4.7 Article

Fishing for DNA? Designing baits for population genetics in target enrichment experiments: Guidelines, considerations and the new tool supeRbaits

期刊

MOLECULAR ECOLOGY RESOURCES
卷 22, 期 5, 页码 2105-2119

出版社

WILEY
DOI: 10.1111/1755-0998.13598

关键词

ancient DNA; baits; capture sequencing; genomics; population genetics; R-package

资金

  1. Icelandic Research Fund
  2. Innovationsfonden: Udvikling af den danske laksebestand - storre populationer, genetiske ressourcer og rekreativt fiskeri
  3. Danish Council for Independent Research Grant DFF [6108-00583]
  4. Australian Research Grant [DP170102043]

向作者/读者索取更多资源

This research presents specific guidelines and considerations for designing capture sequencing experiments for population genetics, focusing on neutral genomic regions and regions subject to selection. The bait design process for three fish species was described, and the performance of the approach was evaluated across historical and modern samples. The supeRbaits R-package, which implements the workflow used for designing the bait sets, is user-friendly and versatile.
Targeted sequencing is an increasingly popular next-generation sequencing (NGS) approach for studying populations that involves focusing sequencing efforts on specific parts of the genome of a species of interest. Methodologies and tools for designing targeted baits are scarce but in high demand. Here, we present specific guidelines and considerations for designing capture sequencing experiments for population genetics for both neutral genomic regions and regions subject to selection. We describe the bait design process for three diverse fish species: Atlantic salmon, Atlantic cod and tiger shark, which was carried out in our research group, and provide an evaluation of the performance of our approach across both historical and modern samples. The workflow used for designing these three bait sets has been implemented in the R-package supeRbaits, which encompasses our considerations and guidelines for bait design for the benefit of researchers and practitioners. The supeRbaits R-package is user-friendly and versatile. It is written in C++ and implemented in R. supeRbaits and its manual are available from Github:

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