A model‐based approach to characterize individual inbreeding at both global and local genomic scales
Abstract
Inbreeding results from the mating of related individuals and may be associated with reduced fitness because it brings together deleterious variants in one individual. In general, inbreeding is estimated with respect to an arbitrary base population consisting of ancestors that are assumed unrelated. We herein propose a model‐based approach to estimate and characterize individual inbreeding at both global and local genomic scales by assuming the individual genome is a mosaic of homozygous‐by‐descent (HBD) and non‐HBD segments. The HBD segments may originate from ancestors tracing back to different periods in the past defining distinct age‐related classes. The lengths of the HBD segments are exponentially distributed with class‐specific parameters reflecting that inbreeding of older origin generates on average shorter stretches of observed homozygous markers. The model is implemented in a hidden Markov model framework that uses marker allele frequencies, genetic distances, genotyping error rates and the sequences of observed genotypes. Note that genotyping errors, low‐fold sequencing or genotype‐by‐sequencing data are easily accommodated under this framework. Based on simulations under the inference model, we show that the genomewide inbreeding coefficients and the parameters of the model are accurately estimated. In addition, when several inbreeding classes are simulated, the model captures them if their ages are sufficiently different. Complementary analyses, either on data sets simulated under more realistic models or on human, dog and sheep real data, illustrate the range of applications of the approach and how it can reveal recent demographic histories among populations (e.g., very recent bottlenecks or founder effects). The method also allows to clearly identify individuals resulting from extreme consanguineous matings.
Citing Literature
Number of times cited according to CrossRef: 15
- R. Meyermans, W. Gorssen, N. Buys, S. Janssens, How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species, BMC Genomics, 10.1186/s12864-020-6463-x, 21, 1, (2020).
- C. Maltecca, F. Tiezzi, J.B. Cole, C. Baes, Symposium review: Exploiting homozygosity in the era of genomics—Selection, inbreeding, and mating programs, Journal of Dairy Science, 10.3168/jds.2019-17846, (2020).
- Seyed Mohammad Ghoreishifar, Hossein Moradi-Shahrbabak, Mohammad Hossein Fallahi, Mohammad Moradi-Shahrbabak, Rostam Abdollahi-Arpanahi, Majid Khansefid, Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis, BMC Genetics, 10.1186/s12863-020-0824-y, 21, 1, (2020).
- Bayode O. Makanjuola, Christian Maltecca, Filippo Miglior, Flavio S. Schenkel, Christine F. Baes, Effect of recent and ancient inbreeding on production and fertility traits in Canadian Holsteins, BMC Genomics, 10.1186/s12864-020-07031-w, 21, 1, (2020).
- Tom Druet, Kamil Oleński, Laurence Flori, Amandine R Bertrand, Wanda Olech, Malgorzata Tokarska, Stanislaw Kaminski, Mathieu Gautier, Genomic Footprints of Recovery in the European Bison, Journal of Heredity, 10.1093/jhered/esaa002, (2020).
- Isabel Álvarez, Iván Fernández, Amadou Traoré, Lucía Pérez-Pardal, Nuria A. Menéndez-Arias, Félix Goyache, Ancient Homozygosity Segments in West African Djallonké Sheep Inform on the Genomic Impact of Livestock Adaptation to the Environment, Animals, 10.3390/ani10071178, 10, 7, (1178), (2020).
- Junjie Zhang, Naveen Kumar Kadri, Erik Mullaart, Richard Spelman, Sébastien Fritz, Didier Boichard, Carole Charlier, Michel Georges, Tom Druet, Genetic architecture of individual variation in recombination rate on the X chromosome in cattle, Heredity, 10.1038/s41437-020-0341-9, (2020).
- W. Gorssen, R. Meyermans, N. Buys, S. Janssens, SNP genotypes reveal breed substructure, selection signatures and highly inbred regions in Piétrain pigs, Animal Genetics, 10.1111/age.12888, 51, 1, (32-42), (2019).
- Aimee R. Taylor, Pierre E. Jacob, Daniel E. Neafsey, Caroline O. Buckee, Estimating Relatedness Between Malaria Parasites, Genetics, 10.1534/genetics.119.302120, 212, 4, (1337-1351), (2019).
- Loic Yengo, Naomi R. Wray, Peter M. Visscher, Extreme inbreeding in a European ancestry sample from the contemporary UK population, Nature Communications, 10.1038/s41467-019-11724-6, 10, 1, (2019).
- Harmen P. Doekes, Roel F. Veerkamp, Piter Bijma, Gerben de Jong, Sipke J. Hiemstra, Jack J. Windig, Inbreeding depression due to recent and ancient inbreeding in Dutch Holstein–Friesian dairy cattle, Genetics Selection Evolution, 10.1186/s12711-019-0497-z, 51, 1, (2019).
- Wilson Nandolo, Gábor Mészáros, Liveness Jessica Banda, Timothy N. Gondwe, Doreen Lamuno, Henry Aaron Mulindwa, Helen N. Nakimbugwe, Maria Wurzinger, Yuri T. Utsunomiya, M. Jennifer Woodward-Greene, Mei Liu, George Liu, Curtis P. Van Tassell, Ino Curik, Benjamin D. Rosen, Johann Sölkner, Timing and Extent of Inbreeding in African Goats, Frontiers in Genetics, 10.3389/fgene.2019.00537, 10, (2019).
- undefined Islam, undefined Li, undefined Liu, undefined Berihulay, undefined Abied, undefined Gebreselassie, undefined Ma, undefined Ma, Genome-Wide Runs of Homozygosity, Effective Population Size, and Detection of Positive Selection Signatures in Six Chinese Goat Breeds, Genes, 10.3390/genes10110938, 10, 11, (938), (2019).
- Jérôme Goudet, Tomas Kay, Bruce S. Weir, How to estimate kinship, Molecular Ecology, 10.1111/mec.14833, 27, 20, (4121-4135), (2018).
- Marina Solé, Ann-Stephan Gori, Pierre Faux, Amandine Bertrand, Frédéric Farnir, Mathieu Gautier, Tom Druet, Age-based partitioning of individual genomic inbreeding levels in Belgian Blue cattle, Genetics Selection Evolution, 10.1186/s12711-017-0370-x, 49, 1, (2017).




