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Volume 22, Number 6—June 2016
Research

Use of Population Genetics to Assess the Ecology, Evolution, and Population Structure of Coccidioides

Marcus M. Teixeira and Bridget M. BarkerComments to Author 
Author affiliations: Translational Genomics Research Institute, Flagstaff, Arizona, USA (M.M. Teixeira, B.M. Barker); Northern Arizona University, Flagstaff (B.M. Barker); University of Arizona, Tucson, Arizona, USA (B.M. Barker)

Main Article

Figure 1

Results of principal coordinate analysis and STRUCTURE analyses of Coccidioides spp. populations. A) Principal coordinate analysis using Nei’s unbiased genetic distance estimates supports 3 main groupings: C. immitis, C. posadasii TX/SA/MX, and C. posadasii Arizona (see also Technical Appendix 3 Figure 2). The greatest separation occurs between species and is reflected in principal coordinate 1 (93.92% of variance). Color-coding for populations: lime green, San Joaquin Valley (SJV); aqua, San Di

Figure 1. Results of principal coordinate analysis and STRUCTURE analyses of Coccidioides spp. populations. A) Principal coordinate analysis using Nei’s unbiased genetic distance estimates supports 3 main groupings: C. immitis, C. posadasii TX/SA/MX, and C. posadasii Arizona (see also Technical Appendix 3 Figure 2). The greatest separation occurs between species and is reflected in principal coordinate 1 (93.92% of variance). Color-coding for populations: lime green, San Joaquin Valley (SJV); aqua, San Diego/Mexico (SDMX); pink, Texas/South America (TXSA); purple, Mexico (MEXICO); red, Tucson (TUCSON); yellow, Phoenix/Yuma (PHOENIX); orange, soil (AZSOIL). B) STRUCTURE analysis. Microsatellite matrices were analyzed with STRUCTURE 2.3.4 to determine population structure within Coccidioides populations (30). The running length of burn-in period was 100,000 repetitions with 1 million Markov chain Monte Carlo repetitions. Default settings in STRUCTURE 2.3.4 were as follows: the admixture model was used to infer α along with the previous sampling location information model (LOCPRIOR) (30). We used CLUMPP, a cluster matching and permutation program (https://web.stanford.edu/group/rosenberglab/clumpp.html), to define populations within the STRUCTURE algorithm. K is the number of significant populations in each main group. A consensual STRUCTURE plot was generated from the admixture values by using the Clustering Markov Packager Across K (CLUMPAK) server, and final plots were built with STRUCTURE PLOT (32,33).

Main Article

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Page created: May 16, 2016
Page updated: May 16, 2016
Page reviewed: May 16, 2016
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