The distribution of heterozygosity in a population is commonly used to quantify inbreeding depression through the use of heterozygosity-fitness correlations (HFCs), but the demographic processes shaping variability in inbreeding are not well understood. For 11 years, we measured heterozygosity and six fitness proxies in a population of the self-incompatible plant Antirrhinum majus. Using a panel of 91 SNPs in 22,353 individuals, we find that relatedness declines rapidly over short spatial scales. Excess variance in heterozygosity between individuals (identity disequilibrium, g2) reflects significant variation in inbreeding. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial patterns of mating and population structure. First, we simulate offspring from matings with fathers at different distances, showing that the pollen dispersal kernel affects expected g2. Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that g2 is consistent with that observed. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Finally, we estimate inbreeding depression through HFCs. Only flowering stem count increases with heterozygosity. Our study shows that heterogeneous density and leptokurtic dispersal can together explain pairwise FST and the distribution of heterozygosity.Competing Interest StatementThe authors have declared no competing interest.
%0 Journal Article
%1 arathoon2021effects
%A Arathoon, Louise
%A Surendranadh, Parvathy
%A Barton, Nicholas
%A Field, David L.
%A Pickup, Melinda
%A Baskett, Carina A.
%D 2021
%I Cold Spring Harbor Laboratory
%J bioRxiv
%K Antirrhinum clines inbreeding snapdragons spatial_demography
%R 10.1101/2020.08.20.259036
%T Effects of fine-scale population structure on inbreeding in a long-term study of snapdragons (Antirrhinum majus)
%U https://www.biorxiv.org/content/early/2021/03/12/2020.08.20.259036
%X The distribution of heterozygosity in a population is commonly used to quantify inbreeding depression through the use of heterozygosity-fitness correlations (HFCs), but the demographic processes shaping variability in inbreeding are not well understood. For 11 years, we measured heterozygosity and six fitness proxies in a population of the self-incompatible plant Antirrhinum majus. Using a panel of 91 SNPs in 22,353 individuals, we find that relatedness declines rapidly over short spatial scales. Excess variance in heterozygosity between individuals (identity disequilibrium, g2) reflects significant variation in inbreeding. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial patterns of mating and population structure. First, we simulate offspring from matings with fathers at different distances, showing that the pollen dispersal kernel affects expected g2. Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that g2 is consistent with that observed. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Finally, we estimate inbreeding depression through HFCs. Only flowering stem count increases with heterozygosity. Our study shows that heterogeneous density and leptokurtic dispersal can together explain pairwise FST and the distribution of heterozygosity.Competing Interest StatementThe authors have declared no competing interest.
@article{arathoon2021effects,
abstract = {The distribution of heterozygosity in a population is commonly used to quantify inbreeding depression through the use of heterozygosity-fitness correlations (HFCs), but the demographic processes shaping variability in inbreeding are not well understood. For 11 years, we measured heterozygosity and six fitness proxies in a population of the self-incompatible plant Antirrhinum majus. Using a panel of 91 SNPs in 22,353 individuals, we find that relatedness declines rapidly over short spatial scales. Excess variance in heterozygosity between individuals (identity disequilibrium, g2) reflects significant variation in inbreeding. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial patterns of mating and population structure. First, we simulate offspring from matings with fathers at different distances, showing that the pollen dispersal kernel affects expected g2. Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that g2 is consistent with that observed. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Finally, we estimate inbreeding depression through HFCs. Only flowering stem count increases with heterozygosity. Our study shows that heterogeneous density and leptokurtic dispersal can together explain pairwise FST and the distribution of heterozygosity.Competing Interest StatementThe authors have declared no competing interest.},
added-at = {2021-04-07T18:08:42.000+0200},
author = {Arathoon, Louise and Surendranadh, Parvathy and Barton, Nicholas and Field, David L. and Pickup, Melinda and Baskett, Carina A.},
biburl = {https://www.bibsonomy.org/bibtex/200296b82b8b330aadd287aca44d8e2f3/peter.ralph},
doi = {10.1101/2020.08.20.259036},
elocation-id = {2020.08.20.259036},
eprint = {https://www.biorxiv.org/content/early/2021/03/12/2020.08.20.259036.full.pdf},
interhash = {664185f07b1ed2b4e98896788e19da34},
intrahash = {00296b82b8b330aadd287aca44d8e2f3},
journal = {bioRxiv},
keywords = {Antirrhinum clines inbreeding snapdragons spatial_demography},
publisher = {Cold Spring Harbor Laboratory},
timestamp = {2021-04-07T18:08:42.000+0200},
title = {Effects of fine-scale population structure on inbreeding in a long-term study of snapdragons (Antirrhinum majus)},
url = {https://www.biorxiv.org/content/early/2021/03/12/2020.08.20.259036},
year = 2021
}