Shona (Manyika) DNA
Genetic origins and closest populations · Zimbabwe · Sub-Saharan Africa
The Shona are the largest people of Zimbabwe, and the Manyika, whose average this page uses, live in the eastern highlands around Mutare and across the border in Mozambique. Shona is a Bantu language, and the stone city of Great Zimbabwe, built between about the 11th and 15th centuries, is widely linked to Shona-speaking communities. In our model, the Manyika average is 74.5% West African, 14.3% Nilotic East African, 7.9% Western rainforest forager (BiAka) and 3.3% Southern African forager (San). That San share is far lower than in South Africa, where the Zulu reach 12.3% and the Sotho 15.3%, so in our data the forager imprint fades as one moves north. The closest modern averages are peoples of Mozambique and Malawi, the Chopi and Bitonga (both 0.0087), then the Chewa, Nyanja and Changana. The closest ancient group is Early Modern Swahili-coast people from Lindi in Tanzania with a Bantu Zone P profile (0.0247), and medieval Pemba also appears.
- Largest ancient components in our model: West African 74.5%, Nilotic East African 14.3%, Western rainforest foragers (BiAka) 7.9%
- Closest modern population in our data: Chopi, distance 0.0087
- Closest ancient group in our data: Tanzania Early Modern Lindi Swahili (Bantu Zone P Profile), distance 0.0247
Where does Shona (Manyika) DNA sit on the genetic map of the world? To answer, we take the averaged Global25 (G25) coordinates of the Shona (Manyika) individuals sampled in Zimbabwe, listed in the G25 sheet as "Manyika" 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 Shona (Manyika) average
Modelled as a mix of deep ancestral reference populations, the Shona (Manyika) average comes out as 74.5% West African, 14.3% Nilotic East African and 7.9% Western rainforest foragers (BiAka). The West African component reflects ancestry from sub-Saharan Africa. With well over half of the total, this single source dominates the profile.
Smaller traces of Southern African foragers (San) (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 loose (fit distance 0.059), which usually means that none of the available reference populations is a close stand-in for part of this ancestry, so read the percentages as rough. 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.
Sankofa – African Ancestry Report
Closest modern populations to Shona (Manyika)
Genetically, the Shona (Manyika) average sits nearest to Chopi at 0.009, Bitonga at 0.009 and Chewa at 0.009. On our scale, a distance of 0.009 counts as very close. Even the tenth closest, Ngoni (Malawi), is only 0.014 away: Shona (Manyika) belongs to a dense cluster of related populations, so small differences inside that cluster should not be over-interpreted.
| # | Population | Distance | Closeness |
|---|---|---|---|
| 1 | Chopi | 0.0087 | Very close |
| 2 | Bitonga | 0.0087 | Very close |
| 3 | Chewa | 0.0094 | Very close |
| 4 | Nyanja | 0.0094 | Very close |
| 5 | Changana | 0.0095 | Very close |
| 6 | Yao | 0.0105 | Very close |
| 7 | Tswa | 0.0105 | Very close |
| 8 | Ndau | 0.0108 | Very close |
| 9 | Sena | 0.0111 | Very close |
| 10 | Ngoni (Malawi) | 0.0140 | Very close |
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 Shona (Manyika)
Among ancient genomes, the closest match to the modern Shona (Manyika) average is Tanzania Early Modern Lindi Swahili (Bantu Zone P Profile) (Early Modern, c. 1500-1800 AD), at 0.025, followed by Saint Helena Late Modern Rupert's Valley (Central/Southern African Bantu Profile) and Tanzania Pemba 600BP. That is a very close match, which suggests strong genetic continuity between those ancient people (or close relatives of theirs) and the modern population. A close ancient match is not proof of direct descent: it means those individuals carried a similar overall mix of ancestry.
| # | Ancient sample or group | Period | Distance |
|---|---|---|---|
| 1 | Tanzania Early Modern Lindi Swahili (Bantu Zone P Profile) | Early Modern, c. 1500-1800 AD | 0.0247 |
| 2 | Saint Helena Late Modern Rupert's Valley (Central/Southern African Bantu Profile) | Late Modern, c. 1800-1950 AD | 0.0280 |
| 3 | Tanzania Pemba 600BP | c. 1350 AD | 0.0290 |
| 4 | COG NgongoMbata 220BP | c. 1750 AD | 0.0336 |
| 5 | Uganda Munsa 500BP | c. 1450 AD | 0.0358 |
| 6 | COG Kindoki 230BP | c. 1700 AD | 0.0363 |
| 7 | Democratic Republic of the Congo Ngongo Mbata 220BP | c. 1750 AD | 0.0372 |
| 8 | Democratic Republic of the Congo Kindoki 230BP | c. 1700 AD | 0.0377 |
| 9 | South Africa Eland Cave 400BP | c. 1550 AD | 0.0405 |
| 10 | South Africa Newcastle 400BP | c. 1550 AD | 0.0417 |
Compare yourself with Shona (Manyika)
Paste your G25 coordinates (scaled, one line, with or without a name in front) and we compute your genetic distance to the Shona (Manyika) average and to its closest neighbours, right in your browser. Nothing is uploaded or stored.
| # | Population | Your distance | Closeness |
|---|
This list only covers Shona (Manyika) and its neighbours. To find out which of our reports actually fits your DNA, run the free Report Finder: it runs the same fit test that every report uses before an order.
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 Shona (Manyika). 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 Shona (Manyika) 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...
More populations from Sub-Saharan Africa
Frequently asked questions
What is the ancient genetic make-up of Shona (Manyika)?
Modelled with deep ancestral reference populations, the Shona (Manyika) average is about 74.5% West African, 14.3% Nilotic East African and 7.9% Western rainforest foragers (BiAka). These proportions are model estimates for a group average, not exact values for any one person.
Which populations are genetically closest to Shona (Manyika)?
In the G25 data, the closest modern populations to the Shona (Manyika) average are Chopi, Bitonga and Chewa. The closest ancient matches are Tanzania Early Modern Lindi Swahili (Bantu Zone P Profile), Saint Helena Late Modern Rupert's Valley (Central/Southern African Bantu Profile) and Tanzania Pemba 600BP.
Can a DNA test tell me if I am Shona (Manyika)?
No DNA test can confirm an ethnicity or a nationality. What DNA can show is how similar your genome is to the sampled Shona (Manyika) 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 Shona (Manyika) ancestry?
Sankofa – African Ancestry Report is the report built for this heritage, and its reference panel fits the Shona (Manyika) 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.