Urban life in Sistan, specialized crafts and connections across the Iranian plateau.
📍 RegionIran
🧬 Closest modern matchBalochi Pakistan
⏳ Time periodEarly Bronze Age · c. 3200–1800 BC
Shahr-i-Sokhta: a Bronze Age city of eastern Iran
Shahr-i-Sokhta, the “Burnt City,” developed in Sistan at a junction of routes connecting the Iranian plateau with Central and South Asia. Founded around 3200 BC, it became a large urban center with separate residential, manufacturing and burial areas. Its main genetic profile reflects the eastern Iranian Bronze Age population landscape, distinct from the Indus-related ancestry also present at the site.
An early city in the Helmand world
The settlement was occupied through several main phases until approximately 1800 BC. Its mudbrick architecture preserves the growth of a complex community organized into areas with different functions. Houses, workshops, monumental structures and a large cemetery show how much activity had become concentrated in one place. Water was fundamental to this urban landscape, and changes in watercourses and climate contributed to the city’s eventual abandonment.
Shahr-i-Sokhta’s crafts included metalworking, stone vessels, beads and pottery. Its position linked the city with the Indus plain, the southern coasts of Iran and other regions of Central Asia. The archaeological remains therefore reveal both local production and participation in a broad exchange system. Residential quarters with courtyards and multiple rooms also show that this economic life was rooted in ordinary households, some of which combined domestic space with craft activity. The city thus combined a regional agricultural setting with activities reaching far beyond Sistan.
The main Bronze Age genetic cluster at Shahr-i-Sokhta combines substantial Iranian-related ancestry with an Anatolian farmer-related contribution. This distinguishes it from the separate Indus-related cluster, whose ancestry includes a much stronger South Asian hunter-gatherer-related strand. The difference helps explain why a major trading city can preserve more than one population history within the same archaeological setting. The main reference is useful alongside Gonur and other southern Central Asian groups for following the ancestry of the Iranian plateau–oasis world. The IVC-profile reference, in turn, makes visible another connection through the city toward South Asia.
In the World Genetics modern G25 comparison, the closest non-self match for Iran EBA Shahr-i-Sokhta is Balochi Pakistan. Other nearby references include Brahui, Makrani, Balochi Iran, and Pashtun Mashwani. This gives the Iran EBA Shahr-i-Sokhta profile its nearest modern genetic context inside the current reference database.
Closest Matches
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What does Iran EBA Shahr-i-Sokhta ancestry look like?
The ancestral breakdown below loads the best-fitting World Genetics calculator for the Iran EBA Shahr-i-Sokhta average. It should be read as a model of deep ancestry components, while the closest-match table is the better guide to which modern populations are most similar in G25 space.
Ancestral Breakdown
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Loading ancestral breakdown.
Where is Iran EBA Shahr-i-Sokhta DNA closest on the map?
The heatmap gives the Iran EBA Shahr-i-Sokhta profile a geographic shape. Warmer areas mark regions where available modern reference populations sit closer to the Iran EBA Shahr-i-Sokhta average, while cooler areas represent more distant matches.
What populations are genetically closest to Iran EBA Shahr-i-Sokhta?
The closest non-self match in this World Genetics comparison is Balochi Pakistan. Other nearby references include Brahui, Makrani, Balochi Iran, and Pashtun Mashwani.
Is Iran EBA Shahr-i-Sokhta DNA closest to Balochi Pakistan?
In the current modern G25 reference set, Balochi Pakistan is the closest listed match to the Iran EBA Shahr-i-Sokhta average after removing Iran EBA Shahr-i-Sokhta itself from the table.
What does the Iran EBA Shahr-i-Sokhta heatmap show?
The heatmap shows where modern reference populations are closer or farther from the Iran EBA Shahr-i-Sokhta G25 average, giving the closest-match results a geographic view.