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 Archaeology – “the scientific study of material remains (as fossil relics, artifacts, and monuments) of past human life and activities”  Studies.

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Presentation on theme: " Archaeology – “the scientific study of material remains (as fossil relics, artifacts, and monuments) of past human life and activities”  Studies."— Presentation transcript:

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3  Archaeology – “the scientific study of material remains (as fossil relics, artifacts, and monuments) of past human life and activities”  Studies the time period starting at the Paleolithic time until the advent of literacy  Slide Credits to Vanessa Patel

4  From bones, compared genomes of three different Neanderthals with five genomes from modern humans from different areas of the world Figure 1- R. E. Green et al., Science 328, 710-722 (2010)  Slide Credits to Vanessa Patel

5 Stoneking, Krause, Nature Reviews Genetics 2011

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21 Signature Haplotypes:  Highly diverged  High LD over a long region

22 Neutral Drift Positive Selection Negative Selection How can we detect negative selection? How can we detect positive selection?

23 Ka/Ks ratio: Ratio of nonsynonymous to synonymous substitutions Very old, persistent, strong positive selection for a protein that keeps adapting Examples: immune response, spermatogenesis Ka/Ks ratio: Ratio of nonsynonymous to synonymous substitutions Very old, persistent, strong positive selection for a protein that keeps adapting Examples: immune response, spermatogenesis

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25 X X X Slide Credits: Marc Schaub

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27 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 S1S1 S2S2 S3S3 S4S4 S5S5 S6S6 Slide Credits: Marc Schaub

28 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C Slide Credits: Marc Schaub

29 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C 3 core haplotypes: ch 0 = 101 ch 1 = 111 ch 2 = 100 Slide Credits: Marc Schaub

30 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C 3 core haplotypes: ch 0 = 101 ch 1 = 111 ch 2 = 100 Slide Credits: Marc Schaub

31 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C 3 core haplotypes: ch 0 = 101 ch 1 = 111 ch 2 = 100 Slide Credits: Marc Schaub

32 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C  Given a core haplotype (101) and a SNP (S 6 )  EHH is the conditional probability of two randomly chosen chromosomes to be homozygous from the core to S 6 given that they include core haplotype 101

33 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C  EHH is the conditional probability of two randomly chosen chromosomes to be homozygous from the core to S 6 given that they include core haplotype 101 Slide Credits: Marc Schaub

34  EHH is the conditional probability of two randomly chosen chromosomes to be homozygous from the core to S 6 given that they include core haplotype 101 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C Slide Credits: Marc Schaub

35 ChrS1S1 S2S2 S3S3 S4S4 S5S5 S6S6 A101110 B111010 C101110 D111100 E100011 F101110 G100100 H111110 I101111 J101111 Core C Slide Credits: Marc Schaub

36  Study of genes known to be implicated in the resistance to malaria.  Infectious disease caused by protozoan parasites of the genus Plasmodium  Frequent in tropical and subtropical regions  Transmitted by the Anopheles mosquito Image source: wikipedia.org Slide Credits: Marc Schaub

37 Image source: NIH - http://history.nih.gov/exhibits/bowman/images/malariacycleBig.jpgNIH - http://history.nih.gov/exhibits/bowman/images/malariacycleBig.jpg Slide Credits: Marc Schaub

38 Image source: CDC - http://www.dpd.cdc.gov/dpdx/images/ParasiteImages/M- R/Malaria/malaria_risk_2003.gif http://www.dpd.cdc.gov/dpdx/images/ParasiteImages/M- R/Malaria/malaria_risk_2003.gif Slide Credits: Marc Schaub

39 Source: Sabeti et al. Nature 2002. Slide Credits: Marc Schaub

40 Source: Sabeti et al. Nature 2002. Slide Credits: Marc Schaub

41 Source: Sabeti et al. Nature 2002. Slide Credits: Marc Schaub

42 Source: Sabeti et al. Nature 2002. Slide Credits: Marc Schaub

43 Source: Sabeti et al. Nature 2002. Slide Credits: Marc Schaub

44  Allison (1954): Sickle-cell anemia is limited to the region in Africa in which malaria is endemic. Image source: wikipedia.org Distribution of malariaDistribution of sickle-cell anemia Slide Credits: Marc Schaub

45  Hypothesis: mutation causing sickle-cell anemia positively selected for the resistance to malaria.  Currat (2002) and Ohashi (2004) identify the mutations in the African respectively Asian populations. Slide Credits: Marc Schaub

46  Single point mutation in the coding region of the Hemoglobin-B gene (glu → val).  Heterozygote advantage:  Resistance to malaria  Slight anemia. Image source: wikipedia.org Slide Credits: Marc Schaub

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48 Source: Ingram and Swallow. Population Genetics of Encyclopedia of Life Sciences. 2007. Slide Credits: Marc Schaub

49 LCT, 5 ’ LCT, 3 ’ Source: Bersaglieri et al. Am. J. Hum. Genet. 2004. Slide Credits: Marc Schaub

50 Source: Catherine Janet Ellen Ingram and Dallas Mary Swallow. Population Genetics of Lactase Persistence and Lactose Intolerance advanced. Encyclopedia of Life Sciences. 2007. Slide Credits: Marc Schaub

51  -13910*T associated with persistent lactose tolerance. Is this mutation causal?  Does not account for tolerance in sub- Saharan populations (Mulcare 2004).  Additional SNPs in an enhancer within 100bp are associated with lactose tolerance.   Several independent causes for lactose tolerance (reviewed in Ingram 2009). Slide Credits: Marc Schaub

52 Lactase persistence (litterature)Predicted lactase persistence 13910*T distribution Source: Ingram et al. Lactose digestion and the evolutionary genetics of lactase persistence. Hum Genet. 2009 Jan;124(6):579-91. Slide Credits: Marc Schaub

53 Less time: Fewer mutations Fewer recombinations

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