PT - JOURNAL ARTICLE AU - Anthony Wilder Wohns AU - Yan Wong AU - Ben Jeffery AU - Ali Akbari AU - Swapan Mallick AU - Ron Pinhasi AU - Nick Patterson AU - David Reich AU - Jerome Kelleher AU - Gil McVean TI - A unified genealogy of modern and ancient genomes AID - 10.1101/2021.02.16.431497 DP - 2021 Jan 01 TA - bioRxiv PG - 2021.02.16.431497 4099 - http://biorxiv.org/content/early/2021/02/17/2021.02.16.431497.short 4100 - http://biorxiv.org/content/early/2021/02/17/2021.02.16.431497.full AB - The sequencing of modern and ancient genomes from around the world has revolutionised our understanding of human history and evolution1,2. However, the general problem of how best to characterise the full complexity of ancestral relationships from the totality of human genomic variation remains unsolved. Patterns of variation in each data set are typically analysed independently, and often using parametric models or data reduction techniques that cannot capture the full complexity of human ancestry3,4. Moreover, variation in sequencing technology5,6, data quality7 and in silico processing8,9, coupled with complexities of data scale10, limit the ability to integrate data sources. Here, we introduce a non-parametric approach to inferring human genealogical history that overcomes many of these challenges and enables us to build the largest genealogy of both modern and ancient humans yet constructed. The genealogy provides a lossless and compact representation of multiple datasets, addresses the challenges of missing and erroneous data, and benefits from using ancient samples to constrain and date relationships. Using simulations and empirical analyses, we demonstrate the power of the method to recover relationships between individuals and populations, as well as to identify descendants of ancient samples. Finally, we show how applying a simple nonparametric estimator of ancestor geographical location to the inferred genealogy recapitulates key events in human history. Our results demonstrate that whole-genome genealogies are a powerful means of synthesising genetic data and provide rich insights into human evolution.Competing Interest StatementGM is a director of and shareholder in Genomics plc and a partner in Peptide Groove LLP.