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Avlsprogrammer for varroatoleranceVidensdeling 2020
AUAARHUS UNIVERSITET INSTITUT FOR AGROØKOLOGI
Varroa tolerance avl
• Annette viste hvordan naturen arbejder
• Så vi ved der findes tolerante bier
• Tyske kolleger har arbejdet mange år
• Amerikanske kolleger arbejder intensivt
• Resultaterne er endnu ikke tydelige
Hvorfor?• De naturligt tolerante bier har sjældent gode
produktionsegenskaber
• Sværmer ofte
• Små bifamilier
• Tab forekommer hyppigt, naturlig selektion
• Biavleren er også en parasit for bierne
RESEARCH ARTICLE Open Access
The transcriptomic signature of lowaggression in honey bees resembles aresponse to infectionClare C. Rittschof1* , Benjamin E. R. Rubin2 and Joseph H. Palmer3
Abstract
Background: Behavior reflects an organism’s health status. Many organisms display a generalized suite of behaviorsthat indicate infection or predict infection susceptibility. We apply this concept to honey bee aggression, a behaviorthat has been associated with positive health outcomes in previous studies. We sequenced the transcriptomes ofthe brain, fat body, and midgut of adult sibling worker bees who developed as pre-adults in relatively high versuslow aggression colonies. Previous studies showed that this pre-adult experience impacts both aggressive behaviorand resilience to pesticides. We performed enrichment analyses on differentially expressed genes to determinewhether variation in aggression resembles the molecular response to infection. We further assessed whether thetranscriptomic signature of aggression in the brain is similar to the neuromolecular response to acute predatorthreat, exposure to a high-aggression environment as an adult, or adult behavioral maturation.
Results: Across all three tissues assessed, genes that are differentially expressed as a function of aggressionsignificantly overlap with genes whose expression is modulated by a variety of pathogens and parasitic feeding. Inthe fat body, and to some degree the midgut, our data specifically support the hypothesis that low aggressionresembles a diseased or parasitized state. However, we find little evidence of active infection in individuals from thelow aggression group. We also find little evidence that the brain molecular signature of aggression is enriched forgenes modulated by social cues that induce aggression in adults. However, we do find evidence that genesassociated with adult behavioral maturation are enriched in our brain samples.
Conclusions: Results support the hypothesis that low aggression resembles a molecular state of infection. Thispattern is most robust in the peripheral fat body, an immune responsive tissue in the honey bee. We find noevidence of acute infection in bees from the low aggression group, suggesting the physiological statecharacterizing low aggression may instead predispose bees to negative health outcomes when they are exposed toadditional stressors. The similarity of molecular signatures associated with the seemingly disparate traits ofaggression and disease suggests that these characteristics may, in fact, be intimately tied.
Keywords: Social immunity, Colony collapse disorder, Social behavior, Nutrition, Stress, Development, Pollinatordeclines, Virus
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
* Correspondence: [email protected] of Kentucky, S-225 Agricultural Science Center North, Lexington,KY 40546, USAFull list of author information is available at the end of the article
Rittschof et al. BMC Genomics (2019) 20:1029 https://doi.org/10.1186/s12864-019-6417-3
RESEARCH ARTICLE Open Access
The transcriptomic signature of lowaggression in honey bees resembles aresponse to infectionClare C. Rittschof1* , Benjamin E. R. Rubin2 and Joseph H. Palmer3
Abstract
Background: Behavior reflects an organism’s health status. Many organisms display a generalized suite of behaviorsthat indicate infection or predict infection susceptibility. We apply this concept to honey bee aggression, a behaviorthat has been associated with positive health outcomes in previous studies. We sequenced the transcriptomes ofthe brain, fat body, and midgut of adult sibling worker bees who developed as pre-adults in relatively high versuslow aggression colonies. Previous studies showed that this pre-adult experience impacts both aggressive behaviorand resilience to pesticides. We performed enrichment analyses on differentially expressed genes to determinewhether variation in aggression resembles the molecular response to infection. We further assessed whether thetranscriptomic signature of aggression in the brain is similar to the neuromolecular response to acute predatorthreat, exposure to a high-aggression environment as an adult, or adult behavioral maturation.
Results: Across all three tissues assessed, genes that are differentially expressed as a function of aggressionsignificantly overlap with genes whose expression is modulated by a variety of pathogens and parasitic feeding. Inthe fat body, and to some degree the midgut, our data specifically support the hypothesis that low aggressionresembles a diseased or parasitized state. However, we find little evidence of active infection in individuals from thelow aggression group. We also find little evidence that the brain molecular signature of aggression is enriched forgenes modulated by social cues that induce aggression in adults. However, we do find evidence that genesassociated with adult behavioral maturation are enriched in our brain samples.
Conclusions: Results support the hypothesis that low aggression resembles a molecular state of infection. Thispattern is most robust in the peripheral fat body, an immune responsive tissue in the honey bee. We find noevidence of acute infection in bees from the low aggression group, suggesting the physiological statecharacterizing low aggression may instead predispose bees to negative health outcomes when they are exposed toadditional stressors. The similarity of molecular signatures associated with the seemingly disparate traits ofaggression and disease suggests that these characteristics may, in fact, be intimately tied.
Keywords: Social immunity, Colony collapse disorder, Social behavior, Nutrition, Stress, Development, Pollinatordeclines, Virus
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
* Correspondence: [email protected] of Kentucky, S-225 Agricultural Science Center North, Lexington,KY 40546, USAFull list of author information is available at the end of the article
Rittschof et al. BMC Genomics (2019) 20:1029 https://doi.org/10.1186/s12864-019-6417-3
Gen aktivitet i bier med lav aggresivitet ligner respons på infektion
do see a signature of carbohydrate metabolism amonggenes differentially expressed in the brain in our study,consistent with studies linking glycolysis and oxidativephosphorylation to social and environmental modulationof aggression [16, 52, 65, 70, 71]. Finally, enrichmentanalyses provide some support for the hypothesis thatvariation in aggression in our study reflects variation inthe pacing of behavioral maturation in adults. Our studyprovides evidence that the molecular state associatedwith low aggression resembles a diseased state, providinga potential physiological link between high aggressionand resilience to health stressors.Although our method for assessing pathogen infec-
tion is indirect and limited to a transcriptional signa-ture in specific tissues, at least some bacterial, fungal,and viral pathogens were found in every individualexamined, suggesting that these data can be used toestimate infection load. Using these estimates, we findno significant differences in the abundance of anypathogen between high and low aggression bees, indi-cating that variation in aggression as a result of
developmental environment is not the result of differ-ences in infection rates. The set of pathogens we con-sidered includes those that are known to commonlyinfect honey bees [13, 20, 25], including DeformedWing Virus, a strain of which has been associated withaggression in a previous study ([24]; see also [72]). Thisapproach for estimating infection rates may be usefulfor studies of honey bee behavior moving forward;despite the use of polyA-enrichment for extractingmRNA, substantial numbers of both bacterial and viralreads were present in our RNAseq datasets.It is important to note that our current study focused
on environmentally-induced variation in behavioral andmolecular phenotypes, specifically the impacts of develop-mental social environment on aggression and gene expres-sion. Additional studies are needed to determine howgenetically-based variation in aggression corresponds tothe disease-related phenotypes we evaluate here. Otherstudies have noted parallels in the molecular signatures ofaggression arising from genetic and environmental factors[3, 27], and genetic variation in aggression is associated
Fig. 1 This schematic provides a summary of enrichment analysis results in the present study. "Infection" (Brain, Fat body, Midgut)indicates the tissue-specific comparison of genes differentially expressed as a function of aggression in the current study to genesdifferentially expressed as a function of infection in [18]. "Adult environment", "Predator threat", and "Behavioral maturation" indicate brainenrichment comparisons of genes differentially expressed as a funciton of aggression in the current study with a previous microarraystudy [3], which evaluated genes differentially expressed following exposure to aggression-inducing alarm cues (Predator threat), exposureto a high versus low aggression environment as an adult (Adult environment), and adult behavioral changes with aging (Behavioralmaturation). In our data analysis, gene lists up and downregulated with infection or parasitic feeding were analyzed separately, whileother aggression comparisons in the brain were analyzed irrespective of expression direction because the brain differentially expressedgene list in our study was short. Significant enrichment is indicated by a dotted circle. Gene numbers listed for each tissue sum to thetotal differentially expressed genes in the current study, not the total genes incorporated in the enrichment analyses; gene conversionsacross studies, spanning multiple genome versions, gene sets, and gene expression analysis methods, decreased the universe of genesused for enrichment analyses
Rittschof et al. BMC Genomics (2019) 20:1029 Page 7 of 14
AvlsarbejdeDronningavler Test gruppe Avlsekspertise
Uddannelse og træning
Afprøvning Data evaluering ogestimation af avlsværdi
Udvælgelse af avlsdronninger
Dronningproduktion
Dronningudveksling
Parringsstation
Dataindsamling og validering
Testbigård
Performance testing protocol Uzunov, Büchler, Bienefeld A guide for European honey bee breeders Version 1.0, April 2015
www.smartbees.eu
In regions where testing and breeding is for first time initiated the selection of first queens’ mothers is based on the obtainable information and data for the local populations. The best available queens, according the breeders knowledge for their performance for certain traits of interest, are selected as queens’ mothers. When breeding is well established mother queens are selected based on the breeding values, published at the end of the
testing period (see chapter Selection & mating design). If available, the information from morphometric or/and molecular analysis, should be taken in to consideration to determine queens’ genetic affiliation to certain native or local honey bee population/subspecies of interest. In a single test station it is recommended to test queens from single subspecies, but different genetic origin (different mother queens).
To ensure adequate and unbiased distribution or exchange of queens between the testing stations the following factors should be taken into consideration:
Ô Population size Ô Size of the geographic area Ô Number of groups of sister queens (at least 3) Ô Number of test stations (at least 3)
□ Number of breeders □ Number of testers
Ô Number of test colonies per test stations (at least 10) Ô Number of mating or instrumental insemination stations (if available)
Having in mind the given factors and limitations there are numerous models for
distribution or exchange of queens between the test stations, which also depends from the organizational and technical capacity of the regional groups. The reliability of the results depends from the number of test colonies, their genetic relationship and the genetic parameters of the trait of interest. Based on the statistical simulations on the records from BEEBREED data base (www.beebreed.eu) there is no reason to test more than 8 colonies from a single sister group since the optimisation between information gain and efforts load for testing is already reached. However, since colonies’ survivability for the course of testing period can be low and many queens or colonies can be lost, mainly as a consequence of the peculiar without treatment management of the test colonies, it is advisable to rear, distribute in different stations and test around 12 queens per sister group. This is particularly relevant where testing and breeding was recently initiated. Consequently, in cases with large testing capacities (numerous testing stations and colonies) the number of sister groups should be increased at the cost of number of queens within the sister group. This approach will also enable testing of sister queens from different mother queens and subsequently facilitate diversification of genotypes included in testing and breeding within population or subspecies.
Figure 5. Simple model of queens’ exchange between test stations where the responsible persons for stations 1, 2 and 3 are breeders, and for station 4 is a tester.
Udveksling af dronninger i avlsarbejdet. Avlerne er 1, 2 og 3, mens biavler 4 kun udføre afprøvning
Performance testing protocol Uzunov, Büchler, Bienefeld A guide for European honey bee breeders Version 1.0, April 2015
www.smartbees.eu
The given examples in Figure 6 represent alternatives for adequate queens’ exchange as a consequence of the abovementioned limitations in some of the countries. The example C is the closes alternative to the optimal model of exchange and sister groups size.
Figure 6. Different models of queens’ distribution or exchange between test stations. Each square represents a colony or queen, different colours represents different origin (colonies with same colour belong to the same sister group), the numbers represents the number of the test stations. A - Six (6) groups of sister queens are reared and mated in the same number of locations and distributed among 6 testing locations. The upper group of sister queens (row) is reared and mated on the respective testing location; B -Three (3) groups of sister queens are reared and mated on 3 locations and distributed among 8 testing locations. The locations where the queens are produced and also under test are squared. The upper group of sister queens (row) is reared and mated in the respective testing location. The non-squared locations are only testers; C - The locations where the queens are produced are marked with single (*) or double stars (**), depending from the number of queen sources. One group of queens came from non-listed location.
For optimising the models for small and endangered local populations, particular precautions and consultations with experts for breeding and population genetics should be taken in advance.
Each queen in test should be individually marked by colour or plate and numerically listed in the breeder’s (association’s) Breeding registry (Annex X) with the information for its mother queen (2a), mating partner (4a), generation, hatching and mating dates, type and place of mating, mark and purpose of use. As an outcome of the registration each queen will obtain its unique breeding number (consisting of codes for the country, association, breeder, registry number and year of birth) which will ensure essential matchless identification and system recognition (Figure 7). DE - 07 - 045 - 389 - 2014 Figure 7. Example of the queen’s identification breeding number and its elements (codes)
Country Association Breeder Registry number Year of birth
Forskellige skemaer til udveksling og afprøvning af avlsmateriale
Performance testing protocol Uzunov, Büchler, Bienefeld A guide for European honey bee breeders Version 1.0, April 2015
www.smartbees.eu
Colonies arrangement To ensure equal opportunities for objective comparison of the test colonies the queens from the different sister groups have to be equitable distributed within the testing station (Figure 8).
Equitable or systematic arrangement of the orientation of the hives’ entrances and their different coloration additionally will improve the objectivity and will reduce drifting (Figures 9 & 10). In any case conventional or inline arrangement of the hives in the test station is not recommended as a precaution from drifting.
Figure 9. Examples of different hives’ arrangement in the test station. Hive Usage of local or commonly known hive types with movable parts and their adequate individual identification is a minimum requirement for implementation of performance testing. Furthermore, it is obligatory that in the single testing station the hives should belong to the same type. For assessment of the natural mite fall screened bottom boards are required. Figure 10. An example testing apiary
from ??????? ????.
Figure 8. Example of distribution of queens from 3 different sister groups (each colours represents different sister group). Opstilling af stader i testbigårde
Performance testing protocol Uzunov, Büchler, Bienefeld A guide for European honey bee breeders Version 1.0, April 2015
www.smartbees.eu
The activities done on the mating station are registered in the Mating station diary (17M). The document contain information about the location of the mating station, responsible person, drone producing colonies and also data about the queens such as owner of the unmated queens, date of arrival, inspection result, mating success and other details (Figure 27).
Documentation such as instrumental insemination diary, testing station
management card etc could be also part of the entire data management system. However, the extent of documentation and administration depends from the needs and ambitious of the breeder or breeding association.
Figure 26. A recordkeeping card. The template is available in Annex X.
Figure 27. A mating station diary. The template is available in Annex X.
Stadekort
Performance testing protocol Uzunov, Büchler, Bienefeld A guide for European honey bee breeders Version 1.0, April 2015
www.smartbees.eu
The information flow and relationship of the abovementioned documents is given in Figure 28.
Data management To minimise errors and typos a particular input mask was developed on the online data base BEEBREED. The layout of the input mask on BEEBREED is identical with the recordkeeping card (Figure 26) which enhances the accuracy and the efficiency during the data enters.
The recorded data are used for estimation of breeding value for certain traits of interest as well as estimation and analysis of parameters relevant to the breeding process. For instance the data from Varroa associated parameters can be used for estimation of regional threshold values, other are combined for gathering information about colony development or some data can be used for optimisation of the testing procedure and reduction of risk factors.
Figure 28. Information flow and relationship of the documents.
Breeding (queen)
registry 2018
Recordkeeping card
Mating station diary
Queen ID
card
Queen ID
card
BEEBREED
(www.beebreed.eu) In case of extended version
of the registry
Queen ID
card
Propagation (selling, exchange etc)
Queen ID
card Propagation
(selling, exchange etc)
online
Breeding (queen) registry
2017
Breeding (queen) registry
2019
Other documentation (management, tests etc)
Arbejdsgange, registering og udvælgelse
Varroa er det nye• Det er væsentlig at udvikle og afprøve
metoder i praksis
• Næppe en løsning for alle
• Hvad kan forventes af en biavler?Hvad kan overkommes?Hvilke metoder giver brugbare data?
• Det kan give resultater, men det vil tage tid
Man arbejder videre med SmartBees protokolen. Afprøves i flere population i forhold til udvikling af tolerance for varroa. Vigtig aspekt er tidsforbrug for biavleren og måling af genetisk gevinst. 3500 Bifamilier i test 2020
www.eurbest.eu
SMR og VSH
• Suppressed Mite Reproduction, nedsat opformering af varroamider
• Varroa Sensitive Hygienic behaviour, varroafølsom udrensning
• Tunge at undersøge, kræver tid og laboratorie
• Nøjes med at se mide med eller uden afkom
Opformering i bifamilie
• Kræver mindst to målinger
• Indskud mens pilen blomstre 3 x 1 uge
• Varroavask i juni, juli og august
• Nedfald ved bekæmpelse
• Præcision er afgørende for resultat
Øvrige observationer
• Bistyrke ved indvintring og udvintring
• Forekomst af virussymptomer
• Fjern bifamilier med mange mider, dominoeffekt
• For få mider gør arbejdet svært, i Tyskland undgår man at vinterbehandle
• Droner er vigtige for biernes sundhed
• Droner der overlever i stade med mange mider, og kommer til parring er interessant
• Smitte af dronninger med virus ved parring
• Dronningetab er hyppige
Lær at leve med tab
• Fabrizio Zagni, da vinteren havde givet tab,“så kom jeg af med de bier der ikke duer”
• Varroa hjælper med at udvælge de bier, der har mest livskraft, de svage dør
Gen Markør Avl
• Kan man avle efter SNPs?
• Altså krydse dronninger og droner med mange gunstige gener for varroatolerance
• Viser de bier at klare sig fint, har man bevist SNPs har den forudset funktion
• Der er 167 SNPs for varroatolerance
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