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Simulations for

Dussex, N., Morales, H. E., Grossen, C., Dalén, L., & van Oosterhout, C. (2023). Purging and accumulation of genetic load in conservation. Trends in Ecology & Evolution
https://www.cell.com/trends/ecology-evolution/fulltext/S0169-5347(23)00131-3

Methods

The model simulated an exome of 10,000 genes of 500 bp each with a recombination rate r=1e-4 (no recombination within genes), and a per base mutation rate m=5e-8. Deleterious selection coefficients (s) were taken from a gamma distribution (mean=-0.05 and shape=0.5) with a tail of 5% of lethal mutation and negative relationship between selection and dominance coefficients (h), following Kardos et al. (2022). We simulated an ancestral population at equilibrium (Ne=10,000) undergoing a severe decline (Ne=10 for 20 generations), followed by a recovery (Ne=2,000 for 20 generations). We calculated the total genetic load and its components, realized and masked load, following the formulas from Bertorelle et al. (2022).

References

Kardos, M., Armstrong, E. E., Fitzpatrick, S. W., Hauser, S., Hedrick, P. W., Miller, J. M., ... & Funk, W. C. (2021). The crucial role of genome-wide genetic variation in conservation. Proceedings of the National Academy of Sciences, 118(48), e2104642118.

Bertorelle, G., Raffini, F., Bosse, M., Bortoluzzi, C., Iannucci, A., Trucchi, E., ... & Van Oosterhout, C. (2022). Genetic load: genomic estimates and applications in non-model animals. Nature Reviews Genetics, 23(8), 492-503.

Code dependencies:

test run

A single replicate for a small run with an ancestral population size Ne=1000

slim -d "K=1000" -d "outPath='./'" -d "outName='out_test'" -d "del_mut=10000" purging_WFnonWF_uncondLoad_exome.slim

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