DOI: 10.5061/dryad.060b1
title: Data from: Estimating relatedness and inbreeding using molecular markers and pedigrees: the effect of demographic history

description: Estimates of inbreeding and relatedness are commonly calculated using
 molecular markers, although the accuracy of such estimates has been
 questioned. As a further complication, in many situations, such estimates
 are required in populations with reduced genetic diversity, which is
 likely to affect their accuracy. We investigated the correlation between
 microsatellite- and pedigree-based coefficients of inbreeding and
 relatedness in laboratory populations of Drosophila melanogaster that had
 passed through bottlenecks to manipulate their genetic diversity. We also
 used simulations to predict expected correlations between marker- and
 pedigree-based estimates and to investigate the influence of linkage
 between loci and null alleles. Our empirical data showed lower
 correlations between marker- and pedigree-based estimates in our control
 (nonbottleneck) population than were predicted by our simulations or those
 found in similar studies. Correlations were weaker in bottleneck
 populations, confirming that extreme reductions in diversity can
 compromise the ability of molecular estimates to detect recent inbreeding
 events. However, this result was highly dependent on the strength of the
 bottleneck and we did not observe or predict any reduction in correlations
 in our population that went through a relatively severe bottleneck of N =
 10 for one generation. Our results are therefore encouraging, as molecular
 estimates appeared robust to quite severe reductions in genetic diversity.
 It should also be remembered that pedigree-based estimates may not capture
 realized identity-by-decent and that marker-based estimates may actually
 be more useful in certain situations.
description: file 1 - x0 data for
 MasterBayesMicrosatellite genotypes
 observed in the experimental control population formatted for the
 MasterBayes package in R. This file must be in the working directory of R
 for many of the simulations below to run. Markers are named using internal
 lab id numbers, see accompanying file for how these relate to locus
 names.file 2 - x1 data for
 MasterBayesfile 3 - x5 data for
 MasterBayesfile 4 - x0 data for
 MasterBayes null alleles removedMicrosatellite genotypes
 observed in the experimental control population formatted for the
 MasterBayes package in R with loci indicated by MICRO-CHECKER as
 containing null alleles removed. Markers are named using internal lab id
 numbers, see accompanying file (Microsatellite list) for how these relate
 to locus names.file 5 - x1 data for
 MasterBayes null alleles removedMicrosatellite genotypes
 observed in the experimental N = 10 x 1 population formatted for the
 MasterBayes package in R with loci indicated by MICRO-CHECKER as
 containing null alleles removed. Markers are named using internal lab id
 numbers, see accompanying file (Microsatellite list) for how these relate
 to locus names.file 6 - x5 data for
 MasterBayes null alleles reomovedMicrosatellite genotypes
 observed in the experimental N = 10 x 5 population formatted for the
 MasterBayes package in R with loci indicated by MICRO-CHECKER as
 containing null alleles removed. Markers are named using internal lab id
 numbers, see accompanying file (Microsatellite list) for how these relate
 to locus names.file 7 - Microsatellite
 listList of internal lab id
 numbers used to label loci in accompanying files along with locus names
 and genetic locations.file 8 - R code for
 simulations based on allele frequencies in experimental
 populationsThis code runs
 simulations based on observed allele frequencies in experimental
 populations. This method does not take linkage into account. The output
 will include mean and 95% confidence intervals for both relatedness and
 inbreeding estimates. Instructions on the first line detail how to change
 the input for the desired population. This code links to the following
 files, which must be in the working directory: files 1 - 3, and file 23 -
 25.file 9 - R code for
 simulations based on allele frequencies in experimental populations
 (linkage taken into account)file 10 - R code for
 simulated bottleneck in the N=10 x1 populationThis code runs a
 simulation of the bottleneck and subsequent pedigree used for the N=10 x1
 population. Once the bottleneck is simulated, only the allele frequencies
 are used to generate the subsequent pedigree so variance in individual IBD
 generated during the bottleneck is not retained. This method takes linkage
 into account. The output will include mean and 95% confidence intervals
 for both relatedness and inbreeding estimates as well as number of alleles
 per locus. This code links to the following files, which must be in the
 working directory: files 16 – 17 and files 23 – 27.file 10 - R code for simulated
 bottleneck in the Nfile 11 - R code for
 simulated bottleneck in the N=10 x5 populationThis code runs a
 simulation of the bottleneck and subsequent pedigree used for the N=10 x5
 population. Once the bottleneck is simulated, only the allele frequencies
 are used to generate the subsequent pedigree so variance in individual IBD
 generated during the bottleneck is not retained. This method takes linkage
 into account. The output will include mean and 95% confidence intervals
 for both relatedness and inbreeding estimates as well as number of alleles
 per locus. This code links to the following files, which must be in the
 working directory: files 16 – 17, files 23 – 26 and file
 28.file 11
 - R code for simulated bottleneck in the
 Nfile 12 - R code for
 simulated bottleneck in the N=10 x1 population with variance in individual
 IBD retainedThis code runs a
 simulation of the bottleneck and subsequent pedigree used for the N=10 x1
 population. Variance in individual IBD generated during the bottleneck
 retained through the pedigree. This method takes linkage into account. The
 output will include mean and 95% confidence intervals for both relatedness
 and inbreeding estimates as well as number of alleles per locus. This code
 links to the following files, which must be in the working directory:
 files 16 – 17 and files 24 – 27.file 12 - R code for simulated
 bottleneck in the Nfile 13 - R code for
 simulated bottleneck in the N=10 x5 population with variance in individual
 IBD retainedThis code runs a
 simulation of the bottleneck and subsequent pedigree used for the N=10 x5
 population. Variance in individual IBD generated during the bottleneck
 retained through the pedigree. This method takes linkage into account. The
 output will include mean and 95% confidence intervals for both relatedness
 and inbreeding estimates as well as number of alleles per locus. This code
 links to the following files, which must be in the working directory:
 files 16 – 17, files 24 – 26 and file 28.file 13 - R code for simulated
 bottleneck in the Nfile 14 - R code for
 simulations with null alleles introduced to all loci with frequency =
 0.05This code runs
 simulations based on observed allele frequencies in the control population
 but with null alleles artificially introduced to all loci at a frequency
 of 0.05. This method does not take linkage into account. The output will
 include mean and 95% confidence intervals for both relatedness and
 inbreeding estimates. This code links to the following files, which must
 be in the working directory: files 22 – 25.file 14 - R code for
 simulations with null alleles introduced to all loci with frequency
 file 15 - R code for
 simulations with null alleles introduced to three loci or three loci
 removedThis code runs
 simulations based on observed allele frequencies in the control population
 but with null alleles artificially introduced to three randomly selected
 loci at a frequency of 0.05 or these same three loci removed from the data
 set. This method does not take linkage into account. The output will
 include mean and 95% confidence intervals for both relatedness and
 inbreeding estimates. This code links to the following files, which must
 be in the working directory: file 1 and files 22 – 25.file 16 - x0 data for
 MasterBayes cr2 onlyMicrosatellite genotypes
 for markers residing on chromosome two observed in the experimental
 control population formatted for the MasterBayes package in R. This file
 must be in the working directory of R for many of the simulations above to
 run.file 17 - x0 data for
 MasterBayes cr3 onlyMicrosatellite genotypes
 for markers residing on chromosome three observed in the experimental
 control population formatted for the MasterBayes package in R. This file
 must be in the working directory of R for many of the simulations above to
 run.file 18 - x1 data for
 MasterBayes cr2 onlyMicrosatellite genotypes
 for markers residing on chromosome two observed in the experimental N = 10
 x 1 population formatted for the MasterBayes package in R. This file must
 be in the working directory of R for many of the simulations above to
 run.file 19 - x1 data for
 MasterBayes cr3 onlyMicrosatellite genotypes
 for markers residing on chromosome three observed in the experimental N =
 10 x 1 population formatted for the MasterBayes package in R. This file
 must be in the working directory of R for many of the simulations above to
 run.file 20 - x5 data for
 MasterBayes cr2 onlyMicrosatellite genotypes
 for markers residing on chromosome two observed in the experimental N = 10
 x 5 population formatted for the MasterBayes package in R. This file must
 be in the working directory of R for many of the simulations above to
 run.file 21 - x5 data for
 MasterBayes cr3 onlyMicrosatellite genotypes
 for markers residing on chromosome three observed in the experimental N =
 10 x 5 population formatted for the MasterBayes package in R. This file
 must be in the working directory of R for many of the simulations above to
 run.file 22 - x0 data for
 MasterBayes 5percent nullsMicrosatellite genotypes
 observed in the experimental control population formatted for the
 MasterBayes package in R with null alleles artificially encoded at a
 frequency of 0.05. This file must be in the working directory of R for
 many of the simulations above to run.file 23 -
 pedigreePedigree, formatted for
 the pedantics package in R, which is the same as that which was used to
 generate individuals of varying inbreeding and relatedness in our
 experimental populations. This file must be in the working directory of R
 for many of the simulations above to run.file 24 - pedigree
 relatednessList of pairwise
 coefficient of relatedness between possible combination of final
 generation individuals in the pedigree. This file must be in the working
 directory of R for many of the simulations above to
 run.file 25 -
 expected_fList of inbreeding
 coefficients for each final generation individual in the
 pedigree.file 26 - pedigree for
 founder simulationPedigree used in
 simulation of bottlenecks.file 27 - bottleneck
 pedigree for x1 founder simulationPedigree needed as part
 of simulate the n = 10 x 1 bottleneck while maintaining variance in
 individual IBD.file 28 - bottleneck
 pedigree for x5 founder simulationPedigree needed as part
 of simulate the n = 10 x 5 bottleneck while maintaining variance in
 individual IBD.list of file names and
 descriptions