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[This corrects the article DOI: 10.1371/journal.pgen.1010871.].
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Measuring inbreeding and its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the best method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. We simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structures (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients ([Formula: see text]) to quantify the strength of inbreeding depression: allele-sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model (LMM) including a genetic relatedness matrix (GRM) as random effect to account for the nonindependence of observations. We find LMMs give better results in scenarios with population or family structure. Within the LMM, we compare three different GRMs and show that in homogeneous populations, there is little difference among the different [Formula: see text] and GRM for inbreeding depression quantification. However, as soon as a strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if i) the phenotypes are regressed on [Formula: see text] based on a weighted version of the correlation of uniting gametes, giving more weight to common alleles and ii) with the GRM obtained from an allele-sharing relatedness estimator.
Asunto(s)
Depresión Endogámica , Modelos Genéticos , Humanos , Linaje , Genética de Población/métodos , Endogamia , AlelosRESUMEN
Population data have become available for sequence data to aid forensic investigations and prepare the forensic community in the move towards implementing NGS methods. This comes with a need for updated population genetic parameters estimates to allow DNA evidence evaluations using sequence data. Initial work has been done on a small sample and here we expand this work by providing estimates of population structure and relatedness for autosomal STR data generated by sequencing technologies. We also discuss the effect of inbreeding on forensic calculations and discuss why the use of genotypic-based estimates may be preferred over allelic-based estimates.