The Xhosa live mainly in the Eastern Cape of South Africa, the southwestern frontier of the great Bantu expansion, where Bantu-speaking farmers met Khoekhoe herders and San foragers. Their language, isiXhosa, the mother tongue of Nelson Mandela, is famous for its many click consonants, borrowed from Khoe languages. In our model, the Xhosa average is 58.9% West African, 15.6% Nilotic East African, 15.2% Southern African forager (San), 9.2% Western rainforest forager (BiAka) and 1.0% Mbuti. Its San share is higher than that of the Zulu (12.3%), their Nguni-speaking neighbours to the northeast, and level with the Sotho (15.3%). The closest modern average is a sample labelled Duma (San), at 0.0091, ahead of the Sotho, southeastern Bantu speakers and the Tswana, while the Zulu come only fifth (0.0267). The closest ancient groups are people from about 1550 AD at Mfongosi in KwaZulu-Natal (0.0353) and at Champagne Castle in the Drakensberg, with Xaro in Botswana, from about 550 AD, further down.

  • Largest ancient components in our model: West African 58.9%, Nilotic East African 15.6%, Southern African foragers (San) 15.2%
  • Closest modern population in our data: Duma (San), distance 0.0091
  • Closest ancient group in our data: South Africa Mfongosi 400BP, distance 0.0353

Where does Xhosa DNA sit on the genetic map of the world? To answer, we take the averaged Global25 (G25) coordinates of the Xhosa individuals sampled in South Africa and compare them with deep ancestral reference populations, with other modern groups and with ancient genomes. It is one of 335 populations in our atlas.

Ancient make-up of the Xhosa average

West African
58.9%
Nilotic East African
15.6%
Southern African foragers (San)
15.2%
Western rainforest foragers (BiAka)
9.2%
Central African rainforest foragers (Mbuti)
1.0%

Modelled as a mix of deep ancestral reference populations, the Xhosa average comes out as 58.9% West African, 15.6% Nilotic East African and 15.2% Southern African foragers (San). The West African component reflects ancestry from sub-Saharan Africa. The Nilotic East African share (15.6%) reflects ancestry found in East African populations.

Smaller traces of Central African rainforest foragers (Mbuti) (under 5%) also appear. At that level they can reflect real minor ancestry, but also simple model noise, so they should not be over-read. The fit is acceptable (fit distance 0.039): treat the proportions as a good approximation rather than exact values. This population was modelled with a global set of reference populations (ancient genomes, plus modern stand-ins where no suitable ancient genome exists), because West Eurasian sources alone cannot describe it.

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Sankofa – African Ancestry Report

Sankofa – African Ancestry Report

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Closest modern populations to Xhosa

Genetically, the Xhosa average sits nearest to Duma (San) at 0.009, Sotho at 0.016 and Bantu (S.E.) at 0.016. On our scale, a distance of 0.009 counts as very close. By the tenth closest (Herero (Namibia)) the distance grows to 0.056, a common pattern for a population that shares ancestry with its neighbours while keeping a profile of its own.

#PopulationDistanceCloseness
1 Duma (San) 0.0091 Very close
2 Sotho 0.0160 Very close
3 Bantu (S.E.) 0.0161 Very close
4 Tswana 0.0229 Very close
5 Zulu 0.0267 Close
6 Damara 0.0291 Close
7 Sotho (South Africa) 0.0328 Close
8 South African (Bantu) 0.0369 Close
9 Pedi 0.0387 Close
10 Herero (Namibia) 0.0561 Moderate

Distances are Euclidean distances between averaged G25 coordinates. On our scale, below 0.025 is very close, below 0.050 close, below 0.080 moderate, and beyond that distant.

Closest ancient populations to Xhosa

Among ancient genomes, the closest match to the modern Xhosa average is South Africa Mfongosi 400BP (c. 1550 AD), at 0.035, followed by South Africa Champagne Castle 400BP and South Africa Newcastle 400BP. That is a close match: much of the modern profile was already present then, while later movements of people added further layers. A close ancient match is not proof of direct descent: it means those individuals carried a similar overall mix of ancestry.

#Ancient sample or groupPeriodDistance
1 South Africa Mfongosi 400BP c. 1550 AD 0.0353
2 South Africa Champagne Castle 400BP c. 1550 AD 0.0423
3 South Africa Newcastle 400BP c. 1550 AD 0.0462
4 Botswana Xaro 1400BP c. 550 AD 0.0526
5 Botswana Xaro 1400BP c. 550 AD 0.0541
6 South Africa Eland Cave 400BP c. 1550 AD 0.0544
7 Botswana Taukome 1100BP c. 850 AD 0.0633
8 Tanzania Early Modern Lindi Swahili (Bantu Zone P Profile) Early Modern, c. 1500-1800 AD 0.0745
9 Tanzania Pemba 600BP c. 1350 AD 0.0820
10 COG NgongoMbata 220BP c. 1750 AD 0.0832

Ancient DNA from South Africa

Our ancient DNA database holds 55 individuals excavated in present-day South Africa, dated from about 8,335 BC to 1810 AD. The most frequent Y-DNA haplogroups among them are A1b (19) and E1b (1), and the most frequent mtDNA haplogroups are L0 (14) and L3 (3). These are people who lived on the same land in the past, not necessarily ancestors of today's Xhosa population.

Most frequent Y-DNA haplogroups

HaplogroupIndividualsExamples
A1b 19 OAK003 OAK014 OAK013
E1b 1 vaa001

Most frequent mtDNA haplogroups

HaplogroupIndividualsExamples
L0 14 OAK014 OAK013 OAK012
L3 3 ela001 new001 mfo001

Ancient DNA studies on South Africa

Browse them in our ancient DNA database: 55 from South Africa.

Compare yourself with Xhosa

Paste your G25 coordinates (scaled, one line, with or without a name in front) and we compute your genetic distance to the Xhosa average and to its closest neighbours, right in your browser. Nothing is uploaded or stored.

No G25 coordinates yet? Get a free simulated G25 from your raw DNA file, or order G25 coordinates.

About these numbers

Keep in mind that a population average is a statistical summary of a limited number of sampled individuals. Real people inside any group vary, some carry more of one ancestry and some less, and no genetic profile decides who is or is not Xhosa. Use these numbers as a map of deep ancestry, not as a label.

Method: averaged G25 coordinates, Euclidean distances to other modern and ancient averages, and a non-negative least-squares model against deep ancestral reference populations (data generated 2026-10-01). Read the full method.

Go deeper than the average

This page describes the Xhosa average. Your own DNA has its own story: Sankofa – African Ancestry Report (15€) models your genome against the ancient sources and modern communities of the region, era by era, in a personal PDF report.

A report built for people of predominantly Sub-Saharan African (SSA) ancestry: modelling against 230+ regional African populations (West, Central, East & Southern Africa, the Horn of Africa, Madagascar) plus the European, Amerindian and...

Frequently asked questions

What is the ancient genetic make-up of Xhosa?

Modelled with deep ancestral reference populations, the Xhosa average is about 58.9% West African, 15.6% Nilotic East African and 15.2% Southern African foragers (San). These proportions are model estimates for a group average, not exact values for any one person.

Which populations are genetically closest to Xhosa?

In the G25 data, the closest modern populations to the Xhosa average are Duma (San), Sotho and Bantu (S.E.). The closest ancient matches are South Africa Mfongosi 400BP, South Africa Champagne Castle 400BP and South Africa Newcastle 400BP.

Can a DNA test tell me if I am Xhosa?

No DNA test can confirm an ethnicity or a nationality. What DNA can show is how similar your genome is to the sampled Xhosa average and to its neighbours. If you have G25 coordinates, paste them in the comparison box on this page to check that for free.

Which ExploreYourDNA report suits Xhosa ancestry?

Sankofa – African Ancestry Report is the report built for this heritage, and its reference panel fits the Xhosa average closely. Your own DNA may differ from the average, so the free Report Finder checks every report against your file before you buy.

Where does the data on this page come from?

From the averaged Global25 (G25) coordinates of the sampled individuals: genetic distances to other modern and ancient population averages, and a non-negative least-squares model against deep ancestral reference populations. The full method is described at https://www.exploreyourdna.com/populations#method.

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