Abstract
Estimated breeding values (EBVs) are traditionally obtained from pedigree information. However, EBVs from high-density genotypes can have higher accuracy than EBVs from pedigree information. At the same time, it has been shown that EBVs from genomic data lead to lower increases in inbreeding compared with traditional selection based on genealogies. Here we evaluate the performance with BLUP selection based on genealogical coancestry with three different genome-based coancestry estimates: (1) an estimate based on shared segments of homozygosity, (2) an approach based on SNP-by-SNP count corrected by allelic frequencies, and (3) the identity by state methodology. We evaluate the effect of different population sizes, different number of genomic markers, and several heritability values for a quantitative trait. The performance of the different measures of coancestry in BLUP is evaluated in the true breeding values after truncation selection and also in terms of coancestry and diversity maintained. Accordingly, cross-performances were also carried out, that is, how prediction based on genealogical records impacts the three other measures of coancestry and inbreeding, and viceversa. Our results show that the genetic gains are very similar for all four coancestries, but the genomic-based methods are superior to using genealogical coancestries in terms of maintaining diversity measured as observed heterozygosity. Furthermore, the measure of coancestry based on shared segments of the genome seems to provide slightly better results on some scenarios, and the increase in inbreeding and loss in diversity is only slightly larger than the other genomic selection methods in those scenarios. Our results shed light on genomic selection vs. traditional genealogical-based BLUP and make the case to manage the population variability using genomic information to preserve the future success of selection programmes.
Highlights
Best linear unbiased prediction (BLUP) is possibly the most common selection method in animal and plant breeding, where it is used to calculate estimated breeding values (EBVs)
We have shown here results for truncation selection performed with four different measures of coancestry: fA, fG, fR and fV
All results shown are selecting the top 50% of sires and dams and we have compared results with three different population sizes, three different heritabilities of the selected trait and three different number of markers per chromosome
Summary
Best linear unbiased prediction (BLUP) is possibly the most common selection method in animal and plant breeding, where it is used to calculate estimated breeding values (EBVs). BLUP and genomic relationships evaluations maximize the genetic gain given the data by increasing the accuracy of the predictions (Henderson, 1984) This method relies on both the additive relationship matrix between the individuals in the population, which are traditionally obtained from pedigree records, and on phenotypic records of the candidates to selection. Genome-based EBV (estimated breeding values based on high-density marker data across the genome) have generally yielded a higher accuracy than pedigree-based EBV (Meuwissen et al, 2001; Goddard, 2009; Hayes et al, 2009; Sonesson et al, 2012; Rodriguez-Ramilo et al, 2014). While the genealogical relationship between two full-sibs is 0.5, using molecular markers like high-density SNP chips, a more accurate value can be obtained, showing that the true relationship deviates from 0.5 (Visscher et al, 2006) and varies among pairs of sibs, depending on the segregation of the parental chromosomes (Garcia-Cortes et al, 2013)
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