At the dawn of the second millennium, the expansion of the Indian Ocean trading network aligned with the emergence of an outward-oriented community along the East African coast to create a cosmopolitan cultural and trading zone known as the Swahili Corridor. On the basis of analyses of new genome-wide genotyping data and uniparental data in 276 individuals from coastal Kenya and the Comoros islands, along with large-scale genetic datasets from the Indian Ocean rim, we reconstruct historical population dynamics to show that the Swahili Corridor is largely an eastern Bantu genetic continuum. Limited gene flows from the Middle East can be seen in Swahili and Comorian populations at dates corresponding to historically documented contacts. However, the main admixture event in southern insular populations, particularly Comorian and Malagasy groups, occurred with individuals from Island Southeast Asia as early as the 8th century, reflecting an earlier dispersal from this region. Remarkably, our results support recent archaeological and linguistic evidence-based suggestions that the Comoros archipelago was the earliest location of contact between Austronesian and African populations in the Swahili Corridor.
Pubmed ID: 29304377 RIS Download
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A software tool for maximum likelihood estimation of individual ancestries from multilocus SNP genotype datasets. It uses the same statistical model as STRUCTURE but calculates estimates much more rapidly using a fast numerical optimization algorithm. It uses a block relaxation approach to alternately update allele frequency and ancestry fraction parameters. Each block update is handled by solving a large number of independent convex optimization problems, which are tackled using a fast sequential quadratic programming algorithm. Convergence of the algorithm is accelerated using a novel quasi-Newton acceleration method.
View all literature mentionsSoftware platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
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