Using pooled data to estimate variance components and breeding values for traits affected by social interactions

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Abstract

Background: Through social interactions, individuals affect one another's phenotype. In such cases, an individual's phenotype is affected by the direct (genetic) effect of the individual itself and the indirect (genetic) effects of the group mates. Using data on individual phenotypes, direct and indirect genetic (co)variances can be estimated. Together, they compose the total genetic variance that determines a population's potential to respond to selection. However, it can be difficult or expensive to obtain individual phenotypes. Phenotypes on traits such as egg production and feed intake are, therefore, often collected on group level. In this study, we investigated whether direct, indirect and total genetic variances, and breeding values can be estimated from pooled data (pooled by group). In addition, we determined the optimal group composition, i.e. the optimal number of families represented in a group to minimise the standard error of the estimates. Methods. This study was performed in three steps. First, all research questions were answered by theoretical derivations. Second, a simulation study was conducted to investigate the estimation of variance components and optimal group composition. Third, individual and pooled survival records on 12 944 purebred laying hens were analysed to investigate the estimation of breeding values and response to selection. Results: Through theoretical derivations and simulations, we showed that the total genetic variance can be estimated from pooled data, but the underlying direct and indirect genetic (co)variances cannot. Moreover, we showed that the most accurate estimates are obtained when group members belong to the same family. Additional theoretical derivations and data analyses on survival records showed that the total genetic variance and breeding values can be estimated from pooled data. Moreover, the correlation between the estimated total breeding values obtained from individual and pooled data was surprisingly close to one. This indicates that, for survival in purebred laying hens, loss in response to selection will be small when using pooled instead of individual data. Conclusions: Using pooled data, the total genetic variance and breeding values can be estimated, but the underlying genetic components cannot. The most accurate estimates are obtained when group members belong to the same family. © 2013 Peeters et al.; licensee BioMed Central Ltd.

Figures

  • Table 1 Notation key
  • Table 2 Within-family variance (σ2w) and number of records per family (m) for three group compositions
  • Table 3 Scenarios used to simulate data
  • Table 4 True and estimated σ2AT and σ 2 E for five scenarios
  • Table 5 Theoretically predicted s:e: σ̂2AT , s:d: σ̂2AT § and s:e: σ̂2AT §§ for three group compositions
  • Table 6 Estimated variance components (with s.e.) from individual and pooled data on survival in laying hens
  • Table 7 Spearman correlation coefficients between ÂD’s and ÂT’s obtained from individual data and  ’s from pooled data on survival in laying hens
  • Figure 1  T’s obtained from individual data plotted against ÂD’s obtained from individual data and  ’s obtained from pooled data on survival in laying hens. A and B for data on W1 hens. C and D for data on WB hens. ΔG1 represents the total response to selection when selecting animals based on their ÂD obtained from individual data or  obtained from pooled data. ΔG2 represents the total response to selection when selecting animals based on their  T obtained from individual data.

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APA

Peeters, K., Ellen, E. D., & Bijma, P. (2013). Using pooled data to estimate variance components and breeding values for traits affected by social interactions. Genetics Selection Evolution, 45(1). https://doi.org/10.1186/1297-9686-45-27

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