Hilaria jamesii data for the Colorado Plateau of the southwestern United States
These data were compiled to investigate the demographic, phylogeographic, and adaptation history of Hilaria jamesii. The data release consists of three tab delimited text files that may be used to infer population structure or putative adaptive loci (hija_adaptation_dataset.stru), relationships among sampling localities (hija_phylogeny_dataset.phylip), or genetic diversity statistics (hija_diversity_stats.vcf). All files record genetic variation on an individual (.stru and .vcf) or sampling locality (.phylip) level. The .vcf file contains all of the information contained in the other files, but the file structures vary based on the programs used for analysis. These files may be opened and edited in a text editor program, such as Notepad ++ (PC) or BBEdit (Mac). The .vcf file can be loaded into the Stacks population program (Catchen et al. 2013) to calculate genetic diversity statistics. The .phylip file can be uploaded to phyML to generate a tree-based visualization of relationships ( http://www.atgc-montpellier.fr/phyml/). The .stru file can be used in the STRUCTURE program (Falush et al. 2007) to estimate population structure.
Citation Information
| Publication Year | 2020 |
|---|---|
| Title | Hilaria jamesii data for the Colorado Plateau of the southwestern United States |
| DOI | 10.5066/P9CNFWOX |
| Authors | Robert T Massatti |
| Product Type | Data Release |
| Record Source | USGS Digital Object Identifier Catalog |
| USGS Organization | Southwest Biological Science Center - Flagstaff, AZ, Headquarters |
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The process of adaptation can be highly dependent upon historical and contemporary factors, especially in environmentally and topographically complex regions affected by Pleistocene glaciations. Here, we investigate Hilaria jamesii (Poaceae), a dryland C4 graminoid, to test how patterns of adaptive genetic variation are linked to its glacial and post‐glacial history. We show that the species persiAuthorsRobert Massatti, L. Lacey Knowles - Connect