Adaptation in structured populations and fuzzy boundaries between hard and soft sweeps

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Title:Main Title: Adaptation in structured populations and fuzzy boundaries between hard and soft sweeps
Description:Abstract: Selective sweeps, the genetic footprint of positive selection, have been extensively studied in the past decades, with dozens of methods developed to identify swept regions. However, these methods suffer from both false positive and false negative reports, and the candidates identified with different methods are often inconsistent with each other. We propose that a biological cause of this problem can be population subdivision, and a technical cause can be incomplete, or inaccurate, modeling of the dynamic process associated with sweeps. Here we used simulations to show how these effects interact and potentially cause bias. In particular, we show that sweeps maybe misclassified as either hard or soft, when the true time stage of a sweep and that implied, or pre-supposed, by the model do not match. We call this “temporal misclassification”. Similarly, “spatial misclassification (softening)” can occur when hard sweeps, which are imported by migration into a new subpopulation, are falsely identified as soft. This can easily happen in case of local adaptation, i.e. when the sweeping allele is not under positive selection in the new subpopulation, and the underlying model assumes panmixis instead of substructure. The claim that most sweeps in the evolutionary history of humans were soft, may have to be reconsidered in the light of these findings.
Responsible Party
Creators:Yichen Zheng (Author), Thomas Wiehe (Author)
Publication Year:2019
CRC1211 Topic:Biology
Related Subproject:B3
Subjects:Keywords: Evolution, Data Management
Geogr. Information Topic:Biota
File Details
Data Type:Data Paper - Research Paper
File Size:4.5 MB
Date:Issued: 11.11.2019
Mime Type:application/pdf
Data Format:PDF
Download Permission:Free
General Access and Use Conditions:According to the CRC1211DB data policy agreement.
Access Limitations:According to the CRC1211DB data policy agreement.
Licence:[Creative Commons] Attribution 4.0 International (CC BY 4.0)
Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:PLoS Computational Biology
Number of Pages:1 (32767 - 32767)
Metadata Details
Metadata Creator:Yichen Zheng
Metadata Created:23.07.2021
Metadata Last Updated:23.07.2021
Funding Phase:1
Metadata Language:English
Metadata Version:V50
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