Essential Site Maintenance: Authorea-powered sites will be updated circa 15:00-17:00 Eastern on Tuesday 5 November.
There should be no interruption to normal services, but please contact us at [email protected] in case you face any issues.

loading page

Integrating Pool-seq uncertainties into demographic inference
  • +2
  • João Carvalho,
  • Hernan Morales,
  • Rui Faria,
  • Roger Butlin,
  • Vitor Sousa
João Carvalho
cE3c - Centre for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Portugal

Corresponding Author:[email protected]

Author Profile
Hernan Morales
Section for Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
Author Profile
Rui Faria
CIBIO - Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO, Laboratório Associado, Universidade do Porto, Vairão, Portugal
Author Profile
Roger Butlin
Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Sheffield, S10 2TN United Kingdom
Author Profile
Vitor Sousa
cE3c - Centre for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Portugal
Author Profile

Abstract

Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modeling Pool-seq sources of error. By jointly modeling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome), and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin), and to infer relevant demographic parameters (e.g., effective sizes, split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e., single origin) and are maintained despite gene flow. These results indicate that demographic modeling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.
13 Apr 2023Submitted to Molecular Ecology Resources
15 Apr 2023Submission Checks Completed
15 Apr 2023Assigned to Editor
15 Apr 2023Review(s) Completed, Editorial Evaluation Pending
17 Apr 2023Reviewer(s) Assigned
17 May 2023Editorial Decision: Revise Minor
15 Jun 20231st Revision Received
19 Jun 2023Submission Checks Completed
19 Jun 2023Assigned to Editor
19 Jun 2023Review(s) Completed, Editorial Evaluation Pending
30 Jun 2023Editorial Decision: Accept