Tales of Human Migration, Admixture, and Selection in Africa

african-migrations

Comprehensive review (behind paywall) Tales of Human Migration, Admixture, and Selection in Africa, by Carina M. Schlebusch & Mattias Jakobsson, Annual Review of Genomics and Human Genetics (2018), Vol. 9.

Abstract (emphasis mine):

In the last three decades, genetic studies have played an increasingly important role in exploring human history. They have helped to conclusively establish that anatomically modern humans first appeared in Africa roughly 250,000–350,000 years before present and subsequently migrated to other parts of the world. The history of humans in Africa is complex and includes demographic events that influenced patterns of genetic variation across the continent. Through genetic studies, it has become evident that deep African population history is captured by relationships among African hunter–gatherers, as the world’s deepest population divergences occur among these groups, and that the deepest population divergence dates to 300,000 years before present. However, the spread of pastoralism and agriculture in the last few thousand years has shaped the geographic distribution of present-day Africans and their genetic diversity. With today’s sequencing technologies, we can obtain full genome sequences from diverse sets of extant and prehistoric Africans. The coming years will contribute exciting new insights toward deciphering human evolutionary history in Africa.

Regarding potential Afroasiatic origins and expansions:

It is currently believed that farming practices in northeastern and eastern Africa developed independently in the Sahara/Sahel (around 7,000 BP) and the Ethiopian highlands (7,000–4,000 BP), while farming in the Nile River Valley developed as a consequence of the Neolithic Revolution in the Middle East (84). Northeastern and eastern African farmers today speak languages from the Afro-Asiatic and Nilo-Saharan linguistic groups, which is also reflected in their genetic affinities (Figure 3, K=6). In the northern parts of East Africa (South Sudan, Somalia, and Ethiopia), Nilo-Saharan and Afro-Asiatic speakers with farming lifeways have completely replaced hunter–gatherers. It is still largely unclear how farming and herding practices influenced the northeastern African prefarming population structure and whether the spread of farming is better explained by demic or cultural diffusion in this part of the world. Genetic studies of contemporary populations and aDNA have started to provide some insights into population continuity and incoming gene flow in this region of Africa.

african-demographic-history
Demographic model of African history and estimated divergences. (a) Population split times, hierarchy, and population sizes (summarized from 123). Horizontal width represents population size; horizontal colored lines represent migrations, with down-pointing triangles indicating admixture into another group. (b) Population structure analysis at 5 assumed ancestries (K=5) for 93 African and 6 non-African populations. Non-Africans (brown), East Africans (blue), West Africans ( green), central African hunter–gatherers (light blue), and Khoe-San (red ) populations are sorted according to their broad historical distributions.

For example, studies have shown that a back-migration from Eurasia into Africa affected most of northeastern and eastern Africa (36, 46, 53, 89, 132) (Figure 1b). A genetic baseline of eastern African ancestral genetic variation unaffected by recent Eurasian admixture and farming migrations within the last 4,500 years has been suggested in the form of the genome sequence of a 4,500-year-old individual from Mota, Ethiopia (36). Based on comparisons with the ancient Mota genome, we know that certain populations from northeastern Africa show deep continuity in their local area with very limited gene flow resulting from recent population movements. For example, the Nilotic herder populations from South Sudan (e.g., Dinka, Nuer, and Shilluk) appear to have remained relatively isolated over time and received little to no gene flow from Eurasians, West African Bantu-speaking farmers, and other surrounding groups (53) (Figures 2 and 3). By contrast, the Nubian and Arab populations to their north show gene flow with Eurasians, which has been connected to the Arab expansion (53). The Nubian, Arab, and Beja populations of northeastern Africa roughly display equal admixture fractions from a local northeastern African gene pool (similar to the Nilotic component) and an incoming Eurasian migrant component (53) (Figure 3). The Eurasian component has been linked to the Middle East and the Arab migration, but only the Arab groups shifted to the Semitic languages; the Nubians and Beja groups kept their original languages. The Eurasian gene flow appears to have spread from north to south along the Nile and Blue Nile in a succession of admixture events (53).

Skoglund and Mathieson’s preprint has also been published in the same volume, without meaningful changes.

Related:

Effective migration in Western Eurasia reveals fine-scale migration surface features

map-effective-migration-eurasia

Interesting poster from SMBE 2017, Maps of effective migration as a summary of global human genetic diversity, by Benjamin Peter, Desislava Petkova, Matthew Stephens & John Novembre, of the JNPopGen group of the University of Chicago.

You can read the full poster in the original PDF, or in compressed image. The following are important excerpts:

Aim: To answer the following questions:

  • Which regions have high/low effective migration?
  • How well is human genetic diversity explained by this pure isolation-by-distance model?
  • How does the explanatory performance of EEMS compare to PCA?

Method: It uses the method proposed by Petkova et al. (2016) to fit a map of time-averaged (effective) migration rates to geographically referenced samples, and merges data from 24 different studies (8740 individuals from 469 populations) to assess human genetic diversity on global and continental scale.

  1. Basic workflow:
    • Merge data, remove duplicated & related individuals.
    • Remove Hunter-Gatherer and recently admixed populations. Their locations are still indicated with (H) and (X), respectively
  2. EEMS analysis
    • Calculate genetic distance matrix between all individuals.
    • Fit migration map to data using EEMS MCMC algorithm
  3. Comparison to PCA: Standard PCA using flashpca (Abraham & Inouye 2014) was used, they compare correlation of genetic distance induced from first ten PCs with the fitted EEMS distance

Interpretation: A continuous habitat is approximated by a discrete grid (light gray). A Bayesian model is used to infer the most likely migration rates, which are given on a log scale compared to the Average (BLUE= 100x higher, BROWN=100x lower

map-effective-migrations-europe
Map of effective migrations in Europe

Results (see maps):

  1. Global diversity patterns correlate with topographical features
  2. In Western Eurasia, EEMS reveals fine-scale migration surface features

Discussion: EEMS Maps are intuitive and direct way to visualize geographically referenced genetic data.

Dense sampling (WEstern Eurasian panel) in particular yields high resolution and accuracy, but the method works well at a global scale (FST=0.06) and just in Western Eurasia (FST=0.01).

EEMS-maps are able to reasonably well predict genetic differences, but hunter-gatherer populations and admixed populations were a priori excluded.

Discovered via Eurogenes. Full image via Reddit.