drawn from Exponential 3. join a random pair of the n 4. n n 1 5. if n = 1 stop, else go to step 2. ) 4N n(n 1) This excellently approximates the distribution of genealogies which arise from samples from a standard (Wright-Fisher) population genetics model with a population size of N, proided n 2 N Eolutionary trees, coalescents, and gene trees: p.39/51

43 A coalescent with migration among populations population 1 population 2 population 3 Eolutionary trees, coalescents, and gene trees: p.40/51

44 A coalescent with recombination Recomb. Different markers hae slightly different coalescent trees Eolutionary trees, coalescents, and gene trees: p.41/51

45 Coalescents for two genes locus A locus B both = recombination Eolutionary trees, coalescents, and gene trees: p.42/51

46 Species trees and trees of gene copies N 1 N 2 t 1 N 4 N 3 t 2 N 5 Eolutionary trees, coalescents, and gene trees: p.43/51

47 Species trees and trees of gene copies N 1 N 2 t 1 N 4 N 3 t 2 N 5 Eolutionary trees, coalescents, and gene trees: p.44/51

48 Species trees and trees of gene copies N 1 N 2 t 1 N 4 N 3 t 2 N 5 Eolutionary trees, coalescents, and gene trees: p.45/51

49 A gene duplication in a phylogeny Frog Human Monkey Squirrel a b a b a b species boundary gene duplication tree of genes Eolutionary trees, coalescents, and gene trees: p.46/51

50 If we just examine the tree of genes Frog Human Monkey Squirrel Human Monkey Squirrel a a a b b b These two trees should be identical Eolutionary trees, coalescents, and gene trees: p.47/51

51 A tree of hemoglobins (Morris Goodman, 1975) Eolutionary trees, coalescents, and gene trees: p.48/51

52 Highlighting the duplication eents Eolutionary trees, coalescents, and gene trees: p.49/51

53 References Billera, L. J., S. P. Holmes, and K. Vogtmann Geometry of the space of phylogenetic trees. Adances in Applied Mathematics 27: Chang, J. T Recent common ancestors of all present-day indiiduals. Adances in Applied Probability 31(4): Edwards, A. W. F. and L. L. Caalli-Sforza Reconstruction of eolutionary trees. pp in Phenetic and Phylogenetic Classification, ed. V. H. Heywood and J. McNeill. Systematics Association Publication No. 6. Systematics Association, London. [First paper on numerical methods for estimating phylogenies (from gene frequencies)] Felsenstein, J Inferring Phylogenies. Sinauer Associates, Sunderland, Massachusetts. [Book you and all your friends must rush out and buy] Semple, C. and M. A. Steel. Phylogenetics. Oxford Lecture Series in Mathematics and Its Applications. Oxford Uniersity Press, Oxford. Eolutionary trees, coalescents, and gene trees: p.50/51

54 How it was done This projection produced as a PDF and iewed using the Full Screen mode (in the View menu) of Adobe Acrobat Reader: I made my PDF using LaTeX (though Adobe Acrobat is another possibility): using the prosper style in LaTeX, using Latex to make a.di file, using dips to turn this into a Postscript file, using ps2pdf to make it into a PDF file, and displaying the slides in Adobe Acrobat Reader. Result: nice slides using freeware. Eolutionary trees, coalescents, and gene trees: p.51/51

Coalescents. Joe Felsenstein. GENOME 453, Autumn Coalescents p.1/48

Coalescents. Joe Felsenstein. GENOME 453, Autumn Coalescents p.1/48 Coalescents p.1/48 Coalescents Joe Felsenstein GENOME 453, Autumn 2015 Coalescents p.2/48 Cann, Stoneking, and Wilson Becky Cann Mark Stoneking the late Allan Wilson Cann, R. L., M. Stoneking, and A. C.

More information

Coalescents. Joe Felsenstein. GENOME 453, Winter Coalescents p.1/39

Coalescents. Joe Felsenstein. GENOME 453, Winter Coalescents p.1/39 Coalescents Joe Felsenstein GENOME 453, Winter 2007 Coalescents p.1/39 Cann, Stoneking, and Wilson Becky Cann Mark Stoneking the late Allan Wilson Cann, R. L., M. Stoneking, and A. C. Wilson. 1987. Mitochondrial

More information

Mitochondrial Eve and Y-chromosome Adam: Who do your genes come from?

Mitochondrial Eve and Y-chromosome Adam: Who do your genes come from? Mitochondrial Eve and Y-chromosome Adam: Who do your genes come from? 28 July 2010. Joe Felsenstein Evening At The Genome Mitochondrial Eve and Y-chromosome Adam: Who do your genes come from? p.1/39 Evolutionary

More information

Lecture 2. Tree space and searching tree space

Lecture 2. Tree space and searching tree space Lecture 2. Tree space and searching tree space Joe Felsenstein epartment of Genome Sciences and epartment of iology Lecture 2. Tree space and searching tree space p.1/48 Orang Gorilla himp Human Gibbon

More information

Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks!

Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks! Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks! Paul has many great tools for teaching phylogenetics at his web site: http://hydrodictyon.eeb.uconn.edu/people/plewis

More information

Comparative method, coalescents, and the future

Comparative method, coalescents, and the future Comparative method, coalescents, and the future Joe Felsenstein Depts. of Genome Sciences and of Biology, University of Washington Comparative method, coalescents, and the future p.1/36 Correlation of

More information

Evolutionary trees and population genetics: a family reunion

Evolutionary trees and population genetics: a family reunion Evolutionary trees and population genetics: a family reunion 9 October 2009. Joe Felsenstein 500th anniversary (or something) of the University of Chicago Evolutionary trees and population genetics: a

More information

Comparative method, coalescents, and the future. Correlation of states in a discrete-state model

Comparative method, coalescents, and the future. Correlation of states in a discrete-state model Comparative method, coalescents, and the future Joe Felsenstein Depts. of Genome Sciences and of Biology, University of Washington Comparative method, coalescents, and the future p.1/28 Correlation of

More information

Lecture 30. Phylogeny methods, part 2 (Searching tree space) p.1/22

Lecture 30. Phylogeny methods, part 2 (Searching tree space) p.1/22 Lecture 30. Phylogeny methods, part 2 (Searching tree space) Joe elsenstein epartment of Genome Sciences and epartment of iology Lecture 30. Phylogeny methods, part 2 (Searching tree space) p.1/22 ll possible

More information

Algorithms for Genetics: Basics of Wright Fisher Model and Coalescent Theory

Algorithms for Genetics: Basics of Wright Fisher Model and Coalescent Theory Algorithms for Genetics: Basics of Wright Fisher Model and Coalescent Theory Vineet Bafna Harish Nagarajan and Nitin Udpa 1 Disclaimer Please note that a lot of the text and figures here are copied from

More information

Coalescent Theory: An Introduction for Phylogenetics

Coalescent Theory: An Introduction for Phylogenetics Coalescent Theory: An Introduction for Phylogenetics Laura Salter Kubatko Departments of Statistics and Evolution, Ecology, and Organismal Biology The Ohio State University lkubatko@stat.ohio-state.edu

More information

Population Structure and Genealogies

Population Structure and Genealogies Population Structure and Genealogies One of the key properties of Kingman s coalescent is that each pair of lineages is equally likely to coalesce whenever a coalescent event occurs. This condition is

More information

Population Genetics using Trees. Peter Beerli Genome Sciences University of Washington Seattle WA

Population Genetics using Trees. Peter Beerli Genome Sciences University of Washington Seattle WA Population Genetics using Trees Peter Beerli Genome Sciences University of Washington Seattle WA Outline 1. Introduction to the basic coalescent Population models The coalescent Likelihood estimation of

More information

Coalescence. Outline History. History, Model, and Application. Coalescence. The Model. Application

Coalescence. Outline History. History, Model, and Application. Coalescence. The Model. Application Coalescence History, Model, and Application Outline History Origins of theory/approach Trace the incorporation of other s ideas Coalescence Definition and descriptions The Model Assumptions and Uses Application

More information

Population genetics: Coalescence theory II

Population genetics: Coalescence theory II Population genetics: Coalescence theory II Peter Beerli August 27, 2009 1 The variance of the coalescence process The coalescent is an accumulation of waiting times. We can think of it as standard queuing

More information

Analysis of geographically structured populations: Estimators based on coalescence

Analysis of geographically structured populations: Estimators based on coalescence Analysis of geographically structured populations: Estimators based on coalescence Peter Beerli Department of Genetics, Box 357360, University of Washington, Seattle WA 9895-7360, Email: beerli@genetics.washington.edu

More information

Genealogical trees, coalescent theory, and the analysis of genetic polymorphisms

Genealogical trees, coalescent theory, and the analysis of genetic polymorphisms Genealogical trees, coalescent theory, and the analysis of genetic polymorphisms Magnus Nordborg University of Southern California The importance of history Genetic polymorphism data represent the outcome

More information

Frequent Inconsistency of Parsimony Under a Simple Model of Cladogenesis

Frequent Inconsistency of Parsimony Under a Simple Model of Cladogenesis Syst. Biol. 52(5):641 648, 2003 Copyright c Society of Systematic Biologists ISSN: 1063-5157 print / 1076-836X online DOI: 10.1080/10635150390235467 Frequent Inconsistency of Parsimony Under a Simple Model

More information

2 The Wright-Fisher model and the neutral theory

2 The Wright-Fisher model and the neutral theory 0 THE WRIGHT-FISHER MODEL AND THE NEUTRAL THEORY The Wright-Fisher model and the neutral theory Although the main interest of population genetics is conceivably in natural selection, we will first assume

More information

Viral epidemiology and the Coalescent

Viral epidemiology and the Coalescent Viral epidemiology and the Coalescent Philippe Lemey and Marc A. Suchard Department of Microbiology and Immunology K.U. Leuven, and Departments of Biomathematics and Human Genetics David Geffen School

More information

The genealogical history of a population The coalescent process. Identity by descent Distribution of pairwise coalescence times

The genealogical history of a population The coalescent process. Identity by descent Distribution of pairwise coalescence times The coalescent The genealogical history of a population The coalescent process Identity by descent Distribution of pairwise coalescence times Adding mutations Expected pairwise differences Evolutionary

More information

Forward thinking: the predictive approach

Forward thinking: the predictive approach Coalescent Theory 1 Forward thinking: the predictive approach Random variation in reproduction causes random fluctuation in allele frequencies. Can describe this process as diffusion: (Wright 1931) showed

More information

TREES OF GENES IN POPULATIONS

TREES OF GENES IN POPULATIONS 1 TREES OF GENES IN POPULATIONS Joseph Felsenstein Abstract Trees of ancestry of copies of genes form in populations, as a result of the randomness of birth, death, and Mendelian reproduction. Considering

More information

Ancestral Recombination Graphs

Ancestral Recombination Graphs Ancestral Recombination Graphs Ancestral relationships among a sample of recombining sequences usually cannot be accurately described by just a single genealogy. Linked sites will have similar, but not

More information

Bioinformatics I, WS 14/15, D. Huson, December 15,

Bioinformatics I, WS 14/15, D. Huson, December 15, Bioinformatics I, WS 4/5, D. Huson, December 5, 204 07 7 Introduction to Population Genetics This chapter is closely based on a tutorial given by Stephan Schiffels (currently Sanger Institute) at the Australian

More information

Parsimony II Search Algorithms

Parsimony II Search Algorithms Parsimony II Search Algorithms Genome 373 Genomic Informatics Elhanan Borenstein Raw distance correction As two DNA sequences diverge, it is easy to see that their maximum raw distance is ~0.75 (assuming

More information

Coalescence time distributions for hypothesis testing -Kapil Rajaraman 498BIN, HW# 2

Coalescence time distributions for hypothesis testing -Kapil Rajaraman 498BIN, HW# 2 Coalescence time distributions for hypothesis testing -Kapil Rajaraman (rajaramn@uiuc.edu) 498BIN, HW# 2 This essay will be an overview of Maryellen Ruvolo s work on studying modern human origins using

More information

Biology 559R: Introduction to Phylogenetic Comparative Methods Topics for this week (Feb 3 & 5):

Biology 559R: Introduction to Phylogenetic Comparative Methods Topics for this week (Feb 3 & 5): Biology 559R: Introduction to Phylogenetic Comparative Methods Topics for this week (Feb 3 & 5): Chronogram estimation: Penalized Likelihood Approach BEAST Presentations of your projects 1 The Anatomy

More information

Chapter 12 Gene Genealogies

Chapter 12 Gene Genealogies Chapter 12 Gene Genealogies Noah A. Rosenberg Program in Molecular and Computational Biology. University of Southern California, Los Angeles, California 90089-1113 USA. E-mail: noahr@usc.edu. Phone: 213-740-2416.

More information

Recap: Properties of Trees. Rooting an unrooted tree. Questions trees can address: Data for phylogeny reconstruction. Rooted vs unrooted trees:

Recap: Properties of Trees. Rooting an unrooted tree. Questions trees can address: Data for phylogeny reconstruction. Rooted vs unrooted trees: Pairwise sequence alignment (global and local) Recap: Properties of rees Multiple sequence alignment global local ubstitution matrices atabase ing L equence statistics Leaf nodes contemporary taxa Internal

More information

Pedigree Reconstruction using Identity by Descent

Pedigree Reconstruction using Identity by Descent Pedigree Reconstruction using Identity by Descent Bonnie Kirkpatrick Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2010-43 http://www.eecs.berkeley.edu/pubs/techrpts/2010/eecs-2010-43.html

More information

Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling

Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling Mary K. Kuhner, Jon Yamato, and Joseph Felsenstein Department of Genetics, University of Washington

More information

MOLECULAR POPULATION GENETICS: COALESCENT METHODS BASED ON SUMMARY STATISTICS

MOLECULAR POPULATION GENETICS: COALESCENT METHODS BASED ON SUMMARY STATISTICS MOLECULAR POPULATION GENETICS: COALESCENT METHODS BASED ON SUMMARY STATISTICS Daniel A. Vasco*, Keith A. Crandall* and Yun-Xin Fu *Department of Zoology, Brigham Young University, Provo, UT 8460, USA Human

More information

arxiv: v1 [q-bio.pe] 4 Mar 2013

arxiv: v1 [q-bio.pe] 4 Mar 2013 Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees arxiv:1303.0673v1 [q-bio.pe] 4 Mar 2013 Sha Zhu 1,, James H Degnan 2 and Bjarki Eldon 3 1

More information

Project. B) Building the PWM Read the instructions of HO_14. 1) Determine all the 9-mers and list them here:

Project. B) Building the PWM Read the instructions of HO_14. 1) Determine all the 9-mers and list them here: Project Please choose ONE project among the given five projects. The last three projects are programming projects. hoose any programming language you want. Note that you can also write programs for the

More information

Bootstraps and testing trees

Bootstraps and testing trees ootstraps and testing trees Joe elsenstein epts. of Genome Sciences and of iology, University of Washington ootstraps and testing trees p.1/20 ln L log-likelihood curve and its confidence interval 2620

More information

Kinship and Population Subdivision

Kinship and Population Subdivision Kinship and Population Subdivision Henry Harpending University of Utah The coefficient of kinship between two diploid organisms describes their overall genetic similarity to each other relative to some

More information

Ioanna Manolopoulou and Brent C. Emerson. October 7, Abstract

Ioanna Manolopoulou and Brent C. Emerson. October 7, Abstract Phylogeographic Ancestral Inference Using the Coalescent Model on Haplotype Trees Ioanna Manolopoulou and Brent C. Emerson October 7, 2011 Abstract Phylogeographic ancestral inference is a question frequently

More information

POPULATION GENETICS: WRIGHT FISHER MODEL AND COALESCENT PROCESS. Hailong Cui and Wangshu Zhang. Superviser: Prof. Quentin Berger

POPULATION GENETICS: WRIGHT FISHER MODEL AND COALESCENT PROCESS. Hailong Cui and Wangshu Zhang. Superviser: Prof. Quentin Berger POPULATIO GEETICS: WRIGHT FISHER MODEL AD COALESCET PROCESS by Hailong Cui and Wangshu Zhang Superviser: Prof. Quentin Berger A Final Project Report Presented In Partial Fulfillment of the Requirements

More information

Warning: software often displays unrooted trees like this:

Warning: software often displays unrooted trees like this: Warning: software often displays unrooted trees like this: /------------------------------ Chara /-------------------------- Chlorella /---------16 \---------------------------- Volvox +-------------------17

More information

Full Length Research Article

Full Length Research Article Full Length Research Article ON THE EXTINCTION PROBABILITY OF A FAMILY NAME *DZAAN, S. K 1., ONAH, E. S 2. & KIMBIR, A. R 2. 1 Department of Mathematics and Computer Science University of Mkar, Gboko Nigeria.

More information

Human origins and analysis of mitochondrial DNA sequences

Human origins and analysis of mitochondrial DNA sequences Human origins and analysis of mitochondrial DNA sequences Science, February 7, 1992 L. Vigilant et al. [1] recently presented "the strongest support yet for the placement of [their] common mtdna [mitochondrial

More information

Tópicos Depto. Ciencias Biológicas, UniAndes Profesor Andrew J. Crawford Semestre II

Tópicos Depto. Ciencias Biológicas, UniAndes Profesor Andrew J. Crawford Semestre II Tópicos Depto. Ciencias Biológicas, UniAndes Profesor Andrew J. Crawford Semestre 29 -II Lab Coalescent simulation using SIMCOAL 17 septiembre 29 Coalescent theory provides a powerful model

More information

6.047/6.878 Lecture 21: Phylogenomics II

6.047/6.878 Lecture 21: Phylogenomics II Guest Lecture by Matt Rasmussen Orit Giguzinsky and Ethan Sherbondy December 13, 2012 1 Contents 1 Introduction 3 2 Inferring Orthologs/Paralogs, Gene Duplication and Loss 3 2.1 Species Tree..............................................

More information

Evaluating the performance of likelihood methods for. detecting population structure and migration

Evaluating the performance of likelihood methods for. detecting population structure and migration Molecular Ecology (2004) 13, 837 851 doi: 10.1111/j.1365-294X.2004.02132.x Evaluating the performance of likelihood methods for Blackwell Publishing, Ltd. detecting population structure and migration ZAID

More information

Your mtdna Full Sequence Results

Your mtdna Full Sequence Results Congratulations! You are one of the first to have your entire mitochondrial DNA (DNA) sequenced! Testing the full sequence has already become the standard practice used by researchers studying the DNA,

More information

The African Origin Hypothesis What do the data tell us?

The African Origin Hypothesis What do the data tell us? The African Origin Hypothesis What do the data tell us? Mitochondrial DNA and Human Evolution Cann, Stoneking and Wilson, Nature 1987. WOS - 1079 citations Mitochondrial DNA and Human Evolution Cann, Stoneking

More information

Part I. Concepts and Methods in Bacterial Population Genetics COPYRIGHTED MATERIAL

Part I. Concepts and Methods in Bacterial Population Genetics COPYRIGHTED MATERIAL Part I Concepts and Methods in Bacterial Population Genetics COPYRIGHTED MATERIAL Chapter 1 The Coalescent of Bacterial Populations Mikkel H. Schierup and Carsten Wiuf 1.1 BACKGROUND AND MOTIVATION Recent

More information

GENEALOGICAL TREES, COALESCENT THEORY AND THE ANALYSIS OF GENETIC POLYMORPHISMS

GENEALOGICAL TREES, COALESCENT THEORY AND THE ANALYSIS OF GENETIC POLYMORPHISMS GENEALOGICAL TREES, COALESCENT THEORY AND THE ANALYSIS OF GENETIC POLYMORPHISMS Noah A. Rosenberg and Magnus Nordborg Improvements in genotyping technologies have led to the increased use of genetic polymorphism

More information

BIOL Evolution. Lecture 8

BIOL Evolution. Lecture 8 BIOL 432 - Evolution Lecture 8 Expected Genotype Frequencies in the Absence of Evolution are Determined by the Hardy-Weinberg Equation. Assumptions: 1) No mutation 2) Random mating 3) Infinite population

More information

Bioinformatics for Evolutionary Biologists

Bioinformatics for Evolutionary Biologists Bioinformatics for Evolutionary Biologists Bernhard Haubold Angelika Börsch-Haubold Bioinformatics for Evolutionary Biologists A Problems Approach 123 Bernhard Haubold Department of Evolutionary Genetics

More information

DISCUSSION: RECENT COMMON ANCESTORS OF ALL PRESENT-DAY INDIVIDUALS

DISCUSSION: RECENT COMMON ANCESTORS OF ALL PRESENT-DAY INDIVIDUALS Adv. Appl. Prob. 31, 1027 1035 (1999) Printed in Northern Ireland Applied Probability Trust 1999 DISCUSSION: RECENT COMMON ANCESTORS OF ALL PRESENT-DAY INDIVIDUALS It is a pleasure to be able to comment

More information

5 Inferring Population

5 Inferring Population 5 Inferring Population History and Demography While population genetics was a very theoretical discipline originally, the modern abundance of population genetic data has forced the field to become more

More information

A Likelihood Method to Estimate/Detect Gene Flow and A Distance Method to. Estimate Species Trees in the Presence of Gene Flow.

A Likelihood Method to Estimate/Detect Gene Flow and A Distance Method to. Estimate Species Trees in the Presence of Gene Flow. A Likelihood Method to Estimate/Detect Gene Flow and A Distance Method to Estimate Species Trees in the Presence of Gene Flow Thesis Presented in Partial Fulfillment of the Requirements for the Degree

More information

Do You Understand Evolutionary Trees? By T. Ryan Gregory

Do You Understand Evolutionary Trees? By T. Ryan Gregory Do You Understand Evolutionary Trees? By T. Ryan Gregory A single figure graces the pages of Charles Darwin's groundbreaking work On the Origin of Species, first published in 1859. The figure in question

More information

Coalescent Theory. Magnus Nordborg. Department of Genetics, Lund University. March 24, 2000

Coalescent Theory. Magnus Nordborg. Department of Genetics, Lund University. March 24, 2000 Coalescent Theory Magnus Nordborg Department of Genetics, Lund University March 24, 2000 Abstract The coalescent process is a powerful modeling tool for population genetics. The allelic states of all homologous

More information

Estimating Effective Population Size and Mutation Rate From Sequence Data Using Metropolis-Hastings Sampling

Estimating Effective Population Size and Mutation Rate From Sequence Data Using Metropolis-Hastings Sampling Copyright 0 1995 by the Genetics Society of America Estimating Effective Population Size and Mutation Rate From Sequence Data Using Metropolis-Hastings Sampling Mary K. Kuhner, Jon Yarnato and Joseph Felsenstein

More information

STAT 536: The Coalescent

STAT 536: The Coalescent STAT 536: The Coalescent Karin S. Dorman Department of Statistics Iowa State University November 7, 2006 Wright-Fisher Model Our old friend the Wright-Fisher model envisions populations moving forward

More information

Introduction to Biosystematics - Zool 575

Introduction to Biosystematics - Zool 575 Introduction to Biosystematics Lecture 21-1. Introduction to maximum likelihood - synopsis of how it works - likelihood of a single sequence - likelihood across a single branch - likelihood as branch length

More information

Origin of Species: Starting the Story with DNA

Origin of Species: Starting the Story with DNA Tested Studies for Laboratory Teaching Proceedings of the Association for Biology Laboratory Education Vol. 32, 88 103, 2011 Origin of Species: Starting the Story with DNA Robert B. Ketcham Department

More information

DNA Opening Doors for Today s s Genealogist

DNA Opening Doors for Today s s Genealogist DNA Opening Doors for Today s s Genealogist Presented to JGSI Sunday, March 30, 2008 Presented by Alvin Holtzman Genetic Genealogy Discussion Points What is DNA How can it help genealogists What to expect

More information

DAR POLICY STATEMENT AND BACKGROUND Using DNA Evidence for DAR Applications

DAR POLICY STATEMENT AND BACKGROUND Using DNA Evidence for DAR Applications Effective January 1, 2014, DAR will begin accepting Y-DNA evidence in support of new member applications and supplemental applications as one element in a structured analysis. This analysis will use a

More information

Theoretical Population Biology. An approximate likelihood for genetic data under a model with recombination and population splitting

Theoretical Population Biology. An approximate likelihood for genetic data under a model with recombination and population splitting Theoretical Population Biology 75 (2009) 33 345 Contents lists available at ScienceDirect Theoretical Population Biology journal homepage: www.elsevier.com/locate/tpb An approximate likelihood for genetic

More information

Phylogeny and Molecular Evolution

Phylogeny and Molecular Evolution Phylogeny and Molecular Evolution Character Based Phylogeny Large Parsimony 1/50 Credit Ron Shamir s lecture notes Notes by Nir Friedman Dan Geiger, Shlomo Moran, Sagi Snir and Ron Shamir Durbin et al.

More information

DNA Testing. February 16, 2018

DNA Testing. February 16, 2018 DNA Testing February 16, 2018 What Is DNA? Double helix ladder structure where the rungs are molecules called nucleotides or bases. DNA contains only four of these nucleotides A, G, C, T The sequence that

More information

The Structure of Genealogies and the Distribution of Fixed Differences Between DNA Sequence Samples From Natural Populations

The Structure of Genealogies and the Distribution of Fixed Differences Between DNA Sequence Samples From Natural Populations Copyright 0 1991 by the Genetics Society of America The Structure of Genealogies the Distribution of Fixed Differences Between DNA Sequence Samples From Natural Populations Department of Biological Sciences,

More information

An Introduction. Your DNA. and Your Family Tree. (Mitochondrial DNA) Presentation by: 4/8/17 Page 1 of 10

An Introduction. Your DNA. and Your Family Tree. (Mitochondrial DNA) Presentation by: 4/8/17 Page 1 of 10 An Introduction Your DNA and Your Family Tree (Mitochondrial DNA) Presentation by: FredCoffey@aol.com 4/8/17 Page 1 of 10 Coffey Surname, y-dna Project We're now ready to move on and look at the type of

More information

Exploring the Demographic History of DNA Sequences Using the Generalized Skyline Plot

Exploring the Demographic History of DNA Sequences Using the Generalized Skyline Plot Exploring the Demographic History of DNA Sequences Using the Generalized Syline Plot Korbinian Strimmer and Oliver G. Pybus Department of Zoology, University of Oxford We present an intuitive visual framewor,

More information

Research Article The Ancestry of Genetic Segments

Research Article The Ancestry of Genetic Segments International Scholarly Research Network ISRN Biomathematics Volume 2012, Article ID 384275, 8 pages doi:105402/2012/384275 Research Article The Ancestry of Genetic Segments R B Campbell Department of

More information

Systematics - BIO 615

Systematics - BIO 615 Outline 1. Optimality riteria: Parsimony continued 2. istance vs character methods 3. uilding a tree vs finding a tree - lustering vs Optimality criterion methods 4. Performance of istance and clustering

More information

Approximating the coalescent with recombination

Approximating the coalescent with recombination Approximating the coalescent with recombination Gilean A. T. McVean* and Niall J. Cardin 360, 1387 1393 doi:10.1098/rstb.2005.1673 Published online 7 July 2005 Department of Statistics, 1 South Parks Road,

More information

Where do evolutionary trees comes from?

Where do evolutionary trees comes from? Probabilistic models of evolutionary trees Joint work with Outline of talk Part 1: History, overview Part 2: Discrete models of tree shape Part 3: Continuous trees Part 4: Applications: phylogenetic diversity,

More information

SSB Debate: Model-based Inference vs. Machine Learning

SSB Debate: Model-based Inference vs. Machine Learning SSB Debate: Model-based nference vs. Machine Learning June 3, 2018 SSB 2018 June 3, 2018 1 / 20 Machine learning in the biological sciences SSB 2018 June 3, 2018 2 / 20 Machine learning in the biological

More information

Walter Steets Houston Genealogical Forum DNA Interest Group January 6, 2018

Walter Steets Houston Genealogical Forum DNA Interest Group January 6, 2018 DNA, Ancestry, and Your Genealogical Research- Segments and centimorgans Walter Steets Houston Genealogical Forum DNA Interest Group January 6, 2018 1 Today s agenda Brief review of previous DIG session

More information

Using Mitochondrial DNA (mtdna) for Genealogy Debbie Parker Wayne, CG, CGL SM

Using Mitochondrial DNA (mtdna) for Genealogy Debbie Parker Wayne, CG, CGL SM Using Mitochondrial DNA (mtdna) for Genealogy Debbie Parker Wayne, CG, CGL SM This is one article of a series on using DNA for genealogical research. There are several types of DNA tests offered for genealogical

More information

[CLIENT] SmithDNA1701 DE January 2017

[CLIENT] SmithDNA1701 DE January 2017 [CLIENT] SmithDNA1701 DE1704205 11 January 2017 DNA Discovery Plan GOAL Create a research plan to determine how the client s DNA results relate to his family tree as currently constructed. The client s

More information

Common ancestors of all humans

Common ancestors of all humans Definitions Skip the methodology and jump down the page to the Conclusion Discussion CAs using Genetics CAs using Archaeology CAs using Mathematical models CAs using Computer simulations Recent news Mark

More information

Estimating Ancient Population Sizes using the Coalescent with Recombination

Estimating Ancient Population Sizes using the Coalescent with Recombination Estimating Ancient Population Sizes using the Coalescent with Recombination Sara Sheehan joint work with Kelley Harris and Yun S. Song May 26, 2012 Sheehan, Harris, Song May 26, 2012 1 Motivation Introduction

More information

Contributed by "Kathy Hallett"

Contributed by Kathy Hallett National Geographic: The Genographic Project Name Background The National Geographic Society is undertaking the ambitious process of tracking human migration using genetic technology. By using the latest

More information

Yoder Doors Opened by DNA Studies

Yoder Doors Opened by DNA Studies Yoder Doors Opened by DNA Studies A Special Report to the 2012 North Carolina Yoder Reunion By Chris Yoder Yoder Newsletter Oct. 2012 www.yodernewsletter.org Established 1983 BACKGROUND How DNA Testing

More information

Statistics, Probability and Noise

Statistics, Probability and Noise Statistics, Probability and Noise Claudia Feregrino-Uribe & Alicia Morales-Reyes Original material: Rene Cumplido Autumn 2015, CCC-INAOE Contents Signal and graph terminology Mean and standard deviation

More information

Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore

Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore Activitydevelop U SING GENETIC MARKERS TO CREATE L INEAGES How do

More information

The Coalescent Model. Florian Weber

The Coalescent Model. Florian Weber The Coalescent Model Florian Weber 23. 7. 2016 The Coalescent Model coalescent = zusammenwachsend Outline Population Genetics and the Wright-Fisher-model The Coalescent on-constant population-sizes Further

More information

Simulated gene genealogy of a sample of size 50 from a population of constant size. The History of Population Size from Whole Genomes.

Simulated gene genealogy of a sample of size 50 from a population of constant size. The History of Population Size from Whole Genomes. Simulated gene genealogy of a sample of size 50 from a population of constant size The History of Population Size from Whole Genomes Alan R Rogers October 1, 2018 Short terminal branches; long basal ones

More information

Growing the Family Tree: The Power of DNA in Reconstructing Family Relationships

Growing the Family Tree: The Power of DNA in Reconstructing Family Relationships Growing the Family Tree: The Power of DNA in Reconstructing Family Relationships Luke A. D. Hutchison Natalie M. Myres Scott R. Woodward Sorenson Molecular Genealogy Foundation (www.smgf.org) 2511 South

More information

Coalescent Likelihood Methods. Mary K. Kuhner Genome Sciences University of Washington Seattle WA

Coalescent Likelihood Methods. Mary K. Kuhner Genome Sciences University of Washington Seattle WA Coalescent Likelihood Methods Mary K. Kuhner Genome Sciences University of Washington Seattle WA Outline 1. Introduction to coalescent theory 2. Practical example 3. Genealogy samplers 4. Break 5. Survey

More information

The Coalescent. Chapter Population Genetic Models

The Coalescent. Chapter Population Genetic Models Chapter 3 The Coalescent To coalesce means to grow together, to join, or to fuse. When two copies of a gene are descended from a common ancestor which gave rise to them in some past generation, looking

More information

The Two Phases of the Coalescent and Fixation Processes

The Two Phases of the Coalescent and Fixation Processes The Two Phases of the Coalescent and Fixation Processes Introduction The coalescent process which traces back the current population to a common ancestor and the fixation process which follows an individual

More information

Meek DNA Project Group B Ancestral Signature

Meek DNA Project Group B Ancestral Signature Meek DNA Project Group B Ancestral Signature The purpose of this paper is to explore the method and logic used by the author in establishing the Y-DNA ancestral signature for The Meek DNA Project Group

More information

The Contest Between Parsimony and Likelihood. Elliott Sober*

The Contest Between Parsimony and Likelihood. Elliott Sober* The Contest Between Parsimony and Likelihood Elliott Sober* Two of the main methods that biologists now use to infer phylogenetic relationships are maximum likelihood and maximum parsimony. The method

More information

Using Y-DNA for Genealogy Debbie Parker Wayne, CG, CGL SM

Using Y-DNA for Genealogy Debbie Parker Wayne, CG, CGL SM Using Y-DNA for Genealogy Debbie Parker Wayne, CG, CGL SM This is one article of a series on using DNA for genealogical research. There are several types of DNA tests offered for genealogical purposes.

More information

MODERN population genetics is data driven and

MODERN population genetics is data driven and Copyright Ó 2009 by the Genetics Society of America DOI: 10.1534/genetics.108.092460 Note Extensions of the Coalescent Effective Population Size John Wakeley 1 and Ori Sargsyan Department of Organismic

More information

Introduction to Autosomal DNA Tools

Introduction to Autosomal DNA Tools GENETIC GENEALOGY JOURNEY Debbie Parker Wayne, CG, CGL Introduction to Autosomal DNA Tools Just as in the old joke about a new genealogist walking into the library and asking for the book that covers my

More information

Walter Steets Houston Genealogical Forum DNA Interest Group April 7, 2018

Walter Steets Houston Genealogical Forum DNA Interest Group April 7, 2018 Ancestry DNA and GEDmatch Walter Steets Houston Genealogical Forum DNA Interest Group April 7, 2018 Today s agenda Recent News about DNA Testing DNA Cautions: DNA Data Used for Forensic Purposes New Technology:

More information

17. Symmetries. Thus, the example above corresponds to the matrix: We shall now look at how permutations relate to trees.

17. Symmetries. Thus, the example above corresponds to the matrix: We shall now look at how permutations relate to trees. 7 Symmetries 7 Permutations A permutation of a set is a reordering of its elements Another way to look at it is as a function Φ that takes as its argument a set of natural numbers of the form {, 2,, n}

More information

Using Autosomal DNA for Genealogy Debbie Parker Wayne, CG, CGL SM

Using Autosomal DNA for Genealogy Debbie Parker Wayne, CG, CGL SM Using Autosomal DNA for Genealogy Debbie Parker Wayne, CG, CGL SM This is one article of a series on using DNA for genealogical research. There are several types of DNA tests offered for genealogical purposes.

More information

CONGEN. Inbreeding vocabulary

CONGEN. Inbreeding vocabulary CONGEN Inbreeding vocabulary Inbreeding Mating between relatives. Inbreeding depression Reduction in fitness due to inbreeding. Identical by descent Alleles that are identical by descent are direct descendents

More information

PHYLOGEOGRAPHIC BREAKS WITHOUT GEOGRAPHIC BARRIERS TO GENE FLOW

PHYLOGEOGRAPHIC BREAKS WITHOUT GEOGRAPHIC BARRIERS TO GENE FLOW Evolution, 56(1), 00, pp. 383 394 PHYLOGEOGRAPHIC BREAKS WITHOUT GEOGRAPHIC BARRIERS TO GENE FLOW DARREN E. IRWIN 1 Section for Animal Ecology, Department of Ecology, Lund University, S-3 6 Lund, Sweden

More information

Big Y-700 White Paper

Big Y-700 White Paper Big Y-700 White Paper Powering discovery in the field of paternal ancestry Authors: Caleb Davis, Michael Sager, Göran Runfeldt, Elliott Greenspan, Arjan Bormans, Bennett Greenspan, and Connie Bormans Last

More information

How good is simple reversal sort? Cycle decompositions. Cycle decompositions. Estimating reversal distance by cycle decomposition

How good is simple reversal sort? Cycle decompositions. Cycle decompositions. Estimating reversal distance by cycle decomposition How good is simple reversal sort? p Not so good actually p It has to do at most n-1 reversals with permutation of length n p The algorithm can return a distance that is as large as (n 1)/2 times the correct

More information