Titel
VolcanoFinder: Genomic scans for adaptive introgression
Autor*in
Xiaoheng Cheng
Huck Institutes of the Life Sciences, Pennsylvania State University
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Abstract
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.
Stichwort
IntrogressionGenomicsVolcanoesGenetic footprintingEuropeHaplotypesNeanderthalsGenome analysis
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
phaidra.univie.ac.at/o:1373844
Erschienen in
Titel
PLOS Genetics
Band
16
Ausgabe
6
ISSN
1553-7404
Erscheinungsdatum
2020
Publication
Public Library of Science (PLoS)
Fördergeber
Erscheinungsdatum
2020
Zugänglichkeit
Rechteangabe
© 2020 Setter et al

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