Knowing which African populations score the highest for each of the 23andme “Sub-Saharan African” (SSA) categories can be a good guideline for their predictive ability. Below screenshots are all taken from people who have kindly agreed to share their results with me. For which i am very grateful! They were either born in the African country highlighted or have both parents from that country. These are obviously first of all individual results and very limited in number because there’s only very few Africans yet who have tested with 23andme. I’m posting them for illustrative purposes, mainly to get a very rough idea what to expect. Undoubtedly with more African 23andme test results you might see different or additional patterns. Still i think in most cases these screenshots below would be representative to some degree for how other people from their nationality or ethnic group would score hypothetically speaking. I will provide a brief overview of the main patterns i’m able to pick up on. Of course it merely shows my personal opinions & thoughts and is not meant to be conclusive in any way 😉
p.s. I’m only showing screenshots of the African breakdown. You’ll notice it will often not add up to 100%. In most cases this is because of a well known “bug” in the current version of Ancestry Composition causing people of 100% “Sub-Saharan African” (SSA) descent to show trace levels of non-SSA admixture or “unassigned” ancestry, this can generally be considered “noise”, i.e. reflecting an artefact of the DNA test. Hopefully it will be fixed with the next update. In some other cases though the individuals will have genuine additional non-SSA ancestry, which might however be “native” to Africa still if it’s labeled as “North African”, otherwise it might reflect historical geneflow from outside of Africa within the last 500 years or even earlier.
- Aside from actual Khoisan or Pygmy individuals taking this test it’s highly unlikely that this socalled “Central & South African” category, a huge misnomer, will reach significant levels (above 20%) among any other Africans or Afro-descendants. Given the samples being used it’s an extremely narrowly defined category, yet it is known that Pygmy and Khoisan markers are highly distinctive and therefore easily detectable by DNA testing. Which makes it still a reliable category if you forget about the labeling. On AncestryDNA the equivalent category (likely based on the very same samples) is called more truthfully “South Central Hunter Gatherers”. Also on the various Ged-Match calculators there’s usually similar separate categories for either San or Pygmies.
- “Central & South African” %’s seem to be most informative for South African Coloureds who are known to have a great deal of Khoisan ancestry, they are however heavily mixed with other ethnic origins as well. Therefore not all South African Coloureds will have it as main African component, socalled “West African” (most likely to be Bantu) also being important and even sometimes “East African” showing up as largest SSA component (see screenshot South Africa 5). In this recent DNA paper increasing Khoisan ancestry levels among South African coloureds were found in the most northwestern parts of South Africa.
- Bantu speakers from South Africa, Zimbabwe & Mozambique are all shown as being overwhelmingly “West African” which is obviously false and having to do with Bantu samples being used for “West Africa”. The South African result (number 6) is showing the highest level of “Central & South African” conforming with significant Khoisan ancestry being found for most South African ethnic groups (see this spreadsheet of Africa9 results). Possibly Khoisan admixture is also being detected for the Mozambican and the three Zimbabweans but at a much more decreased level.
- The SSA breakdown for the two individuals from Madagascar is quite diverse. Although “West African” is predominant both “Central & South African” and even “East African” are being shown at detectable level, especially relative to their total amount of SSA ancestry. It’s intriguing to speculate whether the “Central & South African” scores for Madagascar are suggestive of either Pygmy or San affinity. Given the local Vazimba legends perhaps Pygmy-like ancestry is more likely. See also this recent paper about new findings regarding the earliest African settlers of Madagascar. Also very notable is their Southeast Asian ancestry which is shown as being predominant, other persons from Madagascar might have less Southeast Asian though depending on ethnic background. Afro-descendants showing minor %’s of Southeast Asia might very well have partial Malagassy origins, i’ll discuss this in a separate future post.
**Highest scores among Southern Africans**
South Africa 1
South Africa 2
South Africa 3
South Africa 4
South Africa 5
South Africa 6
**Highest scores among Central Africans**
- Just like the previous results for Bantu speakers from southern Africa also these Central African individuals are misleadingly shown as being over 90% “West African”. Again having to do with Bantu samples being used to define the “West Africa” category, while the “Central Africa & South Africa” category is merely based on Pygmy and Khoisan samples.
- Compared with genuine West African results these Central Africans do seem to score markedly higher for “Central & South African”, in their case suggesting minor ancient Pygmy admixture. I suppose only for some southern Angolans this category might be indicative of Khoisan ancestry instead. These Pygmy admixture levels will again show great variaton according to ethnic group and also location being near the rainforest areas where the interaction between Bantu speaking groups and Pygmy populations would have been greatest.
- I only have a very limited number of Central African screenshots but their Pygmy %’s seem lower than from what i’ve seen on the Ged-Match calculator Africa9 (see the Bakongo (from Congo), Bamoun (from Cameroon) and Fang (from Gabon) scores for Biaka & Mbuti in this spreadsheet). Curiously i’ve seen many Afro-diasporeans score higher “Central & South African” scores than these 5 Central Africans even with their total SSA being less than 80%!
Democratic Republic of Congo (DRC) 1
**Highest scores among Afro-Diaspora**
- “Central & South African” %’s among Afro-descendants are likely to derive almost exclusively from Bantu speaking ancestors who already carried these markers within their genome because of ancient geneflow taking place within Africa. I personally don’t know of any historical records mentioning the presence in the Americas of Pygmy or Khoisan slaves. Given their nomadic lifestyle in highly remote and thinly populated areas and perhaps also because of being deemed physically unsuitable for plantation work it seems any systematic enslavement of Pygmies and Khoisan for Trans Atlantic purposes can be ruled out. Khoisan slaves were however present in the Dutch ruled Cape Colony of South Africa.
- From the results i’ve seen Brazilians by far score the highest “Central & South African” percentages, especially relative to their total SSA. Judging from their documented slave trade origins this was to be expected, Brazil showing the highest shares of slave imports from Central Africa as well as Southeast Africa compared with other destinations in the Americas. It could be indicative of both Pygmy and Khoisan ancestry (carried over by Bantu speaking slaves), however Pygmy affinity seems most likely. Going by the results of Zimbabwe and Mozambique ancient Khoisan admixture outside of South Africa doesn’t seem to be that high.
- Judging from what i’ve seen African American results for “Central & South African” are minor but vary a lot in between the range of 0,2% – 4,9%. I’ve seen far less West Indian results but on average African Americans seem to score slightly higher for this category than Jamaicans perhaps in line with documented slave trade with Congo & northern Angola being more important for the USA than most other former British colonies, especially Jamaica and Barbados.
- Dominicans and Puerto Ricans seem to score relatively high “Central & South African” percentages if you compensate for their generally lower total SSA ancestry. This could however also be a result of random recombination and perhaps certain DNA segments being more likely to be “retained” or “recycled” than others, ending up with a genetic SSA breakdown that could be disproportionate to a genealogical SSA breakdown (if it was somehow possible to reconstruct one completely).