Pedigrees or markers: Which are better in estimating relatedness and inbreeding coefficient? 2016

Jinliang Wang
Institute of Zoology, Zoological Society of London, London NW1 4RY, United Kingdom. Electronic address: jinliang.wang@ioz.ac.uk.

Individual inbreeding coefficient (F) and pairwise relatedness (r) are fundamental parameters in population genetics and have important applications in diverse fields such as human medicine, forensics, plant and animal breeding, conservation and evolutionary biology. Traditionally, both parameters are calculated from pedigrees, but are now increasingly estimated from genetic marker data. Conceptually, a pedigree gives the expected F and r values, FP and rP, with the expectations being taken (hypothetically) over an infinite number of individuals with the same pedigree. In contrast, markers give the realised (actual) F and r values at the particular marker loci of the particular individuals, FM and rM. Both pedigree (FP, rP) and marker (FM, rM) estimates can be used as inferences of genomic inbreeding coefficients FG and genomic relatedness rG, which are the underlying quantities relevant to most applications (such as estimating inbreeding depression and heritability) of F and r. In the pre-genomic era, it was widely accepted that pedigrees are much better than markers in delineating FG and rG, and markers should better be used to validate, amend and construct pedigrees rather than to replace them. Is this still true in the genomic era when genome-wide dense SNPs are available? In this simulation study, I showed that genomic markers can yield much better estimates of FG and rG than pedigrees when they are numerous (say, 10(4) SNPs) under realistic situations (e.g. genome and population sizes). Pedigree estimates are especially poor for species with a small genome, where FG and rG are determined to a large extent by Mendelian segregations and may thus deviate substantially from their expectations (FP and rP). Simulations also confirmed that FM, when estimated from many SNPs, can be much more powerful than FP for detecting inbreeding depression in viability. However, I argue that pedigrees cannot be replaced completely by genomic SNPs, because the former allows for the calculation of more complicated IBD coefficients (involving more than 2 individuals, more than one locus, and more than 2 genes at a locus) for which the latter may have reduced capacity or limited power, and because the former has social and other significance for remote relationships which have little genetic significance and cannot be inferred reliably from markers.

UI MeSH Term Description Entries
D007178 Inbreeding The mating of plants or non-human animals which are closely related genetically. Backcrossing,Half-Sib Mating,Sib Mating,Genetic Inbreeding,Backcrossings,Genetic Inbreedings,Half Sib Mating,Half-Sib Matings,Inbreeding, Genetic,Mating, Half-Sib,Mating, Sib,Matings, Half-Sib,Matings, Sib,Sib Matings
D008957 Models, Genetic Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment. Genetic Models,Genetic Model,Model, Genetic
D010375 Pedigree The record of descent or ancestry, particularly of a particular condition or trait, indicating individual family members, their relationships, and their status with respect to the trait or condition. Family Tree,Genealogical Tree,Genealogic Tree,Genetic Identity,Identity, Genetic,Family Trees,Genealogic Trees,Genealogical Trees,Genetic Identities,Identities, Genetic,Tree, Family,Tree, Genealogic,Tree, Genealogical,Trees, Family,Trees, Genealogic,Trees, Genealogical
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D003241 Consanguinity The magnitude of INBREEDING in humans. Inbreeding, Human,Consanguineous Marriage,Consanguinous Mating,Consanguineous Marriages,Consanguinities,Consanguinous Matings,Human Inbreeding,Human Inbreedings,Inbreedings, Human,Marriage, Consanguineous,Marriages, Consanguineous,Mating, Consanguinous,Matings, Consanguinous
D005819 Genetic Markers A phenotypically recognizable genetic trait which can be used to identify a genetic locus, a linkage group, or a recombination event. Chromosome Markers,DNA Markers,Markers, DNA,Markers, Genetic,Genetic Marker,Marker, Genetic,Chromosome Marker,DNA Marker,Marker, Chromosome,Marker, DNA,Markers, Chromosome
D005828 Genetics, Population The discipline studying genetic composition of populations and effects of factors such as GENETIC SELECTION, population size, MUTATION, migration, and GENETIC DRIFT on the frequencies of various GENOTYPES and PHENOTYPES using a variety of GENETIC TECHNIQUES. Population Genetics
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia

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