1. Lecture 14: Population Assignment and Individual Identity October 8, 2015

2. Last Time uSample calculation of F ST uDefining populations on genetic criteria: introduction to Structure

3. Structure Program  One of the most widely-used programs in population genetics (original paper cited >15,000 times since 2000)  Very flexible model can determine:  The most likely number of uniform groups (populations, K)  The genomic composition of each individual (admixture coefficients)  Possible population of origin

4. Structure is Hierarchical: Groups reveal more substructure when examined separately Rosenberg et al. 2002 Science 298: 2381-2385

5. Today  Principal Components Analysis  Genotype likelihoods  Population assignment  Forensic identification

6. Alternative clustering method: Principal Components Analysis  Structure is very computationally intensive  Often no clear best-supported K-value  Alternative is to use traditional multivariate statistics to find uniform groups  Principal Components Analysis is most commonly used algorithm  EIGENSOFT (PCA, Patterson et al., 2006; PloS Genetics 2:e190). Eckert, Population Structure, 5-Aug-2008 49

7. Principal Components Analysis  Efficient way to summarize multivariate data like genotypes  Each axis passes through maximum variation in data, explains a component of the variation  http://www.mech.uq.edu.au/courses/mech 4710/pca/s1.htm

8. Once you have populations defined, can you assign a migrant individual to their population of origin?

9. Human Population Assignment 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  Novembre et al. 2008 Nature 456:98

10. Population Assignment: Likelihood  Assume you find skin cells and blood under fingernails of a murder victim  Victim had major debts with the Sicilian mafia as well as the Chinese mafia  Can population assignment help to focus investigation?  What is H 1 and what is H 2 ?

11. Population Assignment: Likelihood  "Assignment Tests" based on allele frequencies in source populations and genetic composition of individuals  Likelihood-Based Approaches  Calculate likelihood that individual genotype originated in particular population  Assume Hardy-Weinberg and linkage equilibria  Genotype frequencies corrected for presence of sampled individual  Usually reported as log 10 likelihood for origin in given population relative to other population  Implemented in ‘GENECLASS’ program (http://www.montpellier.inra.fr/URLB/geneclass/g eneclass.html) for m loci for homozygote A i A i in population l at locus k for heterozygote A i A j in population l at locus k

12. Power of Population Assignment using Likelihood  Assignment success depends on:  Number of markers used  Polymorphism of markers  Number of possible source populations  Differentiation of populations  Accuracy of allele frequency estimations  Rules of Thumb (Cornuet et al. 1999) for 100% assignment success, for 10 reference populations need:  30 to 50 reference individuals per population  10 microsatellite loci  HE > 0.6  FST > 0.1

13. Population Assignment Example: A Fish Story  Fishing competition on Lake Saimaa in Southeast Finland  Contestant allegedly caught a 5.5 kg salmon, much larger than usual for the lake  Compared fish from the lake to fish from local markets (originating from Norway and Baltic sea)  7 microsatellites  Based on likelihood analysis, fish was purchased rather than caught in lake Lake Saimaa Market - -log 10 of likelihood that the observed genotype could occur in Lake Saimaa

14. Genetic Typing in Forensics  Highly polymorphic loci provide unique ‘fingerprint’ for each individual  Tie suspects to blood stains, semen, skin cells, hair  Revolutionized criminal justice in last 20 years  Also used in disasters and forensic anthropology  Principles of population genetics must be applied in calculating and interpreting probability of identity

15. Markers in Genetic Typing  Standard set of 13 core loci for forensics: CODIS (Combined DNA Index System)  Sets of highly polymorphic microsatellites (also called VNTR (Variable Number of Tandem Repeats), STR (Short Tandem Repeat) or SSR (Simple Sequence Repeat))  Most are amplified in a single multiplex reaction and analyzed in a single capillary  Very high “exclusion power” (ability to differentiate individuals) http://www.cstl.nist.gov/div831/strbase//mlt_abiid.htm

16. Individual Identity: Likelihood  Assume you find skin cells and blood under fingernails of a murder victim  A hitman for the Sicilian mafia is seen exiting the apartment  You gather DNA evidence from the skin cells and from the suspect  They have identical genotypes  What is the likelihood that the evidence came from the suspect?  What is H 1 and what is H 2 ?

17. Match Probability  Probability of observing a genotype at locus k by chance in population is a function of allele frequencies: for m loci Homozygote Heterozygote  Assumes unlinked (independent loci) and Hardy- Weinberg equilibrium

18. Probability of Identity  Probability 2 randomly selected individuals have same profile at locus k: Homozygotes Heterozygotes for m loci  Exclusion Probability (E): E=1-P

19. Which allele frequency to use?  Human populations show some level of substructuring  F ST generally < 0.03  Challenge is to choose proper ethnic group and account for gene flow from other groups http://books.nap.edu/openbook/0309053951/gifmid/95.gif Illinois Caucasian Georgia Caucasian U.S. Black

20. Substructure in human populations  G ST is quite high among the 5 major groups of human populations for CODIS microsatellites  Relatively low within groups, but not 0!

21. NRC (1996) recommendations  Use population that provides highest probability of observing the genotype (unless other information is known)  Correct homozygous genotypes for substructure within selected population (e.g., Native Americans, hispanics, African Americans, caucasians, Asian Americans)  No correction for heterozygotes HomozygotesHeterozygotes

22. Why is it ‘conservative’ (from the standpoint of proving a match) to ignore substructure for heterozygotes?

23. What if the slimy mob defense attorney argues that the most likely perpetrator is the mob hitman’s brother, who has conveniently “disappeared”? Does the general match probability apply to near relatives?

24. Probability of identity for full sibs Heterozygotes 2 alleles IBD 1 allele IBD 0 alleles IBD General Probability of Identity for Full Sibs: Homozygotes 2 alleles IBD 0 alleles IBD

25. Probability of identity for full sibs For a locus with 5 alleles, each at a frequency of 0.2: P ID = 0.072 P IDsib = 0.368 Probability of identity unrelated individuals

26. What is minimum probability of identity for full sibs?

27. Example: World Trade Center Victims  Match victims using DNA collected from toothbrushes, hair brushes, or relatives  Exact matches not guaranteed  Why not?  Use likelihood to match samples to victims