Comparing inferences derived from microsatellite and RADseq datasets: a case study involving threatened bull trout
Technological advancements have allowed geneticists to exploit an increasing array of molecular markers, many of which have different properties and may provide contrasting insights into the evolutionary history and structure of populations. This has important consequences for conservation managers attempting to identify units at which to conserve intraspecific diversity. In this study we compared the inferences derived from nuclear microsatellites and restriction-site associated DNA (RADseq) data for a threatened freshwater fish, the bull trout Salvelinus confluentus. For both marker types we generated data for the same suite of individuals collected from 24 populations distributed across the species range. The RADseq data were low coverage (mean site coverage < 3X), so we implemented a probabilistic genotyping approach. We performed a comparable suite of analyses for both datasets. Both datasets revealed similar broad patterns of subdivision that reflected primary evolutionary lineages (Coastal and Interior clades). However, the RADseq more clearly and consistently identified the hierarchical phylogenetic structure. Some populations had varying assignments to these lineages depending on the dataset. RADseq data also suggested admixture has shaped the genomic character of several populations. Such a signal was not apparent with the microsatellites, suggesting that the datasets are revealing different aspects of population history. Our study provides a valuable case study in how advances in molecular technology can enhance our understanding of a relatively well-studied species. It also underscores the importance of framing findings generated with high-throughput sequencing technology within the context of past research to enhance conservation decision making.
KeywordsSalmonidae Salvelinus confluentus Restriction-site associated DNA sequencing Conservation genomics Intraspecific diversity
Funding for this project was provided by the US Fish and Wildlife Service Fish and Aquatic Conservation Program and Washington State general funds. We sincerely thank the numerous individual biologists and technicians from the different federal, state, tribal, and non-governmental agencies who collected tissue samples used in these analyses. We also thank Sewall Young and Ken Warheit (WDFW) for sharing scripts for running Stacks. The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the US Fish and Wildlife Service.
- Bradbury IR, Hamilton LC, Dempson B et al (2015) Transatlantic secondary contact in Atlantic Salmon, comparing microsatellites, a single nucleotide polymorphism array and restriction-site associated DNA sequencing for the resolution of complex spatial structure. Mol Ecol 24:5130–5144. https://doi.org/10.1111/mec.13395 CrossRefPubMedGoogle Scholar
- Costello AB, Down TE, Pollard SM et al (2003) Influence of history and contemporary stream hydrology on the evolution of genetic diversity within species: an examination of microsatellite DNA variation in bull trout, Salvelinus confluentus (Pisces: Salmonidae). Evolution 57:328. https://doi.org/10.1554/0014-3820(2003)057%5B0328:TIOHAC%5D2.0.CO;2 CrossRefPubMedGoogle Scholar
- DeYoung RW, Honeycutt RL (2008) The molecular toolbox: genetic techniques in wildlife ecology and management. J Wildl Manage 69:1362–1384. https://doi.org/10.2193/0022-541X(2005)69%5B1362:TMTGTI%5D2.0.CO;2 CrossRefGoogle Scholar
- Excoffier L, Foll M, Petit RJ (2009) Genetic consequences of range expansions. Annu Rev Ecol Evol Syst 40:481–501. https://doi.org/10.1146/annurev.ecolsys.39.110707.173414 CrossRefGoogle Scholar
- Hodel RGJ, Chen S, Payton AC et al (2017) Adding loci improves phylogeographic resolution in red mangroves despite increased missing data: comparing microsatellites and RAD-Seq and investigating loci filtering. Sci Rep 7:17598. https://doi.org/10.1038/s41598-017-16810-7 CrossRefPubMedPubMedCentralGoogle Scholar
- McPhail JD, Baxter JS (1996) A review of bull trout (Salvelinus confluentus) life-history and habitat use in relation to compensation and improvement opportunities. Department of Zoology, University of British Columbia, VancouverGoogle Scholar
- Polfus JL, Manseau M, Simmons D et al (2016) Łeghágots’enetę (learning together): the importance of indigenous perspectives in the identification of biological variationGoogle Scholar
- R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. https://www.R-project.org
- Spruell P, Rieman BE, Knudsen KL et al (1999) Genetic population structure within streams: microsatellite analysis of bull trout populations. Ecol Freshw Fish 8:114–121. https://doi.org/10.1111/j.1600-0633.1999.tb00063.x CrossRefGoogle Scholar
- U.S. Fish and Wildlife Service (2015) Recovery plan for the coterminous United States population of bull trout. Portland, ORGoogle Scholar
- Urban J (2014) How does bowtie2 assign MAPQ scores? [Blog] Biofinysics. URL: http://biofinysics.blogspot.com/2014/05/how-does-bowtie2-assign-mapq-scores.html