Publication
Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus
Publisher:
Cold Spring Harbor Laboratory
Date:
21-08-2020
DOI:
10.1101/2020.08.20.259036
Abstract: Many studies have quantified the distribution of heterozygosity and relatedness in natural populations, but surprisingly few have examined the demographic processes driving these patterns. In this study we take a novel approach by studying how population structure affects both pairwise identity and the distribution of heterozygosity in a natural population of a self-incompatible plant Antirrhinum majus . We look at a measure of the variance in heterozygosity within a population, identity disequilibrium ( g 2 ), together with F ST using a panel of 91 SNPs in 22,353 in iduals collected over 11 years. We find that pairwise relatedness (F ST ) declines rapidly over short spatial scales, and the excess variance in heterozygosity between in iduals ( g 2 ) reflects significant variation in inbreeding. Additionally, we detect an excess of in iduals with around half the average heterozygosity, indicating that some are due to selfing or matings between close relatives. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial population structure. First, by simulating offspring using parents drawn from a range of spatial scales, we show that the known pollen dispersal kernel explains g 2 . Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that the resulting g 2 is consistent with that observed from the field data. In contrast, a simulated population with uniform density underestimates g 2 , indicating that heterogeneous density promotes identity disequilibrium. Our study shows that heterogeneous density and leptokurtic dispersal can together explain the distribution of heterozygosity. Furthermore, our study highlights the limitations of making theoretical predictions from simulations that only assume simple density and dispersal distributions.