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. 2022 Mar 8;13(1):1203.
doi: 10.1038/s41467-022-28827-2.

Ancient genomes from the Himalayas illuminate the genetic history of Tibetans and their Tibeto-Burman speaking neighbors

Chi-Chun Liu  1 , David Witonsky  1 , Anna Gosling  1   2 , Ju Hyeon Lee  3 , Harald Ringbauer  1   4 , Richard Hagan  5   6 , Nisha Patel  7   8 , Raphaela Stahl  9 , John Novembre  1 , Mark Aldenderfer  10 , Christina Warinner  11   12 , Anna Di Rienzo  13 , Choongwon Jeong  14
Affiliations

Ancient genomes from the Himalayas illuminate the genetic history of Tibetans and their Tibeto-Burman speaking neighbors

Chi-Chun Liu et al. Nat Commun. .

Abstract

Present-day Tibetans have adapted both genetically and culturally to the high altitude environment of the Tibetan Plateau, but fundamental questions about their origins remain unanswered. Recent archaeological and genetic research suggests the presence of an early population on the Plateau within the past 40 thousand years, followed by the arrival of subsequent groups within the past 10 thousand years. Here, we obtain new genome-wide data for 33 ancient individuals from high elevation sites on the southern fringe of the Tibetan Plateau in Nepal, who we show are most closely related to present-day Tibetans. They derive most of their ancestry from groups related to Late Neolithic populations at the northeastern edge of the Tibetan Plateau but also harbor a minor genetic component from a distinct and deep Paleolithic Eurasian ancestry. In contrast to their Tibetan neighbors, present-day non-Tibetan Tibeto-Burman speakers living at mid-elevations along the southern and eastern margins of the Plateau form a genetic cline that reflects a distinct genetic history. Finally, a comparison between ancient and present-day highlanders confirms ongoing positive selection of high altitude adaptive alleles.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Geographic locations for ancient groups and present-day Tibeto-Burman speakers.
Circles represent ancient groups and are colored by archaeological periods; squares represent present-day populations of Tibeto-Burman speakers. Left inset: an enlarged view of the seven aMMD sites. Lower left inset: an enlarged view of the present-day Nepalese and Bhutanese populations: 1. Bahing; 2. Bantawa; 3. Baram; 4. Brokkat; 5. Brokpa; 6. Bumthang; 7. Chali; 8. Chamling; 9. Chantyal; 10. Chepang; 11. Chetri; 12. Dakpa; 13. Damai; 14. Dhimal; 15. Dumi; 16. Dzala; 17. Gongduk; 18. Gurung; 19. Khengpa; 20. Kulung; 21. Kurtop; 22. Lakha; 23. Layap; 24. Limbu; 25. Lower_Mustang; 26. Magar; 27. Majhi; 28. Mangde; 29. Monpa; 30. Nachiring; 31. Newar; 32. Ngalop; 33. Nubri; 34. Nup; 35. Puma; 36. Sampang; 37. Sarki; 38. Sherpa; 39. Sherpa_Khumbu; 40. Sonar; 41. Sunwar; 42. Tamang; 43. Thakali; 44. Tshangla; 45. Tsum; 46. Upper_Mustang; 47. Wambule. The base map was created in R v4.0.0 using publicly available map and altitude information from the mapdata v2.3.0 and elevatr v0.3.4 packages.
Fig. 2
Fig. 2. aMMD individuals on the top two PCs of present-day Asian individuals.
We calculated PCs from 486 present-day Asian individuals in the HO dataset and projected aMMD individuals on top of the top PCs. Gray dots represent present-day individuals we used to calculate PCs. Circles represent median positions of present-day groups colored by their language families along with their respective group abbreviations. Red capital letters “U, L, C, R, K, M, S” represent projected aMMD individuals.
Fig. 3
Fig. 3. Admixture graph modeling for aMMD groups using qpGraph.
aMMD groups are modeled as two-way mixtures with Upper_YR_LN as one source and a deep lineage as the other source. The phylogenetic position of the deep lineage is inferred to be around the split between western and eastern Eurasian lineages but no further specification could be made due to limited resolution of our dataset. Here we present a graph for Suila that prefers a deep eastern Eurasian source and one for Lubrak that has zero-length branch suggesting affinity to neither western nor eastern Eurasian lineages. Alternative topologies and those without a deep Eurasian gene flow are presented in Supplementary Fig. 9. Z-scores are calculated by 5 cM block jackknifing as implemented in the qpGraph program.
Fig. 4
Fig. 4. A genetic cline of Tibeto-Burman groups.
We model Tibeto-Burman groups using Nepalese Tibetan from the Tsum region (“Tsum”) and Upper_YR_LN as the two sources using qpAdm. Tibetans from the plateau and Tibetans close to the Himalayas derived the majority of their ancestry from the Tibetan lineage, while Tibeto-Burman groups further to the east derived a much higher proportion of their ancestry from the lowlander lineage. The numbered circles/rectangles represent point estimates from qpAdm, and the thick and thin vertical segments represent ±1 and ±2 standard error measures (SEM) estimated by 5 cM block jackknifing, respectively.
Fig. 5
Fig. 5. Genetic links between Tibeto-Burman speakers.
Tibetan groups from the Plateau and the Himalayas form a genetic cline, with the two poles represented by present-day Nepalese Tibetans (as well as aMMD) and Upper_YR_LN (“the Tibetan cline”). The non-Tibetan Tibeto-Burman cline reflects admixture along the circum-Plateau route and includes mid-altitude populations such as Naxi, Yi, Naga, Tamang and Gurung. Naxi and Yi cannot be modeled as a part of the Tibetan cline, i.e., Tsum+Upper_YR_LN; instead, YR_MN alone adequately models them. Non-Tibetan Tibeto-Burman speakers have higher contribution from the Tibetan lineage (represented by Nepalese Tibetan Tsum), and far-western mid-altitude populations Tamang and Gurung further have South Asian influx. Squares indicate the source populations used in ancestry models (circles).
Fig. 6
Fig. 6. Genome-wide selection scan using outgroup-f3 statistics with sliding windows.
We computed f3 (Tibetans; aMMD, Han) using a sliding window approach with a window size 500 kb and a step size 10 kb. Z-scores for each window were calculated with a resampling approach (see Methods). Windows spanning the EPAS1 and EGLN1 genes harbor the two top signals.
See this image and copyright information in PMC

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