10.5061/DRYAD.V6726
Barley, Anthony J.
University of Kansas
Monnahan, Patrick J.
University of Kansas
Thomson, Robert C.
University of Kansas
Grismer, L. Lee
La Sierra University
Brown, Rafe M.
University of Kansas
Data from: Sun skink landscape genomics: assessing how microevolutionary
processes shape genetic and phenotypic diversity across a heterogeneous
and fragmented landscape
Dryad
dataset
2015
Fst-Pst comparisons
population differentiation
ocean channels
Eutropis multifasciata
2015-03-12T17:24:43Z
2015-03-12T17:24:43Z
en
https://doi.org/10.1111/mec.13151
198956302 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Incorporating genomic data sets into landscape genetic analyses allows for
powerful insights into population genetics, explicitly geographical
correlates of selection, and morphological diversification of organisms
across the geographical template. Here, we utilize an integrative approach
to examine gene flow and detect selection, and we relate these processes
to genetic and phenotypic population differentiation across South-East
Asia in the common sun skink, Eutropis multifasciata. We quantify the
relative effects of geographic and ecological isolation in this system and
find elevated genetic differentiation between populations from island
archipelagos compared to those on the adjacent South-East Asian continent,
which is consistent with expectations concerning landscape fragmentation
in island archipelagos. We also identify a pattern of isolation by
distance, but find no substantial effect of ecological/environmental
variables on genetic differentiation. To assess whether morphological
conservatism in skinks may result from stabilizing selection on
morphological traits, we perform FSTāPST comparisons, but observe that
results are highly dependent on the method of comparison. Taken together,
this work provides novel insights into the manner by which
micro-evolutionary processes may impact macro-evolutionary scale
biodiversity patterns across diverse landscapes, and provide genomewide
confirmation of classic predictions from biogeographical and landscape
ecological theory.
Allele Frequency DataThis file contains allele frequency data for each of
the 14 populations used in the fst-pst analyses. The format of the file
format for each population is as follows, for each line: locus number, the
total number of genes in the population for the locus, the number of
alleles for the locus, the number of copies of each allele in the
population.AlleleFrequency.csvBarcodesThis file contains information on
the barcode sequence assigned to each individual in our
study.StructureThis is a structure formatted file containing genotypic
data for each individual used in the
study.batch_2structure.strBEDASSLEThis is an R object file that was used
to run the BEDASSLE analyses.BootstrapThis R script contains the code for
the bootstrapping procedure for obtaining confidence intervals for the
global pst data as described in the manuscript.Calculate_FstsThis python
script contains the code for calculating global Fst's for each locus
as described in the manuscript.Calc_Fsts.pyFastSimCoalThis archive
contains the files used to run fastsimcoal2 to obtain the
isolation-migration parameter estimates as in the
manuscript.Fst_BootstrapThis R script contains the code for calculating
bootstrapped confidence intervals for global Fst as described in the
manuscript.Fst_boot.RIBDWSThis text file contains the distance matrix
information used for testing for isolation by distance using the Isolation
by distance web server.Maxent ASCIIThis is the habitat suitability output
file from Maxent.multifasciata.ascMorphological DataThis file contains the
morphological data used for calculating Psts.MorphData.csvPopulation
CoordinatesThis file contains the geographic coordinates (WGS84) for each
population used in the landscape genetic
analyses.PopulationCoordinates.csv
Southeast Asia