Accounting for cryptic population substructure enhances detection of inbreeding depression with genomic inbreeding coefficients: an example from a critically endangered marsupial

Characterizing inbreeding depression in wildlife populations can be critical to their conservation. Coefficients of individual inbreeding can be estimated from genome-wide marker data. The degree to which sensitivity of inbreeding coefficients to population genetic substructure alters estimates of inbreeding depression in wild populations is not well understood. Using generalized linear models, we tested the power of two frequently used inbreeding coefficients that are calculated from genome-wide SNP markers, FH and F^III, to predict four fitness traits estimated over two decades in an isolated population of the critically endangered Leadbeater's possum. FH estimates inbreeding as excess observed homozygotes relative to equilibrium expectations, whereas F^III quantifies allelic similarity between the gametes that formed an individual, and upweights rare homozygotes. We estimated FH and F^III from 1,575 genome-wide SNP loci in individuals with fitness trait data (N = 179–237 per trait), and computed revised coefficients, FHby group and F^IIIby group, adjusted for population genetic substructure by calculating them separately within two different genetic groups of individuals identified in the population. Using FH or F^III in the models, inbreeding depression was detected for survival to sexual maturity, longevity and whether individuals bred during their lifetime. F^IIIby group (but not FHby group) additionally revealed significant inbreeding depression for lifetime reproductive output (total offspring assigned to each individual). Estimates of numbers of lethal equivalents indicated substantial inbreeding load, but differing between inbreeding estimators. Inbreeding depression, declining population size, and low and declining genetic diversity suggest that genetic rescue may assist in preventing extinction of this unique Leadbeater's possum population. © 2020 John Wiley & Sons Lt