Data from: Estimating relatedness and inbreeding using molecular markers and pedigrees: the effect of demographic history

Dataset

Description

file 1 - x0 data for MasterBayes.txt (24.93 Kb):
Microsatellite 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 MasterBayes.txt (24.13 Kb)

file 3 - x5 data for MasterBayes.txt (25.38 Kb)

file 4 - x0 data for MasterBayes null alleles removed.txt (18.17 Kb):
Microsatellite 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 removed.txt (15.30 Kb):
Microsatellite 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 reomoved.txt (18.28 Kb):
Microsatellite 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 list.xlsx (56.36 Kb):
List 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 populations.R (6.758 Kb):
This 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).R (8.492 Kb)

file 10 - R code for simulated bottleneck in the N (13.39 Kb):
This 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 11 - R code for simulated bottleneck in the N (14.40 Kb):
This 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 12 - R code for simulated bottleneck in the N (10.27 Kb):
This 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 13 - R code for simulated bottleneck in the N (11.12 Kb):
This 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 14 - R code for simulations with null alleles introduced to all loci with frequency = 0.05 (6.235 Kb):
This 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 15 - R code for simulations with null alleles introduced to three loci or three loci removed.R (12.16 Kb):
This 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 only.txt (16.16 Kb):
Microsatellite 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 only.txt (10.85 Kb):
Microsatellite 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 only.txt (15.48 Kb):
Microsatellite 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 only.txt (10.44 Kb):
Microsatellite 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 only.txt (16.45 Kb):
Microsatellite 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 only.txt (11.11 Kb):
Microsatellite 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 5percen...ls.txt (25.66 Kb):
Microsatellite 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 - pedigree.txt (4.956 Kb):
Pedigree, 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 relatedness.txt (162.5 Kb):
List 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_f.txt (726 bytes):
List of inbreeding coefficients for each final generation individual in the pedigree.

file 26 - pedigree for founder simulation.txt (3.701 Kb):
Pedigree used in simulation of bottlenecks.

file 27 - bottleneck pedigree for x1 founder simulation.txt (131 bytes):
Pedigree needed as part of simulate the n = 10 x 1 bottleneck while maintaining variance in individual IBD.

file 28 - bottleneck pedigree for x5 founder simulation.txt (713 bytes):
Pedigree needed as part of simulate the n = 10 x 5 bottleneck while maintaining variance in individual IBD.

list of file names and descriptions.txt (10.30 Kb)

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.
Date made available16 Sep 2013
PublisherDryad Digital Repository
Geographical coverageMargaret River, Western Australia, Australia, 33.95 °S, 115.07 °E

Keywords

  • Heterozygosity
  • Relatedness
  • Population Bottleneck
  • Null Allele
  • Inbreeding
  • Drosophila melanogaster

Cite this

Robinson, S. P. (Creator), Simmons, L. W. (Creator), Kennington, W. (Creator)(16 Sep 2013). Data from: Estimating relatedness and inbreeding using molecular markers and pedigrees: the effect of demographic history. Dryad Digital Repository. 10.5061/dryad.060b1