Moderator: Mazille
Chuck11 wrote:Witticism wrote:My point is that at the human genetic level there is more diversity within a "taxonomic groupings (e.g. clades or subspecies)" than between "taxonomic groupings (e.g. clades or subspecies)" so the point is moot.And that is my point – it is arbitrary and any studies relating X to the genetics of ‘race’ will be arbitrary and ultimately of little scientific validity.
This belongs in a different section; take it there. This is what we are dealing with
These population's are objectively delineated using the program STRUCTURE. Your point about within and between variance is known as Lewontin's fallacy and it's a fallacy on multiple accounts:
1. What's important is the correlations between genes; that's what allows individuals to be unequivocally assigned to populations. Hence, Witherspoon et al (2007):A good measure of the robustness of racial genetic differentiation is the answer to the following question: ‘‘How often does it happen that a pair of individuals from one population is genetically more dissimilar than two individuals chosen from two different populations?’’ In fact, if many thousands of loci are used as a basis for judging genetic similarity and when individuals are sampled from geographically separated populations, the correct answer, which many will probably find surprising, is: ‘‘Never.’’ ("Genetic similarities within and between human population.")
2. When it comes to FST values, 5-15% variance is generally considered to be a moderate amount of variance. Here is a lovely passage from a recent paper on those "low" FST values:We analyzed a data set composed of short tandem repeat (STR) allele frequencies for eight loci genotyped in both humans and chimpanzees (Deka et al. 1995). These data made it possible to see how FST played out when no one could dispute taxonomic and genetic significance. The answer surprised us...In our analysis, FST was 0.12 for humans, but for humans and chimpanzees together, FST rose only to 0.18 (Long (2010) "Update to Long and Kittles’s “Human Genetic Diversity and the Nonexistence of Biological Races”(2003): Fixation on an Index."
3. As we are diploids, the within population variance is comprised of inter-individual variance and intra-individual variance. When comparing individuals between populations, you have to factor out the latter, which substantially raises the relative within/between individual variance.
Now, what is important here is that socially defined races and racial self identification correspond with ancestral populations, clusters, taxonomic races, or whatever. They don't have to perfectly correspond because we are talking about average differences, just reasonably correspond. (Imaging, a situation in which you have two heterogeneous groups comprised respectively of 90% German Shepherds and 10% Chihuahuas and 90% Chihuahuas and 10% German Shepherds -- you can still ask and investigate if a) one group is taller, b) if the difference has a partial genetic basis, and c) if this is due to --on AVERAGE -- breed i.e. race.) So the question is: "Does self identified race correspond with "ancestral populations, clusters, taxonomic races, etc." And the answer is "yes."We have analyzed genetic data for 326 microsatellite markers that were typed uniformly in a large multiethnic
population-based sample of individuals as part of a study of the genetics of hypertension (Family Blood Pressure
Program). Subjects identified themselves as belonging to one of four major racial/ethnic groups (white, African
American, East Asian, and Hispanic) and were recruited from 15 different geographic locales within the United States
and Taiwan. Genetic cluster analysis of the microsatellite markers produced four major clusters, which showed
near-perfect correspondence with the four self-reported race/ethnicity categories. Of 3,636 subjects of varying race/
ethnicity, only 5 (0.14%) showed genetic cluster membership different from their self-identified race/ethnicity. On
the other hand, we detected only modest genetic differentiation between different current geographic locales within
each race/ethnicity group. Thus, ancient geographic ancestry, which is highly correlated with self-identified race/
ethnicity—as opposed to current residence—is the major determinant of genetic structure in the U.S. population.
Implications of this genetic structure for case-control association studies are discussed (Tang et al., 2005.)
Honestly, what do you make of the hundreds of ongoing admixture studies? The ones that look like this:Admixture Mapping to Identify Spontaneous Preterm Birth Susceptibility Loci in African Americans
Manuck, Tracy A. MD; Lai, Yinglei PhD; Meis, Paul J. MD; Sibai, Baha MD; Spong, Catherine Y. MD; Rouse, Dwight J. MD; Iams, Jay D. MD; Caritis, Steve N. MD; O'Sullivan, Mary J. MD; Wapner, Ronald J. MD; Mercer, Brian MD; Ramin, Susan M. MD; Peaceman, Alan M. MD; for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units Network (MFMU)
OBJECTIVE: Preterm birth is 1.5 times more common in African American (17.8%) than European American women (11.5%), even after controlling for confounding variables. We hypothesize that genetic factors may account for this disparity and can be identified by admixture mapping.
METHODS: This is a secondary analysis of women with at least one prior spontaneous preterm birth enrolled in a multicenter prospective study. DNA was extracted and whole-genome amplified from stored saliva samples. Self-identified African American patients were genotyped with a 1,509 single nucleotide polymorphism (SNP) commercially available admixture panel. A logarithm of odds locus-genome score of 1.5 or higher was considered suggestive and 2 or higher was considered significant for a disease locus.
RESULTS: One hundred seventy-seven African American women with one or more prior spontaneous preterm births were studied. One thousand four hundred fifty SNPs were in Hardy-Weinberg equilibrium and passed quality filters. Individuals had a mean of 78.3% to 87.9% African American ancestry for each SNP. A locus on chromosome 7q21-22 was suggestive of an association with spontaneous preterm birth before 37 weeks of gestation (three SNPs with logarithm of odds scores 1.50–1.99). This signal strengthened when women with at least one preterm birth before 35.0 (eight SNPs with logarithm of odds scores greater than 1.50) and before 32.0 weeks of gestation were considered (15 SNPs with logarithm of odds scores greater than 1.50). No other areas of the genome had logarithm of odds scores higher than 1.5.
CONCLUSION: Spontaneous preterm birth in African American women may be genetically mediated by a susceptibility locus on chromosome 7. This region contains multiple potential candidate genes, including collagen type 1-α-2 gene and genes involved with calcium regulation.
Are they all predicated on a misunderstanding about race? If so, why don't you start emailing to authors and letting them know?

Finally, using just SNP data we predicted ~1% of the variance of crystallized and fluid cognitive phenotypes...
We estimate that 40% of the variation in crystallized-type intelligence and 51% of the variation in fluid-type intelligence between individuals is accounted for by linkage disequilibrium between genotyped common SNP markers and unknown causal variants.

Made of Stars wrote:Genetic determinants 'yes', SNP data as predictors of specific phenotypic differences 'no'. I'm aware that markers like this can pick up differences between whole populations...
but too often they're abused as representing something more specific.
Chuck11 wrote:1) Linkage disequilibrium with SNPs account for a large portion of the genetic variation in intelligence within populations

Genome wide association studies (GWAS) have found hundreds of SNPs that are significantly associated with complex traits such as height...However, in most cases, the published SNPs reliably associated with a trait explain only a small proportion of the known genetic variance...This has been called the ‘missing heritability’ problem (Maher 2008). We proposed two hypotheses that could explain this missing heritability. It could be that the SNPs used in GWAS explain all the additive genetic variance but most of them have such a small effect that they are not significant and therefore not reported. Alternatively, it could be that the mutations causing variation in height are not in perfect linkage disequilibrium (LD) with any of the SNPs and therefore part of the genetic variance is undetected by the SNPs.


jamest wrote:It seems self-evident to me...
Made of Stars wrote:Correct me if I'm wrong, but the second quote completely debunks your argument, and supports my point that SNPs etc don't correlate causally with traits like intelligence..
The purpose of the study was to estimate the proportion of variation in height that is captured by the SNPs that are used in GWAS. Our study differs from published GWAS in that we estimate the total variance explained by the SNPs without focussing on individual SNPs. Consequently, our estimate is not diminished by the failure of individual SNP effects to reach a significance threshold. If most causal variants for human height have such low frequency in the population that they are not in LD with the (common) SNPs on the commercial SNP arrays then the method we used would not detect much more additional variance than already accounted for by the published genome-wide significant loci. If, however, there are many causal variants that are in LD with the common SNPs but the effect sizes are too small to be detected with genome-wide significance, then our method would pick up their contribution to additive genetic variation.
We found that the SNPs explain ~45% of the phenotypic variance (Yang et al. 2010). This is substantially more than the ~10% explained by published, significant SNPs but less than the heritability of 80%. Thus the SNPs track approximately half of the known additive genetic variance. The difference between 10% and 45% is due to many SNPs with such small effects that they are not individually significant in GWAS. However, about half the genetic variance is left unaccounted for. We showed that this amount of missing heritability is expected if the mutations causing variation in height are similar to SNPs with minor allele frequency (MAF) < 0.1. The causal variants are expected to have lower MAF than common SNPs because they are more likely to be subject to some form of natural selection that leads to variants negatively associated with reproductive fitness to be at low frequency. Our study is the first to show that at least half of the heritability for height (typically estimated using twin and family studies) is captured by common SNPs.
and therefore have no place in a discussion of associations between 'race' and 'intelligence'.
Spearthrower wrote:Personally James, I think you owe yourself a lot more than falling for these superficial appearances rather than actually inquiring into the hard biological evidence that completely contradicts your feelings. Feelings, I am sure you are aware, that are in no small part constructed by the society and peer-group you grow up in.
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