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ABSTRACT Although patterns of population genomic variation are well‐studied in animals, there remains room for studies that focus on non‐model taxa with unique biologies. Here we characterise and attempt to explain such patterns in mygalomorph spiders, which are generally sedentary, often occur as spatially clustered demes and show remarkable longevity. Genome‐wide single nucleotide polymorphism (SNP) data were collected for 500 individuals across a phylogenetically representative sample of taxa. We inferred genetic populations within focal taxa using a phylogenetically informed clustering approach, and characterised patterns of diversity and differentiation within‐ and among these genetic populations, respectively. Using phylogenetic comparative methods we asked whether geographical range sizes and ecomorphological variables (behavioural niche and body size) significantly explain patterns of diversity and differentiation. Specifically, we predicted higher genetic diversity in genetic populations with larger geographical ranges, and in small‐bodied taxa. We also predicted greater genetic differentiation in small‐bodied taxa, and in burrowing taxa. We recovered several significant predictors of genetic diversity, but not genetic differentiation. However, we found generally high differentiation across genetic populations for all focal taxa, and a consistent signal for isolation‐by‐distance irrespective of behavioural niche or body size. We hypothesise that high population genetic structuring, likely reflecting combined dispersal limitation and microhabitat specificity, is a shared trait for all mygalomorphs. Few studies have found ubiquitous genetic structuring for an entire ancient and species‐rich animal clade.
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ONeSAMP 3.0: estimation of effective population size via single nucleotide polymorphism data from one population
Abstract The genetic effective size (Ne) is arguably one of the most important characteristics of a population as it impacts the rate of loss of genetic diversity. Methods that estimate Ne are important in population and conservation genetic studies as they quantify the risk of a population being inbred or lacking genetic diversity. Yet there are very few methods that can estimate the Ne from data from a single population and without extensive information about the genetics of the population, such as a linkage map, or a reference genome of the species of interest. We present ONeSAMP 3.0, an algorithm for estimating Ne from single nucleotide polymorphism data collected from a single population sample using approximate Bayesian computation and local linear regression. We demonstrate the utility of this approach using simulated Wright–Fisher populations, and empirical data from five endangered Channel Island fox (Urocyon littoralis) populations to evaluate the performance of ONeSAMP 3.0 compared to a commonly used Ne estimator. Our results show that ONeSAMP 3.0 is broadly applicable to natural populations and is flexible enough that future versions could easily include summary statistics appropriate for a suite of biological and sampling conditions. ONeSAMP 3.0 is publicly available under the GNU General Public License at https://github.com/AaronHong1024/ONeSAMP_3.
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- Award ID(s):
- 2013998
- PAR ID:
- 10533833
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- G3: Genes, Genomes, Genetics
- ISSN:
- 2160-1836
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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