Nonequivalent lethal equivalents: Models and inbreeding metrics for unbiased estimation of inbreeding load

Pirmin Nietlisbach (Corresponding Author), Stefanie Muff, Jane M. Reid, Michael C. Whitlock, Lukas F. Keller

Research output: Contribution to journalArticle

2 Citations (Scopus)
3 Downloads (Pure)

Abstract

Inbreeding depression, the deterioration in mean trait value in progeny of related parents, is a fundamental quantity in genetics, evolutionary biology, animal and plant breeding, and conservation biology. The magnitude of inbreeding depression can be quantified by the inbreeding load, typically measured in numbers of lethal equivalents, a population genetic quantity that allows for comparisons between environments, populations, or species. However, there is as yet no quantitative assessment of which combinations of statistical models and metrics of inbreeding can yield such estimates. Here, we review statistical models that have been used to estimate inbreeding load, and use population genetic simulations to investigate how unbiased estimates can be obtained using genomic and pedigree-based metrics of inbreeding. We use simulated binary viability data (i.e. dead versus alive) as our example, but the concepts apply to any trait that exhibits inbreeding depression. We show that the increasingly popular generalized linear models with logit link do not provide comparable and unbiased population genetic measures of inbreeding load, independent of the metric of inbreeding used. Runs of homozygosity result in unbiased estimates of inbreeding load, whereas inbreeding measured from pedigrees results in slight overestimates. Due to widespread use of models that do not yield unbiased measures of the inbreeding load, some estimates in the literature cannot be compared meaningfully. We surveyed the literature for reliable estimates of the mean inbreeding load from wild vertebrate populations and found an average of 3.5 haploid lethal equivalents for survival to sexual maturity. To obtain comparable estimates, we encourage researchers to use generalized linear models with logarithmic links or maximum likelihood estimation of the exponential equation, and inbreeding coefficients calculated from runs of homozygosity, provided an assembled reference genome of sufficient quality and enough genetic marker data are available.
Original languageEnglish
Pages (from-to)266-279
JournalEvolutionary Applications
Volume12
Issue number2
Early online date23 Oct 2018
DOIs
Publication statusPublished - Feb 2019

Fingerprint

Inbreeding
inbreeding
inbreeding depression
Population Genetics
population genetics
homozygosity
statistical models
lethal genes
Statistical Models
Pedigree
pedigree
Linear Models
linear models
Biological Sciences
plant breeding
inbreeding coefficient
animal breeding
Haploidy
evolutionary biology
sexual maturity

Keywords

  • inbreeding depression
  • conservation biology
  • inbreeding coefficients
  • genomics
  • pedigree
  • runs of homozygosity
  • generalized linear (mixed) models
  • SURVIVAL
  • DEPRESSION
  • POPULATION
  • EVOLUTIONARY
  • SONG SPARROWS
  • WILD
  • QUANTIFICATION
  • GENOME
  • HOMOZYGOSITY
  • PEDIGREE

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Genetics
  • Ecology, Evolution, Behavior and Systematics

Cite this

Nonequivalent lethal equivalents : Models and inbreeding metrics for unbiased estimation of inbreeding load. / Nietlisbach, Pirmin (Corresponding Author); Muff, Stefanie; Reid, Jane M.; Whitlock, Michael C.; Keller, Lukas F.

In: Evolutionary Applications, Vol. 12, No. 2, 02.2019, p. 266-279.

Research output: Contribution to journalArticle

Nietlisbach, Pirmin ; Muff, Stefanie ; Reid, Jane M. ; Whitlock, Michael C. ; Keller, Lukas F. / Nonequivalent lethal equivalents : Models and inbreeding metrics for unbiased estimation of inbreeding load. In: Evolutionary Applications. 2019 ; Vol. 12, No. 2. pp. 266-279.
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