5 research outputs found

    Three different sampling strategies for real data from the buffalo.

    No full text
    <p><i>Local</i>, <i>pooled</i> and <i>scattered</i> sampling of real D-loop data from 34 African buffalo populations. The replication of each sampling strategy involved random drawing of the appropriate number of samples from demes as explained in the main text.</p

    Comparison of EBSP and simulated population sizes under different structural scenarios.

    No full text
    <p>Comparison of EBSP and simulated population sizes under different structural scenarios.</p

    The structure effect in a 40-deme constant-size island model.

    No full text
    <p>For each scenario, 100 replicate data sets were generated and analysed with EBSPs. Light blue lines represent the median inferred female effective population size through time from each replicate. Time is measured in kya or thousands of years ago and is based on a molecular clock for buffalo D-loop sequences. Bold black lines represent the simulated size of the structured population (500 females * 40 demes = 20,000 females). Insert into each panel is a histogram of PSC values (on x-axis; see main text) across replicates. Dashed lines show the prior distribution for PSC. The y-axis in the insert histograms marks the frequency of occurrence in each PSC bin out of 100 replicates.</p

    The structure effect in a 40-deme island model with demographic change.

    No full text
    <p>As <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062992#pone-0062992-g001" target="_blank">Fig. 1</a>, but the bold black line shows the simulated demographic change scenarios (see main text) with one or two changes in population size. Only the intermediary level of gene flow (N<sub>f</sub>m = 1.25) is shown.</p

    Dataset1 and putative SNPs under selection

    No full text
    Dataset 1 contains the called genotypes for 60 plains zebras, 3 Grevy's zebras, 3 mountain zebras and one Quagga zebra. A total of 98,512 SNPs were called. The data is based on the RADseq technology. We used a missingness filter of 0.2 and excluded monomorphic sites.<div><br></div><div>We also include a list of SNPs inferred from pcadapt, which are putatively under selection.<br><div><br></div></div
    corecore