Additional file 2 of Uncertainty in the mating strategy of honeybees causes bias and unreliability in the estimates of genetic parameters
Creators: name: Kistler, Tristan
name: Brascamp, Evert W.
name: Basso, Benjamin
name: Bijma, Piter
name: Phocas, Florence
Publisher: name: figshare
Year: 2024
Subjects: subject: Statistics
subject: FOS: Mathematics

description: Additional file 2: Table S1. Input parameters for the simulations. The table shows the main input parameters for all the simulations, including genetic parameter sets other than that used for the main text. σ2: variance of worker (W), queen (Q) or residual (e) effects in the base population. The only environmental fixed effect was a year effect with variance $${\upsigma }_{{\text{year}}}^{2}$$ σ year 2 . $${{\text{r}}}_{{\text{WQ}}}$$ r WQ : genetic correlation between worker and queen effects. BQs: breeding queens, DPQs: drone-producing queens. Table S2. AIReML starting parameter values and convergence criteria. The table shows the initial values used to estimate (co)variances $${\upsigma }_{{\text{W}}}^{2}$$ σ W 2 , $${\upsigma }_{{\text{Q}}}^{2}$$ σ Q 2 , $${\upsigma }_{{\text{e}}}^{2}$$ σ e 2 and $${\upsigma }_{{\text{WQ}}}$$ σ WQ , respectively, for the worker, queen and residual effects, and the covariance between worker and queen effects. The true values for genetic variances $${\upsigma }_{{\text{W}}}^{2}$$ σ W 2 and $${\upsigma }_{{\text{Q}}}^{2}$$ σ Q 2 were 10 and 20, respectively, and for the covariance 0, − 5, or approximately − 7, respectively, depending on the genetic parameter set. The true $${\upsigma }_{{\text{e}}}^{2}$$ σ e 2 was always equal to 30. Table S3. True and estimated genetic trends for all genetic parameter sets and sire modeling scenarios of controlled mating. $${\upsigma }_{{\text{W}}}^{2}$$ σ W 2 , $${{\text{r}}}_{{\text{WQ}}}$$ r WQ : genetic variance of worker effects and genetic correlation between worker and queen effects. The genetic trends (true and estimated) were calculated as the linear regression coefficients of true breeding values (BV) and estimated breeding values (EBV) for worker (W) and queen (Q) effects over breeding years (after the fifth year of the breeding program, when the nucleus became closed). Controlled mating strategy under the simulation: SS (single sire) and PS (pseudo sire) mating. Sire pedigree modeling for controlled mating: C_SSP, C_dummySSP/Q, C_dummySSP/DPQdam, C_PSP: controlled mated queens are assigned respectively in the pedigree single sires, dummy single sires per dam of DPQ(s), dummy single sires per mated queen, pseudo sires. Table S4. Errors affecting estimates for genetic parameter sets with a null $${{\text{r}}}_{{\text{WQ}}}$$ r WQ and all sire modeling scenarios for controlled mating. $${\upsigma }_{{\text{W}}}^{2}$$ σ W 2 , $${\upsigma }_{{\text{Q}}}^{2}$$ σ Q 2 , $${{\text{r}}}_{{\text{WQ}}}$$ r WQ : genetic variances and correlation for worker and queen effects. $${\upsigma }_{{\text{e}}}^{2}$$ σ e 2 : residual variance. Estimates are denoted by ‘^’; strong deviations differ by more than 20% from the true values. Controlled mating strategy under the simulation: SS (single sire) and PS (pseudo sire) mating. Sire pedigree modeling for controlled mating: C_SSP, C_dummySSP/DPQdam, C_dummySSP/Q, C_PSP: controlled mated queens are assigned respectively in the pedigree single sires, dummy single sires per dam of DPQ(s), dummy single sires per mated queen, pseudo sires. Table S5. Errors affecting estimates for genetic parameter sets with a negative $${{\text{r}}}_{{\text{WQ}}}$$ r WQ and all sire modeling scenarios for controlled mating. $${\upsigma }_{{\text{W}}}^{2}$$ σ W 2 , $${\upsigma }_{{\text{Q}}}^{2}$$ σ Q 2 , $${{\text{r}}}_{{\text{WQ}}}$$ r WQ : genetic variances and correlation for worker and queen effects. $${\upsigma }_{{\text{e}}}^{2}$$ σ e 2 : residual variance. Estimates are denoted by ‘^’; strong deviations differ by more than 20% from the true values. Controlled mating strategy under the simulation: SS (single sire) and PS (pseudo sire) mating. Sire pedigree modeling for controlled mating: C_SSP, C_dummySSP/DPQdam, C_dummySSP/Q, C_PSP: controlled mated queens are assigned respectively in the pedigree single sires, dummy single sires per dam of DPQ(s), dummy single sires per mated queen, pseudo sires. Table S6. Errors affecting estimates for all genetic parameter sets and sire modeling scenarios for open mating. $${\upsigma }_{{\text{W}}}^{2}$$ σ W 2 , $${\upsigma }_{{\text{Q}}}^{2}$$ σ Q 2 , $${{\text{r}}}_{{\text{WQ}}}$$ r WQ : genetic variances and correlation for worker and queen effects. $${\upsigma }_{{\text{e}}}^{2}$$ σ e 2 : residual variance. Estimates are denoted by ‘^’; strong deviations differ by more than 20% from the true values. The controlled mating strategy was single sire mating (SSS). Sire modeling for open mating: O_NoPheno: open-mated DPQ colony phenotypes are excluded from the genetic analysis; O_PSP, O_TwoPSP: open-mated DPQs are assigned in the pedigree respectively a single open mating pseudo sire, or one for each open-mating drone subpopulation (initial BQs and each half of the DPQ); O_FixedGroup or O_RandGroup: the effect of drone subpopulations mating DPQs is accounted for by adding a fixed or a random non-genetic effect in the statistical model that describes the phenotypes. Table S7. True and estimated genetic trends for all genetic parameter sets and sire modeling scenarios for open mating. $${\upsigma }_{{\text{W}}}^{2}$$ σ W 2 , $${{\text{r}}}_{{\text{WQ}}}$$ r WQ : genetic variance of worker effects and genetic correlation between worker and queen effects. The genetic trends (true and estimated) were calculated as the linear regression coefficients of true breeding values (BV) and estimated breeding values (EBV) for worker (W) and queen (Q) effects over breeding years (from the fifth year of the breeding program, when the nucleus became closed). The controlled mating strategy was single sire mating (SS). Sire modeling for open mating: O_NoPheno: open-mated DPQ colony phenotypes are excluded from the genetic analysis; O_PSP, O_TwoPSP: open-mated DPQs are assigned in the pedigree respectively a single open mating pseudo sire, or one for each open-mating drone subpopulation (initial BQs and each half of the DPQ); O_FixedGroup or O_RandGroup: the effect of drone subpopulations mating DPQs is accounted for by adding a fixed or a random non-genetic effect in the statistical model that describes the phenotypes. Table S8. AIReML predicted and realized standard errors (SE) of genetic (co)variances. Predicted SE: mean prediction (by the inverse averaged information matrix) of the SE of genetic (co)variance estimates over repetitions. Realized SE: SD over repetitions of the error on the variance estimates of worker $$({\widehat{\upsigma }}_{{\text{W}}}^{2})$$ ( σ ^ W 2 ) and queen $$({\widehat{\upsigma }}_{{\text{Q}}}^{2})$$ ( σ ^ Q 2 ) effects, as well as the covariance ( $${\widehat{\upsigma }}_{{\text{WQ}}})$$ σ ^ WQ ) . Controlled mating strategy in the simulation: SS (single sire) and PS (pseudo sire) mating. Sire pedigree modeling for controlled mating: C_SSP, C_dummySSP/DPQdam, C_dummySSP/Q, C_PSP: controlled mated queens are assigned respectively in the pedigree single sires, dummy single sires per dam of DPQ(s), dummy single sires per mated queen, pseudo sires.