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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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Distribution of allele frequencies in the last generation of the historical population for a low (a) and a high correlation of LD phase (b). The bounds are 0.01 and 0.99. The plots are the result of one replicate.
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Fig2: Distribution of allele frequencies in the last generation of the historical population for a low (a) and a high correlation of LD phase (b). The bounds are 0.01 and 0.99. The plots are the result of one replicate.

Mentions: Figure 2 shows the distribution of marker allele frequencies for the last generation of the historical population. Since the initial allele frequencies were sampled from a uniform distribution, a kind of uniform distribution was expected with some fluctuations after 2000 generations of random mating, under a balance between mutation and random genetic drift due to finite population size. Although, a U-shaped distribution is typically observed with sequence data [22], allele frequencies on SNP chips tend to be uniform [23].Figure 2


Maximizing crossbred performance through purebred genomic selection.

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

Distribution of allele frequencies in the last generation of the historical population for a low (a) and a high correlation of LD phase (b). The bounds are 0.01 and 0.99. The plots are the result of one replicate.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig2: Distribution of allele frequencies in the last generation of the historical population for a low (a) and a high correlation of LD phase (b). The bounds are 0.01 and 0.99. The plots are the result of one replicate.
Mentions: Figure 2 shows the distribution of marker allele frequencies for the last generation of the historical population. Since the initial allele frequencies were sampled from a uniform distribution, a kind of uniform distribution was expected with some fluctuations after 2000 generations of random mating, under a balance between mutation and random genetic drift due to finite population size. Although, a U-shaped distribution is typically observed with sequence data [22], allele frequencies on SNP chips tend to be uniform [23].Figure 2

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.

Show MeSH