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Factors affecting accuracy of estimated effective number of chromosome segments for numerically small breeds

For numerically small breeds, obtaining a sufficiently large breed‐specific reference population for genomic prediction is challenging or simply not possible, but may be overcome by adding individuals from another breed. To prioritize among available breeds, the effective number of chromosome segmen...

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Detalles Bibliográficos
Autores principales: Marjanovic, Jovana, Calus, Mario P. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891385/
https://www.ncbi.nlm.nih.gov/pubmed/33040409
http://dx.doi.org/10.1111/jbg.12512
Descripción
Sumario:For numerically small breeds, obtaining a sufficiently large breed‐specific reference population for genomic prediction is challenging or simply not possible, but may be overcome by adding individuals from another breed. To prioritize among available breeds, the effective number of chromosome segments (M (e)) can be used as an indicator of relatedness between individuals from different breeds. The M (e) is also an important parameter in determining the accuracy of genomic prediction. The M (e) can be estimated both within a population and between two populations or breeds, as the reciprocal of the variance of genomic relationships. However, the threshold for number of individuals needed to accurately estimate within or between populations M (e) is currently unknown. It is also unknown if a discrepancy in number of genotyped individuals in two breeds affects the estimates of M (e) between populations. In this study, we conducted a simulation that mimics current domestic cattle populations in order to investigate how estimated M (e) is affected by number of genotyped individuals, single‐nucleotide polymorphism (SNP) density and pedigree availability. Our results show that a small sample of 10 genotyped individuals may result in substantial over or underestimation of M (e). While estimates of within population M (e) were hardly affected by SNP density, between population M (e) values were highly dependent on the number of available SNPs, with higher SNP densities being able to detect more independent chromosome segments. When subtracting pedigree from genomic relationships before computing M (e), estimates of within population M (e) were three to four times higher than estimates with genotypes only; however, between M (e) estimates remained the same. For accurate estimation of within and between population M (e), at least 50 individuals should be genotyped per population. Estimates of within M (e) were highly affected by whether pedigree was used or not. For within M (e), even the smallest SNP density (~11k) resulted in accurate representation of family relationships in the population; however, for between M (e), many more markers are needed to capture all independent segments.