VolcanoFinder: Genomic scans for adaptive introgression

English version

Autoři: Derek Setter ^aff001; Sylvain Mousset ^aff001; Xiaoheng Cheng ^aff004; Rasmus Nielsen ^aff005; Michael DeGiorgio ^aff006; Joachim Hermisson ^aff001
Působiště autorů: Department of Mathematics, University of Vienna, Vienna, Austria ^aff001; Vienna Graduate School of Population Genetics, Vienna, Austria ^aff002; School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom ^aff003; Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America ^aff004; Departments of Integrative Biology and Statistics, University of California, Berkeley, Berkeley, California, USA ^aff005; Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida, USA ^aff006; Max F. Perutz Laboratories, University of Vienna, Vienna, Austria ^aff007
Vyšlo v časopise: VolcanoFinder: Genomic scans for adaptive introgression. PLoS Genet 16(6): e32767. doi:10.1371/journal.pgen.1008867
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1008867

Souhrn

Recent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method—VolcanoFinder—to detect recent events of adaptive introgression using polymorphism data from the recipient species only. VolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity. Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder.

Klíčová slova:

Alleles – Europe – Genetic footprinting – Genomic signal processing – Haplotypes – Introgression – Neanderthals – Volcanoes

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