Genebanks and the management of farm animal genetic resources
Editor: J.K. Oldenbroek Publisher: DLO Institute for Animal Science and Health P.O. Box6 5 8200 AB Lelystad The Netherlands
isbn 90-75124-06-6 ©ID-DLO, 1999
All rights reserved. No part of this publication may be reproduced, stored in aretrieva l system, or transmitted in any form or by any means, electronic, mechanical, photocopying or otherwise, without theprior permission of the copyright owner. Applications for such permission, with a statement of the purpose and extent of the reproduction, should be addressed to the Director of the DLO Institute of Animal Science and Health, P.O. Box 65, 8200 AB Lelystad, the Netherlands.
On the cover: upperleft: Reggiana cow upperright: Groningen horse lower left:Iberia n pigs lower right: Finnish Landrace sheep (Photos courtesy ofG.C. Gandini (Reggiana) and OklahomaState University). Contents Preface Page
1. Introduction 1 J.K.Oldenbroe k
2. Choosing the conservation strategy 11 G.C.Gandin i andJ.K . Oldenbroek
3. Measuring the genetic uniqueness in livestock 33 J.H. Eding and G. Laval
4. Selecting breeds for conservation 59 J. Ruane
5. Establishing aconservatio n scheme 75 M.Tor o and A.Mäki-Tanil a
6. Operation of conservation schemes 91 T.H.E. Meuwissen
7. Development ofa nexper t system for conservation 113 J.A. Woolliams andT.H.E . Meuwissen
Preface
Economic, social and environmental developments were the driving force for the selection of highproductiv e breeds tob e used in the intensive animal production systems.Thi s selection decreased the contribution of locally developed breeds withlower-input , lower-output levels to food production andthreatene d the existence ofthes ebreeds .Fo r goodreason s the society andth ebreedin g organisations canno t afford andwil lno t acceptth enon-reversibl e disappearance ofbreed s including the loss of genetic variation within the important farm animal species.World-wid e genebanks for plants in which genetic variation is conservedd o exist already for more then 30year s and onlyi n afe w countries farm animal genebanks exist. A scientific foundation for the set up of afar m animal genebank, itsrol e in conservation for future use and its integration in in situ conservation programs ishighl y needed for the European Union.
Sofar , several organisations were active in the field of conserving animal genetic resources, e.g. theEuropea n Association for Animal Production (EAAP) andth eFoo d and Agricultural Organisation ofth eUnite d Nations (FAO).Thi sboo k can be seen asa n addition toth ewor k published by EAAP and FAO,especiall y as an addition to the"Secondar y Guidelines for Development ofNationa l Farm Animal Genetic Resources Management Plans"o f FAO published in 1998.
Within the Concerted Action BIO4-CT96-0197thre emeeting s were held in 1997an d 1998i n which several aspects ofconservatio n ofgeneti cvariatio n in farm animal populations in Europe were presented and discussed in order todevelo p guidelines for the cryoconservation offar m animal genetic diversity. Much attention waspai dt oth eintegratio n ofth e exsitu conservation in ageneban k inprogram s for in situconservatio n in EU circumstances. Geneticistsfrom Scotland , Norway, Finland, France, Italy, Spain,Th eNetherland s and from FAOparticipate d inthes emeetings . In afourt h meeting in 1998the y synthesised these aspects and discussions for publication in thisbook .
Thereader s of theboo k might bepeopl eworkin g in education, inresearch , in animal breeding andi n governmental andnon-governmenta l organisations.Thi sboo kwil l helpthe m to stimulate awareness for theproblem s resulting from the extinction ofbreed s and create awareness for the opportunities of conservation of genetic diversity within species byth e creation and use of genebanks andmanagemen t of farm animal geneticresource s in theEC . Thecontent s of theboo k will helppeople , whoshoul d make decisions on conservation activities for farm animals, to found their viewpoints. Such activities aim atth e future useo f conserved geneticmateria l in European animal breeding programs andwil l secure future food production and future market demands, e.g. a diversification ofproductio n systems or consumer demands for specialised foods. Chapter 1. Introduction
J.K.Oldenbroe k
Department of Animal Breeding and Genetics, DLO Institute for Animal Science and Health, P.O.Bo x 65,820 0A B Lelystad, The Netherlands
Challengesfor food production anddevelopments inanimal production systems Developments infarm animalpopulations used for food production History ofconservation in Europe Whatis farm animalgenetic variation? Whyshould farm animalgenetic variation be conserved? Who shouldconserve farm animalgenetic variation? Howshould farm animalgenetic variation be conserved? Backgroundto decision making inconservation farm animalgenetic variation
1.1 Challenges for food production and developments in animal production systems
1.1.1 Food for agrowin g global population World-wide the human population is expected togro w by moretha n 50%unti l the year2030 . Inth e past the demand for an increased food production hasbee n realised by acombinatio n of genetic improvements, greater farming inputs and cultivation ofmor elan d for agriculture. It can hardly be expected that in the future the agricultural inputs can still beincrease d andtha t more land can be cultivated for intensive food production systems.Therefore , onth e one hand the genetic improvement of farm animals isth e most viable approach tomee tth e increasing demand for food from animal origin in intensive systems.O nth e otherhan drura l areas might be used for food production with low-input, low-output breeds which arelocall y developed and adapted tothes eareas .
1.1.2 Growing demand for diversification ofanima l production Oneo fth emajo r reasons for the domestication of animals wast o supply food for the family ofth e owner. In the last centuries, animal food supply of mankind inth e developed world is concentrated on specialised farms and farm animals arebre d andmanage d toexpres s production and quality traits in an efficient way. Besides,i n thedevelope d world iti s observed that anincreas e in income leads toris e in thedeman d for specialised foods generated by adiversificatio n of animal production systems.T omak e the genetic approach successful in intensive and extensive circumstances and in the demand for adiversificatio n of animal products, thegeneti c variation must bemaintaine d ormus t be enlarged in our selection activities for farm animals.
1.2 Developments in farm animal populations used for food production
1.2.1 Driving forces In Europe breeding organisations strongly influenced the composition of farm animal populations used for food production. Economic, social and environmental developments were the driving force for the selection ofhig hproductiv e breeds tob e used in intensive animal production systems.Thi s selection decreased the contribution oflow-input , low-output breeds to food production andthreatene d the existence ofthes ebreeds .
1.2.2 Effects of technology Applying genetic science in the improvement of the genetic ability of farm animals andth e use of artificial reproduction techniques led toth e development of advanced breeding schemes and advanced methods toidentif y thegeneti c superior animals within the selected high productive breeds.I n thesebreed s ahig h geneticimprovemen t is obtained for only afe w traits.Th e other traits,whic h were ignored in the selection, were compensated by increasing management efforts. This way ofselectio n widened the gapi nproductivit y between the developed highproductiv e breeds andth e original low-input, low-output breeds,whic h wasa further steptoward s the extinction oflocall y developedbreeds .
1.3 History of conservation in Europe
1.3.1 Increase in erosion andstar t of conservation World-wide the discussion on conservation ofgeneti cresource s in animal production started much latertha n in plantproduction . However, already atth e start ofartificia l insemination of cattle in the fifties, Swedish AI-studs conserved semen from eachbul l used for breeding.I n the sixties, scientific and farmer communities draw attention toth ehig h rate of erosion of animal genetic resources. In Europe, farmers were leaving therura l areas where much breed diversity waspresen t andman y local breeds werereplace d by afe w highly promoted and highly selected breeds.Thes e breedswer e also exported todevelopin g countries outside Europe andreplace d breeds,whic h were well adapted to circumstances and management systems deviating sharplyfrom thos e in Europe. In 1972th e first United Nations Conference on the Environment in Stockholm recognise these developments andproblems . Ultimately, the first Global Technical Consultation on Genetic Resources washel d at FAO-headquarters in Romei n 1980.
1.3.2 FAO-activities forth emanagemen t of farm animal resources In 1985 FAOintroduce d under theresponsibilit y of the Commission on Genetic Resources for Food andAgricultur e an expanded Global Strategy for the Management of Farm Animal Resources. In 1992FA O launched aspecia l action program for the Global Management of Farm Animal Genetic Resources with aframework t o stimulatenationa l participation in the global effort toimplemen t conservation activities.Nationa l andregiona l focus points playa n important rolei n stimulating andco-ordinatin g these actions.Th e Domestic Animal Diversity Information System (DAD-IS) is used to collect information onbreed s and conservation activities and it offers the opportunity toretriev e guidelines for conservation activities.I n 1998thi s program got ane w impulse in the first session of the Intergovernmental Working Group onAnima l Genetic Resources for Food andAgriculture . This working group recommended the Commission on Genetic Resources for Food andAgricultur e that FAO continuet o shapemor e clearly theframework an dfurthe r developth e framework andtha t FAOco-ordinat e the development of acountry-drive n Report on the State ofth e World's Animal Genetic Resources.
1.3.3 Convention on Biological Diversity stimulates awareness for farm animal genetic variation In 1992th e second United Nations Conference onth e Environment in Rio deJaneir o recognised the importance offar m animal geneticresource s in Agenda 21an di nth e Convention on Biological Diversity.Nearl y all countries have signed this convention, which resulted inpolitica l and social awareness ofnationa l animal geneticresource s and activities to conserve them in several countries also within the European Community. The CBD considers farm animal genetic variation asa componen t ofth eoveral l biological diversity. TheCB D recognises the sovereignty of each country over his own genetic resources, which implies also theobligatio n toconserv e theseresources .
1.3.4 Initiatives ofth eEuropea n Association for Animal Production Concerted activities on farm animal genetic resources started in Europe in 1980whe n the EAAP established aworkin g group inthi s field. The main activities weret o organise regular surveys ofbreed s of farm animals in different European countries andt o integrate the genetic science in conservation activities. From 1988t o 1994FA O and EAAPmanage d the Global Data Bank for farm animal genetic resources atth e Hannover Veterinary University in Germany. In 1993th e data were transferred toRom e to DAD-IS ofFAO . Since then, the European national co-ordinators regularly update the databank in Hannover, which send the information also to FAOi n Rome.Accordin g toDAD-I S there are 332 cattle,40 7 sheep, 123 goat, 156pi g and21 3hors e breeds maintained in 37 European countries. In the Western (EU) part ofEurop eth e decline in farm animal genetic resources in theintensificatio n ofanima l production system hastoke n place.I n the Central-Eastern European countries, where development of animal production is still the first priority, the strong decline in farm animal resources mayb e continued.
1.4 What is farm animal genetic variation?
1.4.1 Genetic variation expressed asdifference s in phenotype Between animalsdifference s inproductio n andqualit ytrait s canb e observed aswel l asi n health,reproductio n and conformation traits.Thes e phenotypic differences are theresul t of differences in genetic ability and differences inmanagement . Statistical techniques and knowledge about relationships between animals unravel thephenotypi c variation in quantitative andqualitativ e traits in an environmental part causedb y differences between animals inmanagemen t and the genetic variation caused by differences in coancestry.I n general 50%o fth etota l genetic variation within aspecie si s estimated tob ebetwee nbreeds . Therefore, loss ofbreed s can substantially reduceth e genetic variation within a species.I n statistical term geneticvariatio n isdescribe d asth e variance within andbetwee n breeds. 1.4.2 Genetic variation measured asDNA-poIymorphism' s The development ofmolecula r biological techniques for the detection of DNA- polymorphism's in coding andnon-codin g regions of chromosomes facilitates to describe the genetic variation more accurately. Such information can be used to calculate theresemblanc e between animals within breeds andth eresemblanc e between breeds, which might be used for the development of conservation activities.
1.5 Why should farm animal genetic variation be conserved?
1.5.1 Opportunities to meet future market demands In theprosperou s countries ofth e European Community the demand for specialised food from animal origin increases.Thi sresult s in adiversificatio n of animal production systems ando f animal products. Besides,prosperit y increases the use of animals for other goals like hobby farming andth eus e of animalsfo r sports (horses).Thes e developmentsreques t alarg e variability in the genetic variation ofth e species used. Thebreed s used in thepresen t agricultural systems canno t meet all these future market demands.
1.5.2 Insurance against future changes in production circumstances Thehigh-inpu t high-output systems arecharacterise d byth ehig h useo f fertilisers and concentrate andwithi n these systems veterinary treatment with drugs for preventive and clinical use are sometimespractise d at high levels.Agricultura l pollution andresistanc e against drugs can create conditions for animal production inwhic h higher levelso f respectively feed intake and diseaseresistanc e arerequired . The conservation of genetic variation isnecessar y asa ninsuranc e against changes inproductio n circumstances orth e threat of ane w disease.
1.5.3 Present socio-economic value Inman y countries local breeds are usedb y asmal l group of farmers sometimes for special reasons (e.g.biologica l farming orgrazin g ofmargina l lands) orpurpose s (e.g.loca l products for nichemarkets) .Th e development ofbreedin g programs for these local breeds isto o costly for breeding organisations andth e absenceo f abreedin gprogra m is athrea t for the existence ofth ebreed . However, present socio-economic value,whic h creates income for asmal l group of farmers,justifie s the establishment of aconservatio n program. 1.5.4 Opportunities for research World-wide in animal production, molecular geneticists are searching for genes,whic h influence production, quality of products, andhealt h andreproductio n traits of animals. Inthi s search, crosses between breeds with extreme characteristics playa n important role.The y guarantee ahig h degree of heterozygosity and linkage disequilibrium, which isrequire d to detect associations between highly polymorphic marker loci andpolymorphism' s at quantitative and qualitative trait loci.
1.5.5Cultura l and historic reasons Many breeds areth eresul t of alon g domestication process and alon gperio d ofadaptatio n to local circumstances. They reflect alon g history ofsymbiose s between mankind and farm animals andca n help toclarif y adaptation processes,whic h can still beworthwhil e for the management of animals inpresen t production systems.
1.5.6 Ecological value Within the community the awareness isgrowin g for the ecological value ofregion s asa resul t oflandscape ,natur e and farm management. Within this complex thepresenc e of animals from native origin which interact with parts ofthi s complex is of great ecological importance. Besides,thes e animals can contribute toth e development of local products with an ecological image.
1.6Wh oshoul d conserve farm animal genetic variation?
1.6.1 Role of national governments in an international context Inaccordanc e to theprinciple s ofth eConventio n on Biological Diversity each country is responsible for themanagemen t ofthei r ownnationa l farm animal resources and for the implementation of conservation strategies. However, manybreed s aresprea d over several (neighbouring) countries andexchang e of genetic material between the subpopulations of such aninternationa l breed is very common. Therefore, collaboration between countries in conserving breeds is often themos t efficient strategy. For example, EU-regulations 1467/94 and 2078/92 aimrespectivel y ata n efficient development of conservation plans over countries anda tunifor m stimulatingprocedure s for practical farmers tokee p animals ofbreed s atrisk within conservation plans.A genera l strategy for the establishment of databases inwhic h relevant breed information is stored and ofth e outline of conservation plans might serve conservation activities world-wide. FAOdevelope d afram e work for agloba l strategy for the conservation of animal geneticresource s with thedevelopmen t of anetwor k of co-ordinating institutes and focal points asa backbon e andth e development of adatabas e and of guidelines for conservation activities asmajo r products.
1.6.2 The responsibility ofscientists , breeders and breeding organisations Scientists should develop monitoring and signalling schemes tohel p governmental organisations towatc h overpopulations , which mightbecom e atrisk o r arethreatene d with extinction. Besides,geneti c science shouldb etranslate d in guidelines for conservation plans. Individual breeders andbreedin g organisations mayhel p in conservation activities by offering genetic material to ageneban k and inperformin g breeding programs for small populations at risk.I n collaboration with organisations initiated by governments andwit h national subsidy breeders andbreedin g organisations play ake yrol e in the success of conservation activities.
1.7 How should farm animal genetic variation be conserved?
1.7.1 Selection schemes of breeding organisations Toavoi d inbreeding andt ominimis e random drift in populations under selection breeding organisations shouldpa y alo t of attention to thenumbe r of founder animals andthei r relationship and toth e mating scheme andth e effective number ofbreedin g animals in each generation. Alarg e effective population is aguarante e for the conservation of alarg e amount ofgeneti cvariation . However, costs of abreedin g plan andth e genetic gain,whic h is necessary tojustif y the costs,requir e high selection intensity and ashor t generation interval. Bothmigh tb e athrea t for the genetic variation in apopulatio n of asmal l effective size.
1.7.2 Insitu conservation When abree d is atris k ori sthreatene d byextinctio n in situ conservation ist ob e preferred. Then, all objectives ofconservatio n canb ereache d thebest . Besides,th edevelopmen t ofth e breed can continue,whic h means selection for economicprofi t asfa r iti spossibl e within the limits of asmal l population andi t facilitates adaptation to changing circumstances. However, therisk s ofinbreedin g andrando m drift have toreceiv e full attention in the breeding schemes for small populations.
1.7.3 Ex situ live conservation Sometimes theproductio n ofbreed s mayb e uneconomic andmanagemen t mayb e demanding. Nevertheless, acultural , historic orecologica l value may exist. Suchbreed s can fulfil arol e in zoo's, farm parks ornatura l parks.Th e costs of exsitu live conservation are low,bu t thebree d is kept outside itsproductio n environment towhic h it is adapted.
1.7.4 Ex situ conservation Formos t farm animal species it ispossibl e to cryo-conserve semen andrealis e high or acceptable levels of conception after thawing the semen andinseminatin g females. For some species frozen embryos can be used to create live offspring. Also,recen t developments have been made in freezing techniques for oocytes. Foral l animal species DNA-storage and storage of somatic cells is awell-know n technology. However, techniques likenuclea r transfer shouldb e developed further in ordert o usethes etype s ofstorag et oregenerat e animals. Storage ofgeneti cmateria l in genebanks isno t in linewit h all objectives of conservation. Conservation of abree d in ageneban k doesno t contribute to its socio-economic value, its contribution to culture and history andt o its ecological value.So ,th emai n valueo f ageneban k for farm animalsi s decreasing therisk of/ « situ conservation schemes. Conservation in genebanks might beles s costly compared to in situ conservation when iti s expected that it will take many yearsbefor e an objective of conservation hast ob e fulfilled with the stored genetic material.
1.8 Background todecisio n making in conservation farm animal genetic variation
1.8.1 Aspects of conservation In chapter 1 some general aspects ofconservatio n farm animal genetic variation andth e recent history arebriefl y outlined. For economicreason s it is impossible to keep all low producing breeds of farm animals alive.Therefore , in chapter 2th e strategies,whic h can be chosen for conservation, are outlined. Artificial reproduction techniques, including cryo- conservation of DNA,gametes , embryos and somatic cells, facilitated the establishment of genebanks for farm animal species,i n which genetic variation threatened by extinction of breeds can be stored for possible future use.Th eweightin g of criteria to be used in ordert o make achoic e between strategies are discussed.
1.8.2 Selection of breeds and choosing animals within breeds Several objectives of conservation favour the live conservation ofbreed sno t used anymore for economic reasons in animal production systems.However , both types ofconservatio n are costly. Therefore, scientific knowledge should be usedt omak e proper choices between andwithi n breeds.Man ybreed s were used over different countries ofEurop ei n subpopulations and many breeds originate from common ancestor breeds kept inpas t centuries before breeding programs started. Inchapter s 3,4 and 5o fthi s book the aspects of selection for conservation among andwithi n breeds andth e set up of conservation schemes are described.
1.8.3 Operation ofconservatio n activities Inchapte r 6th e operation of conservation schemes isoutline d anddiscusse d andi n chapter7 thedevelopmen t of an expert system for conservation is described.
Chapter 2.Choosin g the conservation strategy
G.C.Gandini "an d J.K. Oldenbroek2'
1) Istituto di Zootecnica, Universita degli Studi di Milano,Vi a Coloria 10,20133 ,Milan , Italy 2) Department ofAnima l Breeding and Genetics,DL O Institute for Animal Science and Health, P.O.Bo x 65, 8200A BLelystad , TheNetherland s
• Preface • Objectives andtechniques • Optionsfor self-sustaining localbreeds • Costs • Makingthe decision • Legalissues
2.1 Preface
Techniques for conservation of animal geneticresource s (AnGR) are generally divided inin situ,i.e .th emaintenanc e ofth ebreed swithi n theirproductio n systems,an d exsitu. Ex situ techniques are further divided, according to FAO (1998),i n cryoconservation of genetic material, which includes haploid cells (semen, oocytes), diploid cells (in vivo andi n vitro embryos, somatic cells) and DNA,an d exsitu live,i.e .th emaintenanc e ofliv e animals ofa breed outsideit sproductio n system (e.g.herd s kept innatura l protected areas,i n experimental and show farms, inzoos) .
Until recently, exsitu technique s were often advised for their high potential as areliabl e conservation strategy. Today,ther e iswid e consensus on conservation by maintaining populations within their production systems (in situ):
11 • the Convention of Biological Diversity (CBD) (art. 8)emphasise s the importance of in situ conservation and advises (art.9 ) exsitu conservation asa n essential activity complementary to in situmeasures , • FAOunderline s in its "Guidelines"(1998 ) thepriorit y for in situ conservation, • the Common Agriculture Policy (CAP) of the European Community incentives fanning of local endangered breeds in theirproductio n systems (EUreg .2078/92) . Exsitu, however , continues toprovid e powerful and safe tools for conservation ofAnGR .I t seems therefore reasonable tomak e efforts to build a framework for the effective integration ofi nsitu and exsitu techniques , inwhic h exsitu conservatio n is complementary to in situ.
Inthi s chapter wefirs t seeho w in situ and exsitu technique s differ in their capacity toreac h thevariou s conservation objectives.In situ, becaus e itimplie s themaintenanc e ofth ebreed s in theirproductio n systems andi t achieves the widest spectrum of objectives. However, itca n beassociate d with high costs. Iti s useful to evaluate the different options for self-sustaining populations insitu. Economi c incentives mayb eimportan t in theperio d needed toreac h self- sustainability: current EUincentive s andproposition s for additional incentives are discussed. Inreviewin g the scarce literature on costs of conservation techniques, weunderlin e thenee d for moreresearch . Finally,w epropos e some criteria tochoos e themos t appropriate conservation technique for aspecifi c breed and for thebreedin g context. Ashor t discussion on some legal issues associated to themanagemen t ofgenom ebank s concludes this chapter.
2.2 Objectives and techniques
Theobjective s for AnGR conservation, as stated in theintroductio n ofthi sbook , are: • opportunities tomee t future market demands, • insurance against future changes in production circumstances, • present socio-economic value, • opportunities for research, • cultural andhistorica l value, • ecological value.
12 Different techniques are available to achieve the different conservation objectives (table 2.1 .)• Insitu conservatio n iseffectiv e toreac h all objectives. The exsitu liv emetho d excludes the present socio-economic value,becaus e in this conservation strategy thebree d isremove d from its socio-economic context. Forth e samereaso n the cultural and ecological objectives cannot beeffectivel y pursued. Cryoconservation is an option, when socio-economic, cultural and ecological values are missing or are ofn o concern.
In table 2.1, the different techniques are compared onth e basis of factors associated toth e conservation objectives: i)th e opportunity for breed evolution and genetic adaptation, ii)th e opportunity tobette r characterise the breed, iii)th e exposure ofth ebree d torando m genetic drift andinbreeding . Beside the ontogenic process,cryoconservatio n 'freezes' alsoth e evolutionary process ofth ebree d andimpair s itsgeneti c adaptation, i.e. its future production value.Nowadays , very little isknow n onth e performances ofmos t endangered breeds;ther e is anee d toincreas e our knowledge on local breeds in order tobette r define their conservation value (seeparagrap h 2.3.).Population s of small sizear e exposed torando m genetic drift, which ismeasure d aseffectiv e population size and is established asinbreeding . Therat e of genetic drift (see chapter 6) can becontrolle d by accurate selection andmatin g of siresan d dams.Ex situ livepopulation s are expected tob esmalle r than in situpopulation s and consequently they aremor e exposed togeneti c drift. However, exsitu liveconservatio n might facilitate better genetic management. For QTL studies, semen isth e first option. For studies on genetic variation, purified DNA is sufficient.
Intabl e 2.2,ex situ technique s arecompare d for their effectiveness to achieveth e different aimso fcryoconservation . All techniques available ori n development are discussed. Oocytes differ, in terms ofefficienc y to achieve the various aims ofcryoconservation , from embryos because with oocytes iti s still possible tochoos e the desired mating.Nevertheless , oocytes here areno t distinguishedfrom embryos .Embryo s areth efirst optio n for breedre - establishment, followed by somatic cells (cloning),assumin g this technique will be soon available for this purpose. Thebree d can bere-establishe d by using semen for backcrossing females, butthe n four generations arerequire d toachiev e over 90%o fgene s ofth e endangered breed. With semen orsomati c cells cytoplasmic effects ofth eendangere d breed will be lost oraltered . Semen isth e geneticmateria l of choice for creation ofsyntheti cbreeds , for geneintrogressio n and asai dt oth e genetic management of in situ orex situ liv e
13 Table 2.1.Conservatio n objectives, factors associated and conservation techniques. Technique objective cryoconservation exsitu liv e in -situ meet future - insurance yes* yes * yes* socio-economic value no no yes research and education yes ** yes yes cultural-historical value no poor yes ecological value no poor yes factors associated breed evolution/genetic adaptation no poor yes betterknowledg e ofbree d poor poor yes characteristics exposure togeneti c drift no yes (+) yes *severa l differences amongth e threetechniques . See factors associated. **base d on crossings with otherbreeds .
Table 2.2. Conservation aims with different exsitu techniques . exsitu techniqu e aim semen embryos somatic cell DNA breed re-establishment yes* but< 100% yes yes* no creation of synthetic yes poor poor no breeds gene introgression yes poor poor no cryo-aided live scheme yes poor poor no
QTL studies yes poor poor no DNA studies poor poor poor yes *n o extra-chromosomal DNA.
14 programmes (cryo-aided live schemes. Seechapte r 6). Fortha tpurpos e embryos and somatic cells are less efficient.
2.3 Options for self-sustaining local breeds
Thetechniqu e ofmaintainin g endangeredbreed si n theirproductio n environments covers the widest spectrum of conservation objectives. Then, itbecome s important toanalys e the options wehav efo r an efficient insitu conservation.
An analysis ofth edynamic s ofth eerosio n offar m animal geneticresource s in Europei nth e last decades will probably reveal acomple x picture. Itma y shows cultural, social and food demandchanges ,transformatio n ofth e food production chain, countryregulation s and technological changes affecting in various ways thedeclin e ofloca l breeds. Inmos t cases iti s likely that these factors result in alac k in economicprofitabilit y ofth eloca l breed compared to otherbreed s orothe r economic activities in thatregion . Theabsenc e of abreeder s association ora breedin g programme may alsopla y a role.
Thefal l in population size is the first result ofthes e facts. Other effects areth e decrease amongbreeder s in enthusiasm for thepromotio n of theirbreeds ,whic h impairs performance recording and development ofbreedin g schemes.Al l these aspects might trigger a further decline of thebreed , finally leading to extinction.
Iti s likely to assumetha t in conservation ofAnG R prevention of breed decline can bemor e effective than aconservatio n therapy. Therefore, it isimportan t to counteract theprocesse s of breed declinebefor e the population sizewil l beto o small.Thi s will impair the probabilities of success andwil l increase the costs for recovering.
Then, several questions can beraised : • Which options areavailabl e to stop andrevers e the decline process into a self-sustaining programme? • What can welear nfrom recen t experiences?
15 • Doesth e European context offer particular opportunities tomak e local endangered breeds self-sustainable?
These questions will be answered by considering five general options: • establishing the economic performance ofth ebreed , • improving infrastructures andtechnica l assistance, • genetic improvement, • optimisation ofth eproductio n system, • developing activities to increase the market value ofbree dproducts , • developing incentives.
2.3.1 Establishing the economic performance ofth ebree d for most ofth e local European breeds we haven oreliabl e data onthei rperformances . Most often: • performances are estimated on small samples, • available information refer only tophenotypi c data, with no estimates of genetic parameters, • information isno t available on secondary traits, such aslongevity , fertility, mortality, feed andmanagemen t requirements, i.e. onthos e characters, which might significantly contribute tobree d profitability.
Inman y areas onth e world comparisons ofperformance s between crossbred and indigenous blreedshav ebee nbase d onpoo r experimental designs,whic h often producemisleadin g results (FAO, 1998).
It islikel y that better evaluations of theeconomi cperformance s of local breeds may change theresult s of comparisons among local and exoticbreed s andi tma y correct possibly erroneously perceived differences orma y assess possible strongpoint s of theloca l breed.
Inreedcomparison s should first bebase d on agoo d assessment ofbree dperformances . When thebreed s participate in anationa l recording scheme for production traits,th ebiologica l information for the comparison canb egathere d muchmor e accurately andt osom e extenta n economiccompariso n is feasible in combiningperformance s withmarke t prices ofproducts .
16 More accurate comparisons require: • awareness for interactions between the farm management andth e characteristics ofth e breed, which requires comparisons ofbreed s in different management systems.Fo r example,th e composition of the diet may interact withbree d performances, • additional trials at experimental stations or atpractica l farms under controlled conditions. Despitepossibl e high costs,thes e trials offer the opportunity to comparebreed s accurately for input and output factors, which isessentia l for aprope r economic comparison, • studies on farms and in experimental stations including evaluation ofcrossbred s tobette r understand thepotentia l useo fth e local breed in different crossbreeding production systems.
Therelativ e economic advantage ordisadvantag e of abree d is afunctio n ofth erelativ e prices for the different animal products. Abreed , which isno t used inhigh-input , high-output systems, can beprofitabl e in alow-inpu t system through ahig h feed intake capacity, longevity, fertility, hardiness, quality of theproduct s or anich emarke t for its product.
2.3.2 Improving infrastructures andtechnica l assistance Most often local breeds areproducin g in areas characterisedb y alo w socio-economic development. Thismigh t result, withrespec t to abreedin g programme, into alac ko f infrastructure andtechnica l assistance, including networks for milk collection andprocessing , slaughterhouses,network s for commercialisation ofproducts ,performanc e recording and services for technical assistance.Geneti c improvement is animportan t aspect andwil l be discussed in thenex t sub-paragraph. Iti s likely that the lack ofthes eelement s impairs the economicperformanc e ofloca lbreeds .
2.3.3 Genetic improvement In general local breeds dono tbenefi t from modem breeding techniques. Selection programmes may increaseth e genetic ability for productivity and consequently the profitability of localbreeds . Twomajo r considerations have tob e forwarded: • the definition ofbreedin g goals should takeint o account the conservation value ofth e breed. Traitspropose d for selection shouldb e accurately evaluated for their genetic correlationswit hthos etrait s thatdetermin e theconservatio n valueo fth ebreed , inorde rt o
17 avoid the deterioration of its conservation value.Thes e might include adaptation to ahars h environment ort olow-inpu t production systems ortrait s like longevity, fertility, meat and milk quality; selection schemes should take into account themaintenanc e of genetic variation within the breed andrisk s associated with ahig h rate ofinbreeding .T oreac h these goals,a theoretical framework has been developed in the last years andsoftwar e are available for field use(se e chapter6) .
Box 2.1.Reggian a cattle Inth e 1940'sth e Reggiana, aloca l dairy cattle farmed inNorther n Italy, counted more than 40,000 cows,the n progressively dropped to aminimu m of 500cow si n the early eighties.I t was atypica l process ofdisplacemen t of aloca l breed byth e cosmopolitan better-promoted andmor eproductiv e Friesian breed. Since the late eighties several activities were begun to support thebree d (shows,performanc e recording,valorisatio n ofproducts , etc)leadin g toa progressive increase ofth enumbe r of cowsu pt o 1,200 in 1998.A discussio n wasrecentl y opened amongbreeder s to develop some selection programmes. Breeding goals will probably include udder morphology followed bykg .o fprotein ,whil emonitorin g several aspects of milk characteristics (associated to cheeseproduction) , longevity and fertility. Constraints on rate ofinbreedin g havebee n included (Gandini et al, 1998). Iti s felt that, besides increasing profitability, the introduction of abreedin g programme might also increase theinteres t of farmers for their breed.
2.3.4 Optimisation ofth eproductio n system Increasing economicperformanc e ofloca lbreed s mightrequir ere-organisatio n ofthei r production systems,suc h as seasonal planning ofth eproduction , changing age orweigh t at slaughter orintroducin g some crossbreeding.
Attention should begive n toth e conservation ofth e local breed. Taking the introduction of crossbreeding as anexample : • breeding schemes should guarantee the maintenance ofviabl epopulation s ofth eloca l breed through asoun d pure breeding scheme, • thebree d might beuse d for theproductio n ofcommercia l crosses with ahig h performance breed.Th e commercial crosses might benefit ofhighe r inputproductio n systems,whil e the local breed should bemaintaine d in its original production environment tomaintai n its adaptation characteristics, • the use of the local breed as afemal e population (instead of asmal epopulation , which might bemor eprofitable ) mayb e advisable toguarante e the maintenance of alarg e population ofth e local genotype adapted toth eproductio n environment, • theus eo f ahig h performance breed that will produce crosses which cannotb e distinguished from the local breed isno t advisable,becaus e ofth erisk o f non-voluntary introduction of exotic genotypes inth e local breed.
Crossbreeding schemes are of interest also for indigenous breeds in developing countries (FAO, 1998).
2.3.5 Developing activities to increase the market value of breed products
2.3.5.1 Links between products and breeds Thestartin g point isth e question: isth e relationship between breed andproduc t helpful to diversify itsproduct s andt o sell them athighe rprices , i.e. toimprov eth e economic profitability of thebreed ?
Iti sknow n that diversification is an opportunity tograd eproducts . Generally the control and the enhancement of agricultural products' quality isa combinatio n of thera wmateria l (meat ormilk ) andth eprocessing . Once acertai n quality level is achieved, it can bepromote d by advertising,whic h letth e consumer perceive some elements ofth eproduct . Somerecen t experiences (Gandini andGiacomelli , 1997),summarise d in the examples in Box 2.2,suppor t the approach of amarketin g link between products and local breeds.
Only afe w breed-product links havebee n reported inth e literature. In thisrespect , iti s advisable that all experiences in the future will bereported . Some general conclusions canb e drawnfrom know n experiences: • the linkbetwee n product-breed can improvebreed' s economic profitability, • building this link offers several options: e.g.th e link can bepar t of aprotecte d designation of origin (PDO) orca n beuse d to further differentiate aproduc t within amarke t already differentiated (e.g.withi n aPDO) ,
19 the overlapping of an exoticbree d in the farming area of the local breed might hamper (e.g. difficulty of separate milk collection) the creation of alin k between the local breed andth e product, in somecases ,th e linkbetwee n product andth ebreed-environmen t seems tob emor e appropriate than the link between product andbreed .
Box 2.2.Nich e marketing In France, since 1986th e Tarantaise and the Abondance cattlebreed s are associated toth e production ofth e Beaufort andtogethe r with the Montbéliardebree d toth e Reblochon and Abondance cheeses.Th epositiv e economic valorisation ofmil k is documented (Verrier, 1995).O nth e Italian side ofthes eAlp s there isa simila r case:th e Fontina cheese isproduce d manufacturing milk only ofth eValdostan a breed. Other examples,i n France, of links between cheeses andbreed s includes:th e Ossau-Iraty cheeses andth e Manech andBasco - Bearnaise sheepbreeds ,th e Comté cheese andth e cattlebreed s Montbéliardean d Simmenthal, theLaguiol e cheese and the cattle breeds Simmenthal andAubrac . In Italy, the Parmigiano Reggiano cheese since 1955ha s aprotecte d designation oforigi n (PDO).I n 1991 aconsortiu m ofbreeder s startedth e marketing of abran d of Parmigiano Reggianomad e only withmil k of the Reggiana breed (the original breed, before the Friesian, used toproduc e this cheese).Sinc e 1991thi s brand is sold at apric e 16%highe r than the common Parmigiano Reggiano. Therecen t increase ofth enumbe r of cows,fro m 500 ofth e 1980'st o 1,200 in 1998i sthough t tob e strictly associated tothi s operation.
2.3.5.2 Ecological and cultural breed products In thisrespec t wema y consider that (Gandini andGiacomelli , 1997): • in Europe,befor e the intensification and industrialisation process in the last decades, livestock farming was closely linkedt o the use of farmland andwa si n general extensive. Most ofth earea swhic h arerecognise d nowadays asnatura l areas are in fact agro- ecosystems created andmaintaine d by farmers andthei r local breeds.Th edeclin e ofloca l breeds and of theirproductio n systems areraisin g concern for themaintenanc e of these agro-ecosystems andcultura l landscapes; • when grazing ceases,bus h encroachment follows, which makes itmor e difficult to useth e lands for recreation. Farmers maintain landscapes of greatbeauty ,whic h areric h in culture.
20 Examples in thisrespect ar eth e Alpine pastures, which attracts large amounts of touristsi n summer; • thereductio n of livestock grazing isknow n to increase risks associated tonatura l fires, especially in the Mediterranean regions, and to floods in thealpin e areas; • local breeds may beconsidered , from acultura l point of view,t ob etestimonia l ofth e farming civilisation ofth e specific area.
Based onthes e and similar considerations, several countries andth e ECdevelope d specific agriculture andenvironmen t policies, including subsidy systems directed toth e development andmaintenanc e ofrura l landscapes andagro-ecosystem s management. However, subsidies areno t expected tob e available in the long term. Then, the question arises:i s it possible to develop amarke tvalu e for the ecological andcultura l services from local breeds?
Recent experiences allow some optimism: • in Southern Europe, cheese producers andbree d associations started to envisagea n ecological role for their local breeds (see Box2.3.) ; • in Austria, some Tyrolean communities andtouris m enterprises observed that summer tourists expected thepresenc e of afarmin g community with theirbreed s andth e availability of local food products, the presence of animals and afarmin g cultureo n tracking areas.Sinc e afe w years,the y subsidise the farmer community toavoi d the decline of farming activities. In doing so,the yrecognis e amarke t value ofth e cultural and ecological value of farming; • in several parts ofEurop ehorse s arerecognise d asa prope r help toharves t thewoo d under rough conditions. This may facilitates the conservation of theorigina l heavy European horses.
Box 2.3 Ecological use From 1993,i n Savoy in France,her dmil kproductio n (Tarantaise andAbondanc e cattle breeds) for making the Beaufort cheese islimite d to 5,000k gpe r lactation in order to maintain the optimum stocking rate of .7hea d per hectare.O nth e Southern side ofth eAlpes , in the Italian Valle d'Aosta, theproductio n of the Fontina cheese implies that milk comes from Valdostana cattletake n to alpine summerpastures .
21 2.3.6 Incentives During the timeneede d toincreas e the economic profitability of the endangered breed, incentive payments can effectively halt the decline ofth ebreed . Incentives may benecessar y toimprov e the economic profitability ofth ebreed .
2.3.6.1 Current incentives • TheE Uregulatio n 2078/92 provides incentive payments to farmers keeping endangered breeds of several species.Th eincentiv epayment s arethough t to compensate farmers for the lowerprofitabilit y ofth e localbreed s compared to substituting thesebreed s withmor e profitable exoticbreeds .Loca l experiences haveprove d the efficacy of incentives payments.Amon g the different forms ofincentiv e payments (FAO, 1998),th e most effective ones for the short andmediu m term support of thebree d should beused .
• EU Council Regulation 1467/94 ("European Community Programme on the conservation, characterisation, collection andutilisatio n ofgeneti cresource s in agriculture") provides grants to the State members for conservation activities in agriculture. Until now,muc h emphasis hasbee n put on the plant sector. Iti st ob eexpecte d that farm animal genetic resources will getmor e attention in the comingyears .
• The 3rdConferenc e ofth e Parties ofth eCB D(hel d in Buenos Aires in 1996)dre w the attention (in the document "Conservation and sustainable useo f agricultural biological diversity") ofbot h theinternationa l funding agencies andth e CBDt o support the conservation andsustainabl e useo fbiologica l diversity important to agriculture.
2.3.6.2 Proposition for additional incentives Considering that CAP supports local breed conservation, iti s worthwhile toinvestigat e the introduction ofne w measures aimed to AnGR conservation into present EU Regulations. This might include: • subsidies tobu y milk quotas by farmers with endangered breeds to extend their herd size; • subsidies tobu y milk quotas by farmers withnon-endangere d cattle breeds,willin g to extend their herds with cows of endangered breeds;
22 • suckling cows subsidies for endangered breeds producing somemil k for themarke t andi n mixed (suckling anddairy )herd s (Institut del'élevage , 1992); • permission to store semen and embryos of endangered breeds that cannot fulfil thepresen t sanitary rules of theEU . Before this genetic material is used, itha s tob eteste d for the relevant diseases and cost might bepai db y EU; • toinclud e inreg . EU2078/9 2 species presently not-considered, primarily thepig ; • to develop alega l framework for thepromotio n ofbreed-produc t links,takin g into account for example EUregulatio n 2081/92.
2.4 Costs
The future economy of animal production is amajo r argument for preventing erosion of AnGR. Then, costs for their conservation should be seen as aninsuranc e against uncertainty of future market andproductio n circumstances. In ashorte r timehorizon , costs can be seen as aninvestmen t in thedevelopmen t of animal production, asa contributio n to environmental, landscape and cultural conservation and assuppor t to scientific progress.
From the scarce literature on costs of conservation techniques (Breme t al., 1984;Ollivie r and Lauvergne, 1988;Lomke r and Simon, 1994;Ollivie r and Renard, 1995) some considerations canb e stated: • in comparing costs of different techniques, aims should bewel l defined. Cryoconservation with semen can bea ver y costly method when breed re-establishment isth e aim (Lomker and Simon, 1994), • in comparing costs of different techniques,th e conservation time horizon shouldb e taken into account. With cryoconservation, costs ofmaintenanc e are afunctio n ofth enumbe r of yearsbefor e use.Th e advantage ofcryoconservatio n over in situ conservation canb e expressed by thenumbe r of years ofconservatio n above which it becomes cheaper than keeping live animals (Ollivier andLauvergne ,1988) , • cryoconservation costs ofth edifferen t methods vary among species,becaus e differences in efficiency oftechnique s doexist .Fo r example,i n therabbi t embryobanks are cheaper than semen banks (Ollivier and Renard, 1995), • costs are expected to differ significantly amongregion s andcountries ,
23 • in situ costs strongly depend onth e economic competitiveness ofth e endangered breed, i.e. on the subsidiesnecessar y tocompensat e for the gap inprofitabilit y with the high producing breeds (Lomkeran d Simon, 1994), • all the literature refers tosimulate d costs;n orea l data from field projects areavailabl e in the literature, • exsitu conservation isi n general considered tob eles s expensive than in situ conservation.
Moreresearc h isneede d to compare conservation techniques on an economic basis. Some general considerations canb epropose d separately for in situ,ex situ liv e and cryoconservation techniques:
• In situ Our approach ist otr yt otak e thebree dt o self-sustainability, therefore: • incentive payments to farmers should cover thega pi n economicretur n between the endangered breed andth e average commercial breed. Breed comparisons (see paragraph 2.3) are useful to determine the amount ofth eincentiv e payment; • thelengt h of economic incentivepayment s depends onth eperio d necessary totak eth e breed towards self-sustainability; • takingth ebree d towards self-sustainability may imply costs for technical assistance, for the development of abreeder s association, for performances control and breeding schemes,an dcost s toidentify , qualify andmarke t products linked toth e breed andt o market thecultura l andecologica l value ofth ebreed .
It should benote d that, when self-sustainability isreached , conservation costs become zero. Costs of cryo-aided live schemes should beaccounte d for, where applicable.
• Exsitu liv e Costs of exsitu liv e conservation are equal toth e difference between theprofi t from farming the average commercial breed andth e endangered breed. Market strategies promoting tourism (herds kept innatura l protected areas,i n show-farms) andhig h quality products (e.g."biological "products ) can beuse d toincreas e profitability. Costs ofcryo - aided live schemes shouldb e accounted for, where applicable.
24 • Cryoconservation All costs should beaccuratel y accounted for. - Considering semen, costs include: + finding donor males orproducin g matings to obtain males whennecessar y to widen the genetic variation in the semen tob e stored (see chapter5) , + raising males topubert ynecessar y in some situations when itma yb e difficult to find boars becausemale s are usually castrated atearl yage , + taking males to special centres for collection andfreezing , (because ofhealt h regulations, it can be difficult in Europe tous eregula r A.I. facilities), + semen collection andprocessing , + semen storage andmaintenanc e attw o locations (costs of tanks andliqui d nitrogen), • Ifth eai mi sbreed-reconstruction , add costs for backcrossing. - Considering embryos, costs include: + finding donor females, identifying optimal matings andproducin g embryos, + embryo collection andprocessing , + embryo storage andmaintenanc e attw o locations (costs oftank s and liquid nitrogen).
2.5 Makingth e decision
Mostoften , because financial and human resources arelimited , breeds cannot begive n the samepriorit y for conservation. Chapter 4wil l discuss criteria andmethod s for selecting breeds for conservation. When abree d ora seto fbreed sha sbee n selected, the question arises: which in situ or exsitu techniqu e orwhic h in situ and exsitu combinatio n should be used?
Inparagrap h 2.2.,th e capability of eachtechniqu e toreac h the conservation objectives was analysed. Costs oftechnique s were discussed inparagrap h 2.4.No ww epresen t some criteria tochoos e themos t appropriate conservation technique.Th e following nine steps, illustratedi n figure 1,shoul db e considered:
25 1. Evaluate the current conservation values ofth e breed. An accurate evaluation ofth e conservation values ofth ebree d is expected tob e done in selecting breeds for conservation (chapter 4). Two aspectsrequir e further consideration: • to estimate the genetic variation of abree d andit s uniqueness wedevelope d objective criteria (e.g.geneti c distances, genetic parameters). Conversely, we dono t yethav e appropriate and standard tools to evaluate the cultural, ecological andsocio-economica l value of abreed . For example, itmigh t be said that becausebreed s areproduct s of domestication as such, they have acultura l value.Thi s isno t necessarily true,i n general abree d will have acultura l valuewhe n itplaye d in thepas t animportan t role inth e creation anddevelopmen t of local agricultural techniques, food products, gastronomy, landscape, local handcraft techniques, costumesetc. ; • conservation values ofth ebree dmus tb epresen t in afor m that allowthei r conservation. For example,a bree d will have ahig h cultural value worth considering conservation when expressions of this culture are still present in the farming area. Ifnot ,i twil l be only apal etestimon y ofit .
2. Identify the conservation objectives for the breed.No t all the conservation valueso f thebree dma yb etake n asconservatio n objectives. The choice may vary among countries, because the different interest andprioritie s of Government andhuma n societies.E.g . nowadays, cultural andecologica l values aremor e eligible asconservatio n objectives in Europe than in otherregion s ofth e world.
3. Selectth e techniques, which allow reaching the conservation objectives previously identified. Not alltechnique s allowreachin gth e sameconservatio n objectives with equal effectiveness. Following tables 1 and 2,selec t techniques (in situ,ex situ live , cryconservation ) orcombination s ofthes etechnique s that could beuse dt oreac h the conservation objectives previously identified. Ifth e socio-economical value ofth ebree d is anobjective , maintenance ofth ebree dwithi n itsproductiv e context (insitu) i sth eonl y technique available. Ifcultura l value or ecological values are among the conservation objectives, in situ or exsitu liv e techniques can be used. In all thesecases , cryoconservation (agenom ebank ) can beuse d in addition to in situ and exsitu liv et o reduceth erisk o fa bree d loss.Whe n objectives arelimite d toth e opportunities tomee t
26 future demand, the insurance against future changes inproductio n circumstances and the opportunities for research, all techniques andthei r combinations areeligible .
4. Rank techniques for risk. Analyse thetechnique s orcombination s of techniques onth e basis of therisk o f failure and exclude those with anon-acceptabl e level ofrisk . Risk of failure is afunctio n of: • the degree of endangerment ofth ebree d (EAAP Working Group onAnima l Genetic Resources, 1998).Whe n in situ or exsitu live areth e techniques of choice andth e population sizei sver y small,healt h conditions are critical andth esocio-economica l stability ofth eare a is low, therisk o fbree d loss canb ehigh , • thepossibilit y of controlling genetic drift (availability of skilled technicians to perform mating schemes), • the success ofpas t conservation: the success ofremovin g factors that in thepas t limited conservation success.
5. Rank techniques for costs.Fo r all techniques (all exsitu techniques , i.e. semen,embryos , somatic cells) or for combinations oftechnique s that guarantee acceptablerisks o f failure, costs should beevaluated . Rank all techniques onth e basis ofcosts .
6. Rank techniques for the opportunity of breed evolution/adaptation and ofa bette r knowledge ofbree d characteristics. When weprefe r to continue the evolution and genetic adaptation of abreed , then the in situtechniqu e should be chosen.Thi s will also guarantee the opportunities toincreas e ourknowledg e ofth ebreed .
7. Rank cryoconservation techniques for efficiency of conservation aims.No t all theex situtechniques , semen, embryos andcells , allows to achieveth e different cryoconservation aims(se e table 2.2).
8. Rank techniques for efficiency ofconservatio n of cultural and ecological values.I f cultural value orecologica l values areamon g the conservation objectives, in situ or exsitu live techniques canb e used;howeve r exsitu liv eha spoore r performances (table 2.1).
27 9. Choose thetechnique . Consider the different rankings for 1) fo rrisk o f failure, 2) for costs, 3) for opportunity ofbree d evolution/adaptation and ofbette r knowledge ofbree d characteristics, 4) for efficiency ofconservatio n aims 5)fo r efficiency of conservation of cultural and ecological values.Th eweightin g of each of these factors will depend upon the amount ofresource s available, interests andpriorities , strategy preferences.
2.6 Legal issues
Thechoic e ofe xsitu technique s implies the creation ofa genom eban k andth e discussion of some associated legal issues that,becaus e theyhav ebee n barely investigated until now, deservesom eattentio n inthi s paragraph.
FAOrecentl y pointed outth e need todevelo p alega l framework for access to genome-banks (FAO, 1998).Here ,i t is underlined that adiscussio n should be opened with some urgency, considering that:
• indistinct present situations of exsitu collections ofplan t germplasm,buil tbefor e the Convention on Biological Diversity (CBD)entere d into force, shouldb eavoide d in farm animals asmuc h aspossible .Anima l genome-banks are still at an early stage,whic h minimise possible difficulties due topre-existin g situations; • the debates onrelate d issues such as Intellectual Property Rights (IPRs), Farmers' Rights (FRs)an d General Agreement on Trade andTariff s (GATT) areread y to start.
2.6.1 State ofth edebate s • The CBD clearly states among its objectives (article 1)th e "equitable sharing ofth e benefits arising out ofth eutilisatio n of geneticresources , including by appropriate access". Itrecognise s "the sovereignrights o f States over theirnatura l resources"(articl e 15).I t invites each Contracting Party "tocreat econdition s tofacilitat e access togeneti cresource s by other Contracting Parties"(articl e 15).Withi n the CBDframework , access to genetic resources, including genome-banks, aresubjecte d tonationa l legislation, which should promote equitable sharing within andbetwee n countries.
28 • Farmers' Right (FRs) have been developed by FAO under the International Undertaking for Plant Genetic Resources (Resolution 5/89) and are defined as "rights arising from the past, present and future contribution of farmers in conserving, improving and making available plant genetic resources. Theserights ar eveste d in the International Community, astrustee s for present and future generations of farmers, for the purposes of ensuring full benefits of farmers and supporting the continuation of their contributions". • IPRi s aframewor k of laws thatprovide s monopolyrights fo r theproduct s ofhuma n activity, agriculture andtechnology . Itinclud epatents , copyrights, Plant Breeders' Rights, trademarks, etc.Th eCB Ddiscusse s theprotectio n of intellectual propertyright s in article 16"Acces st o andTransfe r ofTechnology" . Itrecognise d thatpatent s andothe rIPR sma y have influenced the implementation ofth eConventio n and stated that Contracting Parties "shall co-operate in thisregar d subject tonationa l legislation andinternationa l lawi n order to ensure that suchrights ar e supportive of andno t run counter its objectives". • Patenting ofbiotechnologica l inventions in the European Union is subjected toth e Directive 98/EC ofth eEuropea n Parliament and ofth e Council.
2.6.2 Developing a framework The development of alega l framework in EU should consider, among others: • thedevelopmen t of FRs for animal geneticresource s in order to i)allo w farmers to fully participate in the benefits derivedfrom th e improved use ofAnGR ,ii ) assist farmers inth e conservation ofthei rbreeds ,iii ) ensure that sufficient funds are available for these purposes; • aful l definition ofintellectua l and commercial properties that may arise from the useo f storedmaterial , both cells andDNA ; • the ownership, if any,o fgenome-banks ,t owhic h contributed farmers, governmental and private organisations, private companies,nationa l andinternationa l funding agencies.
29 References
Brem,G. , F.Graf , H. Krausslich, 1984.Geneti c and economic differences among methods of gene conservation in farm animals. Livestock Production Science 11:65-68 .
FAO, 1998. Secondary Guidelines for Development ofNationa l Farm Animal Genetic Resources Management Plans:managemen t ofsmal l populations atrisk. FAO ,Rome , Italy. 215p.
Gandini,G. , P.D eFilippi ,A . Bagnato,G . Pagnacco, 1998.Selectio n and inbreedingrat ei n asmal l endangered dairy cattle breed: the Reggiana. Proceedings of the6t h World Congress on Genetics Applied toLivestoc k Production. Armidale,28:131-134 .
Gandini, G. and P.Giacomelli , 1997.Wha t economic value for local livestock breeds? Book of abstracts of the48t h Annual meeting ofEAAP :20 .
Institut del'Elevage , 1992.Endangere d ruminants breeds in the EEC:surve y and status of population and proposals for adapted rules tofavou r their breeding. Institut de l'Elevage, Paris (manuscript).
Lomker, R. and D.L. Simon, 1994.Cost s of andinbreedin g in conservation strategies of endangered breeds of cattle. Proceedings ofth e 5th World Congress on Genetics Applied to Livestock Production. Guelph, 21: 393-396.
Ollivier, L.an dJ.J . Lauvergne, 1988.Developmen t andutilisatio n ofanima l genetic resources. Proceedings ofth e 6th World Conference Animal Production, Helsinki: 85-101.
Ollivier, L. andJ.P .Renard , 1995.Th e costs ofcryopreservatio n of animal genetic resources. Book of abstracts ofth e46t h Annual Meeting ofEAAP .
Verrier, E.an d L. Bresson, 1995.L aplac e desrace sbovine s Abondance etTarentais e dans unepolitiqu e d'aménagement du territiore desAlpe s duNor d II:un edynamiqu e nouvelle en course.Bulleti n del'Académi e Vétérinaire deFrance .
30 Figure 1.Choosin g the technique
In situ is the only technique. If breed endangerment is high, in situ + cryoconservation
Thefollowin g techniques are eligible: • in situ • ex situ live • in situ + cryoconservation • ex situ live + cryoconservation V /
Possible objectives are:t o meet future market demands, insurance against future changes, research and education I The following techniques are eligible: • in situ • ex situ live Rank techniques for risk of • cryoconservation (semen and/or embryos failure. Delete those with and/or somatic cells) high risk • in situ + cryoconservation • ex situ live + cryoconservation • in situ + ex situ live
Rank techniques for costs
Rank techniques for breed evolution/adaptation and knowledge
Rank techniques for efficiency toward cryoconservation aims and for conservation of cultural and ecological values i Considering all rankings, choose the most effective technique
31
Chapter 3.Measurin g genetic uniqueness in livestock
J.H.Eding 1' and G.Laval 2)
Department ofAnima l Breeding and Genetics,DL O Institute for Animal Science and Health, P.O. Box 65,820 0A B Lelystad, TheNetherland s Laboratoire deGénétiqu e Cellulaire, INRA, 31326Castane t Tolosan, France
• Introduction • Whatkind of genetic information shouldbe used? • Whatis the basic theorybehind genetic diversity? • Howare genetic distances interpreted? • Whatare the practical considerations?
3.1 Introduction
3.1.1 Uniqueness ofbreed s InEurop e there is alarg e interest in the uniqueness of local breeds (meaning the extent to which abree di sdifferen t toal l others).T okno w theuniquenes s of abree d onemus t study thediversit y in ase t ofbreeds .Ove rth e last few years thenumbe r of studies into diversity and distancesbetwee n European breeds has grown, withman y large-scale projects underway . Theseproject s include studies into cattle (Roslin, Scotland; combined Scandinavian effort withregar d toNordi c breeds),pig s (INRA, France.A projec t that when finished should cover 50differen t breeds),poultry , horses, sheep,goa t andrabbits . Because ofth eincrease d interest inthi s kind ofproject , itmigh t be ofinteres t to look more closely into themechanism s underlying genetic distances andgeneti c diversity.
It shouldb e stated here,tha t the uniqueness ofbreed si sjus t one criterion among others for prioritising breeds for conservation. For afurthe r discussion on allrelevan t criteriaw erefe r to chapter4 .
33 3.1.2 How can diversity be defined? Diversity can be defined in anumbe r of different ways on anumbe r of different levels. Looking atnature ,ther e is an enormous amount ofdiversity . This diversity weca n observe and measure directly isphenotypic. O nth e other hand the largest part of diversity is hidden, because it isgenetic diversity , embodied in the chromosomes of each cell of an animal. Modern technology used in genetics enables ust omeasur e this type of variability.
3.1.3 Measuring diversity Variability between populations (species,breeds ) can be assessed using mathematical tools, which translate the differences toa measur e ofdistanc ebetwee n apai r ofpopulations . Given the distinction between phenotypic andgeneti c variability, it follows that distances can also bedivide d intophenotypi c and genetic distances. Which ofthes e tools is preferred, depends onth e objectives ofth euser .
3.1.4 Phenotypic diversity Ifth einteres t isi nphenotypi c diversity only, one should usephenotypi c distance measures. An example ofth epossibl e use ofphenotypi c distances isprioritisin g of breeds for adaptation criteria. Greatimportanc e isplace d on adaptation ofbreed s tothei r environment, sinceth etren d istowar dmor esustainabl e agricultural systems andwell-adapte d animalswil l bea nessentia l part ofsuc h systems (Seeals ochapte r 2fo r details onbree d comparisons). It should benote d that measuring phenotypic distances doesno t necessarily give the same results asgeneti c distances, becausethe y arebasicall y different measures. Phenotype is determined bygenotyp e and environment (andthei r interaction). Inrelatio n tomeasurin g diversity van Hintum(1994 )discusse s themerit s ofparticula rphenotypi c traits (tob eprecise : quantitative traits)a sa mean st oasses sgeneti cdiversity .H esuggest stha tdistance sbase do n quantitative traits aremor eindicativ e ofadaptatio n to environmental factors. Thisi ssupporte d bya stud yb yBursti n andCharcosse t (1997).The yfoun d atriangula rrelationshi p between phenotypic andmarke rgeneti c distances:Lo w genetic distances areassociate d withlo w phenotypic distances,hig hgeneti cdistances ,however , areassociate d with arang eo f phenotypicdistances ,meanin g thattw opopulation s whichar egeneticall y distantnee dno tb e phenotypically different. Infact , phenotypicallythe ymigh tresembl e eachothe rclosely .I n other words,tw obreed s can showth esam ephenotypi c characteristics withoutbein g closely relatedgenetically , whichmean stha tbreed s can arrive ata simila rphenotyp e along different geneticroutes .
34 Theresult s ofva nHintu msugges t thatphenotypi c distances couldpossibl yb euse d asa quantitative measure for adaptation ofbreed st oparticula r environmental aspects. Phenotypic diversity mayb esee n as'expresse d genetic diversity', i.e.geneti c diversity atth e coding regions.Wherea s the'neutra l genetic diversity' ismeasure d atnon-codin g loci,lik e microsatellites orothe rgeneti cmarkers .Th edifferenc e between 'expressed'an d'neutral ' diversity becomes clearer ifw econside r the example of alarg epopulatio n thati s split intotw o largesubpopulations . Somegeneration s of strong selection canmak eth e expressed traits substantially different andthu s creates alarg e 'expressed genetic'distance . However,becaus eo f thelarg epopulatio n sizes andtherefor e small inbreeding (see 3.3),th e'neutra l geneticdistance ' will besmall .Hence ,th epopulatio n willb econsidere d almost identicalfrom a neutra l genetic distancepoin t ofview ,whil ethe y show substantially different traits.
Mostliteratur e concentrates on'neutra l genetic diversity',whic h will therefore betreate di n detail inthi schapte r andwil lb eshortl y termed'geneti c diversity'.Th e field ofphenotypi c or expressed diversity isnew . Someattempt s toquantif y this diversity havebee nmad eb y principal component analysis(Morrison , 1967).However ,muc hmor eresearc hi sneede d inthi s area.
3.1.5 Genetic diversity FAO defines diversity asgeneti c diversity intype s ofAnima l Genetic Resources, i.e. breeds of aspecie s (Henson, 1992;se e also chapter 4). Another definition iso n the level ofgenes , where asmuc h alleles aspossibl e should beconserve d (Crossa et al. 1993;Smith , 1984).Th e primereaso n for conservation efforts in the EUi sth e concern that without intervention whole species might lose the flexibility to deal with changing circumstances (market demands, production systems,etc.) .Therefore , in the EUcontex t theapproac h istoward straits , meaning the genetic variance in traits (known traits but also unknown traits ofpossibl e future use)shoul db econserved . Thisimplie stha t theconservatio n effort will befocusse d onth e total genetic diversity ofa species ,withou t preferring certain traits to others.Th e latterpoin t ofvie w shifts the conservation effort from allelic diversity to diversity in genotypes. Since most traits dealing with adaptability, production andreproductio n arepolygeni c (influenced bymultipl e genes) it is clear that it isunnecessar y toconserv e every known allelepe r locus (which is impossible in any case).Fo rinstance , atrai ttha t is coded for by 10dialleli c genes will have apotentia l of 59,000 different genotypes. In asituatio n with three alleles per locus thisnumbe r is approximately 60.5millio n different genotypes. Furthermore, calculations
35 show that rare alleles don't contribute substantially toth e genetic variance of atrai t (Falconer andMackay , 1996).Fo rpolygeni c traits,diversit y is in the genotypes andno t in the diversity ofalleles .
In light ofth edevelopment s inth eE U asdescribe d above (and in thefirst paragraph )w ehav e chosen toconcentrat e on describing the tools (genetic andmathematical ) necessary for the conservation ofth etota l of genetic diversity, without emphasising certain (groups of) traits.
3.2 What kind ofgeneti c information should beused ?
Themos twidel y usedgeneti c distances usedifference s in frequencies of allelesi n different populations. Inprincipl e anygen etha t showspolymorphisms ,i.e. has2 o rmor ealleles , canb e used. Inth epas t anumbe r ofdifferen t types ofmarker shav ebee n usedt odesignat e differences inthos e frequencies. Thoseare : • Biochemical markers • Bloodtypes • Allozymes • Geneticmarker s • Random Amplified Polymorphic DNA(RAPD ) • Restricted/Amplified Fragment Length Polymorphisms (RFLPan dAFLP ) • Microsatellites Thefiel d ofmolecula r genetics isstil l in astag e ofrapi d development, with manynew , promising techniques underway .Th edevelopmen t ofDNA-chip si s an example (seeBo x 3.2).
Biochemical markerpolymorphism s arebase do ndifference s inprotei n molecules.Thes e differences occurbecaus e thegene scodin g forthos eprotein s showpolymorphism . Biochemical markers aretherefor e indirect indicators ofgeneti cdifferences . However, differences inth e aminoacid smakin g upth eprotei n dono tnecessaril y lead to detectable differences inproteins . Apar t ofgeneti c diversity willtherefor e stayhidden . Polymorphism ofmarke r loci iso fimportanc e when studying thegeneti crelation s within and between breeds (Bretting andWiderlechner , 1995).Geneti cdiversit y ismainl y afunctio n of geneticrelationship s between animals.T ocorrectl y assessthes erelationship s onth ebasi so f
36 Box3. 1 Literature All thesetype so fgeneti cmarker s havebee n usedi nth eman ystudie s on genetic diversity. For instance,th eus eo fmicrosatellite s hasbee n studies,amongs tman yothers ,b yMoazami - Goudarzy et al.(1997 )i n European cattlebreed s andb y Estoupe tal .(1995 )i npopulation s of honeybee . Brettingan d Widerlechner (1995)giv e aver y useful review onth etype so fmarker s available andthei r utility.
markerdata ,ideall y onewoul d want tohav ea marke r genewit h2 Nallele s divided evenly over Nfounders . After anumbe r ofgeneration s the allelicfrequencie s for thatgen ewoul dreflec t the contribution of each founder toth egrou p ofanimal sunde rinvestigation . Although thiswil lno t beencountere d inrea l life, using markers that exhibit thehighes t degree ofpolymorphis m can best approximate this situation. Thisi sth ereaso n why functional genes (i.e.gene stha t codefo r functional proteins asoppose d tononcodin g loci likemicrosatellites ) andbiochemica l markers are lessfavourabl e for estimating genetic distances.Bot h functional genesan dbiochemica l markers haverole st o fulfil inth ephysiolog y of ananimal .A majo r mutation ina functiona l geneo rgen ecodin g for the biochemical markerwil l ingenera l have adeleteriou s effect. Box3. 2 DNA-chips Iti s estimated that every 100-300 nucleotides in the genome arepolymorphic . There areno w methods under development toidentif y such singlenucleotid e polymorphism (SNP). DNA chips are anove l andstil l developing technology that allows identification of every nucleotide in astudie d DNA sequence in asingl e operation. Ase t ofoligonucleotide s is set ont o asoli d glass or silica support sotha t there is an oligonucleotide for everypossibl e sequence variation. The studied sequence carries afluorescen t dye and is allowed tohybridis e with the set ofoligonucleotides . It hybridises preferentially toth e exactly matching sequence. When upt o 100,000oligonucleotide s can be attached to achi p of 1.7 cm2, aver y largenumbe r of SNPsite s can bequickl y detected by automatic readers.
This opensne wpossibilitie s for the useo f marker loci in diversity studies. Itwil l berelativel y easyt o screen anindividua l for hundreds of loci,increasin g theprecisio n of estimates based on this data.
37 Such amutatio n willprobabl y become extinct after sometime ,leavin g thosemutation s with more favourable effects. Expressed polymorphisms offunctiona l geneso rbiochemica l markers willneve r exhibit theleve l ofpolymorphis m found inmicrosatellite s (with thepossibl e exception ofgene slocate d onth e Major Histocompatibility Complex). Furthermore, onth ereques t ofFAO ,a pane l ofexpert sha s constructed ase to f microsatellite loci for eachspecie s tob euse d asth estandar d sett ocalculat egeneti c distances andgeneti c diversity. Similar activities havebee n undertaken byth eEAA Po nth ereques t ofth eEuropea n Union. Forth ereason sstate d above,w ewil l concentrate hereo nth eus eo fmicrosatellites ,althoug h mostprinciple s outlined inthi s section will applyt oothe r types ofmarker s aswell .
3.3 What is the basic theory behind genetic diversity?
Measuring genetic diversity between breeds isusuall y done by estimating genetic distance. These distances have abas ei npopulatio n genetics.Befor e wediscus s thesemeasure s into detail itmigh t therefore beusefu l tointroduc e someke y terms used in population genetics theory (Formor e detailed discussion ofth e subject see:Maleco t 1969, Falconer and Mackay, 1996).
3.3.1 Kinship and inbreeding. Central notionsi n population genetic theory areinbreeding an dkinship. Individual s are related ifthe y share one ormor e ancestors. The level ofrelatednes s between individuals can be expressed in thecoefficient of kinship, o r0 (Malecot, 1948an d 1969).Th e coefficient of kinship is defined asth eprobabilit y that twoalleles , drawnfrom tw oindividual s arebot h unmutated copies of the same allelefrom a commo n ancestor. Inbreedingmean s mating of related individuals, and can bequantifie d in the offspring of such amatin g asth e probability that two alleles, drawn from the sameindividual , are unmutated copies of one allele from a shared ancestor. Generally this probability isdenote d asF an d for anindividua l Fwil l be equal toth e kinship ofit sparents .
Inpopulatio n genetictheor y there are four evolutionary forces, which cause genetic differences between populations: Random drift, selection, mutation and migration.
38 3.3.2 Random drift Random driftmean s therando m fluctuation of frequencies of alleles duet orando m sampling processes in afinite population .A gen e orlocu s is said tob eneutra l if thedifferen t alleles of thegen e dono t give the individual aselectiv e advantage over others.Microsatellite s are genestha t generally reveal alarg enumbe r of different alleles that are selectively neutral. If weconside r twopopulation s stemmingfrom th e sameancestra l population theexten t ofth e divergence in allele frequencies for such selectively neutral loci is afunctio n ofth eleve l of isolation of onepopulatio n from another.
Withinpopulations Given enough time, say tgenerations , every allele of every locus in afinit e population will drift to afrequenc y of either 1 (fixation) or 0(loss) .Afte r these tgeneration s thepopulatio n is completely inbred. This probability will be larger asth e relationship between theparent s of this offspring will be larger. Inrando m breedingpopulation s with equal numbers ofmale san d females there exists adirec t relationship between inbreeding, thenumbe r ofgeneration s (t) andth epopulatio n size (N),whic his :
1 2N
Theprobabilit y of anallel eneithe r being lostno rfixated i n apopulatio n is approximately proportional to 1-F (Falconer andMackay , 1996).Fro m this it follows that an increase in F will increase thenumbe r of loci that have been fixated.
The calculation of Fi s dependent onwhic h generation wedefin e asth efirst generation . Starting from different generations weobtai n different results.Tha t is why population geneticists areofte n moreintereste d inth erat e ofincreas e of Fpe r generation (AF).Th e relation between the size of arando m breeding population with equal numbers ofmale s and females andA F is:
AF =^ ^ =- L !-/•_, IN
39 Effectivepopulation size However, such an idealised population of equal numbers ofmale s and females breeding in separate generations, is aspecia l case,whic h will notb ereadil y encountered in real life. For more general cases,expression s exist torelat e the sizeo f area l population toth e size ofthi s idealised population in such awa y that parameters (like AF)i nth e idealised population are those observed in therea l population {cf. Lynch and Walsh, 1998;Falcone r and Mackay,
1996).Thi s size iscalle d the effectivepopulation size,referre d to asN e. Inbreeding coefficients ofmor e complicated populations canb e calculatedfrom th e former expressions by substituting Ne for N. For arando m breeding population with unequal numbers of males andfemale s therelatio n between actual and effective population sizeis :
N~ 4 N N \ males females J
Fromthi s expression we can see that effective population sizei s largely determined by the sex with the least number ofbreedin g individuals. When there is large inequality in the numbers ofbot h sexes,th e effective population sizewil l be significantly smaller than the actual population size. Looking at theeffectiv e population size over anumbe r of t (separate) generations we arrive at an analogous expression:
' 1 1 1 1 ^ + + +.. .+ — N N M M V e,\ 'ye,2 'Ve,3 e.l J
Onegeneratio n where the effective sizeha sbee n reduced will have arelativel y large downward effect onth e effective population sizeove rgenerations . When we follow a population over 10generations , during 9o f which itha d aneffectiv e size of 100an d one bottleneckgeneration , where the effective sizewa s 25,th e resulting effective size is 77. A population, which has gone through abottleneck , will experience amarke d increase inth e amount ofinbreedin g and asa resul t an increased amount of fixation of alleles (and losso f otherallele s atth esam elocus) .
40 Recapitulating: The state of apopulatio n canb e expressed in terms of effective population size,whic h in turn determines (therat e of) inbreeding andth e amount of fixation occurringi n thepopulation .
Betweenpopulations Between populations, iti s likely thatrando m drift will cause loss of different alleles. Furthermore,rando m drift causes differences in allele frequencies between populations for alleles that areno t lost. This means that the effects ofdrif t within andbetwee n populations are in opposite direction. Within populations genetic diversity will belost . Thegeneti c diversity between populations, however, will increase as aresul t of these effects. This canb eillustrate d by the following expression (Wright, 1969):
(\'F[T) = (\-FISX\-FST) where FIT isth e inbreeding coefficient of an individual relative toth e whole set of populations (Weassum e that different populations can bethough t of as sub-populations ofon e population). Fisi s the inbreeding coefficient of an individual relativet o its sub-populations.
FST isth e inbreeding coefficient of the subpopulation relative toth e entire population. If F[T stays constant, anincreas e ofFi swil l be compensated for by adecreas ei n FST.
Apart from random drift, described above,ther e are three other evolutionary forces that, toa greater or lesser extent, influence genetic differences between populations. These three are: selection, mutation and migration.
3.3.3 Other evolutionary forces {{selection occurs,meanin g that certain,non-neutra l alleles giveth e carrier aselectiv e advantage, divergence between twopopulation s doesno tnecessaril y reflect the extent of isolation, because bothpopulation s might have been bred inth e same direction, favouring the samealleles . Generally, selectively neutral genes arepreferre d asa too l tostud y divergence.
Ingeneral , mutation is aforc e that increases thegeneti c differentiation between populations. Thismean s mutation is aforce , which can create genetic diversity. However, because
41 mutation occurs with alo w frequency, the influence of this factor is only measurable overa largenumbe r of generations.
Migration (individuals moving from onepopulatio n to another) is ahomogenisin g force: It lessens the genetic differences that existbetwee n populations. Migration is awell-studie d phenomenon, with many models proposed toquantif y and clarify its effect inpopulations .
3.4 How aregeneti c distances interpreted?
In classic population genetics theory apopulatio n (orbreed ) mayb e defined in terms ofth e frequencies of alleles segregating in that population. Wewil l therefore concentrate on a class ofgeneti c distances that use allele frequencies asa basi s of information. Genetic distances havemathematica l properties andbiologica l significance.
Mathematically speaking afunctio n must have somepropertie s tob e adistance . First, the distance between apopulatio n Xan ditsel fmus t bezero ,or : d(X,X)=0. Second, the distance between twopopulatio n Xan dY mus t be symmetrical, or d(X,Y)=d(Y,X). If adistanc e satisfies these conditions iti scalle d asemi-metri c distance. If adistanc e alsosatisfie s the triangular inequality, d(X,Y)< [d(X,Z)+d(Y,Z)],i t is called ametri c distance (Katz, 1986.Se e Box 3.3).
Inbiologica l terms,geneti c distances must have otherpropertie s tob e meaningful. In fact genetic diversityresult sfrom a particula r historic development of the population(s) considered. Therefore, the biological interpretation of genetic distances depends largely onth e divergence model used. Asmentione d before, in population genetics there are four forces: 1)Rando m drift, 2) mutation, 3)selectio n and4 )migration . Since themodel s used to study divergence between twopopulation s descendingfrom on e ancestral population were originally designed with species in mind, these models assume independent evolution of eachpopulation . After speciation (themomen t when twopopulation s becometw o distinct species)ther e isb y definition no migration between populations: In themodels ,migratio n isignore d (This assumption is too strong wherebreed s areconcerned . However, ifmigratio n should occur, it will bereflecte d in the distance). Sincew e assume the useo f selectively neutral
42 microsatellites, selection is assumed not to affect changes in allelefrequencies o fthes e markers.I n short, the observed genetic diversity is determined by twoparameters : Random drift and, over long periods oftime ,mutation . Theclassi cmode l ofrando m drift and mutation wasprimaril y designed for the study ofrelationship s between species.Thi s means that the timeperio d under study is long by definition (thousands ofgenerations) . When studying breeds wear e dealing with much shorter timeperiod s (most ofth e divergence in European breeds occurred about 200year s ago) sotha t the evolutionary effect ofmutatio n can arguably be ignored.
3.4.1 Classical mutation-drift model For agoo d understanding what genetic distances mean underth e classical random drift/mutation model, iti snecessar y todescrib e the assumptions generally used.Th e first assumption istha tpopulation s are assumed tob ei n equilibrium with regard torando m drift andmutation . Therefore, after alarg enumbe r ofgeneration s theinbreedin g coefficient F reaches astead y state,give n byth e expression:
F=- l 1+ 4N/1
Where Ni sth epopulatio n size and ui s themutatio n rate,expresse d asth enumbe r of mutationspe r individual per locus per generation. Thismean s that divergence between populations mainly depends on mutation events occurring overa larg enumbe r ofgenerations .
Historically, the first studies dealing with genetic diversity used biochemical markers (like bloodtypes orallozymes) ,tha t have alo w mutation rate.Therefore , these types of studies were constrained topopulations , which hadbee n separatedfrom eac h other for alon g time (i.e.species) .I nthi s caseth e mostwidel y usedmeasur e isNei' s standard genetic distanceD (Nei, 1972).Thi s distance has an expected value linearwit h divergence time.Tree s constructed with this genetic distance were expected to draw areliabl e phylogeny of species. Withmicrosatellit e loci andthei rparticula r mutation model (high mutation rate),D loose s its linearity with time.Goldstei n and others (like Shriver) have sought toremed y this situation. Their goal wast o useth e high mutation rate ofmicrosatellite s to compare very closely related populations with new types ofgeneti cdistance ,name d (ô^)2,Averag e Squared Difference
43 (ASD) and Dsw whichrestor e the linearity with time (Goldstein et al., 1995a;Goldstei n et al., 1995ban d Shnver et al., 1995, resp.). However, Takezaki andNe i (1996) showedb y simulation that the chord distances (Dc) constructed by Cavalli-Sforza (1967) and DA (Nei, 1987),whic h areno t linear with divergence time when using microsatellites givebette r results in terms of topology of the phylogenetic ordistanc e trees (see 3.5.2)draw n than Goldsteins (ô^)2 or Shrivers distance
(Dsw). This mayb e explained by the fact that the former distances have smaller variances than thelatter . Apparently sacrificing linearity ispreferabl e toth e decrease inprecisio n using 2 linear genetic distances (On the other hand, Dan d (ôR) give abette r estimation ofbranc h length). This classic model should beuse d iftim esinc e divergence is large (for instance, between distant breeds or species)whe n mutation has an effect that canno t be ignored.
Box3. 3 Mathematical properties ofgeneti c distances Thenatura l distancebetwee n twovectors ,X an d Y, in ak-dimensiona l space isth e Euclidean distance:
d(X,Y)= ^£(xi-yif
It's easy to showtha t this distance satisfies the threemathematica l properties mentioned inth e text.Therefore , Rogers's (1972)geneti c distance, D^, =j±t,k,-y,Y
which is derived from the Euclidean distance, satisfies theseproperties , despite the factor VF-
k 2 Notetha t the squared Euclidean distance d (X, Y) =^ (x, - yt f satisfies thetw o first
conditions stated in the text but doesn't satisfy thethir d (triangular inequality). Therefore, distances derived from the squared Euclidean distance (Nei's minimum distance, Reynolds distance, etc.,se e Box 3.5) dono t satisfy thetriangula r inequality.Neithe r does Nei's standard genetic distance. For afurthe r discussion onmathematica l properties of genetic distances seeNe i et al.(1983 ) andKat z(1986) .
44 3.4.2 Pure drift model During short times since divergence (for instance between breeds in Europe) the amount of mutations appearing will benegligible . When wewan t to compare closely related populations themai n factor todescrib e geneticvariabilit y isrando m drift.
Underth epur e drift model, contrary toth e former model, theinbreedin g coefficient Fwil l not reach anequilibriu m value,bu t itsdynamic si sgive n byth eexpressio n given earlier:
F, =1-|1- — 2N
Inthi smode l the expectation ofth eusua l genetic distances (likeNei' s standard distance) isa function of (Fi +F 2),th e coefficient ofinbreedin g inpopulatio n 1 and2 ,respectively . This meanstha t this type ofgeneti cdistanc e actuallymeasure s inbreeding. For example,whe nw e look atNei' s minimum distance (Nei 1973),th e expectation is:
2 E(Dm)= E\^-y,) =*to +Fji-5> ,
wherepo ii sth e frequency ofth ei-t h allele in the founder population. Themos t important aspecto fthi s distance isth eexpressio n (F1+F2).Th epreferre d distancethen , shouldb ea distance,whic h has anexpecte d value equal to (F1+F2),withou t being clouded by 'left-over' terms. Reynolds (1983) introduced ameasur e ofgeneti c distance which isNei' s minimum distancenormalise d by an estimation of heterozygosity in the founder population (1-Z;[xiyi]), effectively removing this part ofth e former equation. The expected value of Reynolds distance istherefor e equal to (Fi+F2)/2 (For moreinformatio n about expression of genetic distances see Box 3.5).
Acautionar y remark: Under the assumption of apur erando m drift model, distance estimates dono t reflect the exact phylogeny ofth epopulation s under study (the distance isno w influenced by t andpopulatio n size,rathe r than t only).However , sinceth emai n interest will befo r conservation value ofbreed srathe r than the exact phylogeny (which canno tb e known
45 in any case), thistyp e of distance should be used for relatively closely related populations, likebreed s in Europe.
Thusfar, ametho d was outlined that measures directlyneutra l geneticvariation . Implicitly is assumed that conservation ofneutra l diversity alsoconserve snon-neutra l variation, because ultimately genetic distances useth e notion of alleles identical bydescent and therefore measure kinship. Inprinciple , kinship is aparamete r valid for the entire genome. Therefore the assumption of conservation by association ofnon-neutra l variation through conservation ofneutra l variation seemsreasonable .Thi s implies aver y general approach towards conservation. All ofgeneti cvariability , known andunknow n is assessed and conserved.
Box3. 4 FSTa sa geneti c distance Wright's FST statistics (Wright, 1969),th e inbreeding within asubpopulatio n relative toth e wholepopulation , is apopula r measure ofgeneti cdiversit y in animal breeding. Inthi s approach breeds are considered tob e subpopulations ofa larg epopulatio n comprising all breeds under study. Fca n be expressed in terms ofheterozygosit y through (Nagylaki, 1998):
'*j wherep x denotes the frequency for the x-th allele of alocu s inth epopulatio n under study.
Iffinite subpopulation s areisolate dfrom eac h other, eachwil l separately experience inbreeding,wit hfixation o f alleles. Which alleles are fixated will differ between populations. Therefore progressing inbreeding means increasing diversity between breeds.Calculatin g FST for ase t ofpopulation s can be done through:
H =\-F = ^- 11 ST L L ST jj il j where theba r aboveH$ denote s that this isth e average expected heterozygosity inth e subpopulations. HTdenote s the expected heterozygosity in thetota l population calculated from frequencies inth e total population (Nagylaki, 1998).
There are alternative ways to calculate FST-Wei r andCockerha m (1984) andRobertso n and Hill (1984)giv e different estimators of FST- The estimator ofRobertso n and Hill gives extra weight torar e alleles for conservational purposes. However, the variance onth e estimator is greater andbot h estimators agree onlywhe n all alleles have equal frequencies).
46 Nagylaki argues that FSTwil l onlyb e an appropriate measure of divergence between populations ifth egeneti c diversity is low tobegi n with. For example: Ifw ehav en
subpopulations of equal size,whic h dono t share alleles,th e expression for FSTbecomes : _(/,-!)(!-/ƒ,) ST ~ n-(l-Hs)
Except when thepopulation s are fully inbred (Hs= 0 ) FSTwil l alwaysb e smaller than 1,eve n though thepopulation s are fully differentiated. Moreover, if wehav e Kpopulation s fixed for
alocu s with L( Classical genetic distances canno t account for migration explicitly (seetext) . Itma yb eo f interest togai n some insight intothi s aspect ofpopulatio n evolution. FST canb euse d for the calculation ofmigratio n ratebetwee n populations. Under the assumption of equilibrium between genetic drift andmigration , the inbreeding coefficient, when in steady state,take s afor m very similar toth einbreedin g coefficient in case of equilibrium between drift andmutation . Theformul a is: Feq =—L_ l+4tfem where m isth emigratio n rate. Iti seviden t that an increase ofmigratio n rate causes adecreas e ofinbreedin g coefficient. These twofactors , mutation andmigration , maintain genetic diversity within natural populations. Buti n terms of genetic diversity between populations the migration allowsa n exchange ofgenes :gene flow. Thi s gene flow tends to homogenise thegeneti c constitution of the seto fpopulations .Then ,migratio n rate causes adecreas e inth e observed genetic diversity between population. Therefore genetic distance values are smaller than those in the case,wher ether e isn omigration . The expression given above alsopermit s to estimate the parameter, Nem (effective sizemultiplie d bymigratio n rate).Generall y programs which give an estimation of FSTals o give anestimatio n ofN em. 47 Box3. 5 Some distance formulae Fornotatio n convenience x;an d y;ar e frequencies ofth ei * allelerespectivel y drawn in population Xan d Y. For simplification reasons, distance formulae are given for one locus.T oexten d those expressions for several loci,on eha st o sum overloc i and divide byth enumbe r ofloc i where summations over alleles appear in the expressions. Neistandard Genetic distance (D): ~Ex>y> £> = -ln 2>'5>? Goldstein's distances: where \xx (=S;ixi)an d uY (=£;iyi)ar e average allelic sizes in each population. AverageSquared Distance (ASD): ASD^J-ifx^. where i andi ' areth e sizes ofth e alleles of amicrosatellit e locus. Shrivers distance (D$w): Dsw=Wxy-{Wx+Wy)l2 where W x x W and W i x=Y, \i- '] i r ' r=T}'- 'Wr XY=YJ\ ~ Aw? i*V I'#I' irt' The chorddistance ofCavalli-Sforza (D,): Dc=(2/^)l2h-X^ Nei'sdistance (DA): Nei'sminimum distance (D„): Reynolds distance (DR^OU,): 2 D _Xk-y) Reynolds 2 i-Lv, 48 InTabl e 3.1 advice is given onwhic h genetic distance shouldb epreferre d in different situations. Table3. 1 Advice onth e choice of appropriate genetic distance measure. Divergence time (generations) Short Intermediate Long (breeds within (breeds world- (species) Europe) wide) (Mutation and drift) (Random drift) (Mutation and drift) Dc + topology + topology DA + topology + topology D + branch length + branch length (on)2 + branch length + branch length Dm +/- DReynol d 3.5 What areth e practical considerations? Inthi s section wewil l discuss somepractica l implications of thetheor y outlined above. 3.5.1 Sampling Since estimating genetic distancei s astatistica l method, the sampling process iso f importance. Sampling occurs hierarchically, in thatfirst individual s aresampled . Then, loci aresample d within individuals.Befor e hand,th e seto floc i sampled shouldb edecide d on, andthi s set shouldb e equal for allpopulation s under investigation. Theindividual s sampled should berandoml y drawn,t oreflec t the actual composition ofth e population. Generally, N=25 sampled animals aretake n tob e aminimu m requirement (FAO, 1998).Wit htha t 2N=50 drawings of alleles perlocu s areperformed , which should givea reasonably reliable estimate of allele frequencies. Inth e case ofver y small populations it mightb eworthwhil e to sample the whole population. Intha t wayth e true gene frequencies areknown . Often wewil l have different sample sizesbetwee n populations. It ispossibl e to correct estimates ofgeneti c distance for unequal sample sizes (Nei, 1987). 49 The sampled loci should preferably be unlinked to oneanother . Here,unlinke d ismean t inth e statistical sense,meanin g that if loci are located on the same chromosome, they should preferably be at least 50 cM apart. Using linked loci introduces acovarianc e between loci, which enlarges the variance on the estimate ofth egeneti c distance. However, moreloc i always addprecisio n toth e estimations of distances. As arul e ofthum b one should choose microsatellites that are as evenly spaced along the genome aspossible . Furthermore, loci differ in theirinformatio n content. Loci used ingeneti c distancing should beinformative , meaning they should display sufficient polymorphism. As stated before, genetic distances are dependent oninbreeding . Inbreeding means individuals will posses two copies ofa n allele descending from the same ancestor: the alleles are identicalby descent. However, alleles can alsob e indistinguishable from one anotherwithou t descendingfrom th e sameindividual , inwhic h case alleles aresai d tob ealike in state.Fo r acorrec t estimation of genetic distances it isimportan t that theprobabilit y oftw o alleles being alike in statei s minimised. This isachieve d by using loci with asmuc hpolymorphis m aspossible . In the set ofmicrosatellit e markerspropose d by FAO,th erul e ofthum bwa s adopted that loci should have atleas t 4 different alleles. One ofth eprerequisite s ofmarker s used toestimat e genetic distance is they shouldhav e simple,mendelia n inheritance (Bretting and Widerlechner, 1995).Therefor e the use ofse x linked loci should be avoided oruse d with caution. 3.5.2 Models and reality Inpractic e there isexchang e ofgeneti cmateria l between breeds.Thi s can happen through migration and crossing ofbreeds .Th emodels ,whic h assumeisolatio n and independent evolution ofpopulation s after divergence, areb y definition valid for species. Inth e caseo f breeds,however , the truerepresentatio n ofrelationship s between breeds will lookmor e likea network than like asimpl ebinar y tree.Moreover , inth e case of hybridbreeds ,wher e two populations were combined to give the hybrid, the development is contrary towha ti s assumed inth emodels ,wher e onepopulatio n acts asa founde r of twodaughte r populations. However, these aspects which diminish diversity between breeds will result in a diminished distance estimate. Closely related breeds,irrespectiv e ofth enatur e ofthei rrelation , will be recognised as such. For conservation purposes it isno tnecessar y topa y extra attention to 50 Box3. 6 Using specific regions ofth e genome Itmigh t bepreferre d toconcentrat e onregion s ofth egenom e associated with certain traits deemed important (now or in the future). The Major Histocompatibility Complex for instance, plays animportan t rolei n health and might therefore receive extra attention. Specialised distance estimates based on loci in thisregio n could be employed. Caution should be taken, however, since this type of distance concentrates on arelativel y small, closely linkedgrou p of loci,whic h causes the distancet o losecorrelatio n withth e remaining genetic diversity. Amajo r consideration in usinggeneti c distances isth e alleged objectivity inrankin g breeds for importance to conservation. Wewoul d liket o stress that this is onlytru ei fon e considers total genetic diversity. Choices of certain regions ofth egenom e over others are by definition based on subjective considerations. Fora furthe r discussion onweighin g this typeo f subjective considerations canb e found in chapter4 . aspects likemigratio n separately. However, if onei s interested inmigration , FSTca n beuse d tocalculat e therat e ofmigratio n between populations. 3.5.3 Distance trees Distance treesar egraphica l representations ormapping s ofth e distance matrix {i.e. the matrix with distances between populations). Under anumbe r of conditions, described in the previous section, thisrepresentatio n can be taken asth ephylogeny . However, under European circumstances thetree s areno t phylogenetic, since differences in effective population size and migration between breedshav e adistortiv e effect. There aredifferen t methods of drawing distance matrix trees.Ne i et al. (1983) discuss and compare the different methods.Th emos t widely known methods areNeighbour-Joinin g(NJ ) and UPGMA (Takezaki andNei , 1996),whic h generally give goodresults .N Ji s superior when different rates ofevolutio n havet ob e assumed. Evolution ratei s among others governed by the effective population size. Since itca n be expected that this will differ from onepopulatio n toth enext , this should beaccounte d for, NJ isth epreferre d technique. Bootstrapping is astatistica l technique ofresamplin g data onth e loci (Weir, 1990;Se eBo x 3.7).Thi s gives thepossibilit y to drawmultipl e trees andestimat ereliabilitie s for the different 51 nodes in thetre e and aleve l ofconfidenc e ofthat tree. Evidently, properties ofth e sampling methods used will have an effect on the confidence levels of thenodes . Aremark : Bootstrapping uses the available data in an efficient manner. Itca n not improveo n thedata . The quality of thebootstra p is therefore limited toth e quality of thedat a used in the bootstrap. Trees canb e drawn with or without aroo tbranch .However , since trees drawn for breedso f livestock areno t phylogenetic, unrooted trees shouldb epreferred . Use ofth eN J method is advisable.Apar tfrom th ereaso n stated above,N Jals ogive shighe rbootstra p values inmos t cases. Box3. 7 Bootstrapping Bootstrapping is atechniqu e togai n information about the distribution ofparameter s ina limited dataset. Itdoe sthi s by creating 'new' observations, thebootstraps . When adatase t consists of« observations, abootstra p is asampl e ofn rando m drawings, with replacement, from the original data. All observations inth eorigina l dataset havea nequa l chanceo fbein g drawn.Th evalu e of thene w bootstrap is the average ofth e sampled parameter (Weir, 1990; Tivange?a/., 1994). Typically, this process isrepeate d alarg enumbe r oftime s (> 1000),t o create alarg enumbe r of 'new'data .Thes e canb euse dt o estimate averages andstandar d deviations of an estimator calculated with the data in question. Inth e case of treeconstruction , bootstrapping canb edon e for allelefrequency dat ao f multiple loci.Bootstra p sampling is usually doneove r loci.Th efrequencies o fth e loci in the bootstrap sample arethe n used to calculate ane w distancematri x after which thismatri x is usedt o construct atree .Th etopolog y (or layout) ofth ebootstra p tree is then evaluated for thenodes ,o rcluster s (seeBo x 3.8) that appear in it.Th ebootstra p value of aparticula r node isth efraction o ftime sthi snod e (or cluster)i sfoun d inwhol e seto fth e 'bootstrapped' trees. 52 Box3. 8 Constructing trees Inth e following wegiv e an example of the construction of atre e using UPGMA.Althoug h NJo n thewhol e givesbette r results, UPGMA illustrates this aspect of assessing diversity more clearly. Suppose wehav e four breeds A,B ,C an d D. The distances between them aregive n below. BCD A .400 .300 .500 B .200 .100 C .300 Westar t with thepai r ofbreed s that is closest toon e another. The closestpai r is (B, D). Therefore wenex t calculate the distances between the cluster (B,D) andA an d Ca sth e average ofth e distances ofB andD .Example :(B ,D) ,A = '/2(.400+ .500)= .450 (B,D) C A .450 .300 (B,D) .250 Again wefin d the smallest distance (between (B,D )an d C)an drecalculat e the distance between this cluster andA (givin g (B,D , C),A = .375).Th eresultin g unrooted treei s drawnbelow .Th ebranche s aredraw n in such awa yth e lengths ofth ebranche s between twobreed s sumu pt oth e distancegive n above. D 53 3.5.4 How dow echoos e breeds using genetic distances? Genetic distances and the tree construction methods described above give insight intoth e genetic uniqueness ofbreed s under investigation. Using another tree construction method, based on adiversit y function suggested by Weitzman (1992), it ispossibl e to assessth e genetic diversity which will be lost when somebreed s are excludedfrom th e initial tree. Thaon d'Arnoldi etal . (1998) givea nexampl e ofthi s using the Weitzman function of diversity toconstruc t a 'diversity tree'.Usin g onlyth e distancesbetwee n populations, Thaon d'Arnoldi et al.us ebranc h length asa n estimation of genetic diversity. However, Thaon d'Arnoldi et al.sugges t including somemeasur e ofwithi n breed diversity (Ne, expected survival time)t o have acleare r indication ofho wmuc h diversity canb epreserve d when certainbreed s are excluded. An alternativet oexclusio n mightb epoolin g ofclosel yrelate d breeds.Thao n d'Arnoldi etal . suggest thispreserve s diversity more efficiently, although it would mean disappearance of twobreed s into ane w synthetic. Objections tothi s suggestion might be formulated, intha t this could mean loss of adaptability traits and other uniquetraits , through the loss ofbree d specific combinations ofgenotypes . Furthermore, if abree d possesses ahig h cultural value (see chapter 4),it slos s will bedeeme d unacceptable. Another way ofmaximisin g genetic diversity is calculating the optimal relative contributions ofeac hbree d to agenom ebank . Thismetho d mightlea dt ocontribution s smaller than required for breed survival. Constraints ast o theminima l population size ornumbe r of contributions perbree d should therefore be included. Alternatively, onecoul d consider pooling related breeds to lift the contribution over the critical level. But here alsoth e objections stated above apply. 54 References Bretting P.K. and M.P. Widrlechner, 1995.Geneti cmarker s andhorticultura l germplasm management. HortScience, 30(7): 1349-1356. Burstin J. and A. Charcosset, 1997.Relationshi p between phenotypic andmarke r distances: theoretical and experimental investigations. Heredity, 79: 477-483. Cavalli-Sforza L.L. andA.W.F . Edwards, 1967.Phylogeneti c analysis: Models and estimation procedures. Evolution, 21: 550-570. Crossa J., CM. Hernandez, P.Bretting , S.A. Eberhart, S.Taba , 1993.Statistica l genetic considerations for maintaining germplas m collections. Theoretical and Applied Genetics,86 : 673-678. Estoup A., L.Garnery , M.Soligna c andJ.M . Cornuet, 1995.Microsatellite s variation in honey bee (Apis mellifera L)populations : hierarchical genetic structure andtes t of infinite allele and stepwisemutatio n models.Genetic s 140: 679-95. Falconer D.S.an dT.F.C . Mackay, 1996.Introductio n into quantitative genetics. Longman House,Harlow , Essex,464p . FAO, 1998. Secondary Guidelines for Development ofNationa l Farm Animal Genetic Resources Management Plans: Management of Small Populations at Risk. FAO,Rome , Italy. 215p. Goldstein D.B.,A.R . Linares,L.L .Cavalli-Sforz a and M.W. Feldman, 1995a.A n evaluation ofgeneti cdistance s for usewit h microsatellites loci.Genetic s 139:463-471 . Goldstein D.B.,A.R . Linares, L.L.Cavalli-Sforz a and M.W. Feldman, 1995b.Geneti c absolute dating on microsatellites andth e origin ofmodern s humans.Proceeding s ofth e National Academy of Science 92:6723-6727 . 55 Henson E.L., 1992.In situ conservation of livestock andpoultry . FAOAnima l Production andHealt h Paper 99,FAO/UNEP , 112p. HintumT.J.L . van, 1994.Drownin g in the genepool: Managing genetic diversity in genebank collections. Doctoral thesis, Swedish University ofAgricultura l Sciences, Department of Plant Breeding Research, Svalöv, Sweden, 11 lp. Katz M., 1986. Etude despropriété s decertain s indices dedistanc e génétique etd e leurs estimateurs. Doctoral thesis,Universit é Paris VII,Paris ,France . Lynch M. and B.Walsh , 1998.Genetic s andAnalysi s of Quantitative Traits. Sinauer Associates, Inc, Sunderland, Massachusetts, USA,980p . Malecot G., 1948.Le s mathématiques del'hérédité . Masson, Paris,60p . Malecot G., 1969.Th emathematic s of heredity.Freeman , SanFrancisco , 86p. Moazami-Goudarzy K., D.Laloe ,J.P . Fouret and F.Grosclaude , 1997.Analysi s of geneticrelationship s between 10cattl ebreed s with 17 microsatellites. Animal Genetics28 : 338-345. Morrison D.F., 1967.Multivariat e statistical methods. McGraw-Hill, New York, USA,338p . Nagylaki T., 1998. Fixation indices in subdivided populations. Genetics 148: 1325-1332. Nei M., 1972.Geneti c distance between populations. American Naturalist 106:283-292 . Nei M., 1973.Th etheor y andestimatio n ofgeneti c distance. Genetic Structure of populations,N.E .Morto n University Press of Hawaii. NeiM. ,Tajim a F.,Taten o Y., 1983.Accurac y ofestimate d phylogenetic trees from molecular data II,Gen e frequency data.Journa l of Molecular Evolution 19:153-170 . 56 Nei M., 1987. Molecular Evolutionary Genetics. Columbia University Press,Ne w York, 51 lp. Reynolds J., 1983. Estimation ofth e coancestry coefficient basis for a short-term genetic distance. Genetics 105: 767-779. Robertson A. and Hill W.G., 1984.Deviatio n from Hardy-Weinbergproportions : Sampling variance andus ei n estimation ofinbreedin g coefficients. Genetics 107:703-718 . RogersJ. , 1972.Measur e ofgeneti c similarities andgeneti c distances. Studies in geneticVII , University of TexasPub . Shriver M.D.,J . Li, E.Boerwinkel , R. Deka, R.E.Ferrel l and R. Chakraborty, 1995. A novel measure ofgeneti c distance for highly polymorphic tandem repeat loci. Molecular Biological Evolution 12:914-920 . Smith C, 1984.Geneti c aspects of conservation in farm livestock. Livestock Production Sciences 11:p37-48 . Takezaki N.an d M.Nei , 1996.Geneti c distances andreconstructio n ofphylogeneti c trees from microsatellite DNA. Genetics 144: 389-399. Thaon d'Arnoldi C, J-L Foulley, L.Ollivier , 1998.A n overview of theWeitzma n approach todiversity . Genetics, Selection, Evolution 30: 149-161. Tivang J. G., J. Nienhuis and O.S. Smith, 1994.Estimatio n of sampling variance of molecular data using the bootstrap procedure. Theoretical andApplie d Genetics 89:259-264 . Weir B.S., 1990.Geneti c data analysis:method s for discrete population genetic data. Sinauer Associates, Inc.Publishers , Sunderland Massachusetts,377p . Weir B.S.an d C.C.Cockerham , 1984.Estimatin g Fstatisti s for the analysis of population structure. Evolution 38: 1358-1370. 57 Weitzman M.L., 1992.O n diversity. Quarterly Journal of Economics,363-405 . Wright S., 1969.Evolutio n andth e Genetics of Populations, Vol.2 ,Th eTheor y of Gene Frequencies, University of Chigago, Chigago,USA . 58 Chapter 4. Selecting breeds for conservation J. Ruane Department ofAnima l Science,Agricultura l University ofNorway , P.O. Box 5025,N-1432 , Norway • Backgroundto criteria for selecting breedsfor conservation • Degree ofendangertnent • Adaptationto a specific environment • Traits ofeconomic importance • Unique traits • Culturalor historical value • Genetic uniqueness ofa breed • Speciesa breed belongs to • Howcan we weight the different criteria? 4.1 Background tocriteri a for selectingbreed s for conservation Resources, both in terms of finances andmanpower , are scarce in the area ofbree d conservation whileth enee d is great. On aworld-wid e basis,i ti s estimated that about one third ofmamma l andpoultr y breeds are endangered, i.e. with < 1000breedin g females or< 2 0 breeding males (Scherf, 1995).I n Europe,th e combination ofth e development of herdbooks andth e use of specifically defined breed standards ledt o aspecia l period of subdivision of many domestic animal populations into largenumber s ofbreeds ,whic h lastedfrom th e endo f the 18thcentur y toth efirst worl dwar . Theproportio n ofbreed s lost this century in Europei s however, highest of all continents (Hall andRuane , 1993) and over40 %ar e currently estimated tob e endangered (Scherf, 1995). In Europe,som e countries have developed national strategies for management of animal geneticresource s (Martyniuk and Planchenault, 1998).I n addition, organisations such asth e European Union (EU)an d theNordi c Council of Ministers have already taken responsibility 59 for the development of funding programmes for co-ordinated activities. Apart from documentation andpromotio n of animal genetic resources, someo fth eavailabl e funding couldb e used for theestablishmen t or support of conservation programmes directed towards specific breeds.Thi s could include in situ or exsitu programme s for endangeredbreeds ; supporting farmers willing to uselow-input , low-output breeds in today's economic climate or supporting genetic improvement programmes andmanagin g inbreeding for breeds not currently endangered, but which maybecom e soi nth enea r future. The question addressed here iswhic h ones should be selected ?I n asituatio n with several hundred endangeredbreeds , this question is verypertinent , asbreed s given support today aremor e likely to survive into the future while thoseno t chosen aremor e likely tobecom e extinct. Inthi s chapter seven criteria (4.2-4.8),whic h might beuse d inth e selection of breeds for conservation will bepresente d andth e weighting ofthes e seven criteria will thenb e discussed. 4.2 Degreeo f endangerment From apurel y conservationist point ofvie w andbecaus e ofth e large uncertainty about the production environment ofth e future, themajo r goal mayb e tomaintai n andconserv e as manybreed s aspossible . In addition, thenumbe r of endangered breeds is currently extremely high, soactio n onthi sfront i s especially important. Notetha t genetic variation isbes t conserved onth e species level by theretentio n of separatepur ebreedin g populations rather than the useo flarg epopulation s without reference tobree d (Hall andBradley , 1995).Thi si s primarily because thepowe r ofmarke t forces canpus h largepopulation s to select for aver y narrow breeding goal whilereproductiv e techniques (which maybecom e far more efficient in the future) alsomak e itpossibl e for individual animals or families tohav e amajo r influence onth e geneticmake-u p ofth epopulation . Thenarro w effective population sizeo fth e global Holstein dairy cattlepopulatio n (e.g. Wickham andBanos , 1998)demonstrate s that the useo f a single,larg epopulatio n isno tnecessaril y agoo dwa y of conserving genetic variation.Th e breed should thusb eth e key unit in conservation of animal geneticresources . Note that the degree of endangerment of abree d doesno t depend only onit s current population size.I t also depends on arang e of factors such asth erat e of change of population 60 size,th edegre e orris k of crossing with other breeds, the degree of organisation ofth e farmers and the distribution pattern of animals over herds (EAAP Working Group on Animal Genetic Resources, 1998). Inth e situation wherew e wish toconserv e asman y breeds aspossible , the degreeo f endangerment isthu s ake y criterion. Based on demographic andpopulatio n statistics, time to extinction ortim e to apre-determine d critical population size can beestimate d for each breed (EAAP Working Group on Animal Genetic Resources, 1998). Breeds with large population sizes andi nn o obvious danger would obviouslyno tb eprioritised . Atth e other extreme, breeds that arealmos t extinct might notnecessaril y be selected for conservation becauseo f the fact that thepopulatio n size isto o low and, in addition, large investments mightb e required torescu e them andbrin g thepopulatio n sizebac k upt o safe levels.Resource s might bebette r used topreven t otherbreed s coming to asimila r end. 4.3 Adaptation to aspecifi c environment Through natural or artificial selection, breeds can genetically become adapted to specific environments andman y such examples areknow n (see Box4.1) . Within continents or large countries,th enumbe r ofbreed s (expressed permillio n people) seems tob ehighes t in remote andperiphera l countries or states,whic h may indicate that adaptation to geographically isolated areas hasbee n animportan t factor in breeddevelopmen t (Hall and Ruane, 1993). Box 4.1 Adaptation • The Kuri cattle's adaptation to the aquatic environment aroundth e islands and shoreso f the Lake Chad Basin, and their inability tothriv e in other environments, is one ofth e clearest examples of adaptation to aspecifi c environment (Tawah et al., 1997). • Thefera l Soay sheep isadapte d toth e very tough conditions ofth e St. Kildaarchipelago , off the coast of Scotland, andi s thought tohav e existed there since Neolithic times (Hall and Bradley, 1995). Although difficult toexpres s in purely economical terms, adaptation ofbreed st o specific environments is veryimportant . Currently, indicators andcriteri a for the adaptation of abree d to its environment arebein g developed by FAO.Ther e is an ever-increasing awareness ofth e importance of sustainable agricultural production systems,an dwell-adapte d animals are central tothes eschemes . Thevalu e of adaptation is acknowledged by the fact that when conserving vulnerable habitats asnationa l or stateparks , domestic breeds traditionally associated with the environment arei n some cases alsoinclude d in theprogramm e (Henson, 1990).Breed s with adaptation toa specific environment should thusb eprioritise d for conservation, especially ifth e environment itself iso fconservatio n interest. 4.4 Traits ofeconomi c importance Breeds would be of special interest for conservation purposes ifthe yhad : a)on e orsevera l traits of economic importance today (e.g.hig h fertility, efficient feed conversion, high qualityproducts , diseaseresistance ) and/or b)on e or several traits that will be ofeconomi c importance in the future. Whileth e first part isquit e clear and couldb edocumented , the secondpar ti shar dt o quantify asi t is obviously difficult to envisagewha t theproductio n environment mayb e like in 20,5 0 or,indeed , 100year stime . However, we canpredic t that inth e world as awhol e therewil l beincrease d demand for animal products asa resul t ofincrease d population growth and urbanisation. In developed countries the emphasis islikel y tob eincreasingl y on food quality and food production under less-intensivecondition s (Upton, 1997),whic h could favour breeds of smaller population size that areles s competitive today. Inaddition , wekno w that theworld' s environment is changing, with increasing C02 concentrations, increasing global temperatures and declining groundwate r levels (e.g.Brown , 1998).Ou r societiesma yals ob eradicall y different inth e future asa resul t of changes in energy supplies, asi ti spredicte d that apermanen t declinei n oil production isvirtuall y certain tobegi n within thenex t 20year s (Hatfield, 1997). Factors such asthes e will affect the production environment in the future, although it ishar d tosa y nowwhic h breeds might be favoured by such changes.Th e onethin g that is sure,i s that the future is uncertain. Breeds with valuable traits of economic importance in today's production environment are obviously important. However, iti sworthwhil erememberin g that traits of economic importance whichprovid e ashort-ter m profit today mayb e oflittl evalu ei n the future duet o changing production circumstances andmarke trequirements . Changes in theEuropea n dairy 62 cattle system over the last 30 years show this quite well where dual-purpose goals (meat and milk)tha t originally were favoured, were abandoned in favour ofgoal s focusing only onmil k production while the emphasis latermove d tomil k quality and secondary traits (Cunningham, 1992).Politica l decisions, such asth e possibleremova l of subsidies inth e EU, could also haverapi d anddramati c consequences onth e economic values of certain traits. When considering this criterion, iti s therefore important to assess whether thetrait s of current economic importance are likely toremai n soi n the future. Regarding traits of future importance, iti s almost impossible to consider which breeds might be favoured for these hypothetical traits.However , this doesno t mean that they areno t important. Thebes t wayt o account for this uncertainty ist o ensure that asman y existingbreed s aspossibl e survive into the future. 4.5 Uniquetrait s Somebreed s couldb eprioritise d for conservation efforts because theyhav e special behavioural, physiological orphenotypi c traits,whic h distinguish them from all others ofth e samespecies .Thes e mayb e duet o single genes of large importance orpolygeni c effects. Someexample s aregive n in Box4.2 . Apart from their curiosity value orthei rpotentia l economic or adaptive significance, the traits may alsob eo f scientific interest, allowing ust oincreas e our scientific knowledge in avariet y ofdifferen t areas, such asth e genetic mechanisms behind human diseases or arang e of physiological and adaptive characters. Aswit h adaptation andtrait s of future economic importance, it is difficult to quantify thebenefit s ofthi s scientific knowledge but again, this doesno t mean that they arenegligible . 4.6 Cultural or historical value Inmuc hth e samewa y aspainting s orbuildings ,breed s canb e appreciated for their cultural or historical merits and can be of valueregionall y ornationally . Aswit h works of art,th e cultural importance of abree d liesi n the eye/mind ofth ebeholder . The cultural value of particularbreed s for societies in developing countries hasbee n discussed recently byKöhler - 63 Rollefson (1997). In European countries, farming was once thetraditiona l working activity butnow , asi s typical for developed countries, the proportion ofth epopulatio n employed in agriculture is low. In some European countries then, the cultural orhistorica l values ofth e breeds mayb e considerable asthe yrepresen t astron g link toth e past. The cultural/historical value of abree d is another criterion that ishar d to quantify but would obviously depend on how long thebree d had existed in theregion , thehistorica l importance of itsproducts ,whethe r itwa s strongly linked with aparticula r tribe orpeopl e andho w strongly the inhabitants ofth eregio n identified with thebreed . Although itma y generate incomefrom touris m through its association with agive n region (Gandini andGiacomelli , 1997),it svalu e is generally abstract rather than purely economical. Provided that financial resources are available most countries are, in general, willing to support aspects ofthei r Box 4.2 Examples ofuniqu e traits • TheMeisha n pigbree dfrom Chin a isextremel y fertile andha sthu sbee n imported to Europe and North America for use in commercial stocks,a swel l as for study in awid e range ofresearc h projects to understand the genetic basis of fertility, andindeed , of other traits (e.g.Jans s etal. , 1997). • Study ofth euniqu emusculatur e ofth eBelgia n Blue cattlebree d has ledt o an increased understanding ofth e geneticmechanism s behind muscular development in mammals (Grobete t al, 1997). • TheNort h Ronaldsay sheep breed isuniqu ei n that it feeds only on seaweed for largepart s of theyea r and, in addition, hasver y efficient copper absorption andhig h salt tolerance (Ponzoni, 1997). • Therar e Gulf CoastNativ e sheepha s high natural resistance tointerna l parasites,a characteristic which ledt o flocks ofth ebree d being established atth e Universities of Florida and Louisiana for research purposes (Henson, 1990). • Many otherbreed s have documented resistance to specific diseases, such asth eN'dam a cattle which survive in areas infested by thetsets e fly, duet o their highresistanc e to trypanosomiasis (the cattle equivalent to sleeping sickness,transmitte d byth e fly) and are consequently atth e centre of alarg eresearc h programme (FAO, 1992). culture and history. Inprioritisin g breeds for conservation, therelativ e weighting ofthi s criterion istherefor e likelyt ob ehighe r for developed than developing countries. 64 4.7 Genetic uniqueness of abree d Mankind has domesticated only afe w species.O f these, only ahandfu l again are ofprimar y significance for food production in global terms.Almos t all ofth emil kproduce d inth e world comes from two species (cattle andbuffaloes ) while 90%o fmea t comes from pigs,poultr y and cattle (FAO, 1996).Geneti cvariatio n within domesticated species is therefore especially important because ofth erelianc e on asmal l number of species.Breed s can accumulate significant genetic differences over timethroug h theprocesse s of genetic isolation, genetic drift, selection andmutation . Sinceman y ofth ebreed s in developed countries are only ofrecen t origin (often within the last 200years) ,thei r genetichistorie s (how theywer e established andi fthe ywer e later crossed with animals of otherbreeds ) are often well described in the literature.Thi s information can be used to identify breeds that arelikel y tob egeneticall y divergent from others ofth e samespecies .Fo r example, thecattl e andgoa t populations in Iceland areknow n tohav e arrived withth efirst settler s in the 9th-10th centuries andt ohav ebee n effectively closed ever since (e.g. Sigurdsson 1995).Wher e documentation ofgeneti c history is limited ornon-existent , genetic uniqueness ofbreed s can be estimated using genetic distance studies based onneutra l genetic loci, such as allozymes ormicrosatellite s (see chapter 3fo r more details). Genetic uniqueness (taxonomiedistinctiveness ) is considered important when prioritising species in conservation biology, andi tha s been argued that it should alsob e usedwhe n prioritising domesticbreed s within species for conservation purposes (e.g. Hall and Bradley, 1995).Geneti c uniqueness is ofvalu ewhe n prioritising breeds becausethos e that are genetically divergent from each other aremor e likely toposses s different alleles and gene combinations affecting arang e oftrait s that mayb eimportan t for adaptation, for future production environments and for scientific purposes. Conservation ofbreed stha t are genetically different istherefor e agoo d way of ensuring that these species will have sufficient geneticvariatio n toadap t andt orespon d to selection in future generations. Thelimitation s of usingneutra l loci to estimate genetic uniqueness for traits that havebee n undernatura l or artificial selection arediscusse db yPonzon i (1997). 65 4.8 Species abree d belongst o Only afe w of the estimated 30-50millio n species of theanima l kingdom havebee n domesticated. Almost all aremammals , predominantly large andherbivorous , while the remainder areprimaril y birdstogethe r with acoupl eo finsec t species (Diamond, 1997).Th e different domesticated species carry out amultitud e ofpurposes ,providin g mankind not only with food (meat,mil k and eggs)bu t alsofibre, leather , fuel, fertiliser, transport and draught power. Some species are of greater importance than others.Cattl e supply 87an d2 5 %o fth e world's supply ofmil k andmea trespectively , buffaloes areresponsibl e for 10%o f allmil k produced while pigs andpoultr y cover4 0 and2 5% o f global meatproductio n (FAO, 1996). Whilemos t ofth e6 previou s criteria might be used for prioritising breeds within species, some effort atprioritisin g particular species is alsonecessar y since decisions onwhic h breeds to conserve arenormall y made atth e country or across-country (e.g.EU ) level andno t merely within species.Assignin g aspecifi c amount ofresource s to each species would entail thata greater number of conservation programmes couldb e established or supported for smaller, less-costly species,suc h aspoultr y orrabbit s compared with larger mammals such ascattl eo r horses.Fo r example, Ollivier and Renard (1995) showed that setting up ageneban k wouldb e much cheaper forrabbi t than cattle,shee p orgoa t breeds.O nth e other hand, selectinga n equal number ofbreed spe r species for conservation would mean that themajorit y of resources would gotoward s thelarger , more-costly species. When FAOchos e 12 populations for amajo r indigenous breed conservation programme (Cunningham, 1992),thes e included 5cattl e and 3shee p breeds with only 1 population each from goats,buffaloes , pigs and camelids andnon e from poultry. This involved prioritising cattle andshee p atth e expense ofth eothe r species,a viewpoin t thatmigh tno t beshare db y all.Thus ,whe n prioritising breeds itwil l always benecessar y tous e some subjective judgementregardin gth eimportanc e ofvariou sspecies . When prioritising species,on ethin g that mustb e considered isth epresen t and estimated future value ofeac h species for the country orregion . Conservation efforts in other countries should alsob e considered andpreferabl y decisions onwha t to conserve shouldb e madei n co operation on aregiona l (e.g.EU )o rgloba l level.Thi s ideally should lead to conservation efforts being concentrated not only onrelate dbreed s of onespecie s buto nbreed s from many 66 species.Anothe r point worth considering iswhethe r species,no t important for food production, such ascat s and dogs should beincluded , because they can be of interest for cultural/historical reasons or for the fact that theyma yhav e uniquetrait s (of potential scientific value).Fo r thisreaso n inNorway , following the establishment of genebanks for cattle,shee p andgoat s in the 1980's, aprogramm e to set up ageneban k for the 7nationa l dog breeds,th emajorit y ofwhic h arethreatened , wasinitiate d in 1992. 4.9 How can weweigh t the different criteria? The seven criteriajus t outlined can be used toprioritis e breeds for conservation. They covera widerang e of different aspects ofbree d characterisation andbree d value.A give n breed could be ofinteres t for conservation purposes duet oon eo rmor eo fthes e criteria. Bodiesprovidin g funding for conservation of specific breeds must in someway ,whethe r consciously or subconsciously, weight them,whil ekeepin g inmin d the different conservation objectives outlined in chapter 1. Firstly, somedecision sregardin g which species areo f interest andthei rrelativ e importance must bemade , sotha t aninitia l framework for decision-making is inplace .Then , iti s probably fair to saytha tth edegre e ofendangermen ti sth esingl emos t important criterion for breedprioritisation . This criterion may even be used across species sotha t acountr y orregio n could tryt omaximis e breed survival, regardless of species. Byensurin g that asman y different breeds aspossibl e surviveint oth efuture , onewoul dals ob eindirectl y weighting traits, asye t unknown, that might be of future economic importance. Screening ofbreed s based onth e degree of endangerment shouldthu sb eth efirst step .I twoul d allow ust o identify agrou p ofbreeds ,whic h wouldinclud e those currently with low population sizes,a s well asthos e which, although current sizes mayno tb e extremely low,migh t soonb e endangered. Then,i nth e second step,th eremainin g five criteria -adaptation , traitso f economic importance, presence of unique traits,cultural/historica l value andgeneti c uniqueness - should all beconsidere d for selecting breedswithi n the group identified inth efirst step .I ti s difficult tosa yexactl yho wthe y shouldb eweighte d andsom e common sensewoul db erequired . Adaptation toa n environment which itself isa necologica l system of special interest would 67 make abree d even more important. Traits which arecurrentl y of economic importance duet o temporary market conditions should not be considered of priority. Someattemp t might be made toran k therelativ e importance of the unique traits -fo r example,whic h ones are likely tohav e thegreates tpractica l importance for mankind ?I n asimila r fashion, therelativ e importance ofth e cultural/historical values of different breeds might alsob e compared. Estimates ofgeneti c differences between breeds would onlyb e ofvalu ei fthe yals o reflected breed differences for important traits thatmigh tpreviousl y havebee n under selection, such as fitness or adaptation. All ofthes e five criteria areimportant . Onemetho d which couldb erecommende d for weighting them isth e use of 'independent selection levels' i.e.breed s which score exceptionally highly even for only one criterion should beprioritise d regardless ofho w they rank for the other criteria. Thus, abree d with aver yhig h cultural/historical valuewoul d be preserved even ifi tha d limited adaptation toa specifi c environment anddi dno t scorehighl y for the criteria of unique traits,trait s of current orfutur e economic importance or genetic uniqueness. Similarly, abree d with highly unique traits should beprioritised , regardless of how itranke d for the otherfou r criteria. Inth e above,i tha sbee n assumed that the choice ofbreed s for conservation hasbee n madeb y national or across-country organisations thatvalu ean dwis ht otak e careo f all aspects of breed characterisation andth e different roles that breeds can satisfy for mankind. However, we should also consider what might happen if otherbodie s have theresponsibilit y for choosingbreeds .The y might not include all five criteria,bu t might only choose those which reflect theirmotive s orobjective s for conservation (see chapter 1).Fo r example,i f breeding organisations wereresponsibl e for choosing breeds then they might only include criteria which would match their objectives for conservation i.e. tomee t future market demands and toadap tt opotentia l changes inproductio n circumstances.Th ecultura l andhistorica l valueo f breeds would thusno t beconsidered . Ifscientist s were to choose thebreeds ,the y might focus on opportunities for research, andagai n the historical/cultural value ofbreed s wouldno tb e included asa criterion . Somenationa l governments ifresponsibl e for choosingbreed s might onlywis h toconserv e breeds for cultural/historical and ecological reasons.The y might thus useadaptatio n to aspecifi c environment and cultural/historical values to select breeds and ignoreth e other criteria. 68 Table 4.1.Fiv ecriteri a used to selectbreed s for conservation andho w theyrelat e toth e objectives for conservation (chapter 1). Criteria for Objectives selection Future Changesi n Socio Opportunity Cultural Ecological market production economical for research historical value demands circum value reasons stances Adaptation No Yes Yes Yes No Yes Traits of economic Yes Yes Yes Yes No No importance Uniquetrait s Yes Yes Yes Yes No No Cultural historical No No Yes No Yes Yes value Genetic uniqueness Yes Yes No Yes No No Given the motives for conservation, the criteria usedb y the decision-makers for breed selection might thus differ. Thewa y inwhic h thefive selectio n criteria might match the different objectives for conservation is outlined in Table 4.1. Sinceth eproces s ofweightin g the different criteria is complicated, asi s obvious from the above discussion, itha s frequently been suggested (e.g.Thao n d'Arnaldi etal. , 1998)tha t genetic distancing should have ake yrol e inbree d selection since,i n contrast to some other criteria, it canprovid e objective, unbiased information for separating breeds. However, objectivity can notb e the sole determinant ofth evalu e of acriterio n andth erelativ e importance ofth e genetic uniqueness ofbreeds , asmeasure d by genetic distance studies,mus t alsob e considered. This is especially valid since the correlation between genetic distances and genetic adaptation or uniqueness oftrait s israthe r low (chapter 3). There isn owa yo f avoiding the fact that some ofth eke y criteria for breedprioritisatio n require a subjective evaluation andweighting . This is obviously difficult, but necessary. At thetim e that decisions arebein g made concerning which breeds to select, concrete planso f action (for example,whethe r they involve direct support to farmers using rarebreeds ,ex situ programmes etc.)ma y alsob eproposed . In this case,th e costs ofth epropose d plans, aswel l 69 asthei r likelihood of success, should alsob econsidere d astw oadditiona l criteria for breed selection. For example,i f thedeclin e in population size of abree d couldb e halted by some simple,inexpensiv e measures to support orestablis h abreedin g programme, then thispla n might be supported. Thecomplexit y ofth ebree dprioritisatio n process outlined in this chapter shows how important it ist o havegoo d information in order tomak e theprope r decisions. However, data is often missing ordocumentatio n mayb epoor . Inthi s case, some subjectivejudgement s may berequire d to estimate some ofth e criteria ort ogaug e their importance. Atth e other extreme, it isimportan t that the limited resources in thefield o f animal genetic resources shouldno t onlyb euse d for detailed breed characterisation. Ifresource s were onlyt ob e usedfo r asingl e criterion, then it should beth e degree of endangerment. Acknowledgement Paula Murphy is acknowledged for useful discussions and comments. 70 References Brown, L.R., 1998.Th e future of growth. Chapter 1 of'The state ofth eworl d 1998',21-40 , WorldWatch Institute, USA. Cunningham, E.P., 1992.Conservatio n and development of animal geneticresource s - FAO outlineprogramme . FAOAnima l Production andHealt h Paper 104:49-53 . Diamond,J. , 1997.Guns , germs and steel. Chapter 9.Jonatha n Cape,London . EAAPWorkin g Group on Animal Genetic Resources, 1998.Assessmen t ofth edegre e of endangerment of livestock breeds.49t h Annual Meeting of theEAAP ,24th-27t h August, Warsaw,5p . FAO, 1992.Proceeding s of an expert consultation on 'Programme for the control of African animal trypanosomiasis andrelate d development', Animal Production and Health Paper 100, FAO, Rome, Italy. FAO, 1996.FA Oyearbook . Volume 50.FAO , Rome,Italy . Gandini, G. and P.Giacomelli , 1997. What economic value for local livestock breeds ?48t h Annual Meeting ofth e EAAP,25-2 8 August, Vienna,8p . Grobet, L.,L.J.R .Martin ,D .Poncelet , D.Pirottin , B.Brouwers ,J . Riquet,A . Schoeberlein, S. Dunner, F. Menissier, J. Massabanda, R. Fries, R. Hanset, andM . Georges, 1997.A deletio n in thebovin emyostati n gene causes the double-muscled phenotype in cattle.Natur e Genetics 17:71-74 . Hall,S.J.G .an d D.G. Bradley, 1995.Conservin g livestock breed diversity. Trendsi n Ecology andEvolutio n 10:267-270 . Hall,S.J.G .an dJ . Ruane,1993 .Livestoc k breeds andthei r conservation -a globa l overview. Conservation Biology 7:815-825 . 71 Hatfield, C.B., 1997.Oi l back onth e global agenda.Natur e 387: 121. Henson, E.L., 1990.Th eorganisatio n of live animal preservation programmes. FAO Animal Production and Health Paper 80: 103-117. Janss, L.L.G., J.A.M.va n Arendonk, and E.W. Brascamp, 1997.Segregatio n analyses for presence ofmajo r genes affecting growth, backfat andlitte r sizei n Dutch Meishan crossbreds. Journal ofAnima l Science 75: 2864-2876. Köhler-Rollefson, I., 1997. Indigenous practices of animal genetic resource management and theirrelevanc e for the conservation of domestic animal diversity in developing countries. Journal ofAnima l Breeding andGenetic s 114:231-238 . Martyniuk, E.an d D. Planchenault, 1998.Anima l geneticresource s and sustainable development in Europe.Proceeding s of 6th World Congress on Genetics Applied to Livestock Production 28:35-42 . OUivier, L.an dJ.P .Renard , 1995.Th e costs ofcryopreservatio n of animal genetic resources.46t h annual meeting ofth eEAAP ,4- 7 September, Prague.7p . Ponzoni, R.W., 1997.Geneti cresource s and conservation, Chapter 16, 437-469,i n The Genetics of Sheep,eds .L . Piper and A. Ruvinsky, CAB International. Scherf, B.D., 1995.Worl d Watch List for Domestic Animal Diversity. 2nd edition,FAO , Rome. Sigurdsson, A., 1995.Multipl e trait genetic evaluation ofdair y cattlewithi n and across country.Doctora l thesis.Swedis h University ofAgricultura l Sciences, Uppsala. Tawah,C.L. , J.E.O Rege, and G.S. Aboagye, 1997.A clos e look at arar eAfrica n breed- the Kuri cattle of Lake Chad Basin: origin, distribution, production and adaptive characteristics. South African Journal of Animal Science 27: 31-40. 72 Thaon d'Arnaldi,C , J.-L.Foulley , and L.Ollivier , 1998.A n overview ofth eWeitzma n approach to diversity. Genetics, Selection and Evolution 30: 149-161. Upton,M. , 1997. Intensification or extensification: which has the lowest environmental burden. World Animal Review 88: 21-29. Wickham, B.W. andG . Banos, 1998.Impac t of international evaluations on dairy cattle breeding programmes.Proceeding s of 6th World Congress on Genetics Applied to Livestock Production 23: 315-322. 73 Chapter 5.Establishin g a conservation scheme M.Toro 1' andA .Mäki-Tamla 2) 1) Centra de Investigacion yTecnologia , Area deMejor a Animal, Carretera del a Coruna, KM.7,21804 0 Madrid, Spam 2) Department of Animal Breeding, Agricultural Research Centre, Institute of Animal Production, 31600Jokioinen , Finland • Introduction • Requirements dueto conservation purpose • Requirements dueto conservation method • Criteria tochoose thefounder animals 5.1 Introduction In thepreviou s chapter we dealt with different criteria why abree d isinclude d ina conservation program. Depending onth ereason swh yth ebree dwa s chosen andth eresource s available, wethe n canprocee d in few alternative ways.I t isver y important tohav e aslittl e compromising aspossibl e in carrying forward the existing variability inth ebreed .Thi si s mainly concernedwit hth e sizeo fth eexercise ,whic h couldb e adjusted by choosing individuals for conservation action from different families andb y carrying out planned matingsbetwee n thechose n animals.Th evariabilit y in the conserved sampleshoul db e maximised. Therefore in selecting the individuals tob eth e founders themselves ort oproduc e them,th etarge t shouldb et ominimis e the overall kinship.Thi s couldb emos t efficiently achievedi fth epedigre e information is available inth epopulation . Ifther e aren opedigre e records available, any otherpossibl e information, such as geographical orhistorica l accounts, couldb euse dt oavoi dredundan t useo f families, unnecessarily increasing averagekinship . Asoun dconservatio n scheme involves also setting upth ebasi cinfrastructur e needed for recording (FAO, 1998),dat a analysis andresponsibl e use ofth eindividual s forbreeding . If necessary, skilledpeopl e shouldb ehire d or educated toru n such aprogram . Themos t 75 sustainable strategy for conservation ist o utilise self-supporting, productive populations.I n those cases it could berelevan t to establish awell-functionin g selection program for the breed. Thegeneti c improvement can concentrate on maintaining orincreasin g the profitability ofth eproductio n in thosetrait s for whichth ebree d still possesses acompetitiv e edge. Wehav e seen inchapte r 3ho wmoder n moleculargeneti cmethod s provide uswit h very powerful tools toquantif y therelationshi p between breeds andpopulations .Typin g of individuals for ase t ofmolecula r geneticmarker s can beexploite d in assessing the relationships between animals within thepopulation . Wear egoin g tose etha t the molecular genetic information can be expressed in the same compact way asth epedigre erecords .Th e marker information could also be used for decision making, infilling th e gaps inpedigre e information ori n differentiating family members or chosen chromosomal regions.Th e phenotypic information onindividual s isth erelevan t criterion when the conservation is driven by theinteres t in specific heritable traits.Th erecord s onsimpl einheritin g exterior traits could alsob e utilised in maximising the variability between individuals. This chapter startswit h assessing what kind ofprogra m is appropriate toarriv e ata satisfactory result when different conservation purposes areconsidered . Thenex t step is about appropriate schemes for such programs. Themai n alternatives arelivin g populations ina production setting orkep t in amor eprotecte d environment andcryo-preserve d sampleso f gametes,embryo s orsomati c cells improve the sustainability of such operations.Becaus e moleculargenetic s offers awhol erang e ofmethod st oquantif y the geneticvariation , it isals o important tostor e DNAfrom a sufficien t number ofindividual s ofth ebreed . Atth e end,w e review themethodolog y that can be usedi n choosing the animals with theai m ofmaximisin g thevariabilit y in theinitia l set-up. 5.2 Requirements duet o conservation purpose Thebree d would survive on aself-supportin g manner ifi twer e used for profitable production. When thebreed s areno ti n activeproduction , theconservatio n programs can be verycostly ,especiall y when therear esevera l breedsinvolve d orwher eth emaintenanc e costs arehigh ,lik ei n cattle.Therefor e wehav et ofind ou tth eminimu mrequirement s for the volume ofth eoperatio n underdifferen t conservation purposes.Althoug h the space 76 requirement in cryo-preservation isver y small,th eproductio n ofpreserve d samples canb e very expensive and should bedon e in acost-effectiv e way with sound geneticpotentia l in mind. 5.2.1 Re-establishment The conservation scheme would always benefit from awell-designe d cryo-preserved genebank to allow successful re-establishment ofth ebree d in the future, even if the current interest is in individuals exhibiting adesirabl e breed specific trait.Th e option for a successful re-establishment sets themos t demanding requirements for the scheme.Th emai n cost factor isth e size ofpopulation . Theminimu m population size isabou t 50individuals , 25o f each sex. Ifth e existing population isver y large, only 1%o fth egeneti c variation is lostb y the starting generation when it ispu t through thebottleneck . Although this might in some cases mean more losses than those takingplac e inth eorigina l population, the compromise madei n entering thebree d in aconservatio n program is still veryreasonable . It is alsoimportan t that theindividual s that form thebasi s ofth econservatio n scheme are chosen sotha t the variability amongst them ismaximised . The criteria tomee t these refinements are discussed below. When thepedigre e records aremissin g or scarce,mor etha n 25male s and 25 females should be sampled ifth eresource s allow it. 5.2.2 Selection program Itha sbee n customary toconside r livepopulation s andcryo-preservatio n schemes as exclusive alternatives. Wewoul d liket o encourage usage of different methods in amutuall y supporting manner. Thepurpos e where alarg e volume isrequired , is aschem e to support an active selection program. Here the cryo-preserved semen doses can beuse d as areserv e to guarantee the success ofth ebreedin g program even inth e case of sudden fatal wide-spread disease or loosing elitebreedin g animals.Therefore , in afas t developing population, animals shouldb e systematically sampled for cryo-preservation. Alsowhe n abree d that hasa n important socio-economic role in providing firm source oflivin gi n extreme (arid, cold or mountain) conditions isgettin g rare,i ti simportan t that asufficien t back-up system is quickly set upt opreven t the breed from loosing avita l geneticvariability . Thebree d mayhav ea n important role inmaintainin g local ecological andenvironmenta l characteristic. Although the agro-biodiversity function mayhav e only local interest, arar ebree d would require safely preserved sources torestor e the variability. 77 5.2.3 Cultural value In Europe,ther e are dozens ofbreed s that have fallen out ofth emos t popular usei n production. However, there are very attractive because ofth e cultural value attached tothem . Inman y cases they symbolise the development of local agricultural heritage and are threatened to disappear due to lack of anywide r interest in the country. In some cases such breeds havebee n revived with thepromotio n ofbree d specific products ortouris m (chapter 2).Th emaintenanc e of such landracepopulation s requires sufficient backing via conservation schemes. 5.2.4 Desirable traits There arebreed s that areinterestin g only because they are exhibiting adesirabl e trait or bearing agen e with potential use.Althoug h thebree d isno t competitive forproductio n traits, itma y carry valuable features such asdiseas eresistanc e or distinctive product quality. Ifth e variation inth e trait werepolygenicall y mediated, alarge r sample wouldb erequired . 5.2.5 DNA samples Molecular geneticsprovide s us with veryremarkabl e tools toanalys e the variation between andwithi n breeds.Th ewithi n breed analysis would alsoinclud e characterising the genetic variation in atrai t or isolating agen e grossly affecting the variation. For such purposes, DNA samples arerequired . Asufficien t number for such analyses would beobtaine d with arando m sample of 25male s and females. 5.3 Requirements duet oth e conservation method Wehav e two different methods ofconservation . Either wekee p living populations orcryo - preserve samples for future needs.Whateve rmetho d is used,w ehav e to consider the design andth e attached costs.A swa smentione d above,th e methods couldb euse d sideb y side whereth e frozen material is supporting the geneticresource s of aselecte d orex situ population. 78 5.3.1 Selection program 5.3.1.1Anima l identification system Theconservatio n scheme can be self-supporting when thebree d has arecognise d commercial value.Th ebree d can maintain its competitive edgei fther ei s awell-organise d selection program built for improving thebes t traits.Therefor e ifther ei sn o such scheme for thebree d this should be quickly set up.Thi s would involve decisions on strategy, logistics and funding. Aminimu m requirement for any scheme where genetic variability ismonitore d ist ohav e individuals tagged with unique identity codes.Thi s isno w anor m in many species within EU, but where iti sno t the case;a codin g system should bedesigned . This would pave awa yt oa databan k where each animal appears along with itsparents .Th epedigre e information isuse d in accomplishing thegeneti c comparison between parent candidates andi n forming sound mating pairs between selected animals. Next wehav et o chooseth e traits which arerecorded . Thetrait s should be simple and cheap tomeasure . 5.3.1.2 Recording scheme Therecord s onrelevan t traits areregularl y collected andlinke d toth e pedigree files. Weca n then quantify towha t extent the differences between animals are duet ogenetic s andho w selection on onetrai t is affected theperformanc e in the otherone . If thetrai t ispoorl y heritable, alarg ebod y of data onrelative s isneeded , before weca n havea reliable way topic k upth e genetically superior animalsfrom th epopulation . The importance of thetrait s andthei r genetic correlations wouldb e assessed together to compute aweigh t for each trait in the overall selection policy. 5.3.1.3Geneti c ranking system The animals aregeneticall y rankedb y adjusting therecord s for bothproductio n environment effects andth e information from relatives.Thi s could simultaneously carried outb y BLUP (best linear unbiased prediction) systems for which there are several computing packages available. Similar kind ofpackag e programs canb e used to quantify the variation in the trait andt ocomput eth eselectio n indexweights . 79 5.3.1.4Selectio n and mating plan Until quite recently the animals were chosen tob eparent s for thenex t generation solelyo n their genetic superiority. When the population is small and selection intensity isver y high, this leads to long-term increase in kinship among individuals. Some ofth econsequence s are decrease of genetic variability, increasedrisk o f achieving predicted progress and inbreeding depression. There areno wmethod s developed (e.g.Meuwissen , 1997)whic h could be used along the geneticrankin g systems that provide selection ofmatin gpair s to arrivea t sustainable selection rationales. 5.3.1.5Cryo-preservatio n scheme Weca n improve the efficiency of selection byresortin g to developments in reproductive technology. Fewermale s areneede d andhighe r intensities of selection can bepractise d if artificial insemination isexploited . Thebes t cows can have dozens of offspring morei f embryos oroocyte s are collectedfrom them . Each selection program shouldb e supportedb y acryo-preservatio n scheme for agenom eresourc e bank. The cheapest way tod othi s ist o store semen orembryos . 5.3.1.6 Infrastructure Abreedin g scheme involves setting upth ebasi c infrastructure needed for recording, data analysis andgeneticall y healthy use of theindividual s for breeding.Thi s would in many cases mean that skilledpeopl e shouldb e hired or educated toru n such aprogra m 5.3.2 Living populations Inman y cases the conservation scheme with alarg e activelyproducin g population isth emos t cost-effective. Therefore, when thepopulatio n isno t inproduction , asmalle r geneban k population shouldb e established. Whenpopulatio n is actively promoted for production purposes, it should have an organised breeding program to maintain its competitiveness amongst other commercial breeds.Thi s would involve the setting up of arecordin g scheme, genetic evaluation system and aprope rpolic y on the useelit e animals eitheri n artificial insemination orembry otransfe r schemes. Ininitiatin g thebreedin g scheme,a larg enumbe r of founder animals with maximised variability shouldb e chosen. Ageneticall y sound selection program wouldthe n involvemonitorin g the development of coancestry in thepopulation . 80 When the interest in thebree d has afairl y narrow basis,especiall y ifth eperformanc e in any production traits isno t profitable, asmal l livepopulatio n is still needed. Such apopulatio n would guarantee that public would stay aware of its existence andresearc h opportunities are kept available. Such aliv e genebank population with maximal retention of its genetic variability shouldb e contemplated although thecurren t interest in the breed isonl y ona specific trait ora gene .A livin g bank of live animals has tob ebase d on genetically sound founders and shouldb e supported by sufficient cryo-preserved material.Th e combined useo f living andcryo-preserve d material has tob eguide d byrationale s that minimise genetic variability. 5.3.3 Cryo-preservation Whenth epopulatio n has little function in currentproduction , inman y casesth e cheapest conservation method is cryo-preservation. Even in this case,however , asmal l living population shouldb e considered asa nor m sotha t thebree dreceive s sufficient attention. Although frozen material doesno trequir e much space,it s creation involves costly steps. Therefore alsoth e cryobank shouldb eproperl y designed. Thebes t design isachieve d by again maximising the variability. Theindividual s that arecontributin g to thepreserve d material arechose n sotha t thegrou p coancestry isminimised . Semen Semen couldb e used in supporting the existing genebank populations orpopulation s that are goingt o bere-establishe dfrom cryo-preserve d oocytes orhav e been re-establishedfrom embryos orsomati c cells.Whateve r thepurpos e is,th e variability will bemaximise d ifth e average coancestry amongmale s isminimised . The female population should alsob etake n into account andth e semen producers canb e obtainedfrom mating s where thewhol e population coancestry is considered. A simplerul e toconstrai n the increase in coancestry isa desig n where eachmal eha s aso n andeac h female has adaughter . Tomee t thisrequiremen t in acost-effectiv e way canb e accomplished when semen sexing is feasible withreasonabl e cost. Semen andoocytes The semen production is almost unlimited whereas onlyrecentl y itha sbecom e possible to obtain reasonable number of oocytes. Oocytes canb e collected from the ovarieso f slaughtered animals orwit h lessrestrictio n about numbers byrepeate d aspirations of follicles from ovaries of living cows.Th e animals producing the gametes should be chosen to minimise the average coancestry. Whenbot h types ofgamete s can be cryo-preserved much more opportunities are left in re-establishing thepopulatio n inth e future by factorial mating in invitro fertilisation . The usual practise is tomat e eachmal e with several females (hierarchical) but interm s ofmaintenanc e of genetic variability iti s bettert omat e females with several males (factorial). Embryos Theadvantag e ofembryo s compared semen isth epossibilit y to store the entire genetic composition. Theparent s should be chosen tominimis e the coancestry and factorial mating shouldb e favoured when the embryos areproduced . Factorial mating would bemos t cost- effectively done by invitro fertilisation . Further savings inresource s couldb emad e ifth e embryos are sexed and subsequently appropriate numbers ofmal e and female embryos are stored. Somatic cells Within the last twoyear s embryo research has made long leaps in developing technology to produce undifferentiated cells from cells taken from adult individuals. Whennucle i from such cells aretransferre d to enucleated eggs,th egeneticall y identical individual couldb e reconstructed. Although the cytoplasm is that ofth erecipien t egg,w ehav e aver y powerful technique toproduc e acop y ofth egeneti c composition ofindividuals . When the techniques become more feasible and consequently areno t too expensive, all the animals in thebree d couldb e sampled. Atth emomen t the highproductio n costs look very limiting andtherefor e minimisation of costs andmaximisatio n ofvariabilit y shouldb e considered together. Thetechnolog y toproduc e undifferentiated somatic cellsha sbee n developed toimprov e the stepsi n gene transfer procedures. Iftha t methodology advances asfas t aspromised , it could 82 mean that we soon will have unlimited sources of genetic variation available when targeted mutagenesis and gene transfer is extensively used. DNA Sofa r wehav e talked about methods torestor e thebree d genetic composition ascheapl y as possible. Becauseth e assessment ofbree d diversity is acontinuou s process andmor e information is accrued along time either ontechnique s oro n useful genomeregions ,w enee d enough DNA from eachbree d to carry out appropriate analyses.Fo rtha tpurpose , DNA from 25randoml y chosen individuals of each sex should be stored. In conclusion, thebes t andleas t costly conservation method ist outilis e theprofitabilit y ofth e animals inth e breed and further improve the self-supporting elementsb y awell-designe d selection program for the competitive traits.I nbreed s that areles sprofitable , alivin g population ispoliticall y very important. In establishing aliv e and cryobank, the following issues should be considered: thenumbe r of founders, with special attention toth enumbe ro f living founders, against the cost of aconservatio n scheme and amaximu m genetic variability ofth e genomeresourc e bank. 5.4 Criteria to chooseth e founder animals Thefirst decisio n in setting up aconservatio n scheme ist o decide about the founder animals that will contribute gametes either toth e cryopreserved gene-bank ort o thefirst generatio n of a liveconservatio n scheme. There is consensus that the initial sampling of animals should maintain the maximum genetic variability present in the breed. Genetic variability comprises allelic diversity (thenumbe ro f alleles coexisting inth epopulatio n ata give n time), observed heterozygosity (theproportio n ofheterozygou s individuals) andexpecte d heterozygosity defined asth eheterozygosit y that would beexpecte d under the Hardy-Weinberg equilibrium, 1-S pi 2,wher e p;i sth e frequency of allele i at agive n locus (Nei, 1973).Th e last one seems tob eth e criterion of choice in the conservation literature (Caballero and Toro, 1998)an dtherefor e the onetha twil l be considered here. 83 Thewa y tocalculat e expected heterozygosity depends on thetyp e of information available, as is explained below. 5.4.1 Pedigree information If genealogical information on candidates is available thebasi c tool isth e kinship coefficient that reflects the expected homozygosity by descent. Therefore, we should use as founders those individuals that minimise the average group kinship including reciprocals and self- kinship among individuals. Let usconside r that Smale s and Dfemale s are available as potential donors ofgamete s andw e also assume that kinship coefficients amongal l candidates areknown .Th e problem will bet o find the ssire s andd dam s that will beth e actual donors such that the average kinshipbetwee n them isminimal . Theaverag e kinship will becalculate d as: * - 7^1 + Z^-sd + 4*rf with ks,k sd andk j being the mean kinship between sires,betwee n sires anddam s and between dams. Thereaso n for recommending this criterion istha t besides maximising expected heterozygosity by descent itwil l minimise thenumbe r ofindividual s with common ancestors andi n simple cases itwoul d result inth e classical criterion of equalising family sizes (Caballero andToro , 1998). Thesituatio n is essentially the same asth e onetha t arises when optimising selection response underrestricte d inbreeding (Toro andPérez-Enciso , 1990;Brisban e andGibson , 1995; Meuwissen, 1997). Theproble m of finding the optimal way ofproducin g afixed tota l number of embryos will be solved in asimila r way. First,w ecalculat e the optimal number ofembryo stha t each individual, either sire or dam should contribute andafterward s weorganis emating si n such waytha t will alsominimis e inbreeding of future embryos.Th eoptima l solution would require toimplemen t afactoria l mating design that, obviously, willno tb ealway s technically feasible 84 and additional restrictions taken account ofth ereproductiv e limitations should be included in the optimisation problem. Ifonl y aseme n bank is available it couldb e convenient to setu p some matings beforehand in order totransfe r the genetic variability present inth e female population tone wbor n males.O n the other hand if somatic cells technology were available it would greatly increase theproportio n of candidates that could be saved. Box 5.1 Group kinship Ifx ;denote s if individual y is selected (x;= 1)o r not (XJ= 0 )th eoptimisatio n problem will be tominimise : sz ^ sd ^ dz subject toth erestriction : ZXJ= s and Zx ;= d Gamete contributions of selected individuals could alsob emad e unequal andth eproble m to solve will be the samealthoug h now swil l be thenumbe r oftota l semen doses, dth e total number ofoocyte s doses and Xj thenumbe r ofdose s contributed byindividua l i. Theproble m canb e solved byintege r programming techniques orb y using anheuristi c algorithm such as simulated annealing (Fernandez andToro , 1998). Amor e complete description ofth e founder population canb edon e usingth e gene dropping technique (MacCluer et al., 1986).Tw ohypothetica l alleles are assigned to each individual of thebas epopulatio n of thepedigree .The n the genotype ofdescendant s is constructed working downth epedigre e by simulating themendelia n segregation. The entireprocedur e isrepeate d manytime s andth e information from the currentpopulation , eithergamet e donors orth e founders oflivin gpopulation , are summarised over iterations. Intha twa y acomplet e description ofth ejoin t distribution ofth efounde r allele survival canb e obtained and to infer theprobabilit y that amendelia n genepresen t inth ebas epopulatio n at agive n frequency will berepresente d inth e foundation stock (Gandini etal , 1994).A n additional information that canb e obtained isth e variance ofkinshi p coefficients. Thisrequire s to simulateman y loci (1000o rmore )i n each iteration reflecting thelinkag epatter n ofth e species (number and length of chromosomes). 85 Box 5.2 Relationship between pedigree and marker kinship TheGudyerba s strain of Iberian pig is conserved as aclose dpopulatio n with complete pedigreerecord s since 1945.Fo r 10animal s ofth e actual population, asimilarit y matrix was calculated based on 63 AFLPpolymorphi c bands and it was compared with the coancestry coefficient matrix calculatedfrom pedigree . Thecorrelatio n coefficient between both values was 0.592(Ovil o etal. , 1998). 5.4.2 Marker information Whenpedigre e information is lacking, kinship can beestimate dfrom molecula r markers. Iff m isth e marker kinship in abialleli c locus,define d asth e probability that twogene s taken at random are alike in state, and fis the coancestry by descent there will berelate d trough: (i-/.)=0-/Xi-5>,2) wherep ;i s the frequency ofallel ei . Therefore thepreviou s criterion ofminimisin g coancestry could, inprinciple ,b e implemented. However, there arepoint s that should be taken into account. First, estimation of kinshiprequire s theus e of codominant markers such asmicrosatellites . When the information camefrom dominan t markers (RAPD,AFLP ) asimilarit y matrix can be calculated thatwil l alsob ecorrelate d with the true coancestry (Lynch and Mulligan, 1994). Second,marker s with alleles atintermediat e gene frequencies will beth emos t informative ones.Third , the estimation error could behig h and at leastbetwee n 30-50 markers would berequired . Fourth, sophisticated methods havebee n developed thatproperl y weight information provided by different loci (Ritland, 1996).A n alternative use ofmarker s could bejus t todetec t themos t important relationships such ast o detect the candidates that are full-sibs, half-sibs orparent - offspring. Themarke r requirements to distinguish between thesetype s ofrelative s are considerably more easyt o fulfil. Asth enumbe r ofmarker s increases, molecular information will give abette r knowledge of thetru e genetic diversity. However, in practise itwil l probably not beth e case in most ofth e practical situations andtherefor e other considerations such aspartia l pedigree information or historical information should betake n into account. 86 5.4.3 Pedigree and marker information When both pedigree andmarke r information exist, the optimal way to combine them would bet ocalculat e kinship coefficient conditional onth e marker information andthe n apply the criterion of minimum coancestry (Toro et al., 1998).Howeve r this calculation would be computationally very costly involving Monte Carlo Markov chain methods. Inpractis ea simpler criterion couldb epreferable . This simple criterion would bet ominimis e kinship calculatedfrom marker s butwithi n the classicalframework o foptima l within family selection (Wang, 1997):eac h sire contributes one son and among the rdam smate d with each sire,on e is selected to contribute aso n andth e remaining r-1 contribute one daughter each. In other words,marke r information wouldb e usedmainl y toselec t within families. Other criteria such asfrequency-dependen t selection can alsob e considered (Toro et al., 1998). 5.4.4 Other marker information Aninterestin g and special marker information can beobtaine dfrom paternall y (Y- chromosome) ormaternall y (mitochondrial) inherited DNA.The yprovid e information on male or female lineage. Inth e founder population ofth e conservation scheme the different haplotypes shouldb e represented. Box 5.3 Mitochondrial DNA polymorphism Variation in mtDNAi s extremely useful in studying genetic diversity. There are anumbe r of reasons for this: • mtDNA ismaternall y inherited with norecombination . Hence thenumbe r ofnucleotid e differences between the mitochondrial genomes isa direc treflectio n ofth egeneti c distance that separates them, • each cell hasthousand s of copies ofmtDNA , • regions ofmtDN A mutate 5-10time s more than nuclearDNA . Theusua l wayt o analysemtDN A is sequencing ofth eD-loo ptha t shows greater variation than theres t of themtDN A molecule. Y chromosome Inth e samewa y asmtDN A could beuse d toidentif y maternal lineages in the populations,Y chromosome sequences provide similar information onpaterna l lineages. 87 5.4.5 Phenotypic information Someadditiona l phenotypic information could alsob e considered. In somebreed s therei s phenotypic variability for exterior traits (different colours or conformation types,presenc e and absence of horns, etc.)tha t couldb e interesting to assure itsmaintenanc e inth e conservation scheme. 5.4.6 Other information Sometimes there is also information on theher d structure of thebreed . Geographical or historical information will permit tokno w if someherd s havebee n maintained isolated. Furthermore,man y traditional breeds aresubdivide d in local varieties that havebee n maintained isolated and show different morphological appearances.Thi s information would bevaluabl e when choosing the founders of aconservatio n scheme.Fo r example,whe n the conservation program of Iberian pig was created in 1943,4- 5 sires and 17-24dam s were chosen from eachon e of four isolated herds (historical information) thatrepresen t local varieties (black hairless strains andred , golden orpie dvarieties) . Obviously, in caseso f breeds with aclea r subpopulation structure someo fth e considerations madei n chapter 3an d 4 wouldb e applicable. References Brisbane,J.R . andJ.P .Gibson , 1995.Balancin g selection response andrat e of inbreeding by including genetic relationship in selection decisions. Theoretical andApplie d Genetics 91: 421-431. Caballero, A.an d M.A. Toro, 1998. Interrelations between effective population size and otherpedigre e tools for themanagemen t of conserved populations. Genetical Research (submitted). FAO, 1998.Secondar y Guidelines for Development ofNationa l Farm Animal Genetic ResourcesManagemen t Plans:Anima l recording for medium inputproductio n environments. FAO,Rome ,Italy , 112p. Fernandez,J . andM.A . Toro, 1998.Th eus eo fmathematica l programming for controlling inbreeding in selection programs.Journa l ofAnima l Breeding andGenetic s (inpress) . Gandini, G.C., R. Leonarduzzi, and A. Bagnato, 1994.Allel e survival in storageo f gametes and embryos for conservation. Proceedings of the 5th World Congress on Genetics Applied to Livestock Production, Guelph, 21: 397-400. Lynch M. and B.G. Milligan, 1994.Analysi s ofpopulatio n genetic structure with RAPD markers. Molecular Ecology 3:91-99 . MacCluer,J.W. ,J.L .VandeBerg , B. Read and O.A. Ryder, 1986.Pedigre e anlysisb y computer simulation. Zoo Biology 5: 147-160. Meuwissen,T.H.E. , 1997.Maximizin g therespons e of selection with apredefine d rateo f inbreeding. Journal of Dairy Science 77: 1905-1916 . Nei,M. , 1973.Analysi s ofgen ediversit y in subdivided populations. Proceedings ofth e National Academy of Sciences USA 70:3321-3323 . 89 Ovilo, C, C. Barragân, C. Castellanos, C. Rodriguez, L.Silió , and M.A. Toro, 1998. Aplicaciones demarcadore smoleculares , (RAPD, AFLP ymicosatélites ) al a caracterización degenotipo s decerd o ibérico. IV Simposio International do Porco Mediterraneo. Universidade de Evora (inpress) . Ritland K., 1996.Estimator s forpairwis erelatednes s and individual inbreeding coefficients. Genetical-Research 67: 175-185. Toro M. and M. Pérez-Enciso, 1990. Optimization of selection response under restricted inbreeding. Genetics, Selection andEvolutio n 22,93-107 . Toro,M. , L.Silio ,J . Rodrigaflez, C.Rodriguez , and J. Fernandez, 1998.Optima l useo f markers in conservation programs. Génétique, Selection et Evolution (inpress) . Wang,J. , 1998.Mor e efficient breeding systems for controlling inbreeding and effective size in animal populations.Heredit y 79:591-599 . 90 Chapter 6. Operation of Conservation Schemes T.H.E. Meuwissen Department of Animal Breeding and Genetics, Institute for Animal Science and Health, P.O. Box 65,820 0 AB Lelystad, The Netherlands • Introduction • Liveconservation schemes • Cryo-conservation schemes • Integrating liveand cryo-conservation schemes 6.1 Introduction 6.1.2 Whatissue s are important? Theoperationa l issues of conservation schemes depend on which kind of conservation plan was chosen in chapter 2 and 5.Th emai n distinction isbetwee n pure live conservation schemes,pur e cryo-conservation schemes,an d acombinatio n between live andcryo - conservation schemes.Withi n the live conservation schemes,on eca n distinguish insitu an d exsitu liv e conservation, but this distinction isno t veryrelevan t for this chapter because the issues that areimportan t for in situ schemes are alsoimportan t to exsitu liv eschemes . Theissue s that areimportan t for live schemesare : • the effective population size atwhic h thebree d is maintained, • selection ofanimal swithi n thebreed , • mating structure of the selected animals, • thegeneti c improvement thatneed s tob e achieved, • monitoring oftrait s andpedigree . These issues will be addressed in section 6.2. Withrespec t toth e issue ofth e selection of animals,not e that some selection ispossible , when siresproduc e more than one son anddam s moretha n onedaughte r andth epopulatio n isno t increasing in size,bu t the selection may well beat random (instead of for atrait) . 91 Themos t relevant operational issue for acryo-conservatio n schemes isth ereplenishment , i.e., replacement, ofretrieval s from thegenom e bank, sinceretrieval s will depleteth e genetic materials in the genomebank . Theoperatio n ofth egenom eban k is described in section 6.3. With respect toth e combination of live conservation schemes and cryo-conservation schemes there aretw oaims : • Aliv e conservation scheme is conducted while cryo-conservation serves asa bac k upi n caseth e live population runs into genetic problems. If old 'back-up' geneticmateria l is retained, the genome bank will keep track ofth e full history ofth e evolution ofth e population. • Cryo-conservation canb e actively used toincreas e the effective population size of asmal l livebreed , andreduc e genetic drift. The former aim is an extension to apur e live conservation schemes, andca nreduc erisks substantially in these schemes.Th e latter aim implies ajudiciou s use cryo-conservation, which will obtain special attention inthi s chapter. Thecombinatio n ofliv e andcryo-conservatio n can result inver y potent conservation strategies because: • It can achieve all the objectives for conservation, namely future economic potential, present socio-economic value,cultura l andhistorica l value, agro-biodiversity conservation,risk reduction , research and education (seechapte r 1). • It canreduc eth e genetic drift substantially, andresemble s in that respect apur e cryo- conservation schemewher e genetic drift isver y small. • Inth e combination of anin situ live andcryo-conservatio n scheme thepopulatio n will still evolve and adapt toth e environmental circumstances. Inth e combination ofa n in situ live and cryo-conservation scheme wehav e tofind a balanc e between the latter two aspects:reducin g genetic drift by using much old cryo-conserved stocks andpromotin g genetic adaptations by using little cryo-conserved stocks.Ho w to find thisbalanc e will be described in section 6.4. 92 6.2 Live conservation schemes 6.2.1 The effective population size From conservation biology theory, effective population sizes should exceed 500animals , otherwise the accumulation of slightly deleterious mutations will deem thepopulatio n to extinction (Lynch et al., 1995).Recently , however, there has arisen acontrovers y over the mutation rate that was assumed. Lynch et al. assumed amutatio n rate of0. 5mutation s per genome pergeneratio n (mutation model A),whil ene w estimation methods resulted inmuc h smaller estimates of 0.03 mutations per genomepe r generation (Garcia-Dorado, et al., 1998) (mutation modelB) . Alsoth e mean selective advantages ofmutation s differed between themutatio n models Aan d Ban d are estimated at0.0 2 and 0.2,respectively , inDrosophila. Hence,unde rth e model B, mutations aremor erar e andhav e larger effects than undermode l A.Not e that deleterious mutations with large effects areles s likely to drift tohig h frequencies inth e population, becausenatura l selection will prevent this.Hence ,bot h these changes inth emutatio n model Bresul t inmuc h smaller effective population sizestha t areneede d topreven t abuil d upo f mutational load. Further research isneede d to assess the critical effective population size,bu t itwil l be much smaller than 500animals . Meuwissen and Woolliams (1994)balance d thedrif t of current deleterious mutations against natural selection, which purges deleterious mutants. Hence,the y avoided theus e of inaccurate estimates ofmutatio n rates.Consequently , theirresult s apply onlyi n the evolutionary short term (say upt o 20generations) ,wher e the effects of abuil d upmutationa l load are still negligible. Inpractice , theseresult s mayb emor e relevant than the evolutionary long term results since 20 generations comprises 20- 100year s for most species, andma yb e even longer in cryo-aided live conservation plan (see section 6.4). If at somepoin t in the distant future aconside r load ofmutation s happened tohav e accumulated, still an action plan can be devised to keep thepopulatio n temporarily at ahighe r effective size in ordert opurg e the deleterious mutants. When varying the assumptions ofthei rmodel , the authors concluded that the critical effective size,i.e. , the sizebelo w which the fitness ofth epopulatio n steadily decreases,i sbetwee n 50an d 100animals . Although moreresearc h isneede d on this subject wewil l assume here that theminimu m effective sizeo f aliv epopulatio n is 50 animals per generation, which yields arat eo f 93 inbreeding of 1%pe r generation.Not e however that the actual sizeo f thepopulatio n may havet o be substantially larger than 50becaus e of unequal numbers ofmale s and females or selection (see Table 6.1 for acompariso n of actual to effective sizes). Effectivepopulation sizeswhen generations overlap Most livestock populations have overlapping generations, i.e., theparent s ofne wbor n animals areno t strictly ofth e same age such that somema y be2 and other 3year s old.W e will assume here that drift, andthu s effective size,i st ob e controlled per generation. The alternative is to control drift peryear . The difference between controlling drift per generation orpe r yearbecome s clear when weconside r acryo-conservatio n scheme,wher e apopulatio n of 50animal s isre-establishe d after 100year s of cryo-storage. Inthi s scheme,th e drift per year is small but thatpe r generation is as large asusua l for apopulatio n sizeo f 50. Also,th e cryo-conserved population didno t achieve anygeneti c adaptation during the last 100years . Hence,th eminimisatio n ofdrif t pergeneratio n can result inn o genetic adaptation, whereas theminimisatio n ofdrif t per generation allows for the fact that thepopulatio n hast oevolve . Becausegeneti c adaptation is oneo fth emai n aims of an in situliv e conservation plan,th e genetic drift should beminimise d per generation, i.e., the effective size should bemaximise d per generation. For exsitu live conservation plans also some genetic adaptation will be desirable inmos t cases andth e same argumentsholds . Sinceth e effective sizepe r generation isrelevan t in populations with overlapping generations, alsoth enumber s of sires and dams selected hast ob e expressed pergeneration . Thenumbe r sires usedpe r generation isth enumbe r ofnewl y introduced sirespe ryea rtime s the average generation interval (averaged over sires anddams) . Similarly, thenumbe r of damsuse d per generation can be calculated. Monitoringof effective population size Whenpedigre e isrecorded , the coefficient ofinbreedin g canb ecalculate d for every animal (Falconer, 1989).Hence ,th e increase ofth e averageinbreedin g coefficient can be calculated peryear . However, the increase ofinbreedin g isdu et o theincreas e ofth e average kinship in thepopulation , whichmake s thatth e mating of completely unrelated isno tpossibl e anymore. Thus,th e future average inbreeding is describedb y the current coefficient ofkinshi p (see chapter 3). Hence,mor e up to dateresult s areobtained , by calculating the average kinship across allpair s of animalsas : 94 Ka= '/4K,(m)+ >/4K,(f)+ '/ïKaCmf), where Ka(m),K a(f), and Ka(mf) areth e average kinships between allpair s ofmales , females, andmale-femal e pairs,respectivel y (excluding pairs of an animal with itself). Thus,th e yearly increase of the average kinship coefficient can be calculated AK(yr). If further, the average age of the sires anddam s atbirt h ofthei r offspring isrecorded , i.e., thegeneratio n interval (L) isrecorded , we can calculate theincreas e ofth e inbreeding per generation asAK(gen )= L AK(yr). Theeffectiv e population size isno wN e= l/(2AK(gen))animal spe r generation. Iti s important tomonito r effective population sizes,becaus e they can be smaller than expected duet oan y effect that increases the variance ofth e family sizeo f the animals (e.g., selection, unequal survival rates). Because ofthi s and because ofth efollowin g sections,i t isver y important to keep records ofth epedigre e in livepopulatio n schemes,i.e. ,t o store the sire andda m identification number of every animal in adat a bank. Table 6.1 Numbers of Sires and Damsneede d to achieve an effective population size of 50.' Random selection Phenotypic: selection 2 Within family selection2 Sires Dams Sires Dams Sires Dams 25 25 35 35 13 13 20 34 30 45 12 14 16 56 25 65 10 50 14 116 20 300 9 1000 smaller numbers of sires areno t possible 1Fro m FAO, 1998. 2 To be described later in the text. 6.2.2 Theselectio n of animals Which animals should serve asparent s for thenex t generation? 6.2.2.1 Minimise genetic drift Withinfamily selection Genetic drift may have tob eminimise d because wewoul d liket omaintai n the genetics of population asclos e totha t ofth eorigina l population aspossible , except for the traits that are undernatura l orartificia l selection. Alternatively, population sizema yb e small andthu s drift 95 will beto o large if wewoul d not minimise it. Thefollowin g selection process will minimise drift, wherenumber s of sires and dams areequal : • Step 1: Whe n asir e has tob ereplaced , select hisreplacemen tfrom hi s own sons, i.e.on e ofhi s sonsreplace s thesire . • Step 2:Selec t thereplacemen t of ada mfrom he r own daughters, i.e. oneo fhe r daughters replaces the dam. The above scheme yields strict within family selection, which keeps family sizes constant. Theeffectiv e population sizei stwic e the actual population size,i.e . Ne =2(N s+ N d), where Ne iseffectiv e population size, andN s andN d areth enumbe r of sires anddams , respectively, with Ns= Nd. Ifth enumbe r of siresi s smaller than thenumbe r of dams,th e minimisation of drift needs extra step (Wang, 1997): • Step 3:Und oth e selection ofth ereplacemen t of ada m that had aso n and adaughte r selected under steps 1 and 2,respectively . Replace the latter dam with adaughte r from another dam,whic h didno t have aso n selected under step 1. Theeffectiv e size underthi s selection ruleis : 2 2 2 Ne= 16 Nd Ns / (3Nd - NsN d+ 2N s ). Random selection In situations where the selection of sires anddam si sles swel l controlled, random selection of sires and damsminimise s drift. The effective population sizei sthe n (Wright, 1931): Ne= 4N sNd/(Ns +N d). [6.1] When thenumber s of sires and dams areequal ,thi sreduce s toth e actual population size,i.e. , underrando m selection andN s =N d: Ne= N s+ Nd. 96 In cases where the use ofbull sma yb enon-rando m due tothei r differences inbreedin gvalue , a simplerul e may be tomarke t only an equal number of doses of semen from eachbull ,t o prevent preferential use of somebulls . Prolongedgeneration intervals Note that the abovenumber s of sires and dams arepe r generation, i.e., ifth e generation interval is4 years ,N s (Nd)i sth enumbe r of sires (dams) selected during 4years .Th e generation interval is defined asth e average ageo fth esire s anddam s atbirt h ofthei r replacements / offspring. Thus,prolongin g the generation interval can bea ver y important method to increase Ns and Nd,an dthu st o increase effective population size and reducegeneti c drift. However, weals o want totu m over generations in ordert o achieve natural and artificial selection response, and ajudiciou s useo f longgeneratio n intervals is recommended. Minimum Kinship Selection When the livepopulatio n has gone through arecen t severe bottleneck , the family structure can bever y unbalanced andwithi n family selection asdescribe d above doesno tminimis e the genetic drift. Inthi s case minimum kinship selection will minimiseth e genetic drift. With minimum kinship selection, agrou p of animals is selected thatminimises : — J\.a L\ Lj Cj Cj Jvjj, where £;(Zj )denote s summation over all selection candidates;K ai sth e average kinship ofth e selected animals; Kyi s coefficient ofkinshi pbetwee n animals ian d j; Cj isth e contribution of animal it oth enex t generation, i.e., c; = V2n ; /N ,n ;i snumbe r ofoffsprin g from animal i,an d Ni stota l number of offspring (the 'A isbecaus e asir e (dam) contributes onlyhal f ofit s genes toth e offspring). Theoptima l contribution c;,tha tminimise s Kai sgive n in Box 6.1. When the family structure isbalanced , minimum kinship selection will result inwithi n family selection. 97 Box 6.1 Minimum Kinship Selection It isusefu l torewrit eth eminimu m kinship selection problem, as described in thetext ,i n matrix notation: Ka= c'Kc , Where K is (q*q)matri x of coefficients of kinships (q= numbe r of selection candidates); and ci svecto r of contributions. It canb e shown that Kai sminimise d when the contributions are: c=/2K1Q(Q'K1Q)1l, where 1i s acolum n vector of ones;Q is a(q*2 )incidenc e matrix ofth e sex of the candidates whereth e first column contains aon e for male and azer o for female candidates, andth e second column contains aon e for female and azer o for male candidates.Th e contributions of themal e andthos e ofth e female candidates will sum to !4. Inth e case of aver y small population, the genetic drift can becontrolle d atth e DNA levelb y calculating the kinship conditional ongeneti cmarke r information (Toro et al., 1998).Th e markers areuse dt o improve the coefficient of kinship between the animals.Improve d inth e sense that the kinship is assessed atth e DNA level,wherea s kinships that arecalculate d from thepedigre e alone are average coefficients of kinship ofth eDN A segments. Optimisation of the contributions is again as described in the Box 6.1, whereno w the coefficients ofkinshi p arebase d onmarke r information. The computation ofth ekinship s conditional onmarke r information requires Monte Carlo Markov Chain methods andi s very computer intensive. Alternatively, the kinships can be calculated without using thepedigre e andth e inaccuracy duet o ignoring thepedigre e can be compensated by applying thewithi n family selection rules ofWan g(1997) .Thi s high tech control ofgeneti c drift may beusefu l in some situations whereth e size ofth e population hasbee n reduced tover y few animals (say acoupl e ofmale s and 10females) . 98 6.2.2.2Selectio n insmal l populations The conserved livepopulatio n mayb ewel l above theminimu m effective size of 50animal s (see section 6.2.1)an d someimprovemen t ofth e genetic adaptations ofth ebree d may be desired as described in chapter 2. Inthi s case two selection methods will be suggested: • Phenotypic selection, i.e., select for ownperformanc e records of the animals. • Optimal contribution selection (Meuwissen, 1997;Grund y et al., 1998). Thefirs t selection method isver y easyt o implement, whereas optimal contribution selection isa rathe r high techmethod . Notetha t selection for BLUP(Bes t LinearUnbiase d Prediction) - breeding value estimates isno t mentioned in the above list,becaus e it can severely reduce the effective population sizebelo w the actual size andthu s increase genetic drift (without people being aware of it). Phenotypicselection Phenotypic selection isth e simplest method of selection, but, at equal rates ofinbreeding ,i t can outperform BLUP-selection.Hence , at equal rates ofinbreeding ,phenotypi c selection isa quite competitive method of selection. Iti sver y easily implemented when thetrait s canb e measured atbot h sexes, for example, simply select the animals with the highest growth rate.I f the animals arekep t in different herds,whic h hampers adirec t comparison of animals across herds, selection can be for the deviation ofth e animals from theher d mean (or herd-year- seasonmean) . When thetrai t is onlyrecorde d on one ofth esexes ,e.g. , litter size, selection couldb e at random in the unrecorded sex.Alternatively , anumbe r of female offspring could be obtained from themal e selection candidates and selection could befo r thephenotypi c mean ofth e offspring ofth emales .Th e latter requires,howeve r that thepopulatio n is ofa quit e large size. Often selection will befo r more than onetrait , i.e., several traitsnee d tob eimproved . As before phenotypic selection will onlyb e for the ownperformance s ofth e animals,bu t theow n performances have tob ecombine d into aselectio n index such that thepopulatio n meanwil l changeint oth erigh t direction. This involves threesteps : 1. Determine the optimal direction ofth e selection, i.e.,pictur eth e animal that is optimally adapted toit s environment (andmarke t niche).Th epictur e ofthi s optimal animal should notb eto o optimistic such that it can bereache d within areasonabl e time horizon. 99 2. Obtain adesire d gains selection index to select the animals in the optimal direction using only own performance records (see Cameron, 1997). See Box 6.2 for abrie f description of the desired gains index. 3. Calculate the selection response that will be achieved within the time horizon using Cameron (1997). Ifth e selection response deviates substantiallyfrom th e original goal of step 1,th egoa l of step 1 should bemad e morerealisti c and steps 2an d 3repeated . From step 2a selectio n index can be calculated for every animal byweighin g theow n performances of thetrait s byth e index weights. Selection proceeds aswit h single trait selection, but with the individual trait replaced by the selection index. The above desired gains index avoids determining economic values for every trait. This seems useful, becauseth e calculation ofeconomi c weights can bever y complicated for traits in which local breeds often excel:fertility , diseaseresistance , longevity and quality of special products. Selection for over-simplified breeding goals can make the characteristics ofth e local breed equal tothos e ofth eintroduce d breed, which has usually been very intensely selected for asimpl ebreedin g goal.I n situations where the calculation of economicweight s is rather straightforward, the traditional optimal selection indices shouldb e used, which areals o described by Cameron (1997). Itshoul db ekep t in mind thatphenotypi c selection will reduce effective population sizes below those for random selection, i.e., the effective sizewil l be smaller than calculated by equation [6.1].Th ereductio n in effect sizeincrease s with theheritabilit y ofth e trait andth e intensity of selection, but typically areductio n of 30% shouldb e expected. Hence,whe n phenotypic selection ispractised , the effective size calculated by Equation 6.1 should yielda t least 70and , more safely, 100animals . Optimal Contribution Selection Optimal contribution selection maximises the genetic level of selected parents,whil e controlling the increase of theaverag ekinshi p in thepopulation . Note that the increase ofth e average kinship (=probabilit y that 2rando m alleles areidentica l by descent) equals the increase of theinbreedin g (=probabilit y that the 2allele s of anindividua l are identical by descent) underrando m mating. Hence, optimal contribution selection maximises the genetic gain while controlling therat e of inbreeding. 100 Box 6.2 Desired Gains Selection Index Let theX j denote thechang e that isneede d for trait it omov e from the current population mean to the desired optimal population mean. Further let xdenot e avecto r ofthes e changes. Thegeneti c variance-covariance matrix of thetrait s isdenote d by G. Iti s assumed that all traits that are tob eimprove d are also measured, otherwise the calculation of theinde x weights ismor e complicated. The optimal desired gains selection index weights canno w be obtainedfrom th e vector: b= G ' x. Thevecto r of selection responses of thetrait s over the time horizon, T,is : AG, XtT 'T L Vb'Pb where: ii s intensity of selection (see Falconer, 1989); Li sth e generation interval; and Pi sth e phenotypic variance-covariance matrix ofth etraits . Wewil l describe optimal contribution selection in its simplest form. Thegeneti c merit ofth e selected parents weighed by their contributions is: G= Si ci EBVi , where E;denote s summation over all selection candidates, EBVji sth e BLUPbreedin g value estimate; a isth e contribution ofth ei-t h selection candidate (as defined in section 6.2.2.1). Note that Ci iszer o for non-selected candidates.Th eaverag e kinship ofth e selected parentsis : Ka= Z j Zj Ci Cj Ky, which should increaseb yn o moretha n AFpe r generation, where AFi sth e desired rate of inbreeding.Thus ,w erestric t the average kinshipto : Ka= t AF, 101 where t isth e generation number. Meuwissen (1997) described an algorithm that optimised the contribution of each candidate, Cj,(an d thusth enumbe r of offspring that each candidate should get), such that the genetic merit ofth eparents , G, ismaximised , and suchtha t the average kinship doesno t exceed t AF. In asimulatio n study, this selection methodrealise d the desired levels ofinbreedin g and yielded about 30%mor e genetic improvement than selection for BLUPbreedin g value estimates (atth esam erat e ofinbreeding) . If levels of inbreeding arehigh , we should account for thenon-linea r increase ofth e inbreeding andreplac e tAFb y l-(l-AF)', i.e., the desired level ofinbreedin g in generationt (see chapter 3),o r alternatively, replace Kyb y 'AAy ,wher e Ay* isth e augmented relationship coefficient (Grundy et al.,1998) .Optima l contribution selection hasbee n extended tobreedin g schemes with overlapping generations by Meuwissen and Sonesson (1998)an d Grundy etal . (1998). Although it ismor e difficult to implement, optimal contribution selection is definitely favoured over selection for BLUPbreedin g value estimates. This isbecaus e optimal contribution selection actively controls therat e ofinbreeding ,wherea s BLUP selection can result inrate s ofinbreedin g that aremuc h higher than expected based on thenumbe r of selected sires anddams . 6.2.3 Mating structures Given the selected sires and dams,whic h sire should be mated towhic h dam? 6.3.2.1 General Mating structures mainly affect the level ofinbreedin g of theoffspring , not therat e atwhic h the level of inbreeding increases over the generations. The latter ismainl y determined byth e selection ofth e animals andth epopulatio n size(sectio n 6.2.2). The inbreeding level ismainl y important to avoid inbreeding depression. 102 Box 6.3 Random mating with exclusion ofsi bmating s Suppose the selection process of section 6.2.2 resulted in: Optimal no of offspring from sire i= mi Optimal no of offspring from damj = fj whereth e sum of them ;(a swel l as is f), N= th e total number of offspring. And a(natural ) mating between asir e and ada m yieldsn offspring. Then thenumbe r of matings needed with sire ii s M; =mj/n , andwit h damj is Fj= fj/n, where somerounding 1 of these figures will berequire d toge t the desired total number of offspring (N). The following steps maytha n beuse d to assign thematings : Step 1: Conside r every sirei n turn, denote the current sireb y sirei . Step 2: Sirei need s Mimatings :sampl e atrando m M;dam s for sirei . If asample d damj isa full orhal f sibo f sirei , another dam is sampled instead of dam j, andthi sproces s is continued until none ofth e sampled dams are aful l orhal f sibo f sirei . Step 3:Decreas e thenumbe r ofmating sneede d for the selected damsj with 1,i.e. , Fji s decreased with 1.I f Fjbecome s zero for some dams, this dam is excluded from the seto f dams from which the mates ofth e sires are selected in Step2 . Step4 : Continue with thenex t sire ii n Step2 unti l all sireshav ebee n considered. Sometimes, only full andhal f sibs ofth e sires will belef t as dams eligible for sampling in Step2 .I n this casew eshoul d re-start the entire sampling process. If after several attempts,w e couldno tfind a vali dmatin g scheme,i t seems that thenumbe r of sires and damsi sto o small, andw eshoul d allow half sibmating s in Step2 . 1 For example ifm/ N =4.459 ,w enee d toroun d this figure toM j= 4 or M; = 5.Th e usual truncation point forroundin g up ordow n is 0.5. Butthi s truncation point canresul t in asu m ofal l Mjtha t isno tequa l toth etota l number ofmating stha tw edesire ,i.e .no t equal toN/n . However, by trial anderro r we can find adifferen t truncation point for rounding that does result in asu m ofth e Mitha t equals N/n.E.g. , ifth e truncation point for rounding is0.4 ,th e abovefigure 4.45 9 isrounde d toMi=5 .Not e thatth e truncation point is always between 0an d 1,an da lowe r truncation point yields alarge r total number ofmating s and viceversa. The samehold s for theroundin g ofth e Fj. 103 6.2.3.2 Non-sib matings Themos t straightforward method tomat e the individuals is assigning themating s atrandom , e.g., when asir e should get 10offsprin g from 10dams ,th edam s aresample d atrando m toth e sire.Th eeffectiv e population sizes will be asdescribe d in section 6.2.2. However, someo f themating s will bebetwee n close relatives, i.e., full-sib andhalf-si b matings.Thi s shouldb e avoided since the offspring from thesemating s will behighl y inbred andwil l thus show much inbreeding depression. The latter can result inreduce d fertility of theinbre d offspring, which is undesirable because itreduce s the scope for further selections. Box 6.3 shows agenera l sampling strategy for the matings,wher e sibmating s are avoided. 6.2.3.3 Minimum inbreeding mating Especially when population sizei s small andinbreedin g levels arehigh , suchtha tth e depression duet oinbreedin g ishigh , itma yb eusefu l tominimis e the average inbreeding level ofth e offspring. Notetha t minimum inbreeding matingspe r se,ca nresul t in large full sib families, because asir ereache s only with oneda m the minimum degree ofkinship ,an d thusth e least inbred offspring. Minimum inbreeding matings should therefore be devised such that alsoth enumbe r of full sibs per family is assmal l aspossible . Integer programming algorithms are useful to obtain theminimu m inbreeding mating structure (Fernandez and Toro, 1998). 6.3 Cryo-conservation schemes Users of cryo-conserved genetic stocks should replenish the genetic material as far as possible.T owha t extent geneticmateria l can bereplenishe d will depend on thekin d of useo f thegeneti c material: • Embryos used for re-establishing thebree d canb ereplenishe d by storing embryosfrom there-establishe d breed intoth e genomebank . Special care hast ob etake n withrespec t to the maintenance ofgeneti cvariation : minimum kinship orwithi n family selection should beuse d toge tth epopulatio n thatresult sfrom th e thawed embryos out ofth ebottl e neck, andth e same selection shouldb e used to select the embryos thatreplenis h the cryo-bank. • Semen used tore-establis h the breed should alsob ereplenishe d byth e re-established breed. Again the maintenance of genetic variation isimportant . Aproble m is heretha t the stocks used for replenishing areno t 100%pur ebred , even after repeated back crossing 104 with the conserved breed. However, the genes of thereplenishe d semen should come for more than 90%from th e conserved breed. Thiswoul db e obtained by4 generations of repeated back crossing. • Agenom e bank of somatic cells can easily bereplenished , since theretrieva l requires thawing and further culturing ofth e cell line.Th e cultured cell line can be cryo-conserved again. • Semen used tocreat e a 'synthetic' breed from several founder breeds canno t be replenished by semen from the original breed. • Semen used for genetic linkage analysis studies can alsono t be replenished. • Semen used for introgression of genes from the genomeban k breed into another breedca n not be replenished. Fortunately, thelatte r three uses ofth egenom eban krequir erathe r small amounts of semen, but still theban k hast ob ereplenished . Therefore, these useso f semen should provide funds for aful l replenishment ofth ebree d in the genomebank . Thelatte r involves re-establishing thebree d from embryos (or semen) toreplenis h the bank. Also,th e information that is obtained from genetic studies,crossbreedin g andre-establishin g the breed (and anybree d comparison involved in that) are very valuable and shouldb e entered into the data bank. 6.4 Integrating live and cryo-conservation • General Aspects • Cryo-back-up live conservation • Cryo-aided live conservation 6.4.1 General aspects Integrated live andcryo-conservatio n schemesresembl e verymuc h theliv e schemes of section 6.2 andhenc e the operational issues of section 6.2 also apply here.Ther e aretw o kinds of integrated live and cryo-conservation schemes: • The cryo-back-up live scheme.A liv e scheme where cryo-stored oldgeneti c material is used asa bac k upi n case (genetic)problem s occur. • The cryo-aided live scheme.A liv e schemewit hprolonge d generation intervals which are achieved by cryo-storage. 105 Itseem srisky t oru n aliv e conservation scheme without any back upi n case ofemergencies . Hence,th e cryo-back-up live scheme isrecommende d for anyliv e scheme.Especially , if the effective population size is only 50.Although , an effective size of 50i s considered to be safe, still inbreeding depression can lead topoo r fertility at some point in the future, or genetic defects can become frequent. Also,disease s and other catastrophes can easily wipe out or severely reduce the small population. Continuous cryo-storage of semen and embryos seems therefore aver y useful tool to minimise theserisks . The cryo-aided live scheme is useful when the (financial) resources areno t sufficient to achieve the minimum effective size of 50i n the livepopulation . With the cryo-conserved stocks the generation interval can be increased until the effective sizeo f 50animal s per generation isreached . The increase ofth egeneratio n interval reduces therat e of genetic adaptation (and improvement) ofth ebree d and should therefore beminimised . 6.4.2 Cryo-back-up live conservation schemes Backup in case of physical disaster In case ofa catastroph e (disease,fire, etc.) ,w emigh tnee d tore-establis h (part of) the population. Therisks o fphysica l disasters are substantially reduced bykeepin g the population at several herds (also themales) . If alarg epar t ofth epopulatio n dies,th eremainde r ofth e population will gothroug h ageneti cbottleneck . Minimum kinship selection mayb euse dt o getth e population out ofth ebottlenec k (Section 6.2.2.1). Ifth e useo f sires across the separate breeding herds islimited , the storage of semen of sires from thepreviou s generation can alleviate thebottlenec k further. Somenatura l disasters spread over alarg eregio n (floods, diseases,tornadoes ) andma ykil l the entirepopulation . For these cases wehav et ob eprepare d tore-establis h the breed. Re establishing abree d is easier with stored embryos than with stored semen.Therefor e some cryo-storage of embryos seems tob eth epreferre d method. The following strategy seems sufficient to achieve areasonabl y recent back-up for re-establish thebreed : 1. Atth ebeginnin g of theconservatio n scheme, cryo-conserve embryosfrom th e founder population. Thenumber sneede d areth e same asthos e for apur e cryo-conservation scheme that aims atre-establishin g abree d (chapter 5). 2. Cryo-conserve semenfrom ever y sire thati s used in every generation of scheme.Thi swil l cost little effort in aA Ibase d scheme,bu tmor e innatura l mating schemes.A reductio n in 106 thenumbe r of sires tob e stored canb e achieved by storing only unrelated sires (no full- or half-sib sires). 3. Repeat step 1 every 5-20 generations.Th efigure o f 20generation s seemsreasonabl e for a scheme without any selection, i.e., we onlywan t tocaptur ene w genetic adaptations of thebreed . The figure of 5generation s seemsreasonabl e in aschem ewit h strong selection, where wed ono t want to lose much geneticprogress . In case of anemergency , weimplan t the most recently stored embryos intorecipient s and mate the offspring with themos trecen t semen stored in step 2.Hence ,i f ithelp sreducin g the cost,w eca n store only female embryos.Th ere-establishe d population will show ageneti c lag toth e deceased population of atth emos t 3(=!^(5+l) )o r 10.5generations ,i fw estor e embryos every 5o r2 0generations ,respectively . On average thela g will be 1.75o r 5.5 generations, respectively. In ordert o avoidproblem s duet onatura l disasters,th e cryoban k shouldb ekep t ata different place than the live animals or,better , attw o different places. Backup in case of genetic problems Despite an effective sizeo f 50, adeleteriou s mutation can drift tohig h frequency inth e population. In the case of arecessiv e genetic defect, the frequency ofth e mutation israthe r highbefor e the defect is discovered inth ehomozygot e animalstha t show the disease. This is because aslon g asth e defect is atlo w frequency itwil l bemainl ypresen t in heterozygote form in thepopulatio n andth e defect will not show.However , when we discover ageneti c defect, wewil l notkno w itsmod e of inheritance (single gene orsevera l genes;recessiv e or dominant). It seemsmos trobus t to select for BLUPbreedin g value estimates toreduc e the prevalence ofth egeneti c defect (possible in combination with optimal contribution selection asdescribe d in section 6.2.2.2). This isbecaus e BLUPbreedin g values estimates are reasonably good estimates ofth etru e geneticvalu e underman y distributions ofth etru e genetic values (Henderson, 1984).Th e useo fBLU Pbreedin g values will decrease the effective population size substantially andthi s canb e aproble mi n small populations.Th e back upstorag eo fseme n andembryo s asdescribe d inth epreviou s section mayb euse dt o increase the effective size ofth epopulation .Not e alsotha t the older animals will have the highestbreedin g value estimates sinceth epopulatio n was deteriorating overtime .Ho wmuc h cryo-storage isneede d toreduc eth e genetic defects is difficult topi npoint ,bu t the storage strategytha twa sdescribe d inth epreviou s section seemst o suffice. 107 Inth epreviou sparagrap h wediscusse d selection against ageneti c defect. The same method can however be applied toremed y genetic problems that aredu et oman y genes.Fo r example, poorreproductiv e performance of the animals can beremed y by selection for reproductive performance. Section 6.2.2.2describe s howt o selectfo r anytrait . Ifth epoo r reproductive performance isconsidere d tob e due toinbreedin g depression, the useo f old cryo-stored genetic stocks can be useful toreduc eth e levels ofinbreedin g inth epopulation . Section 6.2.2.1describe sho wt ominimis eth e kinshipo fth e animals andthu s thelevel so f inbreeding.Agai n the storage strategy asdescribe d inth e previous section seemst oproduc e sufficient amounts of cryo-stored stocks.Fo rth epurpos e ofreducin g thekinshi p ofth e population, it ishoweve r important toretai n oldcryo-conserve d material becauseth e olderth e material the lower the kinship coefficients. 6.4.3 Cryo-aided liveconservatio n schemes Storage ofembryos In ordert o demonstrate theprinciples , wewil lfirst conside r acryo-aide d live scheme that has ageneratio n interval of25. 5years .Th etim efrom birt h toth eproductio n ofth e embryos is1 and2 years , for sires and dams,respectively , the embryos arefroze n for 23years , andth e embryos take 1 yeart o develop into anew-bor n offspring (atota l 25.5year s on average).Thi s schemeinvolve si n yeart : 1. Thaw the embryos that werefrozen 2 3 years ago andimplan t them into arecipien t female. 2. Get embryosb y mating the 1-year-oldsire s and2-year-ol d dams andfreeze thes e embryos. Iti s important that the sires and damsuse d in step 2ar efrom differen t ages such that the generations overlap. Overlapping generations can alsob e obtained by using for 50%o fth e embryos 1-year-oldsire s and for 50%2-year-ol d sires,an d similarly for dams: 50%1-year - olddam s and 50%2-year-old-dams .I npractice ,w e should chooseth emos t convenient way toachiev eth e overlap between thegenerations . Itwil l take some time to set up acryo-aide d live scheme,becaus e initially there will notb e 23-year-old embryos available.Th e scheme canb e set upb yfreezing man y embryosfrom th e founder population, suchtha t these embryos canb euse d in step 1 until theyar e actually23 - year-old. 108 If step2 involve s onemal e andon e female, i.e., every yearon emal e and onefemal e israised , theschem e involves 25male s and2 6 females per generation, since themal e and female generation interval is 25 and2 6years ,respectively . Theeffectiv e sizei s thus approximately 51animal s per generation. Hence,i n this cryo-aided conservation scheme azoo-size d population reaches an effective size of 50. Storage ofSemen The cryo-aided live schemewit h semen storageresemble s that with embryo storage.Fo r example in the following scheme, 1 and 2-year-old females areinseminate d with 23-year-old semen which wasproduce d by 1-year-oldmales ,t o obtain offspring when 50%o fth e dams are2 an d 50%ar e 3-year-old. The average generation interval is 13.25 years (=1/2(23+l) + 1/2('/2*2+'/2*3)). This schemeinvolve s in year t: 1. Inseminate the 1-year-ol d (50%) and 2-year-old (50%)female s with the 23year-old - semen. 2. Obtain semen from 1-year-oldmale s and cryo-conserve it. Theus e of females from different ages is againt o ensure that thegeneration s overlap. Ifw erais e 6male s and 6female s per year in this scheme, andals o usethe m in step 2,th e number ofmale s and females pergeneratio n is24*6=14 4 and2.5*6=15 ,respectively . Using Equation [6.1]thi syield s an effective size of 54. It shouldb enote dtha t the extension of the male generation interval alone isfa r less effective in increasing effective sizetha n extending both generation intervals (see embryo storage section). After somenumbe r of years of extending the male generation interval, ithardl y helps to extend it anyfurther . Plotting thenumbe r ofyear s of storage ofth e semen in agrap h against the effective size,wil l show where the effect ofincreasin g themal e generation interval starts to level off. Iti s deleterious to the conservation schemet o extentth emal e generation interval beyond thisnumbe r ofyears ,becaus e every extension ofth emal e generation interval slows therat e ofgeneti cadaptatio n ofth epopulatio n down. Iti sver y important to take great carewhe n setting up aseme n based cryo-aided conservation scheme. Ifw ewoul d simply store semenfrom th e founder males and usetha t for thefirs t 23year s (analogous toth e embryo storage case),w ewoul d greatly increaseth e 109 genetic contribution of the founder males over that ofth e founder females. This could halve the size ofth e founder population. There are three methods toremed y this problem: 1. Make suretha tth e size ofth emal e founder population istwic e aslarg e as initially intended. 2. Set up the semen cryo-aided schemewit h embryos, asdescribe d in the embryo section, and start toru n the semen aided scheme when the founder population is 23 years oldi n thepresente d example. Inpractic e thisnumbe r of yearsma yb emuc h smaller. 3. Startbreedin gfrom th e founder population usingminimu m kinship selection (section 6.2.2.1)an d store semenfrom th e sires.Not e that within theminimu m kinship selection procedure also the 'stored' males are selection candidates, i.e., even deadmale s canb e selected because their semen is stored. Again, as soon asth epopulatio n is '23 years' old the original semen cryo-aided scheme canb erun ,wher e '23 years' will bemuc h shorter in mostpractica l situations. Iti sno t useful tokee p onrunnin g theminimu m kinship selection scheme,becaus e itwil l tryt opreven t all genetic drift andthu s evolution when the frozen ancestors become more andmor e old. Because ofth ehig h tech selection involved in option 3,th e options 1 or2 ma yb emor e practical. However, options 1 and 2requir e moreresource s interm s of embryos or founder animals,whic h canb emor e costly than hiring ageneticis t to apply ahig h tech selection method. Asmentione d before, cryo-aided schemes can bever y useful toincreas e the effective sizeo f small populations, but care should betake n tokee p onturnin g overth e generations such that thepopulatio n can evolve.Th e actual sizeo fth epopulatio n will often be determined byth e available (financial) resources, andth e generation interval follows from the actual size andth e effective sizetha tneed s tob e achieved. The cryo-storage involved in the cryo-aided schemes serves automatically asa geneti cbac k uptha t isneede d asdescribe d in section 6.4.2. 110 References Cameron,N.D. , 1997.Selectio n indices andpredictio n ofgeneti c merit in animal breeding. CAB International, Oxon, UK,203p . Falconer, D.S.,1989 . Introduction to quantitative genetics.3r d edition, Longman, Harlow, essex, UK. FAO, 1998 Secondary Guidelines for Development ofNationa l Farm Animal Genetic Resources Management Plans -Managemen t ofSmal l Populations atRisk . FAO,Rome ,Italy . 215p. Fernandez, J., and M.A. Toro, 1998.Th eus eo f mathematical programming to control inbreeding in selection schemes.Journa l of Animal Breeding and Genetics (Submitted). Garcia-Dorado, A.,J.L .Monedero ,C . Lopez-Fanjul, 1998.Th emutatio n rate andth e distribution ofmutationa l effects ofviabilit y and fitness in Drosophila Melanogaster. Genetica 103:255-265. Grundy, B., B.Villanueva , andJ.A . Woolliams, 1998.Dynami c selection procedures for constrained inbreeding andthei r consequences for pedigree development. Proceedings ofth e 6th World Congress on Genetics Applied to Livestock Production 25:355-358 . Henderson, C.R., 1984.Application s of linear models in animal breeding. University of Guelph, Canada. Lynch, M.,J . Conery, and R. Burger, 1995.Mutatio n accumulation and the extinction of small populations.America n Naturalist 146: 489-518. Meuwissen, T.H.E. and J.A. Woolliams, 1994.Effectiv e sizes of livestock populations to prevent adeclin e in fitness. Theoretical and Applied Genetics 89:1019-1026. Meuwissen, T.H.E., 1997.Maximizin g therespons e of selection with apre-define d rateo f inbreeding. Journal of Animal Science 75:934-940 . Ill Meuwissen,T.H.E. , and A.K. Sonesson, 1998.Maximizin g therespons e of selection witha pre-defined rate ofinbreedin g II Overlapping generations.Journa l of Animal Science76 : 2575-2583. Toro,M.A. , J. Fernandez,J . Rodriganez, L. Silio, M.Carrmen-Rodriguez , 1998.Optima l useo fmarker s in conservation programmes of captivepopulations . Génétique Selection Evolution (inpress) . Wang,J. , 1997.Mor e efficient breeding systems for controlling inbreeding and effective size in animal populations. Heredity 79:591-599 . Wright, S., 1931.Evolutio n in Mendelian populations. Genetics 16:97-159 . 112 Chapter 7.Developmen t of an expert system for conservation J.A.Woolliams 1' andT.H.E . Meuwissen2) 1) Division ofGenetic s andBiometry , Roslin Institute (Edinburgh), Roslin, Midlothian, EH25 9PS, U.K. 2) Department ofAnima l Breeding andGenetics ,DLO-Institut efo r Animal Science andHealth , P.O.Box 65,820 0 Lelystad, TheNetherlands . • The need • Thecomponents of the expertsystem • Conclusions 7.1 Thenee d There isn origh twa yt o conduct aconservatio n scheme. Therefore there aren oprescription s for a successful conservation scheme that canb ewritte n down like arecipe ,wit h each step automatically following on from thepreviou s step,wit h clear objectives that areunambiguousl y achieved. Nevertheless successful conservation will not happen without (i)sensibl e decisions being taken on alarg enumbe r of critical points,an d (ii)knowin g howt o implement these decisions effectively, and(iii ) experience inpredictin g the outcome offinely balance d decisions. Despite the lack of arecip e for aconservatio n scheme there is still aproces s that has tob emanage d with abeginning , andwit h anultimat e objective of achieving asustainabl e conservation scheme for breeds identified asbein g ofpotentia l benefit tomankind . Therefore we still need tokno w where thebeginnin g ofthi s process is and at eachpoin t inth eproces s wenee d tokno w in which direction tomove . Thisrequire s knowledge acquired from awid e variety ofdisciplines ,rangin g from genetics through agronomy to applied animal husbandry, and at anypoin t this expertise mayno t be onhan d to guide theplannin g andth e decision making process. Therei sthe n arequiremen t for expertise tob e shared andmad e available tothos e inneed . For the expertise tob eusefu l it mustb e in afor m that canb e assimilated and understood. 113 Therecognitio n ofthi s has led to one ofth e objectives of the FAO'sprogramm e for the Global Management ofFar m Animal Genetic Resources being the development of guidelines for useb y countries. ThePrimar y Guideline Document (FAO, 1998a)i smainl y targeted towards policy makers,an di s designed tohel p countries get started by identifying the main elements and objectives of an animal geneticresource s management plan, and outlining the strategic policy directionsrequire d to fulfil these objectives. The Primary Guideline Document is complemented and supportedb y secondary documents targeted mainly atthos etha t implement policy, administratively andtechnically , covering arang e of issues. One ofth e secondary documents isth e FAO Guidelines for the Management of Small Populations atRis k (FAO, 1998b),whic h covers the topic of cryoconservation. Together, these guidelines represent an advancei n themanagemen t of animal geneticresource s and iti srecognise d that such guidelines needt ob eregularl y reviewed (asi spartl y done in thepreviou s chapters ofthi sbook ) to ensure that: (i)knowledg e isupdated , (ii)th e best tools arereferenced , and (iii)practica l experience gained can be fed intoth e decision process. Nevertheless there are arguments that such guidelines need tob edevelope d into an expert system that isbase d upon aPC . 7.1.1 Keeping ontrac k Thedecisio n process for choosing among conservation strategies has multiplepath s with many branching points,wit h previously distinct paths converging andjoinin g together, perhaps only temporarily. It wouldb e desirable tomak e therequire d path aslinea r aspossible ,wit h each step following onnaturall yfrom th e last one. Iti s difficult topresen t suchmultipl e paths cohesively in abook . It can be achieved using acomputerise d system. 7.1.2 Assimilation Even though aboo k may contain allth enecessar y information, iti s daunting for non-specialists to assimilate all the information. Not all parts of theboo k mayb erelevan t toth e application being considered. Therei s adange r that adelug e oftechnica l terms (even though defined inth ebook) ,o r continual cross-referencing, hampers progress. Acomputerise d expert system mayb e designed to allow definitions tob e read, ifdesired ,whe n andwher e they areencountere d simplyb y clicking on the text, with an automaticretur n toth epoin t where the definition wasrequested . The 114 computerised decision pathway can avoid techniques anddefinition s notrelevan t toth e application being considered. 7.1.3 Information atth e point of conservation Whilst themajo r planning ofa conservatio n programme mayb e done in an office, many decisions can onlyb emad e on farms ori n temporary facilities. Acomputerise d PCwit h the reference information stored in an easily retrievable form has some advantages over carrying the actual reference books,althoug h the disadvantage is thenee d topowe rth e PCi n someway . 7.1.4 Recording and data storage During the collection of samples therewil l be anee d torecor d and store information on donors and samples. An expert system couldpromp t for thenecessar y information, and storei t electronically. Thiswoul d facilitate thetransfe r of accurate andcomplet e information to larger databases atsom e point inth e future. 7.1.5 Sampling and mating protocols There mayb e anee d tochoos e animals for sampling based upon pedigrees, orfragment s of pedigrees (see FAO (1998b) Section 5.3 and chapter 5o fthi sbook) , ort o decide upon thematin g design for an embryorecover y based upon the success ofpreviou srecoverie s (see FAO (1998b) Section 5.4.4). Whilstrelativel y simple-to-use algorithms aregive n for these procedures, an expert system could compute these algorithms. In live-animal conservation schemes the expert system may include selection andmatin g tools to helpmee t target rates of inbreeding based upon available pedigrees and genetic evaluations (see chapter 6). 7.1.6 Customising Guidelines need toprovid e some insight intonumber s of samples,number s ofparent s etc. Thisha s been achieved inth e FAO (1998b)guideline s byconsiderin g a set ofminimu m requirements for effective conservation, determined by defining objectives (chapter 6). However whilst this provides agoo d starting framework, onman y occasions thesema yprov e insufficient. • In some casesbreeder s organisations maywis h tog obeyon d these minimum requirements. • In some circumstances the funding available and/or the numbers ofth e endangered breeds availablefrom whic h to collect samples,ma ymak e itimpossibl e to collect of theminimu m number ofsample s envisaged by the FAO(1998b) . 115 Inbot h cases there will be anee d toreconside r the objectives andre-calculat e thenumber s required. Whilst the principles behind the FAO (1998b)guideline s mayb eapplie d with any number ofparent s from the endangered breed, thepresentatio n ofth erequirement s for semen and embryos in Tables 5.3 and 5.5 in FAO(1998b )make s some assumptions upon thenumber s of parents. For the collection of embryos inparticula r iti sno t easy toappl y the guidelines for different numbers of parents without the aid of acompute r (Meuwissen, 1997, see also chapter 6). Nevertheless changing thenumbe r ofparent s could easily be achieved with the expert system. 7.1.7 Benefiting from experience Theexperienc e gainedwithi n aconservatio n scheme canb e collected into adatabas e classified by keywords identifying the decision pathway e.g. outlined in chapter 2 (i.e.wha twa s the species? waslive-anima l conservation chosen, orcryoconservation ? were embryos collected aswel l as semen?).Whe nth e decision process isbein g considered these examples can betriggere d toprovid e information upon outcomes andpeopl e to contact for further information. 7.2 Thecomponent s ofth eexper t system Theconsideration s aboveidentif y several components for the expert system: (i)t oprovid ea knowledge-based decision support system for the entireprocess ; (ii) adatabas e of conservation experience classified according toth e decision framework; (iii) toprovid e tools for the active conservation process (i.e.computerize d record sheets for sample collection, tools for pedigree recording, evaluation and selection tools).Thes e components mayb edevelope d separately (the software 'engines'fo r some ofthes etask s may alreadyhav e been developed) providing the whole system andth enee d for integrating the components is recognised. It isnecessar y toprioritis e these components andi ti sth efirst o fthes etha t appears most inneed , to help guide thepolic y anddecision-maker s through along-ter m and complexproces s in acohesiv e way. Without thebasi c guidance thenee d for the other tools willno t berecognised . 7.2.1 Suggested requirements for abasi c decision support system Oneo fth einitia l questions iswha t kind of system shouldb e designed. Sinceth einitia l FAO (1998a andb )guideline s are accessible onth e Internet and on CD-ROM itwoul d seem asensibl e firstste pt obuil d asyste m that operates through these media. The decision onwhethe r orno t the 116 tool shouldb e intelligent is critical since this will affect the design ofth e tool. However asimpl e perspective onthi s question istha t the development time andtestin g of anintelligen t system may prove lengthy, whereas amor ebasi c system would be availablemor e quickly andma y prove almost as effective. Theinterfac e with the user shouldb e graphical at all timest o helpth e user, withpop-u pmenus . An initial stepwoul d bet o develop the FAO guidelinesb ymappin g out some ofth eke y stepsi n the FAO(1998b ) Figures 1.1,2.1,3.1,4.1 and 5.1, andthos e described in chapter 2an d Figure 1 of thisbook . However these sketches ofth e decision-making process will need tob erefine d and developed. Theinformatio n available from the system shouldinclude : explanations anddefinitions ; what ifs for each decision option; expected outcome(s) from executing theparticula r decision option chosen;recommende d partiesresponsibl e for implementing any action emanating from the decision; andth e next decision point(s) in theprocess . Decision points alsonee d to link torelevan t technical andoperationa l protocols (e.g.recommende d protocol for freezing bull semen). 7.2.2 Database of conservation experience Thebasi c technical specification ofth e database istha t it shouldb erelational , with user-friendly dataretrieval . Itma yb epossibl e to develop therequirement s for classifying conservation schemes from therevise d DAD-IS database. However therewoul db e anee d tolin k the classification into the decision-support system. 7.2.3 Algorithms for managing genetic resources Somebasi c algorithms already exist. For example,th e selection tools of Meuwissen (1997), Grundy etal. (1997a and 1997b)whic h maximise progress whilst maintaining aconstan t effective population size (these algorithms would include BLUP evaluation asa component ; the algorithms from the different authors arever y similar) are available. Anumbe r ofothe rtool s mayb e included: simplegeneratio n oftimetable s (e.g.i n superovulation and embryorecovery) ; simple generation of checklists. More complex tools mayals ob e developed: aids for minimising kinship selection when only alimite d number ofanimal sma yb e used for cryoconservation ofgametes ; determining optimum mating when collecting embryos for cryoconservation in ordert ominimis e the variance of contributionsfrom donors . Others could bedevelope d according toneed . 117 7.3 Conclusions A clear case for an expert system can bemade .Th emos t pressing needi s for a decision-support system, and aconservatio n database. Whilst along-ter m perspective on such asyste m might include acollectio n oftool s for genetic management. Given the expertise onth emanagemen t of geneticresource s that is available within theEU , ranging from conservation practice, through technical protocols toth e development of software tools toai d in theirmanagement , the EUi swel l placed totak e the lead inth e development ofa flexible expert system. Theprovisio n of such asystem , compatible with FAOobjective s on domestic animal diversity,woul d make asignifican t contribution togloba l conservation andth e Convention on Biological Diversity. 118 References FAO, 1998a. Primary Guidelines for Development ofNationa l Farm Animal Genetic Resources Management Plans.FAO , Rome, Italy.215p . FAO, 1998b. Secondary Guidelines for Development ofNationa l Farm Animal Genetic Resources Management Plans:Managemen t of Small Populations atRisk . FAO,Rome , Italy.215 p Grundy, B.,B .Kinghorn , B.Villanuev a andJ.A.Woolliams , 1997a. Abreedin g programme for in situgeneti c conservation of livestock. In:Th ePotentia l Role ofRar eLivestoc k Breeds inU K Farming Systems. British Society ofAnima l Science Meeting andWorksho p Publication. Grundy, B., B.Villanuev a andJ.A . Woolliams, 1997b.Maximisin g response with a predefined rateo finbreedin g for overlapping generation structure. Proceedings ofBritis h Society ofAnima l Science. Scarborough, 27p. Meuwissen,T.H.E. , 1997.Maximisin g therespons e of selection with apredefine d rate of inbreeding. Journal ofAnima l Science 75:934-940 .