title: Ancestral Relationships Using Metafounders: Finite Ancestral Populations and Across Population Relationships.
abstract: Recent use of genomic (marker-based) relationships shows that relationships exist within and across base population (breeds or lines). However, current treatment of pedigree relationships is unable to consider relationships within or across base populations, although such relationships must exist due to finite size of the ancestral population and connections between populations. This complicates the conciliation of both approaches and, in particular, combining pedigree with genomic relationships. We present a coherent theoretical framework to consider base population in pedigree relationships. We suggest a conceptual framework that considers each ancestral population as a finite-sized pool of gametes. This generates across-individual relationships and contrasts with the classical view which each population is considered as an infinite, unrelated pool. Several ancestral populations may be connected and therefore related. Each ancestral population can be represented as a "metafounder," a pseudo-individual included as founder of the pedigree and similar to an "unknown parent group." Metafounders have self- and across relationships according to a set of parameters, which measure ancestral relationships, i.e., homozygozities within populations and relationships across populations. These parameters can be estimated from existing pedigree and marker genotypes using maximum likelihood or a method based on summary statistics, for arbitrarily complex pedigrees. Equivalences of genetic variance and variance components between the classical and this new parameterization are shown. Segregation variance on crosses of populations is modeled. Efficient algorithms for computation of relationship matrices, their inverses, and inbreeding coefficients are presented. Use of metafounders leads to compatibility of genomic and pedigree relationship matrices and to simple computing algorithms. Examples and code are given.
authors: Institut National de la Recherche Agronomique, GenPhySE, Génétique, Physiologie et Systèmes d'Elevage, F-31326 Castanet-Tolosan, France andres.legarra@toulouse.inra.fr.
authors: Andres
authors: A
authors: Legarra
authors: Aarhus University, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, DK-8830 Tjele, Denmark.
authors: Ole F
authors: OF
authors: Christensen
authors: Université de Toulouse, INP, ENSAT, GenPhySE, Génétique, Physiologie et Systèmes d'Elevage, F-31326 Castanet-Tolosan, France.
authors: Zulma G
authors: ZG
authors: Vitezica
authors: Instituto Nacional de Investigación Agropecuaria, Canelones 90200, Uruguay.
authors: Ignacio
authors: I
authors: Aguilar
authors: Animal and Dairy Science, University of Georgia, Athens, Georgia 30602.
authors: Ignacy
authors: I
authors: Misztal
mesh_terms: D000465:Algorithms; D003433:Crosses, Genetic; D014644:Genetic Variation; D005828:Genetics, Population; D023281:Genomics / Q000379:methods*; D005838:Genotype; D007178:Inbreeding; D008957:Models, Genetic; D010375:Pedigree
keywords: GenPred; base populations; genetic drift; marker genotypes; pedigree; relationships; shared data resource