Evolution of Methods for the Quantitative Assessment of Inbreeding in Livestock

Inbreeding is a quantitative measure of autozygosity that underlies the assessment of genetic risks and the management of genetic progress in livestock populations. The development of methods for its estimation reflects a transition from probabilistic pedigree-based models to the direct analysis of genome structure. This review systematizes the evolution of approaches to inbreeding assessment—from the classical inbreeding coefficient F based on identity by descent (IBD) to marker-based, segment-based runs of homozygosity (ROH) and probabilistic homozygous-by-descent (HBD) models. It is shown that the coefficients F_ped, F_GRM, F_ROH, and F_HBD capture related but distinct aspects of autozygosity and are therefore not fully interchangeable. Particular attention is paid to the transition from integral indicators to spatially and temporally stratified analyses of autozygosity, enabling the differentiation between ancient and recent inbreeding. Methodological assumptions, limitations, and the sensitivity of various approaches to marker density, detection parameters, and population demographic structure are discussed. A comparative analysis of methods for calculating F_ROH and segment-based autozygosity is presented. The necessity of a comprehensive assessment of inbreeding and the standardization of analytical protocols for its application in modern breeding programs is substantiated.

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Publication Details

Journal
Biology
Published
2026-03-26
DOI
https://doi.org/10.3390/biology15070530
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
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article

Evolution of Methods for the Quantitative Assessment of Inbreeding in Livestock

Kharon A Amerkhanov, Olga N. Lukonina, Maria Kolosova, Lyubov Getmantseva et al.
Biology
Genetic and phenotypic traits in livestock
article

Evolution of Methods for the Quantitative Assessment of Inbreeding in Livestock

Kharon A Amerkhanov, Olga N. Lukonina, Maria Kolosova, Lyubov Getmantseva, SIROJ BAKOEV, Alexandr Usatov
article en

Abstract

Inbreeding is a quantitative measure of autozygosity that underlies the assessment of genetic risks and the management of genetic progress in livestock populations. The development of methods for its estimation reflects a transition from probabilistic pedigree-based models to the direct analysis of genome structure. This review systematizes the evolution of approaches to inbreeding assessment—from the classical inbreeding coefficient F based on identity by descent (IBD) to marker-based, segment-based runs of homozygosity (ROH) and probabilistic homozygous-by-descent (HBD) models. It is shown that the coefficients F_ped, F_GRM, F_ROH, and F_HBD capture related but distinct aspects of autozygosity and are therefore not fully interchangeable. Particular attention is paid to the transition from integral indicators to spatially and temporally stratified analyses of autozygosity, enabling the differentiation between ancient and recent inbreeding. Methodological assumptions, limitations, and the sensitivity of various approaches to marker density, detection parameters, and population demographic structure are discussed. A comparative analysis of methods for calculating F_ROH and segment-based autozygosity is presented. The necessity of a comprehensive assessment of inbreeding and the standardization of analytical protocols for its application in modern breeding programs is substantiated.

BiologyVol. 15(7)
Russian State Agrarian University - Moscow Timiryazev Agricultural Academy (RU), Southern Federal University (RU), Moscow State Agroengineering University named after V.P. Goryachkin (RU), All-Russian Research Institute of Genetics and Farm Animal Breeding (RU), All Russian Research Institute of Animal Breeding
Openalex Percentile: Top 7%
Genetic and phenotypic traits in livestock
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Evolution of Methods for the Quantitative Assessment of Inbreeding in Livestock — Kharon A Amerkhanov, Olga N. Lukonina, et al. · Biology (2026) | TGRS Research Map | TGRS