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International Bee Research Association - IBRA September 1 “Selective honey bee breeding is a phenomenon that fascinates beekeepers around the world. They often regard it as one of the most enigmatic and complex aspects of beekeeping. Indeed, according to our experiences in participating in many international projects, both beekeepers and bee experts without a background in plant or animal breeding often have trouble correctly interpreting and conceptually visualizing the breeding process. These difficulties arise partly because of the complex reproductive biology of honey bees, where queens mate with a multitude of drones. Fundamentally the greatest struggle for people to understand is how selection of animals with preferred characteristics in one generation leads to improved progeny in the next”. In a new article published in Bee World, Alexandar Uzunov and colleagues from the Bee Institute, Kirchhain, Germany explain the basic concepts behind honey bee breeding programmes, using the specific example of the German bee breeding programme for varroa resistance. The article: “The basic concept of honey bee breeding programs” can be found here: http://www.tandfonline.com/…/…/10.1080/0005772X.2017.1345427 You can become a Member of IBRA here to gain free access to this and all articles in the current issue 94(3), and the entire back catalogue of Bee World to Issue 1 in 1919: http://www.ibrabee.org.uk/2013-05-01-02…/2014-12-12-12-06-01 IBRA is a Registered Charity No 209222. You can make a donation to help our work here: http://www.ibrabee.org.uk/ibra-donations
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ISSN: 0005-772X (Print) 2376-7618 (Online) Journal homepage: http://www.tandfonline.com/loi/tbee20
The Basic Concept of Honey Bee Breeding
Programs
A. Uzunov, E. W. Brascamp & R. Büchler
To cite this article: A. Uzunov, E. W. Brascamp & R. Büchler (2017) The Basic Concept of Honey
Bee Breeding Programs, Bee World, 94:3, 84-87, DOI: 10.1080/0005772X.2017.1345427
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Page 84 • VOL 94 • September 2017 • Bee World
The Basic Concept of Honey Bee
Breeding Programs
A. Uzunov, E. W. Brascamp and R. Büchler
Selective honey bee breeding is a phe-
nomenon that fascinates beekeepers
around the world. ey oen regard it as
one of the most enigmatic and complex
aspects of beekeeping. Indeed, according
to our experiences participating in many
international projects, both beekeepers
and bee experts without a background
in plant or animal breeding oen have
trouble correctly interpreting and con-
ceptually visualizing the breeding process.
ese diculties arise partly because
of the complex reproductive biology of
honey bees, where queens mate with a
multitude of drones. Fundamentally the
greatest struggle for people to understand
is how selection of animals with preferred
characteristics in one generation leads to
improved progeny in the next.
e leading misconception regarding
honey bee breeding is confusing breeding
with the simple rearing and multiplica-
tion of queens, where individual queens
are evaluated predominantly by their egg
laying ability and body size. ose two
markers of queen quality (fecundity and
size) are certainly important for the prop-
agation of queens, but selective breeding
requires more than propagation. Selective
breeding implies the intentional selection
for genetic improvement of the population
as a whole, with every new generation
improved compared to the previous one,
ideally for all traits of interest.
To achieve such improved selection,
queens and colonies in each generation
must be chosen that exhibit the desirable
properties the breeder wishes to propa-
gate, using these as parents for the next
generation so that on average the next
generation is expected to be better than
the previous one. Breeding success for a
certain honey bee population is thus the
cumulative outcome of many actions,
such as performance testing on the colony,
the selection and mating of individuals.
Our aim with this paper is to help demys-
tify conventional honey bee breeding pro-
grams and highlight the typical features of
successful programs, based on the breed-
ing experiences in Central Europe. We
focus on conceptual aspects beekeepers
and breeders can control without discuss-
ing the underlying theories based upon
population and quantitative genetics.
A Breeding Program and
Its Elements
A breeding program represents a set of
systematically planned and implemented
activities aimed at the sustained genetic
improvement of a honey bee population
(Brascamp, 2014; Tiesler et al., 2016).
us, by continuous implementation of
this selection program it is expected that
the colonies in the next generation will
express improved behavior concerning
targeted traits (for instance: gentleness,
calmness on the comb, reduced swarm-
ing), enhanced production (honey, pollen,
wax, royal jelly) and vitality (resistance to
diseases and pests, prolonged life expec-
tancy, etc.).
A breeding program should include
explicit breeding objectives, performance
testing to evaluate the desired character-
istics, estimation of the breeding values,
selection, mating, multiplication of the
improved genetic stock, and evaluation
(Figure 1).
e rst and very important step is to
dene the breeding objective. us, based
on the economic importance, scientic
evidence and practical experience, breed-
ers must decide which traits they intend to
improve, and what is the relative impor-
tance of improving the dierent traits.
Generally, the preferred traits in selection
for honey bees involve improving honey
yield, gentleness, decreasing the swarming
tendancy and increasing Var r o a resist-
ance. Sometimes traits such as coloration,
which are typical for a particular popula-
tion, can be included in the selection pro-
cess. In principle all traits of importance
should be included, because selection
for too limited a set of traits may lead to
deterioration of other relevant traits. For
example selecting only for Var ro a resist-
ance with no regard for the qualities that
make for productive colonies can result in
queens that are not practical for commer-
cial beekeeping.
e German breeding program for
resistance to Var r o a (AGT) is an example
where the focus is on Var ro a resistance
(Table 1), but other traits are also taken
into account. e decision regarding
which traits to include to achieve the
breeding objective depends mainly on the
interests of a particular group of breeders.
Objectives such as the conservation of an
isolated population or specic research
goals can be relevant too.
Since breeding success is accumulated
genetic improvement over time the
© 2017 International Bee Research Association
Figure 1. Elements of a breeding program and sequence of actions. A continual process
of selecting towards the breeding objective. Mating is carried out to produce a next
generation for performance testing, but also for multiplication of the improved material to
be disseminated and utilized in the broad population.
DOI: 10.1080/0005772X.2017.1345427
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© 2017 International Bee Research Association
breeding objective ideally should be con-
sistent from year to year and not subject
to frequent drastic changes. us, before
the objective is dened one should foresee
the needs and demands that might occur
in the future, so that the selection has
long-term relevance. Finally, the breeding
objective should take into account the way
bees are managed and how beekeeping
operations are organized if the goal is
improved stock for beekeepers.
Performance testing requires a standard-
ized methodology for the phenotypic
assessment of traits and accurate data
recording (Büchler et al., 2013; Ruttner,
1972; Uzunov et al., 2015). While in farm
animals performance is generally meas-
ured on individuals (milk production in
dairy cows, egg laying rate in hens), in
honey bees traits are usually observed
on the colony level. is is illustrated in
Figure 2.
On the one hand the workers contribute
to colony’s performance, known as the
worker eect, but the queen (1a) also has
a direct eect (queen eect) on the colo-
ny’s performance. Of course she also con-
tributes indirectly, because she transmits
her breeding value for the worker eect to
the workers. As an example, honey yield is
aected by the ability of workers to collect
nectar, but also by the egg laying capacity
and pheromone production of the queen.
Figure 2 also illustrates that apart from
the queen (1a) that is the mother of the
colony, the drone-producing queens (1b)
also contribute 50% to the breeding value
of the workers. Since drones are haploid
and have no father, it is oen said that
the paternal contributer to the breeding
value of the workers in practice is 4a, the
so-called father colony.
A written guideline for performance
testing (protocol), along with practice
and training of the bee breeders in the
proposed methods (breeders’ capacity
building) are essential so that test colonies
can be evaluated objectively and accu-
rately across apiaries and operations.
Before engaging in a breeding program
and queen evaluation, a number of pre-
paratory activities should be conducted.
ese include establishing test apiaries
and colonies, as well as organizing a
queen exchange among the dierent test
apiaries.1
e next step is the estimation of breeding
values. By denition the breeding value
of an individual is the expected perfor-
mance of the ospring when the indi-
vidual is mated to an average mate and
the ospring is performing in an average
environment. Usually these compli-
cated calculations of the breeding value
estimation are conducted by the facility
that manages the database of performance
testing results.
A best case study of such a system is
represented by BEEBREED (www.
beebreed.eu) where via an online web-
based platform the performance testing
data are stored, breeding values are
estimated and subsequently published. In
BEEBREED the estimated breeding value
of an individual takes into account the
colony’s individual performance as well as
the performances of other colonies in the
same environment (test apiary) and per-
formances of colonies that are ancestors
or other relatives (Figure 3). Comparison
of colony’s performance with that of
colonies at the same test apiary takes into
account dierences caused by beekeeping
techniques applied, weather, food sources
etc. For more details, see Bienefeld et al.
(2007), Büchler et al. (2013), Brascamp
et al. (2016) and Tiesler et al. (2016).
Table 1. The weighting of desirable traits in the AGT breeding program.
aA combination of natural mite fall in spring, mite infestation in late summer and hygienic behavior.
Trait Honey yield Gentleness Calmness Swarming behavior Varroa indexa
Weighting of traits (%) in the total breeding value 15 15 15 15 40
Figure 2. Effects of the workers and queen
on the colony’s performance.
Figure 3. Simplied model of the effects contributing to the estimation of breeding
values according to BLUP Animal Model.
DOI: 10.1080/0005772X.2017.1345427
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To obtain reliable breeding values, it is
important that daughters of each breeder
queen are tested at several test apiaries.
e selection of queens based upon
ranking for estimated breeding values is
a further step in the breeding program.
Usually individual breeders not only select
based upon this criterion but include
additional observations such as overwin-
tering ability, colony strength, etc. us
queens are ranked and selected as mothers
for the next generation of queens as well
as queens to produce drone producing
queens. Oen individual breeders decide
what queens they will use to produce the
next generation, while an association is
oen responsible for selecting the queen
that will be the mother of the queens
that head the multiple drone colonies at
a mating station, under the assumption
that such a mating station is not used
by one single breeder. Via instrumental
insemination or private isolated mating
yards, an individual breeder can control
which queen stock serves as the paternal
ancestor of the next generation.
In honey bees mating deserves specic
attention due to the reproductive behav-
ior of the species. Special measures are
required to control mating, for exam-
ple through the use of mating stations
(isolated mainland or island locations) or
instrumental insemination. According to
theory the breeding value of a progeny
equals half the sum of the breeding values
of the parents. As a consequence, parents
can be selected independently and mated
at random when it concerns the average
breeding value of the next generation.
However, the desire of individual breed-
ers to compensate for a weakness in a
selected queen with the strength of the
mate advocates for the combined selection
of a queen and her mates and not just the
individual parents. For example a queen
that has excellent Var r o a resistance and
honey production, but a higher swarm
tendency might be mated with drones that
originated from a queen that exhibited a
very low swarm drive. Another benet of
selecting both partners is that potential
inbreeding of workers can be taken into
account.
Genetic improvement is the ultimate
goal of a breeding program and involves
eventual propagation of the improved
stock in the general honey bee population
(Büchler et al., 2010; Rinderer et al., 2010).
e beekeeping community can incorpo-
rate improved stock on the maternal side
in the form of graed larvae, queens cells,
virgin or mated queens. rough the use
of drone semen in instrumental insemina-
tion or the mating stations where selected
queens produce drones that will mate the
virgin queens, beekeepers can incorporate
improved genetic stock on the paternal
side, helping to improve the quality of the
bee population.
We feel that the topic of propagation
of improved stock does not receive the
attention it deserves. Activities concerning
this goal, like transparent communication,
marketing and ecient delivery systems,
should be well planned and implemented
and require concerted actions of the bee-
keeping community at large.
Finally, a program should systematically
be subjected to evaluation. is should
be recognized as a distinct element. e
rst step is to compare the predicted
and realized selection response or “does
the program meet its promises?. In the
evaluation, all elements and steps of the
breeding program should be scrutinized
and any obstacles should be identied and
removed.
Here issues like the accuracy of the meth-
odology for data gathering, the recording
of pedigrees, and the accuracy of breeding
value estimations should be evaluated, as
well as re-evaluating strategic goals and
delineating future expectations. In addi-
tion, breeding programs should consider
if the environments in which the daughter
queens of the breeding program perform
are suciently uniform, such that the col-
onies produced from the better line in one
environment are consistently the better
ones in another environment.
Types of Breeding
Programs
In the previous paragraphs we described
a breeding program based strongly on the
results of BEEBREED and the beekeeping
community in Europe. However, the rea-
sons to keep, and possibly improve honey
bees, dier among bee breeders around
the world.
ere is a wide spectrum of breeding pro-
grams. To illustrate this we list the most
common types of breeding programs.
Commercial, aimed to improve the
overall performance of the honey bees
from the population of interest, based
upon the assessment of various traits.
Occasionally, the number of traits is
limited to 3 or 4. However, the main
drive and objective of these commercial
breeding programs is improvement in
commercially important traits (more
honey, less defensive bees, reduced
swarming tendency, etc.). is type of
selection is most common and consid-
ered by us as the most sustainable.
Conservation, aimed at the maintenance
of endangered honey bee populations.
e ultimate goal is maintenance or
enlargement of the population. Genetic
improvement of such populations is a
useful tool in the context of “conser-
vation by utilization, as conservation
by utilization is considered a preferred
mechanism to conserve subspecies or
populations. Along with commonly rec-
ognized traits, relevant on the regional
or local scale, morphological characters
and molecular markers are frequently
the basis for decision-making and selec-
tion, the latter two being used to ensure
that the population is not mixed with
other subspecies.
Research breeding programs can be ini-
tiated for studying certain traits (eects
of the genes, identication of markers,
etc.) of scientic interest as well as
analyzing the eects of hybridization or
inbreeding, assessing the adaptive abil-
ity of populations, resistance to diseases,
genotype by environment interactions,
etc. Generally these breeding programs
are short-term and under the respon-
sibility of research institutes or other
academic institutions.
Whatever type of breeding program is
initialized there is always the question
of the genetic origin of the population
under selection. In general there are two
main approaches. Recently a trend has
emerged for sustainable conservation, a
popular breeding approach to improve
and conserve the native or locally adapted
honey bee populations or subspecies. e
basic philosophy behind this is to reduce
importations and instead utilize and
improve the local populations in compari-
son to the non-local ones.
Alternatively, oen breeders start a breed-
ing program building upon breeds like
Ligustica, Carnica or Buckfast (which can
be considered a breed of recent origin)
with assumed general usefulness accross
environments. From a conservation point
of view the disadvantage of this is that
the mixing of local populations and these
general purpose populations, when kept
in the same area, is dicult to prevent.
Whatever approach is chosen the main
issue during the initiation of the breeding
program is appropriate selection of the
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rst genotypes. Here the best advice is to
choose the best available queens, prefer-
ably based on a breeder’s records, taking
care that the founding queens represent
sucient genetic diversity.
Conducting the Breeding
Program
Breeders, regional groups, scientists,
national and local authorities are the
main partners of a breeding program.
e organization of regular meetings is
important for better coordination of the
activities as well as for exchange of ideas
and overcoming the challenges of imple-
mentation. A close cooperation with sci-
entists can signicantly help the program
achieve its breeding objective, by aiding in
the development of standardized meth-
odology and introducing new approaches
and models of breeding.
Concerning the establishment of con-
trolled mating locations, the cooperation
with local authorities may be important.
If we take in to consideration the above
mentioned elements, the overall success
and sustainability of a breeding program
signicantly depends on the collabora-
tion, communication, transparency and
exchange of ideas among all stakeholders
within and around the breeding program.
Acknowledgment
We would like to thank Dr. Bjorn Dahle,
Dr. Sreten Andonov, Dr. Eliza Cauia, Egoitz
Galarza, Borce Pavlov, Dr. Andreas Hoppe
and Dirk Ahrens-Lagast for their valuble
comments and suggestions for improvement
of the readability of the article and integra-
tion of experience from various breeding
practices across Europe.
Note
1. Location or apiary where testing of the colonies is
performed.
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Retrieved from www.smartbees.eu
A. Uzunov and R. Büchler
Bee Institute in Kirchhain, Erlenstrasse 9,
Kirchhain 35274, Germany
Email: aleksandar.uzunov@llh.hessen.de
E. W. Brascamp
Wageningen University & Research
Animal Breeding and Genomics,
P.O. Box 338, 6700 AH, Wageningen, e
Netherlands
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... Traditionally, beekeepers generate profit from the production of honey, beeswax, pollen, propolis or royal jelly. Other traditional aims of breeding are calmness during inspection, reduced stinging towards the beekeeper, and reduced swarming drive which refers to a behaviour of bees, where half of the colony relocates its nest (Petersen et al. 2020;Ruttner 1988;Uzunov et al. 2017). Over the last few decades, breeding against the parasitic mite Varroa destructor has become a priority, because the parasite contributes to high colony losses (Genersch et al. 2010;Guichard et al. 2020a;Traynor et al. 2016). ...
... Although honey bees contribute to agriculture as a key pollinator (Gallai et al. 2009), adaptation of modern breeding methods to apiculture is comparatively slow. Systematic collection of performance and pedigree data on honey bees in Germany started in the 1950s (Bienefeld and Pirchner 1990) and the estimation of best linear unbiased prediction (BLUP) breeding values began in 1994 (Bienefeld et al. 2007;Hoppe et al. 2020), but to date honey bee breeding programs do not use genomic marker data (Uzunov et al. 2017). Recently, cost-efficient methods for the collection of genomic data in honey bees have become available in the form of a high-density 100K single nucleotide polymorphisms (SNP) chip (Jones et al. 2020). ...
... In commercial honey bee breeding programs, the demands of beekeepers lead to selection traits which differ significantly in terms of methodology and effort for recording and mathematical modelling. Typical aims include increased honey yield, better workability for the beekeeper, and more disease resistance (Petersen et al. 2020;Uzunov et al. 2017). Especially resistance against Varroa destructor is targeted, since this parasitic mite contributes to severe colony losses in numerous countries (Genersch et al. 2010;Guichard et al. 2020a;Traynor et al. 2016). ...
Thesis
Genomische Selektion ist ein Routine-Verfahren bei verschiedenen Nutztierarten, aber noch nicht bei der Honigbiene wegen der Besonderheiten dieser Spezies. Für die Zuchtwertschätzung bei der Honigbiene ist eine spezielle genetische Verwandtschaftsmatrix erforderlich, da die Paarungsbiologie dieser Spezies ungesicherte Vaterschaft, diploide Königinnen und haploide Drohnen umfasst. Die Arbeit präsentiert einen neu-entwickelten Algorithmus zur effizienten Berechnung der Inversen der genetischen Verwandtschaftsmatrix und der Inzuchtkoeffizienten auf großen Datensätzen. Die Methode wurde zur Voraussage von genomischen und Stammbaum-basierten Zuchtwerten in einer Simulationsstudie genutzt. Die Genauigkeit und die Verzerrung der geschätzten Zuchtwerte wurden ausgewertet unter Berücksichtigung verschiedener Größen der Referenzpopulation. Außerdem wurde der Zuchtfortschritt im ersten Durchlauf von Zuchtprogrammen ausgewertet, die Zuchtschemata mit genomischer oder Stammbaum-basierter Selektion nutzten. Ein erheblich größerer Zuchtfortschritt als bei Stammbaum-basierter Selektion wurde mit genomischer Vorselektion erzielt, für die junge Königinnen genotypisiert wurden, und nur die Kandidaten mit den höchsten genomischen Zuchtwerten zur Anpaarung oder Leistungsprüfung zugelassen wurden. Für einen realen Datensatz von ungefähr 3000 genotypisierten Königinnen wurden Stammbaum-basierte und genomische Zuchtwerte für sechs wirtschaftlich bedeutende Merkmale vorhergesagt. Drei Merkmale zeigten eine signifikant höhere Vorhersagegenauigkeit bei genomischer Zuchtwertschätzung gegenüber Stammbaum-basierten Verfahren und die Unterschiede zwischen allen sechs Merkmalen konnten im Wesentlichen aus den genetischen Parametern der Merkmale und der begrenzten Größe der Referenzpopulation erklärt werden. Damit zeigt die Arbeit, dass die genomische Selektion bei der Honigbiene genutzt werden kann, den Zuchtfortschritt zu erhöhen.
... Consequently, we ran 36 ⋅ 36 = 1296 simulations and each of the 36 traits was evaluated with the correct parameter set as well as 35 different incorrect parameter sets. Queens were selected for the sum of the maternal and direct estimated breeding values of their worker groups, which is the standard selection criterion for honeybees (Bienefeld et al., 2007;Brascamp & Bijma, 2014;Uzunov et al., 2017). ...
Article
Full-text available
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.
... In commercial honey bee breeding programs, the demands of beekeepers lead to selection traits which differ significantly in terms of methodology and effort for recording and mathematical modelling. Typical aims include increased honey yield, better workability for the beekeeper, and more disease resistance (Petersen et al. 2020;Uzunov et al. 2017). Especially resistance against Varroa destructor is targeted, since this parasitic mite contributes to severe colony losses in numerous countries (Genersch et al. 2010;Guichard et al. 2020;Traynor et al. 2016). ...
Preprint
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Genomic selection has increased genetic gain in several livestock species, but due to the complicated genetics and reproduction biology not yet in honey bees. Recently, 2 970 queens were genotyped to gather a reference population. For the application of genomic selection in honey bees, this study analyses the predictive ability and bias of pedigree-based and genomic breeding values for honey yield, three workability traits and two traits for resistance against the parasite Varroa destructor. For breeding value estimation, we use a honey bee-specific model with maternal and direct effects, to account for the contributions of the workers and the queen of a colony to the phenotypes. We conducted a validation for the last generation and a five-fold cross-validation. In the validation for the last generation, the predictive ability of pedigree-based estimated breeding values was 0.06 for honey yield, and ranged from 0.2 to 0.41 for the workability traits. The inclusion of genomic marker data improved these predictive abilities to 0.11 for honey yield, and a range from 0.22 to 0.44 for the workability traits. The inclusion of genomic data did not improve the predictive ability for the disease related traits. Traits with high heritability for maternal effects compared to the heritability for direct effects showed the most promising results. Across all traits, the bias with genomic methods was close to the bias with pedigree-based BLUP. The results show that genomic selection can successfully be applied to honey bees.
... Prin urmare, comunitatea științifică pledează în mod constant pentru conservarea diverselor resurse genetice ale albinelor adaptate la nivel local, deoarece probabilitatea de a supraviețui în prezența diferiților factori de stres este mai mare în cazul raselor și ecotipurilor adaptate local [24]. Acest lucru este deosebit de important pentru activitățile de ameliorare, în special având în vedere principiul de "conservare prin utilizare" [25]. ...
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Rezumat: Albina meliferă (Apis mellifera) este o specie importantă din punct de vedere ecologic și economic, care oferă servicii de polenizare sistemelor naturale și agricole. Biodiversitatea albinei este pusă în pericol de importul în masă al mătcilor. În multe regiuni este neclar modul cum au fost afectate populațiile locale prin hibridizarea dintre rase și nu sunt multe informații despre schimbările apărute în timp. În România în mod natural se găsește A. m. carpatica, iar unele studii arată că există și două subpopulații separate de Munții Carpați. În acest studiu am investigat modificările apărute la nivelul nervurii aripilor la albina românească în ultimele patru decenii. Am constatat că în populația contemporană există încă diferențe clare între subpopulațiile intra și extracarpatice ceea ce indică faptul că variabilitatea naturală a albinelor din România se află încă într-o stare bună de conservare. De asemenea, am identificat diferențe semnificative între albinele colectate înainte de și după anul 2000. Modificările observate sunt cel mai probabil cauzate de încrucișarea dintre albinele autohtone și cele din afara țării introduse sporadic de către apicultori. Pentru a susține conservarea și monitorizarea albinei locale am dezvoltat o metodă care să-i faciliteze identificarea.
... Several authors have proposed to conserve honey bee subspecies and their genetic diversity through "utilization" (Uzunov et al., 2017). The promoted idea is that breeding local populations or subspecies to become more suitable for beekeepers would guaranty the adoption and thus the conservation of these genetically "improved" bees. ...
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Many parts of the globe experience severe losses and fragmentation of habitats, affecting the self-sustainability of pollinator populations. A number of bee species coexist as wild and managed populations. Using honey bees as an example, we argue that several management practices in beekeeping threaten genetic diversity in both wild and managed populations, and drive population decline. Large-scale movement of hive stocks, introductions into new areas, breeding programs and trading of queens contribute to reducing genetic diversity, as recent research demonstrated for wild and managed honey bees within a few decades. Examples of the effects of domestication in other organisms show losses of both genetic diversity and fitness functions. Cases of natural selection and feralization resulted in maintenance of a higher genetic diversity, including in a Varroa destructor surviving population of honey bees. To protect the genetic diversity of honey bee populations, exchange between regions should be avoided. The proposed solution to selectively breed all local subspecies for a use in beekeeping would reduce the genetic diversity of each, and not address the value of the genetic diversity present in hybridized populations. The protection of Apis mellifera's, Apis cerana's and Apis koschevnikovi's genetic diversities could be based on natural selection. In beekeeping, it implies to not selectively breed but to leave the choice of the next generation of queens to the colonies, as in nature. Wild populations surrounded by beekeeping activity could be preserved by allowing Darwinian beekeeping in a buffer zone between the wild and regular beekeeping area.
... Die präsentierten Ergebnisse zeigen, dass die Zucht der Honigbiene von stochastischen Simulationsstudien vielfältig profitieren kann. Theoretische Erkenntnisse aus diesen Studien bilden eine wichtige Ergänzung zu praktischen Empfehlungen zur Bienenzucht (Büchler et al., 2013;Uzunov et al., 2017). Sie können anekdotische Erfahrungen untermauern oder widerlegen und führen somit zu einer objektiven Bewertung althergebrachter Zuchtmethoden. ...
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The stochastic simulation program BeeSim was developed to evaluate new breeding strategies for the honeybee. It allows to illustrate the genetic development of breeding populations based on individual queens, worker groups, and drones. In three consecutive studies, the program was applied to demonstrate the influences of different genetic models, to investigate the influence of mating control on honeybee breeding, and to derive selection strategies that are both successful and sustainable. We found that the application of the infinitesimal model in comparison with finite locus models yielded overly optimistic prognoses regarding the maintenance of genetic variance. Therefore it should only be used for short-term studies. Furthermore, we found that controlled mating is crucial for successful breeding, since free mating reduces the breeding success by up to 99%. Finally, we derived optimal selection intensities for sustainable breeding. Depending on the population size, honeybees should be bred in sister groups of three to seven queens and a broad supply of mating stations should be guaranteed. These three studies give an insight into the manifold ways in which honeybee breeding can benefit from stochastic simulations.
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Visual information is processed in the optic lobes, which consist of three retinotopic neuropils. These are the lamina, the medulla and the lobula. Biogenic amines play a crucial role in the control of insect responsiveness, and serotonin is clearly related to aggressiveness in invertebrates. Previous studies suggest that serotonin modulates aggression-related behaviours, possibly via alterations in optic lobe activity. The aim of this investigation was to immunohistochemically localize the distribution of serotonin transporter (SERT) in the optic lobe of moderate, docile and aggressive worker honeybees. SERT-immunoreactive fibres showed a wide distribution in the lamina, medulla and lobula; interestingly, the highest percentage of SERT immunoreactivity was observed across all the visual neuropils of the docile group. Although future research is needed to determine the relationship between the distribution of serotonin fibres in the honeybee brain and aggressive behaviours, our immunohistochemical study provides an anatomical basis supporting the role of serotonin in aggressive behaviour in the honeybee.
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Background: Eusocial insects are crucial to many ecosystems, and particularly the honeybee (Apis mellifera). One approach to facilitate their study in molecular genetics, is to consider whole-colony genotyping by combining DNA of multiple individuals in a single pool sequencing experiment. Cheap and fast, this technique comes with the drawback of producing data requiring dedicated methods to be fully exploited. Despite this limitation, pool sequencing data has been shown to be informative and cost-effective when working on random mating populations. Here, we present new statistical methods for exploiting pool sequencing of eusocial colonies in order to reconstruct the genotype of the queen of the colony. This leverages the possibility to monitor genetic diversity, perform genomic-based studies or implement selective breeding. Results: Using simulations and honeybee real data, we show that the new methods allow for a fast and accurate estimation of the queen's genetic ancestry, with correlations of about 0.9 to that obtained from individual genotyping. Also, it allows for an accurate reconstruction of the queen genotype, with about 2% genotyping error. We further validate the inference using experimental data on colonies with both pool sequencing and individual genotyping of drones. Conclusion: In this study we present statistical models to accurately estimate the genetic ancestry and reconstruct the genotype of the queen from pool sequencing data from workers of an eusocial colony. Such information allows to exploit pool sequencing for traditional population genetics analyses, association studies and for selective breeding. While validated in Apis mellifera, these methods are applicable to other eusocial hymenopterans.
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As usual in science, where one answer raises new questions, following our attempt to demystify the basic concept of honey bee breeding with our article The Basic Concept of Honey Bee Breeding Programs (Uzunov et al., 2017) questions were raised on details about the implementation of a breeding program. Aspects, such as prioritisation of the traits to select for, selection using breeding values, time management of the breeding program, and mating control, prevailed as most intriguing and are indeed aspects to which previously only limited attention has been given. These particular and relevant questions indicate, however, that the message from our previous article reached our target group. This time, we will address in more detail trait prioritisation, the timing of a breeding program and the selection process. Mating control will only be addressed in a general sense. © 2022 International Bee Research Association. Bee World 2022 https://www.tandfonline.com/journals/tbee20
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Heritabilities and genetic correlations were estimated for honey yield and behavioural traits in Austrian honey bees using data on nearly 15,000 colonies of the bee breeders association Biene Österreich collected between 1995 and 2014. The statistical models used distinguished between the genetic effect of workers and that of the queen of the colony. Heritability estimates for worker effect were larger than those for queen effect. Genetic correlations between both effects were negative. Heritability estimates for the sum of both effects (i.e. selection criterion) were 0.27, 0.37, 0.38 and 0.06 for honey yield, gentleness, calmness and swarming behaviour, respectively, indicating that meaningful genetic improvement is possible. Genetic correlations between these traits were generally small to medium, with large standard errors, with the exception of the high genetic correlation between gentleness and calmness. The models we present here can be used to estimate breeding values in honey bees.
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Here we cover a wide range of methods currently in use and recommended in modern queen rearing, selection and breeding. The recommendations are meant to equally serve as standards for both scientific and practical beekeeping purposes. The basic conditions and different management techniques for queen rearing are described, including recommendations for suitable technical equipment. As the success of breeding programmes strongly depends on the selective mating of queens, a subchapter is dedicated to the management and quality control of mating stations. Recommendations for the handling and quality control of queens complete the queen rearing section. The improvement of colony traits usually depends on a comparative testing of colonies. Standardized recommendations for the organization of performance tests and the measurement of the most common selection characters are presented. Statistical methods and data preconditions for the estimation of breeding values which integrate pedigree and performance data from as many colonies as possible are described as the most efficient selection method for large populations. Alternative breeding programmes for small populations or certain scientific questions are briefly mentioned, including also an overview of the young and fast developing field of molecular selection tools. Because the subject of queen rearing and selection is too large to be covered within this paper, plenty of references are given to facilitate comprehensive studies
Article
Full-text available
Here we cover a wide range of methods currently in use and recommended in modern queen rearing, selection and breeding. The recommendations are meant to equally serve as standards for both scientific and practical beekeeping purposes. The basic conditions and different management techniques for queen rearing are described, including recommendations for suitable technical equipment. As the success of breeding programmes strongly depends on the selective mating of queens, a subchapter is dedicated to the management and quality control of mating stations. Recommendations for the handling and quality control of queens complete the queen rearing section. The improvement of colony traits usually depends on a comparative testing of colonies. Standardized recommendations for the organization of performance tests and the measurement of the most common selection characters are presented. Statistical methods and data preconditions for the estimation of breeding values which integrate pedigree and performance data from as many colonies as possible are described as the most efficient selection method for large populations. Alternative breeding programmes for small populations or certain scientific questions are briefly mentioned, including also an overview of the young and fast developing field of molecular selection tools. Because the subject of queen rearing and selection is too large to be covered within this paper, plenty of references are given to facilitate comprehensive studies.
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The rich variety of native honeybee subspecies and ecotypes in Europe offers a good genetic resource for selection towards Varroa resistance. There are some examples of mite resistance that have de-veloped as a consequence of natural selection in wild and managed European populations. However, most colonies are influenced by selective breeding and are intensively managed, including the regular use of miti-cides. We describe all characters used in European breeding programs to test for Varroa resistance. Some of them (e.g., mite population growth, hygienic behavior) have been implemented in large-scale selection pro-grams and significant selection effects have been achieved. Survival tests of pre-selected breeder colonies and drone selection under infestation pressure are new attempts to strengthen effects of natural selection within selective breeding programs. Some perspectives for future breeding activities are discussed.
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The estimation of breeding value for the honey bee is markedly more difficult than for other agricultural animals as colony traits in honey bees are the expression of the combined activities of the queen and workers. Recent studies have shown strong negative genetic correlations between the contributions of both queens and workers to economically important traits (e.g. honey production). The most advantageous method currently available for evaluating breeding values in other animals, the Best Linear Unbiased Prediction (BLUP)-Animal Model, has been adapted to the peculiarities of honey bee genetics and reproduction. This method considers maternal (queen) effects using all available records of relatives and weights these so as to obtain the most accurate prediction of the genotype. It simultaneously considers environmental effects, genetic merit of mates and contemporarily tested colonies, and estimates the breeding values for queen and worker effects on colony traits for each queen.
Breeding for resistance to Varroa destructor in North America
  • Harris Rinderer
  • Hunt
  • De Guzman
Rinderer, Harris, & Hunt, de Guzman (2010). Breeding for resistance to Varroa destructor in North America. Apidologie, 41, 409-424. doi:10.1051/apido/201001
Selection theory, varroa tolerance
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Brascamp, E.W. (2014). Selection theory, varroa tolerance, beebreed. Retrieved from https://www.beebreed.nl/coursequeen-rearing-brascamp-151115.pdf
Performance testing protocol. A Guide for European Honey Bee Breeders
  • A Uzunov
  • R Büchler
  • K Bienefeld
Uzunov, A., Büchler, R., & Bienefeld, K. (2015). Performance testing protocol. A Guide for European Honey Bee Breeders. Retrieved from www.smartbees.eu
Technical recommendations for methods of evaluating performance of bee colonies
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Ruttner, H. (1972). Technical recommendations for methods of evaluating performance of bee colonies. In F. Ruttner (Ed.), Controlled mating and selection of the honey bee (pp. 87-92). Bucharest, Romania: Apimondia Publishing House.