Analyses of Neanderthal and Denisovan genomes have characterized multiple interbreeding events between archaic and modern human populations. While several studies have suggested the presence of deeply diverged lineages in present-day African populations, we lack methods to precisely characterize these introgression events without access to reference archaic genomes. We present a novel reference-free method that combines diverse population genetic summary statistics to identify segments of archaic ancestry in present-day individuals. Using this method, we find that ~7.97±0.6% of the genetic ancestry from the West African Yoruba population traces its origin to an unidentified, archaic population (FDR ≤20%). We find several loci that harbor archaic ancestry at elevated frequencies and that the archaic ancestry in the Yoruba is reduced near selectively constrained regions of the genome suggesting that archaic admixture has had a systematic impact on the fitness of modern human populations both within and outside of Africa.
To understand the source of archaic ancestry in the Yoruba, we first computed a Neanderthal Match 244 Statistic as before and and found a significant enrichment of Neanderthal matching windows (Figure 6B, P 245 value = 5.87 × 10−37 via block jackknife). It is plausible that this archaic ancestry is, at least partly, the 246 result of Neanderthal introgression into the Yoruba mediated by more recent west Eurasian gene flow into 247 Yoruba [10]. However, the proportion of Neanderthal ancestry in Yoruba is very small (about 2 × 10−4) [10] 248 so that we would not expect this small proportion to explain our signal.
Our results suggest that Yoruban individuals trace about 7.9% of their genomes to an as yet unidentified 287 archaic population. This is in agreement with some results from previous papers in other African populations 288 such as the Biaka and the Baka [15], suggesting that there was a rich diversity of hominin species within Africa 289 and that introgression was commonplace.
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Quote: “More data is needed for a complete picture of these ghost populations. For example, it is unclear whether the archaic signatures found here are from the same as those found in other African populations. One advantage of our approach is that the learning algorithm is general allowing it to be applied broadly to diverse prediction problems as well as input features while its simplicity allows for a transparent interpretation”
-------------------- Without data you are just another person with an opinion - Deming Posts: 12143 | From: When you have eliminated the impossible, whatever remains, however improbable | Registered: Jun 2007
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