Category: genetic kinship

More on Population Genetics

Let’s consider some ideas I’ve written about before.

A genetic testing company can in theory define a certain consensus genome as “Puerto Rican,” and it is therefore possible in that case for typical Puerto Ricans to test out as 100% (or 99% or 92 % or 90%.etc.) Puerto Rican.  But if the same genome is interpreted in light of the major continental population groups (races), then someone who is “100% Puerto Rican” would then be, e.g., 50% European, 40% sub-Saharan African, and 10% Amerindian. Same genome, different definition.

The gene frequencies that define “100% European” today would not be the same as, say, several thousand years ago.  Genetic ancestries which back then would have to be classified as non-European would today be part of the European genome, as intrusive elements have been assimilated.  A haplotype today defined by 23andMe as “British/Irish” or “French/German” or “Italian” or “Balkan” may be by the standards of, say, 2000 BC, mostly European (by 2000 BC standards) but with some non-European components (again by 2000 BC standards).  

All of this does NOT mean that ethnicity and race are “socially constructed;” those are biologically real and legitimate entities.  However, the labels used to describe those entities are defined by people and these labels, and these definitions, can change over time.  This also  NOT mean that we should blithely accept intrusive elements entering the European genepool today; genetic interests are future-oriented, and what happened in the past affected the genetic interests of the people at that time, not us today. We are what we are, just like they were what they were.  One set of changes does not in any way obligate or justify a different set of changes.  Everything must be considered in the light of the interests of the people that exist at that time.

The major point, that most “movement” nitwits do not understand, is that people cannot take the labels given to particular gene frequencies or haplotypes at face value in the sense of an absolute and precise entity whose specific definition has the exact same meaning over long periods of time.  The actual degrees of genetic kinship based on the raw genetic data are real and concrete and precisely meaningful – to the extent we take into account statistical error and the over-riding importance of parental populations (that is tied into the topic of this post…what is the parental population you use to define “100% X?”) – but the defining labels are not necessarily so.

Sallis Agrees With the Alt Right on Something

Some good sense.

I essentially agree with and endorse this article, with some caveats, and it should be read together with this piece I wrote several years ago.

The article is reasonably sound, although one caveat is that if one approaches these tests with a sense of realism with respect to their limitations – limitations spelled out in my Counter-Currents piece – then getting tested may not be a bad idea.  Having the raw data could be useful if you can find someone who can do a genetic kinship analysis with it. But taking the details of the data literally – thinking that there’s a real difference between 100% A, 0% B vs. 99.3% A, 0.7% B, for example – is ludicrous. I would take even the 90% confidence readings with a large grain of salt, and the 50% confidence readings are so absurd that the salt grain needs to be the size of the iceberg that sunk the Titanic.

The other caveat to the article is that the comments section is mixed; some comments are useful, some are asinine, so caveat emptor.

There are two basic questions here.

1. Is 23andMe a good test?

2. Assuming an ancestry test is good, is it worthwhile?

To which I answer: 1) No and 2) Maybe, depending on context.

In an absolute sense, 23andMe is superior to DNAPrint’s tests from ~15 years ago; in a relative sense – comparing each test to the “state of  the art” available at the time – it really isn’t better at all.  With the level of understanding and methodology we have today, coupled with a prudent interpretation of the data, one could do much better.

What if a test was sound?  Well, sure, it can be interesting, but I’ll repeat something I’ve been hammering home here over the past few years – the only biopolitically relevant genetic metric is genetic kinship (at all levels of genetic integration).  If one can measure that, then it is useful. All else can be interesting, but not directly important from an EGI standpoint.

And if people are going to hysterically obsess over sub-fractional admixture percentages then this is missing the forest for the trees.

Failure of Fst/Gst

Population genetics.

Both “movement” fetishists as well as anti-racist liars like to misuse Fst/Gst in genetic distance discussions (*) to promote their respective agendas.  Unfortunately for them, Fst/Gst is not really a (direct) measure of genetic distance, and particularly fails even as an indirect proxy when comparing populations that exhibit different levels of heterozygosity (e.g., human ethnies) and/or when considering loci with more than two allele variants.  To have the ill-informed trying to parse differences of, say, Fst/Gst = 0.0060 vs. 0.0065 and trying to make relevant conclusions from that is laughable.  The following are a small sampling of links to cite the next time some idiot tries to play such games (emphasis added):

See here.

See also here:

Likewise, when diversity is equated with heterozygosity, standard similarity measures formed by taking the ratio of mean within-subpopulation diversity to total diversity necessarily approach unity when diversity is high, even if the subpopulations are completely dissimilar (no shared alleles). None of these measures can be interpreted as measures of differentiation or similarity. 

At Wikipedia:

Also, strictly speaking FST is not a genetic distance, as it does not satisfy the triangle inequality. As a consequence new tools for measuring genetic differentiation continue being developed.

And this article here:

One underutilized approach is the coupling of indirect metrics of gene flow (e.g. F-statistics, Dest_Chao) with more direct measures such as kinship or parentage analyses (e.g. Loiselle et al. 1995; Selkoe et al. 2006; Buston et al. 2009; Christie et al. 2010; Palsbøll et al. 2010). Broadly speaking, kinship analyses provide an index of the relative relatedness of all genotyped individuals in a data set, and parentage is a distinct case of kinship whereby the most likely parents of individual juveniles are identified (Vekemans & Hardy 2004; Jones & Arden 2003; reviewed in Blouin 2003; Jones et al. 2010). Kinship coefficients (also known as coefficients of coancestry) are widely interpreted as the probability of identity by descent of the genes, but they are more properly defined as ‘ratios of differences of probabilities of identity in state’ (Hardy & Vekemans 2002, p. 23) from homologous genes sampled randomly from each pair of individuals (Hardy & Vekemans 2002; Rousset 2002; Blouin 2003; Vekemans & Hardy 2004).

By comparison, F-statistics and Dest_Chao are often blind to the relatedness of individuals; different population samples with the same kinship structure can have very different levels of genetic differentiation among them and vice versa.

*True, Salter used Fst in On Genetic Interests, but only because there was no other data available for that purpose at that time.  And Salter makes clear in the book that the proper approach would be to use data from global assays of genetic kinship which did not (and still do not) exist for human ethnies.  It is interesting that population geneticists and ecologists will calculate genetic kinship for plant and non-human animal species, but are either too lazy or politically-motivated to do so for human population groups. However, anecdotal evidence from the genetic kinship data that companies such as 23andme and DeCode used to present to their customers suggest that human genetic kinship findings would not be to the liking of either the fetishists or the anti-racists.