A theoretical derivation of response to selection with and without controlled mating in honeybees

Du, Manuel; Bernstein, Richard; Hoppe, Andreas; Bienefeld, Kaspar

doi:10.1186/s12711-021-00606-5

Cited by 9 publications

(7 citation statements)

References 32 publications

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“…However, it is unclear, how genetic parameters that were received from the QM or WM should be integrated into modern strategies of genetic evaluation. In any case, without controlled mating, the genetic progress in breeding programs will be slow ( Plate et al 2019b ; Du et al 2021a ). When using the QM and WM in populations with controlled mating, one should bear in mind that the genetic influence on a trait is likely to be overestimated.…”

Section: Discussionmentioning

confidence: 99%

“…The situation for the honeybee can be ameliorated by the use of artificial insemination or isolated mating stations, which provide a certain degree of paternal pedigree information ( Bienefeld et al 1989 ; Brascamp and Bijma 2014 ; Uzunov et al 2017 ). But although it has been shown that these strategies substantially enhance genetic response ( Plate et al 2019b ; Du et al 2021a ), many honeybee populations are still bred without or with incomplete mating control ( Andonov et al 2019 ; De la Mora et al 2020 ; Maucourt et al 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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Influence of model selection and data structure on the estimation of genetic parameters in honeybee populations

Bernstein

Hoppe

et al. 2022

G3 Genes|Genomes|Genetics

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Estimating genetic parameters of quantitative traits is a prerequisite for animal breeding. In honeybees, the genetic variance separates into queen and worker effects. However, under data paucity, parameter estimations that account for this peculiarity often yield implausible results. Consequently, simplified models which attribute all genetic contributions to either the queen (queen model) or the workers (worker model) are often used to estimate variance components in honeybees. However, the causes for estimations with the complete model (colony model) to fail and the consequences of simplified models for variance estimates are little understood. We newly developed the necessary theory to compare parameter estimates that were achieved by the colony model with those of the queen and worker models. Furthermore, we performed computer simulations to quantify the influence of model choice, estimation algorithm, true genetic parameters, rates of controlled mating, apiary sizes, and phenotype data completeness on the success of genetic parameter estimations. We found that successful estimations with the colony model were only possible if at least some of the queens mated controlledly on mating stations. In that case, estimates were largely unbiased if more than 20% of the colonies had phenotype records. The simplified queen and worker models proved more stable and yielded plausible parameter estimates for almost all settings. Results obtained from these models were unbiased when mating was uncontrolled, but with controlled mating, the simplified models consistently overestimated heritabilities. This work elucidates the requirements for variance component estimation in honeybees and provides the theoretical groundwork for simplified honeybee models.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of model selection and data structure on the estimation of genetic parameters in honeybee populations

Bernstein

Hoppe

et al. 2022

G3 Genes|Genomes|Genetics

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“…The ratio between maternal and direct genetic gain was also only slightly influenced by the mode of genetic In contrast, earlier studies have shown that this ratio can be heavily influenced by the mating strategy of the breeding programme (Du et al, 2021a;Kistler et al, 2021;Plate et al, 2019b). Furthermore, Bernstein et al (2021) showed that the inclusion of genomic queen data into the BLUP evaluations shifts the breeding focus towards the maternal effects.…”

Section: Single-trait Selectionmentioning

confidence: 87%

“…Instead, both phenomena were consequences of incomplete phenotype records due to preselection strategies. Thus, in comparison with other factors that influence breeding success in honeybees, such as mating control (Du et al, 2021a; Plate et al, 2019b) or the inclusion of genomic data in the relationship matrix (Bernstein et al, 2021; Brascamp et al, 2018; Gupta et al, 2013), the use of correct genetic parameters in single‐trait selection appears secondary. The results clearly suggest that BLUP selection is a viable option in honeybee breeding, also for incipient breeding programmes where genetic parameters cannot yet be estimated with high accuracy.…”

Section: Discussionmentioning

confidence: 99%

Consequences of incorrect genetic parameter estimates for single‐trait and multi‐trait genetic evaluations in honeybees

Bernstein

Hoppe

et al. 2022

J Animal Breeding Genetics

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Genetic and residual variances of traits are important input parameters for best linear unbiased prediction (BLUP) breeding value estimation. In honeybees, estimates of these variances are often associated with large standard errors, entailing a risk to perform genetic evaluations under wrong premises. The consequences hereof have not been sufficiently studied. In particular, there are no adequate investigations on this topic accounting for multi‐trait selection or genetic peculiarities of the honeybee. We performed simulation studies and explored the consequences of selection for honeybee populations with a broad range of true and assumed genetic parameters. We found that in single‐trait evaluations, the response to selection was barely compromised by assuming erroneous parameters, so that reductions in genetic progress after 20 years never exceeded 21%. Phenotypic selection appeared inferior to BLUP selection, particularly under low heritabilities. Parameter choices for genetic evaluation had great effects on inbreeding development. By wrongly assuming high heritabilities, inbreeding rates were reduced by up to 74%. When parallel selection was performed for two traits, the right choice of genetic parameters appeared considerably more crucial as several incorrect premises yielded inadvertent negative selection for one of the traits. This phenomenon occurred in multiple constellations in which the selection traits expressed a negative genetic correlation. It was not reflected in the estimated breeding values. Our results indicate that breeding efforts heavily rely on detailed knowledge on genetic parameters, particularly when multi‐trait selection is performed. Thus, considerable effort should be invested into precise parameter estimations.

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“…The fact that the larvae from the observed patrilines differed in their ability to resist infections by M. plutonius suggests a paternally transmissible mechanism, which raises the prospect of breeding honey bee lineages resistant to this pathogen. Population genetics simulations and modelling studies have shown that controlled breeding of honey bees using high‐quality drones is beneficial for colonies because it increases breeding success (Du et al, 2021; Plate et al, 2019). Such a medication‐free approach is highly desirable, as there is currently no sustainable method in the beekeeping industry for combating EFB infection.…”

Section: Discussionmentioning

confidence: 99%

Differential resistance across paternal genotypes of honey bee brood to the pathogenic bacteriumMelissococcus plutonius

Ameline

Beaurepaire

Ory

et al. 2022

J Applied Entomology

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The bacterium Melissococcus plutonius is the causative agent of European foulbrood (EFB), a disease affecting immature stages (i.e., brood) of honey bees (Forsgren, 2010). This gram-positive bacterium is transmitted by symptomless adult honey bees to young larvae, which become infected after ingesting the pathogen through contaminated food. The bacterium then multiplies in the larvae's gut, which can lead to their death. As a result, within-colony population dynamics are disturbed, to the point that colonies can collapse (Forsgren, 2010). Transmission of EFB between colonies and apiaries is high, leading to local and recurrent outbreaks of increasing frequency in several countries over the last decades (Belloy et al., 2007;Budge et al., 2014;Grossar et al., 2020). Thus, EFB poses a major threat to honey bee health and contributes, together with other biotic and abiotic factors, to recent non-sustainable increases in colony losses in many regions of the Northern hemisphere (Goulson et al., 2015;Neumann & Carreck, 2010).To mitigate the impact of EFB disease, one option for beekeepers is to apply antibiotics, e.g. oxytetracycline hydrochloride. However, antibiotic treatment is not sustainable, as it may (i) remove the symptoms but not the causative agent of the disease (Thompson &

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A theoretical derivation of response to selection with and without controlled mating in honeybees

Cited by 9 publications

References 32 publications

Influence of model selection and data structure on the estimation of genetic parameters in honeybee populations

Influence of model selection and data structure on the estimation of genetic parameters in honeybee populations

Consequences of incorrect genetic parameter estimates for single‐trait and multi‐trait genetic evaluations in honeybees

Differential resistance across paternal genotypes of honey bee brood to the pathogenic bacteriumMelissococcus plutonius

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