[en] The inbreeding coefficient (F) of individuals can be estimated from molecular marker
data, such as SNPs, using measures of homozygosity of individual markers or runs of
homozygosity (ROH) across the genome. These different measures of F can then be
used to estimate the rate of inbreeding depression (ID) for quantitative traits. Some
recent simulation studies have investigated the accuracy of this estimation with contradictory
results. Whereas some studies suggest that estimates of inbreeding from
ROH account more accurately for ID, others suggest that inbreeding measures from
SNP-by-SNP homozygosity giving a large weight to rare alleles are more accurate.
Here, we try to give more light on this issue by carrying out a set of computer simulations
considering a range of population genetic parameters and population sizes.
Our results show that the previous studies are indeed not contradictory. In populations
with low effective size, where relationships are more tight and selection is
relatively less intense, F measures based on ROH provide very accurate estimates of
ID whereas SNP-by-SNP-based F measures with high weight to rare alleles can show
substantial upwardly biased estimates of ID. However, in populations of large effective
size, with more intense selection and trait allele frequencies expected to be low
if they are deleterious for fitness because of purifying selection, average estimates of
ID from SNP-by-SNP-based F values become unbiased or slightly downwardly biased
and those from ROH-based F values become slightly downwardly biased. The noise
attached to all these estimates, nevertheless, can be very high in large-sized populations.
We also investigate the relationship between the different F measures and
the homozygous mutation load, which has been suggested as a proxy of inbreeding
depression.
Disciplines :
Animal production & animal husbandry Genetics & genetic processes
Author, co-author :
Caballero, Armando
Villanueva, Beatriz
Druet, Tom ; Université de Liège - ULiège > Medical Genomics-Unit of Animal Genomics
Language :
English
Title :
On the estimation of inbreeding depression using different measures of inbreeding from molecular markers
Publication date :
2021
Journal title :
Evolutionary Applications
ISSN :
1752-4563
eISSN :
1752-4571
Publisher :
Wiley-Blackwell, United Kingdom
Volume :
14
Pages :
416-428
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
Ackerman, M. S., Johri, P., Spitze, K., Xu, S., Doak, T. G., Young, K., & Lynch, M. (2017). Estimating seven coefficients of pairwise relatedness using population-genomic data. Genetics, 206, 105–118.
Alemu, S. W., Kadri, N. K., Harland, C., Faux, P., Charlier, C., Caballero, A., & Druet, T. (2020). An evaluation of inbreeding measures using a whole genome sequenced cattle pedigree. Heredity, submitted.
Allendorf, F. W., Luikart, G. H., & Aitken, S. N. (2013). Conservation and the genetics of populations. Chichester, UK: John Wiley and Sons.
Bérénos, C., Ellis, P. A., Pilkington, J. G., & Pemberton, J. M. (2016). Genomic analysis reveals depression due to both individual and maternal inbreeding in a free-living mammal population. Molecular Ecology, 25, 3152–3168. https://doi.org/10.1111/mec.13681
Bjelland, D. W., Weigel, K. A., Vukasinovic, N., & Nkrumah, J. D. (2013). Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding. Journal of Dairy Science, 96, 4697–4706. https://doi.org/10.3168/jds.2012-6435
Caballero, A. (2020). Quantitative genetics. Cambridge, UK: Cambridge University Press.
Caballero, A., Bravo, I., & Wang, J. (2017). Inbreeding load and purging: Implications for the short-term survival and the conservation management of small populations. Heredity, 118, 177–185. https://doi.org/10.1038/hdy.2016.80
Caballero, A., & Keightley, P. D. (1994). A pleiotropic nonadditive model of variation in quantitative traits. Genetics, 38, 883–900.
Caballero, A., Tenesa, A., & Keightley, P. D. (2015). The nature of genetic variation for complex traits revealed by GWAS and regional heritability mapping analyses. Genetics, 201, 1601–1613. https://doi.org/10.1534/genetics.115.177220
Ceballos, F. C., Joshi, P. K., Clark, D. W., Ramsay, M., & Wilson, J. F. (2018). Runs of homozygosity: Windows into population history and trait architecture. Nature Reviews Genetics, 19, 220–234. https://doi.org/10.1038/nrg.2017.109
Charlesworth, B. (2015). Causes of natural variation in fitness: evidence from studies of Drosophila populations. Proceedings of the National Academy of Sciences U.S.A., 112, 1662–1669.
Charlesworth, D., & Willis, J. H. (2009). The genetics of inbreeding depression. Nature Reviews Genetics, 10, 783–796. https://doi.org/10.1038/nrg2664
Curik, I., Ferenčaković, M., & Sölkner, J. (2014). Inbreeding and runs of homozygosity: A possible solution to an old problem. Livestock Science, 166, 26–34. https://doi.org/10.1016/j.livsci.2014.05.034
Druet, T., & Gautier, M. (2017). A model-based approach to characterize individual inbreeding at both global and local genomic scales. Molecular Ecology, 26, 5820–5841. https://doi.org/10.1111/mec.14324
Ferenčaković, M., Hamzić, E., Gredler, B., Solberg, T. R., Klemetsdal, G., Curik, I., & Sölkner, J. (2013). Estimates of autozygosity derived from runs of homozygosity: Empirical evidence from selected cattle populations. Journal of Animal Breeding and Genetics, 130, 286–293. https://doi.org/10.1111/jbg.12012
Ferenčaković, M., Sölkner, J., Kapš, M., & Curik, I. (2017). Genome-wide mapping and estimation of inbreeding depression of semen quality traits in a cattle population. Journal of Dairy Science, 100, 4721–4730. https://doi.org/10.3168/jds.2016-12164
Frankham, R., Ballou, J. D., & Briscoe, D. A. (2010). Introduction to conservation genetics. Cambridge, UK: Cambridge University Press.
García-Dorado, A. (2012). Understanding and predicting the fitness decline of shrunk populations: Inbreeding, purging, mutation, and standard selection. Genetics, 190, 1461–1476. https://doi.org/10.1534/genetics.111.135541
Goudet, J., Kay, T., & Weir, B. S. (2018). How to estimate kinship. Molecular Ecology, 27, 4121–4135. https://doi.org/10.1111/mec.14833
Grueber, C. E., Waters, J. M., & Jamieson, I. G. (2011). The imprecision of heterozygosity-fitness correlations hinders the detection of inbreeding and inbreeding depression in a threatened species. Molecular Ecology, 20, 67–79. https://doi.org/10.1111/j.1365-294X.2010.04930.x
Hedrick, P. W. (2012). What is the evidence for heterozygote advantage selection? Trends in Ecology and Evolution, 27, 698–704. https://doi.org/10.1016/j.tree.2012.08.012
Howrigan, D. P., Simonson, M. A., & Keller, M. C. (2011). Detecting autozygosity through runs of homozygosity: A comparison of three autozygosity detection algorithms. BMC Genomics, 12, 460. https://doi.org/10.1186/1471-2164-12-460
Huisman, J., Kruuk, L. E., Ellis, P. A., Clutton-Brock, T., & Pemberton, J. M. (2016). Inbreeding depression across the lifespan in a wild mammal population. Proceedings of the National Academy of Sciences U.S.A., 113, 3585–3590.
Kardos, M., Luikart, G., & Allendorf, F. W. (2015). Measuring individual inbreeding in the age of genomics: Marker-based measures are better than pedigrees. Heredity, 115, 63–72. https://doi.org/10.1038/hdy.2015.17
Kardos, M., Nietlisbach, P., & Hedrick, P. W. (2018). How should we compare different genomic estimates of the strength of inbreeding depression? Proceedings of the National Academy of Sciences U.S.A., 115, E2492–E2493.
Kardos, M., Taylor, H. R., Ellegren, H., Luikart, G., & Allendorf, F. W. (2016). Genomics advances the study of inbreeding depression in the wild. Evolutionary Applications, 9(10), 1205–1218. https://doi.org/10.1111/eva.12414
Keller, M. C., Visscher, P. M., & Goddard, M. E. (2011). Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data. Genetics, 189, 237–249. https://doi.org/10.1534/genetics.111.130922
Kimura, M., & Crow, J. F. (1963). The measurement of effective population number. Evolution, 17, 279–288. https://doi.org/10.1111/j.1558-5646.1963.tb03281.x
Leroy, G. (2014). Inbreeding depression in livestock species: Review and meta-analysis. Animal Genetics, 45, 618–628. https://doi.org/10.1111/age.12178
Li, C. C., & Horvitz, D. G. (1953). Some methods of estimating the inbreeding coefficient. American Journal of Human Genetics, 5, 107–117.
López-Cortegano, E., Vilas, A., Caballero, A., & García-Dorado, A. (2016). Estimation of genetic purging under competitive conditions. Evolution, 70, 1856–1870. https://doi.org/10.1111/evo.12983
Lynch, M., & Walsh, B. (1998). Genetics and analysis of quantitative traits. Sunderland, MA: Sinauer.
Malécot, G. (1948). Les mathématiques de l’hérédité. Paris, France: Masson et Cie.
McQuillan, R., Leutenegger, A.-L., Abdel-Rahman, R., Franklin, C. S., Pericic, M., Barac-Lauc, L., … Wilson, J. F. (2008). Runs of homozygosity in European populations. American Journal of Human Genetics, 83, 359–372. https://doi.org/10.1016/j.ajhg.2008.08.007
Messer, P. (2013). SLiM: Simulating evolution with selection and linkage. Genetics, 194, 1037–1039. https://doi.org/10.1534/genetics.113.152181
Milligan, B. G. (2003). Maximum-likelihood estimation of relatedness. Genetics, 163, 1153–1167.
Morton, N. E., Crow, J. F., & Muller, H. (1956). An estimate of the mutational damage in man from data on consanguineous marriages. Proceedings of the National Academy of Sciences U.S.A., 42, 855–863.
Nietlisbach, P., Muff, S., Reid, J. M., Whitlock, M. C., & Keller, L. F. (2019). Nonequivalent lethal equivalents: Models and inbreeding metrics for unbiased estimation of inbreeding load. Evolutionary Applications, 12(2), 266–279. https://doi.org/10.1111/eva.12713
O’Grady, J. J., Brook, B. W., Reed, D. H., Ballou, J. D., Tonkyn, D. W., & Frankham, R. (2006). Realistic levels of inbreeding depression strongly affect extinction risk in wild populations. Biological Conservation, 133, 42–51. https://doi.org/10.1016/j.biocon.2006.05.016
Pryce, J. E., Haile-Mariam, M., Goddard, M. E., & Hayes, B. J. (2014). Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle. Genetics Selection Evolution, 46, 71.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., … Sham, P. C. (2007). PLINK: A tool set for whole-genome association and population-based linkage analyses. American Journal of Human Genetics, 81, 559–575. https://doi.org/10.1086/519795
Ritland, K. (1996). Estimators for pairwise relatedness and individual inbreeding coefficients. Genetical Research Cambridge, 67, 175–185. https://doi.org/10.1017/S0016672300033620
Robertson, A. (1965). The interpretation of genotypic ratios in domestic animal populations. Animal Science, 7(3), 319–324. https://doi.org/10.1017/S0003356100025770.
Santure, A. W., Stapley, J., Ball, A. D., Birkhead, T. R., Burke, T., & Slate, J. O. N. (2010). On the use of large marker panels to estimate inbreeding and relatedness: Empirical and simulation studies of a pedigreed zebra finch population typed at SNPs. Molecular Ecology, 19, 1439–1451.
Saura, M., Fernández, A., Varona, L., Fernández, A. I., de Cara, M. Á., Barragán, C., & Villanueva, B. (2015). Detecting inbreeding depression for reproductive traits in Iberian pigs using genome-wide data. Genetics Selection Evolution, 47, 1.
Slate, J., & Pemberton, J. M. (2002). Comparing molecular measures for detecting inbreeding depression. Journal of Evolutionary Biology, 15, 20–31. https://doi.org/10.1046/j.1420-9101.2002.00373.x
Szpiech, Z. A., Xu, J. S., Pemberton, T. J., Peng, W. P., Zollner, S., Rosenberg, N. A., & Li, J. Z. (2013). Long runs of homozygosity are enriched for deleterious variation. American Journal of Human Genetics, 93, 90–102. https://doi.org/10.1016/j.ajhg.2013.05.003
Szulkin, M., Bierne, N., & David, P. (2010). Heterozygosity-fitness correlations: A time for reappraisal. Evolution, 64, 1202–1217. https://doi.org/10.1111/j.1558-5646.2010.00966.x
Toro, M., Barragán, C., Óvilo, C., Rodrigañez, J., Rodriguez, C., & Silió, L. (2002). Estimation of coancestry in Iberian pigs using molecular markers. Conservation Genetics, 3, 309–320.
VanRaden, P. M. (2008). Efficient methods to compute genomic predictions. Journal of Dairy Science, 91, 4414–4423. https://doi.org/10.3168/jds.2007-0980
Wang, J. (2007). Triadic IBD coefficients and applications to estimating pairwise relatedness. Genetical Research Cambridge, 89, 135–153. https://doi.org/10.1017/S0016672307008798
Wang, J. (2016). Pedigrees or markers: Which are better in estimating relatedness and inbreeding coefficient? Theoretical Population Biology, 107, 4–13. https://doi.org/10.1016/j.tpb.2015.08.006
Wang, J., Hill, W. G., Charlesworth, D., & Charlesworth, B. (1999). Dynamics of inbreeding depression due to deleterious mutations in small populations: Mutation parameters and inbreeding rate. Genetical Research Cambridge, 74, 165–178.
Wright, S. (1969). Evolution and the genetics of populations, Vol. 2. The theory of gene frequencies. Chicago, IL: University of Chicago Press.
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011). GCTA: A tool for genome-wide complex trait analysis. American Journal of Human Genetics, 88, 76–82. https://doi.org/10.1016/j.ajhg.2010.11.011
Yengo, L., Zhu, Z., Wray, N. R., Weir, B. S., Yang, J., Robinson, M. R., & Visscher, P. M. (2017). Detection and quantification of inbreeding depression for complex traits from SNP data. Proceedings of the National Academy of Sciences U.S.A., 114, 8602–8607.
Yengo, L., Zhu, Z., Wray, N. R., Weir, B. S., Yang, J., Robinson, M. R., & Visscher, P. M. (2018). Estimation of inbreeding depression from SNP data. Proceedings of the National Academy of Sciences U.S.A., 115, E2494–E2495.
Zhang, Q., Calus, M. P., Guldbrandtsen, B., Lund, M. S., & Sahana, G. (2015). Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds. BMC Genetics, 16, 88. https://doi.org/10.1186/s12863-015-0227-7