Dryad
Published October 14, 2013 | Version v1
Dataset Open

Data from: Using genomic tools to maintain diversity and fitness in conservation programmes

Creators

  • 1. Departamento de Mejora Genética Animal; INIA; Ctra. de La Coruña km. 7.5 28040 Madrid Spain*
  • 2. Technical University of Madrid

Description

Conservation programmes aim at maximising the survival probability of populations, by minimising the loss of genetic diversity, which allows populations to adapt to changes, and controlling inbreeding increases. The best known strategy to achieve these goals is optimising the contributions of the parents, to minimise global coancestry in their offspring. Results on neutral scenarios showed that management based on molecular coancestry could maintain more diversity than management based on genealogical coancestry when a large number of markers is available. However, if the population has deleterious mutations, managing using optimal contributions can lead to a decrease in fitness, especially using molecular coancestry, because both beneficial and harmful alleles are maintained, compromising the long-term viability of the population. We introduce here two strategies to avoid this problem: The first one uses molecular coancestry calculated removing markers with low minor allele frequencies, as they could be linked to selected loci. The second one uses a coancestry based on segments of identity by descent, which measures the proportion of genome segments shared by two individuals because of a common ancestor. We compare these strategies under two contrasting mutational models of fitness effects, one assuming many mutations of small effect and another with few mutations of large effect. Using markers at intermediate frequencies maintains a larger fitness than using all markers, but leads to maintaining less diversity. Using the segment-based coancestry provides a compromise solution between maintaining diversity and fitness, especially when the population has some inbreeding load.

Notes

Codes and data for "Using genomic tools to maintain diversity and fitness in conservation programmes"
Files included in file DryaData.tar.gz : BigPopMSD.f90, genotiposCGD.dat, OCgen_ranmat.f90, OCroh_ranmat.f90, DistFreqsSeg_overReps.f90, genotiposMukai.dat, OCmol_ranmat.f90. Genotype data: genotiposCGD.dat and genotiposMukai.dat are obtained after 10000 generations of mutation-selection-drift with BigPopMSD.f90 for the CGD and the Mukai scenarios, respectively. Population size is kept constant at 1000 diploid individuals (500 females and 500 males), and the genome is assumed to have 20 chromosomes of 1 Morgan each. Every chromosome includes 2000 neutral loci, 1000 selected loci and 1000 marker loci, all of them biallelic. For the CGD scenario, the parameters used are lambda is 0.03, beta is 2.3, mean s is 0.264, and mean h is 0.2. For the Mukai scenario, the parameters used are lambda equals 0.5, beta 1, mean s is 0.05, and mean h equals 0.3. BigPopMSD.f90 generates the base population. OCgen_ranmat.f90 performs 10 generations of optimal contributions for population management with random matings between the individuals who contribute. Contributions are calculated to optimise genealogical coancestry, which is calculated assuming the founder individuals are unrelated. The number of replicates is 100, but can be varied, as well as the population size during management. OCmol_ranmat.f90 performs 10 generations of optimal contributions for population management with random matings between the individuals who contribute. Contributions are calculated to optimise molecular coancestry, calculated as identity by state (see Toro et al 2002, Conservation Genetics). The number of replicates is 100, but can be varied, as well as the population size during management. OCroh_ranmat.f90 performs 10 generations of optimal contributions for population management with random matings between the individuals who contribute. Contributions are calculated to optimise IBD-based coancestry, calculated as the proportion of the genome that is identical by descent between individuals. It is calculated by looking only at marker loci, and it requires a minimum length of a segment for it to be considered identical by descent. The number of replicates is 100, but can be varied, as well as the population size during management. DistFreqsSeg_overReps.f90 analyses replicates from the base population to calculate the average number of markers segregating and the average number of runs of homozygosity in the base population. Note that the codes sometimes assume reading from a file not in the same directory. OC...f90 all read from file ../genotipos_1.dat but that can be easily changed to whichever genotypes you want to read. Should you have any issues, contact angeles.decara AT gmail
DryadData.tar.gz

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README_for_DryadData.tar.txt

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Additional details

Related works

Is cited by
10.1111/mec.12560 (DOI)

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