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Click Clack – Milk Attack?? Kristin Jenkins, NESCentGretchen A. Koch, Goucher CollegePaul Mangum, Midland CollegeDavid Matlack, Earlham College Results.

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Presentation on theme: "Click Clack – Milk Attack?? Kristin Jenkins, NESCentGretchen A. Koch, Goucher CollegePaul Mangum, Midland CollegeDavid Matlack, Earlham College Results."— Presentation transcript:

1 Click Clack – Milk Attack?? Kristin Jenkins, NESCentGretchen A. Koch, Goucher CollegePaul Mangum, Midland CollegeDavid Matlack, Earlham College Results Methods Using Microsoft Visual Basic for Applications (VBA) ©, we created a program that grouped the individuals based on language and phenotype. For example, if the individual was named “KEAA001” in the data set, “KE” indicates the country of origin to be Kenya, and “AA” indicates the language spoken to be the Afro-Asiatic language. The program surveyed all of the data presented and grouped the individuals according to the following categories, with the designations in the individual names shown in parentheses: LanguageLactose Tolerance Group Afro-Asiatic (AA)Type 1, Type 2, or Type 3 Nilo-Saharan (NS)Type 1, Type 2, or Type 3 Niger-Kordofanian (NK) Type 1, Type 2, or Type 3 Khoisan (SW and HZ)Type 1, Type 2, or Type 3 The results from this analysis were visualized using a three-dimensional pie chart to readily demonstrate the percentage of individuals in each language exhibiting the different phenotypes. Based on the results from the first analysis, we created another program in VBA that calculated the percentage of ancestral DNA in each language group. In order to complete this task, the number of individuals in each language group for which the genotypes were counted. The program then looked at whether or not the individual genotypes varied from the ancestral genotypes of CC at -13907 bp, TT at -13915 bp, and GG at -14010 bp. If the exact genotype at the specific position on the chromosome was unknown for an individual (indicated by “? ?”) in the data set, then that individual was not interpreted as having an SNP from the ancestral DNA. Hypotheses 1.The frequency of Lactase Non-Persistence (LNP) will be the greatest in the most ancestral language group. 2.The percentage of ancestral genotypes will be higher in the most ancestral language group. Introduction Lactate persistence (also known as lactose tolerance) refers to adult expression of the lactase-phlorizin hydrolase (LPH) enzyme controlled by the LCT gene. The selection for this trait in the human population appears to be correlated with the domestication of cattle and utilization of milk. SNP linked alleles have been identified for European and African populations. The data set presented by Tishkoff et al. 2007 contained the genotype of the SNPs at 13907, 13915, and 14010 base pairs upstream from the LCT gene for 493 individuals. The data set further categorized each individual according to the country in which he or she resides as well as the language spoken. Based on the raw glucose rise after lactose digestion, each individual (for which measurements were available) was given a lactose tolerance phenotype. Those individuals that are lactose intolerant are Type 1; Type 2 individuals show a slight intolerance to lactose. Finally, individuals of Type 3 show a phenotype of lactose tolerance. The original research analyzed the data based on language spoken and country of origin. In contrast to the original paper, our analysis removed the geopolitical borders separating the sampled individuals and combined the samples as language groups. Alec Knight et al., 2003, used Y chromosome and mtDNA variation among African populations and concluded that the click (including Khoisan) languages are the most ancestral of the African languages groups. Conclusion As evident in Figures 1-4, the Afro-Asiatic speakers tested showed a higher proportion of the population with the lactose tolerant phenotype, and the Khoisan speakers showed a higher proportion of lactose intolerant phenotypes. This evidence, based on phenotypes, supports the hypothesis that LNP will be the greatest in the most ancestral language. To further explore this relationship, the second study of genotypes was undertaken. In all three positions, the Khoisan speakers show the highest percentage of the population possessing the ancestral genotype. The most compelling evidence comes from Figure 7, where the three other groups are all below 60% of the population having ancestral genotypes. In sharp contrast, nearly 84% of the Khoisan speakers have ancestral genotypes in the position of the third SNP. This supports the hypothesis expressed by Alec Knight et al., 2003, that the click languages are the most ancestral. References Knight, Alec, et al. 2003. African Y Chromosome and mtDNA Divergence Provides Insight into the History of Click Languages. Current Biology, Volume 13, Issue 8, 15 April 2003, Page 705. Tishkoff, Sarah A, et al. 2007.Convergent adaptation of human lactase persistence in Africa and Europe. Nature Genetics, Volume 39, Number 1, Pages 31 – 40. Acknowledgements We would like to thank the organizers of the 2007 BioQUEST workshop for their dedication and support as well as NESCent, HHMI, Dr. Claudia Neuhauser, Goucher College, and Midland College for their financial support.


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