Genomics: Insight

Human Racial Categorization 

The charged concept of race has long overshadowed human history. Historically armed to place certain groups above others, race remains a powerful social and political factor. From Plessy v. Furguson (1896) - legalizing racial segregation - to the anti-miscegenation laws of the U.S. banning interracial marriages, racism has long been integrated into society. Currently, the COVID-19 pandemic disproportionately impacts workers of color not because of their genetics but because of the lower quality of life and job opportunities available to them.1 The pandemic reveals the historical impact of human classification, racial wealth gaps, and redlining. While many racial policies have been outlawed, their societal harms - often life threatening - still remain. The United States Census Bureau has split race and ethnicity into five categories: White, Black or African American, American Indian and Alaska Native, Asian, and Native Hawaiian and other Pacific Islander. Surveys conducted by the bureau reveal correlations between race and socioeconomic status, the quality of education, and health and healthcare, leading to the question if genetic differences exist between populations.2 Given the negative consequences of contemporary human groups, how can genomic analysis challenge the basis of these classifications? Through studies such as the Human Genome Diversity Project, data on specific microsatellite loci, which are repeated sequences in DNA that can be used to track genetic inheritance between individuals and populations, across individuals is collected from populations across the globe.3 The data was then used to calculate and study the haplotype heterozygosity - or genetic variation - in each population. The greater haplotype heterozygosity, tendency for each loci on a chromosome to be different between individuals, of alleles among individuals in Africa compared to individuals of other continents discredits contemporary groupings of people.

The greater haplotype heterozygosity of alleles among individuals in Africa compared to individuals of other continents discredits contemporary groupings of people.

Method Used to Collect Data

Two important papers focused on  the genetic variation between and across regions. Noah A. Rosenberg’s “A Population-Genetic Perspective on the Similarities and Differences Among Worldwide Human Populations'' provides a collection of answers concerning human population-genetic diversity based on data from the Human Genome Diveristy Project (HGDP-CEPDH Cell Panel). The study collected data of 783 microsatellite polymorphic loci from 1,048 individuals across 53 populations in seven regions: Europe, sub-Saharan Africa, Central/South Asia, East Asia, the Americas, Oceania, and the Middle East. The distribution of the microsatellite polymorphic loci revealed what genetic diversity exists between and among populations. For instance, the D12S2070 locus has exactly eight alleles. Even though one of its alleles can provide information about regional ancestry, it is not definitive evidence of the population affiliation of the individual because the frequency of the allele per region varies from 0.014 to 0.852, and there is no region in which all members or no members contain the allele. Furthermore, loci can often be unique to the individual, rendering the ability to classify people by genome even more unattainable. When each microsatellite can have 2 to 5 repeat units and a diverse selection of alleles at each loci, the likelihood that just two individuals match across multiple loci is tremendously slim.4 In addition to the HGDP-CEPH, other studies were conducted to provide more comprehensive and uniform data sets representative of the world population. “Toward a more Uniform Sampling of Human Genetic Diversity: A Survey of Worldwide Populations by High-density Genotyping” written by Jinchuan Xing and others who collected DNA samples from 296 individuals from 13 populations in Central Europe, West Asia, South/Southeast Asia, America, Polynesus, Central Asia, and West Africa. These were then combined with other studies', such as HapMap, samples to create a final dataset of 246, 554 autosomal loci genotypes from 850 inhabitants of 40 populations across the globe. By calculating the haplotype heterozygosity of each geographical region, the variation in genome within populations could be compared to that of other populations.5 Overall, by studying the genomes of individuals throughout the world, the resulting data would reveal whether or not genetic similarities or differences exist between contemporary human groupings. 

Results and Analysis of Studies 

The studies showed that not only are humans genetically similar within their own population compared to a different region, but also humans can be more genetically different to individuals from the same population. The HGDP-CEPH Cell Panel revealed that each of the 783 loci that were analyzed has on average 11.94 distinct alleles - meaning alleles that set the human microsatellite apart from others in the collection. The data was then split to display the average number of distinct alleles per a subsample of 60 alleles across different geographical regions. In other words, for every 60 alleles randomly collected from each region, how many of them are unique to the individuals of that population. Results revealed that Africa contained the highest number of distinct alleles at around 8 per loci, but the range among locations was only approximately 5 to 8 distinct alleles, and a worldwide sample of alleles from all seven regions display an average of 10 distinct alleles per locus. The small range of distinct alleles reveal that nearly all alleles are found in all seven regions in similar frequencies, conveying little genetic variability exists between worldwide populations. Through organizing each allele in the region they were found in, the data further indicates that few alleles are specific to a specific region and nearly half of all alleles are found in all seven regions. More than 50% of all private alleles - alleles that are found in only a single population - are located in Africa alone, displaying a greater haplotype heterozygosity and therefore greater genetic diversity within Africa than between Africa and other continents. The Xing study supports this finding, revealing a linear decline in haplotype heterozygosity and distance from Africa. Africa by far contains the greatest haplotype heterozygosity compared to all other regions, indicating that people in Africa are more genetically dissimilar to each other than to people in other continents. 

The lack of distinguishable genes within populations prove that social inequality factors such as income disparities between racial lines cannot be explained by genetics.

Conclusion

Can the genetic profile of an individual be used to determine the population affiliation of that individual? The short answer: no.  The lack of distinctive alleles across regions globally indicates that individuals cannot be genetically classified into different populations. In fact, because 92% of alleles are found in every two or more geographical locations and only 7.4% of over 4,000 alleles are unique to one region, only occurring in 1% of the population, the probability of genetic similarity to someone from a different world population equals that to someone from the same.6 As not enough alleles are unique to singular groups, the data set proves that contemporary groupings such as race cannot be backed up by genetics. For example, due to the magnitude of variation within Africa, two people from the continent are likely to be more genetically different from one another than to individuals in other regions. The lack of distinguishable genes within populations indicates that social inequality factors such as income disparities between racial lines cannot be explained by genetics. Connecting race to biology has long been used as an excuse to exploit and segregate human groups. Uncovering genetic myths will be the first step to dismantling a system that perpetuates the lack of access to resources such as education and health care based on contemporary groupings. 

References

1. “Risk for Covid-19 Infection, Hospitalization, and Death by Race/Ethnicity.” Centers for Disease Control and Prevention, 11 Feb. 2020, www.cdc.gov/coronavirus/2019-ncov/covid-data/investigations-discovery/hospitalization-death-by-race-ethnicity.html.
2. Census.gov, 2020, https://data.census.gov/cedsci/table?q=United%20States 
3. Rosenberg. “A Population-Genetic Perspective on the Similarities and Differences among Worldwide Human Populations.” Human Biology, vol. 92, no. 3, 2020, p. 135, 10.13110/humanbiology.92.3.02. Accessed 19 July 2021. https://rosenberglab.stanford.edu/papers/Rosenberg2011-HumBiol.pdf 
4. Xing, Jinchuan, et al. “Toward a More Uniform Sampling of Human Genetic Diversity: A Survey of Worldwide Populations by High-Density Genotyping.” Genomics, vol. 96, no. 4, 1 Oct. 2010, pp. 199–210, www.ncbi.nlm.nih.gov/pmc/articles/PMC2945611/, 10.1016/j.ygeno.2010.07.004. Accessed 9 Feb. 2022.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2945611/ 
5. Rosenberg, Noah. “Genetic Structure of Human Populations.” https://web.stanford.edu/group/rosenberglab/papers/popstruct.pdf.  
6. Rosenberg, Noah. “Genetic Structure of Human Populations.” https://rosenberglab.stanford.edu/supplements/popstructSupp.pdf