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Maximizing crossbred performance through purebred genomic selection.

Esfandyari H, Sørensen AC, Bijma P - Genet. Sel. Evol. (2015)

Bottom Line: Estimated breeding values for CP can be calculated from additive and dominance effects of alleles that are estimated using pure line data.However, for a high correlation of LD phase, marker effects that were estimated using a single combined reference population increased the gain in CP.Furthermore, if the correlation of LD phase between pure lines is high, accuracy of selection can be increased by combining the two pure lines into a single reference population to estimate marker effects.

View Article: PubMed Central - PubMed

Affiliation: Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark. Hadi.esfandyari@mbg.au.dk.

ABSTRACT

Background: In livestock production, many animals are crossbred, with two distinct advantages: heterosis and breed complementarity. Genomic selection (GS) can be used to select purebred parental lines for crossbred performance (CP). Dominance being the likely genetic basis of heterosis, explicitly including dominance in the GS model may be an advantage to select purebreds for CP. Estimated breeding values for CP can be calculated from additive and dominance effects of alleles that are estimated using pure line data. The objective of this simulation study was to investigate the benefits of applying GS to select purebred animals for CP, based on purebred phenotypic and genotypic information. A second objective was to compare the use of two separate pure line reference populations to that of a single reference population that combines both pure lines. These objectives were investigated under two conditions, i.e. either a low or a high correlation of linkage disequilibrium (LD) phase between the pure lines.

Results: The results demonstrate that the gain in CP was higher when parental lines were selected for CP, rather than purebred performance, both with a low and a high correlation of LD phase. For a low correlation of LD phase between the pure lines, the use of two separate reference populations yielded a higher gain in CP than use of a single reference population that combines both pure lines. However, for a high correlation of LD phase, marker effects that were estimated using a single combined reference population increased the gain in CP.

Conclusions: Under the hypothesis that performance of crossbred animals differs from that of purebred animals due to dominance, a dominance model can be used for GS of purebred individuals for CP, without using crossbred data. Furthermore, if the correlation of LD phase between pure lines is high, accuracy of selection can be increased by combining the two pure lines into a single reference population to estimate marker effects.

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Heterosis in crossbred individuals. (a) Results for a low correlation of LD phase between breeds A and B (r = 0.2 for markers 1 cM apart). (b) Results for a high correlation of LD phase between breeds A and B (r = 0.7 for markers 1 cM apart). The plotted heterosis values are means from 30 replicates. Sc. Ref: Selection criteria in both breed A and B was for purebred performance (P) and both breeds had Separate training sets. Sc.1: Selection criteria in breed A was for crossbred performance (C) and selection criteria in breed B was for purebred performance and both breeds had separate training sets. Sc.2: Selection criteria in both breed A and B was for crossbred performance and both breeds had separate training sets. Sc.3: Selection criteria in breed A was for crossbred performance and selection criteria in breed B was for purebred performance and both breeds had a Common training set. Sc.4: Selection criteria in both breed A and B was for crossbred performance and both breeds had a common training set.
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Fig6: Heterosis in crossbred individuals. (a) Results for a low correlation of LD phase between breeds A and B (r = 0.2 for markers 1 cM apart). (b) Results for a high correlation of LD phase between breeds A and B (r = 0.7 for markers 1 cM apart). The plotted heterosis values are means from 30 replicates. Sc. Ref: Selection criteria in both breed A and B was for purebred performance (P) and both breeds had Separate training sets. Sc.1: Selection criteria in breed A was for crossbred performance (C) and selection criteria in breed B was for purebred performance and both breeds had separate training sets. Sc.2: Selection criteria in both breed A and B was for crossbred performance and both breeds had separate training sets. Sc.3: Selection criteria in breed A was for crossbred performance and selection criteria in breed B was for purebred performance and both breeds had a Common training set. Sc.4: Selection criteria in both breed A and B was for crossbred performance and both breeds had a common training set.

Mentions: Based on the definition of heterosis, expected CP can be written as CP = BA + H, where BA denotes the breed average of pure lines and H the heterosis present in the crossbred animals. Thus, the observed advantage of selection for CP in some scenarios may be due to greater response in BA or in H, or in both. Heterosis was calculated at each generation of the crossbred population (Figure 6) and Table 3 shows BA values for each scenario. Since heterosis was simulated due to dominance, total heterosis was simply the sum of heterosis at each locus, H = ∑ dl(pA,l − pB,l)2, where dl is the dominance effect at QTL l, pA,l is the allele frequency at QTL l in breed A, and pB,l is the allele frequency at QTL l in breed B [7]. For both low and high correlations of LD phase, the amount of heterosis in the reference scenario was constant over generations but in other scenarios in which at least one breed was selected for CP, the amount of heterosis increased in each generation, which indicates that selection for CP resulted in greater heterosis and finally in improved performance of crossbred animals. Since heterosis depends on the difference in allele frequencies between the two breeds, these results suggest that selection for CP moves allele frequencies in the two breeds in opposite directions and causes divergence in allele frequencies between both breeds.Figure 6


Maximizing crossbred performance through purebred genomic selection.

Esfandyari H, Sørensen AC, Bijma P - Genet. Sel. Evol. (2015)

Heterosis in crossbred individuals. (a) Results for a low correlation of LD phase between breeds A and B (r = 0.2 for markers 1 cM apart). (b) Results for a high correlation of LD phase between breeds A and B (r = 0.7 for markers 1 cM apart). The plotted heterosis values are means from 30 replicates. Sc. Ref: Selection criteria in both breed A and B was for purebred performance (P) and both breeds had Separate training sets. Sc.1: Selection criteria in breed A was for crossbred performance (C) and selection criteria in breed B was for purebred performance and both breeds had separate training sets. Sc.2: Selection criteria in both breed A and B was for crossbred performance and both breeds had separate training sets. Sc.3: Selection criteria in breed A was for crossbred performance and selection criteria in breed B was for purebred performance and both breeds had a Common training set. Sc.4: Selection criteria in both breed A and B was for crossbred performance and both breeds had a common training set.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4358869&req=5

Fig6: Heterosis in crossbred individuals. (a) Results for a low correlation of LD phase between breeds A and B (r = 0.2 for markers 1 cM apart). (b) Results for a high correlation of LD phase between breeds A and B (r = 0.7 for markers 1 cM apart). The plotted heterosis values are means from 30 replicates. Sc. Ref: Selection criteria in both breed A and B was for purebred performance (P) and both breeds had Separate training sets. Sc.1: Selection criteria in breed A was for crossbred performance (C) and selection criteria in breed B was for purebred performance and both breeds had separate training sets. Sc.2: Selection criteria in both breed A and B was for crossbred performance and both breeds had separate training sets. Sc.3: Selection criteria in breed A was for crossbred performance and selection criteria in breed B was for purebred performance and both breeds had a Common training set. Sc.4: Selection criteria in both breed A and B was for crossbred performance and both breeds had a common training set.
Mentions: Based on the definition of heterosis, expected CP can be written as CP = BA + H, where BA denotes the breed average of pure lines and H the heterosis present in the crossbred animals. Thus, the observed advantage of selection for CP in some scenarios may be due to greater response in BA or in H, or in both. Heterosis was calculated at each generation of the crossbred population (Figure 6) and Table 3 shows BA values for each scenario. Since heterosis was simulated due to dominance, total heterosis was simply the sum of heterosis at each locus, H = ∑ dl(pA,l − pB,l)2, where dl is the dominance effect at QTL l, pA,l is the allele frequency at QTL l in breed A, and pB,l is the allele frequency at QTL l in breed B [7]. For both low and high correlations of LD phase, the amount of heterosis in the reference scenario was constant over generations but in other scenarios in which at least one breed was selected for CP, the amount of heterosis increased in each generation, which indicates that selection for CP resulted in greater heterosis and finally in improved performance of crossbred animals. Since heterosis depends on the difference in allele frequencies between the two breeds, these results suggest that selection for CP moves allele frequencies in the two breeds in opposite directions and causes divergence in allele frequencies between both breeds.Figure 6

Bottom Line: Estimated breeding values for CP can be calculated from additive and dominance effects of alleles that are estimated using pure line data.However, for a high correlation of LD phase, marker effects that were estimated using a single combined reference population increased the gain in CP.Furthermore, if the correlation of LD phase between pure lines is high, accuracy of selection can be increased by combining the two pure lines into a single reference population to estimate marker effects.

View Article: PubMed Central - PubMed

Affiliation: Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark. Hadi.esfandyari@mbg.au.dk.

ABSTRACT

Background: In livestock production, many animals are crossbred, with two distinct advantages: heterosis and breed complementarity. Genomic selection (GS) can be used to select purebred parental lines for crossbred performance (CP). Dominance being the likely genetic basis of heterosis, explicitly including dominance in the GS model may be an advantage to select purebreds for CP. Estimated breeding values for CP can be calculated from additive and dominance effects of alleles that are estimated using pure line data. The objective of this simulation study was to investigate the benefits of applying GS to select purebred animals for CP, based on purebred phenotypic and genotypic information. A second objective was to compare the use of two separate pure line reference populations to that of a single reference population that combines both pure lines. These objectives were investigated under two conditions, i.e. either a low or a high correlation of linkage disequilibrium (LD) phase between the pure lines.

Results: The results demonstrate that the gain in CP was higher when parental lines were selected for CP, rather than purebred performance, both with a low and a high correlation of LD phase. For a low correlation of LD phase between the pure lines, the use of two separate reference populations yielded a higher gain in CP than use of a single reference population that combines both pure lines. However, for a high correlation of LD phase, marker effects that were estimated using a single combined reference population increased the gain in CP.

Conclusions: Under the hypothesis that performance of crossbred animals differs from that of purebred animals due to dominance, a dominance model can be used for GS of purebred individuals for CP, without using crossbred data. Furthermore, if the correlation of LD phase between pure lines is high, accuracy of selection can be increased by combining the two pure lines into a single reference population to estimate marker effects.

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